diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..9e3fa922 --- /dev/null +++ b/.gitignore @@ -0,0 +1,29 @@ +################################################################################ +# 此 .gitignore 文件已由 Microsoft(R) Visual Studio 自动创建。 +################################################################################ + +/huagao/.vs/huagaotwds/v15 +/3rdparty/nick +/huagao/debug/qmake +/huagao/debug +/huagao/Win32/Debug +/huagao/release/qmake +/huagao/Makefile.Release +/huagao/Makefile.Debug +/huagao/Makefile +/huagao/huagaotwds.vcxproj.user +/huagao/huagaotwds.vcxproj.filters +/huagao/huagaotwds.vcxproj +/huagao/huagaotwds.pro.user.4e95af7 +/huagao/huagaotwds.pro.user +/huagao/huagaotwds.aps +/huagao/.qmake.stash +/huagao/huagaotwds.sln +/huagao/.vs/huagaotwds/v16 +/huagao/Win32/Release +/3rdparty/hgOCR/tessdata/chi_sim.traineddata +/huagao/ClassDiagram.cd +/huagao/ClassDiagram3.cd +/huagao/ClassDiagram2.cd +/huagao/ClassDiagram1.cd +/huagao/release diff --git a/3rdparty/hgOCR/include/hg_ocr4.h b/3rdparty/hgOCR/include/hg_ocr4.h new file mode 100644 index 00000000..e979f336 --- /dev/null +++ b/3rdparty/hgOCR/include/hg_ocr4.h @@ -0,0 +1,43 @@ +#ifndef HG_OCR4_H +#define HG_OCR4_H + +#if defined (_WIN32) + #if !defined (HG_OCR4_BUILD) + #define HG_OCR4_API __declspec(dllexport) + #else + #define HG_OCR4_API __declspec(dllimport) + #endif +#else + #define HG_OCR4_API +#endif + +class HG_OCR4_API HG_OCR4 +{ +public: + + enum PSM_TYPE + { + Orientation, + OCR + }; + +public: + HG_OCR4(); + + ~HG_OCR4(); + + int init (const char* filename, PSM_TYPE type); + + int getOrientation(unsigned char* imgData, int width, int height, int channels, int step); + + int getOCR(unsigned char* imageData, int width, int height, int channels, int dpi); + +private: + void init_orientation(const char *filename); + + void init_ocr(const char* filename); +private: + void* api; +}; + +#endif // HG_OCR4_H diff --git a/3rdparty/hgOCR/tessdata/osd.traineddata b/3rdparty/hgOCR/tessdata/osd.traineddata new file mode 100644 index 00000000..183644aa Binary files /dev/null and b/3rdparty/hgOCR/tessdata/osd.traineddata differ diff --git a/3rdparty/hgOCR/x86/bin/HG_OCR4.dll b/3rdparty/hgOCR/x86/bin/HG_OCR4.dll new file mode 100644 index 00000000..4ce44867 Binary files /dev/null and b/3rdparty/hgOCR/x86/bin/HG_OCR4.dll differ diff --git a/3rdparty/hgOCR/x86/lib/HG_OCR4.lib b/3rdparty/hgOCR/x86/lib/HG_OCR4.lib new file mode 100644 index 00000000..4899a91f Binary files /dev/null and b/3rdparty/hgOCR/x86/lib/HG_OCR4.lib differ diff --git a/3rdparty/opencv/include/opencv/cv.h b/3rdparty/opencv/include/opencv/cv.h new file mode 100644 index 00000000..19a74e29 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cv.h @@ -0,0 +1,73 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_CV_H +#define OPENCV_OLD_CV_H + +#if defined(_MSC_VER) + #define CV_DO_PRAGMA(x) __pragma(x) + #define __CVSTR2__(x) #x + #define __CVSTR1__(x) __CVSTR2__(x) + #define __CVMSVCLOC__ __FILE__ "("__CVSTR1__(__LINE__)") : " + #define CV_MSG_PRAGMA(_msg) CV_DO_PRAGMA(message (__CVMSVCLOC__ _msg)) +#elif defined(__GNUC__) + #define CV_DO_PRAGMA(x) _Pragma (#x) + #define CV_MSG_PRAGMA(_msg) CV_DO_PRAGMA(message (_msg)) +#else + #define CV_DO_PRAGMA(x) + #define CV_MSG_PRAGMA(_msg) +#endif +#define CV_WARNING(x) CV_MSG_PRAGMA("Warning: " #x) + +//CV_WARNING("This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module") + +#include "opencv2/core/core_c.h" +#include "opencv2/imgproc/imgproc_c.h" +#include "opencv2/photo/photo_c.h" +#include "opencv2/video/tracking_c.h" +#include "opencv2/objdetect/objdetect_c.h" + +#if !defined(CV_IMPL) +#define CV_IMPL extern "C" +#endif //CV_IMPL + +#endif // __OPENCV_OLD_CV_H_ diff --git a/3rdparty/opencv/include/opencv/cv.hpp b/3rdparty/opencv/include/opencv/cv.hpp new file mode 100644 index 00000000..86739564 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cv.hpp @@ -0,0 +1,60 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_CV_HPP +#define OPENCV_OLD_CV_HPP + +//#if defined(__GNUC__) +//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module" +//#endif + +#include "cv.h" +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" +#include "opencv2/photo.hpp" +#include "opencv2/video.hpp" +#include "opencv2/highgui.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/calib3d.hpp" +#include "opencv2/objdetect.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv/cvaux.h b/3rdparty/opencv/include/opencv/cvaux.h new file mode 100644 index 00000000..c0367cc2 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cvaux.h @@ -0,0 +1,57 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_AUX_H +#define OPENCV_OLD_AUX_H + +//#if defined(__GNUC__) +//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module" +//#endif + +#include "opencv2/core/core_c.h" +#include "opencv2/imgproc/imgproc_c.h" +#include "opencv2/photo/photo_c.h" +#include "opencv2/video/tracking_c.h" +#include "opencv2/objdetect/objdetect_c.h" + +#endif + +/* End of file. */ diff --git a/3rdparty/opencv/include/opencv/cvaux.hpp b/3rdparty/opencv/include/opencv/cvaux.hpp new file mode 100644 index 00000000..4888eef2 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cvaux.hpp @@ -0,0 +1,52 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_AUX_HPP +#define OPENCV_OLD_AUX_HPP + +//#if defined(__GNUC__) +//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module" +//#endif + +#include "cvaux.h" +#include "opencv2/core/utility.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv/cvwimage.h b/3rdparty/opencv/include/opencv/cvwimage.h new file mode 100644 index 00000000..ec0ab141 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cvwimage.h @@ -0,0 +1,46 @@ +/////////////////////////////////////////////////////////////////////////////// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to +// this license. If you do not agree to this license, do not download, +// install, copy or use the software. +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2008, Google, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without +// modification, are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation or contributors may not be used to endorse +// or promote products derived from this software without specific +// prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" +// and any express or implied warranties, including, but not limited to, the +// implied warranties of merchantability and fitness for a particular purpose +// are disclaimed. In no event shall the Intel Corporation or contributors be +// liable for any direct, indirect, incidental, special, exemplary, or +// consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. + + +#ifndef OPENCV_OLD_WIMAGE_HPP +#define OPENCV_OLD_WIMAGE_HPP + +#include "opencv2/core/wimage.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv/cxcore.h b/3rdparty/opencv/include/opencv/cxcore.h new file mode 100644 index 00000000..dc070c77 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cxcore.h @@ -0,0 +1,52 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_CXCORE_H +#define OPENCV_OLD_CXCORE_H + +//#if defined(__GNUC__) +//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module" +//#endif + +#include "opencv2/core/core_c.h" + +#endif diff --git a/3rdparty/opencv/include/opencv/cxcore.hpp b/3rdparty/opencv/include/opencv/cxcore.hpp new file mode 100644 index 00000000..c371677c --- /dev/null +++ b/3rdparty/opencv/include/opencv/cxcore.hpp @@ -0,0 +1,53 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_CXCORE_HPP +#define OPENCV_OLD_CXCORE_HPP + +//#if defined(__GNUC__) +//#warning "This is a deprecated opencv header provided for compatibility. Please include a header from a corresponding opencv module" +//#endif + +#include "cxcore.h" +#include "opencv2/core.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv/cxeigen.hpp b/3rdparty/opencv/include/opencv/cxeigen.hpp new file mode 100644 index 00000000..1d3df914 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cxeigen.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_EIGEN_HPP +#define OPENCV_OLD_EIGEN_HPP + +#include "opencv2/core/eigen.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv/cxmisc.h b/3rdparty/opencv/include/opencv/cxmisc.h new file mode 100644 index 00000000..9b9bc820 --- /dev/null +++ b/3rdparty/opencv/include/opencv/cxmisc.h @@ -0,0 +1,8 @@ +#ifndef OPENCV_OLD_CXMISC_H +#define OPENCV_OLD_CXMISC_H + +#ifdef __cplusplus +# include "opencv2/core/utility.hpp" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv/highgui.h b/3rdparty/opencv/include/opencv/highgui.h new file mode 100644 index 00000000..69b394e0 --- /dev/null +++ b/3rdparty/opencv/include/opencv/highgui.h @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_HIGHGUI_H +#define OPENCV_OLD_HIGHGUI_H + +#include "opencv2/core/core_c.h" +#include "opencv2/highgui/highgui_c.h" + +#endif diff --git a/3rdparty/opencv/include/opencv/ml.h b/3rdparty/opencv/include/opencv/ml.h new file mode 100644 index 00000000..0c376bac --- /dev/null +++ b/3rdparty/opencv/include/opencv/ml.h @@ -0,0 +1,47 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OLD_ML_H +#define OPENCV_OLD_ML_H + +#include "opencv2/core/core_c.h" +#include "opencv2/ml.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv2/calib3d.hpp b/3rdparty/opencv/include/opencv2/calib3d.hpp new file mode 100644 index 00000000..38085266 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/calib3d.hpp @@ -0,0 +1,2618 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CALIB3D_HPP +#define OPENCV_CALIB3D_HPP + +#include "opencv2/core.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/core/affine.hpp" + +/** + @defgroup calib3d Camera Calibration and 3D Reconstruction + +The functions in this section use a so-called pinhole camera model. In this model, a scene view is +formed by projecting 3D points into the image plane using a perspective transformation. + +\f[s \; m' = A [R|t] M'\f] + +or + +\f[s \vecthree{u}{v}{1} = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1} +\begin{bmatrix} +r_{11} & r_{12} & r_{13} & t_1 \\ +r_{21} & r_{22} & r_{23} & t_2 \\ +r_{31} & r_{32} & r_{33} & t_3 +\end{bmatrix} +\begin{bmatrix} +X \\ +Y \\ +Z \\ +1 +\end{bmatrix}\f] + +where: + +- \f$(X, Y, Z)\f$ are the coordinates of a 3D point in the world coordinate space +- \f$(u, v)\f$ are the coordinates of the projection point in pixels +- \f$A\f$ is a camera matrix, or a matrix of intrinsic parameters +- \f$(cx, cy)\f$ is a principal point that is usually at the image center +- \f$fx, fy\f$ are the focal lengths expressed in pixel units. + +Thus, if an image from the camera is scaled by a factor, all of these parameters should be scaled +(multiplied/divided, respectively) by the same factor. The matrix of intrinsic parameters does not +depend on the scene viewed. So, once estimated, it can be re-used as long as the focal length is +fixed (in case of zoom lens). The joint rotation-translation matrix \f$[R|t]\f$ is called a matrix of +extrinsic parameters. It is used to describe the camera motion around a static scene, or vice versa, +rigid motion of an object in front of a still camera. That is, \f$[R|t]\f$ translates coordinates of a +point \f$(X, Y, Z)\f$ to a coordinate system, fixed with respect to the camera. The transformation above +is equivalent to the following (when \f$z \ne 0\f$ ): + +\f[\begin{array}{l} +\vecthree{x}{y}{z} = R \vecthree{X}{Y}{Z} + t \\ +x' = x/z \\ +y' = y/z \\ +u = f_x*x' + c_x \\ +v = f_y*y' + c_y +\end{array}\f] + +The following figure illustrates the pinhole camera model. + +![Pinhole camera model](pics/pinhole_camera_model.png) + +Real lenses usually have some distortion, mostly radial distortion and slight tangential distortion. +So, the above model is extended as: + +\f[\begin{array}{l} +\vecthree{x}{y}{z} = R \vecthree{X}{Y}{Z} + t \\ +x' = x/z \\ +y' = y/z \\ +x'' = x' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} + 2 p_1 x' y' + p_2(r^2 + 2 x'^2) + s_1 r^2 + s_2 r^4 \\ +y'' = y' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} + p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' + s_3 r^2 + s_4 r^4 \\ +\text{where} \quad r^2 = x'^2 + y'^2 \\ +u = f_x*x'' + c_x \\ +v = f_y*y'' + c_y +\end{array}\f] + +\f$k_1\f$, \f$k_2\f$, \f$k_3\f$, \f$k_4\f$, \f$k_5\f$, and \f$k_6\f$ are radial distortion coefficients. \f$p_1\f$ and \f$p_2\f$ are +tangential distortion coefficients. \f$s_1\f$, \f$s_2\f$, \f$s_3\f$, and \f$s_4\f$, are the thin prism distortion +coefficients. Higher-order coefficients are not considered in OpenCV. + +The next figures show two common types of radial distortion: barrel distortion (typically \f$ k_1 < 0 \f$) and pincushion distortion (typically \f$ k_1 > 0 \f$). + +![](pics/distortion_examples.png) +![](pics/distortion_examples2.png) + +In some cases the image sensor may be tilted in order to focus an oblique plane in front of the +camera (Scheimpfug condition). This can be useful for particle image velocimetry (PIV) or +triangulation with a laser fan. The tilt causes a perspective distortion of \f$x''\f$ and +\f$y''\f$. This distortion can be modelled in the following way, see e.g. @cite Louhichi07. + +\f[\begin{array}{l} +s\vecthree{x'''}{y'''}{1} = +\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}(\tau_x, \tau_y)} +{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)} +{0}{0}{1} R(\tau_x, \tau_y) \vecthree{x''}{y''}{1}\\ +u = f_x*x''' + c_x \\ +v = f_y*y''' + c_y +\end{array}\f] + +where the matrix \f$R(\tau_x, \tau_y)\f$ is defined by two rotations with angular parameter \f$\tau_x\f$ +and \f$\tau_y\f$, respectively, + +\f[ +R(\tau_x, \tau_y) = +\vecthreethree{\cos(\tau_y)}{0}{-\sin(\tau_y)}{0}{1}{0}{\sin(\tau_y)}{0}{\cos(\tau_y)} +\vecthreethree{1}{0}{0}{0}{\cos(\tau_x)}{\sin(\tau_x)}{0}{-\sin(\tau_x)}{\cos(\tau_x)} = +\vecthreethree{\cos(\tau_y)}{\sin(\tau_y)\sin(\tau_x)}{-\sin(\tau_y)\cos(\tau_x)} +{0}{\cos(\tau_x)}{\sin(\tau_x)} +{\sin(\tau_y)}{-\cos(\tau_y)\sin(\tau_x)}{\cos(\tau_y)\cos(\tau_x)}. +\f] + +In the functions below the coefficients are passed or returned as + +\f[(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f] + +vector. That is, if the vector contains four elements, it means that \f$k_3=0\f$ . The distortion +coefficients do not depend on the scene viewed. Thus, they also belong to the intrinsic camera +parameters. And they remain the same regardless of the captured image resolution. If, for example, a +camera has been calibrated on images of 320 x 240 resolution, absolutely the same distortion +coefficients can be used for 640 x 480 images from the same camera while \f$f_x\f$, \f$f_y\f$, \f$c_x\f$, and +\f$c_y\f$ need to be scaled appropriately. + +The functions below use the above model to do the following: + +- Project 3D points to the image plane given intrinsic and extrinsic parameters. +- Compute extrinsic parameters given intrinsic parameters, a few 3D points, and their +projections. +- Estimate intrinsic and extrinsic camera parameters from several views of a known calibration +pattern (every view is described by several 3D-2D point correspondences). +- Estimate the relative position and orientation of the stereo camera "heads" and compute the +*rectification* transformation that makes the camera optical axes parallel. + +@note + - A calibration sample for 3 cameras in horizontal position can be found at + opencv_source_code/samples/cpp/3calibration.cpp + - A calibration sample based on a sequence of images can be found at + opencv_source_code/samples/cpp/calibration.cpp + - A calibration sample in order to do 3D reconstruction can be found at + opencv_source_code/samples/cpp/build3dmodel.cpp + - A calibration example on stereo calibration can be found at + opencv_source_code/samples/cpp/stereo_calib.cpp + - A calibration example on stereo matching can be found at + opencv_source_code/samples/cpp/stereo_match.cpp + - (Python) A camera calibration sample can be found at + opencv_source_code/samples/python/calibrate.py + + @{ + @defgroup calib3d_fisheye Fisheye camera model + + Definitions: Let P be a point in 3D of coordinates X in the world reference frame (stored in the + matrix X) The coordinate vector of P in the camera reference frame is: + + \f[Xc = R X + T\f] + + where R is the rotation matrix corresponding to the rotation vector om: R = rodrigues(om); call x, y + and z the 3 coordinates of Xc: + + \f[x = Xc_1 \\ y = Xc_2 \\ z = Xc_3\f] + + The pinhole projection coordinates of P is [a; b] where + + \f[a = x / z \ and \ b = y / z \\ r^2 = a^2 + b^2 \\ \theta = atan(r)\f] + + Fisheye distortion: + + \f[\theta_d = \theta (1 + k_1 \theta^2 + k_2 \theta^4 + k_3 \theta^6 + k_4 \theta^8)\f] + + The distorted point coordinates are [x'; y'] where + + \f[x' = (\theta_d / r) a \\ y' = (\theta_d / r) b \f] + + Finally, conversion into pixel coordinates: The final pixel coordinates vector [u; v] where: + + \f[u = f_x (x' + \alpha y') + c_x \\ + v = f_y y' + c_y\f] + + @defgroup calib3d_c C API + + @} + */ + +namespace cv +{ + +//! @addtogroup calib3d +//! @{ + +//! type of the robust estimation algorithm +enum { LMEDS = 4, //!< least-median of squares algorithm + RANSAC = 8, //!< RANSAC algorithm + RHO = 16 //!< RHO algorithm + }; + +enum { SOLVEPNP_ITERATIVE = 0, + SOLVEPNP_EPNP = 1, //!< EPnP: Efficient Perspective-n-Point Camera Pose Estimation @cite lepetit2009epnp + SOLVEPNP_P3P = 2, //!< Complete Solution Classification for the Perspective-Three-Point Problem @cite gao2003complete + SOLVEPNP_DLS = 3, //!< A Direct Least-Squares (DLS) Method for PnP @cite hesch2011direct + SOLVEPNP_UPNP = 4, //!< Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation @cite penate2013exhaustive + SOLVEPNP_AP3P = 5, //!< An Efficient Algebraic Solution to the Perspective-Three-Point Problem @cite Ke17 + SOLVEPNP_MAX_COUNT //!< Used for count +}; + +enum { CALIB_CB_ADAPTIVE_THRESH = 1, + CALIB_CB_NORMALIZE_IMAGE = 2, + CALIB_CB_FILTER_QUADS = 4, + CALIB_CB_FAST_CHECK = 8 + }; + +enum { CALIB_CB_SYMMETRIC_GRID = 1, + CALIB_CB_ASYMMETRIC_GRID = 2, + CALIB_CB_CLUSTERING = 4 + }; + +enum { CALIB_USE_INTRINSIC_GUESS = 0x00001, + CALIB_FIX_ASPECT_RATIO = 0x00002, + CALIB_FIX_PRINCIPAL_POINT = 0x00004, + CALIB_ZERO_TANGENT_DIST = 0x00008, + CALIB_FIX_FOCAL_LENGTH = 0x00010, + CALIB_FIX_K1 = 0x00020, + CALIB_FIX_K2 = 0x00040, + CALIB_FIX_K3 = 0x00080, + CALIB_FIX_K4 = 0x00800, + CALIB_FIX_K5 = 0x01000, + CALIB_FIX_K6 = 0x02000, + CALIB_RATIONAL_MODEL = 0x04000, + CALIB_THIN_PRISM_MODEL = 0x08000, + CALIB_FIX_S1_S2_S3_S4 = 0x10000, + CALIB_TILTED_MODEL = 0x40000, + CALIB_FIX_TAUX_TAUY = 0x80000, + CALIB_USE_QR = 0x100000, //!< use QR instead of SVD decomposition for solving. Faster but potentially less precise + CALIB_FIX_TANGENT_DIST = 0x200000, + // only for stereo + CALIB_FIX_INTRINSIC = 0x00100, + CALIB_SAME_FOCAL_LENGTH = 0x00200, + // for stereo rectification + CALIB_ZERO_DISPARITY = 0x00400, + CALIB_USE_LU = (1 << 17), //!< use LU instead of SVD decomposition for solving. much faster but potentially less precise + CALIB_USE_EXTRINSIC_GUESS = (1 << 22) //!< for stereoCalibrate + }; + +//! the algorithm for finding fundamental matrix +enum { FM_7POINT = 1, //!< 7-point algorithm + FM_8POINT = 2, //!< 8-point algorithm + FM_LMEDS = 4, //!< least-median algorithm. 7-point algorithm is used. + FM_RANSAC = 8 //!< RANSAC algorithm. It needs at least 15 points. 7-point algorithm is used. + }; + +enum HandEyeCalibrationMethod +{ + CALIB_HAND_EYE_TSAI = 0, //!< A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/Eye Calibration @cite Tsai89 + CALIB_HAND_EYE_PARK = 1, //!< Robot Sensor Calibration: Solving AX = XB on the Euclidean Group @cite Park94 + CALIB_HAND_EYE_HORAUD = 2, //!< Hand-eye Calibration @cite Horaud95 + CALIB_HAND_EYE_ANDREFF = 3, //!< On-line Hand-Eye Calibration @cite Andreff99 + CALIB_HAND_EYE_DANIILIDIS = 4 //!< Hand-Eye Calibration Using Dual Quaternions @cite Daniilidis98 +}; + + +/** @brief Converts a rotation matrix to a rotation vector or vice versa. + +@param src Input rotation vector (3x1 or 1x3) or rotation matrix (3x3). +@param dst Output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. +@param jacobian Optional output Jacobian matrix, 3x9 or 9x3, which is a matrix of partial +derivatives of the output array components with respect to the input array components. + +\f[\begin{array}{l} \theta \leftarrow norm(r) \\ r \leftarrow r/ \theta \\ R = \cos{\theta} I + (1- \cos{\theta} ) r r^T + \sin{\theta} \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} \end{array}\f] + +Inverse transformation can be also done easily, since + +\f[\sin ( \theta ) \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} = \frac{R - R^T}{2}\f] + +A rotation vector is a convenient and most compact representation of a rotation matrix (since any +rotation matrix has just 3 degrees of freedom). The representation is used in the global 3D geometry +optimization procedures like calibrateCamera, stereoCalibrate, or solvePnP . + */ +CV_EXPORTS_W void Rodrigues( InputArray src, OutputArray dst, OutputArray jacobian = noArray() ); + +/** @example samples/cpp/tutorial_code/features2D/Homography/pose_from_homography.cpp +An example program about pose estimation from coplanar points + +Check @ref tutorial_homography "the corresponding tutorial" for more details +*/ + +/** @brief Finds a perspective transformation between two planes. + +@param srcPoints Coordinates of the points in the original plane, a matrix of the type CV_32FC2 +or vector\ . +@param dstPoints Coordinates of the points in the target plane, a matrix of the type CV_32FC2 or +a vector\ . +@param method Method used to compute a homography matrix. The following methods are possible: +- **0** - a regular method using all the points, i.e., the least squares method +- **RANSAC** - RANSAC-based robust method +- **LMEDS** - Least-Median robust method +- **RHO** - PROSAC-based robust method +@param ransacReprojThreshold Maximum allowed reprojection error to treat a point pair as an inlier +(used in the RANSAC and RHO methods only). That is, if +\f[\| \texttt{dstPoints} _i - \texttt{convertPointsHomogeneous} ( \texttt{H} * \texttt{srcPoints} _i) \|_2 > \texttt{ransacReprojThreshold}\f] +then the point \f$i\f$ is considered as an outlier. If srcPoints and dstPoints are measured in pixels, +it usually makes sense to set this parameter somewhere in the range of 1 to 10. +@param mask Optional output mask set by a robust method ( RANSAC or LMEDS ). Note that the input +mask values are ignored. +@param maxIters The maximum number of RANSAC iterations. +@param confidence Confidence level, between 0 and 1. + +The function finds and returns the perspective transformation \f$H\f$ between the source and the +destination planes: + +\f[s_i \vecthree{x'_i}{y'_i}{1} \sim H \vecthree{x_i}{y_i}{1}\f] + +so that the back-projection error + +\f[\sum _i \left ( x'_i- \frac{h_{11} x_i + h_{12} y_i + h_{13}}{h_{31} x_i + h_{32} y_i + h_{33}} \right )^2+ \left ( y'_i- \frac{h_{21} x_i + h_{22} y_i + h_{23}}{h_{31} x_i + h_{32} y_i + h_{33}} \right )^2\f] + +is minimized. If the parameter method is set to the default value 0, the function uses all the point +pairs to compute an initial homography estimate with a simple least-squares scheme. + +However, if not all of the point pairs ( \f$srcPoints_i\f$, \f$dstPoints_i\f$ ) fit the rigid perspective +transformation (that is, there are some outliers), this initial estimate will be poor. In this case, +you can use one of the three robust methods. The methods RANSAC, LMeDS and RHO try many different +random subsets of the corresponding point pairs (of four pairs each, collinear pairs are discarded), estimate the homography matrix +using this subset and a simple least-squares algorithm, and then compute the quality/goodness of the +computed homography (which is the number of inliers for RANSAC or the least median re-projection error for +LMeDS). The best subset is then used to produce the initial estimate of the homography matrix and +the mask of inliers/outliers. + +Regardless of the method, robust or not, the computed homography matrix is refined further (using +inliers only in case of a robust method) with the Levenberg-Marquardt method to reduce the +re-projection error even more. + +The methods RANSAC and RHO can handle practically any ratio of outliers but need a threshold to +distinguish inliers from outliers. The method LMeDS does not need any threshold but it works +correctly only when there are more than 50% of inliers. Finally, if there are no outliers and the +noise is rather small, use the default method (method=0). + +The function is used to find initial intrinsic and extrinsic matrices. Homography matrix is +determined up to a scale. Thus, it is normalized so that \f$h_{33}=1\f$. Note that whenever an \f$H\f$ matrix +cannot be estimated, an empty one will be returned. + +@sa +getAffineTransform, estimateAffine2D, estimateAffinePartial2D, getPerspectiveTransform, warpPerspective, +perspectiveTransform + */ +CV_EXPORTS_W Mat findHomography( InputArray srcPoints, InputArray dstPoints, + int method = 0, double ransacReprojThreshold = 3, + OutputArray mask=noArray(), const int maxIters = 2000, + const double confidence = 0.995); + +/** @overload */ +CV_EXPORTS Mat findHomography( InputArray srcPoints, InputArray dstPoints, + OutputArray mask, int method = 0, double ransacReprojThreshold = 3 ); + +/** @brief Computes an RQ decomposition of 3x3 matrices. + +@param src 3x3 input matrix. +@param mtxR Output 3x3 upper-triangular matrix. +@param mtxQ Output 3x3 orthogonal matrix. +@param Qx Optional output 3x3 rotation matrix around x-axis. +@param Qy Optional output 3x3 rotation matrix around y-axis. +@param Qz Optional output 3x3 rotation matrix around z-axis. + +The function computes a RQ decomposition using the given rotations. This function is used in +decomposeProjectionMatrix to decompose the left 3x3 submatrix of a projection matrix into a camera +and a rotation matrix. + +It optionally returns three rotation matrices, one for each axis, and the three Euler angles in +degrees (as the return value) that could be used in OpenGL. Note, there is always more than one +sequence of rotations about the three principal axes that results in the same orientation of an +object, e.g. see @cite Slabaugh . Returned tree rotation matrices and corresponding three Euler angles +are only one of the possible solutions. + */ +CV_EXPORTS_W Vec3d RQDecomp3x3( InputArray src, OutputArray mtxR, OutputArray mtxQ, + OutputArray Qx = noArray(), + OutputArray Qy = noArray(), + OutputArray Qz = noArray()); + +/** @brief Decomposes a projection matrix into a rotation matrix and a camera matrix. + +@param projMatrix 3x4 input projection matrix P. +@param cameraMatrix Output 3x3 camera matrix K. +@param rotMatrix Output 3x3 external rotation matrix R. +@param transVect Output 4x1 translation vector T. +@param rotMatrixX Optional 3x3 rotation matrix around x-axis. +@param rotMatrixY Optional 3x3 rotation matrix around y-axis. +@param rotMatrixZ Optional 3x3 rotation matrix around z-axis. +@param eulerAngles Optional three-element vector containing three Euler angles of rotation in +degrees. + +The function computes a decomposition of a projection matrix into a calibration and a rotation +matrix and the position of a camera. + +It optionally returns three rotation matrices, one for each axis, and three Euler angles that could +be used in OpenGL. Note, there is always more than one sequence of rotations about the three +principal axes that results in the same orientation of an object, e.g. see @cite Slabaugh . Returned +tree rotation matrices and corresponding three Euler angles are only one of the possible solutions. + +The function is based on RQDecomp3x3 . + */ +CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray cameraMatrix, + OutputArray rotMatrix, OutputArray transVect, + OutputArray rotMatrixX = noArray(), + OutputArray rotMatrixY = noArray(), + OutputArray rotMatrixZ = noArray(), + OutputArray eulerAngles =noArray() ); + +/** @brief Computes partial derivatives of the matrix product for each multiplied matrix. + +@param A First multiplied matrix. +@param B Second multiplied matrix. +@param dABdA First output derivative matrix d(A\*B)/dA of size +\f$\texttt{A.rows*B.cols} \times {A.rows*A.cols}\f$ . +@param dABdB Second output derivative matrix d(A\*B)/dB of size +\f$\texttt{A.rows*B.cols} \times {B.rows*B.cols}\f$ . + +The function computes partial derivatives of the elements of the matrix product \f$A*B\f$ with regard to +the elements of each of the two input matrices. The function is used to compute the Jacobian +matrices in stereoCalibrate but can also be used in any other similar optimization function. + */ +CV_EXPORTS_W void matMulDeriv( InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB ); + +/** @brief Combines two rotation-and-shift transformations. + +@param rvec1 First rotation vector. +@param tvec1 First translation vector. +@param rvec2 Second rotation vector. +@param tvec2 Second translation vector. +@param rvec3 Output rotation vector of the superposition. +@param tvec3 Output translation vector of the superposition. +@param dr3dr1 +@param dr3dt1 +@param dr3dr2 +@param dr3dt2 +@param dt3dr1 +@param dt3dt1 +@param dt3dr2 +@param dt3dt2 Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and +tvec2, respectively. + +The functions compute: + +\f[\begin{array}{l} \texttt{rvec3} = \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right ) \\ \texttt{tvec3} = \mathrm{rodrigues} ( \texttt{rvec2} ) \cdot \texttt{tvec1} + \texttt{tvec2} \end{array} ,\f] + +where \f$\mathrm{rodrigues}\f$ denotes a rotation vector to a rotation matrix transformation, and +\f$\mathrm{rodrigues}^{-1}\f$ denotes the inverse transformation. See Rodrigues for details. + +Also, the functions can compute the derivatives of the output vectors with regards to the input +vectors (see matMulDeriv ). The functions are used inside stereoCalibrate but can also be used in +your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a +function that contains a matrix multiplication. + */ +CV_EXPORTS_W void composeRT( InputArray rvec1, InputArray tvec1, + InputArray rvec2, InputArray tvec2, + OutputArray rvec3, OutputArray tvec3, + OutputArray dr3dr1 = noArray(), OutputArray dr3dt1 = noArray(), + OutputArray dr3dr2 = noArray(), OutputArray dr3dt2 = noArray(), + OutputArray dt3dr1 = noArray(), OutputArray dt3dt1 = noArray(), + OutputArray dt3dr2 = noArray(), OutputArray dt3dt2 = noArray() ); + +/** @brief Projects 3D points to an image plane. + +@param objectPoints Array of object points, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel (or +vector\ ), where N is the number of points in the view. +@param rvec Rotation vector. See Rodrigues for details. +@param tvec Translation vector. +@param cameraMatrix Camera matrix \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is empty, the zero distortion coefficients are assumed. +@param imagePoints Output array of image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, or +vector\ . +@param jacobian Optional output 2Nx(10+\) jacobian matrix of derivatives of image +points with respect to components of the rotation vector, translation vector, focal lengths, +coordinates of the principal point and the distortion coefficients. In the old interface different +components of the jacobian are returned via different output parameters. +@param aspectRatio Optional "fixed aspect ratio" parameter. If the parameter is not 0, the +function assumes that the aspect ratio (*fx/fy*) is fixed and correspondingly adjusts the jacobian +matrix. + +The function computes projections of 3D points to the image plane given intrinsic and extrinsic +camera parameters. Optionally, the function computes Jacobians - matrices of partial derivatives of +image points coordinates (as functions of all the input parameters) with respect to the particular +parameters, intrinsic and/or extrinsic. The Jacobians are used during the global optimization in +calibrateCamera, solvePnP, and stereoCalibrate . The function itself can also be used to compute a +re-projection error given the current intrinsic and extrinsic parameters. + +@note By setting rvec=tvec=(0,0,0) or by setting cameraMatrix to a 3x3 identity matrix, or by +passing zero distortion coefficients, you can get various useful partial cases of the function. This +means that you can compute the distorted coordinates for a sparse set of points or apply a +perspective transformation (and also compute the derivatives) in the ideal zero-distortion setup. + */ +CV_EXPORTS_W void projectPoints( InputArray objectPoints, + InputArray rvec, InputArray tvec, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArray imagePoints, + OutputArray jacobian = noArray(), + double aspectRatio = 0 ); + +/** @example samples/cpp/tutorial_code/features2D/Homography/homography_from_camera_displacement.cpp +An example program about homography from the camera displacement + +Check @ref tutorial_homography "the corresponding tutorial" for more details +*/ + +/** @brief Finds an object pose from 3D-2D point correspondences. + +@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or +1xN/Nx1 3-channel, where N is the number of points. vector\ can be also passed here. +@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel, +where N is the number of points. vector\ can be also passed here. +@param cameraMatrix Input camera matrix \f$A = \vecthreethree{fx}{0}{cx}{0}{fy}{cy}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are +assumed. +@param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec , brings points from +the model coordinate system to the camera coordinate system. +@param tvec Output translation vector. +@param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses +the provided rvec and tvec values as initial approximations of the rotation and translation +vectors, respectively, and further optimizes them. +@param flags Method for solving a PnP problem: +- **SOLVEPNP_ITERATIVE** Iterative method is based on Levenberg-Marquardt optimization. In +this case the function finds such a pose that minimizes reprojection error, that is the sum +of squared distances between the observed projections imagePoints and the projected (using +projectPoints ) objectPoints . +- **SOLVEPNP_P3P** Method is based on the paper of X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang +"Complete Solution Classification for the Perspective-Three-Point Problem" (@cite gao2003complete). +In this case the function requires exactly four object and image points. +- **SOLVEPNP_AP3P** Method is based on the paper of T. Ke, S. Roumeliotis +"An Efficient Algebraic Solution to the Perspective-Three-Point Problem" (@cite Ke17). +In this case the function requires exactly four object and image points. +- **SOLVEPNP_EPNP** Method has been introduced by F.Moreno-Noguer, V.Lepetit and P.Fua in the +paper "EPnP: Efficient Perspective-n-Point Camera Pose Estimation" (@cite lepetit2009epnp). +- **SOLVEPNP_DLS** Method is based on the paper of Joel A. Hesch and Stergios I. Roumeliotis. +"A Direct Least-Squares (DLS) Method for PnP" (@cite hesch2011direct). +- **SOLVEPNP_UPNP** Method is based on the paper of A.Penate-Sanchez, J.Andrade-Cetto, +F.Moreno-Noguer. "Exhaustive Linearization for Robust Camera Pose and Focal Length +Estimation" (@cite penate2013exhaustive). In this case the function also estimates the parameters \f$f_x\f$ and \f$f_y\f$ +assuming that both have the same value. Then the cameraMatrix is updated with the estimated +focal length. +- **SOLVEPNP_AP3P** Method is based on the paper of Tong Ke and Stergios I. Roumeliotis. +"An Efficient Algebraic Solution to the Perspective-Three-Point Problem" (@cite Ke17). In this case the +function requires exactly four object and image points. + +The function estimates the object pose given a set of object points, their corresponding image +projections, as well as the camera matrix and the distortion coefficients, see the figure below +(more precisely, the X-axis of the camera frame is pointing to the right, the Y-axis downward +and the Z-axis forward). + +![](pnp.jpg) + +Points expressed in the world frame \f$ \bf{X}_w \f$ are projected into the image plane \f$ \left[ u, v \right] \f$ +using the perspective projection model \f$ \Pi \f$ and the camera intrinsic parameters matrix \f$ \bf{A} \f$: + +\f[ + \begin{align*} + \begin{bmatrix} + u \\ + v \\ + 1 + \end{bmatrix} &= + \bf{A} \hspace{0.1em} \Pi \hspace{0.2em} ^{c}\bf{M}_w + \begin{bmatrix} + X_{w} \\ + Y_{w} \\ + Z_{w} \\ + 1 + \end{bmatrix} \\ + \begin{bmatrix} + u \\ + v \\ + 1 + \end{bmatrix} &= + \begin{bmatrix} + f_x & 0 & c_x \\ + 0 & f_y & c_y \\ + 0 & 0 & 1 + \end{bmatrix} + \begin{bmatrix} + 1 & 0 & 0 & 0 \\ + 0 & 1 & 0 & 0 \\ + 0 & 0 & 1 & 0 + \end{bmatrix} + \begin{bmatrix} + r_{11} & r_{12} & r_{13} & t_x \\ + r_{21} & r_{22} & r_{23} & t_y \\ + r_{31} & r_{32} & r_{33} & t_z \\ + 0 & 0 & 0 & 1 + \end{bmatrix} + \begin{bmatrix} + X_{w} \\ + Y_{w} \\ + Z_{w} \\ + 1 + \end{bmatrix} + \end{align*} +\f] + +The estimated pose is thus the rotation (`rvec`) and the translation (`tvec`) vectors that allow to transform +a 3D point expressed in the world frame into the camera frame: + +\f[ + \begin{align*} + \begin{bmatrix} + X_c \\ + Y_c \\ + Z_c \\ + 1 + \end{bmatrix} &= + \hspace{0.2em} ^{c}\bf{M}_w + \begin{bmatrix} + X_{w} \\ + Y_{w} \\ + Z_{w} \\ + 1 + \end{bmatrix} \\ + \begin{bmatrix} + X_c \\ + Y_c \\ + Z_c \\ + 1 + \end{bmatrix} &= + \begin{bmatrix} + r_{11} & r_{12} & r_{13} & t_x \\ + r_{21} & r_{22} & r_{23} & t_y \\ + r_{31} & r_{32} & r_{33} & t_z \\ + 0 & 0 & 0 & 1 + \end{bmatrix} + \begin{bmatrix} + X_{w} \\ + Y_{w} \\ + Z_{w} \\ + 1 + \end{bmatrix} + \end{align*} +\f] + +@note + - An example of how to use solvePnP for planar augmented reality can be found at + opencv_source_code/samples/python/plane_ar.py + - If you are using Python: + - Numpy array slices won't work as input because solvePnP requires contiguous + arrays (enforced by the assertion using cv::Mat::checkVector() around line 55 of + modules/calib3d/src/solvepnp.cpp version 2.4.9) + - The P3P algorithm requires image points to be in an array of shape (N,1,2) due + to its calling of cv::undistortPoints (around line 75 of modules/calib3d/src/solvepnp.cpp version 2.4.9) + which requires 2-channel information. + - Thus, given some data D = np.array(...) where D.shape = (N,M), in order to use a subset of + it as, e.g., imagePoints, one must effectively copy it into a new array: imagePoints = + np.ascontiguousarray(D[:,:2]).reshape((N,1,2)) + - The methods **SOLVEPNP_DLS** and **SOLVEPNP_UPNP** cannot be used as the current implementations are + unstable and sometimes give completely wrong results. If you pass one of these two + flags, **SOLVEPNP_EPNP** method will be used instead. + - The minimum number of points is 4 in the general case. In the case of **SOLVEPNP_P3P** and **SOLVEPNP_AP3P** + methods, it is required to use exactly 4 points (the first 3 points are used to estimate all the solutions + of the P3P problem, the last one is used to retain the best solution that minimizes the reprojection error). + - With **SOLVEPNP_ITERATIVE** method and `useExtrinsicGuess=true`, the minimum number of points is 3 (3 points + are sufficient to compute a pose but there are up to 4 solutions). The initial solution should be close to the + global solution to converge. + */ +CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArray rvec, OutputArray tvec, + bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE ); + +/** @brief Finds an object pose from 3D-2D point correspondences using the RANSAC scheme. + +@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or +1xN/Nx1 3-channel, where N is the number of points. vector\ can be also passed here. +@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel, +where N is the number of points. vector\ can be also passed here. +@param cameraMatrix Input camera matrix \f$A = \vecthreethree{fx}{0}{cx}{0}{fy}{cy}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are +assumed. +@param rvec Output rotation vector (see Rodrigues ) that, together with tvec , brings points from +the model coordinate system to the camera coordinate system. +@param tvec Output translation vector. +@param useExtrinsicGuess Parameter used for SOLVEPNP_ITERATIVE. If true (1), the function uses +the provided rvec and tvec values as initial approximations of the rotation and translation +vectors, respectively, and further optimizes them. +@param iterationsCount Number of iterations. +@param reprojectionError Inlier threshold value used by the RANSAC procedure. The parameter value +is the maximum allowed distance between the observed and computed point projections to consider it +an inlier. +@param confidence The probability that the algorithm produces a useful result. +@param inliers Output vector that contains indices of inliers in objectPoints and imagePoints . +@param flags Method for solving a PnP problem (see solvePnP ). + +The function estimates an object pose given a set of object points, their corresponding image +projections, as well as the camera matrix and the distortion coefficients. This function finds such +a pose that minimizes reprojection error, that is, the sum of squared distances between the observed +projections imagePoints and the projected (using projectPoints ) objectPoints. The use of RANSAC +makes the function resistant to outliers. + +@note + - An example of how to use solvePNPRansac for object detection can be found at + opencv_source_code/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/ + - The default method used to estimate the camera pose for the Minimal Sample Sets step + is #SOLVEPNP_EPNP. Exceptions are: + - if you choose #SOLVEPNP_P3P or #SOLVEPNP_AP3P, these methods will be used. + - if the number of input points is equal to 4, #SOLVEPNP_P3P is used. + - The method used to estimate the camera pose using all the inliers is defined by the + flags parameters unless it is equal to #SOLVEPNP_P3P or #SOLVEPNP_AP3P. In this case, + the method #SOLVEPNP_EPNP will be used instead. + */ +CV_EXPORTS_W bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArray rvec, OutputArray tvec, + bool useExtrinsicGuess = false, int iterationsCount = 100, + float reprojectionError = 8.0, double confidence = 0.99, + OutputArray inliers = noArray(), int flags = SOLVEPNP_ITERATIVE ); +/** @brief Finds an object pose from 3 3D-2D point correspondences. + +@param objectPoints Array of object points in the object coordinate space, 3x3 1-channel or +1x3/3x1 3-channel. vector\ can be also passed here. +@param imagePoints Array of corresponding image points, 3x2 1-channel or 1x3/3x1 2-channel. + vector\ can be also passed here. +@param cameraMatrix Input camera matrix \f$A = \vecthreethree{fx}{0}{cx}{0}{fy}{cy}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are +assumed. +@param rvecs Output rotation vectors (see Rodrigues ) that, together with tvecs , brings points from +the model coordinate system to the camera coordinate system. A P3P problem has up to 4 solutions. +@param tvecs Output translation vectors. +@param flags Method for solving a P3P problem: +- **SOLVEPNP_P3P** Method is based on the paper of X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang +"Complete Solution Classification for the Perspective-Three-Point Problem" (@cite gao2003complete). +- **SOLVEPNP_AP3P** Method is based on the paper of Tong Ke and Stergios I. Roumeliotis. +"An Efficient Algebraic Solution to the Perspective-Three-Point Problem" (@cite Ke17). + +The function estimates the object pose given 3 object points, their corresponding image +projections, as well as the camera matrix and the distortion coefficients. + */ +CV_EXPORTS_W int solveP3P( InputArray objectPoints, InputArray imagePoints, + InputArray cameraMatrix, InputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + int flags ); + +/** @brief Finds an initial camera matrix from 3D-2D point correspondences. + +@param objectPoints Vector of vectors of the calibration pattern points in the calibration pattern +coordinate space. In the old interface all the per-view vectors are concatenated. See +calibrateCamera for details. +@param imagePoints Vector of vectors of the projections of the calibration pattern points. In the +old interface all the per-view vectors are concatenated. +@param imageSize Image size in pixels used to initialize the principal point. +@param aspectRatio If it is zero or negative, both \f$f_x\f$ and \f$f_y\f$ are estimated independently. +Otherwise, \f$f_x = f_y * \texttt{aspectRatio}\f$ . + +The function estimates and returns an initial camera matrix for the camera calibration process. +Currently, the function only supports planar calibration patterns, which are patterns where each +object point has z-coordinate =0. + */ +CV_EXPORTS_W Mat initCameraMatrix2D( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints, + Size imageSize, double aspectRatio = 1.0 ); + +/** @brief Finds the positions of internal corners of the chessboard. + +@param image Source chessboard view. It must be an 8-bit grayscale or color image. +@param patternSize Number of inner corners per a chessboard row and column +( patternSize = cvSize(points_per_row,points_per_colum) = cvSize(columns,rows) ). +@param corners Output array of detected corners. +@param flags Various operation flags that can be zero or a combination of the following values: +- **CALIB_CB_ADAPTIVE_THRESH** Use adaptive thresholding to convert the image to black +and white, rather than a fixed threshold level (computed from the average image brightness). +- **CALIB_CB_NORMALIZE_IMAGE** Normalize the image gamma with equalizeHist before +applying fixed or adaptive thresholding. +- **CALIB_CB_FILTER_QUADS** Use additional criteria (like contour area, perimeter, +square-like shape) to filter out false quads extracted at the contour retrieval stage. +- **CALIB_CB_FAST_CHECK** Run a fast check on the image that looks for chessboard corners, +and shortcut the call if none is found. This can drastically speed up the call in the +degenerate condition when no chessboard is observed. + +The function attempts to determine whether the input image is a view of the chessboard pattern and +locate the internal chessboard corners. The function returns a non-zero value if all of the corners +are found and they are placed in a certain order (row by row, left to right in every row). +Otherwise, if the function fails to find all the corners or reorder them, it returns 0. For example, +a regular chessboard has 8 x 8 squares and 7 x 7 internal corners, that is, points where the black +squares touch each other. The detected coordinates are approximate, and to determine their positions +more accurately, the function calls cornerSubPix. You also may use the function cornerSubPix with +different parameters if returned coordinates are not accurate enough. + +Sample usage of detecting and drawing chessboard corners: : +@code + Size patternsize(8,6); //interior number of corners + Mat gray = ....; //source image + vector corners; //this will be filled by the detected corners + + //CALIB_CB_FAST_CHECK saves a lot of time on images + //that do not contain any chessboard corners + bool patternfound = findChessboardCorners(gray, patternsize, corners, + CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE + + CALIB_CB_FAST_CHECK); + + if(patternfound) + cornerSubPix(gray, corners, Size(11, 11), Size(-1, -1), + TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1)); + + drawChessboardCorners(img, patternsize, Mat(corners), patternfound); +@endcode +@note The function requires white space (like a square-thick border, the wider the better) around +the board to make the detection more robust in various environments. Otherwise, if there is no +border and the background is dark, the outer black squares cannot be segmented properly and so the +square grouping and ordering algorithm fails. + */ +CV_EXPORTS_W bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners, + int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE ); + +//! finds subpixel-accurate positions of the chessboard corners +CV_EXPORTS bool find4QuadCornerSubpix( InputArray img, InputOutputArray corners, Size region_size ); + +/** @brief Renders the detected chessboard corners. + +@param image Destination image. It must be an 8-bit color image. +@param patternSize Number of inner corners per a chessboard row and column +(patternSize = cv::Size(points_per_row,points_per_column)). +@param corners Array of detected corners, the output of findChessboardCorners. +@param patternWasFound Parameter indicating whether the complete board was found or not. The +return value of findChessboardCorners should be passed here. + +The function draws individual chessboard corners detected either as red circles if the board was not +found, or as colored corners connected with lines if the board was found. + */ +CV_EXPORTS_W void drawChessboardCorners( InputOutputArray image, Size patternSize, + InputArray corners, bool patternWasFound ); + +/** @brief Draw axes of the world/object coordinate system from pose estimation. @sa solvePnP + +@param image Input/output image. It must have 1 or 3 channels. The number of channels is not altered. +@param cameraMatrix Input 3x3 floating-point matrix of camera intrinsic parameters. +\f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is empty, the zero distortion coefficients are assumed. +@param rvec Rotation vector (see @ref Rodrigues ) that, together with tvec , brings points from +the model coordinate system to the camera coordinate system. +@param tvec Translation vector. +@param length Length of the painted axes in the same unit than tvec (usually in meters). +@param thickness Line thickness of the painted axes. + +This function draws the axes of the world/object coordinate system w.r.t. to the camera frame. +OX is drawn in red, OY in green and OZ in blue. + */ +CV_EXPORTS_W void drawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs, + InputArray rvec, InputArray tvec, float length, int thickness=3); + +struct CV_EXPORTS_W_SIMPLE CirclesGridFinderParameters +{ + CV_WRAP CirclesGridFinderParameters(); + CV_PROP_RW cv::Size2f densityNeighborhoodSize; + CV_PROP_RW float minDensity; + CV_PROP_RW int kmeansAttempts; + CV_PROP_RW int minDistanceToAddKeypoint; + CV_PROP_RW int keypointScale; + CV_PROP_RW float minGraphConfidence; + CV_PROP_RW float vertexGain; + CV_PROP_RW float vertexPenalty; + CV_PROP_RW float existingVertexGain; + CV_PROP_RW float edgeGain; + CV_PROP_RW float edgePenalty; + CV_PROP_RW float convexHullFactor; + CV_PROP_RW float minRNGEdgeSwitchDist; + + enum GridType + { + SYMMETRIC_GRID, ASYMMETRIC_GRID + }; + GridType gridType; +}; + +struct CV_EXPORTS_W_SIMPLE CirclesGridFinderParameters2 : public CirclesGridFinderParameters +{ + CV_WRAP CirclesGridFinderParameters2(); + + CV_PROP_RW float squareSize; //!< Distance between two adjacent points. Used by CALIB_CB_CLUSTERING. + CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from predicion. Used by CALIB_CB_CLUSTERING. +}; + +/** @brief Finds centers in the grid of circles. + +@param image grid view of input circles; it must be an 8-bit grayscale or color image. +@param patternSize number of circles per row and column +( patternSize = Size(points_per_row, points_per_colum) ). +@param centers output array of detected centers. +@param flags various operation flags that can be one of the following values: +- **CALIB_CB_SYMMETRIC_GRID** uses symmetric pattern of circles. +- **CALIB_CB_ASYMMETRIC_GRID** uses asymmetric pattern of circles. +- **CALIB_CB_CLUSTERING** uses a special algorithm for grid detection. It is more robust to +perspective distortions but much more sensitive to background clutter. +@param blobDetector feature detector that finds blobs like dark circles on light background. +@param parameters struct for finding circles in a grid pattern. + +The function attempts to determine whether the input image contains a grid of circles. If it is, the +function locates centers of the circles. The function returns a non-zero value if all of the centers +have been found and they have been placed in a certain order (row by row, left to right in every +row). Otherwise, if the function fails to find all the corners or reorder them, it returns 0. + +Sample usage of detecting and drawing the centers of circles: : +@code + Size patternsize(7,7); //number of centers + Mat gray = ....; //source image + vector centers; //this will be filled by the detected centers + + bool patternfound = findCirclesGrid(gray, patternsize, centers); + + drawChessboardCorners(img, patternsize, Mat(centers), patternfound); +@endcode +@note The function requires white space (like a square-thick border, the wider the better) around +the board to make the detection more robust in various environments. + */ +CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize, + OutputArray centers, int flags, + const Ptr &blobDetector, + CirclesGridFinderParameters parameters); + +/** @overload */ +CV_EXPORTS_W bool findCirclesGrid2( InputArray image, Size patternSize, + OutputArray centers, int flags, + const Ptr &blobDetector, + CirclesGridFinderParameters2 parameters); + +/** @overload */ +CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize, + OutputArray centers, int flags = CALIB_CB_SYMMETRIC_GRID, + const Ptr &blobDetector = SimpleBlobDetector::create()); + +/** @brief Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern. + +@param objectPoints In the new interface it is a vector of vectors of calibration pattern points in +the calibration pattern coordinate space (e.g. std::vector>). The outer +vector contains as many elements as the number of the pattern views. If the same calibration pattern +is shown in each view and it is fully visible, all the vectors will be the same. Although, it is +possible to use partially occluded patterns, or even different patterns in different views. Then, +the vectors will be different. The points are 3D, but since they are in a pattern coordinate system, +then, if the rig is planar, it may make sense to put the model to a XY coordinate plane so that +Z-coordinate of each input object point is 0. +In the old interface all the vectors of object points from different views are concatenated +together. +@param imagePoints In the new interface it is a vector of vectors of the projections of calibration +pattern points (e.g. std::vector>). imagePoints.size() and +objectPoints.size() and imagePoints[i].size() must be equal to objectPoints[i].size() for each i. +In the old interface all the vectors of object points from different views are concatenated +together. +@param imageSize Size of the image used only to initialize the intrinsic camera matrix. +@param cameraMatrix Output 3x3 floating-point camera matrix +\f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . If CV\_CALIB\_USE\_INTRINSIC\_GUESS +and/or CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be +initialized before calling the function. +@param distCoeffs Output vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. +@param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each pattern view +(e.g. std::vector>). That is, each k-th rotation vector together with the corresponding +k-th translation vector (see the next output parameter description) brings the calibration pattern +from the model coordinate space (in which object points are specified) to the world coordinate +space, that is, a real position of the calibration pattern in the k-th pattern view (k=0.. *M* -1). +@param tvecs Output vector of translation vectors estimated for each pattern view. +@param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters. + Order of deviations values: +\f$(f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3, + s_4, \tau_x, \tau_y)\f$ If one of parameters is not estimated, it's deviation is equals to zero. +@param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters. + Order of deviations values: \f$(R_1, T_1, \dotsc , R_M, T_M)\f$ where M is number of pattern views, + \f$R_i, T_i\f$ are concatenated 1x3 vectors. + @param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view. +@param flags Different flags that may be zero or a combination of the following values: +- **CALIB_USE_INTRINSIC_GUESS** cameraMatrix contains valid initial values of +fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image +center ( imageSize is used), and focal distances are computed in a least-squares fashion. +Note, that if intrinsic parameters are known, there is no need to use this function just to +estimate extrinsic parameters. Use solvePnP instead. +- **CALIB_FIX_PRINCIPAL_POINT** The principal point is not changed during the global +optimization. It stays at the center or at a different location specified when +CALIB_USE_INTRINSIC_GUESS is set too. +- **CALIB_FIX_ASPECT_RATIO** The functions considers only fy as a free parameter. The +ratio fx/fy stays the same as in the input cameraMatrix . When +CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are +ignored, only their ratio is computed and used further. +- **CALIB_ZERO_TANGENT_DIST** Tangential distortion coefficients \f$(p_1, p_2)\f$ are set +to zeros and stay zero. +- **CALIB_FIX_K1,...,CALIB_FIX_K6** The corresponding radial distortion +coefficient is not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is +set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. +- **CALIB_RATIONAL_MODEL** Coefficients k4, k5, and k6 are enabled. To provide the +backward compatibility, this extra flag should be explicitly specified to make the +calibration function use the rational model and return 8 coefficients. If the flag is not +set, the function computes and returns only 5 distortion coefficients. +- **CALIB_THIN_PRISM_MODEL** Coefficients s1, s2, s3 and s4 are enabled. To provide the +backward compatibility, this extra flag should be explicitly specified to make the +calibration function use the thin prism model and return 12 coefficients. If the flag is not +set, the function computes and returns only 5 distortion coefficients. +- **CALIB_FIX_S1_S2_S3_S4** The thin prism distortion coefficients are not changed during +the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the +supplied distCoeffs matrix is used. Otherwise, it is set to 0. +- **CALIB_TILTED_MODEL** Coefficients tauX and tauY are enabled. To provide the +backward compatibility, this extra flag should be explicitly specified to make the +calibration function use the tilted sensor model and return 14 coefficients. If the flag is not +set, the function computes and returns only 5 distortion coefficients. +- **CALIB_FIX_TAUX_TAUY** The coefficients of the tilted sensor model are not changed during +the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the +supplied distCoeffs matrix is used. Otherwise, it is set to 0. +@param criteria Termination criteria for the iterative optimization algorithm. + +@return the overall RMS re-projection error. + +The function estimates the intrinsic camera parameters and extrinsic parameters for each of the +views. The algorithm is based on @cite Zhang2000 and @cite BouguetMCT . The coordinates of 3D object +points and their corresponding 2D projections in each view must be specified. That may be achieved +by using an object with a known geometry and easily detectable feature points. Such an object is +called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as +a calibration rig (see findChessboardCorners ). Currently, initialization of intrinsic parameters +(when CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration +patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also +be used as long as initial cameraMatrix is provided. + +The algorithm performs the following steps: + +- Compute the initial intrinsic parameters (the option only available for planar calibration + patterns) or read them from the input parameters. The distortion coefficients are all set to + zeros initially unless some of CALIB_FIX_K? are specified. + +- Estimate the initial camera pose as if the intrinsic parameters have been already known. This is + done using solvePnP . + +- Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error, + that is, the total sum of squared distances between the observed feature points imagePoints and + the projected (using the current estimates for camera parameters and the poses) object points + objectPoints. See projectPoints for details. + +@note + If you use a non-square (=non-NxN) grid and findChessboardCorners for calibration, and + calibrateCamera returns bad values (zero distortion coefficients, an image center very far from + (w/2-0.5,h/2-0.5), and/or large differences between \f$f_x\f$ and \f$f_y\f$ (ratios of 10:1 or more)), + then you have probably used patternSize=cvSize(rows,cols) instead of using + patternSize=cvSize(cols,rows) in findChessboardCorners . + +@sa + findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort + */ +CV_EXPORTS_AS(calibrateCameraExtended) double calibrateCamera( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints, Size imageSize, + InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + OutputArray stdDeviationsIntrinsics, + OutputArray stdDeviationsExtrinsics, + OutputArray perViewErrors, + int flags = 0, TermCriteria criteria = TermCriteria( + TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) ); + +/** @overload double calibrateCamera( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints, Size imageSize, + InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + OutputArray stdDeviations, OutputArray perViewErrors, + int flags = 0, TermCriteria criteria = TermCriteria( + TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) ) + */ +CV_EXPORTS_W double calibrateCamera( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints, Size imageSize, + InputOutputArray cameraMatrix, InputOutputArray distCoeffs, + OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, + int flags = 0, TermCriteria criteria = TermCriteria( + TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) ); + +/** @brief Computes useful camera characteristics from the camera matrix. + +@param cameraMatrix Input camera matrix that can be estimated by calibrateCamera or +stereoCalibrate . +@param imageSize Input image size in pixels. +@param apertureWidth Physical width in mm of the sensor. +@param apertureHeight Physical height in mm of the sensor. +@param fovx Output field of view in degrees along the horizontal sensor axis. +@param fovy Output field of view in degrees along the vertical sensor axis. +@param focalLength Focal length of the lens in mm. +@param principalPoint Principal point in mm. +@param aspectRatio \f$f_y/f_x\f$ + +The function computes various useful camera characteristics from the previously estimated camera +matrix. + +@note + Do keep in mind that the unity measure 'mm' stands for whatever unit of measure one chooses for + the chessboard pitch (it can thus be any value). + */ +CV_EXPORTS_W void calibrationMatrixValues( InputArray cameraMatrix, Size imageSize, + double apertureWidth, double apertureHeight, + CV_OUT double& fovx, CV_OUT double& fovy, + CV_OUT double& focalLength, CV_OUT Point2d& principalPoint, + CV_OUT double& aspectRatio ); + +/** @brief Calibrates the stereo camera. + +@param objectPoints Vector of vectors of the calibration pattern points. +@param imagePoints1 Vector of vectors of the projections of the calibration pattern points, +observed by the first camera. +@param imagePoints2 Vector of vectors of the projections of the calibration pattern points, +observed by the second camera. +@param cameraMatrix1 Input/output first camera matrix: +\f$\vecthreethree{f_x^{(j)}}{0}{c_x^{(j)}}{0}{f_y^{(j)}}{c_y^{(j)}}{0}{0}{1}\f$ , \f$j = 0,\, 1\f$ . If +any of CALIB_USE_INTRINSIC_GUESS , CALIB_FIX_ASPECT_RATIO , +CALIB_FIX_INTRINSIC , or CALIB_FIX_FOCAL_LENGTH are specified, some or all of the +matrix components must be initialized. See the flags description for details. +@param distCoeffs1 Input/output vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. The output vector length depends on the flags. +@param cameraMatrix2 Input/output second camera matrix. The parameter is similar to cameraMatrix1 +@param distCoeffs2 Input/output lens distortion coefficients for the second camera. The parameter +is similar to distCoeffs1 . +@param imageSize Size of the image used only to initialize intrinsic camera matrix. +@param R Output rotation matrix between the 1st and the 2nd camera coordinate systems. +@param T Output translation vector between the coordinate systems of the cameras. +@param E Output essential matrix. +@param F Output fundamental matrix. +@param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view. +@param flags Different flags that may be zero or a combination of the following values: +- **CALIB_FIX_INTRINSIC** Fix cameraMatrix? and distCoeffs? so that only R, T, E , and F +matrices are estimated. +- **CALIB_USE_INTRINSIC_GUESS** Optimize some or all of the intrinsic parameters +according to the specified flags. Initial values are provided by the user. +- **CALIB_USE_EXTRINSIC_GUESS** R, T contain valid initial values that are optimized further. +Otherwise R, T are initialized to the median value of the pattern views (each dimension separately). +- **CALIB_FIX_PRINCIPAL_POINT** Fix the principal points during the optimization. +- **CALIB_FIX_FOCAL_LENGTH** Fix \f$f^{(j)}_x\f$ and \f$f^{(j)}_y\f$ . +- **CALIB_FIX_ASPECT_RATIO** Optimize \f$f^{(j)}_y\f$ . Fix the ratio \f$f^{(j)}_x/f^{(j)}_y\f$ +. +- **CALIB_SAME_FOCAL_LENGTH** Enforce \f$f^{(0)}_x=f^{(1)}_x\f$ and \f$f^{(0)}_y=f^{(1)}_y\f$ . +- **CALIB_ZERO_TANGENT_DIST** Set tangential distortion coefficients for each camera to +zeros and fix there. +- **CALIB_FIX_K1,...,CALIB_FIX_K6** Do not change the corresponding radial +distortion coefficient during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, +the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0. +- **CALIB_RATIONAL_MODEL** Enable coefficients k4, k5, and k6. To provide the backward +compatibility, this extra flag should be explicitly specified to make the calibration +function use the rational model and return 8 coefficients. If the flag is not set, the +function computes and returns only 5 distortion coefficients. +- **CALIB_THIN_PRISM_MODEL** Coefficients s1, s2, s3 and s4 are enabled. To provide the +backward compatibility, this extra flag should be explicitly specified to make the +calibration function use the thin prism model and return 12 coefficients. If the flag is not +set, the function computes and returns only 5 distortion coefficients. +- **CALIB_FIX_S1_S2_S3_S4** The thin prism distortion coefficients are not changed during +the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the +supplied distCoeffs matrix is used. Otherwise, it is set to 0. +- **CALIB_TILTED_MODEL** Coefficients tauX and tauY are enabled. To provide the +backward compatibility, this extra flag should be explicitly specified to make the +calibration function use the tilted sensor model and return 14 coefficients. If the flag is not +set, the function computes and returns only 5 distortion coefficients. +- **CALIB_FIX_TAUX_TAUY** The coefficients of the tilted sensor model are not changed during +the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the +supplied distCoeffs matrix is used. Otherwise, it is set to 0. +@param criteria Termination criteria for the iterative optimization algorithm. + +The function estimates transformation between two cameras making a stereo pair. If you have a stereo +camera where the relative position and orientation of two cameras is fixed, and if you computed +poses of an object relative to the first camera and to the second camera, (R1, T1) and (R2, T2), +respectively (this can be done with solvePnP ), then those poses definitely relate to each other. +This means that, given ( \f$R_1\f$,\f$T_1\f$ ), it should be possible to compute ( \f$R_2\f$,\f$T_2\f$ ). You only +need to know the position and orientation of the second camera relative to the first camera. This is +what the described function does. It computes ( \f$R\f$,\f$T\f$ ) so that: + +\f[R_2=R*R_1\f] +\f[T_2=R*T_1 + T,\f] + +Optionally, it computes the essential matrix E: + +\f[E= \vecthreethree{0}{-T_2}{T_1}{T_2}{0}{-T_0}{-T_1}{T_0}{0} *R\f] + +where \f$T_i\f$ are components of the translation vector \f$T\f$ : \f$T=[T_0, T_1, T_2]^T\f$ . And the function +can also compute the fundamental matrix F: + +\f[F = cameraMatrix2^{-T} E cameraMatrix1^{-1}\f] + +Besides the stereo-related information, the function can also perform a full calibration of each of +two cameras. However, due to the high dimensionality of the parameter space and noise in the input +data, the function can diverge from the correct solution. If the intrinsic parameters can be +estimated with high accuracy for each of the cameras individually (for example, using +calibrateCamera ), you are recommended to do so and then pass CALIB_FIX_INTRINSIC flag to the +function along with the computed intrinsic parameters. Otherwise, if all the parameters are +estimated at once, it makes sense to restrict some parameters, for example, pass +CALIB_SAME_FOCAL_LENGTH and CALIB_ZERO_TANGENT_DIST flags, which is usually a +reasonable assumption. + +Similarly to calibrateCamera , the function minimizes the total re-projection error for all the +points in all the available views from both cameras. The function returns the final value of the +re-projection error. + */ +CV_EXPORTS_AS(stereoCalibrateExtended) double stereoCalibrate( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, + InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, + InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, + Size imageSize, InputOutputArray R,InputOutputArray T, OutputArray E, OutputArray F, + OutputArray perViewErrors, int flags = CALIB_FIX_INTRINSIC, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) ); + +/// @overload +CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints, + InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, + InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, + InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, + Size imageSize, OutputArray R,OutputArray T, OutputArray E, OutputArray F, + int flags = CALIB_FIX_INTRINSIC, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) ); + +/** @brief Computes rectification transforms for each head of a calibrated stereo camera. + +@param cameraMatrix1 First camera matrix. +@param distCoeffs1 First camera distortion parameters. +@param cameraMatrix2 Second camera matrix. +@param distCoeffs2 Second camera distortion parameters. +@param imageSize Size of the image used for stereo calibration. +@param R Rotation matrix between the coordinate systems of the first and the second cameras. +@param T Translation vector between coordinate systems of the cameras. +@param R1 Output 3x3 rectification transform (rotation matrix) for the first camera. +@param R2 Output 3x3 rectification transform (rotation matrix) for the second camera. +@param P1 Output 3x4 projection matrix in the new (rectified) coordinate systems for the first +camera. +@param P2 Output 3x4 projection matrix in the new (rectified) coordinate systems for the second +camera. +@param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see reprojectImageTo3D ). +@param flags Operation flags that may be zero or CALIB_ZERO_DISPARITY . If the flag is set, +the function makes the principal points of each camera have the same pixel coordinates in the +rectified views. And if the flag is not set, the function may still shift the images in the +horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the +useful image area. +@param alpha Free scaling parameter. If it is -1 or absent, the function performs the default +scaling. Otherwise, the parameter should be between 0 and 1. alpha=0 means that the rectified +images are zoomed and shifted so that only valid pixels are visible (no black areas after +rectification). alpha=1 means that the rectified image is decimated and shifted so that all the +pixels from the original images from the cameras are retained in the rectified images (no source +image pixels are lost). Obviously, any intermediate value yields an intermediate result between +those two extreme cases. +@param newImageSize New image resolution after rectification. The same size should be passed to +initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0) +is passed (default), it is set to the original imageSize . Setting it to larger value can help you +preserve details in the original image, especially when there is a big radial distortion. +@param validPixROI1 Optional output rectangles inside the rectified images where all the pixels +are valid. If alpha=0 , the ROIs cover the whole images. Otherwise, they are likely to be smaller +(see the picture below). +@param validPixROI2 Optional output rectangles inside the rectified images where all the pixels +are valid. If alpha=0 , the ROIs cover the whole images. Otherwise, they are likely to be smaller +(see the picture below). + +The function computes the rotation matrices for each camera that (virtually) make both camera image +planes the same plane. Consequently, this makes all the epipolar lines parallel and thus simplifies +the dense stereo correspondence problem. The function takes the matrices computed by stereoCalibrate +as input. As output, it provides two rotation matrices and also two projection matrices in the new +coordinates. The function distinguishes the following two cases: + +- **Horizontal stereo**: the first and the second camera views are shifted relative to each other + mainly along the x axis (with possible small vertical shift). In the rectified images, the + corresponding epipolar lines in the left and right cameras are horizontal and have the same + y-coordinate. P1 and P2 look like: + + \f[\texttt{P1} = \begin{bmatrix} f & 0 & cx_1 & 0 \\ 0 & f & cy & 0 \\ 0 & 0 & 1 & 0 \end{bmatrix}\f] + + \f[\texttt{P2} = \begin{bmatrix} f & 0 & cx_2 & T_x*f \\ 0 & f & cy & 0 \\ 0 & 0 & 1 & 0 \end{bmatrix} ,\f] + + where \f$T_x\f$ is a horizontal shift between the cameras and \f$cx_1=cx_2\f$ if + CALIB_ZERO_DISPARITY is set. + +- **Vertical stereo**: the first and the second camera views are shifted relative to each other + mainly in vertical direction (and probably a bit in the horizontal direction too). The epipolar + lines in the rectified images are vertical and have the same x-coordinate. P1 and P2 look like: + + \f[\texttt{P1} = \begin{bmatrix} f & 0 & cx & 0 \\ 0 & f & cy_1 & 0 \\ 0 & 0 & 1 & 0 \end{bmatrix}\f] + + \f[\texttt{P2} = \begin{bmatrix} f & 0 & cx & 0 \\ 0 & f & cy_2 & T_y*f \\ 0 & 0 & 1 & 0 \end{bmatrix} ,\f] + + where \f$T_y\f$ is a vertical shift between the cameras and \f$cy_1=cy_2\f$ if CALIB_ZERO_DISPARITY is + set. + +As you can see, the first three columns of P1 and P2 will effectively be the new "rectified" camera +matrices. The matrices, together with R1 and R2 , can then be passed to initUndistortRectifyMap to +initialize the rectification map for each camera. + +See below the screenshot from the stereo_calib.cpp sample. Some red horizontal lines pass through +the corresponding image regions. This means that the images are well rectified, which is what most +stereo correspondence algorithms rely on. The green rectangles are roi1 and roi2 . You see that +their interiors are all valid pixels. + +![image](pics/stereo_undistort.jpg) + */ +CV_EXPORTS_W void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs1, + InputArray cameraMatrix2, InputArray distCoeffs2, + Size imageSize, InputArray R, InputArray T, + OutputArray R1, OutputArray R2, + OutputArray P1, OutputArray P2, + OutputArray Q, int flags = CALIB_ZERO_DISPARITY, + double alpha = -1, Size newImageSize = Size(), + CV_OUT Rect* validPixROI1 = 0, CV_OUT Rect* validPixROI2 = 0 ); + +/** @brief Computes a rectification transform for an uncalibrated stereo camera. + +@param points1 Array of feature points in the first image. +@param points2 The corresponding points in the second image. The same formats as in +findFundamentalMat are supported. +@param F Input fundamental matrix. It can be computed from the same set of point pairs using +findFundamentalMat . +@param imgSize Size of the image. +@param H1 Output rectification homography matrix for the first image. +@param H2 Output rectification homography matrix for the second image. +@param threshold Optional threshold used to filter out the outliers. If the parameter is greater +than zero, all the point pairs that do not comply with the epipolar geometry (that is, the points +for which \f$|\texttt{points2[i]}^T*\texttt{F}*\texttt{points1[i]}|>\texttt{threshold}\f$ ) are +rejected prior to computing the homographies. Otherwise, all the points are considered inliers. + +The function computes the rectification transformations without knowing intrinsic parameters of the +cameras and their relative position in the space, which explains the suffix "uncalibrated". Another +related difference from stereoRectify is that the function outputs not the rectification +transformations in the object (3D) space, but the planar perspective transformations encoded by the +homography matrices H1 and H2 . The function implements the algorithm @cite Hartley99 . + +@note + While the algorithm does not need to know the intrinsic parameters of the cameras, it heavily + depends on the epipolar geometry. Therefore, if the camera lenses have a significant distortion, + it would be better to correct it before computing the fundamental matrix and calling this + function. For example, distortion coefficients can be estimated for each head of stereo camera + separately by using calibrateCamera . Then, the images can be corrected using undistort , or + just the point coordinates can be corrected with undistortPoints . + */ +CV_EXPORTS_W bool stereoRectifyUncalibrated( InputArray points1, InputArray points2, + InputArray F, Size imgSize, + OutputArray H1, OutputArray H2, + double threshold = 5 ); + +//! computes the rectification transformations for 3-head camera, where all the heads are on the same line. +CV_EXPORTS_W float rectify3Collinear( InputArray cameraMatrix1, InputArray distCoeffs1, + InputArray cameraMatrix2, InputArray distCoeffs2, + InputArray cameraMatrix3, InputArray distCoeffs3, + InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3, + Size imageSize, InputArray R12, InputArray T12, + InputArray R13, InputArray T13, + OutputArray R1, OutputArray R2, OutputArray R3, + OutputArray P1, OutputArray P2, OutputArray P3, + OutputArray Q, double alpha, Size newImgSize, + CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags ); + +/** @brief Returns the new camera matrix based on the free scaling parameter. + +@param cameraMatrix Input camera matrix. +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ of +4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are +assumed. +@param imageSize Original image size. +@param alpha Free scaling parameter between 0 (when all the pixels in the undistorted image are +valid) and 1 (when all the source image pixels are retained in the undistorted image). See +stereoRectify for details. +@param newImgSize Image size after rectification. By default, it is set to imageSize . +@param validPixROI Optional output rectangle that outlines all-good-pixels region in the +undistorted image. See roi1, roi2 description in stereoRectify . +@param centerPrincipalPoint Optional flag that indicates whether in the new camera matrix the +principal point should be at the image center or not. By default, the principal point is chosen to +best fit a subset of the source image (determined by alpha) to the corrected image. +@return new_camera_matrix Output new camera matrix. + +The function computes and returns the optimal new camera matrix based on the free scaling parameter. +By varying this parameter, you may retrieve only sensible pixels alpha=0 , keep all the original +image pixels if there is valuable information in the corners alpha=1 , or get something in between. +When alpha\>0 , the undistorted result is likely to have some black pixels corresponding to +"virtual" pixels outside of the captured distorted image. The original camera matrix, distortion +coefficients, the computed new camera matrix, and newImageSize should be passed to +initUndistortRectifyMap to produce the maps for remap . + */ +CV_EXPORTS_W Mat getOptimalNewCameraMatrix( InputArray cameraMatrix, InputArray distCoeffs, + Size imageSize, double alpha, Size newImgSize = Size(), + CV_OUT Rect* validPixROI = 0, + bool centerPrincipalPoint = false); + +/** @brief Computes Hand-Eye calibration: \f$_{}^{g}\textrm{T}_c\f$ + +@param[in] R_gripper2base Rotation part extracted from the homogeneous matrix that transforms a point +expressed in the gripper frame to the robot base frame (\f$_{}^{b}\textrm{T}_g\f$). +This is a vector (`vector`) that contains the rotation matrices for all the transformations +from gripper frame to robot base frame. +@param[in] t_gripper2base Translation part extracted from the homogeneous matrix that transforms a point +expressed in the gripper frame to the robot base frame (\f$_{}^{b}\textrm{T}_g\f$). +This is a vector (`vector`) that contains the translation vectors for all the transformations +from gripper frame to robot base frame. +@param[in] R_target2cam Rotation part extracted from the homogeneous matrix that transforms a point +expressed in the target frame to the camera frame (\f$_{}^{c}\textrm{T}_t\f$). +This is a vector (`vector`) that contains the rotation matrices for all the transformations +from calibration target frame to camera frame. +@param[in] t_target2cam Rotation part extracted from the homogeneous matrix that transforms a point +expressed in the target frame to the camera frame (\f$_{}^{c}\textrm{T}_t\f$). +This is a vector (`vector`) that contains the translation vectors for all the transformations +from calibration target frame to camera frame. +@param[out] R_cam2gripper Estimated rotation part extracted from the homogeneous matrix that transforms a point +expressed in the camera frame to the gripper frame (\f$_{}^{g}\textrm{T}_c\f$). +@param[out] t_cam2gripper Estimated translation part extracted from the homogeneous matrix that transforms a point +expressed in the camera frame to the gripper frame (\f$_{}^{g}\textrm{T}_c\f$). +@param[in] method One of the implemented Hand-Eye calibration method, see cv::HandEyeCalibrationMethod + +The function performs the Hand-Eye calibration using various methods. One approach consists in estimating the +rotation then the translation (separable solutions) and the following methods are implemented: + - R. Tsai, R. Lenz A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/EyeCalibration \cite Tsai89 + - F. Park, B. Martin Robot Sensor Calibration: Solving AX = XB on the Euclidean Group \cite Park94 + - R. Horaud, F. Dornaika Hand-Eye Calibration \cite Horaud95 + +Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions), +with the following implemented method: + - N. Andreff, R. Horaud, B. Espiau On-line Hand-Eye Calibration \cite Andreff99 + - K. Daniilidis Hand-Eye Calibration Using Dual Quaternions \cite Daniilidis98 + +The following picture describes the Hand-Eye calibration problem where the transformation between a camera ("eye") +mounted on a robot gripper ("hand") has to be estimated. + +![](pics/hand-eye_figure.png) + +The calibration procedure is the following: + - a static calibration pattern is used to estimate the transformation between the target frame + and the camera frame + - the robot gripper is moved in order to acquire several poses + - for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for + instance the robot kinematics +\f[ + \begin{bmatrix} + X_b\\ + Y_b\\ + Z_b\\ + 1 + \end{bmatrix} + = + \begin{bmatrix} + _{}^{b}\textrm{R}_g & _{}^{b}\textrm{t}_g \\ + 0_{1 \times 3} & 1 + \end{bmatrix} + \begin{bmatrix} + X_g\\ + Y_g\\ + Z_g\\ + 1 + \end{bmatrix} +\f] + - for each pose, the homogeneous transformation between the calibration target frame and the camera frame is recorded using + for instance a pose estimation method (PnP) from 2D-3D point correspondences +\f[ + \begin{bmatrix} + X_c\\ + Y_c\\ + Z_c\\ + 1 + \end{bmatrix} + = + \begin{bmatrix} + _{}^{c}\textrm{R}_t & _{}^{c}\textrm{t}_t \\ + 0_{1 \times 3} & 1 + \end{bmatrix} + \begin{bmatrix} + X_t\\ + Y_t\\ + Z_t\\ + 1 + \end{bmatrix} +\f] + +The Hand-Eye calibration procedure returns the following homogeneous transformation +\f[ + \begin{bmatrix} + X_g\\ + Y_g\\ + Z_g\\ + 1 + \end{bmatrix} + = + \begin{bmatrix} + _{}^{g}\textrm{R}_c & _{}^{g}\textrm{t}_c \\ + 0_{1 \times 3} & 1 + \end{bmatrix} + \begin{bmatrix} + X_c\\ + Y_c\\ + Z_c\\ + 1 + \end{bmatrix} +\f] + +This problem is also known as solving the \f$\mathbf{A}\mathbf{X}=\mathbf{X}\mathbf{B}\f$ equation: +\f[ + \begin{align*} + ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &= + \hspace{0.1em} ^{b}{\textrm{T}_g}^{(2)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\ + + (^{b}{\textrm{T}_g}^{(2)})^{-1} \hspace{0.2em} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c &= + \hspace{0.1em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\ + + \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\ + \end{align*} +\f] + +\note +Additional information can be found on this [website](http://campar.in.tum.de/Chair/HandEyeCalibration). +\note +A minimum of 2 motions with non parallel rotation axes are necessary to determine the hand-eye transformation. +So at least 3 different poses are required, but it is strongly recommended to use many more poses. + + */ +CV_EXPORTS_W void calibrateHandEye( InputArrayOfArrays R_gripper2base, InputArrayOfArrays t_gripper2base, + InputArrayOfArrays R_target2cam, InputArrayOfArrays t_target2cam, + OutputArray R_cam2gripper, OutputArray t_cam2gripper, + HandEyeCalibrationMethod method=CALIB_HAND_EYE_TSAI ); + +/** @brief Converts points from Euclidean to homogeneous space. + +@param src Input vector of N-dimensional points. +@param dst Output vector of N+1-dimensional points. + +The function converts points from Euclidean to homogeneous space by appending 1's to the tuple of +point coordinates. That is, each point (x1, x2, ..., xn) is converted to (x1, x2, ..., xn, 1). + */ +CV_EXPORTS_W void convertPointsToHomogeneous( InputArray src, OutputArray dst ); + +/** @brief Converts points from homogeneous to Euclidean space. + +@param src Input vector of N-dimensional points. +@param dst Output vector of N-1-dimensional points. + +The function converts points homogeneous to Euclidean space using perspective projection. That is, +each point (x1, x2, ... x(n-1), xn) is converted to (x1/xn, x2/xn, ..., x(n-1)/xn). When xn=0, the +output point coordinates will be (0,0,0,...). + */ +CV_EXPORTS_W void convertPointsFromHomogeneous( InputArray src, OutputArray dst ); + +/** @brief Converts points to/from homogeneous coordinates. + +@param src Input array or vector of 2D, 3D, or 4D points. +@param dst Output vector of 2D, 3D, or 4D points. + +The function converts 2D or 3D points from/to homogeneous coordinates by calling either +convertPointsToHomogeneous or convertPointsFromHomogeneous. + +@note The function is obsolete. Use one of the previous two functions instead. + */ +CV_EXPORTS void convertPointsHomogeneous( InputArray src, OutputArray dst ); + +/** @brief Calculates a fundamental matrix from the corresponding points in two images. + +@param points1 Array of N points from the first image. The point coordinates should be +floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1 . +@param method Method for computing a fundamental matrix. +- **CV_FM_7POINT** for a 7-point algorithm. \f$N = 7\f$ +- **CV_FM_8POINT** for an 8-point algorithm. \f$N \ge 8\f$ +- **CV_FM_RANSAC** for the RANSAC algorithm. \f$N \ge 8\f$ +- **CV_FM_LMEDS** for the LMedS algorithm. \f$N \ge 8\f$ +@param ransacReprojThreshold Parameter used only for RANSAC. It is the maximum distance from a point to an epipolar +line in pixels, beyond which the point is considered an outlier and is not used for computing the +final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the +point localization, image resolution, and the image noise. +@param confidence Parameter used for the RANSAC and LMedS methods only. It specifies a desirable level +of confidence (probability) that the estimated matrix is correct. +@param mask + +The epipolar geometry is described by the following equation: + +\f[[p_2; 1]^T F [p_1; 1] = 0\f] + +where \f$F\f$ is a fundamental matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the +second images, respectively. + +The function calculates the fundamental matrix using one of four methods listed above and returns +the found fundamental matrix. Normally just one matrix is found. But in case of the 7-point +algorithm, the function may return up to 3 solutions ( \f$9 \times 3\f$ matrix that stores all 3 +matrices sequentially). + +The calculated fundamental matrix may be passed further to computeCorrespondEpilines that finds the +epipolar lines corresponding to the specified points. It can also be passed to +stereoRectifyUncalibrated to compute the rectification transformation. : +@code + // Example. Estimation of fundamental matrix using the RANSAC algorithm + int point_count = 100; + vector points1(point_count); + vector points2(point_count); + + // initialize the points here ... + for( int i = 0; i < point_count; i++ ) + { + points1[i] = ...; + points2[i] = ...; + } + + Mat fundamental_matrix = + findFundamentalMat(points1, points2, FM_RANSAC, 3, 0.99); +@endcode + */ +CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2, + int method = FM_RANSAC, + double ransacReprojThreshold = 3., double confidence = 0.99, + OutputArray mask = noArray() ); + +/** @overload */ +CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2, + OutputArray mask, int method = FM_RANSAC, + double ransacReprojThreshold = 3., double confidence = 0.99 ); + +/** @brief Calculates an essential matrix from the corresponding points in two images. + +@param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should +be floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1 . +@param cameraMatrix Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +Note that this function assumes that points1 and points2 are feature points from cameras with the +same camera matrix. +@param method Method for computing an essential matrix. +- **RANSAC** for the RANSAC algorithm. +- **LMEDS** for the LMedS algorithm. +@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of +confidence (probability) that the estimated matrix is correct. +@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar +line in pixels, beyond which the point is considered an outlier and is not used for computing the +final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the +point localization, image resolution, and the image noise. +@param mask Output array of N elements, every element of which is set to 0 for outliers and to 1 +for the other points. The array is computed only in the RANSAC and LMedS methods. + +This function estimates essential matrix based on the five-point algorithm solver in @cite Nister03 . +@cite SteweniusCFS is also a related. The epipolar geometry is described by the following equation: + +\f[[p_2; 1]^T K^{-T} E K^{-1} [p_1; 1] = 0\f] + +where \f$E\f$ is an essential matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the +second images, respectively. The result of this function may be passed further to +decomposeEssentialMat or recoverPose to recover the relative pose between cameras. + */ +CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2, + InputArray cameraMatrix, int method = RANSAC, + double prob = 0.999, double threshold = 1.0, + OutputArray mask = noArray() ); + +/** @overload +@param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should +be floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1 . +@param focal focal length of the camera. Note that this function assumes that points1 and points2 +are feature points from cameras with same focal length and principal point. +@param pp principal point of the camera. +@param method Method for computing a fundamental matrix. +- **RANSAC** for the RANSAC algorithm. +- **LMEDS** for the LMedS algorithm. +@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar +line in pixels, beyond which the point is considered an outlier and is not used for computing the +final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the +point localization, image resolution, and the image noise. +@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of +confidence (probability) that the estimated matrix is correct. +@param mask Output array of N elements, every element of which is set to 0 for outliers and to 1 +for the other points. The array is computed only in the RANSAC and LMedS methods. + +This function differs from the one above that it computes camera matrix from focal length and +principal point: + +\f[K = +\begin{bmatrix} +f & 0 & x_{pp} \\ +0 & f & y_{pp} \\ +0 & 0 & 1 +\end{bmatrix}\f] + */ +CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2, + double focal = 1.0, Point2d pp = Point2d(0, 0), + int method = RANSAC, double prob = 0.999, + double threshold = 1.0, OutputArray mask = noArray() ); + +/** @brief Decompose an essential matrix to possible rotations and translation. + +@param E The input essential matrix. +@param R1 One possible rotation matrix. +@param R2 Another possible rotation matrix. +@param t One possible translation. + +This function decompose an essential matrix E using svd decomposition @cite HartleyZ00 . Generally 4 +possible poses exists for a given E. They are \f$[R_1, t]\f$, \f$[R_1, -t]\f$, \f$[R_2, t]\f$, \f$[R_2, -t]\f$. By +decomposing E, you can only get the direction of the translation, so the function returns unit t. + */ +CV_EXPORTS_W void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t ); + +/** @brief Recover relative camera rotation and translation from an estimated essential matrix and the +corresponding points in two images, using cheirality check. Returns the number of inliers which pass +the check. + +@param E The input essential matrix. +@param points1 Array of N 2D points from the first image. The point coordinates should be +floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1 . +@param cameraMatrix Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +Note that this function assumes that points1 and points2 are feature points from cameras with the +same camera matrix. +@param R Recovered relative rotation. +@param t Recovered relative translation. +@param mask Input/output mask for inliers in points1 and points2. +: If it is not empty, then it marks inliers in points1 and points2 for then given essential +matrix E. Only these inliers will be used to recover pose. In the output mask only inliers +which pass the cheirality check. +This function decomposes an essential matrix using decomposeEssentialMat and then verifies possible +pose hypotheses by doing cheirality check. The cheirality check basically means that the +triangulated 3D points should have positive depth. Some details can be found in @cite Nister03 . + +This function can be used to process output E and mask from findEssentialMat. In this scenario, +points1 and points2 are the same input for findEssentialMat. : +@code + // Example. Estimation of fundamental matrix using the RANSAC algorithm + int point_count = 100; + vector points1(point_count); + vector points2(point_count); + + // initialize the points here ... + for( int i = 0; i < point_count; i++ ) + { + points1[i] = ...; + points2[i] = ...; + } + + // cametra matrix with both focal lengths = 1, and principal point = (0, 0) + Mat cameraMatrix = Mat::eye(3, 3, CV_64F); + + Mat E, R, t, mask; + + E = findEssentialMat(points1, points2, cameraMatrix, RANSAC, 0.999, 1.0, mask); + recoverPose(E, points1, points2, cameraMatrix, R, t, mask); +@endcode + */ +CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2, + InputArray cameraMatrix, OutputArray R, OutputArray t, + InputOutputArray mask = noArray() ); + +/** @overload +@param E The input essential matrix. +@param points1 Array of N 2D points from the first image. The point coordinates should be +floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1 . +@param R Recovered relative rotation. +@param t Recovered relative translation. +@param focal Focal length of the camera. Note that this function assumes that points1 and points2 +are feature points from cameras with same focal length and principal point. +@param pp principal point of the camera. +@param mask Input/output mask for inliers in points1 and points2. +: If it is not empty, then it marks inliers in points1 and points2 for then given essential +matrix E. Only these inliers will be used to recover pose. In the output mask only inliers +which pass the cheirality check. + +This function differs from the one above that it computes camera matrix from focal length and +principal point: + +\f[K = +\begin{bmatrix} +f & 0 & x_{pp} \\ +0 & f & y_{pp} \\ +0 & 0 & 1 +\end{bmatrix}\f] + */ +CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2, + OutputArray R, OutputArray t, + double focal = 1.0, Point2d pp = Point2d(0, 0), + InputOutputArray mask = noArray() ); + +/** @overload +@param E The input essential matrix. +@param points1 Array of N 2D points from the first image. The point coordinates should be +floating-point (single or double precision). +@param points2 Array of the second image points of the same size and format as points1. +@param cameraMatrix Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +Note that this function assumes that points1 and points2 are feature points from cameras with the +same camera matrix. +@param R Recovered relative rotation. +@param t Recovered relative translation. +@param distanceThresh threshold distance which is used to filter out far away points (i.e. infinite points). +@param mask Input/output mask for inliers in points1 and points2. +: If it is not empty, then it marks inliers in points1 and points2 for then given essential +matrix E. Only these inliers will be used to recover pose. In the output mask only inliers +which pass the cheirality check. +@param triangulatedPoints 3d points which were reconstructed by triangulation. + */ + +CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2, + InputArray cameraMatrix, OutputArray R, OutputArray t, double distanceThresh, InputOutputArray mask = noArray(), + OutputArray triangulatedPoints = noArray()); + +/** @brief For points in an image of a stereo pair, computes the corresponding epilines in the other image. + +@param points Input points. \f$N \times 1\f$ or \f$1 \times N\f$ matrix of type CV_32FC2 or +vector\ . +@param whichImage Index of the image (1 or 2) that contains the points . +@param F Fundamental matrix that can be estimated using findFundamentalMat or stereoRectify . +@param lines Output vector of the epipolar lines corresponding to the points in the other image. +Each line \f$ax + by + c=0\f$ is encoded by 3 numbers \f$(a, b, c)\f$ . + +For every point in one of the two images of a stereo pair, the function finds the equation of the +corresponding epipolar line in the other image. + +From the fundamental matrix definition (see findFundamentalMat ), line \f$l^{(2)}_i\f$ in the second +image for the point \f$p^{(1)}_i\f$ in the first image (when whichImage=1 ) is computed as: + +\f[l^{(2)}_i = F p^{(1)}_i\f] + +And vice versa, when whichImage=2, \f$l^{(1)}_i\f$ is computed from \f$p^{(2)}_i\f$ as: + +\f[l^{(1)}_i = F^T p^{(2)}_i\f] + +Line coefficients are defined up to a scale. They are normalized so that \f$a_i^2+b_i^2=1\f$ . + */ +CV_EXPORTS_W void computeCorrespondEpilines( InputArray points, int whichImage, + InputArray F, OutputArray lines ); + +/** @brief Reconstructs points by triangulation. + +@param projMatr1 3x4 projection matrix of the first camera. +@param projMatr2 3x4 projection matrix of the second camera. +@param projPoints1 2xN array of feature points in the first image. In case of c++ version it can +be also a vector of feature points or two-channel matrix of size 1xN or Nx1. +@param projPoints2 2xN array of corresponding points in the second image. In case of c++ version +it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1. +@param points4D 4xN array of reconstructed points in homogeneous coordinates. + +The function reconstructs 3-dimensional points (in homogeneous coordinates) by using their +observations with a stereo camera. Projections matrices can be obtained from stereoRectify. + +@note + Keep in mind that all input data should be of float type in order for this function to work. + +@sa + reprojectImageTo3D + */ +CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2, + InputArray projPoints1, InputArray projPoints2, + OutputArray points4D ); + +/** @brief Refines coordinates of corresponding points. + +@param F 3x3 fundamental matrix. +@param points1 1xN array containing the first set of points. +@param points2 1xN array containing the second set of points. +@param newPoints1 The optimized points1. +@param newPoints2 The optimized points2. + +The function implements the Optimal Triangulation Method (see Multiple View Geometry for details). +For each given point correspondence points1[i] \<-\> points2[i], and a fundamental matrix F, it +computes the corrected correspondences newPoints1[i] \<-\> newPoints2[i] that minimize the geometric +error \f$d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2\f$ (where \f$d(a,b)\f$ is the +geometric distance between points \f$a\f$ and \f$b\f$ ) subject to the epipolar constraint +\f$newPoints2^T * F * newPoints1 = 0\f$ . + */ +CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2, + OutputArray newPoints1, OutputArray newPoints2 ); + +/** @brief Filters off small noise blobs (speckles) in the disparity map + +@param img The input 16-bit signed disparity image +@param newVal The disparity value used to paint-off the speckles +@param maxSpeckleSize The maximum speckle size to consider it a speckle. Larger blobs are not +affected by the algorithm +@param maxDiff Maximum difference between neighbor disparity pixels to put them into the same +blob. Note that since StereoBM, StereoSGBM and may be other algorithms return a fixed-point +disparity map, where disparity values are multiplied by 16, this scale factor should be taken into +account when specifying this parameter value. +@param buf The optional temporary buffer to avoid memory allocation within the function. + */ +CV_EXPORTS_W void filterSpeckles( InputOutputArray img, double newVal, + int maxSpeckleSize, double maxDiff, + InputOutputArray buf = noArray() ); + +//! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify()) +CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2, + int minDisparity, int numberOfDisparities, + int SADWindowSize ); + +//! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm +CV_EXPORTS_W void validateDisparity( InputOutputArray disparity, InputArray cost, + int minDisparity, int numberOfDisparities, + int disp12MaxDisp = 1 ); + +/** @brief Reprojects a disparity image to 3D space. + +@param disparity Input single-channel 8-bit unsigned, 16-bit signed, 32-bit signed or 32-bit +floating-point disparity image. If 16-bit signed format is used, the values are assumed to have no +fractional bits. +@param _3dImage Output 3-channel floating-point image of the same size as disparity . Each +element of _3dImage(x,y) contains 3D coordinates of the point (x,y) computed from the disparity +map. +@param Q \f$4 \times 4\f$ perspective transformation matrix that can be obtained with stereoRectify. +@param handleMissingValues Indicates, whether the function should handle missing values (i.e. +points where the disparity was not computed). If handleMissingValues=true, then pixels with the +minimal disparity that corresponds to the outliers (see StereoMatcher::compute ) are transformed +to 3D points with a very large Z value (currently set to 10000). +@param ddepth The optional output array depth. If it is -1, the output image will have CV_32F +depth. ddepth can also be set to CV_16S, CV_32S or CV_32F. + +The function transforms a single-channel disparity map to a 3-channel image representing a 3D +surface. That is, for each pixel (x,y) and the corresponding disparity d=disparity(x,y) , it +computes: + +\f[\begin{array}{l} [X \; Y \; Z \; W]^T = \texttt{Q} *[x \; y \; \texttt{disparity} (x,y) \; 1]^T \\ \texttt{\_3dImage} (x,y) = (X/W, \; Y/W, \; Z/W) \end{array}\f] + +The matrix Q can be an arbitrary \f$4 \times 4\f$ matrix (for example, the one computed by +stereoRectify). To reproject a sparse set of points {(x,y,d),...} to 3D space, use +perspectiveTransform . + */ +CV_EXPORTS_W void reprojectImageTo3D( InputArray disparity, + OutputArray _3dImage, InputArray Q, + bool handleMissingValues = false, + int ddepth = -1 ); + +/** @brief Calculates the Sampson Distance between two points. + +The function cv::sampsonDistance calculates and returns the first order approximation of the geometric error as: +\f[ +sd( \texttt{pt1} , \texttt{pt2} )= +\frac{(\texttt{pt2}^t \cdot \texttt{F} \cdot \texttt{pt1})^2} +{((\texttt{F} \cdot \texttt{pt1})(0))^2 + +((\texttt{F} \cdot \texttt{pt1})(1))^2 + +((\texttt{F}^t \cdot \texttt{pt2})(0))^2 + +((\texttt{F}^t \cdot \texttt{pt2})(1))^2} +\f] +The fundamental matrix may be calculated using the cv::findFundamentalMat function. See @cite HartleyZ00 11.4.3 for details. +@param pt1 first homogeneous 2d point +@param pt2 second homogeneous 2d point +@param F fundamental matrix +@return The computed Sampson distance. +*/ +CV_EXPORTS_W double sampsonDistance(InputArray pt1, InputArray pt2, InputArray F); + +/** @brief Computes an optimal affine transformation between two 3D point sets. + +It computes +\f[ +\begin{bmatrix} +x\\ +y\\ +z\\ +\end{bmatrix} += +\begin{bmatrix} +a_{11} & a_{12} & a_{13}\\ +a_{21} & a_{22} & a_{23}\\ +a_{31} & a_{32} & a_{33}\\ +\end{bmatrix} +\begin{bmatrix} +X\\ +Y\\ +Z\\ +\end{bmatrix} ++ +\begin{bmatrix} +b_1\\ +b_2\\ +b_3\\ +\end{bmatrix} +\f] + +@param src First input 3D point set containing \f$(X,Y,Z)\f$. +@param dst Second input 3D point set containing \f$(x,y,z)\f$. +@param out Output 3D affine transformation matrix \f$3 \times 4\f$ of the form +\f[ +\begin{bmatrix} +a_{11} & a_{12} & a_{13} & b_1\\ +a_{21} & a_{22} & a_{23} & b_2\\ +a_{31} & a_{32} & a_{33} & b_3\\ +\end{bmatrix} +\f] +@param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier). +@param ransacThreshold Maximum reprojection error in the RANSAC algorithm to consider a point as +an inlier. +@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything +between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation +significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation. + +The function estimates an optimal 3D affine transformation between two 3D point sets using the +RANSAC algorithm. + */ +CV_EXPORTS_W int estimateAffine3D(InputArray src, InputArray dst, + OutputArray out, OutputArray inliers, + double ransacThreshold = 3, double confidence = 0.99); + +/** @brief Computes an optimal affine transformation between two 2D point sets. + +It computes +\f[ +\begin{bmatrix} +x\\ +y\\ +\end{bmatrix} += +\begin{bmatrix} +a_{11} & a_{12}\\ +a_{21} & a_{22}\\ +\end{bmatrix} +\begin{bmatrix} +X\\ +Y\\ +\end{bmatrix} ++ +\begin{bmatrix} +b_1\\ +b_2\\ +\end{bmatrix} +\f] + +@param from First input 2D point set containing \f$(X,Y)\f$. +@param to Second input 2D point set containing \f$(x,y)\f$. +@param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier). +@param method Robust method used to compute transformation. The following methods are possible: +- cv::RANSAC - RANSAC-based robust method +- cv::LMEDS - Least-Median robust method +RANSAC is the default method. +@param ransacReprojThreshold Maximum reprojection error in the RANSAC algorithm to consider +a point as an inlier. Applies only to RANSAC. +@param maxIters The maximum number of robust method iterations. +@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything +between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation +significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation. +@param refineIters Maximum number of iterations of refining algorithm (Levenberg-Marquardt). +Passing 0 will disable refining, so the output matrix will be output of robust method. + +@return Output 2D affine transformation matrix \f$2 \times 3\f$ or empty matrix if transformation +could not be estimated. The returned matrix has the following form: +\f[ +\begin{bmatrix} +a_{11} & a_{12} & b_1\\ +a_{21} & a_{22} & b_2\\ +\end{bmatrix} +\f] + +The function estimates an optimal 2D affine transformation between two 2D point sets using the +selected robust algorithm. + +The computed transformation is then refined further (using only inliers) with the +Levenberg-Marquardt method to reduce the re-projection error even more. + +@note +The RANSAC method can handle practically any ratio of outliers but needs a threshold to +distinguish inliers from outliers. The method LMeDS does not need any threshold but it works +correctly only when there are more than 50% of inliers. + +@sa estimateAffinePartial2D, getAffineTransform +*/ +CV_EXPORTS_W cv::Mat estimateAffine2D(InputArray from, InputArray to, OutputArray inliers = noArray(), + int method = RANSAC, double ransacReprojThreshold = 3, + size_t maxIters = 2000, double confidence = 0.99, + size_t refineIters = 10); + +/** @brief Computes an optimal limited affine transformation with 4 degrees of freedom between +two 2D point sets. + +@param from First input 2D point set. +@param to Second input 2D point set. +@param inliers Output vector indicating which points are inliers. +@param method Robust method used to compute transformation. The following methods are possible: +- cv::RANSAC - RANSAC-based robust method +- cv::LMEDS - Least-Median robust method +RANSAC is the default method. +@param ransacReprojThreshold Maximum reprojection error in the RANSAC algorithm to consider +a point as an inlier. Applies only to RANSAC. +@param maxIters The maximum number of robust method iterations. +@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything +between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation +significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation. +@param refineIters Maximum number of iterations of refining algorithm (Levenberg-Marquardt). +Passing 0 will disable refining, so the output matrix will be output of robust method. + +@return Output 2D affine transformation (4 degrees of freedom) matrix \f$2 \times 3\f$ or +empty matrix if transformation could not be estimated. + +The function estimates an optimal 2D affine transformation with 4 degrees of freedom limited to +combinations of translation, rotation, and uniform scaling. Uses the selected algorithm for robust +estimation. + +The computed transformation is then refined further (using only inliers) with the +Levenberg-Marquardt method to reduce the re-projection error even more. + +Estimated transformation matrix is: +\f[ \begin{bmatrix} \cos(\theta) \cdot s & -\sin(\theta) \cdot s & t_x \\ + \sin(\theta) \cdot s & \cos(\theta) \cdot s & t_y +\end{bmatrix} \f] +Where \f$ \theta \f$ is the rotation angle, \f$ s \f$ the scaling factor and \f$ t_x, t_y \f$ are +translations in \f$ x, y \f$ axes respectively. + +@note +The RANSAC method can handle practically any ratio of outliers but need a threshold to +distinguish inliers from outliers. The method LMeDS does not need any threshold but it works +correctly only when there are more than 50% of inliers. + +@sa estimateAffine2D, getAffineTransform +*/ +CV_EXPORTS_W cv::Mat estimateAffinePartial2D(InputArray from, InputArray to, OutputArray inliers = noArray(), + int method = RANSAC, double ransacReprojThreshold = 3, + size_t maxIters = 2000, double confidence = 0.99, + size_t refineIters = 10); + +/** @example samples/cpp/tutorial_code/features2D/Homography/decompose_homography.cpp +An example program with homography decomposition. + +Check @ref tutorial_homography "the corresponding tutorial" for more details. +*/ + +/** @brief Decompose a homography matrix to rotation(s), translation(s) and plane normal(s). + +@param H The input homography matrix between two images. +@param K The input intrinsic camera calibration matrix. +@param rotations Array of rotation matrices. +@param translations Array of translation matrices. +@param normals Array of plane normal matrices. + +This function extracts relative camera motion between two views observing a planar object from the +homography H induced by the plane. The intrinsic camera matrix K must also be provided. The function +may return up to four mathematical solution sets. At least two of the solutions may further be +invalidated if point correspondences are available by applying positive depth constraint (all points +must be in front of the camera). The decomposition method is described in detail in @cite Malis . + */ +CV_EXPORTS_W int decomposeHomographyMat(InputArray H, + InputArray K, + OutputArrayOfArrays rotations, + OutputArrayOfArrays translations, + OutputArrayOfArrays normals); + +/** @brief Filters homography decompositions based on additional information. + +@param rotations Vector of rotation matrices. +@param normals Vector of plane normal matrices. +@param beforePoints Vector of (rectified) visible reference points before the homography is applied +@param afterPoints Vector of (rectified) visible reference points after the homography is applied +@param possibleSolutions Vector of int indices representing the viable solution set after filtering +@param pointsMask optional Mat/Vector of 8u type representing the mask for the inliers as given by the findHomography function + +This function is intended to filter the output of the decomposeHomographyMat based on additional +information as described in @cite Malis . The summary of the method: the decomposeHomographyMat function +returns 2 unique solutions and their "opposites" for a total of 4 solutions. If we have access to the +sets of points visible in the camera frame before and after the homography transformation is applied, +we can determine which are the true potential solutions and which are the opposites by verifying which +homographies are consistent with all visible reference points being in front of the camera. The inputs +are left unchanged; the filtered solution set is returned as indices into the existing one. + +*/ +CV_EXPORTS_W void filterHomographyDecompByVisibleRefpoints(InputArrayOfArrays rotations, + InputArrayOfArrays normals, + InputArray beforePoints, + InputArray afterPoints, + OutputArray possibleSolutions, + InputArray pointsMask = noArray()); + +/** @brief The base class for stereo correspondence algorithms. + */ +class CV_EXPORTS_W StereoMatcher : public Algorithm +{ +public: + enum { DISP_SHIFT = 4, + DISP_SCALE = (1 << DISP_SHIFT) + }; + + /** @brief Computes disparity map for the specified stereo pair + + @param left Left 8-bit single-channel image. + @param right Right image of the same size and the same type as the left one. + @param disparity Output disparity map. It has the same size as the input images. Some algorithms, + like StereoBM or StereoSGBM compute 16-bit fixed-point disparity map (where each disparity value + has 4 fractional bits), whereas other algorithms output 32-bit floating-point disparity map. + */ + CV_WRAP virtual void compute( InputArray left, InputArray right, + OutputArray disparity ) = 0; + + CV_WRAP virtual int getMinDisparity() const = 0; + CV_WRAP virtual void setMinDisparity(int minDisparity) = 0; + + CV_WRAP virtual int getNumDisparities() const = 0; + CV_WRAP virtual void setNumDisparities(int numDisparities) = 0; + + CV_WRAP virtual int getBlockSize() const = 0; + CV_WRAP virtual void setBlockSize(int blockSize) = 0; + + CV_WRAP virtual int getSpeckleWindowSize() const = 0; + CV_WRAP virtual void setSpeckleWindowSize(int speckleWindowSize) = 0; + + CV_WRAP virtual int getSpeckleRange() const = 0; + CV_WRAP virtual void setSpeckleRange(int speckleRange) = 0; + + CV_WRAP virtual int getDisp12MaxDiff() const = 0; + CV_WRAP virtual void setDisp12MaxDiff(int disp12MaxDiff) = 0; +}; + + +/** @brief Class for computing stereo correspondence using the block matching algorithm, introduced and +contributed to OpenCV by K. Konolige. + */ +class CV_EXPORTS_W StereoBM : public StereoMatcher +{ +public: + enum { PREFILTER_NORMALIZED_RESPONSE = 0, + PREFILTER_XSOBEL = 1 + }; + + CV_WRAP virtual int getPreFilterType() const = 0; + CV_WRAP virtual void setPreFilterType(int preFilterType) = 0; + + CV_WRAP virtual int getPreFilterSize() const = 0; + CV_WRAP virtual void setPreFilterSize(int preFilterSize) = 0; + + CV_WRAP virtual int getPreFilterCap() const = 0; + CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0; + + CV_WRAP virtual int getTextureThreshold() const = 0; + CV_WRAP virtual void setTextureThreshold(int textureThreshold) = 0; + + CV_WRAP virtual int getUniquenessRatio() const = 0; + CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0; + + CV_WRAP virtual int getSmallerBlockSize() const = 0; + CV_WRAP virtual void setSmallerBlockSize(int blockSize) = 0; + + CV_WRAP virtual Rect getROI1() const = 0; + CV_WRAP virtual void setROI1(Rect roi1) = 0; + + CV_WRAP virtual Rect getROI2() const = 0; + CV_WRAP virtual void setROI2(Rect roi2) = 0; + + /** @brief Creates StereoBM object + + @param numDisparities the disparity search range. For each pixel algorithm will find the best + disparity from 0 (default minimum disparity) to numDisparities. The search range can then be + shifted by changing the minimum disparity. + @param blockSize the linear size of the blocks compared by the algorithm. The size should be odd + (as the block is centered at the current pixel). Larger block size implies smoother, though less + accurate disparity map. Smaller block size gives more detailed disparity map, but there is higher + chance for algorithm to find a wrong correspondence. + + The function create StereoBM object. You can then call StereoBM::compute() to compute disparity for + a specific stereo pair. + */ + CV_WRAP static Ptr create(int numDisparities = 0, int blockSize = 21); +}; + +/** @brief The class implements the modified H. Hirschmuller algorithm @cite HH08 that differs from the original +one as follows: + +- By default, the algorithm is single-pass, which means that you consider only 5 directions +instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the +algorithm but beware that it may consume a lot of memory. +- The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the +blocks to single pixels. +- Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi +sub-pixel metric from @cite BT98 is used. Though, the color images are supported as well. +- Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for +example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness +check, quadratic interpolation and speckle filtering). + +@note + - (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found + at opencv_source_code/samples/python/stereo_match.py + */ +class CV_EXPORTS_W StereoSGBM : public StereoMatcher +{ +public: + enum + { + MODE_SGBM = 0, + MODE_HH = 1, + MODE_SGBM_3WAY = 2, + MODE_HH4 = 3 + }; + + CV_WRAP virtual int getPreFilterCap() const = 0; + CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0; + + CV_WRAP virtual int getUniquenessRatio() const = 0; + CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0; + + CV_WRAP virtual int getP1() const = 0; + CV_WRAP virtual void setP1(int P1) = 0; + + CV_WRAP virtual int getP2() const = 0; + CV_WRAP virtual void setP2(int P2) = 0; + + CV_WRAP virtual int getMode() const = 0; + CV_WRAP virtual void setMode(int mode) = 0; + + /** @brief Creates StereoSGBM object + + @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes + rectification algorithms can shift images, so this parameter needs to be adjusted accordingly. + @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than + zero. In the current implementation, this parameter must be divisible by 16. + @param blockSize Matched block size. It must be an odd number \>=1 . Normally, it should be + somewhere in the 3..11 range. + @param P1 The first parameter controlling the disparity smoothness. See below. + @param P2 The second parameter controlling the disparity smoothness. The larger the values are, + the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 + between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor + pixels. The algorithm requires P2 \> P1 . See stereo_match.cpp sample where some reasonably good + P1 and P2 values are shown (like 8\*number_of_image_channels\*SADWindowSize\*SADWindowSize and + 32\*number_of_image_channels\*SADWindowSize\*SADWindowSize , respectively). + @param disp12MaxDiff Maximum allowed difference (in integer pixel units) in the left-right + disparity check. Set it to a non-positive value to disable the check. + @param preFilterCap Truncation value for the prefiltered image pixels. The algorithm first + computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. + The result values are passed to the Birchfield-Tomasi pixel cost function. + @param uniquenessRatio Margin in percentage by which the best (minimum) computed cost function + value should "win" the second best value to consider the found match correct. Normally, a value + within the 5-15 range is good enough. + @param speckleWindowSize Maximum size of smooth disparity regions to consider their noise speckles + and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the + 50-200 range. + @param speckleRange Maximum disparity variation within each connected component. If you do speckle + filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. + Normally, 1 or 2 is good enough. + @param mode Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming + algorithm. It will consume O(W\*H\*numDisparities) bytes, which is large for 640x480 stereo and + huge for HD-size pictures. By default, it is set to false . + + The first constructor initializes StereoSGBM with all the default parameters. So, you only have to + set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter + to a custom value. + */ + CV_WRAP static Ptr create(int minDisparity = 0, int numDisparities = 16, int blockSize = 3, + int P1 = 0, int P2 = 0, int disp12MaxDiff = 0, + int preFilterCap = 0, int uniquenessRatio = 0, + int speckleWindowSize = 0, int speckleRange = 0, + int mode = StereoSGBM::MODE_SGBM); +}; + +//! @} calib3d + +/** @brief The methods in this namespace use a so-called fisheye camera model. + @ingroup calib3d_fisheye +*/ +namespace fisheye +{ +//! @addtogroup calib3d_fisheye +//! @{ + + enum{ + CALIB_USE_INTRINSIC_GUESS = 1 << 0, + CALIB_RECOMPUTE_EXTRINSIC = 1 << 1, + CALIB_CHECK_COND = 1 << 2, + CALIB_FIX_SKEW = 1 << 3, + CALIB_FIX_K1 = 1 << 4, + CALIB_FIX_K2 = 1 << 5, + CALIB_FIX_K3 = 1 << 6, + CALIB_FIX_K4 = 1 << 7, + CALIB_FIX_INTRINSIC = 1 << 8, + CALIB_FIX_PRINCIPAL_POINT = 1 << 9 + }; + + /** @brief Projects points using fisheye model + + @param objectPoints Array of object points, 1xN/Nx1 3-channel (or vector\ ), where N is + the number of points in the view. + @param imagePoints Output array of image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, or + vector\. + @param affine + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param alpha The skew coefficient. + @param jacobian Optional output 2Nx15 jacobian matrix of derivatives of image points with respect + to components of the focal lengths, coordinates of the principal point, distortion coefficients, + rotation vector, translation vector, and the skew. In the old interface different components of + the jacobian are returned via different output parameters. + + The function computes projections of 3D points to the image plane given intrinsic and extrinsic + camera parameters. Optionally, the function computes Jacobians - matrices of partial derivatives of + image points coordinates (as functions of all the input parameters) with respect to the particular + parameters, intrinsic and/or extrinsic. + */ + CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine, + InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray()); + + /** @overload */ + CV_EXPORTS_W void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec, + InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray()); + + /** @brief Distorts 2D points using fisheye model. + + @param undistorted Array of object points, 1xN/Nx1 2-channel (or vector\ ), where N is + the number of points in the view. + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param alpha The skew coefficient. + @param distorted Output array of image points, 1xN/Nx1 2-channel, or vector\ . + + Note that the function assumes the camera matrix of the undistorted points to be identity. + This means if you want to transform back points undistorted with undistortPoints() you have to + multiply them with \f$P^{-1}\f$. + */ + CV_EXPORTS_W void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0); + + /** @brief Undistorts 2D points using fisheye model + + @param distorted Array of object points, 1xN/Nx1 2-channel (or vector\ ), where N is the + number of points in the view. + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 + 1-channel or 1x1 3-channel + @param P New camera matrix (3x3) or new projection matrix (3x4) + @param undistorted Output array of image points, 1xN/Nx1 2-channel, or vector\ . + */ + CV_EXPORTS_W void undistortPoints(InputArray distorted, OutputArray undistorted, + InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray()); + + /** @brief Computes undistortion and rectification maps for image transform by cv::remap(). If D is empty zero + distortion is used, if R or P is empty identity matrixes are used. + + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 + 1-channel or 1x1 3-channel + @param P New camera matrix (3x3) or new projection matrix (3x4) + @param size Undistorted image size. + @param m1type Type of the first output map that can be CV_32FC1 or CV_16SC2 . See convertMaps() + for details. + @param map1 The first output map. + @param map2 The second output map. + */ + CV_EXPORTS_W void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P, + const cv::Size& size, int m1type, OutputArray map1, OutputArray map2); + + /** @brief Transforms an image to compensate for fisheye lens distortion. + + @param distorted image with fisheye lens distortion. + @param undistorted Output image with compensated fisheye lens distortion. + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param Knew Camera matrix of the distorted image. By default, it is the identity matrix but you + may additionally scale and shift the result by using a different matrix. + @param new_size + + The function transforms an image to compensate radial and tangential lens distortion. + + The function is simply a combination of fisheye::initUndistortRectifyMap (with unity R ) and remap + (with bilinear interpolation). See the former function for details of the transformation being + performed. + + See below the results of undistortImage. + - a\) result of undistort of perspective camera model (all possible coefficients (k_1, k_2, k_3, + k_4, k_5, k_6) of distortion were optimized under calibration) + - b\) result of fisheye::undistortImage of fisheye camera model (all possible coefficients (k_1, k_2, + k_3, k_4) of fisheye distortion were optimized under calibration) + - c\) original image was captured with fisheye lens + + Pictures a) and b) almost the same. But if we consider points of image located far from the center + of image, we can notice that on image a) these points are distorted. + + ![image](pics/fisheye_undistorted.jpg) + */ + CV_EXPORTS_W void undistortImage(InputArray distorted, OutputArray undistorted, + InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size()); + + /** @brief Estimates new camera matrix for undistortion or rectification. + + @param K Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{_1}\f$. + @param image_size + @param D Input vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3 + 1-channel or 1x1 3-channel + @param P New camera matrix (3x3) or new projection matrix (3x4) + @param balance Sets the new focal length in range between the min focal length and the max focal + length. Balance is in range of [0, 1]. + @param new_size + @param fov_scale Divisor for new focal length. + */ + CV_EXPORTS_W void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R, + OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0); + + /** @brief Performs camera calibaration + + @param objectPoints vector of vectors of calibration pattern points in the calibration pattern + coordinate space. + @param imagePoints vector of vectors of the projections of calibration pattern points. + imagePoints.size() and objectPoints.size() and imagePoints[i].size() must be equal to + objectPoints[i].size() for each i. + @param image_size Size of the image used only to initialize the intrinsic camera matrix. + @param K Output 3x3 floating-point camera matrix + \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . If + fisheye::CALIB_USE_INTRINSIC_GUESS/ is specified, some or all of fx, fy, cx, cy must be + initialized before calling the function. + @param D Output vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$. + @param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each pattern view. + That is, each k-th rotation vector together with the corresponding k-th translation vector (see + the next output parameter description) brings the calibration pattern from the model coordinate + space (in which object points are specified) to the world coordinate space, that is, a real + position of the calibration pattern in the k-th pattern view (k=0.. *M* -1). + @param tvecs Output vector of translation vectors estimated for each pattern view. + @param flags Different flags that may be zero or a combination of the following values: + - **fisheye::CALIB_USE_INTRINSIC_GUESS** cameraMatrix contains valid initial values of + fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image + center ( imageSize is used), and focal distances are computed in a least-squares fashion. + - **fisheye::CALIB_RECOMPUTE_EXTRINSIC** Extrinsic will be recomputed after each iteration + of intrinsic optimization. + - **fisheye::CALIB_CHECK_COND** The functions will check validity of condition number. + - **fisheye::CALIB_FIX_SKEW** Skew coefficient (alpha) is set to zero and stay zero. + - **fisheye::CALIB_FIX_K1..fisheye::CALIB_FIX_K4** Selected distortion coefficients + are set to zeros and stay zero. + - **fisheye::CALIB_FIX_PRINCIPAL_POINT** The principal point is not changed during the global +optimization. It stays at the center or at a different location specified when CALIB_USE_INTRINSIC_GUESS is set too. + @param criteria Termination criteria for the iterative optimization algorithm. + */ + CV_EXPORTS_W double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size, + InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON)); + + /** @brief Stereo rectification for fisheye camera model + + @param K1 First camera matrix. + @param D1 First camera distortion parameters. + @param K2 Second camera matrix. + @param D2 Second camera distortion parameters. + @param imageSize Size of the image used for stereo calibration. + @param R Rotation matrix between the coordinate systems of the first and the second + cameras. + @param tvec Translation vector between coordinate systems of the cameras. + @param R1 Output 3x3 rectification transform (rotation matrix) for the first camera. + @param R2 Output 3x3 rectification transform (rotation matrix) for the second camera. + @param P1 Output 3x4 projection matrix in the new (rectified) coordinate systems for the first + camera. + @param P2 Output 3x4 projection matrix in the new (rectified) coordinate systems for the second + camera. + @param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see reprojectImageTo3D ). + @param flags Operation flags that may be zero or CALIB_ZERO_DISPARITY . If the flag is set, + the function makes the principal points of each camera have the same pixel coordinates in the + rectified views. And if the flag is not set, the function may still shift the images in the + horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the + useful image area. + @param newImageSize New image resolution after rectification. The same size should be passed to + initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0) + is passed (default), it is set to the original imageSize . Setting it to larger value can help you + preserve details in the original image, especially when there is a big radial distortion. + @param balance Sets the new focal length in range between the min focal length and the max focal + length. Balance is in range of [0, 1]. + @param fov_scale Divisor for new focal length. + */ + CV_EXPORTS_W void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec, + OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(), + double balance = 0.0, double fov_scale = 1.0); + + /** @brief Performs stereo calibration + + @param objectPoints Vector of vectors of the calibration pattern points. + @param imagePoints1 Vector of vectors of the projections of the calibration pattern points, + observed by the first camera. + @param imagePoints2 Vector of vectors of the projections of the calibration pattern points, + observed by the second camera. + @param K1 Input/output first camera matrix: + \f$\vecthreethree{f_x^{(j)}}{0}{c_x^{(j)}}{0}{f_y^{(j)}}{c_y^{(j)}}{0}{0}{1}\f$ , \f$j = 0,\, 1\f$ . If + any of fisheye::CALIB_USE_INTRINSIC_GUESS , fisheye::CALIB_FIX_INTRINSIC are specified, + some or all of the matrix components must be initialized. + @param D1 Input/output vector of distortion coefficients \f$(k_1, k_2, k_3, k_4)\f$ of 4 elements. + @param K2 Input/output second camera matrix. The parameter is similar to K1 . + @param D2 Input/output lens distortion coefficients for the second camera. The parameter is + similar to D1 . + @param imageSize Size of the image used only to initialize intrinsic camera matrix. + @param R Output rotation matrix between the 1st and the 2nd camera coordinate systems. + @param T Output translation vector between the coordinate systems of the cameras. + @param flags Different flags that may be zero or a combination of the following values: + - **fisheye::CALIB_FIX_INTRINSIC** Fix K1, K2? and D1, D2? so that only R, T matrices + are estimated. + - **fisheye::CALIB_USE_INTRINSIC_GUESS** K1, K2 contains valid initial values of + fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image + center (imageSize is used), and focal distances are computed in a least-squares fashion. + - **fisheye::CALIB_RECOMPUTE_EXTRINSIC** Extrinsic will be recomputed after each iteration + of intrinsic optimization. + - **fisheye::CALIB_CHECK_COND** The functions will check validity of condition number. + - **fisheye::CALIB_FIX_SKEW** Skew coefficient (alpha) is set to zero and stay zero. + - **fisheye::CALIB_FIX_K1..4** Selected distortion coefficients are set to zeros and stay + zero. + @param criteria Termination criteria for the iterative optimization algorithm. + */ + CV_EXPORTS_W double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, + InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize, + OutputArray R, OutputArray T, int flags = fisheye::CALIB_FIX_INTRINSIC, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON)); + +//! @} calib3d_fisheye +} // end namespace fisheye + +} //end namespace cv + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/calib3d/calib3d_c.h" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/calib3d/calib3d.hpp b/3rdparty/opencv/include/opencv2/calib3d/calib3d.hpp new file mode 100644 index 00000000..b3da45ed --- /dev/null +++ b/3rdparty/opencv/include/opencv2/calib3d/calib3d.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/calib3d.hpp" diff --git a/3rdparty/opencv/include/opencv2/calib3d/calib3d_c.h b/3rdparty/opencv/include/opencv2/calib3d/calib3d_c.h new file mode 100644 index 00000000..8ec6390d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/calib3d/calib3d_c.h @@ -0,0 +1,427 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CALIB3D_C_H +#define OPENCV_CALIB3D_C_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup calib3d_c + @{ + */ + +/****************************************************************************************\ +* Camera Calibration, Pose Estimation and Stereo * +\****************************************************************************************/ + +typedef struct CvPOSITObject CvPOSITObject; + +/* Allocates and initializes CvPOSITObject structure before doing cvPOSIT */ +CVAPI(CvPOSITObject*) cvCreatePOSITObject( CvPoint3D32f* points, int point_count ); + + +/* Runs POSIT (POSe from ITeration) algorithm for determining 3d position of + an object given its model and projection in a weak-perspective case */ +CVAPI(void) cvPOSIT( CvPOSITObject* posit_object, CvPoint2D32f* image_points, + double focal_length, CvTermCriteria criteria, + float* rotation_matrix, float* translation_vector); + +/* Releases CvPOSITObject structure */ +CVAPI(void) cvReleasePOSITObject( CvPOSITObject** posit_object ); + +/* updates the number of RANSAC iterations */ +CVAPI(int) cvRANSACUpdateNumIters( double p, double err_prob, + int model_points, int max_iters ); + +CVAPI(void) cvConvertPointsHomogeneous( const CvMat* src, CvMat* dst ); + +/* Calculates fundamental matrix given a set of corresponding points */ +#define CV_FM_7POINT 1 +#define CV_FM_8POINT 2 + +#define CV_LMEDS 4 +#define CV_RANSAC 8 + +#define CV_FM_LMEDS_ONLY CV_LMEDS +#define CV_FM_RANSAC_ONLY CV_RANSAC +#define CV_FM_LMEDS CV_LMEDS +#define CV_FM_RANSAC CV_RANSAC + +enum +{ + CV_ITERATIVE = 0, + CV_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation" + CV_P3P = 2, // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem" + CV_DLS = 3 // Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP" +}; + +CVAPI(int) cvFindFundamentalMat( const CvMat* points1, const CvMat* points2, + CvMat* fundamental_matrix, + int method CV_DEFAULT(CV_FM_RANSAC), + double param1 CV_DEFAULT(3.), double param2 CV_DEFAULT(0.99), + CvMat* status CV_DEFAULT(NULL) ); + +/* For each input point on one of images + computes parameters of the corresponding + epipolar line on the other image */ +CVAPI(void) cvComputeCorrespondEpilines( const CvMat* points, + int which_image, + const CvMat* fundamental_matrix, + CvMat* correspondent_lines ); + +/* Triangulation functions */ + +CVAPI(void) cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2, + CvMat* projPoints1, CvMat* projPoints2, + CvMat* points4D); + +CVAPI(void) cvCorrectMatches(CvMat* F, CvMat* points1, CvMat* points2, + CvMat* new_points1, CvMat* new_points2); + + +/* Computes the optimal new camera matrix according to the free scaling parameter alpha: + alpha=0 - only valid pixels will be retained in the undistorted image + alpha=1 - all the source image pixels will be retained in the undistorted image +*/ +CVAPI(void) cvGetOptimalNewCameraMatrix( const CvMat* camera_matrix, + const CvMat* dist_coeffs, + CvSize image_size, double alpha, + CvMat* new_camera_matrix, + CvSize new_imag_size CV_DEFAULT(cvSize(0,0)), + CvRect* valid_pixel_ROI CV_DEFAULT(0), + int center_principal_point CV_DEFAULT(0)); + +/* Converts rotation vector to rotation matrix or vice versa */ +CVAPI(int) cvRodrigues2( const CvMat* src, CvMat* dst, + CvMat* jacobian CV_DEFAULT(0) ); + +/* Finds perspective transformation between the object plane and image (view) plane */ +CVAPI(int) cvFindHomography( const CvMat* src_points, + const CvMat* dst_points, + CvMat* homography, + int method CV_DEFAULT(0), + double ransacReprojThreshold CV_DEFAULT(3), + CvMat* mask CV_DEFAULT(0), + int maxIters CV_DEFAULT(2000), + double confidence CV_DEFAULT(0.995)); + +/* Computes RQ decomposition for 3x3 matrices */ +CVAPI(void) cvRQDecomp3x3( const CvMat *matrixM, CvMat *matrixR, CvMat *matrixQ, + CvMat *matrixQx CV_DEFAULT(NULL), + CvMat *matrixQy CV_DEFAULT(NULL), + CvMat *matrixQz CV_DEFAULT(NULL), + CvPoint3D64f *eulerAngles CV_DEFAULT(NULL)); + +/* Computes projection matrix decomposition */ +CVAPI(void) cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr, + CvMat *rotMatr, CvMat *posVect, + CvMat *rotMatrX CV_DEFAULT(NULL), + CvMat *rotMatrY CV_DEFAULT(NULL), + CvMat *rotMatrZ CV_DEFAULT(NULL), + CvPoint3D64f *eulerAngles CV_DEFAULT(NULL)); + +/* Computes d(AB)/dA and d(AB)/dB */ +CVAPI(void) cvCalcMatMulDeriv( const CvMat* A, const CvMat* B, CvMat* dABdA, CvMat* dABdB ); + +/* Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)), + t3 = rodrigues(r2)*t1 + t2 and the respective derivatives */ +CVAPI(void) cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1, + const CvMat* _rvec2, const CvMat* _tvec2, + CvMat* _rvec3, CvMat* _tvec3, + CvMat* dr3dr1 CV_DEFAULT(0), CvMat* dr3dt1 CV_DEFAULT(0), + CvMat* dr3dr2 CV_DEFAULT(0), CvMat* dr3dt2 CV_DEFAULT(0), + CvMat* dt3dr1 CV_DEFAULT(0), CvMat* dt3dt1 CV_DEFAULT(0), + CvMat* dt3dr2 CV_DEFAULT(0), CvMat* dt3dt2 CV_DEFAULT(0) ); + +/* Projects object points to the view plane using + the specified extrinsic and intrinsic camera parameters */ +CVAPI(void) cvProjectPoints2( const CvMat* object_points, const CvMat* rotation_vector, + const CvMat* translation_vector, const CvMat* camera_matrix, + const CvMat* distortion_coeffs, CvMat* image_points, + CvMat* dpdrot CV_DEFAULT(NULL), CvMat* dpdt CV_DEFAULT(NULL), + CvMat* dpdf CV_DEFAULT(NULL), CvMat* dpdc CV_DEFAULT(NULL), + CvMat* dpddist CV_DEFAULT(NULL), + double aspect_ratio CV_DEFAULT(0)); + +/* Finds extrinsic camera parameters from + a few known corresponding point pairs and intrinsic parameters */ +CVAPI(void) cvFindExtrinsicCameraParams2( const CvMat* object_points, + const CvMat* image_points, + const CvMat* camera_matrix, + const CvMat* distortion_coeffs, + CvMat* rotation_vector, + CvMat* translation_vector, + int use_extrinsic_guess CV_DEFAULT(0) ); + +/* Computes initial estimate of the intrinsic camera parameters + in case of planar calibration target (e.g. chessboard) */ +CVAPI(void) cvInitIntrinsicParams2D( const CvMat* object_points, + const CvMat* image_points, + const CvMat* npoints, CvSize image_size, + CvMat* camera_matrix, + double aspect_ratio CV_DEFAULT(1.) ); + +#define CV_CALIB_CB_ADAPTIVE_THRESH 1 +#define CV_CALIB_CB_NORMALIZE_IMAGE 2 +#define CV_CALIB_CB_FILTER_QUADS 4 +#define CV_CALIB_CB_FAST_CHECK 8 + +// Performs a fast check if a chessboard is in the input image. This is a workaround to +// a problem of cvFindChessboardCorners being slow on images with no chessboard +// - src: input image +// - size: chessboard size +// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called, +// 0 if there is no chessboard, -1 in case of error +CVAPI(int) cvCheckChessboard(IplImage* src, CvSize size); + + /* Detects corners on a chessboard calibration pattern */ +CVAPI(int) cvFindChessboardCorners( const void* image, CvSize pattern_size, + CvPoint2D32f* corners, + int* corner_count CV_DEFAULT(NULL), + int flags CV_DEFAULT(CV_CALIB_CB_ADAPTIVE_THRESH+CV_CALIB_CB_NORMALIZE_IMAGE) ); + +/* Draws individual chessboard corners or the whole chessboard detected */ +CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size, + CvPoint2D32f* corners, + int count, int pattern_was_found ); + +#define CV_CALIB_USE_INTRINSIC_GUESS 1 +#define CV_CALIB_FIX_ASPECT_RATIO 2 +#define CV_CALIB_FIX_PRINCIPAL_POINT 4 +#define CV_CALIB_ZERO_TANGENT_DIST 8 +#define CV_CALIB_FIX_FOCAL_LENGTH 16 +#define CV_CALIB_FIX_K1 32 +#define CV_CALIB_FIX_K2 64 +#define CV_CALIB_FIX_K3 128 +#define CV_CALIB_FIX_K4 2048 +#define CV_CALIB_FIX_K5 4096 +#define CV_CALIB_FIX_K6 8192 +#define CV_CALIB_RATIONAL_MODEL 16384 +#define CV_CALIB_THIN_PRISM_MODEL 32768 +#define CV_CALIB_FIX_S1_S2_S3_S4 65536 +#define CV_CALIB_TILTED_MODEL 262144 +#define CV_CALIB_FIX_TAUX_TAUY 524288 +#define CV_CALIB_FIX_TANGENT_DIST 2097152 + +#define CV_CALIB_NINTRINSIC 18 + +/* Finds intrinsic and extrinsic camera parameters + from a few views of known calibration pattern */ +CVAPI(double) cvCalibrateCamera2( const CvMat* object_points, + const CvMat* image_points, + const CvMat* point_counts, + CvSize image_size, + CvMat* camera_matrix, + CvMat* distortion_coeffs, + CvMat* rotation_vectors CV_DEFAULT(NULL), + CvMat* translation_vectors CV_DEFAULT(NULL), + int flags CV_DEFAULT(0), + CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria( + CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON)) ); + +/* Computes various useful characteristics of the camera from the data computed by + cvCalibrateCamera2 */ +CVAPI(void) cvCalibrationMatrixValues( const CvMat *camera_matrix, + CvSize image_size, + double aperture_width CV_DEFAULT(0), + double aperture_height CV_DEFAULT(0), + double *fovx CV_DEFAULT(NULL), + double *fovy CV_DEFAULT(NULL), + double *focal_length CV_DEFAULT(NULL), + CvPoint2D64f *principal_point CV_DEFAULT(NULL), + double *pixel_aspect_ratio CV_DEFAULT(NULL)); + +#define CV_CALIB_FIX_INTRINSIC 256 +#define CV_CALIB_SAME_FOCAL_LENGTH 512 + +/* Computes the transformation from one camera coordinate system to another one + from a few correspondent views of the same calibration target. Optionally, calibrates + both cameras */ +CVAPI(double) cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1, + const CvMat* image_points2, const CvMat* npoints, + CvMat* camera_matrix1, CvMat* dist_coeffs1, + CvMat* camera_matrix2, CvMat* dist_coeffs2, + CvSize image_size, CvMat* R, CvMat* T, + CvMat* E CV_DEFAULT(0), CvMat* F CV_DEFAULT(0), + int flags CV_DEFAULT(CV_CALIB_FIX_INTRINSIC), + CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria( + CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6)) ); + +#define CV_CALIB_ZERO_DISPARITY 1024 + +/* Computes 3D rotations (+ optional shift) for each camera coordinate system to make both + views parallel (=> to make all the epipolar lines horizontal or vertical) */ +CVAPI(void) cvStereoRectify( const CvMat* camera_matrix1, const CvMat* camera_matrix2, + const CvMat* dist_coeffs1, const CvMat* dist_coeffs2, + CvSize image_size, const CvMat* R, const CvMat* T, + CvMat* R1, CvMat* R2, CvMat* P1, CvMat* P2, + CvMat* Q CV_DEFAULT(0), + int flags CV_DEFAULT(CV_CALIB_ZERO_DISPARITY), + double alpha CV_DEFAULT(-1), + CvSize new_image_size CV_DEFAULT(cvSize(0,0)), + CvRect* valid_pix_ROI1 CV_DEFAULT(0), + CvRect* valid_pix_ROI2 CV_DEFAULT(0)); + +/* Computes rectification transformations for uncalibrated pair of images using a set + of point correspondences */ +CVAPI(int) cvStereoRectifyUncalibrated( const CvMat* points1, const CvMat* points2, + const CvMat* F, CvSize img_size, + CvMat* H1, CvMat* H2, + double threshold CV_DEFAULT(5)); + + + +/* stereo correspondence parameters and functions */ + +#define CV_STEREO_BM_NORMALIZED_RESPONSE 0 +#define CV_STEREO_BM_XSOBEL 1 + +/* Block matching algorithm structure */ +typedef struct CvStereoBMState +{ + // pre-filtering (normalization of input images) + int preFilterType; // =CV_STEREO_BM_NORMALIZED_RESPONSE now + int preFilterSize; // averaging window size: ~5x5..21x21 + int preFilterCap; // the output of pre-filtering is clipped by [-preFilterCap,preFilterCap] + + // correspondence using Sum of Absolute Difference (SAD) + int SADWindowSize; // ~5x5..21x21 + int minDisparity; // minimum disparity (can be negative) + int numberOfDisparities; // maximum disparity - minimum disparity (> 0) + + // post-filtering + int textureThreshold; // the disparity is only computed for pixels + // with textured enough neighborhood + int uniquenessRatio; // accept the computed disparity d* only if + // SAD(d) >= SAD(d*)*(1 + uniquenessRatio/100.) + // for any d != d*+/-1 within the search range. + int speckleWindowSize; // disparity variation window + int speckleRange; // acceptable range of variation in window + + int trySmallerWindows; // if 1, the results may be more accurate, + // at the expense of slower processing + CvRect roi1, roi2; + int disp12MaxDiff; + + // temporary buffers + CvMat* preFilteredImg0; + CvMat* preFilteredImg1; + CvMat* slidingSumBuf; + CvMat* cost; + CvMat* disp; +} CvStereoBMState; + +#define CV_STEREO_BM_BASIC 0 +#define CV_STEREO_BM_FISH_EYE 1 +#define CV_STEREO_BM_NARROW 2 + +CVAPI(CvStereoBMState*) cvCreateStereoBMState(int preset CV_DEFAULT(CV_STEREO_BM_BASIC), + int numberOfDisparities CV_DEFAULT(0)); + +CVAPI(void) cvReleaseStereoBMState( CvStereoBMState** state ); + +CVAPI(void) cvFindStereoCorrespondenceBM( const CvArr* left, const CvArr* right, + CvArr* disparity, CvStereoBMState* state ); + +CVAPI(CvRect) cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity, + int numberOfDisparities, int SADWindowSize ); + +CVAPI(void) cvValidateDisparity( CvArr* disparity, const CvArr* cost, + int minDisparity, int numberOfDisparities, + int disp12MaxDiff CV_DEFAULT(1) ); + +/* Reprojects the computed disparity image to the 3D space using the specified 4x4 matrix */ +CVAPI(void) cvReprojectImageTo3D( const CvArr* disparityImage, + CvArr* _3dImage, const CvMat* Q, + int handleMissingValues CV_DEFAULT(0) ); + +/** @} calib3d_c */ + +#ifdef __cplusplus +} // extern "C" + +////////////////////////////////////////////////////////////////////////////////////////// +class CV_EXPORTS CvLevMarq +{ +public: + CvLevMarq(); + CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria= + cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON), + bool completeSymmFlag=false ); + ~CvLevMarq(); + void init( int nparams, int nerrs, CvTermCriteria criteria= + cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON), + bool completeSymmFlag=false ); + bool update( const CvMat*& param, CvMat*& J, CvMat*& err ); + bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm ); + + void clear(); + void step(); + enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 }; + + cv::Ptr mask; + cv::Ptr prevParam; + cv::Ptr param; + cv::Ptr J; + cv::Ptr err; + cv::Ptr JtJ; + cv::Ptr JtJN; + cv::Ptr JtErr; + cv::Ptr JtJV; + cv::Ptr JtJW; + double prevErrNorm, errNorm; + int lambdaLg10; + CvTermCriteria criteria; + int state; + int iters; + bool completeSymmFlag; + int solveMethod; +}; + +#endif + +#endif /* OPENCV_CALIB3D_C_H */ diff --git a/3rdparty/opencv/include/opencv2/core.hpp b/3rdparty/opencv/include/opencv2/core.hpp new file mode 100644 index 00000000..089c0db3 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core.hpp @@ -0,0 +1,3285 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2015, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Copyright (C) 2015, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_HPP +#define OPENCV_CORE_HPP + +#ifndef __cplusplus +# error core.hpp header must be compiled as C++ +#endif + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/version.hpp" +#include "opencv2/core/base.hpp" +#include "opencv2/core/cvstd.hpp" +#include "opencv2/core/traits.hpp" +#include "opencv2/core/matx.hpp" +#include "opencv2/core/types.hpp" +#include "opencv2/core/mat.hpp" +#include "opencv2/core/persistence.hpp" + +/** +@defgroup core Core functionality +@{ + @defgroup core_basic Basic structures + @defgroup core_c C structures and operations + @{ + @defgroup core_c_glue Connections with C++ + @} + @defgroup core_array Operations on arrays + @defgroup core_xml XML/YAML Persistence + @defgroup core_cluster Clustering + @defgroup core_utils Utility and system functions and macros + @{ + @defgroup core_utils_sse SSE utilities + @defgroup core_utils_neon NEON utilities + @defgroup core_utils_softfloat Softfloat support + @defgroup core_utils_samples Utility functions for OpenCV samples + @} + @defgroup core_opengl OpenGL interoperability + @defgroup core_ipp Intel IPP Asynchronous C/C++ Converters + @defgroup core_optim Optimization Algorithms + @defgroup core_directx DirectX interoperability + @defgroup core_eigen Eigen support + @defgroup core_opencl OpenCL support + @defgroup core_va_intel Intel VA-API/OpenCL (CL-VA) interoperability + @defgroup core_hal Hardware Acceleration Layer + @{ + @defgroup core_hal_functions Functions + @defgroup core_hal_interface Interface + @defgroup core_hal_intrin Universal intrinsics + @{ + @defgroup core_hal_intrin_impl Private implementation helpers + @} + @} +@} + */ + +namespace cv { + +//! @addtogroup core_utils +//! @{ + +/*! @brief Class passed to an error. + +This class encapsulates all or almost all necessary +information about the error happened in the program. The exception is +usually constructed and thrown implicitly via CV_Error and CV_Error_ macros. +@see error + */ +class CV_EXPORTS Exception : public std::exception +{ +public: + /*! + Default constructor + */ + Exception(); + /*! + Full constructor. Normally the constructor is not called explicitly. + Instead, the macros CV_Error(), CV_Error_() and CV_Assert() are used. + */ + Exception(int _code, const String& _err, const String& _func, const String& _file, int _line); + virtual ~Exception() throw(); + + /*! + \return the error description and the context as a text string. + */ + virtual const char *what() const throw() CV_OVERRIDE; + void formatMessage(); + + String msg; ///< the formatted error message + + int code; ///< error code @see CVStatus + String err; ///< error description + String func; ///< function name. Available only when the compiler supports getting it + String file; ///< source file name where the error has occurred + int line; ///< line number in the source file where the error has occurred +}; + +/*! @brief Signals an error and raises the exception. + +By default the function prints information about the error to stderr, +then it either stops if cv::setBreakOnError() had been called before or raises the exception. +It is possible to alternate error processing by using #redirectError(). +@param exc the exception raisen. +@deprecated drop this version + */ +CV_EXPORTS void error( const Exception& exc ); + +enum SortFlags { SORT_EVERY_ROW = 0, //!< each matrix row is sorted independently + SORT_EVERY_COLUMN = 1, //!< each matrix column is sorted + //!< independently; this flag and the previous one are + //!< mutually exclusive. + SORT_ASCENDING = 0, //!< each matrix row is sorted in the ascending + //!< order. + SORT_DESCENDING = 16 //!< each matrix row is sorted in the + //!< descending order; this flag and the previous one are also + //!< mutually exclusive. + }; + +//! @} core_utils + +//! @addtogroup core +//! @{ + +//! Covariation flags +enum CovarFlags { + /** The output covariance matrix is calculated as: + \f[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...],\f] + The covariance matrix will be nsamples x nsamples. Such an unusual covariance matrix is used + for fast PCA of a set of very large vectors (see, for example, the EigenFaces technique for + face recognition). Eigenvalues of this "scrambled" matrix match the eigenvalues of the true + covariance matrix. The "true" eigenvectors can be easily calculated from the eigenvectors of + the "scrambled" covariance matrix. */ + COVAR_SCRAMBLED = 0, + /**The output covariance matrix is calculated as: + \f[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...] \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T,\f] + covar will be a square matrix of the same size as the total number of elements in each input + vector. One and only one of #COVAR_SCRAMBLED and #COVAR_NORMAL must be specified.*/ + COVAR_NORMAL = 1, + /** If the flag is specified, the function does not calculate mean from + the input vectors but, instead, uses the passed mean vector. This is useful if mean has been + pre-calculated or known in advance, or if the covariance matrix is calculated by parts. In + this case, mean is not a mean vector of the input sub-set of vectors but rather the mean + vector of the whole set.*/ + COVAR_USE_AVG = 2, + /** If the flag is specified, the covariance matrix is scaled. In the + "normal" mode, scale is 1./nsamples . In the "scrambled" mode, scale is the reciprocal of the + total number of elements in each input vector. By default (if the flag is not specified), the + covariance matrix is not scaled ( scale=1 ).*/ + COVAR_SCALE = 4, + /** If the flag is + specified, all the input vectors are stored as rows of the samples matrix. mean should be a + single-row vector in this case.*/ + COVAR_ROWS = 8, + /** If the flag is + specified, all the input vectors are stored as columns of the samples matrix. mean should be a + single-column vector in this case.*/ + COVAR_COLS = 16 +}; + +//! k-Means flags +enum KmeansFlags { + /** Select random initial centers in each attempt.*/ + KMEANS_RANDOM_CENTERS = 0, + /** Use kmeans++ center initialization by Arthur and Vassilvitskii [Arthur2007].*/ + KMEANS_PP_CENTERS = 2, + /** During the first (and possibly the only) attempt, use the + user-supplied labels instead of computing them from the initial centers. For the second and + further attempts, use the random or semi-random centers. Use one of KMEANS_\*_CENTERS flag + to specify the exact method.*/ + KMEANS_USE_INITIAL_LABELS = 1 +}; + +//! type of line +enum LineTypes { + FILLED = -1, + LINE_4 = 4, //!< 4-connected line + LINE_8 = 8, //!< 8-connected line + LINE_AA = 16 //!< antialiased line +}; + +//! Only a subset of Hershey fonts are supported +enum HersheyFonts { + FONT_HERSHEY_SIMPLEX = 0, //!< normal size sans-serif font + FONT_HERSHEY_PLAIN = 1, //!< small size sans-serif font + FONT_HERSHEY_DUPLEX = 2, //!< normal size sans-serif font (more complex than FONT_HERSHEY_SIMPLEX) + FONT_HERSHEY_COMPLEX = 3, //!< normal size serif font + FONT_HERSHEY_TRIPLEX = 4, //!< normal size serif font (more complex than FONT_HERSHEY_COMPLEX) + FONT_HERSHEY_COMPLEX_SMALL = 5, //!< smaller version of FONT_HERSHEY_COMPLEX + FONT_HERSHEY_SCRIPT_SIMPLEX = 6, //!< hand-writing style font + FONT_HERSHEY_SCRIPT_COMPLEX = 7, //!< more complex variant of FONT_HERSHEY_SCRIPT_SIMPLEX + FONT_ITALIC = 16 //!< flag for italic font +}; + +enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/columns of the matrix. + REDUCE_AVG = 1, //!< the output is the mean vector of all rows/columns of the matrix. + REDUCE_MAX = 2, //!< the output is the maximum (column/row-wise) of all rows/columns of the matrix. + REDUCE_MIN = 3 //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix. + }; + + +/** @brief Swaps two matrices +*/ +CV_EXPORTS void swap(Mat& a, Mat& b); +/** @overload */ +CV_EXPORTS void swap( UMat& a, UMat& b ); + +//! @} core + +//! @addtogroup core_array +//! @{ + +/** @brief Computes the source location of an extrapolated pixel. + +The function computes and returns the coordinate of a donor pixel corresponding to the specified +extrapolated pixel when using the specified extrapolation border mode. For example, if you use +cv::BORDER_WRAP mode in the horizontal direction, cv::BORDER_REFLECT_101 in the vertical direction and +want to compute value of the "virtual" pixel Point(-5, 100) in a floating-point image img , it +looks like: +@code{.cpp} + float val = img.at(borderInterpolate(100, img.rows, cv::BORDER_REFLECT_101), + borderInterpolate(-5, img.cols, cv::BORDER_WRAP)); +@endcode +Normally, the function is not called directly. It is used inside filtering functions and also in +copyMakeBorder. +@param p 0-based coordinate of the extrapolated pixel along one of the axes, likely \<0 or \>= len +@param len Length of the array along the corresponding axis. +@param borderType Border type, one of the #BorderTypes, except for #BORDER_TRANSPARENT and +#BORDER_ISOLATED . When borderType==#BORDER_CONSTANT , the function always returns -1, regardless +of p and len. + +@sa copyMakeBorder +*/ +CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType); + +/** @example samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp +An example using copyMakeBorder function. +Check @ref tutorial_copyMakeBorder "the corresponding tutorial" for more details +*/ + +/** @brief Forms a border around an image. + +The function copies the source image into the middle of the destination image. The areas to the +left, to the right, above and below the copied source image will be filled with extrapolated +pixels. This is not what filtering functions based on it do (they extrapolate pixels on-fly), but +what other more complex functions, including your own, may do to simplify image boundary handling. + +The function supports the mode when src is already in the middle of dst . In this case, the +function does not copy src itself but simply constructs the border, for example: + +@code{.cpp} + // let border be the same in all directions + int border=2; + // constructs a larger image to fit both the image and the border + Mat gray_buf(rgb.rows + border*2, rgb.cols + border*2, rgb.depth()); + // select the middle part of it w/o copying data + Mat gray(gray_canvas, Rect(border, border, rgb.cols, rgb.rows)); + // convert image from RGB to grayscale + cvtColor(rgb, gray, COLOR_RGB2GRAY); + // form a border in-place + copyMakeBorder(gray, gray_buf, border, border, + border, border, BORDER_REPLICATE); + // now do some custom filtering ... + ... +@endcode +@note When the source image is a part (ROI) of a bigger image, the function will try to use the +pixels outside of the ROI to form a border. To disable this feature and always do extrapolation, as +if src was not a ROI, use borderType | #BORDER_ISOLATED. + +@param src Source image. +@param dst Destination image of the same type as src and the size Size(src.cols+left+right, +src.rows+top+bottom) . +@param top +@param bottom +@param left +@param right Parameter specifying how many pixels in each direction from the source image rectangle +to extrapolate. For example, top=1, bottom=1, left=1, right=1 mean that 1 pixel-wide border needs +to be built. +@param borderType Border type. See borderInterpolate for details. +@param value Border value if borderType==BORDER_CONSTANT . + +@sa borderInterpolate +*/ +CV_EXPORTS_W void copyMakeBorder(InputArray src, OutputArray dst, + int top, int bottom, int left, int right, + int borderType, const Scalar& value = Scalar() ); + +/** @brief Calculates the per-element sum of two arrays or an array and a scalar. + +The function add calculates: +- Sum of two arrays when both input arrays have the same size and the same number of channels: +\f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1}(I) + \texttt{src2}(I)) \quad \texttt{if mask}(I) \ne0\f] +- Sum of an array and a scalar when src2 is constructed from Scalar or has the same number of +elements as `src1.channels()`: +\f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1}(I) + \texttt{src2} ) \quad \texttt{if mask}(I) \ne0\f] +- Sum of a scalar and an array when src1 is constructed from Scalar or has the same number of +elements as `src2.channels()`: +\f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1} + \texttt{src2}(I) ) \quad \texttt{if mask}(I) \ne0\f] +where `I` is a multi-dimensional index of array elements. In case of multi-channel arrays, each +channel is processed independently. + +The first function in the list above can be replaced with matrix expressions: +@code{.cpp} + dst = src1 + src2; + dst += src1; // equivalent to add(dst, src1, dst); +@endcode +The input arrays and the output array can all have the same or different depths. For example, you +can add a 16-bit unsigned array to a 8-bit signed array and store the sum as a 32-bit +floating-point array. Depth of the output array is determined by the dtype parameter. In the second +and third cases above, as well as in the first case, when src1.depth() == src2.depth(), dtype can +be set to the default -1. In this case, the output array will have the same depth as the input +array, be it src1, src2 or both. +@note Saturation is not applied when the output array has the depth CV_32S. You may even get +result of an incorrect sign in the case of overflow. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array that has the same size and number of channels as the input array(s); the +depth is defined by dtype or src1/src2. +@param mask optional operation mask - 8-bit single channel array, that specifies elements of the +output array to be changed. +@param dtype optional depth of the output array (see the discussion below). +@sa subtract, addWeighted, scaleAdd, Mat::convertTo +*/ +CV_EXPORTS_W void add(InputArray src1, InputArray src2, OutputArray dst, + InputArray mask = noArray(), int dtype = -1); + +/** @brief Calculates the per-element difference between two arrays or array and a scalar. + +The function subtract calculates: +- Difference between two arrays, when both input arrays have the same size and the same number of +channels: + \f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1}(I) - \texttt{src2}(I)) \quad \texttt{if mask}(I) \ne0\f] +- Difference between an array and a scalar, when src2 is constructed from Scalar or has the same +number of elements as `src1.channels()`: + \f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1}(I) - \texttt{src2} ) \quad \texttt{if mask}(I) \ne0\f] +- Difference between a scalar and an array, when src1 is constructed from Scalar or has the same +number of elements as `src2.channels()`: + \f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src1} - \texttt{src2}(I) ) \quad \texttt{if mask}(I) \ne0\f] +- The reverse difference between a scalar and an array in the case of `SubRS`: + \f[\texttt{dst}(I) = \texttt{saturate} ( \texttt{src2} - \texttt{src1}(I) ) \quad \texttt{if mask}(I) \ne0\f] +where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each +channel is processed independently. + +The first function in the list above can be replaced with matrix expressions: +@code{.cpp} + dst = src1 - src2; + dst -= src1; // equivalent to subtract(dst, src1, dst); +@endcode +The input arrays and the output array can all have the same or different depths. For example, you +can subtract to 8-bit unsigned arrays and store the difference in a 16-bit signed array. Depth of +the output array is determined by dtype parameter. In the second and third cases above, as well as +in the first case, when src1.depth() == src2.depth(), dtype can be set to the default -1. In this +case the output array will have the same depth as the input array, be it src1, src2 or both. +@note Saturation is not applied when the output array has the depth CV_32S. You may even get +result of an incorrect sign in the case of overflow. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array of the same size and the same number of channels as the input array. +@param mask optional operation mask; this is an 8-bit single channel array that specifies elements +of the output array to be changed. +@param dtype optional depth of the output array +@sa add, addWeighted, scaleAdd, Mat::convertTo + */ +CV_EXPORTS_W void subtract(InputArray src1, InputArray src2, OutputArray dst, + InputArray mask = noArray(), int dtype = -1); + + +/** @brief Calculates the per-element scaled product of two arrays. + +The function multiply calculates the per-element product of two arrays: + +\f[\texttt{dst} (I)= \texttt{saturate} ( \texttt{scale} \cdot \texttt{src1} (I) \cdot \texttt{src2} (I))\f] + +There is also a @ref MatrixExpressions -friendly variant of the first function. See Mat::mul . + +For a not-per-element matrix product, see gemm . + +@note Saturation is not applied when the output array has the depth +CV_32S. You may even get result of an incorrect sign in the case of +overflow. +@param src1 first input array. +@param src2 second input array of the same size and the same type as src1. +@param dst output array of the same size and type as src1. +@param scale optional scale factor. +@param dtype optional depth of the output array +@sa add, subtract, divide, scaleAdd, addWeighted, accumulate, accumulateProduct, accumulateSquare, +Mat::convertTo +*/ +CV_EXPORTS_W void multiply(InputArray src1, InputArray src2, + OutputArray dst, double scale = 1, int dtype = -1); + +/** @brief Performs per-element division of two arrays or a scalar by an array. + +The function cv::divide divides one array by another: +\f[\texttt{dst(I) = saturate(src1(I)*scale/src2(I))}\f] +or a scalar by an array when there is no src1 : +\f[\texttt{dst(I) = saturate(scale/src2(I))}\f] + +When src2(I) is zero, dst(I) will also be zero. Different channels of +multi-channel arrays are processed independently. + +@note Saturation is not applied when the output array has the depth CV_32S. You may even get +result of an incorrect sign in the case of overflow. +@param src1 first input array. +@param src2 second input array of the same size and type as src1. +@param scale scalar factor. +@param dst output array of the same size and type as src2. +@param dtype optional depth of the output array; if -1, dst will have depth src2.depth(), but in +case of an array-by-array division, you can only pass -1 when src1.depth()==src2.depth(). +@sa multiply, add, subtract +*/ +CV_EXPORTS_W void divide(InputArray src1, InputArray src2, OutputArray dst, + double scale = 1, int dtype = -1); + +/** @overload */ +CV_EXPORTS_W void divide(double scale, InputArray src2, + OutputArray dst, int dtype = -1); + +/** @brief Calculates the sum of a scaled array and another array. + +The function scaleAdd is one of the classical primitive linear algebra operations, known as DAXPY +or SAXPY in [BLAS](http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms). It calculates +the sum of a scaled array and another array: +\f[\texttt{dst} (I)= \texttt{scale} \cdot \texttt{src1} (I) + \texttt{src2} (I)\f] +The function can also be emulated with a matrix expression, for example: +@code{.cpp} + Mat A(3, 3, CV_64F); + ... + A.row(0) = A.row(1)*2 + A.row(2); +@endcode +@param src1 first input array. +@param alpha scale factor for the first array. +@param src2 second input array of the same size and type as src1. +@param dst output array of the same size and type as src1. +@sa add, addWeighted, subtract, Mat::dot, Mat::convertTo +*/ +CV_EXPORTS_W void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst); + +/** @example samples/cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp +Check @ref tutorial_trackbar "the corresponding tutorial" for more details +*/ + +/** @brief Calculates the weighted sum of two arrays. + +The function addWeighted calculates the weighted sum of two arrays as follows: +\f[\texttt{dst} (I)= \texttt{saturate} ( \texttt{src1} (I)* \texttt{alpha} + \texttt{src2} (I)* \texttt{beta} + \texttt{gamma} )\f] +where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each +channel is processed independently. +The function can be replaced with a matrix expression: +@code{.cpp} + dst = src1*alpha + src2*beta + gamma; +@endcode +@note Saturation is not applied when the output array has the depth CV_32S. You may even get +result of an incorrect sign in the case of overflow. +@param src1 first input array. +@param alpha weight of the first array elements. +@param src2 second input array of the same size and channel number as src1. +@param beta weight of the second array elements. +@param gamma scalar added to each sum. +@param dst output array that has the same size and number of channels as the input arrays. +@param dtype optional depth of the output array; when both input arrays have the same depth, dtype +can be set to -1, which will be equivalent to src1.depth(). +@sa add, subtract, scaleAdd, Mat::convertTo +*/ +CV_EXPORTS_W void addWeighted(InputArray src1, double alpha, InputArray src2, + double beta, double gamma, OutputArray dst, int dtype = -1); + +/** @brief Scales, calculates absolute values, and converts the result to 8-bit. + +On each element of the input array, the function convertScaleAbs +performs three operations sequentially: scaling, taking an absolute +value, conversion to an unsigned 8-bit type: +\f[\texttt{dst} (I)= \texttt{saturate\_cast} (| \texttt{src} (I)* \texttt{alpha} + \texttt{beta} |)\f] +In case of multi-channel arrays, the function processes each channel +independently. When the output is not 8-bit, the operation can be +emulated by calling the Mat::convertTo method (or by using matrix +expressions) and then by calculating an absolute value of the result. +For example: +@code{.cpp} + Mat_ A(30,30); + randu(A, Scalar(-100), Scalar(100)); + Mat_ B = A*5 + 3; + B = abs(B); + // Mat_ B = abs(A*5+3) will also do the job, + // but it will allocate a temporary matrix +@endcode +@param src input array. +@param dst output array. +@param alpha optional scale factor. +@param beta optional delta added to the scaled values. +@sa Mat::convertTo, cv::abs(const Mat&) +*/ +CV_EXPORTS_W void convertScaleAbs(InputArray src, OutputArray dst, + double alpha = 1, double beta = 0); + +/** @brief Converts an array to half precision floating number. + +This function converts FP32 (single precision floating point) from/to FP16 (half precision floating point). CV_16S format is used to represent FP16 data. +There are two use modes (src -> dst): CV_32F -> CV_16S and CV_16S -> CV_32F. The input array has to have type of CV_32F or +CV_16S to represent the bit depth. If the input array is neither of them, the function will raise an error. +The format of half precision floating point is defined in IEEE 754-2008. + +@param src input array. +@param dst output array. +*/ +CV_EXPORTS_W void convertFp16(InputArray src, OutputArray dst); + +/** @brief Performs a look-up table transform of an array. + +The function LUT fills the output array with values from the look-up table. Indices of the entries +are taken from the input array. That is, the function processes each element of src as follows: +\f[\texttt{dst} (I) \leftarrow \texttt{lut(src(I) + d)}\f] +where +\f[d = \fork{0}{if \(\texttt{src}\) has depth \(\texttt{CV_8U}\)}{128}{if \(\texttt{src}\) has depth \(\texttt{CV_8S}\)}\f] +@param src input array of 8-bit elements. +@param lut look-up table of 256 elements; in case of multi-channel input array, the table should +either have a single channel (in this case the same table is used for all channels) or the same +number of channels as in the input array. +@param dst output array of the same size and number of channels as src, and the same depth as lut. +@sa convertScaleAbs, Mat::convertTo +*/ +CV_EXPORTS_W void LUT(InputArray src, InputArray lut, OutputArray dst); + +/** @brief Calculates the sum of array elements. + +The function cv::sum calculates and returns the sum of array elements, +independently for each channel. +@param src input array that must have from 1 to 4 channels. +@sa countNonZero, mean, meanStdDev, norm, minMaxLoc, reduce +*/ +CV_EXPORTS_AS(sumElems) Scalar sum(InputArray src); + +/** @brief Counts non-zero array elements. + +The function returns the number of non-zero elements in src : +\f[\sum _{I: \; \texttt{src} (I) \ne0 } 1\f] +@param src single-channel array. +@sa mean, meanStdDev, norm, minMaxLoc, calcCovarMatrix +*/ +CV_EXPORTS_W int countNonZero( InputArray src ); + +/** @brief Returns the list of locations of non-zero pixels + +Given a binary matrix (likely returned from an operation such +as threshold(), compare(), >, ==, etc, return all of +the non-zero indices as a cv::Mat or std::vector (x,y) +For example: +@code{.cpp} + cv::Mat binaryImage; // input, binary image + cv::Mat locations; // output, locations of non-zero pixels + cv::findNonZero(binaryImage, locations); + + // access pixel coordinates + Point pnt = locations.at(i); +@endcode +or +@code{.cpp} + cv::Mat binaryImage; // input, binary image + vector locations; // output, locations of non-zero pixels + cv::findNonZero(binaryImage, locations); + + // access pixel coordinates + Point pnt = locations[i]; +@endcode +@param src single-channel array (type CV_8UC1) +@param idx the output array, type of cv::Mat or std::vector, corresponding to non-zero indices in the input +*/ +CV_EXPORTS_W void findNonZero( InputArray src, OutputArray idx ); + +/** @brief Calculates an average (mean) of array elements. + +The function cv::mean calculates the mean value M of array elements, +independently for each channel, and return it: +\f[\begin{array}{l} N = \sum _{I: \; \texttt{mask} (I) \ne 0} 1 \\ M_c = \left ( \sum _{I: \; \texttt{mask} (I) \ne 0}{ \texttt{mtx} (I)_c} \right )/N \end{array}\f] +When all the mask elements are 0's, the function returns Scalar::all(0) +@param src input array that should have from 1 to 4 channels so that the result can be stored in +Scalar_ . +@param mask optional operation mask. +@sa countNonZero, meanStdDev, norm, minMaxLoc +*/ +CV_EXPORTS_W Scalar mean(InputArray src, InputArray mask = noArray()); + +/** Calculates a mean and standard deviation of array elements. + +The function cv::meanStdDev calculates the mean and the standard deviation M +of array elements independently for each channel and returns it via the +output parameters: +\f[\begin{array}{l} N = \sum _{I, \texttt{mask} (I) \ne 0} 1 \\ \texttt{mean} _c = \frac{\sum_{ I: \; \texttt{mask}(I) \ne 0} \texttt{src} (I)_c}{N} \\ \texttt{stddev} _c = \sqrt{\frac{\sum_{ I: \; \texttt{mask}(I) \ne 0} \left ( \texttt{src} (I)_c - \texttt{mean} _c \right )^2}{N}} \end{array}\f] +When all the mask elements are 0's, the function returns +mean=stddev=Scalar::all(0). +@note The calculated standard deviation is only the diagonal of the +complete normalized covariance matrix. If the full matrix is needed, you +can reshape the multi-channel array M x N to the single-channel array +M\*N x mtx.channels() (only possible when the matrix is continuous) and +then pass the matrix to calcCovarMatrix . +@param src input array that should have from 1 to 4 channels so that the results can be stored in +Scalar_ 's. +@param mean output parameter: calculated mean value. +@param stddev output parameter: calculated standard deviation. +@param mask optional operation mask. +@sa countNonZero, mean, norm, minMaxLoc, calcCovarMatrix +*/ +CV_EXPORTS_W void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev, + InputArray mask=noArray()); + +/** @brief Calculates the absolute norm of an array. + +This version of #norm calculates the absolute norm of src1. The type of norm to calculate is specified using #NormTypes. + +As example for one array consider the function \f$r(x)= \begin{pmatrix} x \\ 1-x \end{pmatrix}, x \in [-1;1]\f$. +The \f$ L_{1}, L_{2} \f$ and \f$ L_{\infty} \f$ norm for the sample value \f$r(-1) = \begin{pmatrix} -1 \\ 2 \end{pmatrix}\f$ +is calculated as follows +\f{align*} + \| r(-1) \|_{L_1} &= |-1| + |2| = 3 \\ + \| r(-1) \|_{L_2} &= \sqrt{(-1)^{2} + (2)^{2}} = \sqrt{5} \\ + \| r(-1) \|_{L_\infty} &= \max(|-1|,|2|) = 2 +\f} +and for \f$r(0.5) = \begin{pmatrix} 0.5 \\ 0.5 \end{pmatrix}\f$ the calculation is +\f{align*} + \| r(0.5) \|_{L_1} &= |0.5| + |0.5| = 1 \\ + \| r(0.5) \|_{L_2} &= \sqrt{(0.5)^{2} + (0.5)^{2}} = \sqrt{0.5} \\ + \| r(0.5) \|_{L_\infty} &= \max(|0.5|,|0.5|) = 0.5. +\f} +The following graphic shows all values for the three norm functions \f$\| r(x) \|_{L_1}, \| r(x) \|_{L_2}\f$ and \f$\| r(x) \|_{L_\infty}\f$. +It is notable that the \f$ L_{1} \f$ norm forms the upper and the \f$ L_{\infty} \f$ norm forms the lower border for the example function \f$ r(x) \f$. +![Graphs for the different norm functions from the above example](pics/NormTypes_OneArray_1-2-INF.png) + +When the mask parameter is specified and it is not empty, the norm is + +If normType is not specified, #NORM_L2 is used. +calculated only over the region specified by the mask. + +Multi-channel input arrays are treated as single-channel arrays, that is, +the results for all channels are combined. + +Hamming norms can only be calculated with CV_8U depth arrays. + +@param src1 first input array. +@param normType type of the norm (see #NormTypes). +@param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type. +*/ +CV_EXPORTS_W double norm(InputArray src1, int normType = NORM_L2, InputArray mask = noArray()); + +/** @brief Calculates an absolute difference norm or a relative difference norm. + +This version of cv::norm calculates the absolute difference norm +or the relative difference norm of arrays src1 and src2. +The type of norm to calculate is specified using #NormTypes. + +@param src1 first input array. +@param src2 second input array of the same size and the same type as src1. +@param normType type of the norm (see #NormTypes). +@param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type. +*/ +CV_EXPORTS_W double norm(InputArray src1, InputArray src2, + int normType = NORM_L2, InputArray mask = noArray()); +/** @overload +@param src first input array. +@param normType type of the norm (see #NormTypes). +*/ +CV_EXPORTS double norm( const SparseMat& src, int normType ); + +/** @brief Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric. + +This function calculates the Peak Signal-to-Noise Ratio (PSNR) image quality metric in decibels (dB), between two input arrays src1 and src2. Arrays must have depth CV_8U. + +The PSNR is calculated as follows: + +\f[ +\texttt{PSNR} = 10 \cdot \log_{10}{\left( \frac{R^2}{MSE} \right) } +\f] + +where R is the maximum integer value of depth CV_8U (255) and MSE is the mean squared error between the two arrays. + +@param src1 first input array. +@param src2 second input array of the same size as src1. + + */ +CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2); + +/** @brief naive nearest neighbor finder + +see http://en.wikipedia.org/wiki/Nearest_neighbor_search +@todo document + */ +CV_EXPORTS_W void batchDistance(InputArray src1, InputArray src2, + OutputArray dist, int dtype, OutputArray nidx, + int normType = NORM_L2, int K = 0, + InputArray mask = noArray(), int update = 0, + bool crosscheck = false); + +/** @brief Normalizes the norm or value range of an array. + +The function cv::normalize normalizes scale and shift the input array elements so that +\f[\| \texttt{dst} \| _{L_p}= \texttt{alpha}\f] +(where p=Inf, 1 or 2) when normType=NORM_INF, NORM_L1, or NORM_L2, respectively; or so that +\f[\min _I \texttt{dst} (I)= \texttt{alpha} , \, \, \max _I \texttt{dst} (I)= \texttt{beta}\f] + +when normType=NORM_MINMAX (for dense arrays only). The optional mask specifies a sub-array to be +normalized. This means that the norm or min-n-max are calculated over the sub-array, and then this +sub-array is modified to be normalized. If you want to only use the mask to calculate the norm or +min-max but modify the whole array, you can use norm and Mat::convertTo. + +In case of sparse matrices, only the non-zero values are analyzed and transformed. Because of this, +the range transformation for sparse matrices is not allowed since it can shift the zero level. + +Possible usage with some positive example data: +@code{.cpp} + vector positiveData = { 2.0, 8.0, 10.0 }; + vector normalizedData_l1, normalizedData_l2, normalizedData_inf, normalizedData_minmax; + + // Norm to probability (total count) + // sum(numbers) = 20.0 + // 2.0 0.1 (2.0/20.0) + // 8.0 0.4 (8.0/20.0) + // 10.0 0.5 (10.0/20.0) + normalize(positiveData, normalizedData_l1, 1.0, 0.0, NORM_L1); + + // Norm to unit vector: ||positiveData|| = 1.0 + // 2.0 0.15 + // 8.0 0.62 + // 10.0 0.77 + normalize(positiveData, normalizedData_l2, 1.0, 0.0, NORM_L2); + + // Norm to max element + // 2.0 0.2 (2.0/10.0) + // 8.0 0.8 (8.0/10.0) + // 10.0 1.0 (10.0/10.0) + normalize(positiveData, normalizedData_inf, 1.0, 0.0, NORM_INF); + + // Norm to range [0.0;1.0] + // 2.0 0.0 (shift to left border) + // 8.0 0.75 (6.0/8.0) + // 10.0 1.0 (shift to right border) + normalize(positiveData, normalizedData_minmax, 1.0, 0.0, NORM_MINMAX); +@endcode + +@param src input array. +@param dst output array of the same size as src . +@param alpha norm value to normalize to or the lower range boundary in case of the range +normalization. +@param beta upper range boundary in case of the range normalization; it is not used for the norm +normalization. +@param norm_type normalization type (see cv::NormTypes). +@param dtype when negative, the output array has the same type as src; otherwise, it has the same +number of channels as src and the depth =CV_MAT_DEPTH(dtype). +@param mask optional operation mask. +@sa norm, Mat::convertTo, SparseMat::convertTo +*/ +CV_EXPORTS_W void normalize( InputArray src, InputOutputArray dst, double alpha = 1, double beta = 0, + int norm_type = NORM_L2, int dtype = -1, InputArray mask = noArray()); + +/** @overload +@param src input array. +@param dst output array of the same size as src . +@param alpha norm value to normalize to or the lower range boundary in case of the range +normalization. +@param normType normalization type (see cv::NormTypes). +*/ +CV_EXPORTS void normalize( const SparseMat& src, SparseMat& dst, double alpha, int normType ); + +/** @brief Finds the global minimum and maximum in an array. + +The function cv::minMaxLoc finds the minimum and maximum element values and their positions. The +extremums are searched across the whole array or, if mask is not an empty array, in the specified +array region. + +The function do not work with multi-channel arrays. If you need to find minimum or maximum +elements across all the channels, use Mat::reshape first to reinterpret the array as +single-channel. Or you may extract the particular channel using either extractImageCOI , or +mixChannels , or split . +@param src input single-channel array. +@param minVal pointer to the returned minimum value; NULL is used if not required. +@param maxVal pointer to the returned maximum value; NULL is used if not required. +@param minLoc pointer to the returned minimum location (in 2D case); NULL is used if not required. +@param maxLoc pointer to the returned maximum location (in 2D case); NULL is used if not required. +@param mask optional mask used to select a sub-array. +@sa max, min, compare, inRange, extractImageCOI, mixChannels, split, Mat::reshape +*/ +CV_EXPORTS_W void minMaxLoc(InputArray src, CV_OUT double* minVal, + CV_OUT double* maxVal = 0, CV_OUT Point* minLoc = 0, + CV_OUT Point* maxLoc = 0, InputArray mask = noArray()); + + +/** @brief Finds the global minimum and maximum in an array + +The function cv::minMaxIdx finds the minimum and maximum element values and their positions. The +extremums are searched across the whole array or, if mask is not an empty array, in the specified +array region. The function does not work with multi-channel arrays. If you need to find minimum or +maximum elements across all the channels, use Mat::reshape first to reinterpret the array as +single-channel. Or you may extract the particular channel using either extractImageCOI , or +mixChannels , or split . In case of a sparse matrix, the minimum is found among non-zero elements +only. +@note When minIdx is not NULL, it must have at least 2 elements (as well as maxIdx), even if src is +a single-row or single-column matrix. In OpenCV (following MATLAB) each array has at least 2 +dimensions, i.e. single-column matrix is Mx1 matrix (and therefore minIdx/maxIdx will be +(i1,0)/(i2,0)) and single-row matrix is 1xN matrix (and therefore minIdx/maxIdx will be +(0,j1)/(0,j2)). +@param src input single-channel array. +@param minVal pointer to the returned minimum value; NULL is used if not required. +@param maxVal pointer to the returned maximum value; NULL is used if not required. +@param minIdx pointer to the returned minimum location (in nD case); NULL is used if not required; +Otherwise, it must point to an array of src.dims elements, the coordinates of the minimum element +in each dimension are stored there sequentially. +@param maxIdx pointer to the returned maximum location (in nD case). NULL is used if not required. +@param mask specified array region +*/ +CV_EXPORTS void minMaxIdx(InputArray src, double* minVal, double* maxVal = 0, + int* minIdx = 0, int* maxIdx = 0, InputArray mask = noArray()); + +/** @overload +@param a input single-channel array. +@param minVal pointer to the returned minimum value; NULL is used if not required. +@param maxVal pointer to the returned maximum value; NULL is used if not required. +@param minIdx pointer to the returned minimum location (in nD case); NULL is used if not required; +Otherwise, it must point to an array of src.dims elements, the coordinates of the minimum element +in each dimension are stored there sequentially. +@param maxIdx pointer to the returned maximum location (in nD case). NULL is used if not required. +*/ +CV_EXPORTS void minMaxLoc(const SparseMat& a, double* minVal, + double* maxVal, int* minIdx = 0, int* maxIdx = 0); + +/** @brief Reduces a matrix to a vector. + +The function #reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of +1D vectors and performing the specified operation on the vectors until a single row/column is +obtained. For example, the function can be used to compute horizontal and vertical projections of a +raster image. In case of #REDUCE_MAX and #REDUCE_MIN , the output image should have the same type as the source one. +In case of #REDUCE_SUM and #REDUCE_AVG , the output may have a larger element bit-depth to preserve accuracy. +And multi-channel arrays are also supported in these two reduction modes. + +The following code demonstrates its usage for a single channel matrix. +@snippet snippets/core_reduce.cpp example + +And the following code demonstrates its usage for a two-channel matrix. +@snippet snippets/core_reduce.cpp example2 + +@param src input 2D matrix. +@param dst output vector. Its size and type is defined by dim and dtype parameters. +@param dim dimension index along which the matrix is reduced. 0 means that the matrix is reduced to +a single row. 1 means that the matrix is reduced to a single column. +@param rtype reduction operation that could be one of #ReduceTypes +@param dtype when negative, the output vector will have the same type as the input matrix, +otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()). +@sa repeat +*/ +CV_EXPORTS_W void reduce(InputArray src, OutputArray dst, int dim, int rtype, int dtype = -1); + +/** @brief Creates one multi-channel array out of several single-channel ones. + +The function cv::merge merges several arrays to make a single multi-channel array. That is, each +element of the output array will be a concatenation of the elements of the input arrays, where +elements of i-th input array are treated as mv[i].channels()-element vectors. + +The function cv::split does the reverse operation. If you need to shuffle channels in some other +advanced way, use cv::mixChannels. + +The following example shows how to merge 3 single channel matrices into a single 3-channel matrix. +@snippet snippets/core_merge.cpp example + +@param mv input array of matrices to be merged; all the matrices in mv must have the same +size and the same depth. +@param count number of input matrices when mv is a plain C array; it must be greater than zero. +@param dst output array of the same size and the same depth as mv[0]; The number of channels will +be equal to the parameter count. +@sa mixChannels, split, Mat::reshape +*/ +CV_EXPORTS void merge(const Mat* mv, size_t count, OutputArray dst); + +/** @overload +@param mv input vector of matrices to be merged; all the matrices in mv must have the same +size and the same depth. +@param dst output array of the same size and the same depth as mv[0]; The number of channels will +be the total number of channels in the matrix array. + */ +CV_EXPORTS_W void merge(InputArrayOfArrays mv, OutputArray dst); + +/** @brief Divides a multi-channel array into several single-channel arrays. + +The function cv::split splits a multi-channel array into separate single-channel arrays: +\f[\texttt{mv} [c](I) = \texttt{src} (I)_c\f] +If you need to extract a single channel or do some other sophisticated channel permutation, use +mixChannels . + +The following example demonstrates how to split a 3-channel matrix into 3 single channel matrices. +@snippet snippets/core_split.cpp example + +@param src input multi-channel array. +@param mvbegin output array; the number of arrays must match src.channels(); the arrays themselves are +reallocated, if needed. +@sa merge, mixChannels, cvtColor +*/ +CV_EXPORTS void split(const Mat& src, Mat* mvbegin); + +/** @overload +@param m input multi-channel array. +@param mv output vector of arrays; the arrays themselves are reallocated, if needed. +*/ +CV_EXPORTS_W void split(InputArray m, OutputArrayOfArrays mv); + +/** @brief Copies specified channels from input arrays to the specified channels of +output arrays. + +The function cv::mixChannels provides an advanced mechanism for shuffling image channels. + +cv::split,cv::merge,cv::extractChannel,cv::insertChannel and some forms of cv::cvtColor are partial cases of cv::mixChannels. + +In the example below, the code splits a 4-channel BGRA image into a 3-channel BGR (with B and R +channels swapped) and a separate alpha-channel image: +@code{.cpp} + Mat bgra( 100, 100, CV_8UC4, Scalar(255,0,0,255) ); + Mat bgr( bgra.rows, bgra.cols, CV_8UC3 ); + Mat alpha( bgra.rows, bgra.cols, CV_8UC1 ); + + // forming an array of matrices is a quite efficient operation, + // because the matrix data is not copied, only the headers + Mat out[] = { bgr, alpha }; + // bgra[0] -> bgr[2], bgra[1] -> bgr[1], + // bgra[2] -> bgr[0], bgra[3] -> alpha[0] + int from_to[] = { 0,2, 1,1, 2,0, 3,3 }; + mixChannels( &bgra, 1, out, 2, from_to, 4 ); +@endcode +@note Unlike many other new-style C++ functions in OpenCV (see the introduction section and +Mat::create ), cv::mixChannels requires the output arrays to be pre-allocated before calling the +function. +@param src input array or vector of matrices; all of the matrices must have the same size and the +same depth. +@param nsrcs number of matrices in `src`. +@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and +depth must be the same as in `src[0]`. +@param ndsts number of matrices in `dst`. +@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is +a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in +dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to +src[0].channels()-1, the second input image channels are indexed from src[0].channels() to +src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image +channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is +filled with zero . +@param npairs number of index pairs in `fromTo`. +@sa split, merge, extractChannel, insertChannel, cvtColor +*/ +CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts, + const int* fromTo, size_t npairs); + +/** @overload +@param src input array or vector of matrices; all of the matrices must have the same size and the +same depth. +@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and +depth must be the same as in src[0]. +@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is +a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in +dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to +src[0].channels()-1, the second input image channels are indexed from src[0].channels() to +src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image +channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is +filled with zero . +@param npairs number of index pairs in fromTo. +*/ +CV_EXPORTS void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst, + const int* fromTo, size_t npairs); + +/** @overload +@param src input array or vector of matrices; all of the matrices must have the same size and the +same depth. +@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and +depth must be the same as in src[0]. +@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is +a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in +dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to +src[0].channels()-1, the second input image channels are indexed from src[0].channels() to +src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image +channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is +filled with zero . +*/ +CV_EXPORTS_W void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst, + const std::vector& fromTo); + +/** @brief Extracts a single channel from src (coi is 0-based index) +@param src input array +@param dst output array +@param coi index of channel to extract +@sa mixChannels, split +*/ +CV_EXPORTS_W void extractChannel(InputArray src, OutputArray dst, int coi); + +/** @brief Inserts a single channel to dst (coi is 0-based index) +@param src input array +@param dst output array +@param coi index of channel for insertion +@sa mixChannels, merge +*/ +CV_EXPORTS_W void insertChannel(InputArray src, InputOutputArray dst, int coi); + +/** @brief Flips a 2D array around vertical, horizontal, or both axes. + +The function cv::flip flips the array in one of three different ways (row +and column indices are 0-based): +\f[\texttt{dst} _{ij} = +\left\{ +\begin{array}{l l} +\texttt{src} _{\texttt{src.rows}-i-1,j} & if\; \texttt{flipCode} = 0 \\ +\texttt{src} _{i, \texttt{src.cols} -j-1} & if\; \texttt{flipCode} > 0 \\ +\texttt{src} _{ \texttt{src.rows} -i-1, \texttt{src.cols} -j-1} & if\; \texttt{flipCode} < 0 \\ +\end{array} +\right.\f] +The example scenarios of using the function are the following: +* Vertical flipping of the image (flipCode == 0) to switch between + top-left and bottom-left image origin. This is a typical operation + in video processing on Microsoft Windows\* OS. +* Horizontal flipping of the image with the subsequent horizontal + shift and absolute difference calculation to check for a + vertical-axis symmetry (flipCode \> 0). +* Simultaneous horizontal and vertical flipping of the image with + the subsequent shift and absolute difference calculation to check + for a central symmetry (flipCode \< 0). +* Reversing the order of point arrays (flipCode \> 0 or + flipCode == 0). +@param src input array. +@param dst output array of the same size and type as src. +@param flipCode a flag to specify how to flip the array; 0 means +flipping around the x-axis and positive value (for example, 1) means +flipping around y-axis. Negative value (for example, -1) means flipping +around both axes. +@sa transpose , repeat , completeSymm +*/ +CV_EXPORTS_W void flip(InputArray src, OutputArray dst, int flipCode); + +enum RotateFlags { + ROTATE_90_CLOCKWISE = 0, //! A = (cv::Mat_(3, 2) << 1, 4, + 2, 5, + 3, 6); + cv::Mat_ B = (cv::Mat_(3, 2) << 7, 10, + 8, 11, + 9, 12); + + cv::Mat C; + cv::hconcat(A, B, C); + //C: + //[1, 4, 7, 10; + // 2, 5, 8, 11; + // 3, 6, 9, 12] + @endcode + @param src1 first input array to be considered for horizontal concatenation. + @param src2 second input array to be considered for horizontal concatenation. + @param dst output array. It has the same number of rows and depth as the src1 and src2, and the sum of cols of the src1 and src2. + */ +CV_EXPORTS void hconcat(InputArray src1, InputArray src2, OutputArray dst); +/** @overload + @code{.cpp} + std::vector matrices = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)), + cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)), + cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),}; + + cv::Mat out; + cv::hconcat( matrices, out ); + //out: + //[1, 2, 3; + // 1, 2, 3; + // 1, 2, 3; + // 1, 2, 3] + @endcode + @param src input array or vector of matrices. all of the matrices must have the same number of rows and the same depth. + @param dst output array. It has the same number of rows and depth as the src, and the sum of cols of the src. +same depth. + */ +CV_EXPORTS_W void hconcat(InputArrayOfArrays src, OutputArray dst); + +/** @brief Applies vertical concatenation to given matrices. + +The function vertically concatenates two or more cv::Mat matrices (with the same number of cols). +@code{.cpp} + cv::Mat matArray[] = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)), + cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)), + cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),}; + + cv::Mat out; + cv::vconcat( matArray, 3, out ); + //out: + //[1, 1, 1, 1; + // 2, 2, 2, 2; + // 3, 3, 3, 3] +@endcode +@param src input array or vector of matrices. all of the matrices must have the same number of cols and the same depth. +@param nsrc number of matrices in src. +@param dst output array. It has the same number of cols and depth as the src, and the sum of rows of the src. +@sa cv::hconcat(const Mat*, size_t, OutputArray), @sa cv::hconcat(InputArrayOfArrays, OutputArray) and @sa cv::hconcat(InputArray, InputArray, OutputArray) +*/ +CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, OutputArray dst); +/** @overload + @code{.cpp} + cv::Mat_ A = (cv::Mat_(3, 2) << 1, 7, + 2, 8, + 3, 9); + cv::Mat_ B = (cv::Mat_(3, 2) << 4, 10, + 5, 11, + 6, 12); + + cv::Mat C; + cv::vconcat(A, B, C); + //C: + //[1, 7; + // 2, 8; + // 3, 9; + // 4, 10; + // 5, 11; + // 6, 12] + @endcode + @param src1 first input array to be considered for vertical concatenation. + @param src2 second input array to be considered for vertical concatenation. + @param dst output array. It has the same number of cols and depth as the src1 and src2, and the sum of rows of the src1 and src2. + */ +CV_EXPORTS void vconcat(InputArray src1, InputArray src2, OutputArray dst); +/** @overload + @code{.cpp} + std::vector matrices = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)), + cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)), + cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),}; + + cv::Mat out; + cv::vconcat( matrices, out ); + //out: + //[1, 1, 1, 1; + // 2, 2, 2, 2; + // 3, 3, 3, 3] + @endcode + @param src input array or vector of matrices. all of the matrices must have the same number of cols and the same depth + @param dst output array. It has the same number of cols and depth as the src, and the sum of rows of the src. +same depth. + */ +CV_EXPORTS_W void vconcat(InputArrayOfArrays src, OutputArray dst); + +/** @brief computes bitwise conjunction of the two arrays (dst = src1 & src2) +Calculates the per-element bit-wise conjunction of two arrays or an +array and a scalar. + +The function cv::bitwise_and calculates the per-element bit-wise logical conjunction for: +* Two arrays when src1 and src2 have the same size: + \f[\texttt{dst} (I) = \texttt{src1} (I) \wedge \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +* An array and a scalar when src2 is constructed from Scalar or has + the same number of elements as `src1.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} (I) \wedge \texttt{src2} \quad \texttt{if mask} (I) \ne0\f] +* A scalar and an array when src1 is constructed from Scalar or has + the same number of elements as `src2.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} \wedge \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +In case of floating-point arrays, their machine-specific bit +representations (usually IEEE754-compliant) are used for the operation. +In case of multi-channel arrays, each channel is processed +independently. In the second and third cases above, the scalar is first +converted to the array type. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array that has the same size and type as the input +arrays. +@param mask optional operation mask, 8-bit single channel array, that +specifies elements of the output array to be changed. +*/ +CV_EXPORTS_W void bitwise_and(InputArray src1, InputArray src2, + OutputArray dst, InputArray mask = noArray()); + +/** @brief Calculates the per-element bit-wise disjunction of two arrays or an +array and a scalar. + +The function cv::bitwise_or calculates the per-element bit-wise logical disjunction for: +* Two arrays when src1 and src2 have the same size: + \f[\texttt{dst} (I) = \texttt{src1} (I) \vee \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +* An array and a scalar when src2 is constructed from Scalar or has + the same number of elements as `src1.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} (I) \vee \texttt{src2} \quad \texttt{if mask} (I) \ne0\f] +* A scalar and an array when src1 is constructed from Scalar or has + the same number of elements as `src2.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} \vee \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +In case of floating-point arrays, their machine-specific bit +representations (usually IEEE754-compliant) are used for the operation. +In case of multi-channel arrays, each channel is processed +independently. In the second and third cases above, the scalar is first +converted to the array type. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array that has the same size and type as the input +arrays. +@param mask optional operation mask, 8-bit single channel array, that +specifies elements of the output array to be changed. +*/ +CV_EXPORTS_W void bitwise_or(InputArray src1, InputArray src2, + OutputArray dst, InputArray mask = noArray()); + +/** @brief Calculates the per-element bit-wise "exclusive or" operation on two +arrays or an array and a scalar. + +The function cv::bitwise_xor calculates the per-element bit-wise logical "exclusive-or" +operation for: +* Two arrays when src1 and src2 have the same size: + \f[\texttt{dst} (I) = \texttt{src1} (I) \oplus \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +* An array and a scalar when src2 is constructed from Scalar or has + the same number of elements as `src1.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} (I) \oplus \texttt{src2} \quad \texttt{if mask} (I) \ne0\f] +* A scalar and an array when src1 is constructed from Scalar or has + the same number of elements as `src2.channels()`: + \f[\texttt{dst} (I) = \texttt{src1} \oplus \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f] +In case of floating-point arrays, their machine-specific bit +representations (usually IEEE754-compliant) are used for the operation. +In case of multi-channel arrays, each channel is processed +independently. In the 2nd and 3rd cases above, the scalar is first +converted to the array type. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array that has the same size and type as the input +arrays. +@param mask optional operation mask, 8-bit single channel array, that +specifies elements of the output array to be changed. +*/ +CV_EXPORTS_W void bitwise_xor(InputArray src1, InputArray src2, + OutputArray dst, InputArray mask = noArray()); + +/** @brief Inverts every bit of an array. + +The function cv::bitwise_not calculates per-element bit-wise inversion of the input +array: +\f[\texttt{dst} (I) = \neg \texttt{src} (I)\f] +In case of a floating-point input array, its machine-specific bit +representation (usually IEEE754-compliant) is used for the operation. In +case of multi-channel arrays, each channel is processed independently. +@param src input array. +@param dst output array that has the same size and type as the input +array. +@param mask optional operation mask, 8-bit single channel array, that +specifies elements of the output array to be changed. +*/ +CV_EXPORTS_W void bitwise_not(InputArray src, OutputArray dst, + InputArray mask = noArray()); + +/** @brief Calculates the per-element absolute difference between two arrays or between an array and a scalar. + +The function cv::absdiff calculates: +* Absolute difference between two arrays when they have the same + size and type: + \f[\texttt{dst}(I) = \texttt{saturate} (| \texttt{src1}(I) - \texttt{src2}(I)|)\f] +* Absolute difference between an array and a scalar when the second + array is constructed from Scalar or has as many elements as the + number of channels in `src1`: + \f[\texttt{dst}(I) = \texttt{saturate} (| \texttt{src1}(I) - \texttt{src2} |)\f] +* Absolute difference between a scalar and an array when the first + array is constructed from Scalar or has as many elements as the + number of channels in `src2`: + \f[\texttt{dst}(I) = \texttt{saturate} (| \texttt{src1} - \texttt{src2}(I) |)\f] + where I is a multi-dimensional index of array elements. In case of + multi-channel arrays, each channel is processed independently. +@note Saturation is not applied when the arrays have the depth CV_32S. +You may even get a negative value in the case of overflow. +@param src1 first input array or a scalar. +@param src2 second input array or a scalar. +@param dst output array that has the same size and type as input arrays. +@sa cv::abs(const Mat&) +*/ +CV_EXPORTS_W void absdiff(InputArray src1, InputArray src2, OutputArray dst); + +/** @brief Checks if array elements lie between the elements of two other arrays. + +The function checks the range as follows: +- For every element of a single-channel input array: + \f[\texttt{dst} (I)= \texttt{lowerb} (I)_0 \leq \texttt{src} (I)_0 \leq \texttt{upperb} (I)_0\f] +- For two-channel arrays: + \f[\texttt{dst} (I)= \texttt{lowerb} (I)_0 \leq \texttt{src} (I)_0 \leq \texttt{upperb} (I)_0 \land \texttt{lowerb} (I)_1 \leq \texttt{src} (I)_1 \leq \texttt{upperb} (I)_1\f] +- and so forth. + +That is, dst (I) is set to 255 (all 1 -bits) if src (I) is within the +specified 1D, 2D, 3D, ... box and 0 otherwise. + +When the lower and/or upper boundary parameters are scalars, the indexes +(I) at lowerb and upperb in the above formulas should be omitted. +@param src first input array. +@param lowerb inclusive lower boundary array or a scalar. +@param upperb inclusive upper boundary array or a scalar. +@param dst output array of the same size as src and CV_8U type. +*/ +CV_EXPORTS_W void inRange(InputArray src, InputArray lowerb, + InputArray upperb, OutputArray dst); + +/** @brief Performs the per-element comparison of two arrays or an array and scalar value. + +The function compares: +* Elements of two arrays when src1 and src2 have the same size: + \f[\texttt{dst} (I) = \texttt{src1} (I) \,\texttt{cmpop}\, \texttt{src2} (I)\f] +* Elements of src1 with a scalar src2 when src2 is constructed from + Scalar or has a single element: + \f[\texttt{dst} (I) = \texttt{src1}(I) \,\texttt{cmpop}\, \texttt{src2}\f] +* src1 with elements of src2 when src1 is constructed from Scalar or + has a single element: + \f[\texttt{dst} (I) = \texttt{src1} \,\texttt{cmpop}\, \texttt{src2} (I)\f] +When the comparison result is true, the corresponding element of output +array is set to 255. The comparison operations can be replaced with the +equivalent matrix expressions: +@code{.cpp} + Mat dst1 = src1 >= src2; + Mat dst2 = src1 < 8; + ... +@endcode +@param src1 first input array or a scalar; when it is an array, it must have a single channel. +@param src2 second input array or a scalar; when it is an array, it must have a single channel. +@param dst output array of type ref CV_8U that has the same size and the same number of channels as + the input arrays. +@param cmpop a flag, that specifies correspondence between the arrays (cv::CmpTypes) +@sa checkRange, min, max, threshold +*/ +CV_EXPORTS_W void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop); + +/** @brief Calculates per-element minimum of two arrays or an array and a scalar. + +The function cv::min calculates the per-element minimum of two arrays: +\f[\texttt{dst} (I)= \min ( \texttt{src1} (I), \texttt{src2} (I))\f] +or array and a scalar: +\f[\texttt{dst} (I)= \min ( \texttt{src1} (I), \texttt{value} )\f] +@param src1 first input array. +@param src2 second input array of the same size and type as src1. +@param dst output array of the same size and type as src1. +@sa max, compare, inRange, minMaxLoc +*/ +CV_EXPORTS_W void min(InputArray src1, InputArray src2, OutputArray dst); +/** @overload +needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare) +*/ +CV_EXPORTS void min(const Mat& src1, const Mat& src2, Mat& dst); +/** @overload +needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare) +*/ +CV_EXPORTS void min(const UMat& src1, const UMat& src2, UMat& dst); + +/** @brief Calculates per-element maximum of two arrays or an array and a scalar. + +The function cv::max calculates the per-element maximum of two arrays: +\f[\texttt{dst} (I)= \max ( \texttt{src1} (I), \texttt{src2} (I))\f] +or array and a scalar: +\f[\texttt{dst} (I)= \max ( \texttt{src1} (I), \texttt{value} )\f] +@param src1 first input array. +@param src2 second input array of the same size and type as src1 . +@param dst output array of the same size and type as src1. +@sa min, compare, inRange, minMaxLoc, @ref MatrixExpressions +*/ +CV_EXPORTS_W void max(InputArray src1, InputArray src2, OutputArray dst); +/** @overload +needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare) +*/ +CV_EXPORTS void max(const Mat& src1, const Mat& src2, Mat& dst); +/** @overload +needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare) +*/ +CV_EXPORTS void max(const UMat& src1, const UMat& src2, UMat& dst); + +/** @brief Calculates a square root of array elements. + +The function cv::sqrt calculates a square root of each input array element. +In case of multi-channel arrays, each channel is processed +independently. The accuracy is approximately the same as of the built-in +std::sqrt . +@param src input floating-point array. +@param dst output array of the same size and type as src. +*/ +CV_EXPORTS_W void sqrt(InputArray src, OutputArray dst); + +/** @brief Raises every array element to a power. + +The function cv::pow raises every element of the input array to power : +\f[\texttt{dst} (I) = \fork{\texttt{src}(I)^{power}}{if \(\texttt{power}\) is integer}{|\texttt{src}(I)|^{power}}{otherwise}\f] + +So, for a non-integer power exponent, the absolute values of input array +elements are used. However, it is possible to get true values for +negative values using some extra operations. In the example below, +computing the 5th root of array src shows: +@code{.cpp} + Mat mask = src < 0; + pow(src, 1./5, dst); + subtract(Scalar::all(0), dst, dst, mask); +@endcode +For some values of power, such as integer values, 0.5 and -0.5, +specialized faster algorithms are used. + +Special values (NaN, Inf) are not handled. +@param src input array. +@param power exponent of power. +@param dst output array of the same size and type as src. +@sa sqrt, exp, log, cartToPolar, polarToCart +*/ +CV_EXPORTS_W void pow(InputArray src, double power, OutputArray dst); + +/** @brief Calculates the exponent of every array element. + +The function cv::exp calculates the exponent of every element of the input +array: +\f[\texttt{dst} [I] = e^{ src(I) }\f] + +The maximum relative error is about 7e-6 for single-precision input and +less than 1e-10 for double-precision input. Currently, the function +converts denormalized values to zeros on output. Special values (NaN, +Inf) are not handled. +@param src input array. +@param dst output array of the same size and type as src. +@sa log , cartToPolar , polarToCart , phase , pow , sqrt , magnitude +*/ +CV_EXPORTS_W void exp(InputArray src, OutputArray dst); + +/** @brief Calculates the natural logarithm of every array element. + +The function cv::log calculates the natural logarithm of every element of the input array: +\f[\texttt{dst} (I) = \log (\texttt{src}(I)) \f] + +Output on zero, negative and special (NaN, Inf) values is undefined. + +@param src input array. +@param dst output array of the same size and type as src . +@sa exp, cartToPolar, polarToCart, phase, pow, sqrt, magnitude +*/ +CV_EXPORTS_W void log(InputArray src, OutputArray dst); + +/** @brief Calculates x and y coordinates of 2D vectors from their magnitude and angle. + +The function cv::polarToCart calculates the Cartesian coordinates of each 2D +vector represented by the corresponding elements of magnitude and angle: +\f[\begin{array}{l} \texttt{x} (I) = \texttt{magnitude} (I) \cos ( \texttt{angle} (I)) \\ \texttt{y} (I) = \texttt{magnitude} (I) \sin ( \texttt{angle} (I)) \\ \end{array}\f] + +The relative accuracy of the estimated coordinates is about 1e-6. +@param magnitude input floating-point array of magnitudes of 2D vectors; +it can be an empty matrix (=Mat()), in this case, the function assumes +that all the magnitudes are =1; if it is not empty, it must have the +same size and type as angle. +@param angle input floating-point array of angles of 2D vectors. +@param x output array of x-coordinates of 2D vectors; it has the same +size and type as angle. +@param y output array of y-coordinates of 2D vectors; it has the same +size and type as angle. +@param angleInDegrees when true, the input angles are measured in +degrees, otherwise, they are measured in radians. +@sa cartToPolar, magnitude, phase, exp, log, pow, sqrt +*/ +CV_EXPORTS_W void polarToCart(InputArray magnitude, InputArray angle, + OutputArray x, OutputArray y, bool angleInDegrees = false); + +/** @brief Calculates the magnitude and angle of 2D vectors. + +The function cv::cartToPolar calculates either the magnitude, angle, or both +for every 2D vector (x(I),y(I)): +\f[\begin{array}{l} \texttt{magnitude} (I)= \sqrt{\texttt{x}(I)^2+\texttt{y}(I)^2} , \\ \texttt{angle} (I)= \texttt{atan2} ( \texttt{y} (I), \texttt{x} (I))[ \cdot180 / \pi ] \end{array}\f] + +The angles are calculated with accuracy about 0.3 degrees. For the point +(0,0), the angle is set to 0. +@param x array of x-coordinates; this must be a single-precision or +double-precision floating-point array. +@param y array of y-coordinates, that must have the same size and same type as x. +@param magnitude output array of magnitudes of the same size and type as x. +@param angle output array of angles that has the same size and type as +x; the angles are measured in radians (from 0 to 2\*Pi) or in degrees (0 to 360 degrees). +@param angleInDegrees a flag, indicating whether the angles are measured +in radians (which is by default), or in degrees. +@sa Sobel, Scharr +*/ +CV_EXPORTS_W void cartToPolar(InputArray x, InputArray y, + OutputArray magnitude, OutputArray angle, + bool angleInDegrees = false); + +/** @brief Calculates the rotation angle of 2D vectors. + +The function cv::phase calculates the rotation angle of each 2D vector that +is formed from the corresponding elements of x and y : +\f[\texttt{angle} (I) = \texttt{atan2} ( \texttt{y} (I), \texttt{x} (I))\f] + +The angle estimation accuracy is about 0.3 degrees. When x(I)=y(I)=0 , +the corresponding angle(I) is set to 0. +@param x input floating-point array of x-coordinates of 2D vectors. +@param y input array of y-coordinates of 2D vectors; it must have the +same size and the same type as x. +@param angle output array of vector angles; it has the same size and +same type as x . +@param angleInDegrees when true, the function calculates the angle in +degrees, otherwise, they are measured in radians. +*/ +CV_EXPORTS_W void phase(InputArray x, InputArray y, OutputArray angle, + bool angleInDegrees = false); + +/** @brief Calculates the magnitude of 2D vectors. + +The function cv::magnitude calculates the magnitude of 2D vectors formed +from the corresponding elements of x and y arrays: +\f[\texttt{dst} (I) = \sqrt{\texttt{x}(I)^2 + \texttt{y}(I)^2}\f] +@param x floating-point array of x-coordinates of the vectors. +@param y floating-point array of y-coordinates of the vectors; it must +have the same size as x. +@param magnitude output array of the same size and type as x. +@sa cartToPolar, polarToCart, phase, sqrt +*/ +CV_EXPORTS_W void magnitude(InputArray x, InputArray y, OutputArray magnitude); + +/** @brief Checks every element of an input array for invalid values. + +The function cv::checkRange checks that every array element is neither NaN nor infinite. When minVal \> +-DBL_MAX and maxVal \< DBL_MAX, the function also checks that each value is between minVal and +maxVal. In case of multi-channel arrays, each channel is processed independently. If some values +are out of range, position of the first outlier is stored in pos (when pos != NULL). Then, the +function either returns false (when quiet=true) or throws an exception. +@param a input array. +@param quiet a flag, indicating whether the functions quietly return false when the array elements +are out of range or they throw an exception. +@param pos optional output parameter, when not NULL, must be a pointer to array of src.dims +elements. +@param minVal inclusive lower boundary of valid values range. +@param maxVal exclusive upper boundary of valid values range. +*/ +CV_EXPORTS_W bool checkRange(InputArray a, bool quiet = true, CV_OUT Point* pos = 0, + double minVal = -DBL_MAX, double maxVal = DBL_MAX); + +/** @brief converts NaN's to the given number +*/ +CV_EXPORTS_W void patchNaNs(InputOutputArray a, double val = 0); + +/** @brief Performs generalized matrix multiplication. + +The function cv::gemm performs generalized matrix multiplication similar to the +gemm functions in BLAS level 3. For example, +`gemm(src1, src2, alpha, src3, beta, dst, GEMM_1_T + GEMM_3_T)` +corresponds to +\f[\texttt{dst} = \texttt{alpha} \cdot \texttt{src1} ^T \cdot \texttt{src2} + \texttt{beta} \cdot \texttt{src3} ^T\f] + +In case of complex (two-channel) data, performed a complex matrix +multiplication. + +The function can be replaced with a matrix expression. For example, the +above call can be replaced with: +@code{.cpp} + dst = alpha*src1.t()*src2 + beta*src3.t(); +@endcode +@param src1 first multiplied input matrix that could be real(CV_32FC1, +CV_64FC1) or complex(CV_32FC2, CV_64FC2). +@param src2 second multiplied input matrix of the same type as src1. +@param alpha weight of the matrix product. +@param src3 third optional delta matrix added to the matrix product; it +should have the same type as src1 and src2. +@param beta weight of src3. +@param dst output matrix; it has the proper size and the same type as +input matrices. +@param flags operation flags (cv::GemmFlags) +@sa mulTransposed , transform +*/ +CV_EXPORTS_W void gemm(InputArray src1, InputArray src2, double alpha, + InputArray src3, double beta, OutputArray dst, int flags = 0); + +/** @brief Calculates the product of a matrix and its transposition. + +The function cv::mulTransposed calculates the product of src and its +transposition: +\f[\texttt{dst} = \texttt{scale} ( \texttt{src} - \texttt{delta} )^T ( \texttt{src} - \texttt{delta} )\f] +if aTa=true , and +\f[\texttt{dst} = \texttt{scale} ( \texttt{src} - \texttt{delta} ) ( \texttt{src} - \texttt{delta} )^T\f] +otherwise. The function is used to calculate the covariance matrix. With +zero delta, it can be used as a faster substitute for general matrix +product A\*B when B=A' +@param src input single-channel matrix. Note that unlike gemm, the +function can multiply not only floating-point matrices. +@param dst output square matrix. +@param aTa Flag specifying the multiplication ordering. See the +description below. +@param delta Optional delta matrix subtracted from src before the +multiplication. When the matrix is empty ( delta=noArray() ), it is +assumed to be zero, that is, nothing is subtracted. If it has the same +size as src , it is simply subtracted. Otherwise, it is "repeated" (see +repeat ) to cover the full src and then subtracted. Type of the delta +matrix, when it is not empty, must be the same as the type of created +output matrix. See the dtype parameter description below. +@param scale Optional scale factor for the matrix product. +@param dtype Optional type of the output matrix. When it is negative, +the output matrix will have the same type as src . Otherwise, it will be +type=CV_MAT_DEPTH(dtype) that should be either CV_32F or CV_64F . +@sa calcCovarMatrix, gemm, repeat, reduce +*/ +CV_EXPORTS_W void mulTransposed( InputArray src, OutputArray dst, bool aTa, + InputArray delta = noArray(), + double scale = 1, int dtype = -1 ); + +/** @brief Transposes a matrix. + +The function cv::transpose transposes the matrix src : +\f[\texttt{dst} (i,j) = \texttt{src} (j,i)\f] +@note No complex conjugation is done in case of a complex matrix. It +should be done separately if needed. +@param src input array. +@param dst output array of the same type as src. +*/ +CV_EXPORTS_W void transpose(InputArray src, OutputArray dst); + +/** @brief Performs the matrix transformation of every array element. + +The function cv::transform performs the matrix transformation of every +element of the array src and stores the results in dst : +\f[\texttt{dst} (I) = \texttt{m} \cdot \texttt{src} (I)\f] +(when m.cols=src.channels() ), or +\f[\texttt{dst} (I) = \texttt{m} \cdot [ \texttt{src} (I); 1]\f] +(when m.cols=src.channels()+1 ) + +Every element of the N -channel array src is interpreted as N -element +vector that is transformed using the M x N or M x (N+1) matrix m to +M-element vector - the corresponding element of the output array dst . + +The function may be used for geometrical transformation of +N -dimensional points, arbitrary linear color space transformation (such +as various kinds of RGB to YUV transforms), shuffling the image +channels, and so forth. +@param src input array that must have as many channels (1 to 4) as +m.cols or m.cols-1. +@param dst output array of the same size and depth as src; it has as +many channels as m.rows. +@param m transformation 2x2 or 2x3 floating-point matrix. +@sa perspectiveTransform, getAffineTransform, estimateAffine2D, warpAffine, warpPerspective +*/ +CV_EXPORTS_W void transform(InputArray src, OutputArray dst, InputArray m ); + +/** @brief Performs the perspective matrix transformation of vectors. + +The function cv::perspectiveTransform transforms every element of src by +treating it as a 2D or 3D vector, in the following way: +\f[(x, y, z) \rightarrow (x'/w, y'/w, z'/w)\f] +where +\f[(x', y', z', w') = \texttt{mat} \cdot \begin{bmatrix} x & y & z & 1 \end{bmatrix}\f] +and +\f[w = \fork{w'}{if \(w' \ne 0\)}{\infty}{otherwise}\f] + +Here a 3D vector transformation is shown. In case of a 2D vector +transformation, the z component is omitted. + +@note The function transforms a sparse set of 2D or 3D vectors. If you +want to transform an image using perspective transformation, use +warpPerspective . If you have an inverse problem, that is, you want to +compute the most probable perspective transformation out of several +pairs of corresponding points, you can use getPerspectiveTransform or +findHomography . +@param src input two-channel or three-channel floating-point array; each +element is a 2D/3D vector to be transformed. +@param dst output array of the same size and type as src. +@param m 3x3 or 4x4 floating-point transformation matrix. +@sa transform, warpPerspective, getPerspectiveTransform, findHomography +*/ +CV_EXPORTS_W void perspectiveTransform(InputArray src, OutputArray dst, InputArray m ); + +/** @brief Copies the lower or the upper half of a square matrix to its another half. + +The function cv::completeSymm copies the lower or the upper half of a square matrix to +its another half. The matrix diagonal remains unchanged: + - \f$\texttt{m}_{ij}=\texttt{m}_{ji}\f$ for \f$i > j\f$ if + lowerToUpper=false + - \f$\texttt{m}_{ij}=\texttt{m}_{ji}\f$ for \f$i < j\f$ if + lowerToUpper=true + +@param m input-output floating-point square matrix. +@param lowerToUpper operation flag; if true, the lower half is copied to +the upper half. Otherwise, the upper half is copied to the lower half. +@sa flip, transpose +*/ +CV_EXPORTS_W void completeSymm(InputOutputArray m, bool lowerToUpper = false); + +/** @brief Initializes a scaled identity matrix. + +The function cv::setIdentity initializes a scaled identity matrix: +\f[\texttt{mtx} (i,j)= \fork{\texttt{value}}{ if \(i=j\)}{0}{otherwise}\f] + +The function can also be emulated using the matrix initializers and the +matrix expressions: +@code + Mat A = Mat::eye(4, 3, CV_32F)*5; + // A will be set to [[5, 0, 0], [0, 5, 0], [0, 0, 5], [0, 0, 0]] +@endcode +@param mtx matrix to initialize (not necessarily square). +@param s value to assign to diagonal elements. +@sa Mat::zeros, Mat::ones, Mat::setTo, Mat::operator= +*/ +CV_EXPORTS_W void setIdentity(InputOutputArray mtx, const Scalar& s = Scalar(1)); + +/** @brief Returns the determinant of a square floating-point matrix. + +The function cv::determinant calculates and returns the determinant of the +specified matrix. For small matrices ( mtx.cols=mtx.rows\<=3 ), the +direct method is used. For larger matrices, the function uses LU +factorization with partial pivoting. + +For symmetric positively-determined matrices, it is also possible to use +eigen decomposition to calculate the determinant. +@param mtx input matrix that must have CV_32FC1 or CV_64FC1 type and +square size. +@sa trace, invert, solve, eigen, @ref MatrixExpressions +*/ +CV_EXPORTS_W double determinant(InputArray mtx); + +/** @brief Returns the trace of a matrix. + +The function cv::trace returns the sum of the diagonal elements of the +matrix mtx . +\f[\mathrm{tr} ( \texttt{mtx} ) = \sum _i \texttt{mtx} (i,i)\f] +@param mtx input matrix. +*/ +CV_EXPORTS_W Scalar trace(InputArray mtx); + +/** @brief Finds the inverse or pseudo-inverse of a matrix. + +The function cv::invert inverts the matrix src and stores the result in dst +. When the matrix src is singular or non-square, the function calculates +the pseudo-inverse matrix (the dst matrix) so that norm(src\*dst - I) is +minimal, where I is an identity matrix. + +In case of the #DECOMP_LU method, the function returns non-zero value if +the inverse has been successfully calculated and 0 if src is singular. + +In case of the #DECOMP_SVD method, the function returns the inverse +condition number of src (the ratio of the smallest singular value to the +largest singular value) and 0 if src is singular. The SVD method +calculates a pseudo-inverse matrix if src is singular. + +Similarly to #DECOMP_LU, the method #DECOMP_CHOLESKY works only with +non-singular square matrices that should also be symmetrical and +positively defined. In this case, the function stores the inverted +matrix in dst and returns non-zero. Otherwise, it returns 0. + +@param src input floating-point M x N matrix. +@param dst output matrix of N x M size and the same type as src. +@param flags inversion method (cv::DecompTypes) +@sa solve, SVD +*/ +CV_EXPORTS_W double invert(InputArray src, OutputArray dst, int flags = DECOMP_LU); + +/** @brief Solves one or more linear systems or least-squares problems. + +The function cv::solve solves a linear system or least-squares problem (the +latter is possible with SVD or QR methods, or by specifying the flag +#DECOMP_NORMAL ): +\f[\texttt{dst} = \arg \min _X \| \texttt{src1} \cdot \texttt{X} - \texttt{src2} \|\f] + +If #DECOMP_LU or #DECOMP_CHOLESKY method is used, the function returns 1 +if src1 (or \f$\texttt{src1}^T\texttt{src1}\f$ ) is non-singular. Otherwise, +it returns 0. In the latter case, dst is not valid. Other methods find a +pseudo-solution in case of a singular left-hand side part. + +@note If you want to find a unity-norm solution of an under-defined +singular system \f$\texttt{src1}\cdot\texttt{dst}=0\f$ , the function solve +will not do the work. Use SVD::solveZ instead. + +@param src1 input matrix on the left-hand side of the system. +@param src2 input matrix on the right-hand side of the system. +@param dst output solution. +@param flags solution (matrix inversion) method (#DecompTypes) +@sa invert, SVD, eigen +*/ +CV_EXPORTS_W bool solve(InputArray src1, InputArray src2, + OutputArray dst, int flags = DECOMP_LU); + +/** @brief Sorts each row or each column of a matrix. + +The function cv::sort sorts each matrix row or each matrix column in +ascending or descending order. So you should pass two operation flags to +get desired behaviour. If you want to sort matrix rows or columns +lexicographically, you can use STL std::sort generic function with the +proper comparison predicate. + +@param src input single-channel array. +@param dst output array of the same size and type as src. +@param flags operation flags, a combination of #SortFlags +@sa sortIdx, randShuffle +*/ +CV_EXPORTS_W void sort(InputArray src, OutputArray dst, int flags); + +/** @brief Sorts each row or each column of a matrix. + +The function cv::sortIdx sorts each matrix row or each matrix column in the +ascending or descending order. So you should pass two operation flags to +get desired behaviour. Instead of reordering the elements themselves, it +stores the indices of sorted elements in the output array. For example: +@code + Mat A = Mat::eye(3,3,CV_32F), B; + sortIdx(A, B, SORT_EVERY_ROW + SORT_ASCENDING); + // B will probably contain + // (because of equal elements in A some permutations are possible): + // [[1, 2, 0], [0, 2, 1], [0, 1, 2]] +@endcode +@param src input single-channel array. +@param dst output integer array of the same size as src. +@param flags operation flags that could be a combination of cv::SortFlags +@sa sort, randShuffle +*/ +CV_EXPORTS_W void sortIdx(InputArray src, OutputArray dst, int flags); + +/** @brief Finds the real roots of a cubic equation. + +The function solveCubic finds the real roots of a cubic equation: +- if coeffs is a 4-element vector: +\f[\texttt{coeffs} [0] x^3 + \texttt{coeffs} [1] x^2 + \texttt{coeffs} [2] x + \texttt{coeffs} [3] = 0\f] +- if coeffs is a 3-element vector: +\f[x^3 + \texttt{coeffs} [0] x^2 + \texttt{coeffs} [1] x + \texttt{coeffs} [2] = 0\f] + +The roots are stored in the roots array. +@param coeffs equation coefficients, an array of 3 or 4 elements. +@param roots output array of real roots that has 1 or 3 elements. +@return number of real roots. It can be 0, 1 or 2. +*/ +CV_EXPORTS_W int solveCubic(InputArray coeffs, OutputArray roots); + +/** @brief Finds the real or complex roots of a polynomial equation. + +The function cv::solvePoly finds real and complex roots of a polynomial equation: +\f[\texttt{coeffs} [n] x^{n} + \texttt{coeffs} [n-1] x^{n-1} + ... + \texttt{coeffs} [1] x + \texttt{coeffs} [0] = 0\f] +@param coeffs array of polynomial coefficients. +@param roots output (complex) array of roots. +@param maxIters maximum number of iterations the algorithm does. +*/ +CV_EXPORTS_W double solvePoly(InputArray coeffs, OutputArray roots, int maxIters = 300); + +/** @brief Calculates eigenvalues and eigenvectors of a symmetric matrix. + +The function cv::eigen calculates just eigenvalues, or eigenvalues and eigenvectors of the symmetric +matrix src: +@code + src*eigenvectors.row(i).t() = eigenvalues.at(i)*eigenvectors.row(i).t() +@endcode + +@note Use cv::eigenNonSymmetric for calculation of real eigenvalues and eigenvectors of non-symmetric matrix. + +@param src input matrix that must have CV_32FC1 or CV_64FC1 type, square size and be symmetrical +(src ^T^ == src). +@param eigenvalues output vector of eigenvalues of the same type as src; the eigenvalues are stored +in the descending order. +@param eigenvectors output matrix of eigenvectors; it has the same size and type as src; the +eigenvectors are stored as subsequent matrix rows, in the same order as the corresponding +eigenvalues. +@sa eigenNonSymmetric, completeSymm , PCA +*/ +CV_EXPORTS_W bool eigen(InputArray src, OutputArray eigenvalues, + OutputArray eigenvectors = noArray()); + +/** @brief Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only). + +@note Assumes real eigenvalues. + +The function calculates eigenvalues and eigenvectors (optional) of the square matrix src: +@code + src*eigenvectors.row(i).t() = eigenvalues.at(i)*eigenvectors.row(i).t() +@endcode + +@param src input matrix (CV_32FC1 or CV_64FC1 type). +@param eigenvalues output vector of eigenvalues (type is the same type as src). +@param eigenvectors output matrix of eigenvectors (type is the same type as src). The eigenvectors are stored as subsequent matrix rows, in the same order as the corresponding eigenvalues. +@sa eigen +*/ +CV_EXPORTS_W void eigenNonSymmetric(InputArray src, OutputArray eigenvalues, + OutputArray eigenvectors); + +/** @brief Calculates the covariance matrix of a set of vectors. + +The function cv::calcCovarMatrix calculates the covariance matrix and, optionally, the mean vector of +the set of input vectors. +@param samples samples stored as separate matrices +@param nsamples number of samples +@param covar output covariance matrix of the type ctype and square size. +@param mean input or output (depending on the flags) array as the average value of the input vectors. +@param flags operation flags as a combination of #CovarFlags +@param ctype type of the matrixl; it equals 'CV_64F' by default. +@sa PCA, mulTransposed, Mahalanobis +@todo InputArrayOfArrays +*/ +CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean, + int flags, int ctype = CV_64F); + +/** @overload +@note use #COVAR_ROWS or #COVAR_COLS flag +@param samples samples stored as rows/columns of a single matrix. +@param covar output covariance matrix of the type ctype and square size. +@param mean input or output (depending on the flags) array as the average value of the input vectors. +@param flags operation flags as a combination of #CovarFlags +@param ctype type of the matrixl; it equals 'CV_64F' by default. +*/ +CV_EXPORTS_W void calcCovarMatrix( InputArray samples, OutputArray covar, + InputOutputArray mean, int flags, int ctype = CV_64F); + +/** wrap PCA::operator() */ +CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean, + OutputArray eigenvectors, int maxComponents = 0); + +/** wrap PCA::operator() and add eigenvalues output parameter */ +CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean, + OutputArray eigenvectors, OutputArray eigenvalues, + int maxComponents = 0); + +/** wrap PCA::operator() */ +CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean, + OutputArray eigenvectors, double retainedVariance); + +/** wrap PCA::operator() and add eigenvalues output parameter */ +CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean, + OutputArray eigenvectors, OutputArray eigenvalues, + double retainedVariance); + +/** wrap PCA::project */ +CV_EXPORTS_W void PCAProject(InputArray data, InputArray mean, + InputArray eigenvectors, OutputArray result); + +/** wrap PCA::backProject */ +CV_EXPORTS_W void PCABackProject(InputArray data, InputArray mean, + InputArray eigenvectors, OutputArray result); + +/** wrap SVD::compute */ +CV_EXPORTS_W void SVDecomp( InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags = 0 ); + +/** wrap SVD::backSubst */ +CV_EXPORTS_W void SVBackSubst( InputArray w, InputArray u, InputArray vt, + InputArray rhs, OutputArray dst ); + +/** @brief Calculates the Mahalanobis distance between two vectors. + +The function cv::Mahalanobis calculates and returns the weighted distance between two vectors: +\f[d( \texttt{vec1} , \texttt{vec2} )= \sqrt{\sum_{i,j}{\texttt{icovar(i,j)}\cdot(\texttt{vec1}(I)-\texttt{vec2}(I))\cdot(\texttt{vec1(j)}-\texttt{vec2(j)})} }\f] +The covariance matrix may be calculated using the #calcCovarMatrix function and then inverted using +the invert function (preferably using the #DECOMP_SVD method, as the most accurate). +@param v1 first 1D input vector. +@param v2 second 1D input vector. +@param icovar inverse covariance matrix. +*/ +CV_EXPORTS_W double Mahalanobis(InputArray v1, InputArray v2, InputArray icovar); + +/** @brief Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array. + +The function cv::dft performs one of the following: +- Forward the Fourier transform of a 1D vector of N elements: + \f[Y = F^{(N)} \cdot X,\f] + where \f$F^{(N)}_{jk}=\exp(-2\pi i j k/N)\f$ and \f$i=\sqrt{-1}\f$ +- Inverse the Fourier transform of a 1D vector of N elements: + \f[\begin{array}{l} X'= \left (F^{(N)} \right )^{-1} \cdot Y = \left (F^{(N)} \right )^* \cdot y \\ X = (1/N) \cdot X, \end{array}\f] + where \f$F^*=\left(\textrm{Re}(F^{(N)})-\textrm{Im}(F^{(N)})\right)^T\f$ +- Forward the 2D Fourier transform of a M x N matrix: + \f[Y = F^{(M)} \cdot X \cdot F^{(N)}\f] +- Inverse the 2D Fourier transform of a M x N matrix: + \f[\begin{array}{l} X'= \left (F^{(M)} \right )^* \cdot Y \cdot \left (F^{(N)} \right )^* \\ X = \frac{1}{M \cdot N} \cdot X' \end{array}\f] + +In case of real (single-channel) data, the output spectrum of the forward Fourier transform or input +spectrum of the inverse Fourier transform can be represented in a packed format called *CCS* +(complex-conjugate-symmetrical). It was borrowed from IPL (Intel\* Image Processing Library). Here +is how 2D *CCS* spectrum looks: +\f[\begin{bmatrix} Re Y_{0,0} & Re Y_{0,1} & Im Y_{0,1} & Re Y_{0,2} & Im Y_{0,2} & \cdots & Re Y_{0,N/2-1} & Im Y_{0,N/2-1} & Re Y_{0,N/2} \\ Re Y_{1,0} & Re Y_{1,1} & Im Y_{1,1} & Re Y_{1,2} & Im Y_{1,2} & \cdots & Re Y_{1,N/2-1} & Im Y_{1,N/2-1} & Re Y_{1,N/2} \\ Im Y_{1,0} & Re Y_{2,1} & Im Y_{2,1} & Re Y_{2,2} & Im Y_{2,2} & \cdots & Re Y_{2,N/2-1} & Im Y_{2,N/2-1} & Im Y_{1,N/2} \\ \hdotsfor{9} \\ Re Y_{M/2-1,0} & Re Y_{M-3,1} & Im Y_{M-3,1} & \hdotsfor{3} & Re Y_{M-3,N/2-1} & Im Y_{M-3,N/2-1}& Re Y_{M/2-1,N/2} \\ Im Y_{M/2-1,0} & Re Y_{M-2,1} & Im Y_{M-2,1} & \hdotsfor{3} & Re Y_{M-2,N/2-1} & Im Y_{M-2,N/2-1}& Im Y_{M/2-1,N/2} \\ Re Y_{M/2,0} & Re Y_{M-1,1} & Im Y_{M-1,1} & \hdotsfor{3} & Re Y_{M-1,N/2-1} & Im Y_{M-1,N/2-1}& Re Y_{M/2,N/2} \end{bmatrix}\f] + +In case of 1D transform of a real vector, the output looks like the first row of the matrix above. + +So, the function chooses an operation mode depending on the flags and size of the input array: +- If #DFT_ROWS is set or the input array has a single row or single column, the function + performs a 1D forward or inverse transform of each row of a matrix when #DFT_ROWS is set. + Otherwise, it performs a 2D transform. +- If the input array is real and #DFT_INVERSE is not set, the function performs a forward 1D or + 2D transform: + - When #DFT_COMPLEX_OUTPUT is set, the output is a complex matrix of the same size as + input. + - When #DFT_COMPLEX_OUTPUT is not set, the output is a real matrix of the same size as + input. In case of 2D transform, it uses the packed format as shown above. In case of a + single 1D transform, it looks like the first row of the matrix above. In case of + multiple 1D transforms (when using the #DFT_ROWS flag), each row of the output matrix + looks like the first row of the matrix above. +- If the input array is complex and either #DFT_INVERSE or #DFT_REAL_OUTPUT are not set, the + output is a complex array of the same size as input. The function performs a forward or + inverse 1D or 2D transform of the whole input array or each row of the input array + independently, depending on the flags DFT_INVERSE and DFT_ROWS. +- When #DFT_INVERSE is set and the input array is real, or it is complex but #DFT_REAL_OUTPUT + is set, the output is a real array of the same size as input. The function performs a 1D or 2D + inverse transformation of the whole input array or each individual row, depending on the flags + #DFT_INVERSE and #DFT_ROWS. + +If #DFT_SCALE is set, the scaling is done after the transformation. + +Unlike dct , the function supports arrays of arbitrary size. But only those arrays are processed +efficiently, whose sizes can be factorized in a product of small prime numbers (2, 3, and 5 in the +current implementation). Such an efficient DFT size can be calculated using the getOptimalDFTSize +method. + +The sample below illustrates how to calculate a DFT-based convolution of two 2D real arrays: +@code + void convolveDFT(InputArray A, InputArray B, OutputArray C) + { + // reallocate the output array if needed + C.create(abs(A.rows - B.rows)+1, abs(A.cols - B.cols)+1, A.type()); + Size dftSize; + // calculate the size of DFT transform + dftSize.width = getOptimalDFTSize(A.cols + B.cols - 1); + dftSize.height = getOptimalDFTSize(A.rows + B.rows - 1); + + // allocate temporary buffers and initialize them with 0's + Mat tempA(dftSize, A.type(), Scalar::all(0)); + Mat tempB(dftSize, B.type(), Scalar::all(0)); + + // copy A and B to the top-left corners of tempA and tempB, respectively + Mat roiA(tempA, Rect(0,0,A.cols,A.rows)); + A.copyTo(roiA); + Mat roiB(tempB, Rect(0,0,B.cols,B.rows)); + B.copyTo(roiB); + + // now transform the padded A & B in-place; + // use "nonzeroRows" hint for faster processing + dft(tempA, tempA, 0, A.rows); + dft(tempB, tempB, 0, B.rows); + + // multiply the spectrums; + // the function handles packed spectrum representations well + mulSpectrums(tempA, tempB, tempA); + + // transform the product back from the frequency domain. + // Even though all the result rows will be non-zero, + // you need only the first C.rows of them, and thus you + // pass nonzeroRows == C.rows + dft(tempA, tempA, DFT_INVERSE + DFT_SCALE, C.rows); + + // now copy the result back to C. + tempA(Rect(0, 0, C.cols, C.rows)).copyTo(C); + + // all the temporary buffers will be deallocated automatically + } +@endcode +To optimize this sample, consider the following approaches: +- Since nonzeroRows != 0 is passed to the forward transform calls and since A and B are copied to + the top-left corners of tempA and tempB, respectively, it is not necessary to clear the whole + tempA and tempB. It is only necessary to clear the tempA.cols - A.cols ( tempB.cols - B.cols) + rightmost columns of the matrices. +- This DFT-based convolution does not have to be applied to the whole big arrays, especially if B + is significantly smaller than A or vice versa. Instead, you can calculate convolution by parts. + To do this, you need to split the output array C into multiple tiles. For each tile, estimate + which parts of A and B are required to calculate convolution in this tile. If the tiles in C are + too small, the speed will decrease a lot because of repeated work. In the ultimate case, when + each tile in C is a single pixel, the algorithm becomes equivalent to the naive convolution + algorithm. If the tiles are too big, the temporary arrays tempA and tempB become too big and + there is also a slowdown because of bad cache locality. So, there is an optimal tile size + somewhere in the middle. +- If different tiles in C can be calculated in parallel and, thus, the convolution is done by + parts, the loop can be threaded. + +All of the above improvements have been implemented in #matchTemplate and #filter2D . Therefore, by +using them, you can get the performance even better than with the above theoretically optimal +implementation. Though, those two functions actually calculate cross-correlation, not convolution, +so you need to "flip" the second convolution operand B vertically and horizontally using flip . +@note +- An example using the discrete fourier transform can be found at + opencv_source_code/samples/cpp/dft.cpp +- (Python) An example using the dft functionality to perform Wiener deconvolution can be found + at opencv_source/samples/python/deconvolution.py +- (Python) An example rearranging the quadrants of a Fourier image can be found at + opencv_source/samples/python/dft.py +@param src input array that could be real or complex. +@param dst output array whose size and type depends on the flags . +@param flags transformation flags, representing a combination of the #DftFlags +@param nonzeroRows when the parameter is not zero, the function assumes that only the first +nonzeroRows rows of the input array (#DFT_INVERSE is not set) or only the first nonzeroRows of the +output array (#DFT_INVERSE is set) contain non-zeros, thus, the function can handle the rest of the +rows more efficiently and save some time; this technique is very useful for calculating array +cross-correlation or convolution using DFT. +@sa dct , getOptimalDFTSize , mulSpectrums, filter2D , matchTemplate , flip , cartToPolar , +magnitude , phase +*/ +CV_EXPORTS_W void dft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0); + +/** @brief Calculates the inverse Discrete Fourier Transform of a 1D or 2D array. + +idft(src, dst, flags) is equivalent to dft(src, dst, flags | #DFT_INVERSE) . +@note None of dft and idft scales the result by default. So, you should pass #DFT_SCALE to one of +dft or idft explicitly to make these transforms mutually inverse. +@sa dft, dct, idct, mulSpectrums, getOptimalDFTSize +@param src input floating-point real or complex array. +@param dst output array whose size and type depend on the flags. +@param flags operation flags (see dft and #DftFlags). +@param nonzeroRows number of dst rows to process; the rest of the rows have undefined content (see +the convolution sample in dft description. +*/ +CV_EXPORTS_W void idft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0); + +/** @brief Performs a forward or inverse discrete Cosine transform of 1D or 2D array. + +The function cv::dct performs a forward or inverse discrete Cosine transform (DCT) of a 1D or 2D +floating-point array: +- Forward Cosine transform of a 1D vector of N elements: + \f[Y = C^{(N)} \cdot X\f] + where + \f[C^{(N)}_{jk}= \sqrt{\alpha_j/N} \cos \left ( \frac{\pi(2k+1)j}{2N} \right )\f] + and + \f$\alpha_0=1\f$, \f$\alpha_j=2\f$ for *j \> 0*. +- Inverse Cosine transform of a 1D vector of N elements: + \f[X = \left (C^{(N)} \right )^{-1} \cdot Y = \left (C^{(N)} \right )^T \cdot Y\f] + (since \f$C^{(N)}\f$ is an orthogonal matrix, \f$C^{(N)} \cdot \left(C^{(N)}\right)^T = I\f$ ) +- Forward 2D Cosine transform of M x N matrix: + \f[Y = C^{(N)} \cdot X \cdot \left (C^{(N)} \right )^T\f] +- Inverse 2D Cosine transform of M x N matrix: + \f[X = \left (C^{(N)} \right )^T \cdot X \cdot C^{(N)}\f] + +The function chooses the mode of operation by looking at the flags and size of the input array: +- If (flags & #DCT_INVERSE) == 0 , the function does a forward 1D or 2D transform. Otherwise, it + is an inverse 1D or 2D transform. +- If (flags & #DCT_ROWS) != 0 , the function performs a 1D transform of each row. +- If the array is a single column or a single row, the function performs a 1D transform. +- If none of the above is true, the function performs a 2D transform. + +@note Currently dct supports even-size arrays (2, 4, 6 ...). For data analysis and approximation, you +can pad the array when necessary. +Also, the function performance depends very much, and not monotonically, on the array size (see +getOptimalDFTSize ). In the current implementation DCT of a vector of size N is calculated via DFT +of a vector of size N/2 . Thus, the optimal DCT size N1 \>= N can be calculated as: +@code + size_t getOptimalDCTSize(size_t N) { return 2*getOptimalDFTSize((N+1)/2); } + N1 = getOptimalDCTSize(N); +@endcode +@param src input floating-point array. +@param dst output array of the same size and type as src . +@param flags transformation flags as a combination of cv::DftFlags (DCT_*) +@sa dft , getOptimalDFTSize , idct +*/ +CV_EXPORTS_W void dct(InputArray src, OutputArray dst, int flags = 0); + +/** @brief Calculates the inverse Discrete Cosine Transform of a 1D or 2D array. + +idct(src, dst, flags) is equivalent to dct(src, dst, flags | DCT_INVERSE). +@param src input floating-point single-channel array. +@param dst output array of the same size and type as src. +@param flags operation flags. +@sa dct, dft, idft, getOptimalDFTSize +*/ +CV_EXPORTS_W void idct(InputArray src, OutputArray dst, int flags = 0); + +/** @brief Performs the per-element multiplication of two Fourier spectrums. + +The function cv::mulSpectrums performs the per-element multiplication of the two CCS-packed or complex +matrices that are results of a real or complex Fourier transform. + +The function, together with dft and idft , may be used to calculate convolution (pass conjB=false ) +or correlation (pass conjB=true ) of two arrays rapidly. When the arrays are complex, they are +simply multiplied (per element) with an optional conjugation of the second-array elements. When the +arrays are real, they are assumed to be CCS-packed (see dft for details). +@param a first input array. +@param b second input array of the same size and type as src1 . +@param c output array of the same size and type as src1 . +@param flags operation flags; currently, the only supported flag is cv::DFT_ROWS, which indicates that +each row of src1 and src2 is an independent 1D Fourier spectrum. If you do not want to use this flag, then simply add a `0` as value. +@param conjB optional flag that conjugates the second input array before the multiplication (true) +or not (false). +*/ +CV_EXPORTS_W void mulSpectrums(InputArray a, InputArray b, OutputArray c, + int flags, bool conjB = false); + +/** @brief Returns the optimal DFT size for a given vector size. + +DFT performance is not a monotonic function of a vector size. Therefore, when you calculate +convolution of two arrays or perform the spectral analysis of an array, it usually makes sense to +pad the input data with zeros to get a bit larger array that can be transformed much faster than the +original one. Arrays whose size is a power-of-two (2, 4, 8, 16, 32, ...) are the fastest to process. +Though, the arrays whose size is a product of 2's, 3's, and 5's (for example, 300 = 5\*5\*3\*2\*2) +are also processed quite efficiently. + +The function cv::getOptimalDFTSize returns the minimum number N that is greater than or equal to vecsize +so that the DFT of a vector of size N can be processed efficiently. In the current implementation N += 2 ^p^ \* 3 ^q^ \* 5 ^r^ for some integer p, q, r. + +The function returns a negative number if vecsize is too large (very close to INT_MAX ). + +While the function cannot be used directly to estimate the optimal vector size for DCT transform +(since the current DCT implementation supports only even-size vectors), it can be easily processed +as getOptimalDFTSize((vecsize+1)/2)\*2. +@param vecsize vector size. +@sa dft , dct , idft , idct , mulSpectrums +*/ +CV_EXPORTS_W int getOptimalDFTSize(int vecsize); + +/** @brief Returns the default random number generator. + +The function cv::theRNG returns the default random number generator. For each thread, there is a +separate random number generator, so you can use the function safely in multi-thread environments. +If you just need to get a single random number using this generator or initialize an array, you can +use randu or randn instead. But if you are going to generate many random numbers inside a loop, it +is much faster to use this function to retrieve the generator and then use RNG::operator _Tp() . +@sa RNG, randu, randn +*/ +CV_EXPORTS RNG& theRNG(); + +/** @brief Sets state of default random number generator. + +The function cv::setRNGSeed sets state of default random number generator to custom value. +@param seed new state for default random number generator +@sa RNG, randu, randn +*/ +CV_EXPORTS_W void setRNGSeed(int seed); + +/** @brief Generates a single uniformly-distributed random number or an array of random numbers. + +Non-template variant of the function fills the matrix dst with uniformly-distributed +random numbers from the specified range: +\f[\texttt{low} _c \leq \texttt{dst} (I)_c < \texttt{high} _c\f] +@param dst output array of random numbers; the array must be pre-allocated. +@param low inclusive lower boundary of the generated random numbers. +@param high exclusive upper boundary of the generated random numbers. +@sa RNG, randn, theRNG +*/ +CV_EXPORTS_W void randu(InputOutputArray dst, InputArray low, InputArray high); + +/** @brief Fills the array with normally distributed random numbers. + +The function cv::randn fills the matrix dst with normally distributed random numbers with the specified +mean vector and the standard deviation matrix. The generated random numbers are clipped to fit the +value range of the output array data type. +@param dst output array of random numbers; the array must be pre-allocated and have 1 to 4 channels. +@param mean mean value (expectation) of the generated random numbers. +@param stddev standard deviation of the generated random numbers; it can be either a vector (in +which case a diagonal standard deviation matrix is assumed) or a square matrix. +@sa RNG, randu +*/ +CV_EXPORTS_W void randn(InputOutputArray dst, InputArray mean, InputArray stddev); + +/** @brief Shuffles the array elements randomly. + +The function cv::randShuffle shuffles the specified 1D array by randomly choosing pairs of elements and +swapping them. The number of such swap operations will be dst.rows\*dst.cols\*iterFactor . +@param dst input/output numerical 1D array. +@param iterFactor scale factor that determines the number of random swap operations (see the details +below). +@param rng optional random number generator used for shuffling; if it is zero, theRNG () is used +instead. +@sa RNG, sort +*/ +CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor = 1., RNG* rng = 0); + +/** @brief Principal Component Analysis + +The class is used to calculate a special basis for a set of vectors. The +basis will consist of eigenvectors of the covariance matrix calculated +from the input set of vectors. The class %PCA can also transform +vectors to/from the new coordinate space defined by the basis. Usually, +in this new coordinate system, each vector from the original set (and +any linear combination of such vectors) can be quite accurately +approximated by taking its first few components, corresponding to the +eigenvectors of the largest eigenvalues of the covariance matrix. +Geometrically it means that you calculate a projection of the vector to +a subspace formed by a few eigenvectors corresponding to the dominant +eigenvalues of the covariance matrix. And usually such a projection is +very close to the original vector. So, you can represent the original +vector from a high-dimensional space with a much shorter vector +consisting of the projected vector's coordinates in the subspace. Such a +transformation is also known as Karhunen-Loeve Transform, or KLT. +See http://en.wikipedia.org/wiki/Principal_component_analysis + +The sample below is the function that takes two matrices. The first +function stores a set of vectors (a row per vector) that is used to +calculate PCA. The second function stores another "test" set of vectors +(a row per vector). First, these vectors are compressed with PCA, then +reconstructed back, and then the reconstruction error norm is computed +and printed for each vector. : + +@code{.cpp} +using namespace cv; + +PCA compressPCA(const Mat& pcaset, int maxComponents, + const Mat& testset, Mat& compressed) +{ + PCA pca(pcaset, // pass the data + Mat(), // we do not have a pre-computed mean vector, + // so let the PCA engine to compute it + PCA::DATA_AS_ROW, // indicate that the vectors + // are stored as matrix rows + // (use PCA::DATA_AS_COL if the vectors are + // the matrix columns) + maxComponents // specify, how many principal components to retain + ); + // if there is no test data, just return the computed basis, ready-to-use + if( !testset.data ) + return pca; + CV_Assert( testset.cols == pcaset.cols ); + + compressed.create(testset.rows, maxComponents, testset.type()); + + Mat reconstructed; + for( int i = 0; i < testset.rows; i++ ) + { + Mat vec = testset.row(i), coeffs = compressed.row(i), reconstructed; + // compress the vector, the result will be stored + // in the i-th row of the output matrix + pca.project(vec, coeffs); + // and then reconstruct it + pca.backProject(coeffs, reconstructed); + // and measure the error + printf("%d. diff = %g\n", i, norm(vec, reconstructed, NORM_L2)); + } + return pca; +} +@endcode +@sa calcCovarMatrix, mulTransposed, SVD, dft, dct +*/ +class CV_EXPORTS PCA +{ +public: + enum Flags { DATA_AS_ROW = 0, //!< indicates that the input samples are stored as matrix rows + DATA_AS_COL = 1, //!< indicates that the input samples are stored as matrix columns + USE_AVG = 2 //! + }; + + /** @brief default constructor + + The default constructor initializes an empty %PCA structure. The other + constructors initialize the structure and call PCA::operator()(). + */ + PCA(); + + /** @overload + @param data input samples stored as matrix rows or matrix columns. + @param mean optional mean value; if the matrix is empty (@c noArray()), + the mean is computed from the data. + @param flags operation flags; currently the parameter is only used to + specify the data layout (PCA::Flags) + @param maxComponents maximum number of components that %PCA should + retain; by default, all the components are retained. + */ + PCA(InputArray data, InputArray mean, int flags, int maxComponents = 0); + + /** @overload + @param data input samples stored as matrix rows or matrix columns. + @param mean optional mean value; if the matrix is empty (noArray()), + the mean is computed from the data. + @param flags operation flags; currently the parameter is only used to + specify the data layout (PCA::Flags) + @param retainedVariance Percentage of variance that PCA should retain. + Using this parameter will let the PCA decided how many components to + retain but it will always keep at least 2. + */ + PCA(InputArray data, InputArray mean, int flags, double retainedVariance); + + /** @brief performs %PCA + + The operator performs %PCA of the supplied dataset. It is safe to reuse + the same PCA structure for multiple datasets. That is, if the structure + has been previously used with another dataset, the existing internal + data is reclaimed and the new @ref eigenvalues, @ref eigenvectors and @ref + mean are allocated and computed. + + The computed @ref eigenvalues are sorted from the largest to the smallest and + the corresponding @ref eigenvectors are stored as eigenvectors rows. + + @param data input samples stored as the matrix rows or as the matrix + columns. + @param mean optional mean value; if the matrix is empty (noArray()), + the mean is computed from the data. + @param flags operation flags; currently the parameter is only used to + specify the data layout. (Flags) + @param maxComponents maximum number of components that PCA should + retain; by default, all the components are retained. + */ + PCA& operator()(InputArray data, InputArray mean, int flags, int maxComponents = 0); + + /** @overload + @param data input samples stored as the matrix rows or as the matrix + columns. + @param mean optional mean value; if the matrix is empty (noArray()), + the mean is computed from the data. + @param flags operation flags; currently the parameter is only used to + specify the data layout. (PCA::Flags) + @param retainedVariance Percentage of variance that %PCA should retain. + Using this parameter will let the %PCA decided how many components to + retain but it will always keep at least 2. + */ + PCA& operator()(InputArray data, InputArray mean, int flags, double retainedVariance); + + /** @brief Projects vector(s) to the principal component subspace. + + The methods project one or more vectors to the principal component + subspace, where each vector projection is represented by coefficients in + the principal component basis. The first form of the method returns the + matrix that the second form writes to the result. So the first form can + be used as a part of expression while the second form can be more + efficient in a processing loop. + @param vec input vector(s); must have the same dimensionality and the + same layout as the input data used at %PCA phase, that is, if + DATA_AS_ROW are specified, then `vec.cols==data.cols` + (vector dimensionality) and `vec.rows` is the number of vectors to + project, and the same is true for the PCA::DATA_AS_COL case. + */ + Mat project(InputArray vec) const; + + /** @overload + @param vec input vector(s); must have the same dimensionality and the + same layout as the input data used at PCA phase, that is, if + DATA_AS_ROW are specified, then `vec.cols==data.cols` + (vector dimensionality) and `vec.rows` is the number of vectors to + project, and the same is true for the PCA::DATA_AS_COL case. + @param result output vectors; in case of PCA::DATA_AS_COL, the + output matrix has as many columns as the number of input vectors, this + means that `result.cols==vec.cols` and the number of rows match the + number of principal components (for example, `maxComponents` parameter + passed to the constructor). + */ + void project(InputArray vec, OutputArray result) const; + + /** @brief Reconstructs vectors from their PC projections. + + The methods are inverse operations to PCA::project. They take PC + coordinates of projected vectors and reconstruct the original vectors. + Unless all the principal components have been retained, the + reconstructed vectors are different from the originals. But typically, + the difference is small if the number of components is large enough (but + still much smaller than the original vector dimensionality). As a + result, PCA is used. + @param vec coordinates of the vectors in the principal component + subspace, the layout and size are the same as of PCA::project output + vectors. + */ + Mat backProject(InputArray vec) const; + + /** @overload + @param vec coordinates of the vectors in the principal component + subspace, the layout and size are the same as of PCA::project output + vectors. + @param result reconstructed vectors; the layout and size are the same as + of PCA::project input vectors. + */ + void backProject(InputArray vec, OutputArray result) const; + + /** @brief write PCA objects + + Writes @ref eigenvalues @ref eigenvectors and @ref mean to specified FileStorage + */ + void write(FileStorage& fs) const; + + /** @brief load PCA objects + + Loads @ref eigenvalues @ref eigenvectors and @ref mean from specified FileNode + */ + void read(const FileNode& fn); + + Mat eigenvectors; //!< eigenvectors of the covariation matrix + Mat eigenvalues; //!< eigenvalues of the covariation matrix + Mat mean; //!< mean value subtracted before the projection and added after the back projection +}; + +/** @example samples/cpp/pca.cpp +An example using %PCA for dimensionality reduction while maintaining an amount of variance +*/ + +/** @example samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp +Check @ref tutorial_introduction_to_pca "the corresponding tutorial" for more details +*/ + +/** +@brief Linear Discriminant Analysis +@todo document this class +*/ +class CV_EXPORTS LDA +{ +public: + /** @brief constructor + Initializes a LDA with num_components (default 0). + */ + explicit LDA(int num_components = 0); + + /** Initializes and performs a Discriminant Analysis with Fisher's + Optimization Criterion on given data in src and corresponding labels + in labels. If 0 (or less) number of components are given, they are + automatically determined for given data in computation. + */ + LDA(InputArrayOfArrays src, InputArray labels, int num_components = 0); + + /** Serializes this object to a given filename. + */ + void save(const String& filename) const; + + /** Deserializes this object from a given filename. + */ + void load(const String& filename); + + /** Serializes this object to a given cv::FileStorage. + */ + void save(FileStorage& fs) const; + + /** Deserializes this object from a given cv::FileStorage. + */ + void load(const FileStorage& node); + + /** destructor + */ + ~LDA(); + + /** Compute the discriminants for data in src (row aligned) and labels. + */ + void compute(InputArrayOfArrays src, InputArray labels); + + /** Projects samples into the LDA subspace. + src may be one or more row aligned samples. + */ + Mat project(InputArray src); + + /** Reconstructs projections from the LDA subspace. + src may be one or more row aligned projections. + */ + Mat reconstruct(InputArray src); + + /** Returns the eigenvectors of this LDA. + */ + Mat eigenvectors() const { return _eigenvectors; } + + /** Returns the eigenvalues of this LDA. + */ + Mat eigenvalues() const { return _eigenvalues; } + + static Mat subspaceProject(InputArray W, InputArray mean, InputArray src); + static Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src); + +protected: + bool _dataAsRow; // unused, but needed for 3.0 ABI compatibility. + int _num_components; + Mat _eigenvectors; + Mat _eigenvalues; + void lda(InputArrayOfArrays src, InputArray labels); +}; + +/** @brief Singular Value Decomposition + +Class for computing Singular Value Decomposition of a floating-point +matrix. The Singular Value Decomposition is used to solve least-square +problems, under-determined linear systems, invert matrices, compute +condition numbers, and so on. + +If you want to compute a condition number of a matrix or an absolute value of +its determinant, you do not need `u` and `vt`. You can pass +flags=SVD::NO_UV|... . Another flag SVD::FULL_UV indicates that full-size u +and vt must be computed, which is not necessary most of the time. + +@sa invert, solve, eigen, determinant +*/ +class CV_EXPORTS SVD +{ +public: + enum Flags { + /** allow the algorithm to modify the decomposed matrix; it can save space and speed up + processing. currently ignored. */ + MODIFY_A = 1, + /** indicates that only a vector of singular values `w` is to be processed, while u and vt + will be set to empty matrices */ + NO_UV = 2, + /** when the matrix is not square, by default the algorithm produces u and vt matrices of + sufficiently large size for the further A reconstruction; if, however, FULL_UV flag is + specified, u and vt will be full-size square orthogonal matrices.*/ + FULL_UV = 4 + }; + + /** @brief the default constructor + + initializes an empty SVD structure + */ + SVD(); + + /** @overload + initializes an empty SVD structure and then calls SVD::operator() + @param src decomposed matrix. The depth has to be CV_32F or CV_64F. + @param flags operation flags (SVD::Flags) + */ + SVD( InputArray src, int flags = 0 ); + + /** @brief the operator that performs SVD. The previously allocated u, w and vt are released. + + The operator performs the singular value decomposition of the supplied + matrix. The u,`vt` , and the vector of singular values w are stored in + the structure. The same SVD structure can be reused many times with + different matrices. Each time, if needed, the previous u,`vt` , and w + are reclaimed and the new matrices are created, which is all handled by + Mat::create. + @param src decomposed matrix. The depth has to be CV_32F or CV_64F. + @param flags operation flags (SVD::Flags) + */ + SVD& operator ()( InputArray src, int flags = 0 ); + + /** @brief decomposes matrix and stores the results to user-provided matrices + + The methods/functions perform SVD of matrix. Unlike SVD::SVD constructor + and SVD::operator(), they store the results to the user-provided + matrices: + + @code{.cpp} + Mat A, w, u, vt; + SVD::compute(A, w, u, vt); + @endcode + + @param src decomposed matrix. The depth has to be CV_32F or CV_64F. + @param w calculated singular values + @param u calculated left singular vectors + @param vt transposed matrix of right singular vectors + @param flags operation flags - see SVD::Flags. + */ + static void compute( InputArray src, OutputArray w, + OutputArray u, OutputArray vt, int flags = 0 ); + + /** @overload + computes singular values of a matrix + @param src decomposed matrix. The depth has to be CV_32F or CV_64F. + @param w calculated singular values + @param flags operation flags - see SVD::Flags. + */ + static void compute( InputArray src, OutputArray w, int flags = 0 ); + + /** @brief performs back substitution + */ + static void backSubst( InputArray w, InputArray u, + InputArray vt, InputArray rhs, + OutputArray dst ); + + /** @brief solves an under-determined singular linear system + + The method finds a unit-length solution x of a singular linear system + A\*x = 0. Depending on the rank of A, there can be no solutions, a + single solution or an infinite number of solutions. In general, the + algorithm solves the following problem: + \f[dst = \arg \min _{x: \| x \| =1} \| src \cdot x \|\f] + @param src left-hand-side matrix. + @param dst found solution. + */ + static void solveZ( InputArray src, OutputArray dst ); + + /** @brief performs a singular value back substitution. + + The method calculates a back substitution for the specified right-hand + side: + + \f[\texttt{x} = \texttt{vt} ^T \cdot diag( \texttt{w} )^{-1} \cdot \texttt{u} ^T \cdot \texttt{rhs} \sim \texttt{A} ^{-1} \cdot \texttt{rhs}\f] + + Using this technique you can either get a very accurate solution of the + convenient linear system, or the best (in the least-squares terms) + pseudo-solution of an overdetermined linear system. + + @param rhs right-hand side of a linear system (u\*w\*v')\*dst = rhs to + be solved, where A has been previously decomposed. + + @param dst found solution of the system. + + @note Explicit SVD with the further back substitution only makes sense + if you need to solve many linear systems with the same left-hand side + (for example, src ). If all you need is to solve a single system + (possibly with multiple rhs immediately available), simply call solve + add pass #DECOMP_SVD there. It does absolutely the same thing. + */ + void backSubst( InputArray rhs, OutputArray dst ) const; + + /** @todo document */ + template static + void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt ); + + /** @todo document */ + template static + void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w ); + + /** @todo document */ + template static + void backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u, const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, Matx<_Tp, n, nb>& dst ); + + Mat u, w, vt; +}; + +/** @brief Random Number Generator + +Random number generator. It encapsulates the state (currently, a 64-bit +integer) and has methods to return scalar random values and to fill +arrays with random values. Currently it supports uniform and Gaussian +(normal) distributions. The generator uses Multiply-With-Carry +algorithm, introduced by G. Marsaglia ( + ). +Gaussian-distribution random numbers are generated using the Ziggurat +algorithm ( ), +introduced by G. Marsaglia and W. W. Tsang. +*/ +class CV_EXPORTS RNG +{ +public: + enum { UNIFORM = 0, + NORMAL = 1 + }; + + /** @brief constructor + + These are the RNG constructors. The first form sets the state to some + pre-defined value, equal to 2\*\*32-1 in the current implementation. The + second form sets the state to the specified value. If you passed state=0 + , the constructor uses the above default value instead to avoid the + singular random number sequence, consisting of all zeros. + */ + RNG(); + /** @overload + @param state 64-bit value used to initialize the RNG. + */ + RNG(uint64 state); + /**The method updates the state using the MWC algorithm and returns the + next 32-bit random number.*/ + unsigned next(); + + /**Each of the methods updates the state using the MWC algorithm and + returns the next random number of the specified type. In case of integer + types, the returned number is from the available value range for the + specified type. In case of floating-point types, the returned value is + from [0,1) range. + */ + operator uchar(); + /** @overload */ + operator schar(); + /** @overload */ + operator ushort(); + /** @overload */ + operator short(); + /** @overload */ + operator unsigned(); + /** @overload */ + operator int(); + /** @overload */ + operator float(); + /** @overload */ + operator double(); + + /** @brief returns a random integer sampled uniformly from [0, N). + + The methods transform the state using the MWC algorithm and return the + next random number. The first form is equivalent to RNG::next . The + second form returns the random number modulo N , which means that the + result is in the range [0, N) . + */ + unsigned operator ()(); + /** @overload + @param N upper non-inclusive boundary of the returned random number. + */ + unsigned operator ()(unsigned N); + + /** @brief returns uniformly distributed integer random number from [a,b) range + + The methods transform the state using the MWC algorithm and return the + next uniformly-distributed random number of the specified type, deduced + from the input parameter type, from the range [a, b) . There is a nuance + illustrated by the following sample: + + @code{.cpp} + RNG rng; + + // always produces 0 + double a = rng.uniform(0, 1); + + // produces double from [0, 1) + double a1 = rng.uniform((double)0, (double)1); + + // produces float from [0, 1) + float b = rng.uniform(0.f, 1.f); + + // produces double from [0, 1) + double c = rng.uniform(0., 1.); + + // may cause compiler error because of ambiguity: + // RNG::uniform(0, (int)0.999999)? or RNG::uniform((double)0, 0.99999)? + double d = rng.uniform(0, 0.999999); + @endcode + + The compiler does not take into account the type of the variable to + which you assign the result of RNG::uniform . The only thing that + matters to the compiler is the type of a and b parameters. So, if you + want a floating-point random number, but the range boundaries are + integer numbers, either put dots in the end, if they are constants, or + use explicit type cast operators, as in the a1 initialization above. + @param a lower inclusive boundary of the returned random number. + @param b upper non-inclusive boundary of the returned random number. + */ + int uniform(int a, int b); + /** @overload */ + float uniform(float a, float b); + /** @overload */ + double uniform(double a, double b); + + /** @brief Fills arrays with random numbers. + + @param mat 2D or N-dimensional matrix; currently matrices with more than + 4 channels are not supported by the methods, use Mat::reshape as a + possible workaround. + @param distType distribution type, RNG::UNIFORM or RNG::NORMAL. + @param a first distribution parameter; in case of the uniform + distribution, this is an inclusive lower boundary, in case of the normal + distribution, this is a mean value. + @param b second distribution parameter; in case of the uniform + distribution, this is a non-inclusive upper boundary, in case of the + normal distribution, this is a standard deviation (diagonal of the + standard deviation matrix or the full standard deviation matrix). + @param saturateRange pre-saturation flag; for uniform distribution only; + if true, the method will first convert a and b to the acceptable value + range (according to the mat datatype) and then will generate uniformly + distributed random numbers within the range [saturate(a), saturate(b)), + if saturateRange=false, the method will generate uniformly distributed + random numbers in the original range [a, b) and then will saturate them, + it means, for example, that + theRNG().fill(mat_8u, RNG::UNIFORM, -DBL_MAX, DBL_MAX) will likely + produce array mostly filled with 0's and 255's, since the range (0, 255) + is significantly smaller than [-DBL_MAX, DBL_MAX). + + Each of the methods fills the matrix with the random values from the + specified distribution. As the new numbers are generated, the RNG state + is updated accordingly. In case of multiple-channel images, every + channel is filled independently, which means that RNG cannot generate + samples from the multi-dimensional Gaussian distribution with + non-diagonal covariance matrix directly. To do that, the method + generates samples from multi-dimensional standard Gaussian distribution + with zero mean and identity covariation matrix, and then transforms them + using transform to get samples from the specified Gaussian distribution. + */ + void fill( InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange = false ); + + /** @brief Returns the next random number sampled from the Gaussian distribution + @param sigma standard deviation of the distribution. + + The method transforms the state using the MWC algorithm and returns the + next random number from the Gaussian distribution N(0,sigma) . That is, + the mean value of the returned random numbers is zero and the standard + deviation is the specified sigma . + */ + double gaussian(double sigma); + + uint64 state; + + bool operator ==(const RNG& other) const; +}; + +/** @brief Mersenne Twister random number generator + +Inspired by http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/CODES/mt19937ar.c +@todo document +*/ +class CV_EXPORTS RNG_MT19937 +{ +public: + RNG_MT19937(); + RNG_MT19937(unsigned s); + void seed(unsigned s); + + unsigned next(); + + operator int(); + operator unsigned(); + operator float(); + operator double(); + + unsigned operator ()(unsigned N); + unsigned operator ()(); + + /** @brief returns uniformly distributed integer random number from [a,b) range*/ + int uniform(int a, int b); + /** @brief returns uniformly distributed floating-point random number from [a,b) range*/ + float uniform(float a, float b); + /** @brief returns uniformly distributed double-precision floating-point random number from [a,b) range*/ + double uniform(double a, double b); + +private: + enum PeriodParameters {N = 624, M = 397}; + unsigned state[N]; + int mti; +}; + +//! @} core_array + +//! @addtogroup core_cluster +//! @{ + +/** @example samples/cpp/kmeans.cpp +An example on K-means clustering +*/ + +/** @brief Finds centers of clusters and groups input samples around the clusters. + +The function kmeans implements a k-means algorithm that finds the centers of cluster_count clusters +and groups the input samples around the clusters. As an output, \f$\texttt{bestLabels}_i\f$ contains a +0-based cluster index for the sample stored in the \f$i^{th}\f$ row of the samples matrix. + +@note +- (Python) An example on K-means clustering can be found at + opencv_source_code/samples/python/kmeans.py +@param data Data for clustering. An array of N-Dimensional points with float coordinates is needed. +Examples of this array can be: +- Mat points(count, 2, CV_32F); +- Mat points(count, 1, CV_32FC2); +- Mat points(1, count, CV_32FC2); +- std::vector\ points(sampleCount); +@param K Number of clusters to split the set by. +@param bestLabels Input/output integer array that stores the cluster indices for every sample. +@param criteria The algorithm termination criteria, that is, the maximum number of iterations and/or +the desired accuracy. The accuracy is specified as criteria.epsilon. As soon as each of the cluster +centers moves by less than criteria.epsilon on some iteration, the algorithm stops. +@param attempts Flag to specify the number of times the algorithm is executed using different +initial labellings. The algorithm returns the labels that yield the best compactness (see the last +function parameter). +@param flags Flag that can take values of cv::KmeansFlags +@param centers Output matrix of the cluster centers, one row per each cluster center. +@return The function returns the compactness measure that is computed as +\f[\sum _i \| \texttt{samples} _i - \texttt{centers} _{ \texttt{labels} _i} \| ^2\f] +after every attempt. The best (minimum) value is chosen and the corresponding labels and the +compactness value are returned by the function. Basically, you can use only the core of the +function, set the number of attempts to 1, initialize labels each time using a custom algorithm, +pass them with the ( flags = #KMEANS_USE_INITIAL_LABELS ) flag, and then choose the best +(most-compact) clustering. +*/ +CV_EXPORTS_W double kmeans( InputArray data, int K, InputOutputArray bestLabels, + TermCriteria criteria, int attempts, + int flags, OutputArray centers = noArray() ); + +//! @} core_cluster + +//! @addtogroup core_basic +//! @{ + +/////////////////////////////// Formatted output of cv::Mat /////////////////////////// + +/** @todo document */ +class CV_EXPORTS Formatted +{ +public: + virtual const char* next() = 0; + virtual void reset() = 0; + virtual ~Formatted(); +}; + +/** @todo document */ +class CV_EXPORTS Formatter +{ +public: + enum { FMT_DEFAULT = 0, + FMT_MATLAB = 1, + FMT_CSV = 2, + FMT_PYTHON = 3, + FMT_NUMPY = 4, + FMT_C = 5 + }; + + virtual ~Formatter(); + + virtual Ptr format(const Mat& mtx) const = 0; + + virtual void set32fPrecision(int p = 8) = 0; + virtual void set64fPrecision(int p = 16) = 0; + virtual void setMultiline(bool ml = true) = 0; + + static Ptr get(int fmt = FMT_DEFAULT); + +}; + +static inline +String& operator << (String& out, Ptr fmtd) +{ + fmtd->reset(); + for(const char* str = fmtd->next(); str; str = fmtd->next()) + out += cv::String(str); + return out; +} + +static inline +String& operator << (String& out, const Mat& mtx) +{ + return out << Formatter::get()->format(mtx); +} + +//////////////////////////////////////// Algorithm //////////////////////////////////// + +class CV_EXPORTS Algorithm; + +template struct ParamType {}; + + +/** @brief This is a base class for all more or less complex algorithms in OpenCV + +especially for classes of algorithms, for which there can be multiple implementations. The examples +are stereo correspondence (for which there are algorithms like block matching, semi-global block +matching, graph-cut etc.), background subtraction (which can be done using mixture-of-gaussians +models, codebook-based algorithm etc.), optical flow (block matching, Lucas-Kanade, Horn-Schunck +etc.). + +Here is example of SimpleBlobDetector use in your application via Algorithm interface: +@snippet snippets/core_various.cpp Algorithm +*/ +class CV_EXPORTS_W Algorithm +{ +public: + Algorithm(); + virtual ~Algorithm(); + + /** @brief Clears the algorithm state + */ + CV_WRAP virtual void clear() {} + + /** @brief Stores algorithm parameters in a file storage + */ + virtual void write(FileStorage& fs) const { CV_UNUSED(fs); } + + /** @brief simplified API for language bindings + * @overload + */ + CV_WRAP void write(const Ptr& fs, const String& name = String()) const; + + /** @brief Reads algorithm parameters from a file storage + */ + CV_WRAP virtual void read(const FileNode& fn) { CV_UNUSED(fn); } + + /** @brief Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read + */ + CV_WRAP virtual bool empty() const { return false; } + + /** @brief Reads algorithm from the file node + + This is static template method of Algorithm. It's usage is following (in the case of SVM): + @code + cv::FileStorage fsRead("example.xml", FileStorage::READ); + Ptr svm = Algorithm::read(fsRead.root()); + @endcode + In order to make this method work, the derived class must overwrite Algorithm::read(const + FileNode& fn) and also have static create() method without parameters + (or with all the optional parameters) + */ + template static Ptr<_Tp> read(const FileNode& fn) + { + Ptr<_Tp> obj = _Tp::create(); + obj->read(fn); + return !obj->empty() ? obj : Ptr<_Tp>(); + } + + /** @brief Loads algorithm from the file + + @param filename Name of the file to read. + @param objname The optional name of the node to read (if empty, the first top-level node will be used) + + This is static template method of Algorithm. It's usage is following (in the case of SVM): + @code + Ptr svm = Algorithm::load("my_svm_model.xml"); + @endcode + In order to make this method work, the derived class must overwrite Algorithm::read(const + FileNode& fn). + */ + template static Ptr<_Tp> load(const String& filename, const String& objname=String()) + { + FileStorage fs(filename, FileStorage::READ); + CV_Assert(fs.isOpened()); + FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname]; + if (fn.empty()) return Ptr<_Tp>(); + Ptr<_Tp> obj = _Tp::create(); + obj->read(fn); + return !obj->empty() ? obj : Ptr<_Tp>(); + } + + /** @brief Loads algorithm from a String + + @param strModel The string variable containing the model you want to load. + @param objname The optional name of the node to read (if empty, the first top-level node will be used) + + This is static template method of Algorithm. It's usage is following (in the case of SVM): + @code + Ptr svm = Algorithm::loadFromString(myStringModel); + @endcode + */ + template static Ptr<_Tp> loadFromString(const String& strModel, const String& objname=String()) + { + FileStorage fs(strModel, FileStorage::READ + FileStorage::MEMORY); + FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname]; + Ptr<_Tp> obj = _Tp::create(); + obj->read(fn); + return !obj->empty() ? obj : Ptr<_Tp>(); + } + + /** Saves the algorithm to a file. + In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs). */ + CV_WRAP virtual void save(const String& filename) const; + + /** Returns the algorithm string identifier. + This string is used as top level xml/yml node tag when the object is saved to a file or string. */ + CV_WRAP virtual String getDefaultName() const; + +protected: + void writeFormat(FileStorage& fs) const; +}; + +struct Param { + enum { INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7, + UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12 }; +}; + + + +template<> struct ParamType +{ + typedef bool const_param_type; + typedef bool member_type; + + enum { type = Param::BOOLEAN }; +}; + +template<> struct ParamType +{ + typedef int const_param_type; + typedef int member_type; + + enum { type = Param::INT }; +}; + +template<> struct ParamType +{ + typedef double const_param_type; + typedef double member_type; + + enum { type = Param::REAL }; +}; + +template<> struct ParamType +{ + typedef const String& const_param_type; + typedef String member_type; + + enum { type = Param::STRING }; +}; + +template<> struct ParamType +{ + typedef const Mat& const_param_type; + typedef Mat member_type; + + enum { type = Param::MAT }; +}; + +template<> struct ParamType > +{ + typedef const std::vector& const_param_type; + typedef std::vector member_type; + + enum { type = Param::MAT_VECTOR }; +}; + +template<> struct ParamType +{ + typedef const Ptr& const_param_type; + typedef Ptr member_type; + + enum { type = Param::ALGORITHM }; +}; + +template<> struct ParamType +{ + typedef float const_param_type; + typedef float member_type; + + enum { type = Param::FLOAT }; +}; + +template<> struct ParamType +{ + typedef unsigned const_param_type; + typedef unsigned member_type; + + enum { type = Param::UNSIGNED_INT }; +}; + +template<> struct ParamType +{ + typedef uint64 const_param_type; + typedef uint64 member_type; + + enum { type = Param::UINT64 }; +}; + +template<> struct ParamType +{ + typedef uchar const_param_type; + typedef uchar member_type; + + enum { type = Param::UCHAR }; +}; + +template<> struct ParamType +{ + typedef const Scalar& const_param_type; + typedef Scalar member_type; + + enum { type = Param::SCALAR }; +}; + +//! @} core_basic + +} //namespace cv + +#include "opencv2/core/operations.hpp" +#include "opencv2/core/cvstd.inl.hpp" +#include "opencv2/core/utility.hpp" +#include "opencv2/core/optim.hpp" +#include "opencv2/core/ovx.hpp" + +#endif /*OPENCV_CORE_HPP*/ diff --git a/3rdparty/opencv/include/opencv2/core/affine.hpp b/3rdparty/opencv/include/opencv2/core/affine.hpp new file mode 100644 index 00000000..7e2ed307 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/affine.hpp @@ -0,0 +1,678 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_AFFINE3_HPP +#define OPENCV_CORE_AFFINE3_HPP + +#ifdef __cplusplus + +#include + +namespace cv +{ + +//! @addtogroup core +//! @{ + + /** @brief Affine transform + * + * It represents a 4x4 homogeneous transformation matrix \f$T\f$ + * + * \f[T = + * \begin{bmatrix} + * R & t\\ + * 0 & 1\\ + * \end{bmatrix} + * \f] + * + * where \f$R\f$ is a 3x3 rotation matrix and \f$t\f$ is a 3x1 translation vector. + * + * You can specify \f$R\f$ either by a 3x3 rotation matrix or by a 3x1 rotation vector, + * which is converted to a 3x3 rotation matrix by the Rodrigues formula. + * + * To construct a matrix \f$T\f$ representing first rotation around the axis \f$r\f$ with rotation + * angle \f$|r|\f$ in radian (right hand rule) and then translation by the vector \f$t\f$, you can use + * + * @code + * cv::Vec3f r, t; + * cv::Affine3f T(r, t); + * @endcode + * + * If you already have the rotation matrix \f$R\f$, then you can use + * + * @code + * cv::Matx33f R; + * cv::Affine3f T(R, t); + * @endcode + * + * To extract the rotation matrix \f$R\f$ from \f$T\f$, use + * + * @code + * cv::Matx33f R = T.rotation(); + * @endcode + * + * To extract the translation vector \f$t\f$ from \f$T\f$, use + * + * @code + * cv::Vec3f t = T.translation(); + * @endcode + * + * To extract the rotation vector \f$r\f$ from \f$T\f$, use + * + * @code + * cv::Vec3f r = T.rvec(); + * @endcode + * + * Note that since the mapping from rotation vectors to rotation matrices + * is many to one. The returned rotation vector is not necessarily the one + * you used before to set the matrix. + * + * If you have two transformations \f$T = T_1 * T_2\f$, use + * + * @code + * cv::Affine3f T, T1, T2; + * T = T2.concatenate(T1); + * @endcode + * + * To get the inverse transform of \f$T\f$, use + * + * @code + * cv::Affine3f T, T_inv; + * T_inv = T.inv(); + * @endcode + * + */ + template + class Affine3 + { + public: + typedef T float_type; + typedef Matx Mat3; + typedef Matx Mat4; + typedef Vec Vec3; + + //! Default constructor. It represents a 4x4 identity matrix. + Affine3(); + + //! Augmented affine matrix + Affine3(const Mat4& affine); + + /** + * The resulting 4x4 matrix is + * + * \f[ + * \begin{bmatrix} + * R & t\\ + * 0 & 1\\ + * \end{bmatrix} + * \f] + * + * @param R 3x3 rotation matrix. + * @param t 3x1 translation vector. + */ + Affine3(const Mat3& R, const Vec3& t = Vec3::all(0)); + + /** + * Rodrigues vector. + * + * The last row of the current matrix is set to [0,0,0,1]. + * + * @param rvec 3x1 rotation vector. Its direction indicates the rotation axis and its length + * indicates the rotation angle in radian (using right hand rule). + * @param t 3x1 translation vector. + */ + Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0)); + + /** + * Combines all constructors above. Supports 4x4, 3x4, 3x3, 1x3, 3x1 sizes of data matrix. + * + * The last row of the current matrix is set to [0,0,0,1] when data is not 4x4. + * + * @param data 1-channel matrix. + * when it is 4x4, it is copied to the current matrix and t is not used. + * When it is 3x4, it is copied to the upper part 3x4 of the current matrix and t is not used. + * When it is 3x3, it is copied to the upper left 3x3 part of the current matrix. + * When it is 3x1 or 1x3, it is treated as a rotation vector and the Rodrigues formula is used + * to compute a 3x3 rotation matrix. + * @param t 3x1 translation vector. It is used only when data is neither 4x4 nor 3x4. + */ + explicit Affine3(const Mat& data, const Vec3& t = Vec3::all(0)); + + //! From 16-element array + explicit Affine3(const float_type* vals); + + //! Create an 4x4 identity transform + static Affine3 Identity(); + + /** + * Rotation matrix. + * + * Copy the rotation matrix to the upper left 3x3 part of the current matrix. + * The remaining elements of the current matrix are not changed. + * + * @param R 3x3 rotation matrix. + * + */ + void rotation(const Mat3& R); + + /** + * Rodrigues vector. + * + * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected. + * + * @param rvec 3x1 rotation vector. The direction indicates the rotation axis and + * its length indicates the rotation angle in radian (using the right thumb convention). + */ + void rotation(const Vec3& rvec); + + /** + * Combines rotation methods above. Supports 3x3, 1x3, 3x1 sizes of data matrix. + * + * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected. + * + * @param data 1-channel matrix. + * When it is a 3x3 matrix, it sets the upper left 3x3 part of the current matrix. + * When it is a 1x3 or 3x1 matrix, it is used as a rotation vector. The Rodrigues formula + * is used to compute the rotation matrix and sets the upper left 3x3 part of the current matrix. + */ + void rotation(const Mat& data); + + /** + * Copy the 3x3 matrix L to the upper left part of the current matrix + * + * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected. + * + * @param L 3x3 matrix. + */ + void linear(const Mat3& L); + + /** + * Copy t to the first three elements of the last column of the current matrix + * + * It sets the upper right 3x1 part of the matrix. The remaining part is unaffected. + * + * @param t 3x1 translation vector. + */ + void translation(const Vec3& t); + + //! @return the upper left 3x3 part + Mat3 rotation() const; + + //! @return the upper left 3x3 part + Mat3 linear() const; + + //! @return the upper right 3x1 part + Vec3 translation() const; + + //! Rodrigues vector. + //! @return a vector representing the upper left 3x3 rotation matrix of the current matrix. + //! @warning Since the mapping between rotation vectors and rotation matrices is many to one, + //! this function returns only one rotation vector that represents the current rotation matrix, + //! which is not necessarily the same one set by `rotation(const Vec3& rvec)`. + Vec3 rvec() const; + + //! @return the inverse of the current matrix. + Affine3 inv(int method = cv::DECOMP_SVD) const; + + //! a.rotate(R) is equivalent to Affine(R, 0) * a; + Affine3 rotate(const Mat3& R) const; + + //! a.rotate(rvec) is equivalent to Affine(rvec, 0) * a; + Affine3 rotate(const Vec3& rvec) const; + + //! a.translate(t) is equivalent to Affine(E, t) * a, where E is an identity matrix + Affine3 translate(const Vec3& t) const; + + //! a.concatenate(affine) is equivalent to affine * a; + Affine3 concatenate(const Affine3& affine) const; + + template operator Affine3() const; + + template Affine3 cast() const; + + Mat4 matrix; + +#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H + Affine3(const Eigen::Transform& affine); + Affine3(const Eigen::Transform& affine); + operator Eigen::Transform() const; + operator Eigen::Transform() const; +#endif + }; + + template static + Affine3 operator*(const Affine3& affine1, const Affine3& affine2); + + //! V is a 3-element vector with member fields x, y and z + template static + V operator*(const Affine3& affine, const V& vector); + + typedef Affine3 Affine3f; + typedef Affine3 Affine3d; + + static Vec3f operator*(const Affine3f& affine, const Vec3f& vector); + static Vec3d operator*(const Affine3d& affine, const Vec3d& vector); + + template class DataType< Affine3<_Tp> > + { + public: + typedef Affine3<_Tp> value_type; + typedef Affine3::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 16, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; + }; + + namespace traits { + template + struct Depth< Affine3<_Tp> > { enum { value = Depth<_Tp>::value }; }; + template + struct Type< Affine3<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 16) }; }; + } // namespace + +//! @} core + +} + +//! @cond IGNORED + +/////////////////////////////////////////////////////////////////////////////////// +// Implementation + +template inline +cv::Affine3::Affine3() + : matrix(Mat4::eye()) +{} + +template inline +cv::Affine3::Affine3(const Mat4& affine) + : matrix(affine) +{} + +template inline +cv::Affine3::Affine3(const Mat3& R, const Vec3& t) +{ + rotation(R); + translation(t); + matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; + matrix.val[15] = 1; +} + +template inline +cv::Affine3::Affine3(const Vec3& _rvec, const Vec3& t) +{ + rotation(_rvec); + translation(t); + matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; + matrix.val[15] = 1; +} + +template inline +cv::Affine3::Affine3(const cv::Mat& data, const Vec3& t) +{ + CV_Assert(data.type() == cv::traits::Type::value); + CV_Assert(data.channels() == 1); + + if (data.cols == 4 && data.rows == 4) + { + data.copyTo(matrix); + return; + } + else if (data.cols == 4 && data.rows == 3) + { + rotation(data(Rect(0, 0, 3, 3))); + translation(data(Rect(3, 0, 1, 3))); + } + else + { + rotation(data); + translation(t); + } + + matrix.val[12] = matrix.val[13] = matrix.val[14] = 0; + matrix.val[15] = 1; +} + +template inline +cv::Affine3::Affine3(const float_type* vals) : matrix(vals) +{} + +template inline +cv::Affine3 cv::Affine3::Identity() +{ + return Affine3(cv::Affine3::Mat4::eye()); +} + +template inline +void cv::Affine3::rotation(const Mat3& R) +{ + linear(R); +} + +template inline +void cv::Affine3::rotation(const Vec3& _rvec) +{ + double theta = norm(_rvec); + + if (theta < DBL_EPSILON) + rotation(Mat3::eye()); + else + { + double c = std::cos(theta); + double s = std::sin(theta); + double c1 = 1. - c; + double itheta = (theta != 0) ? 1./theta : 0.; + + Point3_ r = _rvec*itheta; + + Mat3 rrt( r.x*r.x, r.x*r.y, r.x*r.z, r.x*r.y, r.y*r.y, r.y*r.z, r.x*r.z, r.y*r.z, r.z*r.z ); + Mat3 r_x( 0, -r.z, r.y, r.z, 0, -r.x, -r.y, r.x, 0 ); + + // R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x] + // where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0] + Mat3 R = c*Mat3::eye() + c1*rrt + s*r_x; + + rotation(R); + } +} + +//Combines rotation methods above. Supports 3x3, 1x3, 3x1 sizes of data matrix; +template inline +void cv::Affine3::rotation(const cv::Mat& data) +{ + CV_Assert(data.type() == cv::traits::Type::value); + CV_Assert(data.channels() == 1); + + if (data.cols == 3 && data.rows == 3) + { + Mat3 R; + data.copyTo(R); + rotation(R); + } + else if ((data.cols == 3 && data.rows == 1) || (data.cols == 1 && data.rows == 3)) + { + Vec3 _rvec; + data.reshape(1, 3).copyTo(_rvec); + rotation(_rvec); + } + else + CV_Error(Error::StsError, "Input matrix can only be 3x3, 1x3 or 3x1"); +} + +template inline +void cv::Affine3::linear(const Mat3& L) +{ + matrix.val[0] = L.val[0]; matrix.val[1] = L.val[1]; matrix.val[ 2] = L.val[2]; + matrix.val[4] = L.val[3]; matrix.val[5] = L.val[4]; matrix.val[ 6] = L.val[5]; + matrix.val[8] = L.val[6]; matrix.val[9] = L.val[7]; matrix.val[10] = L.val[8]; +} + +template inline +void cv::Affine3::translation(const Vec3& t) +{ + matrix.val[3] = t[0]; matrix.val[7] = t[1]; matrix.val[11] = t[2]; +} + +template inline +typename cv::Affine3::Mat3 cv::Affine3::rotation() const +{ + return linear(); +} + +template inline +typename cv::Affine3::Mat3 cv::Affine3::linear() const +{ + typename cv::Affine3::Mat3 R; + R.val[0] = matrix.val[0]; R.val[1] = matrix.val[1]; R.val[2] = matrix.val[ 2]; + R.val[3] = matrix.val[4]; R.val[4] = matrix.val[5]; R.val[5] = matrix.val[ 6]; + R.val[6] = matrix.val[8]; R.val[7] = matrix.val[9]; R.val[8] = matrix.val[10]; + return R; +} + +template inline +typename cv::Affine3::Vec3 cv::Affine3::translation() const +{ + return Vec3(matrix.val[3], matrix.val[7], matrix.val[11]); +} + +template inline +typename cv::Affine3::Vec3 cv::Affine3::rvec() const +{ + cv::Vec3d w; + cv::Matx33d u, vt, R = rotation(); + cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A); + R = u * vt; + + double rx = R.val[7] - R.val[5]; + double ry = R.val[2] - R.val[6]; + double rz = R.val[3] - R.val[1]; + + double s = std::sqrt((rx*rx + ry*ry + rz*rz)*0.25); + double c = (R.val[0] + R.val[4] + R.val[8] - 1) * 0.5; + c = c > 1.0 ? 1.0 : c < -1.0 ? -1.0 : c; + double theta = acos(c); + + if( s < 1e-5 ) + { + if( c > 0 ) + rx = ry = rz = 0; + else + { + double t; + t = (R.val[0] + 1) * 0.5; + rx = std::sqrt(std::max(t, 0.0)); + t = (R.val[4] + 1) * 0.5; + ry = std::sqrt(std::max(t, 0.0)) * (R.val[1] < 0 ? -1.0 : 1.0); + t = (R.val[8] + 1) * 0.5; + rz = std::sqrt(std::max(t, 0.0)) * (R.val[2] < 0 ? -1.0 : 1.0); + + if( fabs(rx) < fabs(ry) && fabs(rx) < fabs(rz) && (R.val[5] > 0) != (ry*rz > 0) ) + rz = -rz; + theta /= std::sqrt(rx*rx + ry*ry + rz*rz); + rx *= theta; + ry *= theta; + rz *= theta; + } + } + else + { + double vth = 1/(2*s); + vth *= theta; + rx *= vth; ry *= vth; rz *= vth; + } + + return cv::Vec3d(rx, ry, rz); +} + +template inline +cv::Affine3 cv::Affine3::inv(int method) const +{ + return matrix.inv(method); +} + +template inline +cv::Affine3 cv::Affine3::rotate(const Mat3& R) const +{ + Mat3 Lc = linear(); + Vec3 tc = translation(); + Mat4 result; + result.val[12] = result.val[13] = result.val[14] = 0; + result.val[15] = 1; + + for(int j = 0; j < 3; ++j) + { + for(int i = 0; i < 3; ++i) + { + float_type value = 0; + for(int k = 0; k < 3; ++k) + value += R(j, k) * Lc(k, i); + result(j, i) = value; + } + + result(j, 3) = R.row(j).dot(tc.t()); + } + return result; +} + +template inline +cv::Affine3 cv::Affine3::rotate(const Vec3& _rvec) const +{ + return rotate(Affine3f(_rvec).rotation()); +} + +template inline +cv::Affine3 cv::Affine3::translate(const Vec3& t) const +{ + Mat4 m = matrix; + m.val[ 3] += t[0]; + m.val[ 7] += t[1]; + m.val[11] += t[2]; + return m; +} + +template inline +cv::Affine3 cv::Affine3::concatenate(const Affine3& affine) const +{ + return (*this).rotate(affine.rotation()).translate(affine.translation()); +} + +template template inline +cv::Affine3::operator Affine3() const +{ + return Affine3(matrix); +} + +template template inline +cv::Affine3 cv::Affine3::cast() const +{ + return Affine3(matrix); +} + +template inline +cv::Affine3 cv::operator*(const cv::Affine3& affine1, const cv::Affine3& affine2) +{ + return affine2.concatenate(affine1); +} + +template inline +V cv::operator*(const cv::Affine3& affine, const V& v) +{ + const typename Affine3::Mat4& m = affine.matrix; + + V r; + r.x = m.val[0] * v.x + m.val[1] * v.y + m.val[ 2] * v.z + m.val[ 3]; + r.y = m.val[4] * v.x + m.val[5] * v.y + m.val[ 6] * v.z + m.val[ 7]; + r.z = m.val[8] * v.x + m.val[9] * v.y + m.val[10] * v.z + m.val[11]; + return r; +} + +static inline +cv::Vec3f cv::operator*(const cv::Affine3f& affine, const cv::Vec3f& v) +{ + const cv::Matx44f& m = affine.matrix; + cv::Vec3f r; + r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; + r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; + r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; + return r; +} + +static inline +cv::Vec3d cv::operator*(const cv::Affine3d& affine, const cv::Vec3d& v) +{ + const cv::Matx44d& m = affine.matrix; + cv::Vec3d r; + r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3]; + r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7]; + r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11]; + return r; +} + + + +#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H + +template inline +cv::Affine3::Affine3(const Eigen::Transform& affine) +{ + cv::Mat(4, 4, cv::traits::Type::value, affine.matrix().data()).copyTo(matrix); +} + +template inline +cv::Affine3::Affine3(const Eigen::Transform& affine) +{ + Eigen::Transform a = affine; + cv::Mat(4, 4, cv::traits::Type::value, a.matrix().data()).copyTo(matrix); +} + +template inline +cv::Affine3::operator Eigen::Transform() const +{ + Eigen::Transform r; + cv::Mat hdr(4, 4, cv::traits::Type::value, r.matrix().data()); + cv::Mat(matrix, false).copyTo(hdr); + return r; +} + +template inline +cv::Affine3::operator Eigen::Transform() const +{ + return this->operator Eigen::Transform(); +} + +#endif /* defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H */ + +//! @endcond + +#endif /* __cplusplus */ + +#endif /* OPENCV_CORE_AFFINE3_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/base.hpp b/3rdparty/opencv/include/opencv2/core/base.hpp new file mode 100644 index 00000000..31cd7a82 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/base.hpp @@ -0,0 +1,707 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2014, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_BASE_HPP +#define OPENCV_CORE_BASE_HPP + +#ifndef __cplusplus +# error base.hpp header must be compiled as C++ +#endif + +#include "opencv2/opencv_modules.hpp" + +#include +#include + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/cvstd.hpp" + +namespace cv +{ + +//! @addtogroup core_utils +//! @{ + +namespace Error { +//! error codes +enum Code { + StsOk= 0, //!< everything is ok + StsBackTrace= -1, //!< pseudo error for back trace + StsError= -2, //!< unknown /unspecified error + StsInternal= -3, //!< internal error (bad state) + StsNoMem= -4, //!< insufficient memory + StsBadArg= -5, //!< function arg/param is bad + StsBadFunc= -6, //!< unsupported function + StsNoConv= -7, //!< iteration didn't converge + StsAutoTrace= -8, //!< tracing + HeaderIsNull= -9, //!< image header is NULL + BadImageSize= -10, //!< image size is invalid + BadOffset= -11, //!< offset is invalid + BadDataPtr= -12, //!< + BadStep= -13, //!< image step is wrong, this may happen for a non-continuous matrix. + BadModelOrChSeq= -14, //!< + BadNumChannels= -15, //!< bad number of channels, for example, some functions accept only single channel matrices. + BadNumChannel1U= -16, //!< + BadDepth= -17, //!< input image depth is not supported by the function + BadAlphaChannel= -18, //!< + BadOrder= -19, //!< number of dimensions is out of range + BadOrigin= -20, //!< incorrect input origin + BadAlign= -21, //!< incorrect input align + BadCallBack= -22, //!< + BadTileSize= -23, //!< + BadCOI= -24, //!< input COI is not supported + BadROISize= -25, //!< incorrect input roi + MaskIsTiled= -26, //!< + StsNullPtr= -27, //!< null pointer + StsVecLengthErr= -28, //!< incorrect vector length + StsFilterStructContentErr= -29, //!< incorrect filter structure content + StsKernelStructContentErr= -30, //!< incorrect transform kernel content + StsFilterOffsetErr= -31, //!< incorrect filter offset value + StsBadSize= -201, //!< the input/output structure size is incorrect + StsDivByZero= -202, //!< division by zero + StsInplaceNotSupported= -203, //!< in-place operation is not supported + StsObjectNotFound= -204, //!< request can't be completed + StsUnmatchedFormats= -205, //!< formats of input/output arrays differ + StsBadFlag= -206, //!< flag is wrong or not supported + StsBadPoint= -207, //!< bad CvPoint + StsBadMask= -208, //!< bad format of mask (neither 8uC1 nor 8sC1) + StsUnmatchedSizes= -209, //!< sizes of input/output structures do not match + StsUnsupportedFormat= -210, //!< the data format/type is not supported by the function + StsOutOfRange= -211, //!< some of parameters are out of range + StsParseError= -212, //!< invalid syntax/structure of the parsed file + StsNotImplemented= -213, //!< the requested function/feature is not implemented + StsBadMemBlock= -214, //!< an allocated block has been corrupted + StsAssert= -215, //!< assertion failed + GpuNotSupported= -216, //!< no CUDA support + GpuApiCallError= -217, //!< GPU API call error + OpenGlNotSupported= -218, //!< no OpenGL support + OpenGlApiCallError= -219, //!< OpenGL API call error + OpenCLApiCallError= -220, //!< OpenCL API call error + OpenCLDoubleNotSupported= -221, + OpenCLInitError= -222, //!< OpenCL initialization error + OpenCLNoAMDBlasFft= -223 +}; +} //Error + +//! @} core_utils + +//! @addtogroup core_array +//! @{ + +//! matrix decomposition types +enum DecompTypes { + /** Gaussian elimination with the optimal pivot element chosen. */ + DECOMP_LU = 0, + /** singular value decomposition (SVD) method; the system can be over-defined and/or the matrix + src1 can be singular */ + DECOMP_SVD = 1, + /** eigenvalue decomposition; the matrix src1 must be symmetrical */ + DECOMP_EIG = 2, + /** Cholesky \f$LL^T\f$ factorization; the matrix src1 must be symmetrical and positively + defined */ + DECOMP_CHOLESKY = 3, + /** QR factorization; the system can be over-defined and/or the matrix src1 can be singular */ + DECOMP_QR = 4, + /** while all the previous flags are mutually exclusive, this flag can be used together with + any of the previous; it means that the normal equations + \f$\texttt{src1}^T\cdot\texttt{src1}\cdot\texttt{dst}=\texttt{src1}^T\texttt{src2}\f$ are + solved instead of the original system + \f$\texttt{src1}\cdot\texttt{dst}=\texttt{src2}\f$ */ + DECOMP_NORMAL = 16 +}; + +/** norm types + +src1 and src2 denote input arrays. +*/ + +enum NormTypes { + /** + \f[ + norm = \forkthree + {\|\texttt{src1}\|_{L_{\infty}} = \max _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) } + {\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} = \max _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) } + {\frac{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} }{\|\texttt{src2}\|_{L_{\infty}} }}{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_INF}\) } + \f] + */ + NORM_INF = 1, + /** + \f[ + norm = \forkthree + {\| \texttt{src1} \| _{L_1} = \sum _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\)} + { \| \texttt{src1} - \texttt{src2} \| _{L_1} = \sum _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) } + { \frac{\|\texttt{src1}-\texttt{src2}\|_{L_1} }{\|\texttt{src2}\|_{L_1}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L1}\) } + \f]*/ + NORM_L1 = 2, + /** + \f[ + norm = \forkthree + { \| \texttt{src1} \| _{L_2} = \sqrt{\sum_I \texttt{src1}(I)^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) } + { \| \texttt{src1} - \texttt{src2} \| _{L_2} = \sqrt{\sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) } + { \frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) } + \f] + */ + NORM_L2 = 4, + /** + \f[ + norm = \forkthree + { \| \texttt{src1} \| _{L_2} ^{2} = \sum_I \texttt{src1}(I)^2} {if \(\texttt{normType} = \texttt{NORM_L2SQR}\)} + { \| \texttt{src1} - \texttt{src2} \| _{L_2} ^{2} = \sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2 }{if \(\texttt{normType} = \texttt{NORM_L2SQR}\) } + { \left(\frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}}\right)^2 }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) } + \f] + */ + NORM_L2SQR = 5, + /** + In the case of one input array, calculates the Hamming distance of the array from zero, + In the case of two input arrays, calculates the Hamming distance between the arrays. + */ + NORM_HAMMING = 6, + /** + Similar to NORM_HAMMING, but in the calculation, each two bits of the input sequence will + be added and treated as a single bit to be used in the same calculation as NORM_HAMMING. + */ + NORM_HAMMING2 = 7, + NORM_TYPE_MASK = 7, //!< bit-mask which can be used to separate norm type from norm flags + NORM_RELATIVE = 8, //!< flag + NORM_MINMAX = 32 //!< flag + }; + +//! comparison types +enum CmpTypes { CMP_EQ = 0, //!< src1 is equal to src2. + CMP_GT = 1, //!< src1 is greater than src2. + CMP_GE = 2, //!< src1 is greater than or equal to src2. + CMP_LT = 3, //!< src1 is less than src2. + CMP_LE = 4, //!< src1 is less than or equal to src2. + CMP_NE = 5 //!< src1 is unequal to src2. + }; + +//! generalized matrix multiplication flags +enum GemmFlags { GEMM_1_T = 1, //!< transposes src1 + GEMM_2_T = 2, //!< transposes src2 + GEMM_3_T = 4 //!< transposes src3 + }; + +enum DftFlags { + /** performs an inverse 1D or 2D transform instead of the default forward + transform. */ + DFT_INVERSE = 1, + /** scales the result: divide it by the number of array elements. Normally, it is + combined with DFT_INVERSE. */ + DFT_SCALE = 2, + /** performs a forward or inverse transform of every individual row of the input + matrix; this flag enables you to transform multiple vectors simultaneously and can be used to + decrease the overhead (which is sometimes several times larger than the processing itself) to + perform 3D and higher-dimensional transformations and so forth.*/ + DFT_ROWS = 4, + /** performs a forward transformation of 1D or 2D real array; the result, + though being a complex array, has complex-conjugate symmetry (*CCS*, see the function + description below for details), and such an array can be packed into a real array of the same + size as input, which is the fastest option and which is what the function does by default; + however, you may wish to get a full complex array (for simpler spectrum analysis, and so on) - + pass the flag to enable the function to produce a full-size complex output array. */ + DFT_COMPLEX_OUTPUT = 16, + /** performs an inverse transformation of a 1D or 2D complex array; the + result is normally a complex array of the same size, however, if the input array has + conjugate-complex symmetry (for example, it is a result of forward transformation with + DFT_COMPLEX_OUTPUT flag), the output is a real array; while the function itself does not + check whether the input is symmetrical or not, you can pass the flag and then the function + will assume the symmetry and produce the real output array (note that when the input is packed + into a real array and inverse transformation is executed, the function treats the input as a + packed complex-conjugate symmetrical array, and the output will also be a real array). */ + DFT_REAL_OUTPUT = 32, + /** specifies that input is complex input. If this flag is set, the input must have 2 channels. + On the other hand, for backwards compatibility reason, if input has 2 channels, input is + already considered complex. */ + DFT_COMPLEX_INPUT = 64, + /** performs an inverse 1D or 2D transform instead of the default forward transform. */ + DCT_INVERSE = DFT_INVERSE, + /** performs a forward or inverse transform of every individual row of the input + matrix. This flag enables you to transform multiple vectors simultaneously and can be used to + decrease the overhead (which is sometimes several times larger than the processing itself) to + perform 3D and higher-dimensional transforms and so forth.*/ + DCT_ROWS = DFT_ROWS +}; + +//! Various border types, image boundaries are denoted with `|` +//! @see borderInterpolate, copyMakeBorder +enum BorderTypes { + BORDER_CONSTANT = 0, //!< `iiiiii|abcdefgh|iiiiiii` with some specified `i` + BORDER_REPLICATE = 1, //!< `aaaaaa|abcdefgh|hhhhhhh` + BORDER_REFLECT = 2, //!< `fedcba|abcdefgh|hgfedcb` + BORDER_WRAP = 3, //!< `cdefgh|abcdefgh|abcdefg` + BORDER_REFLECT_101 = 4, //!< `gfedcb|abcdefgh|gfedcba` + BORDER_TRANSPARENT = 5, //!< `uvwxyz|abcdefgh|ijklmno` + + BORDER_REFLECT101 = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101 + BORDER_DEFAULT = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101 + BORDER_ISOLATED = 16 //!< do not look outside of ROI +}; + +//! @} core_array + +//! @addtogroup core_utils +//! @{ + +/*! @brief Signals an error and raises the exception. + +By default the function prints information about the error to stderr, +then it either stops if setBreakOnError() had been called before or raises the exception. +It is possible to alternate error processing by using redirectError(). +@param _code - error code (Error::Code) +@param _err - error description +@param _func - function name. Available only when the compiler supports getting it +@param _file - source file name where the error has occurred +@param _line - line number in the source file where the error has occurred +@see CV_Error, CV_Error_, CV_Assert, CV_DbgAssert + */ +CV_EXPORTS void error(int _code, const String& _err, const char* _func, const char* _file, int _line); + +#ifdef __GNUC__ +# if defined __clang__ || defined __APPLE__ +# pragma GCC diagnostic push +# pragma GCC diagnostic ignored "-Winvalid-noreturn" +# endif +#endif + +/** same as cv::error, but does not return */ +CV_INLINE CV_NORETURN void errorNoReturn(int _code, const String& _err, const char* _func, const char* _file, int _line) +{ + error(_code, _err, _func, _file, _line); +#ifdef __GNUC__ +# if !defined __clang__ && !defined __APPLE__ + // this suppresses this warning: "noreturn" function does return [enabled by default] + __builtin_trap(); + // or use infinite loop: for (;;) {} +# endif +#endif +} +#ifdef __GNUC__ +# if defined __clang__ || defined __APPLE__ +# pragma GCC diagnostic pop +# endif +#endif + +#ifdef CV_STATIC_ANALYSIS + +// In practice, some macro are not processed correctly (noreturn is not detected). +// We need to use simplified definition for them. +#define CV_Error(...) do { abort(); } while (0) +#define CV_Error_( code, args ) do { cv::format args; abort(); } while (0) +#define CV_Assert( expr ) do { if (!(expr)) abort(); } while (0) +#define CV_ErrorNoReturn CV_Error +#define CV_ErrorNoReturn_ CV_Error_ + +#else // CV_STATIC_ANALYSIS + +/** @brief Call the error handler. + +Currently, the error handler prints the error code and the error message to the standard +error stream `stderr`. In the Debug configuration, it then provokes memory access violation, so that +the execution stack and all the parameters can be analyzed by the debugger. In the Release +configuration, the exception is thrown. + +@param code one of Error::Code +@param msg error message +*/ +#define CV_Error( code, msg ) cv::error( code, msg, CV_Func, __FILE__, __LINE__ ) + +/** @brief Call the error handler. + +This macro can be used to construct an error message on-fly to include some dynamic information, +for example: +@code + // note the extra parentheses around the formatted text message + CV_Error_(Error::StsOutOfRange, + ("the value at (%d, %d)=%g is out of range", badPt.x, badPt.y, badValue)); +@endcode +@param code one of Error::Code +@param args printf-like formatted error message in parentheses +*/ +#define CV_Error_( code, args ) cv::error( code, cv::format args, CV_Func, __FILE__, __LINE__ ) + +/** @brief Checks a condition at runtime and throws exception if it fails + +The macros CV_Assert (and CV_DbgAssert(expr)) evaluate the specified expression. If it is 0, the macros +raise an error (see cv::error). The macro CV_Assert checks the condition in both Debug and Release +configurations while CV_DbgAssert is only retained in the Debug configuration. +*/ +#define CV_Assert( expr ) do { if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ ); } while(0) + +//! @cond IGNORED +#define CV__ErrorNoReturn( code, msg ) cv::errorNoReturn( code, msg, CV_Func, __FILE__, __LINE__ ) +#define CV__ErrorNoReturn_( code, args ) cv::errorNoReturn( code, cv::format args, CV_Func, __FILE__, __LINE__ ) +#ifdef __OPENCV_BUILD +#undef CV_Error +#define CV_Error CV__ErrorNoReturn +#undef CV_Error_ +#define CV_Error_ CV__ErrorNoReturn_ +#undef CV_Assert +#define CV_Assert( expr ) do { if(!!(expr)) ; else cv::errorNoReturn( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ ); } while(0) +#else +// backward compatibility +#define CV_ErrorNoReturn CV__ErrorNoReturn +#define CV_ErrorNoReturn_ CV__ErrorNoReturn_ +#endif +//! @endcond + +#endif // CV_STATIC_ANALYSIS + +//! @cond IGNORED + +#if defined OPENCV_FORCE_MULTIARG_ASSERT_CHECK && defined CV_STATIC_ANALYSIS +#warning "OPENCV_FORCE_MULTIARG_ASSERT_CHECK can't be used with CV_STATIC_ANALYSIS" +#undef OPENCV_FORCE_MULTIARG_ASSERT_CHECK +#endif + +#ifdef OPENCV_FORCE_MULTIARG_ASSERT_CHECK +#define CV_Assert_1( expr ) do { if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ ); } while(0) +#else +#define CV_Assert_1 CV_Assert +#endif +#define CV_Assert_2( expr1, expr2 ) CV_Assert_1(expr1); CV_Assert_1(expr2) +#define CV_Assert_3( expr1, expr2, expr3 ) CV_Assert_2(expr1, expr2); CV_Assert_1(expr3) +#define CV_Assert_4( expr1, expr2, expr3, expr4 ) CV_Assert_3(expr1, expr2, expr3); CV_Assert_1(expr4) +#define CV_Assert_5( expr1, expr2, expr3, expr4, expr5 ) CV_Assert_4(expr1, expr2, expr3, expr4); CV_Assert_1(expr5) +#define CV_Assert_6( expr1, expr2, expr3, expr4, expr5, expr6 ) CV_Assert_5(expr1, expr2, expr3, expr4, expr5); CV_Assert_1(expr6) +#define CV_Assert_7( expr1, expr2, expr3, expr4, expr5, expr6, expr7 ) CV_Assert_6(expr1, expr2, expr3, expr4, expr5, expr6 ); CV_Assert_1(expr7) +#define CV_Assert_8( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ) CV_Assert_7(expr1, expr2, expr3, expr4, expr5, expr6, expr7 ); CV_Assert_1(expr8) +#define CV_Assert_9( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ) CV_Assert_8(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8 ); CV_Assert_1(expr9) +#define CV_Assert_10( expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9, expr10 ) CV_Assert_9(expr1, expr2, expr3, expr4, expr5, expr6, expr7, expr8, expr9 ); CV_Assert_1(expr10) + +#define CV_Assert_N(...) do { __CV_CAT(CV_Assert_, __CV_VA_NUM_ARGS(__VA_ARGS__)) (__VA_ARGS__); } while(0) + +#ifdef OPENCV_FORCE_MULTIARG_ASSERT_CHECK +#undef CV_Assert +#define CV_Assert CV_Assert_N +#endif +//! @endcond + +#if defined _DEBUG || defined CV_STATIC_ANALYSIS +# define CV_DbgAssert(expr) CV_Assert(expr) +#else +/** replaced with CV_Assert(expr) in Debug configuration */ +# define CV_DbgAssert(expr) +#endif + +/* + * Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor + * bit count of A exclusive XOR'ed with B + */ +struct CV_EXPORTS Hamming +{ + enum { normType = NORM_HAMMING }; + typedef unsigned char ValueType; + typedef int ResultType; + + /** this will count the bits in a ^ b + */ + ResultType operator()( const unsigned char* a, const unsigned char* b, int size ) const; +}; + +typedef Hamming HammingLUT; + +/////////////////////////////////// inline norms //////////////////////////////////// + +template inline _Tp cv_abs(_Tp x) { return std::abs(x); } +inline int cv_abs(uchar x) { return x; } +inline int cv_abs(schar x) { return std::abs(x); } +inline int cv_abs(ushort x) { return x; } +inline int cv_abs(short x) { return std::abs(x); } + +template static inline +_AccTp normL2Sqr(const _Tp* a, int n) +{ + _AccTp s = 0; + int i=0; +#if CV_ENABLE_UNROLLED + for( ; i <= n - 4; i += 4 ) + { + _AccTp v0 = a[i], v1 = a[i+1], v2 = a[i+2], v3 = a[i+3]; + s += v0*v0 + v1*v1 + v2*v2 + v3*v3; + } +#endif + for( ; i < n; i++ ) + { + _AccTp v = a[i]; + s += v*v; + } + return s; +} + +template static inline +_AccTp normL1(const _Tp* a, int n) +{ + _AccTp s = 0; + int i = 0; +#if CV_ENABLE_UNROLLED + for(; i <= n - 4; i += 4 ) + { + s += (_AccTp)cv_abs(a[i]) + (_AccTp)cv_abs(a[i+1]) + + (_AccTp)cv_abs(a[i+2]) + (_AccTp)cv_abs(a[i+3]); + } +#endif + for( ; i < n; i++ ) + s += cv_abs(a[i]); + return s; +} + +template static inline +_AccTp normInf(const _Tp* a, int n) +{ + _AccTp s = 0; + for( int i = 0; i < n; i++ ) + s = std::max(s, (_AccTp)cv_abs(a[i])); + return s; +} + +template static inline +_AccTp normL2Sqr(const _Tp* a, const _Tp* b, int n) +{ + _AccTp s = 0; + int i= 0; +#if CV_ENABLE_UNROLLED + for(; i <= n - 4; i += 4 ) + { + _AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]); + s += v0*v0 + v1*v1 + v2*v2 + v3*v3; + } +#endif + for( ; i < n; i++ ) + { + _AccTp v = _AccTp(a[i] - b[i]); + s += v*v; + } + return s; +} + +static inline float normL2Sqr(const float* a, const float* b, int n) +{ + float s = 0.f; + for( int i = 0; i < n; i++ ) + { + float v = a[i] - b[i]; + s += v*v; + } + return s; +} + +template static inline +_AccTp normL1(const _Tp* a, const _Tp* b, int n) +{ + _AccTp s = 0; + int i= 0; +#if CV_ENABLE_UNROLLED + for(; i <= n - 4; i += 4 ) + { + _AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]); + s += std::abs(v0) + std::abs(v1) + std::abs(v2) + std::abs(v3); + } +#endif + for( ; i < n; i++ ) + { + _AccTp v = _AccTp(a[i] - b[i]); + s += std::abs(v); + } + return s; +} + +inline float normL1(const float* a, const float* b, int n) +{ + float s = 0.f; + for( int i = 0; i < n; i++ ) + { + s += std::abs(a[i] - b[i]); + } + return s; +} + +inline int normL1(const uchar* a, const uchar* b, int n) +{ + int s = 0; + for( int i = 0; i < n; i++ ) + { + s += std::abs(a[i] - b[i]); + } + return s; +} + +template static inline +_AccTp normInf(const _Tp* a, const _Tp* b, int n) +{ + _AccTp s = 0; + for( int i = 0; i < n; i++ ) + { + _AccTp v0 = a[i] - b[i]; + s = std::max(s, std::abs(v0)); + } + return s; +} + +/** @brief Computes the cube root of an argument. + + The function cubeRoot computes \f$\sqrt[3]{\texttt{val}}\f$. Negative arguments are handled correctly. + NaN and Inf are not handled. The accuracy approaches the maximum possible accuracy for + single-precision data. + @param val A function argument. + */ +CV_EXPORTS_W float cubeRoot(float val); + +/** @brief Calculates the angle of a 2D vector in degrees. + + The function fastAtan2 calculates the full-range angle of an input 2D vector. The angle is measured + in degrees and varies from 0 to 360 degrees. The accuracy is about 0.3 degrees. + @param x x-coordinate of the vector. + @param y y-coordinate of the vector. + */ +CV_EXPORTS_W float fastAtan2(float y, float x); + +/** proxy for hal::LU */ +CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n); +/** proxy for hal::LU */ +CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n); +/** proxy for hal::Cholesky */ +CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n); +/** proxy for hal::Cholesky */ +CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n); + +////////////////// forward declarations for important OpenCV types ////////////////// + +//! @cond IGNORED + +template class Vec; +template class Matx; + +template class Complex; +template class Point_; +template class Point3_; +template class Size_; +template class Rect_; +template class Scalar_; + +class CV_EXPORTS RotatedRect; +class CV_EXPORTS Range; +class CV_EXPORTS TermCriteria; +class CV_EXPORTS KeyPoint; +class CV_EXPORTS DMatch; +class CV_EXPORTS RNG; + +class CV_EXPORTS Mat; +class CV_EXPORTS MatExpr; + +class CV_EXPORTS UMat; + +class CV_EXPORTS SparseMat; +typedef Mat MatND; + +template class Mat_; +template class SparseMat_; + +class CV_EXPORTS MatConstIterator; +class CV_EXPORTS SparseMatIterator; +class CV_EXPORTS SparseMatConstIterator; +template class MatIterator_; +template class MatConstIterator_; +template class SparseMatIterator_; +template class SparseMatConstIterator_; + +namespace ogl +{ + class CV_EXPORTS Buffer; + class CV_EXPORTS Texture2D; + class CV_EXPORTS Arrays; +} + +namespace cuda +{ + class CV_EXPORTS GpuMat; + class CV_EXPORTS HostMem; + class CV_EXPORTS Stream; + class CV_EXPORTS Event; +} + +namespace cudev +{ + template class GpuMat_; +} + +namespace ipp +{ +#if OPENCV_ABI_COMPATIBILITY > 300 +CV_EXPORTS unsigned long long getIppFeatures(); +#else +CV_EXPORTS int getIppFeatures(); +#endif +CV_EXPORTS void setIppStatus(int status, const char * const funcname = NULL, const char * const filename = NULL, + int line = 0); +CV_EXPORTS int getIppStatus(); +CV_EXPORTS String getIppErrorLocation(); +CV_EXPORTS_W bool useIPP(); +CV_EXPORTS_W void setUseIPP(bool flag); +CV_EXPORTS_W String getIppVersion(); + +// IPP Not-Exact mode. This function may force use of IPP then both IPP and OpenCV provide proper results +// but have internal accuracy differences which have too much direct or indirect impact on accuracy tests. +CV_EXPORTS_W bool useIPP_NotExact(); +CV_EXPORTS_W void setUseIPP_NotExact(bool flag); +#if OPENCV_ABI_COMPATIBILITY < 400 +CV_EXPORTS_W bool useIPP_NE(); +CV_EXPORTS_W void setUseIPP_NE(bool flag); +#endif + +} // ipp + +//! @endcond + +//! @} core_utils + + + + +} // cv + +#include "opencv2/core/neon_utils.hpp" +#include "opencv2/core/vsx_utils.hpp" +#include "opencv2/core/check.hpp" + +#endif //OPENCV_CORE_BASE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/bindings_utils.hpp b/3rdparty/opencv/include/opencv2/core/bindings_utils.hpp new file mode 100644 index 00000000..c1123f2b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/bindings_utils.hpp @@ -0,0 +1,23 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_CORE_BINDINGS_UTILS_HPP +#define OPENCV_CORE_BINDINGS_UTILS_HPP + +namespace cv { namespace utils { +//! @addtogroup core_utils +//! @{ + +CV_EXPORTS_W String dumpInputArray(InputArray argument); + +CV_EXPORTS_W String dumpInputArrayOfArrays(InputArrayOfArrays argument); + +CV_EXPORTS_W String dumpInputOutputArray(InputOutputArray argument); + +CV_EXPORTS_W String dumpInputOutputArrayOfArrays(InputOutputArrayOfArrays argument); + +//! @} +}} // namespace + +#endif // OPENCV_CORE_BINDINGS_UTILS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/bufferpool.hpp b/3rdparty/opencv/include/opencv2/core/bufferpool.hpp new file mode 100644 index 00000000..4698e5da --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/bufferpool.hpp @@ -0,0 +1,40 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved. + +#ifndef OPENCV_CORE_BUFFER_POOL_HPP +#define OPENCV_CORE_BUFFER_POOL_HPP + +#ifdef _MSC_VER +#pragma warning(push) +#pragma warning(disable: 4265) +#endif + +namespace cv +{ + +//! @addtogroup core +//! @{ + +class BufferPoolController +{ +protected: + ~BufferPoolController() { } +public: + virtual size_t getReservedSize() const = 0; + virtual size_t getMaxReservedSize() const = 0; + virtual void setMaxReservedSize(size_t size) = 0; + virtual void freeAllReservedBuffers() = 0; +}; + +//! @} + +} + +#ifdef _MSC_VER +#pragma warning(pop) +#endif + +#endif // OPENCV_CORE_BUFFER_POOL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/check.hpp b/3rdparty/opencv/include/opencv2/core/check.hpp new file mode 100644 index 00000000..bf441383 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/check.hpp @@ -0,0 +1,157 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_CORE_CHECK_HPP +#define OPENCV_CORE_CHECK_HPP + +#include + +namespace cv { + +/** Returns string of cv::Mat depth value: CV_8U -> "CV_8U" or "" */ +CV_EXPORTS const char* depthToString(int depth); + +/** Returns string of cv::Mat depth value: CV_8UC3 -> "CV_8UC3" or "" */ +CV_EXPORTS const String typeToString(int type); + + +//! @cond IGNORED +namespace detail { + +/** Returns string of cv::Mat depth value: CV_8U -> "CV_8U" or NULL */ +CV_EXPORTS const char* depthToString_(int depth); + +/** Returns string of cv::Mat depth value: CV_8UC3 -> "CV_8UC3" or cv::String() */ +CV_EXPORTS const cv::String typeToString_(int type); + +enum TestOp { + TEST_CUSTOM = 0, + TEST_EQ = 1, + TEST_NE = 2, + TEST_LE = 3, + TEST_LT = 4, + TEST_GE = 5, + TEST_GT = 6, + CV__LAST_TEST_OP +}; + +struct CheckContext { + const char* func; + const char* file; + int line; + enum TestOp testOp; + const char* message; + const char* p1_str; + const char* p2_str; +}; + +#ifndef CV__CHECK_FILENAME +# define CV__CHECK_FILENAME __FILE__ +#endif + +#ifndef CV__CHECK_FUNCTION +# if defined _MSC_VER +# define CV__CHECK_FUNCTION __FUNCSIG__ +# elif defined __GNUC__ +# define CV__CHECK_FUNCTION __PRETTY_FUNCTION__ +# else +# define CV__CHECK_FUNCTION "" +# endif +#endif + +#define CV__CHECK_LOCATION_VARNAME(id) CVAUX_CONCAT(CVAUX_CONCAT(__cv_check_, id), __LINE__) +#define CV__DEFINE_CHECK_CONTEXT(id, message, testOp, p1_str, p2_str) \ + static const cv::detail::CheckContext CV__CHECK_LOCATION_VARNAME(id) = \ + { CV__CHECK_FUNCTION, CV__CHECK_FILENAME, __LINE__, testOp, message, p1_str, p2_str } + +CV_EXPORTS void CV_NORETURN check_failed_auto(const int v1, const int v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v1, const size_t v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const float v1, const float v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const double v1, const double v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatDepth(const int v1, const int v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatType(const int v1, const int v2, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v1, const int v2, const CheckContext& ctx); + +CV_EXPORTS void CV_NORETURN check_failed_auto(const int v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const float v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_auto(const double v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatDepth(const int v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatType(const int v, const CheckContext& ctx); +CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v, const CheckContext& ctx); + + +#define CV__TEST_EQ(v1, v2) ((v1) == (v2)) +#define CV__TEST_NE(v1, v2) ((v1) != (v2)) +#define CV__TEST_LE(v1, v2) ((v1) <= (v2)) +#define CV__TEST_LT(v1, v2) ((v1) < (v2)) +#define CV__TEST_GE(v1, v2) ((v1) >= (v2)) +#define CV__TEST_GT(v1, v2) ((v1) > (v2)) + +#define CV__CHECK(id, op, type, v1, v2, v1_str, v2_str, msg_str) do { \ + if(CV__TEST_##op((v1), (v2))) ; else { \ + CV__DEFINE_CHECK_CONTEXT(id, msg_str, cv::detail::TEST_ ## op, v1_str, v2_str); \ + cv::detail::check_failed_ ## type((v1), (v2), CV__CHECK_LOCATION_VARNAME(id)); \ + } \ +} while (0) + +#define CV__CHECK_CUSTOM_TEST(id, type, v, test_expr, v_str, test_expr_str, msg_str) do { \ + if(!!(test_expr)) ; else { \ + CV__DEFINE_CHECK_CONTEXT(id, msg_str, cv::detail::TEST_CUSTOM, v_str, test_expr_str); \ + cv::detail::check_failed_ ## type((v), CV__CHECK_LOCATION_VARNAME(id)); \ + } \ +} while (0) + +} // namespace +//! @endcond + + +/// Supported values of these types: int, float, double +#define CV_CheckEQ(v1, v2, msg) CV__CHECK(_, EQ, auto, v1, v2, #v1, #v2, msg) +#define CV_CheckNE(v1, v2, msg) CV__CHECK(_, NE, auto, v1, v2, #v1, #v2, msg) +#define CV_CheckLE(v1, v2, msg) CV__CHECK(_, LE, auto, v1, v2, #v1, #v2, msg) +#define CV_CheckLT(v1, v2, msg) CV__CHECK(_, LT, auto, v1, v2, #v1, #v2, msg) +#define CV_CheckGE(v1, v2, msg) CV__CHECK(_, GE, auto, v1, v2, #v1, #v2, msg) +#define CV_CheckGT(v1, v2, msg) CV__CHECK(_, GT, auto, v1, v2, #v1, #v2, msg) + +/// Check with additional "decoding" of type values in error message +#define CV_CheckTypeEQ(t1, t2, msg) CV__CHECK(_, EQ, MatType, t1, t2, #t1, #t2, msg) +/// Check with additional "decoding" of depth values in error message +#define CV_CheckDepthEQ(d1, d2, msg) CV__CHECK(_, EQ, MatDepth, d1, d2, #d1, #d2, msg) + +#define CV_CheckChannelsEQ(c1, c2, msg) CV__CHECK(_, EQ, MatChannels, c1, c2, #c1, #c2, msg) + +/// Example: type == CV_8UC1 || type == CV_8UC3 +#define CV_CheckType(t, test_expr, msg) CV__CHECK_CUSTOM_TEST(_, MatType, t, (test_expr), #t, #test_expr, msg) + +/// Example: depth == CV_32F || depth == CV_64F +#define CV_CheckDepth(t, test_expr, msg) CV__CHECK_CUSTOM_TEST(_, MatDepth, t, (test_expr), #t, #test_expr, msg) + +/// Example: v == A || v == B +#define CV_Check(v, test_expr, msg) CV__CHECK_CUSTOM_TEST(_, auto, v, (test_expr), #v, #test_expr, msg) + +/// Some complex conditions: CV_Check(src2, src2.empty() || (src2.type() == src1.type() && src2.size() == src1.size()), "src2 should have same size/type as src1") +// TODO define pretty-printers + +#ifndef NDEBUG +#define CV_DbgCheck(v, test_expr, msg) CV__CHECK_CUSTOM_TEST(_, auto, v, (test_expr), #v, #test_expr, msg) +#define CV_DbgCheckEQ(v1, v2, msg) CV__CHECK(_, EQ, auto, v1, v2, #v1, #v2, msg) +#define CV_DbgCheckNE(v1, v2, msg) CV__CHECK(_, NE, auto, v1, v2, #v1, #v2, msg) +#define CV_DbgCheckLE(v1, v2, msg) CV__CHECK(_, LE, auto, v1, v2, #v1, #v2, msg) +#define CV_DbgCheckLT(v1, v2, msg) CV__CHECK(_, LT, auto, v1, v2, #v1, #v2, msg) +#define CV_DbgCheckGE(v1, v2, msg) CV__CHECK(_, GE, auto, v1, v2, #v1, #v2, msg) +#define CV_DbgCheckGT(v1, v2, msg) CV__CHECK(_, GT, auto, v1, v2, #v1, #v2, msg) +#else +#define CV_DbgCheck(v, test_expr, msg) do { } while (0) +#define CV_DbgCheckEQ(v1, v2, msg) do { } while (0) +#define CV_DbgCheckNE(v1, v2, msg) do { } while (0) +#define CV_DbgCheckLE(v1, v2, msg) do { } while (0) +#define CV_DbgCheckLT(v1, v2, msg) do { } while (0) +#define CV_DbgCheckGE(v1, v2, msg) do { } while (0) +#define CV_DbgCheckGT(v1, v2, msg) do { } while (0) +#endif + +} // namespace + +#endif // OPENCV_CORE_CHECK_HPP diff --git a/3rdparty/opencv/include/opencv2/core/core.hpp b/3rdparty/opencv/include/opencv2/core/core.hpp new file mode 100644 index 00000000..43891835 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/core.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/core.hpp" diff --git a/3rdparty/opencv/include/opencv2/core/core_c.h b/3rdparty/opencv/include/opencv2/core/core_c.h new file mode 100644 index 00000000..e5fe516d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/core_c.h @@ -0,0 +1,3175 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + + +#ifndef OPENCV_CORE_C_H +#define OPENCV_CORE_C_H + +#include "opencv2/core/types_c.h" + +#ifdef __cplusplus +# ifdef _MSC_VER +/* disable warning C4190: 'function' has C-linkage specified, but returns UDT 'typename' + which is incompatible with C + + It is OK to disable it because we only extend few plain structures with + C++ construrtors for simpler interoperability with C++ API of the library +*/ +# pragma warning(disable:4190) +# elif defined __clang__ && __clang_major__ >= 3 +# pragma GCC diagnostic ignored "-Wreturn-type-c-linkage" +# endif +#endif + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup core_c + @{ +*/ + +/****************************************************************************************\ +* Array allocation, deallocation, initialization and access to elements * +\****************************************************************************************/ + +/** `malloc` wrapper. + If there is no enough memory, the function + (as well as other OpenCV functions that call cvAlloc) + raises an error. */ +CVAPI(void*) cvAlloc( size_t size ); + +/** `free` wrapper. + Here and further all the memory releasing functions + (that all call cvFree) take double pointer in order to + to clear pointer to the data after releasing it. + Passing pointer to NULL pointer is Ok: nothing happens in this case +*/ +CVAPI(void) cvFree_( void* ptr ); +#define cvFree(ptr) (cvFree_(*(ptr)), *(ptr)=0) + +/** @brief Creates an image header but does not allocate the image data. + +@param size Image width and height +@param depth Image depth (see cvCreateImage ) +@param channels Number of channels (see cvCreateImage ) + */ +CVAPI(IplImage*) cvCreateImageHeader( CvSize size, int depth, int channels ); + +/** @brief Initializes an image header that was previously allocated. + +The returned IplImage\* points to the initialized header. +@param image Image header to initialize +@param size Image width and height +@param depth Image depth (see cvCreateImage ) +@param channels Number of channels (see cvCreateImage ) +@param origin Top-left IPL_ORIGIN_TL or bottom-left IPL_ORIGIN_BL +@param align Alignment for image rows, typically 4 or 8 bytes + */ +CVAPI(IplImage*) cvInitImageHeader( IplImage* image, CvSize size, int depth, + int channels, int origin CV_DEFAULT(0), + int align CV_DEFAULT(4)); + +/** @brief Creates an image header and allocates the image data. + +This function call is equivalent to the following code: +@code + header = cvCreateImageHeader(size, depth, channels); + cvCreateData(header); +@endcode +@param size Image width and height +@param depth Bit depth of image elements. See IplImage for valid depths. +@param channels Number of channels per pixel. See IplImage for details. This function only creates +images with interleaved channels. + */ +CVAPI(IplImage*) cvCreateImage( CvSize size, int depth, int channels ); + +/** @brief Deallocates an image header. + +This call is an analogue of : +@code + if(image ) + { + iplDeallocate(*image, IPL_IMAGE_HEADER | IPL_IMAGE_ROI); + *image = 0; + } +@endcode +but it does not use IPL functions by default (see the CV_TURN_ON_IPL_COMPATIBILITY macro). +@param image Double pointer to the image header + */ +CVAPI(void) cvReleaseImageHeader( IplImage** image ); + +/** @brief Deallocates the image header and the image data. + +This call is a shortened form of : +@code + if(*image ) + { + cvReleaseData(*image); + cvReleaseImageHeader(image); + } +@endcode +@param image Double pointer to the image header +*/ +CVAPI(void) cvReleaseImage( IplImage** image ); + +/** Creates a copy of IPL image (widthStep may differ) */ +CVAPI(IplImage*) cvCloneImage( const IplImage* image ); + +/** @brief Sets the channel of interest in an IplImage. + +If the ROI is set to NULL and the coi is *not* 0, the ROI is allocated. Most OpenCV functions do +*not* support the COI setting, so to process an individual image/matrix channel one may copy (via +cvCopy or cvSplit) the channel to a separate image/matrix, process it and then copy the result +back (via cvCopy or cvMerge) if needed. +@param image A pointer to the image header +@param coi The channel of interest. 0 - all channels are selected, 1 - first channel is selected, +etc. Note that the channel indices become 1-based. + */ +CVAPI(void) cvSetImageCOI( IplImage* image, int coi ); + +/** @brief Returns the index of the channel of interest. + +Returns the channel of interest of in an IplImage. Returned values correspond to the coi in +cvSetImageCOI. +@param image A pointer to the image header + */ +CVAPI(int) cvGetImageCOI( const IplImage* image ); + +/** @brief Sets an image Region Of Interest (ROI) for a given rectangle. + +If the original image ROI was NULL and the rect is not the whole image, the ROI structure is +allocated. + +Most OpenCV functions support the use of ROI and treat the image rectangle as a separate image. For +example, all of the pixel coordinates are counted from the top-left (or bottom-left) corner of the +ROI, not the original image. +@param image A pointer to the image header +@param rect The ROI rectangle + */ +CVAPI(void) cvSetImageROI( IplImage* image, CvRect rect ); + +/** @brief Resets the image ROI to include the entire image and releases the ROI structure. + +This produces a similar result to the following, but in addition it releases the ROI structure. : +@code + cvSetImageROI(image, cvRect(0, 0, image->width, image->height )); + cvSetImageCOI(image, 0); +@endcode +@param image A pointer to the image header + */ +CVAPI(void) cvResetImageROI( IplImage* image ); + +/** @brief Returns the image ROI. + +If there is no ROI set, cvRect(0,0,image-\>width,image-\>height) is returned. +@param image A pointer to the image header + */ +CVAPI(CvRect) cvGetImageROI( const IplImage* image ); + +/** @brief Creates a matrix header but does not allocate the matrix data. + +The function allocates a new matrix header and returns a pointer to it. The matrix data can then be +allocated using cvCreateData or set explicitly to user-allocated data via cvSetData. +@param rows Number of rows in the matrix +@param cols Number of columns in the matrix +@param type Type of the matrix elements, see cvCreateMat + */ +CVAPI(CvMat*) cvCreateMatHeader( int rows, int cols, int type ); + +#define CV_AUTOSTEP 0x7fffffff + +/** @brief Initializes a pre-allocated matrix header. + +This function is often used to process raw data with OpenCV matrix functions. For example, the +following code computes the matrix product of two matrices, stored as ordinary arrays: +@code + double a[] = { 1, 2, 3, 4, + 5, 6, 7, 8, + 9, 10, 11, 12 }; + + double b[] = { 1, 5, 9, + 2, 6, 10, + 3, 7, 11, + 4, 8, 12 }; + + double c[9]; + CvMat Ma, Mb, Mc ; + + cvInitMatHeader(&Ma, 3, 4, CV_64FC1, a); + cvInitMatHeader(&Mb, 4, 3, CV_64FC1, b); + cvInitMatHeader(&Mc, 3, 3, CV_64FC1, c); + + cvMatMulAdd(&Ma, &Mb, 0, &Mc); + // the c array now contains the product of a (3x4) and b (4x3) +@endcode +@param mat A pointer to the matrix header to be initialized +@param rows Number of rows in the matrix +@param cols Number of columns in the matrix +@param type Type of the matrix elements, see cvCreateMat . +@param data Optional: data pointer assigned to the matrix header +@param step Optional: full row width in bytes of the assigned data. By default, the minimal +possible step is used which assumes there are no gaps between subsequent rows of the matrix. + */ +CVAPI(CvMat*) cvInitMatHeader( CvMat* mat, int rows, int cols, + int type, void* data CV_DEFAULT(NULL), + int step CV_DEFAULT(CV_AUTOSTEP) ); + +/** @brief Creates a matrix header and allocates the matrix data. + +The function call is equivalent to the following code: +@code + CvMat* mat = cvCreateMatHeader(rows, cols, type); + cvCreateData(mat); +@endcode +@param rows Number of rows in the matrix +@param cols Number of columns in the matrix +@param type The type of the matrix elements in the form +CV_\\C\ , where S=signed, U=unsigned, F=float. For +example, CV _ 8UC1 means the elements are 8-bit unsigned and the there is 1 channel, and CV _ +32SC2 means the elements are 32-bit signed and there are 2 channels. + */ +CVAPI(CvMat*) cvCreateMat( int rows, int cols, int type ); + +/** @brief Deallocates a matrix. + +The function decrements the matrix data reference counter and deallocates matrix header. If the data +reference counter is 0, it also deallocates the data. : +@code + if(*mat ) + cvDecRefData(*mat); + cvFree((void**)mat); +@endcode +@param mat Double pointer to the matrix + */ +CVAPI(void) cvReleaseMat( CvMat** mat ); + +/** @brief Decrements an array data reference counter. + +The function decrements the data reference counter in a CvMat or CvMatND if the reference counter + +pointer is not NULL. If the counter reaches zero, the data is deallocated. In the current +implementation the reference counter is not NULL only if the data was allocated using the +cvCreateData function. The counter will be NULL in other cases such as: external data was assigned +to the header using cvSetData, header is part of a larger matrix or image, or the header was +converted from an image or n-dimensional matrix header. +@param arr Pointer to an array header + */ +CV_INLINE void cvDecRefData( CvArr* arr ) +{ + if( CV_IS_MAT( arr )) + { + CvMat* mat = (CvMat*)arr; + mat->data.ptr = NULL; + if( mat->refcount != NULL && --*mat->refcount == 0 ) + cvFree( &mat->refcount ); + mat->refcount = NULL; + } + else if( CV_IS_MATND( arr )) + { + CvMatND* mat = (CvMatND*)arr; + mat->data.ptr = NULL; + if( mat->refcount != NULL && --*mat->refcount == 0 ) + cvFree( &mat->refcount ); + mat->refcount = NULL; + } +} + +/** @brief Increments array data reference counter. + +The function increments CvMat or CvMatND data reference counter and returns the new counter value if +the reference counter pointer is not NULL, otherwise it returns zero. +@param arr Array header + */ +CV_INLINE int cvIncRefData( CvArr* arr ) +{ + int refcount = 0; + if( CV_IS_MAT( arr )) + { + CvMat* mat = (CvMat*)arr; + if( mat->refcount != NULL ) + refcount = ++*mat->refcount; + } + else if( CV_IS_MATND( arr )) + { + CvMatND* mat = (CvMatND*)arr; + if( mat->refcount != NULL ) + refcount = ++*mat->refcount; + } + return refcount; +} + + +/** Creates an exact copy of the input matrix (except, may be, step value) */ +CVAPI(CvMat*) cvCloneMat( const CvMat* mat ); + + +/** @brief Returns matrix header corresponding to the rectangular sub-array of input image or matrix. + +The function returns header, corresponding to a specified rectangle of the input array. In other + +words, it allows the user to treat a rectangular part of input array as a stand-alone array. ROI is +taken into account by the function so the sub-array of ROI is actually extracted. +@param arr Input array +@param submat Pointer to the resultant sub-array header +@param rect Zero-based coordinates of the rectangle of interest + */ +CVAPI(CvMat*) cvGetSubRect( const CvArr* arr, CvMat* submat, CvRect rect ); +#define cvGetSubArr cvGetSubRect + +/** @brief Returns array row or row span. + +The function returns the header, corresponding to a specified row/row span of the input array. +cvGetRow(arr, submat, row) is a shortcut for cvGetRows(arr, submat, row, row+1). +@param arr Input array +@param submat Pointer to the resulting sub-array header +@param start_row Zero-based index of the starting row (inclusive) of the span +@param end_row Zero-based index of the ending row (exclusive) of the span +@param delta_row Index step in the row span. That is, the function extracts every delta_row -th +row from start_row and up to (but not including) end_row . + */ +CVAPI(CvMat*) cvGetRows( const CvArr* arr, CvMat* submat, + int start_row, int end_row, + int delta_row CV_DEFAULT(1)); + +/** @overload +@param arr Input array +@param submat Pointer to the resulting sub-array header +@param row Zero-based index of the selected row +*/ +CV_INLINE CvMat* cvGetRow( const CvArr* arr, CvMat* submat, int row ) +{ + return cvGetRows( arr, submat, row, row + 1, 1 ); +} + + +/** @brief Returns one of more array columns. + +The function returns the header, corresponding to a specified column span of the input array. That + +is, no data is copied. Therefore, any modifications of the submatrix will affect the original array. +If you need to copy the columns, use cvCloneMat. cvGetCol(arr, submat, col) is a shortcut for +cvGetCols(arr, submat, col, col+1). +@param arr Input array +@param submat Pointer to the resulting sub-array header +@param start_col Zero-based index of the starting column (inclusive) of the span +@param end_col Zero-based index of the ending column (exclusive) of the span + */ +CVAPI(CvMat*) cvGetCols( const CvArr* arr, CvMat* submat, + int start_col, int end_col ); + +/** @overload +@param arr Input array +@param submat Pointer to the resulting sub-array header +@param col Zero-based index of the selected column +*/ +CV_INLINE CvMat* cvGetCol( const CvArr* arr, CvMat* submat, int col ) +{ + return cvGetCols( arr, submat, col, col + 1 ); +} + +/** @brief Returns one of array diagonals. + +The function returns the header, corresponding to a specified diagonal of the input array. +@param arr Input array +@param submat Pointer to the resulting sub-array header +@param diag Index of the array diagonal. Zero value corresponds to the main diagonal, -1 +corresponds to the diagonal above the main, 1 corresponds to the diagonal below the main, and so +forth. + */ +CVAPI(CvMat*) cvGetDiag( const CvArr* arr, CvMat* submat, + int diag CV_DEFAULT(0)); + +/** low-level scalar <-> raw data conversion functions */ +CVAPI(void) cvScalarToRawData( const CvScalar* scalar, void* data, int type, + int extend_to_12 CV_DEFAULT(0) ); + +CVAPI(void) cvRawDataToScalar( const void* data, int type, CvScalar* scalar ); + +/** @brief Creates a new matrix header but does not allocate the matrix data. + +The function allocates a header for a multi-dimensional dense array. The array data can further be +allocated using cvCreateData or set explicitly to user-allocated data via cvSetData. +@param dims Number of array dimensions +@param sizes Array of dimension sizes +@param type Type of array elements, see cvCreateMat + */ +CVAPI(CvMatND*) cvCreateMatNDHeader( int dims, const int* sizes, int type ); + +/** @brief Creates the header and allocates the data for a multi-dimensional dense array. + +This function call is equivalent to the following code: +@code + CvMatND* mat = cvCreateMatNDHeader(dims, sizes, type); + cvCreateData(mat); +@endcode +@param dims Number of array dimensions. This must not exceed CV_MAX_DIM (32 by default, but can be +changed at build time). +@param sizes Array of dimension sizes. +@param type Type of array elements, see cvCreateMat . + */ +CVAPI(CvMatND*) cvCreateMatND( int dims, const int* sizes, int type ); + +/** @brief Initializes a pre-allocated multi-dimensional array header. + +@param mat A pointer to the array header to be initialized +@param dims The number of array dimensions +@param sizes An array of dimension sizes +@param type Type of array elements, see cvCreateMat +@param data Optional data pointer assigned to the matrix header + */ +CVAPI(CvMatND*) cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes, + int type, void* data CV_DEFAULT(NULL) ); + +/** @brief Deallocates a multi-dimensional array. + +The function decrements the array data reference counter and releases the array header. If the +reference counter reaches 0, it also deallocates the data. : +@code + if(*mat ) + cvDecRefData(*mat); + cvFree((void**)mat); +@endcode +@param mat Double pointer to the array + */ +CV_INLINE void cvReleaseMatND( CvMatND** mat ) +{ + cvReleaseMat( (CvMat**)mat ); +} + +/** Creates a copy of CvMatND (except, may be, steps) */ +CVAPI(CvMatND*) cvCloneMatND( const CvMatND* mat ); + +/** @brief Creates sparse array. + +The function allocates a multi-dimensional sparse array. Initially the array contain no elements, +that is PtrND and other related functions will return 0 for every index. +@param dims Number of array dimensions. In contrast to the dense matrix, the number of dimensions is +practically unlimited (up to \f$2^{16}\f$ ). +@param sizes Array of dimension sizes +@param type Type of array elements. The same as for CvMat + */ +CVAPI(CvSparseMat*) cvCreateSparseMat( int dims, const int* sizes, int type ); + +/** @brief Deallocates sparse array. + +The function releases the sparse array and clears the array pointer upon exit. +@param mat Double pointer to the array + */ +CVAPI(void) cvReleaseSparseMat( CvSparseMat** mat ); + +/** Creates a copy of CvSparseMat (except, may be, zero items) */ +CVAPI(CvSparseMat*) cvCloneSparseMat( const CvSparseMat* mat ); + +/** @brief Initializes sparse array elements iterator. + +The function initializes iterator of sparse array elements and returns pointer to the first element, +or NULL if the array is empty. +@param mat Input array +@param mat_iterator Initialized iterator + */ +CVAPI(CvSparseNode*) cvInitSparseMatIterator( const CvSparseMat* mat, + CvSparseMatIterator* mat_iterator ); + +/** @brief Returns the next sparse matrix element + +The function moves iterator to the next sparse matrix element and returns pointer to it. In the +current version there is no any particular order of the elements, because they are stored in the +hash table. The sample below demonstrates how to iterate through the sparse matrix: +@code + // print all the non-zero sparse matrix elements and compute their sum + double sum = 0; + int i, dims = cvGetDims(sparsemat); + CvSparseMatIterator it; + CvSparseNode* node = cvInitSparseMatIterator(sparsemat, &it); + + for(; node != 0; node = cvGetNextSparseNode(&it)) + { + int* idx = CV_NODE_IDX(array, node); + float val = *(float*)CV_NODE_VAL(array, node); + printf("M"); + for(i = 0; i < dims; i++ ) + printf("[%d]", idx[i]); + printf("=%g\n", val); + + sum += val; + } + + printf("nTotal sum = %g\n", sum); +@endcode +@param mat_iterator Sparse array iterator + */ +CV_INLINE CvSparseNode* cvGetNextSparseNode( CvSparseMatIterator* mat_iterator ) +{ + if( mat_iterator->node->next ) + return mat_iterator->node = mat_iterator->node->next; + else + { + int idx; + for( idx = ++mat_iterator->curidx; idx < mat_iterator->mat->hashsize; idx++ ) + { + CvSparseNode* node = (CvSparseNode*)mat_iterator->mat->hashtable[idx]; + if( node ) + { + mat_iterator->curidx = idx; + return mat_iterator->node = node; + } + } + return NULL; + } +} + + +#define CV_MAX_ARR 10 + +/** matrix iterator: used for n-ary operations on dense arrays */ +typedef struct CvNArrayIterator +{ + int count; /**< number of arrays */ + int dims; /**< number of dimensions to iterate */ + CvSize size; /**< maximal common linear size: { width = size, height = 1 } */ + uchar* ptr[CV_MAX_ARR]; /**< pointers to the array slices */ + int stack[CV_MAX_DIM]; /**< for internal use */ + CvMatND* hdr[CV_MAX_ARR]; /**< pointers to the headers of the + matrices that are processed */ +} +CvNArrayIterator; + +#define CV_NO_DEPTH_CHECK 1 +#define CV_NO_CN_CHECK 2 +#define CV_NO_SIZE_CHECK 4 + +/** initializes iterator that traverses through several arrays simulteneously + (the function together with cvNextArraySlice is used for + N-ari element-wise operations) */ +CVAPI(int) cvInitNArrayIterator( int count, CvArr** arrs, + const CvArr* mask, CvMatND* stubs, + CvNArrayIterator* array_iterator, + int flags CV_DEFAULT(0) ); + +/** returns zero value if iteration is finished, non-zero (slice length) otherwise */ +CVAPI(int) cvNextNArraySlice( CvNArrayIterator* array_iterator ); + + +/** @brief Returns type of array elements. + +The function returns type of the array elements. In the case of IplImage the type is converted to +CvMat-like representation. For example, if the image has been created as: +@code + IplImage* img = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3); +@endcode +The code cvGetElemType(img) will return CV_8UC3. +@param arr Input array + */ +CVAPI(int) cvGetElemType( const CvArr* arr ); + +/** @brief Return number of array dimensions + +The function returns the array dimensionality and the array of dimension sizes. In the case of +IplImage or CvMat it always returns 2 regardless of number of image/matrix rows. For example, the +following code calculates total number of array elements: +@code + int sizes[CV_MAX_DIM]; + int i, total = 1; + int dims = cvGetDims(arr, size); + for(i = 0; i < dims; i++ ) + total *= sizes[i]; +@endcode +@param arr Input array +@param sizes Optional output vector of the array dimension sizes. For 2d arrays the number of rows +(height) goes first, number of columns (width) next. + */ +CVAPI(int) cvGetDims( const CvArr* arr, int* sizes CV_DEFAULT(NULL) ); + + +/** @brief Returns array size along the specified dimension. + +@param arr Input array +@param index Zero-based dimension index (for matrices 0 means number of rows, 1 means number of +columns; for images 0 means height, 1 means width) + */ +CVAPI(int) cvGetDimSize( const CvArr* arr, int index ); + + +/** @brief Return pointer to a particular array element. + +The functions return a pointer to a specific array element. Number of array dimension should match +to the number of indices passed to the function except for cvPtr1D function that can be used for +sequential access to 1D, 2D or nD dense arrays. + +The functions can be used for sparse arrays as well - if the requested node does not exist they +create it and set it to zero. + +All these as well as other functions accessing array elements ( cvGetND , cvGetRealND , cvSet +, cvSetND , cvSetRealND ) raise an error in case if the element index is out of range. +@param arr Input array +@param idx0 The first zero-based component of the element index +@param type Optional output parameter: type of matrix elements + */ +CVAPI(uchar*) cvPtr1D( const CvArr* arr, int idx0, int* type CV_DEFAULT(NULL)); +/** @overload */ +CVAPI(uchar*) cvPtr2D( const CvArr* arr, int idx0, int idx1, int* type CV_DEFAULT(NULL) ); +/** @overload */ +CVAPI(uchar*) cvPtr3D( const CvArr* arr, int idx0, int idx1, int idx2, + int* type CV_DEFAULT(NULL)); +/** @overload +@param arr Input array +@param idx Array of the element indices +@param type Optional output parameter: type of matrix elements +@param create_node Optional input parameter for sparse matrices. Non-zero value of the parameter +means that the requested element is created if it does not exist already. +@param precalc_hashval Optional input parameter for sparse matrices. If the pointer is not NULL, +the function does not recalculate the node hash value, but takes it from the specified location. +It is useful for speeding up pair-wise operations (TODO: provide an example) +*/ +CVAPI(uchar*) cvPtrND( const CvArr* arr, const int* idx, int* type CV_DEFAULT(NULL), + int create_node CV_DEFAULT(1), + unsigned* precalc_hashval CV_DEFAULT(NULL)); + +/** @brief Return a specific array element. + +The functions return a specific array element. In the case of a sparse array the functions return 0 +if the requested node does not exist (no new node is created by the functions). +@param arr Input array +@param idx0 The first zero-based component of the element index + */ +CVAPI(CvScalar) cvGet1D( const CvArr* arr, int idx0 ); +/** @overload */ +CVAPI(CvScalar) cvGet2D( const CvArr* arr, int idx0, int idx1 ); +/** @overload */ +CVAPI(CvScalar) cvGet3D( const CvArr* arr, int idx0, int idx1, int idx2 ); +/** @overload +@param arr Input array +@param idx Array of the element indices +*/ +CVAPI(CvScalar) cvGetND( const CvArr* arr, const int* idx ); + +/** @brief Return a specific element of single-channel 1D, 2D, 3D or nD array. + +Returns a specific element of a single-channel array. If the array has multiple channels, a runtime +error is raised. Note that Get?D functions can be used safely for both single-channel and +multiple-channel arrays though they are a bit slower. + +In the case of a sparse array the functions return 0 if the requested node does not exist (no new +node is created by the functions). +@param arr Input array. Must have a single channel. +@param idx0 The first zero-based component of the element index + */ +CVAPI(double) cvGetReal1D( const CvArr* arr, int idx0 ); +/** @overload */ +CVAPI(double) cvGetReal2D( const CvArr* arr, int idx0, int idx1 ); +/** @overload */ +CVAPI(double) cvGetReal3D( const CvArr* arr, int idx0, int idx1, int idx2 ); +/** @overload +@param arr Input array. Must have a single channel. +@param idx Array of the element indices +*/ +CVAPI(double) cvGetRealND( const CvArr* arr, const int* idx ); + +/** @brief Change the particular array element. + +The functions assign the new value to a particular array element. In the case of a sparse array the +functions create the node if it does not exist yet. +@param arr Input array +@param idx0 The first zero-based component of the element index +@param value The assigned value + */ +CVAPI(void) cvSet1D( CvArr* arr, int idx0, CvScalar value ); +/** @overload */ +CVAPI(void) cvSet2D( CvArr* arr, int idx0, int idx1, CvScalar value ); +/** @overload */ +CVAPI(void) cvSet3D( CvArr* arr, int idx0, int idx1, int idx2, CvScalar value ); +/** @overload +@param arr Input array +@param idx Array of the element indices +@param value The assigned value +*/ +CVAPI(void) cvSetND( CvArr* arr, const int* idx, CvScalar value ); + +/** @brief Change a specific array element. + +The functions assign a new value to a specific element of a single-channel array. If the array has +multiple channels, a runtime error is raised. Note that the Set\*D function can be used safely for +both single-channel and multiple-channel arrays, though they are a bit slower. + +In the case of a sparse array the functions create the node if it does not yet exist. +@param arr Input array +@param idx0 The first zero-based component of the element index +@param value The assigned value + */ +CVAPI(void) cvSetReal1D( CvArr* arr, int idx0, double value ); +/** @overload */ +CVAPI(void) cvSetReal2D( CvArr* arr, int idx0, int idx1, double value ); +/** @overload */ +CVAPI(void) cvSetReal3D( CvArr* arr, int idx0, + int idx1, int idx2, double value ); +/** @overload +@param arr Input array +@param idx Array of the element indices +@param value The assigned value +*/ +CVAPI(void) cvSetRealND( CvArr* arr, const int* idx, double value ); + +/** clears element of ND dense array, + in case of sparse arrays it deletes the specified node */ +CVAPI(void) cvClearND( CvArr* arr, const int* idx ); + +/** @brief Returns matrix header for arbitrary array. + +The function returns a matrix header for the input array that can be a matrix - CvMat, an image - +IplImage, or a multi-dimensional dense array - CvMatND (the third option is allowed only if +allowND != 0) . In the case of matrix the function simply returns the input pointer. In the case of +IplImage\* or CvMatND it initializes the header structure with parameters of the current image ROI +and returns &header. Because COI is not supported by CvMat, it is returned separately. + +The function provides an easy way to handle both types of arrays - IplImage and CvMat using the same +code. Input array must have non-zero data pointer, otherwise the function will report an error. + +@note If the input array is IplImage with planar data layout and COI set, the function returns the +pointer to the selected plane and COI == 0. This feature allows user to process IplImage structures +with planar data layout, even though OpenCV does not support such images. +@param arr Input array +@param header Pointer to CvMat structure used as a temporary buffer +@param coi Optional output parameter for storing COI +@param allowND If non-zero, the function accepts multi-dimensional dense arrays (CvMatND\*) and +returns 2D matrix (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or +more than 2 dimensions). The CvMatND array must be continuous. +@sa cvGetImage, cvarrToMat. + */ +CVAPI(CvMat*) cvGetMat( const CvArr* arr, CvMat* header, + int* coi CV_DEFAULT(NULL), + int allowND CV_DEFAULT(0)); + +/** @brief Returns image header for arbitrary array. + +The function returns the image header for the input array that can be a matrix (CvMat) or image +(IplImage). In the case of an image the function simply returns the input pointer. In the case of +CvMat it initializes an image_header structure with the parameters of the input matrix. Note that +if we transform IplImage to CvMat using cvGetMat and then transform CvMat back to IplImage using +this function, we will get different headers if the ROI is set in the original image. +@param arr Input array +@param image_header Pointer to IplImage structure used as a temporary buffer + */ +CVAPI(IplImage*) cvGetImage( const CvArr* arr, IplImage* image_header ); + + +/** @brief Changes the shape of a multi-dimensional array without copying the data. + +The function is an advanced version of cvReshape that can work with multi-dimensional arrays as +well (though it can work with ordinary images and matrices) and change the number of dimensions. + +Below are the two samples from the cvReshape description rewritten using cvReshapeMatND: +@code + IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3); + IplImage gray_img_hdr, *gray_img; + gray_img = (IplImage*)cvReshapeMatND(color_img, sizeof(gray_img_hdr), &gray_img_hdr, 1, 0, 0); + ... + int size[] = { 2, 2, 2 }; + CvMatND* mat = cvCreateMatND(3, size, CV_32F); + CvMat row_header, *row; + row = (CvMat*)cvReshapeMatND(mat, sizeof(row_header), &row_header, 0, 1, 0); +@endcode +In C, the header file for this function includes a convenient macro cvReshapeND that does away with +the sizeof_header parameter. So, the lines containing the call to cvReshapeMatND in the examples +may be replaced as follow: +@code + gray_img = (IplImage*)cvReshapeND(color_img, &gray_img_hdr, 1, 0, 0); + ... + row = (CvMat*)cvReshapeND(mat, &row_header, 0, 1, 0); +@endcode +@param arr Input array +@param sizeof_header Size of output header to distinguish between IplImage, CvMat and CvMatND +output headers +@param header Output header to be filled +@param new_cn New number of channels. new_cn = 0 means that the number of channels remains +unchanged. +@param new_dims New number of dimensions. new_dims = 0 means that the number of dimensions +remains the same. +@param new_sizes Array of new dimension sizes. Only new_dims-1 values are used, because the +total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not +used. + */ +CVAPI(CvArr*) cvReshapeMatND( const CvArr* arr, + int sizeof_header, CvArr* header, + int new_cn, int new_dims, int* new_sizes ); + +#define cvReshapeND( arr, header, new_cn, new_dims, new_sizes ) \ + cvReshapeMatND( (arr), sizeof(*(header)), (header), \ + (new_cn), (new_dims), (new_sizes)) + +/** @brief Changes shape of matrix/image without copying data. + +The function initializes the CvMat header so that it points to the same data as the original array +but has a different shape - different number of channels, different number of rows, or both. + +The following example code creates one image buffer and two image headers, the first is for a +320x240x3 image and the second is for a 960x240x1 image: +@code + IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3); + CvMat gray_mat_hdr; + IplImage gray_img_hdr, *gray_img; + cvReshape(color_img, &gray_mat_hdr, 1); + gray_img = cvGetImage(&gray_mat_hdr, &gray_img_hdr); +@endcode +And the next example converts a 3x3 matrix to a single 1x9 vector: +@code + CvMat* mat = cvCreateMat(3, 3, CV_32F); + CvMat row_header, *row; + row = cvReshape(mat, &row_header, 0, 1); +@endcode +@param arr Input array +@param header Output header to be filled +@param new_cn New number of channels. 'new_cn = 0' means that the number of channels remains +unchanged. +@param new_rows New number of rows. 'new_rows = 0' means that the number of rows remains +unchanged unless it needs to be changed according to new_cn value. +*/ +CVAPI(CvMat*) cvReshape( const CvArr* arr, CvMat* header, + int new_cn, int new_rows CV_DEFAULT(0) ); + +/** Repeats source 2d array several times in both horizontal and + vertical direction to fill destination array */ +CVAPI(void) cvRepeat( const CvArr* src, CvArr* dst ); + +/** @brief Allocates array data + +The function allocates image, matrix or multi-dimensional dense array data. Note that in the case of +matrix types OpenCV allocation functions are used. In the case of IplImage they are used unless +CV_TURN_ON_IPL_COMPATIBILITY() has been called before. In the latter case IPL functions are used +to allocate the data. +@param arr Array header + */ +CVAPI(void) cvCreateData( CvArr* arr ); + +/** @brief Releases array data. + +The function releases the array data. In the case of CvMat or CvMatND it simply calls +cvDecRefData(), that is the function can not deallocate external data. See also the note to +cvCreateData . +@param arr Array header + */ +CVAPI(void) cvReleaseData( CvArr* arr ); + +/** @brief Assigns user data to the array header. + +The function assigns user data to the array header. Header should be initialized before using +cvCreateMatHeader, cvCreateImageHeader, cvCreateMatNDHeader, cvInitMatHeader, +cvInitImageHeader or cvInitMatNDHeader. +@param arr Array header +@param data User data +@param step Full row length in bytes + */ +CVAPI(void) cvSetData( CvArr* arr, void* data, int step ); + +/** @brief Retrieves low-level information about the array. + +The function fills output variables with low-level information about the array data. All output + +parameters are optional, so some of the pointers may be set to NULL. If the array is IplImage with +ROI set, the parameters of ROI are returned. + +The following example shows how to get access to array elements. It computes absolute values of the +array elements : +@code + float* data; + int step; + CvSize size; + + cvGetRawData(array, (uchar**)&data, &step, &size); + step /= sizeof(data[0]); + + for(int y = 0; y < size.height; y++, data += step ) + for(int x = 0; x < size.width; x++ ) + data[x] = (float)fabs(data[x]); +@endcode +@param arr Array header +@param data Output pointer to the whole image origin or ROI origin if ROI is set +@param step Output full row length in bytes +@param roi_size Output ROI size + */ +CVAPI(void) cvGetRawData( const CvArr* arr, uchar** data, + int* step CV_DEFAULT(NULL), + CvSize* roi_size CV_DEFAULT(NULL)); + +/** @brief Returns size of matrix or image ROI. + +The function returns number of rows (CvSize::height) and number of columns (CvSize::width) of the +input matrix or image. In the case of image the size of ROI is returned. +@param arr array header + */ +CVAPI(CvSize) cvGetSize( const CvArr* arr ); + +/** @brief Copies one array to another. + +The function copies selected elements from an input array to an output array: + +\f[\texttt{dst} (I)= \texttt{src} (I) \quad \text{if} \quad \texttt{mask} (I) \ne 0.\f] + +If any of the passed arrays is of IplImage type, then its ROI and COI fields are used. Both arrays +must have the same type, the same number of dimensions, and the same size. The function can also +copy sparse arrays (mask is not supported in this case). +@param src The source array +@param dst The destination array +@param mask Operation mask, 8-bit single channel array; specifies elements of the destination array +to be changed + */ +CVAPI(void) cvCopy( const CvArr* src, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @brief Sets every element of an array to a given value. + +The function copies the scalar value to every selected element of the destination array: +\f[\texttt{arr} (I)= \texttt{value} \quad \text{if} \quad \texttt{mask} (I) \ne 0\f] +If array arr is of IplImage type, then is ROI used, but COI must not be set. +@param arr The destination array +@param value Fill value +@param mask Operation mask, 8-bit single channel array; specifies elements of the destination +array to be changed + */ +CVAPI(void) cvSet( CvArr* arr, CvScalar value, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @brief Clears the array. + +The function clears the array. In the case of dense arrays (CvMat, CvMatND or IplImage), +cvZero(array) is equivalent to cvSet(array,cvScalarAll(0),0). In the case of sparse arrays all the +elements are removed. +@param arr Array to be cleared + */ +CVAPI(void) cvSetZero( CvArr* arr ); +#define cvZero cvSetZero + + +/** Splits a multi-channel array into the set of single-channel arrays or + extracts particular [color] plane */ +CVAPI(void) cvSplit( const CvArr* src, CvArr* dst0, CvArr* dst1, + CvArr* dst2, CvArr* dst3 ); + +/** Merges a set of single-channel arrays into the single multi-channel array + or inserts one particular [color] plane to the array */ +CVAPI(void) cvMerge( const CvArr* src0, const CvArr* src1, + const CvArr* src2, const CvArr* src3, + CvArr* dst ); + +/** Copies several channels from input arrays to + certain channels of output arrays */ +CVAPI(void) cvMixChannels( const CvArr** src, int src_count, + CvArr** dst, int dst_count, + const int* from_to, int pair_count ); + +/** @brief Converts one array to another with optional linear transformation. + +The function has several different purposes, and thus has several different names. It copies one +array to another with optional scaling, which is performed first, and/or optional type conversion, +performed after: + +\f[\texttt{dst} (I) = \texttt{scale} \texttt{src} (I) + ( \texttt{shift} _0, \texttt{shift} _1,...)\f] + +All the channels of multi-channel arrays are processed independently. + +The type of conversion is done with rounding and saturation, that is if the result of scaling + +conversion can not be represented exactly by a value of the destination array element type, it is +set to the nearest representable value on the real axis. +@param src Source array +@param dst Destination array +@param scale Scale factor +@param shift Value added to the scaled source array elements + */ +CVAPI(void) cvConvertScale( const CvArr* src, CvArr* dst, + double scale CV_DEFAULT(1), + double shift CV_DEFAULT(0) ); +#define cvCvtScale cvConvertScale +#define cvScale cvConvertScale +#define cvConvert( src, dst ) cvConvertScale( (src), (dst), 1, 0 ) + + +/** Performs linear transformation on every source array element, + stores absolute value of the result: + dst(x,y,c) = abs(scale*src(x,y,c)+shift). + destination array must have 8u type. + In other cases one may use cvConvertScale + cvAbsDiffS */ +CVAPI(void) cvConvertScaleAbs( const CvArr* src, CvArr* dst, + double scale CV_DEFAULT(1), + double shift CV_DEFAULT(0) ); +#define cvCvtScaleAbs cvConvertScaleAbs + + +/** checks termination criteria validity and + sets eps to default_eps (if it is not set), + max_iter to default_max_iters (if it is not set) +*/ +CVAPI(CvTermCriteria) cvCheckTermCriteria( CvTermCriteria criteria, + double default_eps, + int default_max_iters ); + +/****************************************************************************************\ +* Arithmetic, logic and comparison operations * +\****************************************************************************************/ + +/** dst(mask) = src1(mask) + src2(mask) */ +CVAPI(void) cvAdd( const CvArr* src1, const CvArr* src2, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(mask) = src(mask) + value */ +CVAPI(void) cvAddS( const CvArr* src, CvScalar value, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(mask) = src1(mask) - src2(mask) */ +CVAPI(void) cvSub( const CvArr* src1, const CvArr* src2, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(mask) = src(mask) - value = src(mask) + (-value) */ +CV_INLINE void cvSubS( const CvArr* src, CvScalar value, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL)) +{ + cvAddS( src, cvScalar( -value.val[0], -value.val[1], -value.val[2], -value.val[3]), + dst, mask ); +} + +/** dst(mask) = value - src(mask) */ +CVAPI(void) cvSubRS( const CvArr* src, CvScalar value, CvArr* dst, + const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src1(idx) * src2(idx) * scale + (scaled element-wise multiplication of 2 arrays) */ +CVAPI(void) cvMul( const CvArr* src1, const CvArr* src2, + CvArr* dst, double scale CV_DEFAULT(1) ); + +/** element-wise division/inversion with scaling: + dst(idx) = src1(idx) * scale / src2(idx) + or dst(idx) = scale / src2(idx) if src1 == 0 */ +CVAPI(void) cvDiv( const CvArr* src1, const CvArr* src2, + CvArr* dst, double scale CV_DEFAULT(1)); + +/** dst = src1 * scale + src2 */ +CVAPI(void) cvScaleAdd( const CvArr* src1, CvScalar scale, + const CvArr* src2, CvArr* dst ); +#define cvAXPY( A, real_scalar, B, C ) cvScaleAdd(A, cvRealScalar(real_scalar), B, C) + +/** dst = src1 * alpha + src2 * beta + gamma */ +CVAPI(void) cvAddWeighted( const CvArr* src1, double alpha, + const CvArr* src2, double beta, + double gamma, CvArr* dst ); + +/** @brief Calculates the dot product of two arrays in Euclidean metrics. + +The function calculates and returns the Euclidean dot product of two arrays. + +\f[src1 \bullet src2 = \sum _I ( \texttt{src1} (I) \texttt{src2} (I))\f] + +In the case of multiple channel arrays, the results for all channels are accumulated. In particular, +cvDotProduct(a,a) where a is a complex vector, will return \f$||\texttt{a}||^2\f$. The function can +process multi-dimensional arrays, row by row, layer by layer, and so on. +@param src1 The first source array +@param src2 The second source array + */ +CVAPI(double) cvDotProduct( const CvArr* src1, const CvArr* src2 ); + +/** dst(idx) = src1(idx) & src2(idx) */ +CVAPI(void) cvAnd( const CvArr* src1, const CvArr* src2, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src(idx) & value */ +CVAPI(void) cvAndS( const CvArr* src, CvScalar value, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src1(idx) | src2(idx) */ +CVAPI(void) cvOr( const CvArr* src1, const CvArr* src2, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src(idx) | value */ +CVAPI(void) cvOrS( const CvArr* src, CvScalar value, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src1(idx) ^ src2(idx) */ +CVAPI(void) cvXor( const CvArr* src1, const CvArr* src2, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = src(idx) ^ value */ +CVAPI(void) cvXorS( const CvArr* src, CvScalar value, + CvArr* dst, const CvArr* mask CV_DEFAULT(NULL)); + +/** dst(idx) = ~src(idx) */ +CVAPI(void) cvNot( const CvArr* src, CvArr* dst ); + +/** dst(idx) = lower(idx) <= src(idx) < upper(idx) */ +CVAPI(void) cvInRange( const CvArr* src, const CvArr* lower, + const CvArr* upper, CvArr* dst ); + +/** dst(idx) = lower <= src(idx) < upper */ +CVAPI(void) cvInRangeS( const CvArr* src, CvScalar lower, + CvScalar upper, CvArr* dst ); + +#define CV_CMP_EQ 0 +#define CV_CMP_GT 1 +#define CV_CMP_GE 2 +#define CV_CMP_LT 3 +#define CV_CMP_LE 4 +#define CV_CMP_NE 5 + +/** The comparison operation support single-channel arrays only. + Destination image should be 8uC1 or 8sC1 */ + +/** dst(idx) = src1(idx) _cmp_op_ src2(idx) */ +CVAPI(void) cvCmp( const CvArr* src1, const CvArr* src2, CvArr* dst, int cmp_op ); + +/** dst(idx) = src1(idx) _cmp_op_ value */ +CVAPI(void) cvCmpS( const CvArr* src, double value, CvArr* dst, int cmp_op ); + +/** dst(idx) = min(src1(idx),src2(idx)) */ +CVAPI(void) cvMin( const CvArr* src1, const CvArr* src2, CvArr* dst ); + +/** dst(idx) = max(src1(idx),src2(idx)) */ +CVAPI(void) cvMax( const CvArr* src1, const CvArr* src2, CvArr* dst ); + +/** dst(idx) = min(src(idx),value) */ +CVAPI(void) cvMinS( const CvArr* src, double value, CvArr* dst ); + +/** dst(idx) = max(src(idx),value) */ +CVAPI(void) cvMaxS( const CvArr* src, double value, CvArr* dst ); + +/** dst(x,y,c) = abs(src1(x,y,c) - src2(x,y,c)) */ +CVAPI(void) cvAbsDiff( const CvArr* src1, const CvArr* src2, CvArr* dst ); + +/** dst(x,y,c) = abs(src(x,y,c) - value(c)) */ +CVAPI(void) cvAbsDiffS( const CvArr* src, CvArr* dst, CvScalar value ); +#define cvAbs( src, dst ) cvAbsDiffS( (src), (dst), cvScalarAll(0)) + +/****************************************************************************************\ +* Math operations * +\****************************************************************************************/ + +/** Does cartesian->polar coordinates conversion. + Either of output components (magnitude or angle) is optional */ +CVAPI(void) cvCartToPolar( const CvArr* x, const CvArr* y, + CvArr* magnitude, CvArr* angle CV_DEFAULT(NULL), + int angle_in_degrees CV_DEFAULT(0)); + +/** Does polar->cartesian coordinates conversion. + Either of output components (magnitude or angle) is optional. + If magnitude is missing it is assumed to be all 1's */ +CVAPI(void) cvPolarToCart( const CvArr* magnitude, const CvArr* angle, + CvArr* x, CvArr* y, + int angle_in_degrees CV_DEFAULT(0)); + +/** Does powering: dst(idx) = src(idx)^power */ +CVAPI(void) cvPow( const CvArr* src, CvArr* dst, double power ); + +/** Does exponention: dst(idx) = exp(src(idx)). + Overflow is not handled yet. Underflow is handled. + Maximal relative error is ~7e-6 for single-precision input */ +CVAPI(void) cvExp( const CvArr* src, CvArr* dst ); + +/** Calculates natural logarithms: dst(idx) = log(abs(src(idx))). + Logarithm of 0 gives large negative number(~-700) + Maximal relative error is ~3e-7 for single-precision output +*/ +CVAPI(void) cvLog( const CvArr* src, CvArr* dst ); + +/** Fast arctangent calculation */ +CVAPI(float) cvFastArctan( float y, float x ); + +/** Fast cubic root calculation */ +CVAPI(float) cvCbrt( float value ); + +#define CV_CHECK_RANGE 1 +#define CV_CHECK_QUIET 2 +/** Checks array values for NaNs, Infs or simply for too large numbers + (if CV_CHECK_RANGE is set). If CV_CHECK_QUIET is set, + no runtime errors is raised (function returns zero value in case of "bad" values). + Otherwise cvError is called */ +CVAPI(int) cvCheckArr( const CvArr* arr, int flags CV_DEFAULT(0), + double min_val CV_DEFAULT(0), double max_val CV_DEFAULT(0)); +#define cvCheckArray cvCheckArr + +#define CV_RAND_UNI 0 +#define CV_RAND_NORMAL 1 + +/** @brief Fills an array with random numbers and updates the RNG state. + +The function fills the destination array with uniformly or normally distributed random numbers. +@param rng CvRNG state initialized by cvRNG +@param arr The destination array +@param dist_type Distribution type +> - **CV_RAND_UNI** uniform distribution +> - **CV_RAND_NORMAL** normal or Gaussian distribution +@param param1 The first parameter of the distribution. In the case of a uniform distribution it is +the inclusive lower boundary of the random numbers range. In the case of a normal distribution it +is the mean value of the random numbers. +@param param2 The second parameter of the distribution. In the case of a uniform distribution it +is the exclusive upper boundary of the random numbers range. In the case of a normal distribution +it is the standard deviation of the random numbers. +@sa randu, randn, RNG::fill. + */ +CVAPI(void) cvRandArr( CvRNG* rng, CvArr* arr, int dist_type, + CvScalar param1, CvScalar param2 ); + +CVAPI(void) cvRandShuffle( CvArr* mat, CvRNG* rng, + double iter_factor CV_DEFAULT(1.)); + +#define CV_SORT_EVERY_ROW 0 +#define CV_SORT_EVERY_COLUMN 1 +#define CV_SORT_ASCENDING 0 +#define CV_SORT_DESCENDING 16 + +CVAPI(void) cvSort( const CvArr* src, CvArr* dst CV_DEFAULT(NULL), + CvArr* idxmat CV_DEFAULT(NULL), + int flags CV_DEFAULT(0)); + +/** Finds real roots of a cubic equation */ +CVAPI(int) cvSolveCubic( const CvMat* coeffs, CvMat* roots ); + +/** Finds all real and complex roots of a polynomial equation */ +CVAPI(void) cvSolvePoly(const CvMat* coeffs, CvMat *roots2, + int maxiter CV_DEFAULT(20), int fig CV_DEFAULT(100)); + +/****************************************************************************************\ +* Matrix operations * +\****************************************************************************************/ + +/** @brief Calculates the cross product of two 3D vectors. + +The function calculates the cross product of two 3D vectors: +\f[\texttt{dst} = \texttt{src1} \times \texttt{src2}\f] +or: +\f[\begin{array}{l} \texttt{dst} _1 = \texttt{src1} _2 \texttt{src2} _3 - \texttt{src1} _3 \texttt{src2} _2 \\ \texttt{dst} _2 = \texttt{src1} _3 \texttt{src2} _1 - \texttt{src1} _1 \texttt{src2} _3 \\ \texttt{dst} _3 = \texttt{src1} _1 \texttt{src2} _2 - \texttt{src1} _2 \texttt{src2} _1 \end{array}\f] +@param src1 The first source vector +@param src2 The second source vector +@param dst The destination vector + */ +CVAPI(void) cvCrossProduct( const CvArr* src1, const CvArr* src2, CvArr* dst ); + +/** Matrix transform: dst = A*B + C, C is optional */ +#define cvMatMulAdd( src1, src2, src3, dst ) cvGEMM( (src1), (src2), 1., (src3), 1., (dst), 0 ) +#define cvMatMul( src1, src2, dst ) cvMatMulAdd( (src1), (src2), NULL, (dst)) + +#define CV_GEMM_A_T 1 +#define CV_GEMM_B_T 2 +#define CV_GEMM_C_T 4 +/** Extended matrix transform: + dst = alpha*op(A)*op(B) + beta*op(C), where op(X) is X or X^T */ +CVAPI(void) cvGEMM( const CvArr* src1, const CvArr* src2, double alpha, + const CvArr* src3, double beta, CvArr* dst, + int tABC CV_DEFAULT(0)); +#define cvMatMulAddEx cvGEMM + +/** Transforms each element of source array and stores + resultant vectors in destination array */ +CVAPI(void) cvTransform( const CvArr* src, CvArr* dst, + const CvMat* transmat, + const CvMat* shiftvec CV_DEFAULT(NULL)); +#define cvMatMulAddS cvTransform + +/** Does perspective transform on every element of input array */ +CVAPI(void) cvPerspectiveTransform( const CvArr* src, CvArr* dst, + const CvMat* mat ); + +/** Calculates (A-delta)*(A-delta)^T (order=0) or (A-delta)^T*(A-delta) (order=1) */ +CVAPI(void) cvMulTransposed( const CvArr* src, CvArr* dst, int order, + const CvArr* delta CV_DEFAULT(NULL), + double scale CV_DEFAULT(1.) ); + +/** Tranposes matrix. Square matrices can be transposed in-place */ +CVAPI(void) cvTranspose( const CvArr* src, CvArr* dst ); +#define cvT cvTranspose + +/** Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part */ +CVAPI(void) cvCompleteSymm( CvMat* matrix, int LtoR CV_DEFAULT(0) ); + +/** Mirror array data around horizontal (flip=0), + vertical (flip=1) or both(flip=-1) axises: + cvFlip(src) flips images vertically and sequences horizontally (inplace) */ +CVAPI(void) cvFlip( const CvArr* src, CvArr* dst CV_DEFAULT(NULL), + int flip_mode CV_DEFAULT(0)); +#define cvMirror cvFlip + + +#define CV_SVD_MODIFY_A 1 +#define CV_SVD_U_T 2 +#define CV_SVD_V_T 4 + +/** Performs Singular Value Decomposition of a matrix */ +CVAPI(void) cvSVD( CvArr* A, CvArr* W, CvArr* U CV_DEFAULT(NULL), + CvArr* V CV_DEFAULT(NULL), int flags CV_DEFAULT(0)); + +/** Performs Singular Value Back Substitution (solves A*X = B): + flags must be the same as in cvSVD */ +CVAPI(void) cvSVBkSb( const CvArr* W, const CvArr* U, + const CvArr* V, const CvArr* B, + CvArr* X, int flags ); + +#define CV_LU 0 +#define CV_SVD 1 +#define CV_SVD_SYM 2 +#define CV_CHOLESKY 3 +#define CV_QR 4 +#define CV_NORMAL 16 + +/** Inverts matrix */ +CVAPI(double) cvInvert( const CvArr* src, CvArr* dst, + int method CV_DEFAULT(CV_LU)); +#define cvInv cvInvert + +/** Solves linear system (src1)*(dst) = (src2) + (returns 0 if src1 is a singular and CV_LU method is used) */ +CVAPI(int) cvSolve( const CvArr* src1, const CvArr* src2, CvArr* dst, + int method CV_DEFAULT(CV_LU)); + +/** Calculates determinant of input matrix */ +CVAPI(double) cvDet( const CvArr* mat ); + +/** Calculates trace of the matrix (sum of elements on the main diagonal) */ +CVAPI(CvScalar) cvTrace( const CvArr* mat ); + +/** Finds eigen values and vectors of a symmetric matrix */ +CVAPI(void) cvEigenVV( CvArr* mat, CvArr* evects, CvArr* evals, + double eps CV_DEFAULT(0), + int lowindex CV_DEFAULT(-1), + int highindex CV_DEFAULT(-1)); + +///* Finds selected eigen values and vectors of a symmetric matrix */ +//CVAPI(void) cvSelectedEigenVV( CvArr* mat, CvArr* evects, CvArr* evals, +// int lowindex, int highindex ); + +/** Makes an identity matrix (mat_ij = i == j) */ +CVAPI(void) cvSetIdentity( CvArr* mat, CvScalar value CV_DEFAULT(cvRealScalar(1)) ); + +/** Fills matrix with given range of numbers */ +CVAPI(CvArr*) cvRange( CvArr* mat, double start, double end ); + +/** @anchor core_c_CovarFlags +@name Flags for cvCalcCovarMatrix +@see cvCalcCovarMatrix + @{ +*/ + +/** flag for cvCalcCovarMatrix, transpose([v1-avg, v2-avg,...]) * [v1-avg,v2-avg,...] */ +#define CV_COVAR_SCRAMBLED 0 + +/** flag for cvCalcCovarMatrix, [v1-avg, v2-avg,...] * transpose([v1-avg,v2-avg,...]) */ +#define CV_COVAR_NORMAL 1 + +/** flag for cvCalcCovarMatrix, do not calc average (i.e. mean vector) - use the input vector instead + (useful for calculating covariance matrix by parts) */ +#define CV_COVAR_USE_AVG 2 + +/** flag for cvCalcCovarMatrix, scale the covariance matrix coefficients by number of the vectors */ +#define CV_COVAR_SCALE 4 + +/** flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its rows */ +#define CV_COVAR_ROWS 8 + +/** flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its columns */ +#define CV_COVAR_COLS 16 + +/** @} */ + +/** Calculates covariation matrix for a set of vectors +@see @ref core_c_CovarFlags "flags" +*/ +CVAPI(void) cvCalcCovarMatrix( const CvArr** vects, int count, + CvArr* cov_mat, CvArr* avg, int flags ); + +#define CV_PCA_DATA_AS_ROW 0 +#define CV_PCA_DATA_AS_COL 1 +#define CV_PCA_USE_AVG 2 +CVAPI(void) cvCalcPCA( const CvArr* data, CvArr* mean, + CvArr* eigenvals, CvArr* eigenvects, int flags ); + +CVAPI(void) cvProjectPCA( const CvArr* data, const CvArr* mean, + const CvArr* eigenvects, CvArr* result ); + +CVAPI(void) cvBackProjectPCA( const CvArr* proj, const CvArr* mean, + const CvArr* eigenvects, CvArr* result ); + +/** Calculates Mahalanobis(weighted) distance */ +CVAPI(double) cvMahalanobis( const CvArr* vec1, const CvArr* vec2, const CvArr* mat ); +#define cvMahalonobis cvMahalanobis + +/****************************************************************************************\ +* Array Statistics * +\****************************************************************************************/ + +/** Finds sum of array elements */ +CVAPI(CvScalar) cvSum( const CvArr* arr ); + +/** Calculates number of non-zero pixels */ +CVAPI(int) cvCountNonZero( const CvArr* arr ); + +/** Calculates mean value of array elements */ +CVAPI(CvScalar) cvAvg( const CvArr* arr, const CvArr* mask CV_DEFAULT(NULL) ); + +/** Calculates mean and standard deviation of pixel values */ +CVAPI(void) cvAvgSdv( const CvArr* arr, CvScalar* mean, CvScalar* std_dev, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** Finds global minimum, maximum and their positions */ +CVAPI(void) cvMinMaxLoc( const CvArr* arr, double* min_val, double* max_val, + CvPoint* min_loc CV_DEFAULT(NULL), + CvPoint* max_loc CV_DEFAULT(NULL), + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @anchor core_c_NormFlags + @name Flags for cvNorm and cvNormalize + @{ +*/ +#define CV_C 1 +#define CV_L1 2 +#define CV_L2 4 +#define CV_NORM_MASK 7 +#define CV_RELATIVE 8 +#define CV_DIFF 16 +#define CV_MINMAX 32 + +#define CV_DIFF_C (CV_DIFF | CV_C) +#define CV_DIFF_L1 (CV_DIFF | CV_L1) +#define CV_DIFF_L2 (CV_DIFF | CV_L2) +#define CV_RELATIVE_C (CV_RELATIVE | CV_C) +#define CV_RELATIVE_L1 (CV_RELATIVE | CV_L1) +#define CV_RELATIVE_L2 (CV_RELATIVE | CV_L2) +/** @} */ + +/** Finds norm, difference norm or relative difference norm for an array (or two arrays) +@see ref core_c_NormFlags "flags" +*/ +CVAPI(double) cvNorm( const CvArr* arr1, const CvArr* arr2 CV_DEFAULT(NULL), + int norm_type CV_DEFAULT(CV_L2), + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @see ref core_c_NormFlags "flags" */ +CVAPI(void) cvNormalize( const CvArr* src, CvArr* dst, + double a CV_DEFAULT(1.), double b CV_DEFAULT(0.), + int norm_type CV_DEFAULT(CV_L2), + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @anchor core_c_ReduceFlags + @name Flags for cvReduce + @{ +*/ +#define CV_REDUCE_SUM 0 +#define CV_REDUCE_AVG 1 +#define CV_REDUCE_MAX 2 +#define CV_REDUCE_MIN 3 +/** @} */ + +/** @see @ref core_c_ReduceFlags "flags" */ +CVAPI(void) cvReduce( const CvArr* src, CvArr* dst, int dim CV_DEFAULT(-1), + int op CV_DEFAULT(CV_REDUCE_SUM) ); + +/****************************************************************************************\ +* Discrete Linear Transforms and Related Functions * +\****************************************************************************************/ + +/** @anchor core_c_DftFlags + @name Flags for cvDFT, cvDCT and cvMulSpectrums + @{ + */ +#define CV_DXT_FORWARD 0 +#define CV_DXT_INVERSE 1 +#define CV_DXT_SCALE 2 /**< divide result by size of array */ +#define CV_DXT_INV_SCALE (CV_DXT_INVERSE + CV_DXT_SCALE) +#define CV_DXT_INVERSE_SCALE CV_DXT_INV_SCALE +#define CV_DXT_ROWS 4 /**< transform each row individually */ +#define CV_DXT_MUL_CONJ 8 /**< conjugate the second argument of cvMulSpectrums */ +/** @} */ + +/** Discrete Fourier Transform: + complex->complex, + real->ccs (forward), + ccs->real (inverse) +@see core_c_DftFlags "flags" +*/ +CVAPI(void) cvDFT( const CvArr* src, CvArr* dst, int flags, + int nonzero_rows CV_DEFAULT(0) ); +#define cvFFT cvDFT + +/** Multiply results of DFTs: DFT(X)*DFT(Y) or DFT(X)*conj(DFT(Y)) +@see core_c_DftFlags "flags" +*/ +CVAPI(void) cvMulSpectrums( const CvArr* src1, const CvArr* src2, + CvArr* dst, int flags ); + +/** Finds optimal DFT vector size >= size0 */ +CVAPI(int) cvGetOptimalDFTSize( int size0 ); + +/** Discrete Cosine Transform +@see core_c_DftFlags "flags" +*/ +CVAPI(void) cvDCT( const CvArr* src, CvArr* dst, int flags ); + +/****************************************************************************************\ +* Dynamic data structures * +\****************************************************************************************/ + +/** Calculates length of sequence slice (with support of negative indices). */ +CVAPI(int) cvSliceLength( CvSlice slice, const CvSeq* seq ); + + +/** Creates new memory storage. + block_size == 0 means that default, + somewhat optimal size, is used (currently, it is 64K) */ +CVAPI(CvMemStorage*) cvCreateMemStorage( int block_size CV_DEFAULT(0)); + + +/** Creates a memory storage that will borrow memory blocks from parent storage */ +CVAPI(CvMemStorage*) cvCreateChildMemStorage( CvMemStorage* parent ); + + +/** Releases memory storage. All the children of a parent must be released before + the parent. A child storage returns all the blocks to parent when it is released */ +CVAPI(void) cvReleaseMemStorage( CvMemStorage** storage ); + + +/** Clears memory storage. This is the only way(!!!) (besides cvRestoreMemStoragePos) + to reuse memory allocated for the storage - cvClearSeq,cvClearSet ... + do not free any memory. + A child storage returns all the blocks to the parent when it is cleared */ +CVAPI(void) cvClearMemStorage( CvMemStorage* storage ); + +/** Remember a storage "free memory" position */ +CVAPI(void) cvSaveMemStoragePos( const CvMemStorage* storage, CvMemStoragePos* pos ); + +/** Restore a storage "free memory" position */ +CVAPI(void) cvRestoreMemStoragePos( CvMemStorage* storage, CvMemStoragePos* pos ); + +/** Allocates continuous buffer of the specified size in the storage */ +CVAPI(void*) cvMemStorageAlloc( CvMemStorage* storage, size_t size ); + +/** Allocates string in memory storage */ +CVAPI(CvString) cvMemStorageAllocString( CvMemStorage* storage, const char* ptr, + int len CV_DEFAULT(-1) ); + +/** Creates new empty sequence that will reside in the specified storage */ +CVAPI(CvSeq*) cvCreateSeq( int seq_flags, size_t header_size, + size_t elem_size, CvMemStorage* storage ); + +/** Changes default size (granularity) of sequence blocks. + The default size is ~1Kbyte */ +CVAPI(void) cvSetSeqBlockSize( CvSeq* seq, int delta_elems ); + + +/** Adds new element to the end of sequence. Returns pointer to the element */ +CVAPI(schar*) cvSeqPush( CvSeq* seq, const void* element CV_DEFAULT(NULL)); + + +/** Adds new element to the beginning of sequence. Returns pointer to it */ +CVAPI(schar*) cvSeqPushFront( CvSeq* seq, const void* element CV_DEFAULT(NULL)); + + +/** Removes the last element from sequence and optionally saves it */ +CVAPI(void) cvSeqPop( CvSeq* seq, void* element CV_DEFAULT(NULL)); + + +/** Removes the first element from sequence and optioanally saves it */ +CVAPI(void) cvSeqPopFront( CvSeq* seq, void* element CV_DEFAULT(NULL)); + + +#define CV_FRONT 1 +#define CV_BACK 0 +/** Adds several new elements to the end of sequence */ +CVAPI(void) cvSeqPushMulti( CvSeq* seq, const void* elements, + int count, int in_front CV_DEFAULT(0) ); + +/** Removes several elements from the end of sequence and optionally saves them */ +CVAPI(void) cvSeqPopMulti( CvSeq* seq, void* elements, + int count, int in_front CV_DEFAULT(0) ); + +/** Inserts a new element in the middle of sequence. + cvSeqInsert(seq,0,elem) == cvSeqPushFront(seq,elem) */ +CVAPI(schar*) cvSeqInsert( CvSeq* seq, int before_index, + const void* element CV_DEFAULT(NULL)); + +/** Removes specified sequence element */ +CVAPI(void) cvSeqRemove( CvSeq* seq, int index ); + + +/** Removes all the elements from the sequence. The freed memory + can be reused later only by the same sequence unless cvClearMemStorage + or cvRestoreMemStoragePos is called */ +CVAPI(void) cvClearSeq( CvSeq* seq ); + + +/** Retrieves pointer to specified sequence element. + Negative indices are supported and mean counting from the end + (e.g -1 means the last sequence element) */ +CVAPI(schar*) cvGetSeqElem( const CvSeq* seq, int index ); + +/** Calculates index of the specified sequence element. + Returns -1 if element does not belong to the sequence */ +CVAPI(int) cvSeqElemIdx( const CvSeq* seq, const void* element, + CvSeqBlock** block CV_DEFAULT(NULL) ); + +/** Initializes sequence writer. The new elements will be added to the end of sequence */ +CVAPI(void) cvStartAppendToSeq( CvSeq* seq, CvSeqWriter* writer ); + + +/** Combination of cvCreateSeq and cvStartAppendToSeq */ +CVAPI(void) cvStartWriteSeq( int seq_flags, int header_size, + int elem_size, CvMemStorage* storage, + CvSeqWriter* writer ); + +/** Closes sequence writer, updates sequence header and returns pointer + to the resultant sequence + (which may be useful if the sequence was created using cvStartWriteSeq)) +*/ +CVAPI(CvSeq*) cvEndWriteSeq( CvSeqWriter* writer ); + + +/** Updates sequence header. May be useful to get access to some of previously + written elements via cvGetSeqElem or sequence reader */ +CVAPI(void) cvFlushSeqWriter( CvSeqWriter* writer ); + + +/** Initializes sequence reader. + The sequence can be read in forward or backward direction */ +CVAPI(void) cvStartReadSeq( const CvSeq* seq, CvSeqReader* reader, + int reverse CV_DEFAULT(0) ); + + +/** Returns current sequence reader position (currently observed sequence element) */ +CVAPI(int) cvGetSeqReaderPos( CvSeqReader* reader ); + + +/** Changes sequence reader position. It may seek to an absolute or + to relative to the current position */ +CVAPI(void) cvSetSeqReaderPos( CvSeqReader* reader, int index, + int is_relative CV_DEFAULT(0)); + +/** Copies sequence content to a continuous piece of memory */ +CVAPI(void*) cvCvtSeqToArray( const CvSeq* seq, void* elements, + CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ) ); + +/** Creates sequence header for array. + After that all the operations on sequences that do not alter the content + can be applied to the resultant sequence */ +CVAPI(CvSeq*) cvMakeSeqHeaderForArray( int seq_type, int header_size, + int elem_size, void* elements, int total, + CvSeq* seq, CvSeqBlock* block ); + +/** Extracts sequence slice (with or without copying sequence elements) */ +CVAPI(CvSeq*) cvSeqSlice( const CvSeq* seq, CvSlice slice, + CvMemStorage* storage CV_DEFAULT(NULL), + int copy_data CV_DEFAULT(0)); + +CV_INLINE CvSeq* cvCloneSeq( const CvSeq* seq, CvMemStorage* storage CV_DEFAULT(NULL)) +{ + return cvSeqSlice( seq, CV_WHOLE_SEQ, storage, 1 ); +} + +/** Removes sequence slice */ +CVAPI(void) cvSeqRemoveSlice( CvSeq* seq, CvSlice slice ); + +/** Inserts a sequence or array into another sequence */ +CVAPI(void) cvSeqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr ); + +/** a < b ? -1 : a > b ? 1 : 0 */ +typedef int (CV_CDECL* CvCmpFunc)(const void* a, const void* b, void* userdata ); + +/** Sorts sequence in-place given element comparison function */ +CVAPI(void) cvSeqSort( CvSeq* seq, CvCmpFunc func, void* userdata CV_DEFAULT(NULL) ); + +/** Finds element in a [sorted] sequence */ +CVAPI(schar*) cvSeqSearch( CvSeq* seq, const void* elem, CvCmpFunc func, + int is_sorted, int* elem_idx, + void* userdata CV_DEFAULT(NULL) ); + +/** Reverses order of sequence elements in-place */ +CVAPI(void) cvSeqInvert( CvSeq* seq ); + +/** Splits sequence into one or more equivalence classes using the specified criteria */ +CVAPI(int) cvSeqPartition( const CvSeq* seq, CvMemStorage* storage, + CvSeq** labels, CvCmpFunc is_equal, void* userdata ); + +/************ Internal sequence functions ************/ +CVAPI(void) cvChangeSeqBlock( void* reader, int direction ); +CVAPI(void) cvCreateSeqBlock( CvSeqWriter* writer ); + + +/** Creates a new set */ +CVAPI(CvSet*) cvCreateSet( int set_flags, int header_size, + int elem_size, CvMemStorage* storage ); + +/** Adds new element to the set and returns pointer to it */ +CVAPI(int) cvSetAdd( CvSet* set_header, CvSetElem* elem CV_DEFAULT(NULL), + CvSetElem** inserted_elem CV_DEFAULT(NULL) ); + +/** Fast variant of cvSetAdd */ +CV_INLINE CvSetElem* cvSetNew( CvSet* set_header ) +{ + CvSetElem* elem = set_header->free_elems; + if( elem ) + { + set_header->free_elems = elem->next_free; + elem->flags = elem->flags & CV_SET_ELEM_IDX_MASK; + set_header->active_count++; + } + else + cvSetAdd( set_header, NULL, &elem ); + return elem; +} + +/** Removes set element given its pointer */ +CV_INLINE void cvSetRemoveByPtr( CvSet* set_header, void* elem ) +{ + CvSetElem* _elem = (CvSetElem*)elem; + assert( _elem->flags >= 0 /*&& (elem->flags & CV_SET_ELEM_IDX_MASK) < set_header->total*/ ); + _elem->next_free = set_header->free_elems; + _elem->flags = (_elem->flags & CV_SET_ELEM_IDX_MASK) | CV_SET_ELEM_FREE_FLAG; + set_header->free_elems = _elem; + set_header->active_count--; +} + +/** Removes element from the set by its index */ +CVAPI(void) cvSetRemove( CvSet* set_header, int index ); + +/** Returns a set element by index. If the element doesn't belong to the set, + NULL is returned */ +CV_INLINE CvSetElem* cvGetSetElem( const CvSet* set_header, int idx ) +{ + CvSetElem* elem = (CvSetElem*)(void *)cvGetSeqElem( (CvSeq*)set_header, idx ); + return elem && CV_IS_SET_ELEM( elem ) ? elem : 0; +} + +/** Removes all the elements from the set */ +CVAPI(void) cvClearSet( CvSet* set_header ); + +/** Creates new graph */ +CVAPI(CvGraph*) cvCreateGraph( int graph_flags, int header_size, + int vtx_size, int edge_size, + CvMemStorage* storage ); + +/** Adds new vertex to the graph */ +CVAPI(int) cvGraphAddVtx( CvGraph* graph, const CvGraphVtx* vtx CV_DEFAULT(NULL), + CvGraphVtx** inserted_vtx CV_DEFAULT(NULL) ); + + +/** Removes vertex from the graph together with all incident edges */ +CVAPI(int) cvGraphRemoveVtx( CvGraph* graph, int index ); +CVAPI(int) cvGraphRemoveVtxByPtr( CvGraph* graph, CvGraphVtx* vtx ); + + +/** Link two vertices specified by indices or pointers if they + are not connected or return pointer to already existing edge + connecting the vertices. + Functions return 1 if a new edge was created, 0 otherwise */ +CVAPI(int) cvGraphAddEdge( CvGraph* graph, + int start_idx, int end_idx, + const CvGraphEdge* edge CV_DEFAULT(NULL), + CvGraphEdge** inserted_edge CV_DEFAULT(NULL) ); + +CVAPI(int) cvGraphAddEdgeByPtr( CvGraph* graph, + CvGraphVtx* start_vtx, CvGraphVtx* end_vtx, + const CvGraphEdge* edge CV_DEFAULT(NULL), + CvGraphEdge** inserted_edge CV_DEFAULT(NULL) ); + +/** Remove edge connecting two vertices */ +CVAPI(void) cvGraphRemoveEdge( CvGraph* graph, int start_idx, int end_idx ); +CVAPI(void) cvGraphRemoveEdgeByPtr( CvGraph* graph, CvGraphVtx* start_vtx, + CvGraphVtx* end_vtx ); + +/** Find edge connecting two vertices */ +CVAPI(CvGraphEdge*) cvFindGraphEdge( const CvGraph* graph, int start_idx, int end_idx ); +CVAPI(CvGraphEdge*) cvFindGraphEdgeByPtr( const CvGraph* graph, + const CvGraphVtx* start_vtx, + const CvGraphVtx* end_vtx ); +#define cvGraphFindEdge cvFindGraphEdge +#define cvGraphFindEdgeByPtr cvFindGraphEdgeByPtr + +/** Remove all vertices and edges from the graph */ +CVAPI(void) cvClearGraph( CvGraph* graph ); + + +/** Count number of edges incident to the vertex */ +CVAPI(int) cvGraphVtxDegree( const CvGraph* graph, int vtx_idx ); +CVAPI(int) cvGraphVtxDegreeByPtr( const CvGraph* graph, const CvGraphVtx* vtx ); + + +/** Retrieves graph vertex by given index */ +#define cvGetGraphVtx( graph, idx ) (CvGraphVtx*)cvGetSetElem((CvSet*)(graph), (idx)) + +/** Retrieves index of a graph vertex given its pointer */ +#define cvGraphVtxIdx( graph, vtx ) ((vtx)->flags & CV_SET_ELEM_IDX_MASK) + +/** Retrieves index of a graph edge given its pointer */ +#define cvGraphEdgeIdx( graph, edge ) ((edge)->flags & CV_SET_ELEM_IDX_MASK) + +#define cvGraphGetVtxCount( graph ) ((graph)->active_count) +#define cvGraphGetEdgeCount( graph ) ((graph)->edges->active_count) + +#define CV_GRAPH_VERTEX 1 +#define CV_GRAPH_TREE_EDGE 2 +#define CV_GRAPH_BACK_EDGE 4 +#define CV_GRAPH_FORWARD_EDGE 8 +#define CV_GRAPH_CROSS_EDGE 16 +#define CV_GRAPH_ANY_EDGE 30 +#define CV_GRAPH_NEW_TREE 32 +#define CV_GRAPH_BACKTRACKING 64 +#define CV_GRAPH_OVER -1 + +#define CV_GRAPH_ALL_ITEMS -1 + +/** flags for graph vertices and edges */ +#define CV_GRAPH_ITEM_VISITED_FLAG (1 << 30) +#define CV_IS_GRAPH_VERTEX_VISITED(vtx) \ + (((CvGraphVtx*)(vtx))->flags & CV_GRAPH_ITEM_VISITED_FLAG) +#define CV_IS_GRAPH_EDGE_VISITED(edge) \ + (((CvGraphEdge*)(edge))->flags & CV_GRAPH_ITEM_VISITED_FLAG) +#define CV_GRAPH_SEARCH_TREE_NODE_FLAG (1 << 29) +#define CV_GRAPH_FORWARD_EDGE_FLAG (1 << 28) + +typedef struct CvGraphScanner +{ + CvGraphVtx* vtx; /* current graph vertex (or current edge origin) */ + CvGraphVtx* dst; /* current graph edge destination vertex */ + CvGraphEdge* edge; /* current edge */ + + CvGraph* graph; /* the graph */ + CvSeq* stack; /* the graph vertex stack */ + int index; /* the lower bound of certainly visited vertices */ + int mask; /* event mask */ +} +CvGraphScanner; + +/** Creates new graph scanner. */ +CVAPI(CvGraphScanner*) cvCreateGraphScanner( CvGraph* graph, + CvGraphVtx* vtx CV_DEFAULT(NULL), + int mask CV_DEFAULT(CV_GRAPH_ALL_ITEMS)); + +/** Releases graph scanner. */ +CVAPI(void) cvReleaseGraphScanner( CvGraphScanner** scanner ); + +/** Get next graph element */ +CVAPI(int) cvNextGraphItem( CvGraphScanner* scanner ); + +/** Creates a copy of graph */ +CVAPI(CvGraph*) cvCloneGraph( const CvGraph* graph, CvMemStorage* storage ); + + +/** Does look-up transformation. Elements of the source array + (that should be 8uC1 or 8sC1) are used as indexes in lutarr 256-element table */ +CVAPI(void) cvLUT( const CvArr* src, CvArr* dst, const CvArr* lut ); + + +/******************* Iteration through the sequence tree *****************/ +typedef struct CvTreeNodeIterator +{ + const void* node; + int level; + int max_level; +} +CvTreeNodeIterator; + +CVAPI(void) cvInitTreeNodeIterator( CvTreeNodeIterator* tree_iterator, + const void* first, int max_level ); +CVAPI(void*) cvNextTreeNode( CvTreeNodeIterator* tree_iterator ); +CVAPI(void*) cvPrevTreeNode( CvTreeNodeIterator* tree_iterator ); + +/** Inserts sequence into tree with specified "parent" sequence. + If parent is equal to frame (e.g. the most external contour), + then added contour will have null pointer to parent. */ +CVAPI(void) cvInsertNodeIntoTree( void* node, void* parent, void* frame ); + +/** Removes contour from tree (together with the contour children). */ +CVAPI(void) cvRemoveNodeFromTree( void* node, void* frame ); + +/** Gathers pointers to all the sequences, + accessible from the `first`, to the single sequence */ +CVAPI(CvSeq*) cvTreeToNodeSeq( const void* first, int header_size, + CvMemStorage* storage ); + +/** The function implements the K-means algorithm for clustering an array of sample + vectors in a specified number of classes */ +#define CV_KMEANS_USE_INITIAL_LABELS 1 +CVAPI(int) cvKMeans2( const CvArr* samples, int cluster_count, CvArr* labels, + CvTermCriteria termcrit, int attempts CV_DEFAULT(1), + CvRNG* rng CV_DEFAULT(0), int flags CV_DEFAULT(0), + CvArr* _centers CV_DEFAULT(0), double* compactness CV_DEFAULT(0) ); + +/****************************************************************************************\ +* System functions * +\****************************************************************************************/ + +/** Loads optimized functions from IPP, MKL etc. or switches back to pure C code */ +CVAPI(int) cvUseOptimized( int on_off ); + +typedef IplImage* (CV_STDCALL* Cv_iplCreateImageHeader) + (int,int,int,char*,char*,int,int,int,int,int, + IplROI*,IplImage*,void*,IplTileInfo*); +typedef void (CV_STDCALL* Cv_iplAllocateImageData)(IplImage*,int,int); +typedef void (CV_STDCALL* Cv_iplDeallocate)(IplImage*,int); +typedef IplROI* (CV_STDCALL* Cv_iplCreateROI)(int,int,int,int,int); +typedef IplImage* (CV_STDCALL* Cv_iplCloneImage)(const IplImage*); + +/** @brief Makes OpenCV use IPL functions for allocating IplImage and IplROI structures. + +Normally, the function is not called directly. Instead, a simple macro +CV_TURN_ON_IPL_COMPATIBILITY() is used that calls cvSetIPLAllocators and passes there pointers +to IPL allocation functions. : +@code + ... + CV_TURN_ON_IPL_COMPATIBILITY() + ... +@endcode +@param create_header pointer to a function, creating IPL image header. +@param allocate_data pointer to a function, allocating IPL image data. +@param deallocate pointer to a function, deallocating IPL image. +@param create_roi pointer to a function, creating IPL image ROI (i.e. Region of Interest). +@param clone_image pointer to a function, cloning an IPL image. + */ +CVAPI(void) cvSetIPLAllocators( Cv_iplCreateImageHeader create_header, + Cv_iplAllocateImageData allocate_data, + Cv_iplDeallocate deallocate, + Cv_iplCreateROI create_roi, + Cv_iplCloneImage clone_image ); + +#define CV_TURN_ON_IPL_COMPATIBILITY() \ + cvSetIPLAllocators( iplCreateImageHeader, iplAllocateImage, \ + iplDeallocate, iplCreateROI, iplCloneImage ) + +/****************************************************************************************\ +* Data Persistence * +\****************************************************************************************/ + +/********************************** High-level functions ********************************/ + +/** @brief Opens file storage for reading or writing data. + +The function opens file storage for reading or writing data. In the latter case, a new file is +created or an existing file is rewritten. The type of the read or written file is determined by the +filename extension: .xml for XML, .yml or .yaml for YAML and .json for JSON. + +At the same time, it also supports adding parameters like "example.xml?base64". + +The function returns a pointer to the CvFileStorage structure. +If the file cannot be opened then the function returns NULL. +@param filename Name of the file associated with the storage +@param memstorage Memory storage used for temporary data and for +: storing dynamic structures, such as CvSeq or CvGraph . If it is NULL, a temporary memory + storage is created and used. +@param flags Can be one of the following: +> - **CV_STORAGE_READ** the storage is open for reading +> - **CV_STORAGE_WRITE** the storage is open for writing + (use **CV_STORAGE_WRITE | CV_STORAGE_WRITE_BASE64** to write rawdata in Base64) +@param encoding + */ +CVAPI(CvFileStorage*) cvOpenFileStorage( const char* filename, CvMemStorage* memstorage, + int flags, const char* encoding CV_DEFAULT(NULL) ); + +/** @brief Releases file storage. + +The function closes the file associated with the storage and releases all the temporary structures. +It must be called after all I/O operations with the storage are finished. +@param fs Double pointer to the released file storage + */ +CVAPI(void) cvReleaseFileStorage( CvFileStorage** fs ); + +/** returns attribute value or 0 (NULL) if there is no such attribute */ +CVAPI(const char*) cvAttrValue( const CvAttrList* attr, const char* attr_name ); + +/** @brief Starts writing a new structure. + +The function starts writing a compound structure (collection) that can be a sequence or a map. After +all the structure fields, which can be scalars or structures, are written, cvEndWriteStruct should +be called. The function can be used to group some objects or to implement the write function for a +some user object (see CvTypeInfo). +@param fs File storage +@param name Name of the written structure. The structure can be accessed by this name when the +storage is read. +@param struct_flags A combination one of the following values: +- **CV_NODE_SEQ** the written structure is a sequence (see discussion of CvFileStorage ), + that is, its elements do not have a name. +- **CV_NODE_MAP** the written structure is a map (see discussion of CvFileStorage ), that + is, all its elements have names. +One and only one of the two above flags must be specified +- **CV_NODE_FLOW** the optional flag that makes sense only for YAML streams. It means that + the structure is written as a flow (not as a block), which is more compact. It is + recommended to use this flag for structures or arrays whose elements are all scalars. +@param type_name Optional parameter - the object type name. In + case of XML it is written as a type_id attribute of the structure opening tag. In the case of + YAML it is written after a colon following the structure name (see the example in + CvFileStorage description). In case of JSON it is written as a name/value pair. + Mainly it is used with user objects. When the storage is read, the + encoded type name is used to determine the object type (see CvTypeInfo and cvFindType ). +@param attributes This parameter is not used in the current implementation + */ +CVAPI(void) cvStartWriteStruct( CvFileStorage* fs, const char* name, + int struct_flags, const char* type_name CV_DEFAULT(NULL), + CvAttrList attributes CV_DEFAULT(cvAttrList())); + +/** @brief Finishes writing to a file node collection. +@param fs File storage +@sa cvStartWriteStruct. + */ +CVAPI(void) cvEndWriteStruct( CvFileStorage* fs ); + +/** @brief Writes an integer value. + +The function writes a single integer value (with or without a name) to the file storage. +@param fs File storage +@param name Name of the written value. Should be NULL if and only if the parent structure is a +sequence. +@param value The written value + */ +CVAPI(void) cvWriteInt( CvFileStorage* fs, const char* name, int value ); + +/** @brief Writes a floating-point value. + +The function writes a single floating-point value (with or without a name) to file storage. Special +values are encoded as follows: NaN (Not A Number) as .NaN, infinity as +.Inf or -.Inf. + +The following example shows how to use the low-level writing functions to store custom structures, +such as termination criteria, without registering a new type. : +@code + void write_termcriteria( CvFileStorage* fs, const char* struct_name, + CvTermCriteria* termcrit ) + { + cvStartWriteStruct( fs, struct_name, CV_NODE_MAP, NULL, cvAttrList(0,0)); + cvWriteComment( fs, "termination criteria", 1 ); // just a description + if( termcrit->type & CV_TERMCRIT_ITER ) + cvWriteInteger( fs, "max_iterations", termcrit->max_iter ); + if( termcrit->type & CV_TERMCRIT_EPS ) + cvWriteReal( fs, "accuracy", termcrit->epsilon ); + cvEndWriteStruct( fs ); + } +@endcode +@param fs File storage +@param name Name of the written value. Should be NULL if and only if the parent structure is a +sequence. +@param value The written value +*/ +CVAPI(void) cvWriteReal( CvFileStorage* fs, const char* name, double value ); + +/** @brief Writes a text string. + +The function writes a text string to file storage. +@param fs File storage +@param name Name of the written string . Should be NULL if and only if the parent structure is a +sequence. +@param str The written text string +@param quote If non-zero, the written string is put in quotes, regardless of whether they are +required. Otherwise, if the flag is zero, quotes are used only when they are required (e.g. when +the string starts with a digit or contains spaces). + */ +CVAPI(void) cvWriteString( CvFileStorage* fs, const char* name, + const char* str, int quote CV_DEFAULT(0) ); + +/** @brief Writes a comment. + +The function writes a comment into file storage. The comments are skipped when the storage is read. +@param fs File storage +@param comment The written comment, single-line or multi-line +@param eol_comment If non-zero, the function tries to put the comment at the end of current line. +If the flag is zero, if the comment is multi-line, or if it does not fit at the end of the current +line, the comment starts a new line. + */ +CVAPI(void) cvWriteComment( CvFileStorage* fs, const char* comment, + int eol_comment ); + +/** @brief Writes an object to file storage. + +The function writes an object to file storage. First, the appropriate type info is found using +cvTypeOf. Then, the write method associated with the type info is called. + +Attributes are used to customize the writing procedure. The standard types support the following +attributes (all the dt attributes have the same format as in cvWriteRawData): + +-# CvSeq + - **header_dt** description of user fields of the sequence header that follow CvSeq, or + CvChain (if the sequence is a Freeman chain) or CvContour (if the sequence is a contour or + point sequence) + - **dt** description of the sequence elements. + - **recursive** if the attribute is present and is not equal to "0" or "false", the whole + tree of sequences (contours) is stored. +-# CvGraph + - **header_dt** description of user fields of the graph header that follows CvGraph; + - **vertex_dt** description of user fields of graph vertices + - **edge_dt** description of user fields of graph edges (note that the edge weight is + always written, so there is no need to specify it explicitly) + +Below is the code that creates the YAML file shown in the CvFileStorage description: +@code + #include "cxcore.h" + + int main( int argc, char** argv ) + { + CvMat* mat = cvCreateMat( 3, 3, CV_32F ); + CvFileStorage* fs = cvOpenFileStorage( "example.yml", 0, CV_STORAGE_WRITE ); + + cvSetIdentity( mat ); + cvWrite( fs, "A", mat, cvAttrList(0,0) ); + + cvReleaseFileStorage( &fs ); + cvReleaseMat( &mat ); + return 0; + } +@endcode +@param fs File storage +@param name Name of the written object. Should be NULL if and only if the parent structure is a +sequence. +@param ptr Pointer to the object +@param attributes The attributes of the object. They are specific for each particular type (see +the discussion below). + */ +CVAPI(void) cvWrite( CvFileStorage* fs, const char* name, const void* ptr, + CvAttrList attributes CV_DEFAULT(cvAttrList())); + +/** @brief Starts the next stream. + +The function finishes the currently written stream and starts the next stream. In the case of XML +the file with multiple streams looks like this: +@code{.xml} + + + + + + + ... +@endcode +The YAML file will look like this: +@code{.yaml} + %YAML 1.0 + # stream #1 data + ... + --- + # stream #2 data +@endcode +This is useful for concatenating files or for resuming the writing process. +@param fs File storage + */ +CVAPI(void) cvStartNextStream( CvFileStorage* fs ); + +/** @brief Writes multiple numbers. + +The function writes an array, whose elements consist of single or multiple numbers. The function +call can be replaced with a loop containing a few cvWriteInt and cvWriteReal calls, but a single +call is more efficient. Note that because none of the elements have a name, they should be written +to a sequence rather than a map. +@param fs File storage +@param src Pointer to the written array +@param len Number of the array elements to write +@param dt Specification of each array element, see @ref format_spec "format specification" + */ +CVAPI(void) cvWriteRawData( CvFileStorage* fs, const void* src, + int len, const char* dt ); + +/** @brief Writes multiple numbers in Base64. + +If either CV_STORAGE_WRITE_BASE64 or cv::FileStorage::WRITE_BASE64 is used, +this function will be the same as cvWriteRawData. If neither, the main +difference is that it outputs a sequence in Base64 encoding rather than +in plain text. + +This function can only be used to write a sequence with a type "binary". + +@param fs File storage +@param src Pointer to the written array +@param len Number of the array elements to write +@param dt Specification of each array element, see @ref format_spec "format specification" +*/ +CVAPI(void) cvWriteRawDataBase64( CvFileStorage* fs, const void* src, + int len, const char* dt ); + +/** @brief Returns a unique pointer for a given name. + +The function returns a unique pointer for each particular file node name. This pointer can be then +passed to the cvGetFileNode function that is faster than cvGetFileNodeByName because it compares +text strings by comparing pointers rather than the strings' content. + +Consider the following example where an array of points is encoded as a sequence of 2-entry maps: +@code + points: + - { x: 10, y: 10 } + - { x: 20, y: 20 } + - { x: 30, y: 30 } + # ... +@endcode +Then, it is possible to get hashed "x" and "y" pointers to speed up decoding of the points. : +@code + #include "cxcore.h" + + int main( int argc, char** argv ) + { + CvFileStorage* fs = cvOpenFileStorage( "points.yml", 0, CV_STORAGE_READ ); + CvStringHashNode* x_key = cvGetHashedNode( fs, "x", -1, 1 ); + CvStringHashNode* y_key = cvGetHashedNode( fs, "y", -1, 1 ); + CvFileNode* points = cvGetFileNodeByName( fs, 0, "points" ); + + if( CV_NODE_IS_SEQ(points->tag) ) + { + CvSeq* seq = points->data.seq; + int i, total = seq->total; + CvSeqReader reader; + cvStartReadSeq( seq, &reader, 0 ); + for( i = 0; i < total; i++ ) + { + CvFileNode* pt = (CvFileNode*)reader.ptr; + #if 1 // faster variant + CvFileNode* xnode = cvGetFileNode( fs, pt, x_key, 0 ); + CvFileNode* ynode = cvGetFileNode( fs, pt, y_key, 0 ); + assert( xnode && CV_NODE_IS_INT(xnode->tag) && + ynode && CV_NODE_IS_INT(ynode->tag)); + int x = xnode->data.i; // or x = cvReadInt( xnode, 0 ); + int y = ynode->data.i; // or y = cvReadInt( ynode, 0 ); + #elif 1 // slower variant; does not use x_key & y_key + CvFileNode* xnode = cvGetFileNodeByName( fs, pt, "x" ); + CvFileNode* ynode = cvGetFileNodeByName( fs, pt, "y" ); + assert( xnode && CV_NODE_IS_INT(xnode->tag) && + ynode && CV_NODE_IS_INT(ynode->tag)); + int x = xnode->data.i; // or x = cvReadInt( xnode, 0 ); + int y = ynode->data.i; // or y = cvReadInt( ynode, 0 ); + #else // the slowest yet the easiest to use variant + int x = cvReadIntByName( fs, pt, "x", 0 ); + int y = cvReadIntByName( fs, pt, "y", 0 ); + #endif + CV_NEXT_SEQ_ELEM( seq->elem_size, reader ); + printf(" + } + } + cvReleaseFileStorage( &fs ); + return 0; + } +@endcode +Please note that whatever method of accessing a map you are using, it is still much slower than +using plain sequences; for example, in the above example, it is more efficient to encode the points +as pairs of integers in a single numeric sequence. +@param fs File storage +@param name Literal node name +@param len Length of the name (if it is known apriori), or -1 if it needs to be calculated +@param create_missing Flag that specifies, whether an absent key should be added into the hash table +*/ +CVAPI(CvStringHashNode*) cvGetHashedKey( CvFileStorage* fs, const char* name, + int len CV_DEFAULT(-1), + int create_missing CV_DEFAULT(0)); + +/** @brief Retrieves one of the top-level nodes of the file storage. + +The function returns one of the top-level file nodes. The top-level nodes do not have a name, they +correspond to the streams that are stored one after another in the file storage. If the index is out +of range, the function returns a NULL pointer, so all the top-level nodes can be iterated by +subsequent calls to the function with stream_index=0,1,..., until the NULL pointer is returned. +This function can be used as a base for recursive traversal of the file storage. +@param fs File storage +@param stream_index Zero-based index of the stream. See cvStartNextStream . In most cases, +there is only one stream in the file; however, there can be several. + */ +CVAPI(CvFileNode*) cvGetRootFileNode( const CvFileStorage* fs, + int stream_index CV_DEFAULT(0) ); + +/** @brief Finds a node in a map or file storage. + +The function finds a file node. It is a faster version of cvGetFileNodeByName (see +cvGetHashedKey discussion). Also, the function can insert a new node, if it is not in the map yet. +@param fs File storage +@param map The parent map. If it is NULL, the function searches a top-level node. If both map and +key are NULLs, the function returns the root file node - a map that contains top-level nodes. +@param key Unique pointer to the node name, retrieved with cvGetHashedKey +@param create_missing Flag that specifies whether an absent node should be added to the map + */ +CVAPI(CvFileNode*) cvGetFileNode( CvFileStorage* fs, CvFileNode* map, + const CvStringHashNode* key, + int create_missing CV_DEFAULT(0) ); + +/** @brief Finds a node in a map or file storage. + +The function finds a file node by name. The node is searched either in map or, if the pointer is +NULL, among the top-level file storage nodes. Using this function for maps and cvGetSeqElem (or +sequence reader) for sequences, it is possible to navigate through the file storage. To speed up +multiple queries for a certain key (e.g., in the case of an array of structures) one may use a +combination of cvGetHashedKey and cvGetFileNode. +@param fs File storage +@param map The parent map. If it is NULL, the function searches in all the top-level nodes +(streams), starting with the first one. +@param name The file node name + */ +CVAPI(CvFileNode*) cvGetFileNodeByName( const CvFileStorage* fs, + const CvFileNode* map, + const char* name ); + +/** @brief Retrieves an integer value from a file node. + +The function returns an integer that is represented by the file node. If the file node is NULL, the +default_value is returned (thus, it is convenient to call the function right after cvGetFileNode +without checking for a NULL pointer). If the file node has type CV_NODE_INT, then node-\>data.i is +returned. If the file node has type CV_NODE_REAL, then node-\>data.f is converted to an integer +and returned. Otherwise the error is reported. +@param node File node +@param default_value The value that is returned if node is NULL + */ +CV_INLINE int cvReadInt( const CvFileNode* node, int default_value CV_DEFAULT(0) ) +{ + return !node ? default_value : + CV_NODE_IS_INT(node->tag) ? node->data.i : + CV_NODE_IS_REAL(node->tag) ? cvRound(node->data.f) : 0x7fffffff; +} + +/** @brief Finds a file node and returns its value. + +The function is a simple superposition of cvGetFileNodeByName and cvReadInt. +@param fs File storage +@param map The parent map. If it is NULL, the function searches a top-level node. +@param name The node name +@param default_value The value that is returned if the file node is not found + */ +CV_INLINE int cvReadIntByName( const CvFileStorage* fs, const CvFileNode* map, + const char* name, int default_value CV_DEFAULT(0) ) +{ + return cvReadInt( cvGetFileNodeByName( fs, map, name ), default_value ); +} + +/** @brief Retrieves a floating-point value from a file node. + +The function returns a floating-point value that is represented by the file node. If the file node +is NULL, the default_value is returned (thus, it is convenient to call the function right after +cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_REAL , +then node-\>data.f is returned. If the file node has type CV_NODE_INT , then node-:math:\>data.f +is converted to floating-point and returned. Otherwise the result is not determined. +@param node File node +@param default_value The value that is returned if node is NULL + */ +CV_INLINE double cvReadReal( const CvFileNode* node, double default_value CV_DEFAULT(0.) ) +{ + return !node ? default_value : + CV_NODE_IS_INT(node->tag) ? (double)node->data.i : + CV_NODE_IS_REAL(node->tag) ? node->data.f : 1e300; +} + +/** @brief Finds a file node and returns its value. + +The function is a simple superposition of cvGetFileNodeByName and cvReadReal . +@param fs File storage +@param map The parent map. If it is NULL, the function searches a top-level node. +@param name The node name +@param default_value The value that is returned if the file node is not found + */ +CV_INLINE double cvReadRealByName( const CvFileStorage* fs, const CvFileNode* map, + const char* name, double default_value CV_DEFAULT(0.) ) +{ + return cvReadReal( cvGetFileNodeByName( fs, map, name ), default_value ); +} + +/** @brief Retrieves a text string from a file node. + +The function returns a text string that is represented by the file node. If the file node is NULL, +the default_value is returned (thus, it is convenient to call the function right after +cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_STR , then +node-:math:\>data.str.ptr is returned. Otherwise the result is not determined. +@param node File node +@param default_value The value that is returned if node is NULL + */ +CV_INLINE const char* cvReadString( const CvFileNode* node, + const char* default_value CV_DEFAULT(NULL) ) +{ + return !node ? default_value : CV_NODE_IS_STRING(node->tag) ? node->data.str.ptr : 0; +} + +/** @brief Finds a file node by its name and returns its value. + +The function is a simple superposition of cvGetFileNodeByName and cvReadString . +@param fs File storage +@param map The parent map. If it is NULL, the function searches a top-level node. +@param name The node name +@param default_value The value that is returned if the file node is not found + */ +CV_INLINE const char* cvReadStringByName( const CvFileStorage* fs, const CvFileNode* map, + const char* name, const char* default_value CV_DEFAULT(NULL) ) +{ + return cvReadString( cvGetFileNodeByName( fs, map, name ), default_value ); +} + + +/** @brief Decodes an object and returns a pointer to it. + +The function decodes a user object (creates an object in a native representation from the file +storage subtree) and returns it. The object to be decoded must be an instance of a registered type +that supports the read method (see CvTypeInfo). The type of the object is determined by the type +name that is encoded in the file. If the object is a dynamic structure, it is created either in +memory storage and passed to cvOpenFileStorage or, if a NULL pointer was passed, in temporary +memory storage, which is released when cvReleaseFileStorage is called. Otherwise, if the object is +not a dynamic structure, it is created in a heap and should be released with a specialized function +or by using the generic cvRelease. +@param fs File storage +@param node The root object node +@param attributes Unused parameter + */ +CVAPI(void*) cvRead( CvFileStorage* fs, CvFileNode* node, + CvAttrList* attributes CV_DEFAULT(NULL)); + +/** @brief Finds an object by name and decodes it. + +The function is a simple superposition of cvGetFileNodeByName and cvRead. +@param fs File storage +@param map The parent map. If it is NULL, the function searches a top-level node. +@param name The node name +@param attributes Unused parameter + */ +CV_INLINE void* cvReadByName( CvFileStorage* fs, const CvFileNode* map, + const char* name, CvAttrList* attributes CV_DEFAULT(NULL) ) +{ + return cvRead( fs, cvGetFileNodeByName( fs, map, name ), attributes ); +} + + +/** @brief Initializes the file node sequence reader. + +The function initializes the sequence reader to read data from a file node. The initialized reader +can be then passed to cvReadRawDataSlice. +@param fs File storage +@param src The file node (a sequence) to read numbers from +@param reader Pointer to the sequence reader + */ +CVAPI(void) cvStartReadRawData( const CvFileStorage* fs, const CvFileNode* src, + CvSeqReader* reader ); + +/** @brief Initializes file node sequence reader. + +The function reads one or more elements from the file node, representing a sequence, to a +user-specified array. The total number of read sequence elements is a product of total and the +number of components in each array element. For example, if dt=2if, the function will read total\*3 +sequence elements. As with any sequence, some parts of the file node sequence can be skipped or read +repeatedly by repositioning the reader using cvSetSeqReaderPos. +@param fs File storage +@param reader The sequence reader. Initialize it with cvStartReadRawData . +@param count The number of elements to read +@param dst Pointer to the destination array +@param dt Specification of each array element. It has the same format as in cvWriteRawData . + */ +CVAPI(void) cvReadRawDataSlice( const CvFileStorage* fs, CvSeqReader* reader, + int count, void* dst, const char* dt ); + +/** @brief Reads multiple numbers. + +The function reads elements from a file node that represents a sequence of scalars. +@param fs File storage +@param src The file node (a sequence) to read numbers from +@param dst Pointer to the destination array +@param dt Specification of each array element. It has the same format as in cvWriteRawData . + */ +CVAPI(void) cvReadRawData( const CvFileStorage* fs, const CvFileNode* src, + void* dst, const char* dt ); + +/** @brief Writes a file node to another file storage. + +The function writes a copy of a file node to file storage. Possible applications of the function are +merging several file storages into one and conversion between XML, YAML and JSON formats. +@param fs Destination file storage +@param new_node_name New name of the file node in the destination file storage. To keep the +existing name, use cvcvGetFileNodeName +@param node The written node +@param embed If the written node is a collection and this parameter is not zero, no extra level of +hierarchy is created. Instead, all the elements of node are written into the currently written +structure. Of course, map elements can only be embedded into another map, and sequence elements +can only be embedded into another sequence. + */ +CVAPI(void) cvWriteFileNode( CvFileStorage* fs, const char* new_node_name, + const CvFileNode* node, int embed ); + +/** @brief Returns the name of a file node. + +The function returns the name of a file node or NULL, if the file node does not have a name or if +node is NULL. +@param node File node + */ +CVAPI(const char*) cvGetFileNodeName( const CvFileNode* node ); + +/*********************************** Adding own types ***********************************/ + +/** @brief Registers a new type. + +The function registers a new type, which is described by info . The function creates a copy of the +structure, so the user should delete it after calling the function. +@param info Type info structure + */ +CVAPI(void) cvRegisterType( const CvTypeInfo* info ); + +/** @brief Unregisters the type. + +The function unregisters a type with a specified name. If the name is unknown, it is possible to +locate the type info by an instance of the type using cvTypeOf or by iterating the type list, +starting from cvFirstType, and then calling cvUnregisterType(info-\>typeName). +@param type_name Name of an unregistered type + */ +CVAPI(void) cvUnregisterType( const char* type_name ); + +/** @brief Returns the beginning of a type list. + +The function returns the first type in the list of registered types. Navigation through the list can +be done via the prev and next fields of the CvTypeInfo structure. + */ +CVAPI(CvTypeInfo*) cvFirstType(void); + +/** @brief Finds a type by its name. + +The function finds a registered type by its name. It returns NULL if there is no type with the +specified name. +@param type_name Type name + */ +CVAPI(CvTypeInfo*) cvFindType( const char* type_name ); + +/** @brief Returns the type of an object. + +The function finds the type of a given object. It iterates through the list of registered types and +calls the is_instance function/method for every type info structure with that object until one of +them returns non-zero or until the whole list has been traversed. In the latter case, the function +returns NULL. +@param struct_ptr The object pointer + */ +CVAPI(CvTypeInfo*) cvTypeOf( const void* struct_ptr ); + +/** @brief Releases an object. + +The function finds the type of a given object and calls release with the double pointer. +@param struct_ptr Double pointer to the object + */ +CVAPI(void) cvRelease( void** struct_ptr ); + +/** @brief Makes a clone of an object. + +The function finds the type of a given object and calls clone with the passed object. Of course, if +you know the object type, for example, struct_ptr is CvMat\*, it is faster to call the specific +function, like cvCloneMat. +@param struct_ptr The object to clone + */ +CVAPI(void*) cvClone( const void* struct_ptr ); + +/** @brief Saves an object to a file. + +The function saves an object to a file. It provides a simple interface to cvWrite . +@param filename File name +@param struct_ptr Object to save +@param name Optional object name. If it is NULL, the name will be formed from filename . +@param comment Optional comment to put in the beginning of the file +@param attributes Optional attributes passed to cvWrite + */ +CVAPI(void) cvSave( const char* filename, const void* struct_ptr, + const char* name CV_DEFAULT(NULL), + const char* comment CV_DEFAULT(NULL), + CvAttrList attributes CV_DEFAULT(cvAttrList())); + +/** @brief Loads an object from a file. + +The function loads an object from a file. It basically reads the specified file, find the first +top-level node and calls cvRead for that node. If the file node does not have type information or +the type information can not be found by the type name, the function returns NULL. After the object +is loaded, the file storage is closed and all the temporary buffers are deleted. Thus, to load a +dynamic structure, such as a sequence, contour, or graph, one should pass a valid memory storage +destination to the function. +@param filename File name +@param memstorage Memory storage for dynamic structures, such as CvSeq or CvGraph . It is not used +for matrices or images. +@param name Optional object name. If it is NULL, the first top-level object in the storage will be +loaded. +@param real_name Optional output parameter that will contain the name of the loaded object +(useful if name=NULL ) + */ +CVAPI(void*) cvLoad( const char* filename, + CvMemStorage* memstorage CV_DEFAULT(NULL), + const char* name CV_DEFAULT(NULL), + const char** real_name CV_DEFAULT(NULL) ); + +/*********************************** Measuring Execution Time ***************************/ + +/** helper functions for RNG initialization and accurate time measurement: + uses internal clock counter on x86 */ +CVAPI(int64) cvGetTickCount( void ); +CVAPI(double) cvGetTickFrequency( void ); + +/*********************************** CPU capabilities ***********************************/ + +CVAPI(int) cvCheckHardwareSupport(int feature); + +/*********************************** Multi-Threading ************************************/ + +/** retrieve/set the number of threads used in OpenMP implementations */ +CVAPI(int) cvGetNumThreads( void ); +CVAPI(void) cvSetNumThreads( int threads CV_DEFAULT(0) ); +/** get index of the thread being executed */ +CVAPI(int) cvGetThreadNum( void ); + + +/********************************** Error Handling **************************************/ + +/** Get current OpenCV error status */ +CVAPI(int) cvGetErrStatus( void ); + +/** Sets error status silently */ +CVAPI(void) cvSetErrStatus( int status ); + +#define CV_ErrModeLeaf 0 /* Print error and exit program */ +#define CV_ErrModeParent 1 /* Print error and continue */ +#define CV_ErrModeSilent 2 /* Don't print and continue */ + +/** Retrieves current error processing mode */ +CVAPI(int) cvGetErrMode( void ); + +/** Sets error processing mode, returns previously used mode */ +CVAPI(int) cvSetErrMode( int mode ); + +/** Sets error status and performs some additional actions (displaying message box, + writing message to stderr, terminating application etc.) + depending on the current error mode */ +CVAPI(void) cvError( int status, const char* func_name, + const char* err_msg, const char* file_name, int line ); + +/** Retrieves textual description of the error given its code */ +CVAPI(const char*) cvErrorStr( int status ); + +/** Retrieves detailed information about the last error occurred */ +CVAPI(int) cvGetErrInfo( const char** errcode_desc, const char** description, + const char** filename, int* line ); + +/** Maps IPP error codes to the counterparts from OpenCV */ +CVAPI(int) cvErrorFromIppStatus( int ipp_status ); + +typedef int (CV_CDECL *CvErrorCallback)( int status, const char* func_name, + const char* err_msg, const char* file_name, int line, void* userdata ); + +/** Assigns a new error-handling function */ +CVAPI(CvErrorCallback) cvRedirectError( CvErrorCallback error_handler, + void* userdata CV_DEFAULT(NULL), + void** prev_userdata CV_DEFAULT(NULL) ); + +/** Output nothing */ +CVAPI(int) cvNulDevReport( int status, const char* func_name, const char* err_msg, + const char* file_name, int line, void* userdata ); + +/** Output to console(fprintf(stderr,...)) */ +CVAPI(int) cvStdErrReport( int status, const char* func_name, const char* err_msg, + const char* file_name, int line, void* userdata ); + +/** Output to MessageBox(WIN32) */ +CVAPI(int) cvGuiBoxReport( int status, const char* func_name, const char* err_msg, + const char* file_name, int line, void* userdata ); + +#define OPENCV_ERROR(status,func,context) \ +cvError((status),(func),(context),__FILE__,__LINE__) + +#define OPENCV_ASSERT(expr,func,context) \ +{if (! (expr)) \ +{OPENCV_ERROR(CV_StsInternal,(func),(context));}} + +#define OPENCV_CALL( Func ) \ +{ \ +Func; \ +} + + +/** CV_FUNCNAME macro defines icvFuncName constant which is used by CV_ERROR macro */ +#ifdef CV_NO_FUNC_NAMES +#define CV_FUNCNAME( Name ) +#define cvFuncName "" +#else +#define CV_FUNCNAME( Name ) \ +static char cvFuncName[] = Name +#endif + + +/** + CV_ERROR macro unconditionally raises error with passed code and message. + After raising error, control will be transferred to the exit label. + */ +#define CV_ERROR( Code, Msg ) \ +{ \ + cvError( (Code), cvFuncName, Msg, __FILE__, __LINE__ ); \ + __CV_EXIT__; \ +} + +/** + CV_CHECK macro checks error status after CV (or IPL) + function call. If error detected, control will be transferred to the exit + label. + */ +#define CV_CHECK() \ +{ \ + if( cvGetErrStatus() < 0 ) \ + CV_ERROR( CV_StsBackTrace, "Inner function failed." ); \ +} + + +/** + CV_CALL macro calls CV (or IPL) function, checks error status and + signals a error if the function failed. Useful in "parent node" + error processing mode + */ +#define CV_CALL( Func ) \ +{ \ + Func; \ + CV_CHECK(); \ +} + + +/** Runtime assertion macro */ +#define CV_ASSERT( Condition ) \ +{ \ + if( !(Condition) ) \ + CV_ERROR( CV_StsInternal, "Assertion: " #Condition " failed" ); \ +} + +#define __CV_BEGIN__ { +#define __CV_END__ goto exit; exit: ; } +#define __CV_EXIT__ goto exit + +/** @} core_c */ + +#ifdef __cplusplus +} // extern "C" +#endif + +#ifdef __cplusplus + +//! @addtogroup core_c_glue +//! @{ + +//! class for automatic module/RTTI data registration/unregistration +struct CV_EXPORTS CvType +{ + CvType( const char* type_name, + CvIsInstanceFunc is_instance, CvReleaseFunc release=0, + CvReadFunc read=0, CvWriteFunc write=0, CvCloneFunc clone=0 ); + ~CvType(); + CvTypeInfo* info; + + static CvTypeInfo* first; + static CvTypeInfo* last; +}; + +//! @} + +#include "opencv2/core/utility.hpp" + +namespace cv +{ + +//! @addtogroup core_c_glue +//! @{ + +/////////////////////////////////////////// glue /////////////////////////////////////////// + +//! converts array (CvMat or IplImage) to cv::Mat +CV_EXPORTS Mat cvarrToMat(const CvArr* arr, bool copyData=false, + bool allowND=true, int coiMode=0, + AutoBuffer* buf=0); + +static inline Mat cvarrToMatND(const CvArr* arr, bool copyData=false, int coiMode=0) +{ + return cvarrToMat(arr, copyData, true, coiMode); +} + + +//! extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it. +CV_EXPORTS void extractImageCOI(const CvArr* arr, OutputArray coiimg, int coi=-1); +//! inserts single-channel cv::Mat into a multi-channel CvMat or IplImage +CV_EXPORTS void insertImageCOI(InputArray coiimg, CvArr* arr, int coi=-1); + + + +////// specialized implementations of DefaultDeleter::operator() for classic OpenCV types ////// + +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvMat* obj) const; +template<> CV_EXPORTS void DefaultDeleter::operator ()(IplImage* obj) const; +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvMatND* obj) const; +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvSparseMat* obj) const; +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvMemStorage* obj) const; + +////////////// convenient wrappers for operating old-style dynamic structures ////////////// + +template class SeqIterator; + +typedef Ptr MemStorage; + +/*! + Template Sequence Class derived from CvSeq + + The class provides more convenient access to sequence elements, + STL-style operations and iterators. + + \note The class is targeted for simple data types, + i.e. no constructors or destructors + are called for the sequence elements. +*/ +template class Seq +{ +public: + typedef SeqIterator<_Tp> iterator; + typedef SeqIterator<_Tp> const_iterator; + + //! the default constructor + Seq(); + //! the constructor for wrapping CvSeq structure. The real element type in CvSeq should match _Tp. + Seq(const CvSeq* seq); + //! creates the empty sequence that resides in the specified storage + Seq(MemStorage& storage, int headerSize = sizeof(CvSeq)); + //! returns read-write reference to the specified element + _Tp& operator [](int idx); + //! returns read-only reference to the specified element + const _Tp& operator[](int idx) const; + //! returns iterator pointing to the beginning of the sequence + SeqIterator<_Tp> begin() const; + //! returns iterator pointing to the element following the last sequence element + SeqIterator<_Tp> end() const; + //! returns the number of elements in the sequence + size_t size() const; + //! returns the type of sequence elements (CV_8UC1 ... CV_64FC(CV_CN_MAX) ...) + int type() const; + //! returns the depth of sequence elements (CV_8U ... CV_64F) + int depth() const; + //! returns the number of channels in each sequence element + int channels() const; + //! returns the size of each sequence element + size_t elemSize() const; + //! returns index of the specified sequence element + size_t index(const _Tp& elem) const; + //! appends the specified element to the end of the sequence + void push_back(const _Tp& elem); + //! appends the specified element to the front of the sequence + void push_front(const _Tp& elem); + //! appends zero or more elements to the end of the sequence + void push_back(const _Tp* elems, size_t count); + //! appends zero or more elements to the front of the sequence + void push_front(const _Tp* elems, size_t count); + //! inserts the specified element to the specified position + void insert(int idx, const _Tp& elem); + //! inserts zero or more elements to the specified position + void insert(int idx, const _Tp* elems, size_t count); + //! removes element at the specified position + void remove(int idx); + //! removes the specified subsequence + void remove(const Range& r); + + //! returns reference to the first sequence element + _Tp& front(); + //! returns read-only reference to the first sequence element + const _Tp& front() const; + //! returns reference to the last sequence element + _Tp& back(); + //! returns read-only reference to the last sequence element + const _Tp& back() const; + //! returns true iff the sequence contains no elements + bool empty() const; + + //! removes all the elements from the sequence + void clear(); + //! removes the first element from the sequence + void pop_front(); + //! removes the last element from the sequence + void pop_back(); + //! removes zero or more elements from the beginning of the sequence + void pop_front(_Tp* elems, size_t count); + //! removes zero or more elements from the end of the sequence + void pop_back(_Tp* elems, size_t count); + + //! copies the whole sequence or the sequence slice to the specified vector + void copyTo(std::vector<_Tp>& vec, const Range& range=Range::all()) const; + //! returns the vector containing all the sequence elements + operator std::vector<_Tp>() const; + + CvSeq* seq; +}; + + +/*! + STL-style Sequence Iterator inherited from the CvSeqReader structure +*/ +template class SeqIterator : public CvSeqReader +{ +public: + //! the default constructor + SeqIterator(); + //! the constructor setting the iterator to the beginning or to the end of the sequence + SeqIterator(const Seq<_Tp>& seq, bool seekEnd=false); + //! positions the iterator within the sequence + void seek(size_t pos); + //! reports the current iterator position + size_t tell() const; + //! returns reference to the current sequence element + _Tp& operator *(); + //! returns read-only reference to the current sequence element + const _Tp& operator *() const; + //! moves iterator to the next sequence element + SeqIterator& operator ++(); + //! moves iterator to the next sequence element + SeqIterator operator ++(int) const; + //! moves iterator to the previous sequence element + SeqIterator& operator --(); + //! moves iterator to the previous sequence element + SeqIterator operator --(int) const; + + //! moves iterator forward by the specified offset (possibly negative) + SeqIterator& operator +=(int); + //! moves iterator backward by the specified offset (possibly negative) + SeqIterator& operator -=(int); + + // this is index of the current element module seq->total*2 + // (to distinguish between 0 and seq->total) + int index; +}; + + + +// bridge C++ => C Seq API +CV_EXPORTS schar* seqPush( CvSeq* seq, const void* element=0); +CV_EXPORTS schar* seqPushFront( CvSeq* seq, const void* element=0); +CV_EXPORTS void seqPop( CvSeq* seq, void* element=0); +CV_EXPORTS void seqPopFront( CvSeq* seq, void* element=0); +CV_EXPORTS void seqPopMulti( CvSeq* seq, void* elements, + int count, int in_front=0 ); +CV_EXPORTS void seqRemove( CvSeq* seq, int index ); +CV_EXPORTS void clearSeq( CvSeq* seq ); +CV_EXPORTS schar* getSeqElem( const CvSeq* seq, int index ); +CV_EXPORTS void seqRemoveSlice( CvSeq* seq, CvSlice slice ); +CV_EXPORTS void seqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr ); + +template inline Seq<_Tp>::Seq() : seq(0) {} +template inline Seq<_Tp>::Seq( const CvSeq* _seq ) : seq((CvSeq*)_seq) +{ + CV_Assert(!_seq || _seq->elem_size == sizeof(_Tp)); +} + +template inline Seq<_Tp>::Seq( MemStorage& storage, + int headerSize ) +{ + CV_Assert(headerSize >= (int)sizeof(CvSeq)); + seq = cvCreateSeq(DataType<_Tp>::type, headerSize, sizeof(_Tp), storage); +} + +template inline _Tp& Seq<_Tp>::operator [](int idx) +{ return *(_Tp*)getSeqElem(seq, idx); } + +template inline const _Tp& Seq<_Tp>::operator [](int idx) const +{ return *(_Tp*)getSeqElem(seq, idx); } + +template inline SeqIterator<_Tp> Seq<_Tp>::begin() const +{ return SeqIterator<_Tp>(*this); } + +template inline SeqIterator<_Tp> Seq<_Tp>::end() const +{ return SeqIterator<_Tp>(*this, true); } + +template inline size_t Seq<_Tp>::size() const +{ return seq ? seq->total : 0; } + +template inline int Seq<_Tp>::type() const +{ return seq ? CV_MAT_TYPE(seq->flags) : 0; } + +template inline int Seq<_Tp>::depth() const +{ return seq ? CV_MAT_DEPTH(seq->flags) : 0; } + +template inline int Seq<_Tp>::channels() const +{ return seq ? CV_MAT_CN(seq->flags) : 0; } + +template inline size_t Seq<_Tp>::elemSize() const +{ return seq ? seq->elem_size : 0; } + +template inline size_t Seq<_Tp>::index(const _Tp& elem) const +{ return cvSeqElemIdx(seq, &elem); } + +template inline void Seq<_Tp>::push_back(const _Tp& elem) +{ cvSeqPush(seq, &elem); } + +template inline void Seq<_Tp>::push_front(const _Tp& elem) +{ cvSeqPushFront(seq, &elem); } + +template inline void Seq<_Tp>::push_back(const _Tp* elem, size_t count) +{ cvSeqPushMulti(seq, elem, (int)count, 0); } + +template inline void Seq<_Tp>::push_front(const _Tp* elem, size_t count) +{ cvSeqPushMulti(seq, elem, (int)count, 1); } + +template inline _Tp& Seq<_Tp>::back() +{ return *(_Tp*)getSeqElem(seq, -1); } + +template inline const _Tp& Seq<_Tp>::back() const +{ return *(const _Tp*)getSeqElem(seq, -1); } + +template inline _Tp& Seq<_Tp>::front() +{ return *(_Tp*)getSeqElem(seq, 0); } + +template inline const _Tp& Seq<_Tp>::front() const +{ return *(const _Tp*)getSeqElem(seq, 0); } + +template inline bool Seq<_Tp>::empty() const +{ return !seq || seq->total == 0; } + +template inline void Seq<_Tp>::clear() +{ if(seq) clearSeq(seq); } + +template inline void Seq<_Tp>::pop_back() +{ seqPop(seq); } + +template inline void Seq<_Tp>::pop_front() +{ seqPopFront(seq); } + +template inline void Seq<_Tp>::pop_back(_Tp* elem, size_t count) +{ seqPopMulti(seq, elem, (int)count, 0); } + +template inline void Seq<_Tp>::pop_front(_Tp* elem, size_t count) +{ seqPopMulti(seq, elem, (int)count, 1); } + +template inline void Seq<_Tp>::insert(int idx, const _Tp& elem) +{ seqInsert(seq, idx, &elem); } + +template inline void Seq<_Tp>::insert(int idx, const _Tp* elems, size_t count) +{ + CvMat m = cvMat(1, count, DataType<_Tp>::type, elems); + seqInsertSlice(seq, idx, &m); +} + +template inline void Seq<_Tp>::remove(int idx) +{ seqRemove(seq, idx); } + +template inline void Seq<_Tp>::remove(const Range& r) +{ seqRemoveSlice(seq, cvSlice(r.start, r.end)); } + +template inline void Seq<_Tp>::copyTo(std::vector<_Tp>& vec, const Range& range) const +{ + size_t len = !seq ? 0 : range == Range::all() ? seq->total : range.end - range.start; + vec.resize(len); + if( seq && len ) + cvCvtSeqToArray(seq, &vec[0], cvSlice(range)); +} + +template inline Seq<_Tp>::operator std::vector<_Tp>() const +{ + std::vector<_Tp> vec; + copyTo(vec); + return vec; +} + +template inline SeqIterator<_Tp>::SeqIterator() +{ memset(this, 0, sizeof(*this)); } + +template inline SeqIterator<_Tp>::SeqIterator(const Seq<_Tp>& _seq, bool seekEnd) +{ + cvStartReadSeq(_seq.seq, this); + index = seekEnd ? _seq.seq->total : 0; +} + +template inline void SeqIterator<_Tp>::seek(size_t pos) +{ + cvSetSeqReaderPos(this, (int)pos, false); + index = pos; +} + +template inline size_t SeqIterator<_Tp>::tell() const +{ return index; } + +template inline _Tp& SeqIterator<_Tp>::operator *() +{ return *(_Tp*)ptr; } + +template inline const _Tp& SeqIterator<_Tp>::operator *() const +{ return *(const _Tp*)ptr; } + +template inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator ++() +{ + CV_NEXT_SEQ_ELEM(sizeof(_Tp), *this); + if( ++index >= seq->total*2 ) + index = 0; + return *this; +} + +template inline SeqIterator<_Tp> SeqIterator<_Tp>::operator ++(int) const +{ + SeqIterator<_Tp> it = *this; + ++*this; + return it; +} + +template inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator --() +{ + CV_PREV_SEQ_ELEM(sizeof(_Tp), *this); + if( --index < 0 ) + index = seq->total*2-1; + return *this; +} + +template inline SeqIterator<_Tp> SeqIterator<_Tp>::operator --(int) const +{ + SeqIterator<_Tp> it = *this; + --*this; + return it; +} + +template inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator +=(int delta) +{ + cvSetSeqReaderPos(this, delta, 1); + index += delta; + int n = seq->total*2; + if( index < 0 ) + index += n; + if( index >= n ) + index -= n; + return *this; +} + +template inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator -=(int delta) +{ + return (*this += -delta); +} + +template inline ptrdiff_t operator - (const SeqIterator<_Tp>& a, + const SeqIterator<_Tp>& b) +{ + ptrdiff_t delta = a.index - b.index, n = a.seq->total; + if( delta > n || delta < -n ) + delta += delta < 0 ? n : -n; + return delta; +} + +template inline bool operator == (const SeqIterator<_Tp>& a, + const SeqIterator<_Tp>& b) +{ + return a.seq == b.seq && a.index == b.index; +} + +template inline bool operator != (const SeqIterator<_Tp>& a, + const SeqIterator<_Tp>& b) +{ + return !(a == b); +} + +//! @} + +} // cv + +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/cuda.hpp b/3rdparty/opencv/include/opencv2/core/cuda.hpp new file mode 100644 index 00000000..820aba71 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda.hpp @@ -0,0 +1,1049 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CUDA_HPP +#define OPENCV_CORE_CUDA_HPP + +#ifndef __cplusplus +# error cuda.hpp header must be compiled as C++ +#endif + +#include "opencv2/core.hpp" +#include "opencv2/core/cuda_types.hpp" + +/** + @defgroup cuda CUDA-accelerated Computer Vision + @{ + @defgroup cudacore Core part + @{ + @defgroup cudacore_init Initialization and Information + @defgroup cudacore_struct Data Structures + @} + @} + */ + +namespace cv { namespace cuda { + +//! @addtogroup cudacore_struct +//! @{ + +//=================================================================================== +// GpuMat +//=================================================================================== + +/** @brief Base storage class for GPU memory with reference counting. + +Its interface matches the Mat interface with the following limitations: + +- no arbitrary dimensions support (only 2D) +- no functions that return references to their data (because references on GPU are not valid for + CPU) +- no expression templates technique support + +Beware that the latter limitation may lead to overloaded matrix operators that cause memory +allocations. The GpuMat class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be +passed directly to the kernel. + +@note In contrast with Mat, in most cases GpuMat::isContinuous() == false . This means that rows are +aligned to a size depending on the hardware. Single-row GpuMat is always a continuous matrix. + +@note You are not recommended to leave static or global GpuMat variables allocated, that is, to rely +on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory +release function returns error if the CUDA context has been destroyed before. + +Some member functions are described as a "Blocking Call" while some are described as a +"Non-Blocking Call". Blocking functions are synchronous to host. It is guaranteed that the GPU +operation is finished when the function returns. However, non-blocking functions are asynchronous to +host. Those functions may return even if the GPU operation is not finished. + +Compared to their blocking counterpart, non-blocking functions accept Stream as an additional +argument. If a non-default stream is passed, the GPU operation may overlap with operations in other +streams. + +@sa Mat + */ +class CV_EXPORTS GpuMat +{ +public: + class CV_EXPORTS Allocator + { + public: + virtual ~Allocator() {} + + // allocator must fill data, step and refcount fields + virtual bool allocate(GpuMat* mat, int rows, int cols, size_t elemSize) = 0; + virtual void free(GpuMat* mat) = 0; + }; + + //! default allocator + static Allocator* defaultAllocator(); + static void setDefaultAllocator(Allocator* allocator); + + //! default constructor + explicit GpuMat(Allocator* allocator = defaultAllocator()); + + //! constructs GpuMat of the specified size and type + GpuMat(int rows, int cols, int type, Allocator* allocator = defaultAllocator()); + GpuMat(Size size, int type, Allocator* allocator = defaultAllocator()); + + //! constucts GpuMat and fills it with the specified value _s + GpuMat(int rows, int cols, int type, Scalar s, Allocator* allocator = defaultAllocator()); + GpuMat(Size size, int type, Scalar s, Allocator* allocator = defaultAllocator()); + + //! copy constructor + GpuMat(const GpuMat& m); + + //! constructor for GpuMat headers pointing to user-allocated data + GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP); + GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP); + + //! creates a GpuMat header for a part of the bigger matrix + GpuMat(const GpuMat& m, Range rowRange, Range colRange); + GpuMat(const GpuMat& m, Rect roi); + + //! builds GpuMat from host memory (Blocking call) + explicit GpuMat(InputArray arr, Allocator* allocator = defaultAllocator()); + + //! destructor - calls release() + ~GpuMat(); + + //! assignment operators + GpuMat& operator =(const GpuMat& m); + + //! allocates new GpuMat data unless the GpuMat already has specified size and type + void create(int rows, int cols, int type); + void create(Size size, int type); + + //! decreases reference counter, deallocate the data when reference counter reaches 0 + void release(); + + //! swaps with other smart pointer + void swap(GpuMat& mat); + + /** @brief Performs data upload to GpuMat (Blocking call) + + This function copies data from host memory to device memory. As being a blocking call, it is + guaranteed that the copy operation is finished when this function returns. + */ + void upload(InputArray arr); + + /** @brief Performs data upload to GpuMat (Non-Blocking call) + + This function copies data from host memory to device memory. As being a non-blocking call, this + function may return even if the copy operation is not finished. + + The copy operation may be overlapped with operations in other non-default streams if \p stream is + not the default stream and \p dst is HostMem allocated with HostMem::PAGE_LOCKED option. + */ + void upload(InputArray arr, Stream& stream); + + /** @brief Performs data download from GpuMat (Blocking call) + + This function copies data from device memory to host memory. As being a blocking call, it is + guaranteed that the copy operation is finished when this function returns. + */ + void download(OutputArray dst) const; + + /** @brief Performs data download from GpuMat (Non-Blocking call) + + This function copies data from device memory to host memory. As being a non-blocking call, this + function may return even if the copy operation is not finished. + + The copy operation may be overlapped with operations in other non-default streams if \p stream is + not the default stream and \p dst is HostMem allocated with HostMem::PAGE_LOCKED option. + */ + void download(OutputArray dst, Stream& stream) const; + + //! returns deep copy of the GpuMat, i.e. the data is copied + GpuMat clone() const; + + //! copies the GpuMat content to device memory (Blocking call) + void copyTo(OutputArray dst) const; + + //! copies the GpuMat content to device memory (Non-Blocking call) + void copyTo(OutputArray dst, Stream& stream) const; + + //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call) + void copyTo(OutputArray dst, InputArray mask) const; + + //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call) + void copyTo(OutputArray dst, InputArray mask, Stream& stream) const; + + //! sets some of the GpuMat elements to s (Blocking call) + GpuMat& setTo(Scalar s); + + //! sets some of the GpuMat elements to s (Non-Blocking call) + GpuMat& setTo(Scalar s, Stream& stream); + + //! sets some of the GpuMat elements to s, according to the mask (Blocking call) + GpuMat& setTo(Scalar s, InputArray mask); + + //! sets some of the GpuMat elements to s, according to the mask (Non-Blocking call) + GpuMat& setTo(Scalar s, InputArray mask, Stream& stream); + + //! converts GpuMat to another datatype (Blocking call) + void convertTo(OutputArray dst, int rtype) const; + + //! converts GpuMat to another datatype (Non-Blocking call) + void convertTo(OutputArray dst, int rtype, Stream& stream) const; + + //! converts GpuMat to another datatype with scaling (Blocking call) + void convertTo(OutputArray dst, int rtype, double alpha, double beta = 0.0) const; + + //! converts GpuMat to another datatype with scaling (Non-Blocking call) + void convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const; + + //! converts GpuMat to another datatype with scaling (Non-Blocking call) + void convertTo(OutputArray dst, int rtype, double alpha, double beta, Stream& stream) const; + + void assignTo(GpuMat& m, int type=-1) const; + + //! returns pointer to y-th row + uchar* ptr(int y = 0); + const uchar* ptr(int y = 0) const; + + //! template version of the above method + template _Tp* ptr(int y = 0); + template const _Tp* ptr(int y = 0) const; + + template operator PtrStepSz<_Tp>() const; + template operator PtrStep<_Tp>() const; + + //! returns a new GpuMat header for the specified row + GpuMat row(int y) const; + + //! returns a new GpuMat header for the specified column + GpuMat col(int x) const; + + //! ... for the specified row span + GpuMat rowRange(int startrow, int endrow) const; + GpuMat rowRange(Range r) const; + + //! ... for the specified column span + GpuMat colRange(int startcol, int endcol) const; + GpuMat colRange(Range r) const; + + //! extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.) + GpuMat operator ()(Range rowRange, Range colRange) const; + GpuMat operator ()(Rect roi) const; + + //! creates alternative GpuMat header for the same data, with different + //! number of channels and/or different number of rows + GpuMat reshape(int cn, int rows = 0) const; + + //! locates GpuMat header within a parent GpuMat + void locateROI(Size& wholeSize, Point& ofs) const; + + //! moves/resizes the current GpuMat ROI inside the parent GpuMat + GpuMat& adjustROI(int dtop, int dbottom, int dleft, int dright); + + //! returns true iff the GpuMat data is continuous + //! (i.e. when there are no gaps between successive rows) + bool isContinuous() const; + + //! returns element size in bytes + size_t elemSize() const; + + //! returns the size of element channel in bytes + size_t elemSize1() const; + + //! returns element type + int type() const; + + //! returns element type + int depth() const; + + //! returns number of channels + int channels() const; + + //! returns step/elemSize1() + size_t step1() const; + + //! returns GpuMat size : width == number of columns, height == number of rows + Size size() const; + + //! returns true if GpuMat data is NULL + bool empty() const; + + //! internal use method: updates the continuity flag + void updateContinuityFlag(); + + /*! includes several bit-fields: + - the magic signature + - continuity flag + - depth + - number of channels + */ + int flags; + + //! the number of rows and columns + int rows, cols; + + //! a distance between successive rows in bytes; includes the gap if any + size_t step; + + //! pointer to the data + uchar* data; + + //! pointer to the reference counter; + //! when GpuMat points to user-allocated data, the pointer is NULL + int* refcount; + + //! helper fields used in locateROI and adjustROI + uchar* datastart; + const uchar* dataend; + + //! allocator + Allocator* allocator; +}; + +/** @brief Creates a continuous matrix. + +@param rows Row count. +@param cols Column count. +@param type Type of the matrix. +@param arr Destination matrix. This parameter changes only if it has a proper type and area ( +\f$\texttt{rows} \times \texttt{cols}\f$ ). + +Matrix is called continuous if its elements are stored continuously, that is, without gaps at the +end of each row. + */ +CV_EXPORTS void createContinuous(int rows, int cols, int type, OutputArray arr); + +/** @brief Ensures that the size of a matrix is big enough and the matrix has a proper type. + +@param rows Minimum desired number of rows. +@param cols Minimum desired number of columns. +@param type Desired matrix type. +@param arr Destination matrix. + +The function does not reallocate memory if the matrix has proper attributes already. + */ +CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, OutputArray arr); + +/** @brief BufferPool for use with CUDA streams + +BufferPool utilizes Stream's allocator to create new buffers for GpuMat's. It is +only useful when enabled with #setBufferPoolUsage. + +@code + setBufferPoolUsage(true); +@endcode + +@note #setBufferPoolUsage must be called \em before any Stream declaration. + +Users may specify custom allocator for Stream and may implement their own stream based +functions utilizing the same underlying GPU memory management. + +If custom allocator is not specified, BufferPool utilizes StackAllocator by +default. StackAllocator allocates a chunk of GPU device memory beforehand, +and when GpuMat is declared later on, it is given the pre-allocated memory. +This kind of strategy reduces the number of calls for memory allocating APIs +such as cudaMalloc or cudaMallocPitch. + +Below is an example that utilizes BufferPool with StackAllocator: + +@code + #include + + using namespace cv; + using namespace cv::cuda + + int main() + { + setBufferPoolUsage(true); // Tell OpenCV that we are going to utilize BufferPool + setBufferPoolConfig(getDevice(), 1024 * 1024 * 64, 2); // Allocate 64 MB, 2 stacks (default is 10 MB, 5 stacks) + + Stream stream1, stream2; // Each stream uses 1 stack + BufferPool pool1(stream1), pool2(stream2); + + GpuMat d_src1 = pool1.getBuffer(4096, 4096, CV_8UC1); // 16MB + GpuMat d_dst1 = pool1.getBuffer(4096, 4096, CV_8UC3); // 48MB, pool1 is now full + + GpuMat d_src2 = pool2.getBuffer(1024, 1024, CV_8UC1); // 1MB + GpuMat d_dst2 = pool2.getBuffer(1024, 1024, CV_8UC3); // 3MB + + cvtColor(d_src1, d_dst1, CV_GRAY2BGR, 0, stream1); + cvtColor(d_src2, d_dst2, CV_GRAY2BGR, 0, stream2); + } +@endcode + +If we allocate another GpuMat on pool1 in the above example, it will be carried out by +the DefaultAllocator since the stack for pool1 is full. + +@code + GpuMat d_add1 = pool1.getBuffer(1024, 1024, CV_8UC1); // Stack for pool1 is full, memory is allocated with DefaultAllocator +@endcode + +If a third stream is declared in the above example, allocating with #getBuffer +within that stream will also be carried out by the DefaultAllocator because we've run out of +stacks. + +@code + Stream stream3; // Only 2 stacks were allocated, we've run out of stacks + BufferPool pool3(stream3); + GpuMat d_src3 = pool3.getBuffer(1024, 1024, CV_8UC1); // Memory is allocated with DefaultAllocator +@endcode + +@warning When utilizing StackAllocator, deallocation order is important. + +Just like a stack, deallocation must be done in LIFO order. Below is an example of +erroneous usage that violates LIFO rule. If OpenCV is compiled in Debug mode, this +sample code will emit CV_Assert error. + +@code + int main() + { + setBufferPoolUsage(true); // Tell OpenCV that we are going to utilize BufferPool + Stream stream; // A default size (10 MB) stack is allocated to this stream + BufferPool pool(stream); + + GpuMat mat1 = pool.getBuffer(1024, 1024, CV_8UC1); // Allocate mat1 (1MB) + GpuMat mat2 = pool.getBuffer(1024, 1024, CV_8UC1); // Allocate mat2 (1MB) + + mat1.release(); // erroneous usage : mat2 must be deallocated before mat1 + } +@endcode + +Since C++ local variables are destroyed in the reverse order of construction, +the code sample below satisfies the LIFO rule. Local GpuMat's are deallocated +and the corresponding memory is automatically returned to the pool for later usage. + +@code + int main() + { + setBufferPoolUsage(true); // Tell OpenCV that we are going to utilize BufferPool + setBufferPoolConfig(getDevice(), 1024 * 1024 * 64, 2); // Allocate 64 MB, 2 stacks (default is 10 MB, 5 stacks) + + Stream stream1, stream2; // Each stream uses 1 stack + BufferPool pool1(stream1), pool2(stream2); + + for (int i = 0; i < 10; i++) + { + GpuMat d_src1 = pool1.getBuffer(4096, 4096, CV_8UC1); // 16MB + GpuMat d_dst1 = pool1.getBuffer(4096, 4096, CV_8UC3); // 48MB, pool1 is now full + + GpuMat d_src2 = pool2.getBuffer(1024, 1024, CV_8UC1); // 1MB + GpuMat d_dst2 = pool2.getBuffer(1024, 1024, CV_8UC3); // 3MB + + d_src1.setTo(Scalar(i), stream1); + d_src2.setTo(Scalar(i), stream2); + + cvtColor(d_src1, d_dst1, CV_GRAY2BGR, 0, stream1); + cvtColor(d_src2, d_dst2, CV_GRAY2BGR, 0, stream2); + // The order of destruction of the local variables is: + // d_dst2 => d_src2 => d_dst1 => d_src1 + // LIFO rule is satisfied, this code runs without error + } + } +@endcode + */ +class CV_EXPORTS BufferPool +{ +public: + + //! Gets the BufferPool for the given stream. + explicit BufferPool(Stream& stream); + + //! Allocates a new GpuMat of given size and type. + GpuMat getBuffer(int rows, int cols, int type); + + //! Allocates a new GpuMat of given size and type. + GpuMat getBuffer(Size size, int type) { return getBuffer(size.height, size.width, type); } + + //! Returns the allocator associated with the stream. + Ptr getAllocator() const { return allocator_; } + +private: + Ptr allocator_; +}; + +//! BufferPool management (must be called before Stream creation) +CV_EXPORTS void setBufferPoolUsage(bool on); +CV_EXPORTS void setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount); + +//=================================================================================== +// HostMem +//=================================================================================== + +/** @brief Class with reference counting wrapping special memory type allocation functions from CUDA. + +Its interface is also Mat-like but with additional memory type parameters. + +- **PAGE_LOCKED** sets a page locked memory type used commonly for fast and asynchronous + uploading/downloading data from/to GPU. +- **SHARED** specifies a zero copy memory allocation that enables mapping the host memory to GPU + address space, if supported. +- **WRITE_COMBINED** sets the write combined buffer that is not cached by CPU. Such buffers are + used to supply GPU with data when GPU only reads it. The advantage is a better CPU cache + utilization. + +@note Allocation size of such memory types is usually limited. For more details, see *CUDA 2.2 +Pinned Memory APIs* document or *CUDA C Programming Guide*. + */ +class CV_EXPORTS HostMem +{ +public: + enum AllocType { PAGE_LOCKED = 1, SHARED = 2, WRITE_COMBINED = 4 }; + + static MatAllocator* getAllocator(AllocType alloc_type = PAGE_LOCKED); + + explicit HostMem(AllocType alloc_type = PAGE_LOCKED); + + HostMem(const HostMem& m); + + HostMem(int rows, int cols, int type, AllocType alloc_type = PAGE_LOCKED); + HostMem(Size size, int type, AllocType alloc_type = PAGE_LOCKED); + + //! creates from host memory with coping data + explicit HostMem(InputArray arr, AllocType alloc_type = PAGE_LOCKED); + + ~HostMem(); + + HostMem& operator =(const HostMem& m); + + //! swaps with other smart pointer + void swap(HostMem& b); + + //! returns deep copy of the matrix, i.e. the data is copied + HostMem clone() const; + + //! allocates new matrix data unless the matrix already has specified size and type. + void create(int rows, int cols, int type); + void create(Size size, int type); + + //! creates alternative HostMem header for the same data, with different + //! number of channels and/or different number of rows + HostMem reshape(int cn, int rows = 0) const; + + //! decrements reference counter and released memory if needed. + void release(); + + //! returns matrix header with disabled reference counting for HostMem data. + Mat createMatHeader() const; + + /** @brief Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting + for it. + + This can be done only if memory was allocated with the SHARED flag and if it is supported by the + hardware. Laptops often share video and CPU memory, so address spaces can be mapped, which + eliminates an extra copy. + */ + GpuMat createGpuMatHeader() const; + + // Please see cv::Mat for descriptions + bool isContinuous() const; + size_t elemSize() const; + size_t elemSize1() const; + int type() const; + int depth() const; + int channels() const; + size_t step1() const; + Size size() const; + bool empty() const; + + // Please see cv::Mat for descriptions + int flags; + int rows, cols; + size_t step; + + uchar* data; + int* refcount; + + uchar* datastart; + const uchar* dataend; + + AllocType alloc_type; +}; + +/** @brief Page-locks the memory of matrix and maps it for the device(s). + +@param m Input matrix. + */ +CV_EXPORTS void registerPageLocked(Mat& m); + +/** @brief Unmaps the memory of matrix and makes it pageable again. + +@param m Input matrix. + */ +CV_EXPORTS void unregisterPageLocked(Mat& m); + +//=================================================================================== +// Stream +//=================================================================================== + +/** @brief This class encapsulates a queue of asynchronous calls. + +@note Currently, you may face problems if an operation is enqueued twice with different data. Some +functions use the constant GPU memory, and next call may update the memory before the previous one +has been finished. But calling different operations asynchronously is safe because each operation +has its own constant buffer. Memory copy/upload/download/set operations to the buffers you hold are +also safe. + +@note The Stream class is not thread-safe. Please use different Stream objects for different CPU threads. + +@code +void thread1() +{ + cv::cuda::Stream stream1; + cv::cuda::func1(..., stream1); +} + +void thread2() +{ + cv::cuda::Stream stream2; + cv::cuda::func2(..., stream2); +} +@endcode + +@note By default all CUDA routines are launched in Stream::Null() object, if the stream is not specified by user. +In multi-threading environment the stream objects must be passed explicitly (see previous note). + */ +class CV_EXPORTS Stream +{ + typedef void (Stream::*bool_type)() const; + void this_type_does_not_support_comparisons() const {} + +public: + typedef void (*StreamCallback)(int status, void* userData); + + //! creates a new asynchronous stream + Stream(); + + //! creates a new asynchronous stream with custom allocator + Stream(const Ptr& allocator); + + /** @brief Returns true if the current stream queue is finished. Otherwise, it returns false. + */ + bool queryIfComplete() const; + + /** @brief Blocks the current CPU thread until all operations in the stream are complete. + */ + void waitForCompletion(); + + /** @brief Makes a compute stream wait on an event. + */ + void waitEvent(const Event& event); + + /** @brief Adds a callback to be called on the host after all currently enqueued items in the stream have + completed. + + @note Callbacks must not make any CUDA API calls. Callbacks must not perform any synchronization + that may depend on outstanding device work or other callbacks that are not mandated to run earlier. + Callbacks without a mandated order (in independent streams) execute in undefined order and may be + serialized. + */ + void enqueueHostCallback(StreamCallback callback, void* userData); + + //! return Stream object for default CUDA stream + static Stream& Null(); + + //! returns true if stream object is not default (!= 0) + operator bool_type() const; + + class Impl; + +private: + Ptr impl_; + Stream(const Ptr& impl); + + friend struct StreamAccessor; + friend class BufferPool; + friend class DefaultDeviceInitializer; +}; + +class CV_EXPORTS Event +{ +public: + enum CreateFlags + { + DEFAULT = 0x00, /**< Default event flag */ + BLOCKING_SYNC = 0x01, /**< Event uses blocking synchronization */ + DISABLE_TIMING = 0x02, /**< Event will not record timing data */ + INTERPROCESS = 0x04 /**< Event is suitable for interprocess use. DisableTiming must be set */ + }; + + explicit Event(CreateFlags flags = DEFAULT); + + //! records an event + void record(Stream& stream = Stream::Null()); + + //! queries an event's status + bool queryIfComplete() const; + + //! waits for an event to complete + void waitForCompletion(); + + //! computes the elapsed time between events + static float elapsedTime(const Event& start, const Event& end); + + class Impl; + +private: + Ptr impl_; + Event(const Ptr& impl); + + friend struct EventAccessor; +}; + +//! @} cudacore_struct + +//=================================================================================== +// Initialization & Info +//=================================================================================== + +//! @addtogroup cudacore_init +//! @{ + +/** @brief Returns the number of installed CUDA-enabled devices. + +Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support, +this function returns 0. If the CUDA driver is not installed, or is incompatible, this function +returns -1. + */ +CV_EXPORTS int getCudaEnabledDeviceCount(); + +/** @brief Sets a device and initializes it for the current thread. + +@param device System index of a CUDA device starting with 0. + +If the call of this function is omitted, a default device is initialized at the fist CUDA usage. + */ +CV_EXPORTS void setDevice(int device); + +/** @brief Returns the current device index set by cuda::setDevice or initialized by default. + */ +CV_EXPORTS int getDevice(); + +/** @brief Explicitly destroys and cleans up all resources associated with the current device in the current +process. + +Any subsequent API call to this device will reinitialize the device. + */ +CV_EXPORTS void resetDevice(); + +/** @brief Enumeration providing CUDA computing features. + */ +enum FeatureSet +{ + FEATURE_SET_COMPUTE_10 = 10, + FEATURE_SET_COMPUTE_11 = 11, + FEATURE_SET_COMPUTE_12 = 12, + FEATURE_SET_COMPUTE_13 = 13, + FEATURE_SET_COMPUTE_20 = 20, + FEATURE_SET_COMPUTE_21 = 21, + FEATURE_SET_COMPUTE_30 = 30, + FEATURE_SET_COMPUTE_32 = 32, + FEATURE_SET_COMPUTE_35 = 35, + FEATURE_SET_COMPUTE_50 = 50, + + GLOBAL_ATOMICS = FEATURE_SET_COMPUTE_11, + SHARED_ATOMICS = FEATURE_SET_COMPUTE_12, + NATIVE_DOUBLE = FEATURE_SET_COMPUTE_13, + WARP_SHUFFLE_FUNCTIONS = FEATURE_SET_COMPUTE_30, + DYNAMIC_PARALLELISM = FEATURE_SET_COMPUTE_35 +}; + +//! checks whether current device supports the given feature +CV_EXPORTS bool deviceSupports(FeatureSet feature_set); + +/** @brief Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was +built for. + +According to the CUDA C Programming Guide Version 3.2: "PTX code produced for some specific compute +capability can always be compiled to binary code of greater or equal compute capability". + */ +class CV_EXPORTS TargetArchs +{ +public: + /** @brief The following method checks whether the module was built with the support of the given feature: + + @param feature_set Features to be checked. See :ocvcuda::FeatureSet. + */ + static bool builtWith(FeatureSet feature_set); + + /** @brief There is a set of methods to check whether the module contains intermediate (PTX) or binary CUDA + code for the given architecture(s): + + @param major Major compute capability version. + @param minor Minor compute capability version. + */ + static bool has(int major, int minor); + static bool hasPtx(int major, int minor); + static bool hasBin(int major, int minor); + + static bool hasEqualOrLessPtx(int major, int minor); + static bool hasEqualOrGreater(int major, int minor); + static bool hasEqualOrGreaterPtx(int major, int minor); + static bool hasEqualOrGreaterBin(int major, int minor); +}; + +/** @brief Class providing functionality for querying the specified GPU properties. + */ +class CV_EXPORTS DeviceInfo +{ +public: + //! creates DeviceInfo object for the current GPU + DeviceInfo(); + + /** @brief The constructors. + + @param device_id System index of the CUDA device starting with 0. + + Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it + constructs an object for the current device. + */ + DeviceInfo(int device_id); + + /** @brief Returns system index of the CUDA device starting with 0. + */ + int deviceID() const; + + //! ASCII string identifying device + const char* name() const; + + //! global memory available on device in bytes + size_t totalGlobalMem() const; + + //! shared memory available per block in bytes + size_t sharedMemPerBlock() const; + + //! 32-bit registers available per block + int regsPerBlock() const; + + //! warp size in threads + int warpSize() const; + + //! maximum pitch in bytes allowed by memory copies + size_t memPitch() const; + + //! maximum number of threads per block + int maxThreadsPerBlock() const; + + //! maximum size of each dimension of a block + Vec3i maxThreadsDim() const; + + //! maximum size of each dimension of a grid + Vec3i maxGridSize() const; + + //! clock frequency in kilohertz + int clockRate() const; + + //! constant memory available on device in bytes + size_t totalConstMem() const; + + //! major compute capability + int majorVersion() const; + + //! minor compute capability + int minorVersion() const; + + //! alignment requirement for textures + size_t textureAlignment() const; + + //! pitch alignment requirement for texture references bound to pitched memory + size_t texturePitchAlignment() const; + + //! number of multiprocessors on device + int multiProcessorCount() const; + + //! specified whether there is a run time limit on kernels + bool kernelExecTimeoutEnabled() const; + + //! device is integrated as opposed to discrete + bool integrated() const; + + //! device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer + bool canMapHostMemory() const; + + enum ComputeMode + { + ComputeModeDefault, /**< default compute mode (Multiple threads can use cudaSetDevice with this device) */ + ComputeModeExclusive, /**< compute-exclusive-thread mode (Only one thread in one process will be able to use cudaSetDevice with this device) */ + ComputeModeProhibited, /**< compute-prohibited mode (No threads can use cudaSetDevice with this device) */ + ComputeModeExclusiveProcess /**< compute-exclusive-process mode (Many threads in one process will be able to use cudaSetDevice with this device) */ + }; + + //! compute mode + ComputeMode computeMode() const; + + //! maximum 1D texture size + int maxTexture1D() const; + + //! maximum 1D mipmapped texture size + int maxTexture1DMipmap() const; + + //! maximum size for 1D textures bound to linear memory + int maxTexture1DLinear() const; + + //! maximum 2D texture dimensions + Vec2i maxTexture2D() const; + + //! maximum 2D mipmapped texture dimensions + Vec2i maxTexture2DMipmap() const; + + //! maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory + Vec3i maxTexture2DLinear() const; + + //! maximum 2D texture dimensions if texture gather operations have to be performed + Vec2i maxTexture2DGather() const; + + //! maximum 3D texture dimensions + Vec3i maxTexture3D() const; + + //! maximum Cubemap texture dimensions + int maxTextureCubemap() const; + + //! maximum 1D layered texture dimensions + Vec2i maxTexture1DLayered() const; + + //! maximum 2D layered texture dimensions + Vec3i maxTexture2DLayered() const; + + //! maximum Cubemap layered texture dimensions + Vec2i maxTextureCubemapLayered() const; + + //! maximum 1D surface size + int maxSurface1D() const; + + //! maximum 2D surface dimensions + Vec2i maxSurface2D() const; + + //! maximum 3D surface dimensions + Vec3i maxSurface3D() const; + + //! maximum 1D layered surface dimensions + Vec2i maxSurface1DLayered() const; + + //! maximum 2D layered surface dimensions + Vec3i maxSurface2DLayered() const; + + //! maximum Cubemap surface dimensions + int maxSurfaceCubemap() const; + + //! maximum Cubemap layered surface dimensions + Vec2i maxSurfaceCubemapLayered() const; + + //! alignment requirements for surfaces + size_t surfaceAlignment() const; + + //! device can possibly execute multiple kernels concurrently + bool concurrentKernels() const; + + //! device has ECC support enabled + bool ECCEnabled() const; + + //! PCI bus ID of the device + int pciBusID() const; + + //! PCI device ID of the device + int pciDeviceID() const; + + //! PCI domain ID of the device + int pciDomainID() const; + + //! true if device is a Tesla device using TCC driver, false otherwise + bool tccDriver() const; + + //! number of asynchronous engines + int asyncEngineCount() const; + + //! device shares a unified address space with the host + bool unifiedAddressing() const; + + //! peak memory clock frequency in kilohertz + int memoryClockRate() const; + + //! global memory bus width in bits + int memoryBusWidth() const; + + //! size of L2 cache in bytes + int l2CacheSize() const; + + //! maximum resident threads per multiprocessor + int maxThreadsPerMultiProcessor() const; + + //! gets free and total device memory + void queryMemory(size_t& totalMemory, size_t& freeMemory) const; + size_t freeMemory() const; + size_t totalMemory() const; + + /** @brief Provides information on CUDA feature support. + + @param feature_set Features to be checked. See cuda::FeatureSet. + + This function returns true if the device has the specified CUDA feature. Otherwise, it returns false + */ + bool supports(FeatureSet feature_set) const; + + /** @brief Checks the CUDA module and device compatibility. + + This function returns true if the CUDA module can be run on the specified device. Otherwise, it + returns false . + */ + bool isCompatible() const; + +private: + int device_id_; +}; + +CV_EXPORTS void printCudaDeviceInfo(int device); +CV_EXPORTS void printShortCudaDeviceInfo(int device); + +/** @brief Converts an array to half precision floating number. + +@param _src input array. +@param _dst output array. +@param stream Stream for the asynchronous version. +@sa convertFp16 +*/ +CV_EXPORTS void convertFp16(InputArray _src, OutputArray _dst, Stream& stream = Stream::Null()); + +//! @} cudacore_init + +}} // namespace cv { namespace cuda { + + +#include "opencv2/core/cuda.inl.hpp" + +#endif /* OPENCV_CORE_CUDA_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda.inl.hpp b/3rdparty/opencv/include/opencv2/core/cuda.inl.hpp new file mode 100644 index 00000000..35ae2e49 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda.inl.hpp @@ -0,0 +1,631 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CUDAINL_HPP +#define OPENCV_CORE_CUDAINL_HPP + +#include "opencv2/core/cuda.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { + +//=================================================================================== +// GpuMat +//=================================================================================== + +inline +GpuMat::GpuMat(Allocator* allocator_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{} + +inline +GpuMat::GpuMat(int rows_, int cols_, int type_, Allocator* allocator_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{ + if (rows_ > 0 && cols_ > 0) + create(rows_, cols_, type_); +} + +inline +GpuMat::GpuMat(Size size_, int type_, Allocator* allocator_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{ + if (size_.height > 0 && size_.width > 0) + create(size_.height, size_.width, type_); +} + +inline +GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_, Allocator* allocator_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{ + if (rows_ > 0 && cols_ > 0) + { + create(rows_, cols_, type_); + setTo(s_); + } +} + +inline +GpuMat::GpuMat(Size size_, int type_, Scalar s_, Allocator* allocator_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{ + if (size_.height > 0 && size_.width > 0) + { + create(size_.height, size_.width, type_); + setTo(s_); + } +} + +inline +GpuMat::GpuMat(const GpuMat& m) + : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), allocator(m.allocator) +{ + if (refcount) + CV_XADD(refcount, 1); +} + +inline +GpuMat::GpuMat(InputArray arr, Allocator* allocator_) : + flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_) +{ + upload(arr); +} + +inline +GpuMat::~GpuMat() +{ + release(); +} + +inline +GpuMat& GpuMat::operator =(const GpuMat& m) +{ + if (this != &m) + { + GpuMat temp(m); + swap(temp); + } + + return *this; +} + +inline +void GpuMat::create(Size size_, int type_) +{ + create(size_.height, size_.width, type_); +} + +inline +void GpuMat::swap(GpuMat& b) +{ + std::swap(flags, b.flags); + std::swap(rows, b.rows); + std::swap(cols, b.cols); + std::swap(step, b.step); + std::swap(data, b.data); + std::swap(datastart, b.datastart); + std::swap(dataend, b.dataend); + std::swap(refcount, b.refcount); + std::swap(allocator, b.allocator); +} + +inline +GpuMat GpuMat::clone() const +{ + GpuMat m; + copyTo(m); + return m; +} + +inline +void GpuMat::copyTo(OutputArray dst, InputArray mask) const +{ + copyTo(dst, mask, Stream::Null()); +} + +inline +GpuMat& GpuMat::setTo(Scalar s) +{ + return setTo(s, Stream::Null()); +} + +inline +GpuMat& GpuMat::setTo(Scalar s, InputArray mask) +{ + return setTo(s, mask, Stream::Null()); +} + +inline +void GpuMat::convertTo(OutputArray dst, int rtype) const +{ + convertTo(dst, rtype, Stream::Null()); +} + +inline +void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, double beta) const +{ + convertTo(dst, rtype, alpha, beta, Stream::Null()); +} + +inline +void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const +{ + convertTo(dst, rtype, alpha, 0.0, stream); +} + +inline +void GpuMat::assignTo(GpuMat& m, int _type) const +{ + if (_type < 0) + m = *this; + else + convertTo(m, _type); +} + +inline +uchar* GpuMat::ptr(int y) +{ + CV_DbgAssert( (unsigned)y < (unsigned)rows ); + return data + step * y; +} + +inline +const uchar* GpuMat::ptr(int y) const +{ + CV_DbgAssert( (unsigned)y < (unsigned)rows ); + return data + step * y; +} + +template inline +_Tp* GpuMat::ptr(int y) +{ + return (_Tp*)ptr(y); +} + +template inline +const _Tp* GpuMat::ptr(int y) const +{ + return (const _Tp*)ptr(y); +} + +template inline +GpuMat::operator PtrStepSz() const +{ + return PtrStepSz(rows, cols, (T*)data, step); +} + +template inline +GpuMat::operator PtrStep() const +{ + return PtrStep((T*)data, step); +} + +inline +GpuMat GpuMat::row(int y) const +{ + return GpuMat(*this, Range(y, y+1), Range::all()); +} + +inline +GpuMat GpuMat::col(int x) const +{ + return GpuMat(*this, Range::all(), Range(x, x+1)); +} + +inline +GpuMat GpuMat::rowRange(int startrow, int endrow) const +{ + return GpuMat(*this, Range(startrow, endrow), Range::all()); +} + +inline +GpuMat GpuMat::rowRange(Range r) const +{ + return GpuMat(*this, r, Range::all()); +} + +inline +GpuMat GpuMat::colRange(int startcol, int endcol) const +{ + return GpuMat(*this, Range::all(), Range(startcol, endcol)); +} + +inline +GpuMat GpuMat::colRange(Range r) const +{ + return GpuMat(*this, Range::all(), r); +} + +inline +GpuMat GpuMat::operator ()(Range rowRange_, Range colRange_) const +{ + return GpuMat(*this, rowRange_, colRange_); +} + +inline +GpuMat GpuMat::operator ()(Rect roi) const +{ + return GpuMat(*this, roi); +} + +inline +bool GpuMat::isContinuous() const +{ + return (flags & Mat::CONTINUOUS_FLAG) != 0; +} + +inline +size_t GpuMat::elemSize() const +{ + return CV_ELEM_SIZE(flags); +} + +inline +size_t GpuMat::elemSize1() const +{ + return CV_ELEM_SIZE1(flags); +} + +inline +int GpuMat::type() const +{ + return CV_MAT_TYPE(flags); +} + +inline +int GpuMat::depth() const +{ + return CV_MAT_DEPTH(flags); +} + +inline +int GpuMat::channels() const +{ + return CV_MAT_CN(flags); +} + +inline +size_t GpuMat::step1() const +{ + return step / elemSize1(); +} + +inline +Size GpuMat::size() const +{ + return Size(cols, rows); +} + +inline +bool GpuMat::empty() const +{ + return data == 0; +} + +static inline +GpuMat createContinuous(int rows, int cols, int type) +{ + GpuMat m; + createContinuous(rows, cols, type, m); + return m; +} + +static inline +void createContinuous(Size size, int type, OutputArray arr) +{ + createContinuous(size.height, size.width, type, arr); +} + +static inline +GpuMat createContinuous(Size size, int type) +{ + GpuMat m; + createContinuous(size, type, m); + return m; +} + +static inline +void ensureSizeIsEnough(Size size, int type, OutputArray arr) +{ + ensureSizeIsEnough(size.height, size.width, type, arr); +} + +static inline +void swap(GpuMat& a, GpuMat& b) +{ + a.swap(b); +} + +//=================================================================================== +// HostMem +//=================================================================================== + +inline +HostMem::HostMem(AllocType alloc_type_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_) +{ +} + +inline +HostMem::HostMem(const HostMem& m) + : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), alloc_type(m.alloc_type) +{ + if( refcount ) + CV_XADD(refcount, 1); +} + +inline +HostMem::HostMem(int rows_, int cols_, int type_, AllocType alloc_type_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_) +{ + if (rows_ > 0 && cols_ > 0) + create(rows_, cols_, type_); +} + +inline +HostMem::HostMem(Size size_, int type_, AllocType alloc_type_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_) +{ + if (size_.height > 0 && size_.width > 0) + create(size_.height, size_.width, type_); +} + +inline +HostMem::HostMem(InputArray arr, AllocType alloc_type_) + : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_) +{ + arr.getMat().copyTo(*this); +} + +inline +HostMem::~HostMem() +{ + release(); +} + +inline +HostMem& HostMem::operator =(const HostMem& m) +{ + if (this != &m) + { + HostMem temp(m); + swap(temp); + } + + return *this; +} + +inline +void HostMem::swap(HostMem& b) +{ + std::swap(flags, b.flags); + std::swap(rows, b.rows); + std::swap(cols, b.cols); + std::swap(step, b.step); + std::swap(data, b.data); + std::swap(datastart, b.datastart); + std::swap(dataend, b.dataend); + std::swap(refcount, b.refcount); + std::swap(alloc_type, b.alloc_type); +} + +inline +HostMem HostMem::clone() const +{ + HostMem m(size(), type(), alloc_type); + createMatHeader().copyTo(m); + return m; +} + +inline +void HostMem::create(Size size_, int type_) +{ + create(size_.height, size_.width, type_); +} + +inline +Mat HostMem::createMatHeader() const +{ + return Mat(size(), type(), data, step); +} + +inline +bool HostMem::isContinuous() const +{ + return (flags & Mat::CONTINUOUS_FLAG) != 0; +} + +inline +size_t HostMem::elemSize() const +{ + return CV_ELEM_SIZE(flags); +} + +inline +size_t HostMem::elemSize1() const +{ + return CV_ELEM_SIZE1(flags); +} + +inline +int HostMem::type() const +{ + return CV_MAT_TYPE(flags); +} + +inline +int HostMem::depth() const +{ + return CV_MAT_DEPTH(flags); +} + +inline +int HostMem::channels() const +{ + return CV_MAT_CN(flags); +} + +inline +size_t HostMem::step1() const +{ + return step / elemSize1(); +} + +inline +Size HostMem::size() const +{ + return Size(cols, rows); +} + +inline +bool HostMem::empty() const +{ + return data == 0; +} + +static inline +void swap(HostMem& a, HostMem& b) +{ + a.swap(b); +} + +//=================================================================================== +// Stream +//=================================================================================== + +inline +Stream::Stream(const Ptr& impl) + : impl_(impl) +{ +} + +//=================================================================================== +// Event +//=================================================================================== + +inline +Event::Event(const Ptr& impl) + : impl_(impl) +{ +} + +//=================================================================================== +// Initialization & Info +//=================================================================================== + +inline +bool TargetArchs::has(int major, int minor) +{ + return hasPtx(major, minor) || hasBin(major, minor); +} + +inline +bool TargetArchs::hasEqualOrGreater(int major, int minor) +{ + return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor); +} + +inline +DeviceInfo::DeviceInfo() +{ + device_id_ = getDevice(); +} + +inline +DeviceInfo::DeviceInfo(int device_id) +{ + CV_Assert( device_id >= 0 && device_id < getCudaEnabledDeviceCount() ); + device_id_ = device_id; +} + +inline +int DeviceInfo::deviceID() const +{ + return device_id_; +} + +inline +size_t DeviceInfo::freeMemory() const +{ + size_t _totalMemory = 0, _freeMemory = 0; + queryMemory(_totalMemory, _freeMemory); + return _freeMemory; +} + +inline +size_t DeviceInfo::totalMemory() const +{ + size_t _totalMemory = 0, _freeMemory = 0; + queryMemory(_totalMemory, _freeMemory); + return _totalMemory; +} + +inline +bool DeviceInfo::supports(FeatureSet feature_set) const +{ + int version = majorVersion() * 10 + minorVersion(); + return version >= feature_set; +} + + +}} // namespace cv { namespace cuda { + +//=================================================================================== +// Mat +//=================================================================================== + +namespace cv { + +inline +Mat::Mat(const cuda::GpuMat& m) + : flags(0), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows) +{ + m.download(*this); +} + +} + +//! @endcond + +#endif // OPENCV_CORE_CUDAINL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/block.hpp b/3rdparty/opencv/include/opencv2/core/cuda/block.hpp new file mode 100644 index 00000000..c277f0ea --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/block.hpp @@ -0,0 +1,211 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_DEVICE_BLOCK_HPP +#define OPENCV_CUDA_DEVICE_BLOCK_HPP + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + struct Block + { + static __device__ __forceinline__ unsigned int id() + { + return blockIdx.x; + } + + static __device__ __forceinline__ unsigned int stride() + { + return blockDim.x * blockDim.y * blockDim.z; + } + + static __device__ __forceinline__ void sync() + { + __syncthreads(); + } + + static __device__ __forceinline__ int flattenedThreadId() + { + return threadIdx.z * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x; + } + + template + static __device__ __forceinline__ void fill(It beg, It end, const T& value) + { + int STRIDE = stride(); + It t = beg + flattenedThreadId(); + + for(; t < end; t += STRIDE) + *t = value; + } + + template + static __device__ __forceinline__ void yota(OutIt beg, OutIt end, T value) + { + int STRIDE = stride(); + int tid = flattenedThreadId(); + value += tid; + + for(OutIt t = beg + tid; t < end; t += STRIDE, value += STRIDE) + *t = value; + } + + template + static __device__ __forceinline__ void copy(InIt beg, InIt end, OutIt out) + { + int STRIDE = stride(); + InIt t = beg + flattenedThreadId(); + OutIt o = out + (t - beg); + + for(; t < end; t += STRIDE, o += STRIDE) + *o = *t; + } + + template + static __device__ __forceinline__ void transform(InIt beg, InIt end, OutIt out, UnOp op) + { + int STRIDE = stride(); + InIt t = beg + flattenedThreadId(); + OutIt o = out + (t - beg); + + for(; t < end; t += STRIDE, o += STRIDE) + *o = op(*t); + } + + template + static __device__ __forceinline__ void transform(InIt1 beg1, InIt1 end1, InIt2 beg2, OutIt out, BinOp op) + { + int STRIDE = stride(); + InIt1 t1 = beg1 + flattenedThreadId(); + InIt2 t2 = beg2 + flattenedThreadId(); + OutIt o = out + (t1 - beg1); + + for(; t1 < end1; t1 += STRIDE, t2 += STRIDE, o += STRIDE) + *o = op(*t1, *t2); + } + + template + static __device__ __forceinline__ void reduce(volatile T* buffer, BinOp op) + { + int tid = flattenedThreadId(); + T val = buffer[tid]; + + if (CTA_SIZE >= 1024) { if (tid < 512) buffer[tid] = val = op(val, buffer[tid + 512]); __syncthreads(); } + if (CTA_SIZE >= 512) { if (tid < 256) buffer[tid] = val = op(val, buffer[tid + 256]); __syncthreads(); } + if (CTA_SIZE >= 256) { if (tid < 128) buffer[tid] = val = op(val, buffer[tid + 128]); __syncthreads(); } + if (CTA_SIZE >= 128) { if (tid < 64) buffer[tid] = val = op(val, buffer[tid + 64]); __syncthreads(); } + + if (tid < 32) + { + if (CTA_SIZE >= 64) { buffer[tid] = val = op(val, buffer[tid + 32]); } + if (CTA_SIZE >= 32) { buffer[tid] = val = op(val, buffer[tid + 16]); } + if (CTA_SIZE >= 16) { buffer[tid] = val = op(val, buffer[tid + 8]); } + if (CTA_SIZE >= 8) { buffer[tid] = val = op(val, buffer[tid + 4]); } + if (CTA_SIZE >= 4) { buffer[tid] = val = op(val, buffer[tid + 2]); } + if (CTA_SIZE >= 2) { buffer[tid] = val = op(val, buffer[tid + 1]); } + } + } + + template + static __device__ __forceinline__ T reduce(volatile T* buffer, T init, BinOp op) + { + int tid = flattenedThreadId(); + T val = buffer[tid] = init; + __syncthreads(); + + if (CTA_SIZE >= 1024) { if (tid < 512) buffer[tid] = val = op(val, buffer[tid + 512]); __syncthreads(); } + if (CTA_SIZE >= 512) { if (tid < 256) buffer[tid] = val = op(val, buffer[tid + 256]); __syncthreads(); } + if (CTA_SIZE >= 256) { if (tid < 128) buffer[tid] = val = op(val, buffer[tid + 128]); __syncthreads(); } + if (CTA_SIZE >= 128) { if (tid < 64) buffer[tid] = val = op(val, buffer[tid + 64]); __syncthreads(); } + + if (tid < 32) + { + if (CTA_SIZE >= 64) { buffer[tid] = val = op(val, buffer[tid + 32]); } + if (CTA_SIZE >= 32) { buffer[tid] = val = op(val, buffer[tid + 16]); } + if (CTA_SIZE >= 16) { buffer[tid] = val = op(val, buffer[tid + 8]); } + if (CTA_SIZE >= 8) { buffer[tid] = val = op(val, buffer[tid + 4]); } + if (CTA_SIZE >= 4) { buffer[tid] = val = op(val, buffer[tid + 2]); } + if (CTA_SIZE >= 2) { buffer[tid] = val = op(val, buffer[tid + 1]); } + } + __syncthreads(); + return buffer[0]; + } + + template + static __device__ __forceinline__ void reduce_n(T* data, unsigned int n, BinOp op) + { + int ftid = flattenedThreadId(); + int sft = stride(); + + if (sft < n) + { + for (unsigned int i = sft + ftid; i < n; i += sft) + data[ftid] = op(data[ftid], data[i]); + + __syncthreads(); + + n = sft; + } + + while (n > 1) + { + unsigned int half = n/2; + + if (ftid < half) + data[ftid] = op(data[ftid], data[n - ftid - 1]); + + __syncthreads(); + + n = n - half; + } + } + }; +}}} + +//! @endcond + +#endif /* OPENCV_CUDA_DEVICE_BLOCK_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/border_interpolate.hpp b/3rdparty/opencv/include/opencv2/core/cuda/border_interpolate.hpp new file mode 100644 index 00000000..874f705b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/border_interpolate.hpp @@ -0,0 +1,722 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_BORDER_INTERPOLATE_HPP +#define OPENCV_CUDA_BORDER_INTERPOLATE_HPP + +#include "saturate_cast.hpp" +#include "vec_traits.hpp" +#include "vec_math.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + ////////////////////////////////////////////////////////////// + // BrdConstant + + template struct BrdRowConstant + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdRowConstant(int width_, const D& val_ = VecTraits::all(0)) : width(width_), val(val_) {} + + template __device__ __forceinline__ D at_low(int x, const T* data) const + { + return x >= 0 ? saturate_cast(data[x]) : val; + } + + template __device__ __forceinline__ D at_high(int x, const T* data) const + { + return x < width ? saturate_cast(data[x]) : val; + } + + template __device__ __forceinline__ D at(int x, const T* data) const + { + return (x >= 0 && x < width) ? saturate_cast(data[x]) : val; + } + + int width; + D val; + }; + + template struct BrdColConstant + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdColConstant(int height_, const D& val_ = VecTraits::all(0)) : height(height_), val(val_) {} + + template __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const + { + return y >= 0 ? saturate_cast(*(const T*)((const char*)data + y * step)) : val; + } + + template __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const + { + return y < height ? saturate_cast(*(const T*)((const char*)data + y * step)) : val; + } + + template __device__ __forceinline__ D at(int y, const T* data, size_t step) const + { + return (y >= 0 && y < height) ? saturate_cast(*(const T*)((const char*)data + y * step)) : val; + } + + int height; + D val; + }; + + template struct BrdConstant + { + typedef D result_type; + + __host__ __device__ __forceinline__ BrdConstant(int height_, int width_, const D& val_ = VecTraits::all(0)) : height(height_), width(width_), val(val_) + { + } + + template __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const + { + return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast(((const T*)((const uchar*)data + y * step))[x]) : val; + } + + template __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const + { + return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast(src(y, x)) : val; + } + + int height; + int width; + D val; + }; + + ////////////////////////////////////////////////////////////// + // BrdReplicate + + template struct BrdRowReplicate + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdRowReplicate(int width) : last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdRowReplicate(int width, U) : last_col(width - 1) {} + + __device__ __forceinline__ int idx_col_low(int x) const + { + return ::max(x, 0); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return ::min(x, last_col); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_low(idx_col_high(x)); + } + + template __device__ __forceinline__ D at_low(int x, const T* data) const + { + return saturate_cast(data[idx_col_low(x)]); + } + + template __device__ __forceinline__ D at_high(int x, const T* data) const + { + return saturate_cast(data[idx_col_high(x)]); + } + + template __device__ __forceinline__ D at(int x, const T* data) const + { + return saturate_cast(data[idx_col(x)]); + } + + int last_col; + }; + + template struct BrdColReplicate + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdColReplicate(int height) : last_row(height - 1) {} + template __host__ __device__ __forceinline__ BrdColReplicate(int height, U) : last_row(height - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return ::max(y, 0); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return ::min(y, last_row); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_low(idx_row_high(y)); + } + + template __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const + { + return saturate_cast(*(const T*)((const char*)data + idx_row_low(y) * step)); + } + + template __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const + { + return saturate_cast(*(const T*)((const char*)data + idx_row_high(y) * step)); + } + + template __device__ __forceinline__ D at(int y, const T* data, size_t step) const + { + return saturate_cast(*(const T*)((const char*)data + idx_row(y) * step)); + } + + int last_row; + }; + + template struct BrdReplicate + { + typedef D result_type; + + __host__ __device__ __forceinline__ BrdReplicate(int height, int width) : last_row(height - 1), last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdReplicate(int height, int width, U) : last_row(height - 1), last_col(width - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return ::max(y, 0); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return ::min(y, last_row); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_low(idx_row_high(y)); + } + + __device__ __forceinline__ int idx_col_low(int x) const + { + return ::max(x, 0); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return ::min(x, last_col); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_low(idx_col_high(x)); + } + + template __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const + { + return saturate_cast(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]); + } + + template __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const + { + return saturate_cast(src(idx_row(y), idx_col(x))); + } + + int last_row; + int last_col; + }; + + ////////////////////////////////////////////////////////////// + // BrdReflect101 + + template struct BrdRowReflect101 + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdRowReflect101(int width) : last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdRowReflect101(int width, U) : last_col(width - 1) {} + + __device__ __forceinline__ int idx_col_low(int x) const + { + return ::abs(x) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return ::abs(last_col - ::abs(last_col - x)) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_low(idx_col_high(x)); + } + + template __device__ __forceinline__ D at_low(int x, const T* data) const + { + return saturate_cast(data[idx_col_low(x)]); + } + + template __device__ __forceinline__ D at_high(int x, const T* data) const + { + return saturate_cast(data[idx_col_high(x)]); + } + + template __device__ __forceinline__ D at(int x, const T* data) const + { + return saturate_cast(data[idx_col(x)]); + } + + int last_col; + }; + + template struct BrdColReflect101 + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdColReflect101(int height) : last_row(height - 1) {} + template __host__ __device__ __forceinline__ BrdColReflect101(int height, U) : last_row(height - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return ::abs(y) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return ::abs(last_row - ::abs(last_row - y)) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_low(idx_row_high(y)); + } + + template __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_low(y) * step)); + } + + template __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_high(y) * step)); + } + + template __device__ __forceinline__ D at(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row(y) * step)); + } + + int last_row; + }; + + template struct BrdReflect101 + { + typedef D result_type; + + __host__ __device__ __forceinline__ BrdReflect101(int height, int width) : last_row(height - 1), last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdReflect101(int height, int width, U) : last_row(height - 1), last_col(width - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return ::abs(y) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return ::abs(last_row - ::abs(last_row - y)) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_low(idx_row_high(y)); + } + + __device__ __forceinline__ int idx_col_low(int x) const + { + return ::abs(x) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return ::abs(last_col - ::abs(last_col - x)) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_low(idx_col_high(x)); + } + + template __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const + { + return saturate_cast(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]); + } + + template __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const + { + return saturate_cast(src(idx_row(y), idx_col(x))); + } + + int last_row; + int last_col; + }; + + ////////////////////////////////////////////////////////////// + // BrdReflect + + template struct BrdRowReflect + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdRowReflect(int width) : last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdRowReflect(int width, U) : last_col(width - 1) {} + + __device__ __forceinline__ int idx_col_low(int x) const + { + return (::abs(x) - (x < 0)) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return ::abs(last_col - ::abs(last_col - x) + (x > last_col)) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_high(::abs(x) - (x < 0)); + } + + template __device__ __forceinline__ D at_low(int x, const T* data) const + { + return saturate_cast(data[idx_col_low(x)]); + } + + template __device__ __forceinline__ D at_high(int x, const T* data) const + { + return saturate_cast(data[idx_col_high(x)]); + } + + template __device__ __forceinline__ D at(int x, const T* data) const + { + return saturate_cast(data[idx_col(x)]); + } + + int last_col; + }; + + template struct BrdColReflect + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdColReflect(int height) : last_row(height - 1) {} + template __host__ __device__ __forceinline__ BrdColReflect(int height, U) : last_row(height - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return (::abs(y) - (y < 0)) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return ::abs(last_row - ::abs(last_row - y) + (y > last_row)) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_high(::abs(y) - (y < 0)); + } + + template __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_low(y) * step)); + } + + template __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_high(y) * step)); + } + + template __device__ __forceinline__ D at(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row(y) * step)); + } + + int last_row; + }; + + template struct BrdReflect + { + typedef D result_type; + + __host__ __device__ __forceinline__ BrdReflect(int height, int width) : last_row(height - 1), last_col(width - 1) {} + template __host__ __device__ __forceinline__ BrdReflect(int height, int width, U) : last_row(height - 1), last_col(width - 1) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return (::abs(y) - (y < 0)) % (last_row + 1); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return /*::abs*/(last_row - ::abs(last_row - y) + (y > last_row)) /*% (last_row + 1)*/; + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_low(idx_row_high(y)); + } + + __device__ __forceinline__ int idx_col_low(int x) const + { + return (::abs(x) - (x < 0)) % (last_col + 1); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return (last_col - ::abs(last_col - x) + (x > last_col)); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_low(idx_col_high(x)); + } + + template __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const + { + return saturate_cast(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]); + } + + template __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const + { + return saturate_cast(src(idx_row(y), idx_col(x))); + } + + int last_row; + int last_col; + }; + + ////////////////////////////////////////////////////////////// + // BrdWrap + + template struct BrdRowWrap + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdRowWrap(int width_) : width(width_) {} + template __host__ __device__ __forceinline__ BrdRowWrap(int width_, U) : width(width_) {} + + __device__ __forceinline__ int idx_col_low(int x) const + { + return (x >= 0) * x + (x < 0) * (x - ((x - width + 1) / width) * width); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return (x < width) * x + (x >= width) * (x % width); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_high(idx_col_low(x)); + } + + template __device__ __forceinline__ D at_low(int x, const T* data) const + { + return saturate_cast(data[idx_col_low(x)]); + } + + template __device__ __forceinline__ D at_high(int x, const T* data) const + { + return saturate_cast(data[idx_col_high(x)]); + } + + template __device__ __forceinline__ D at(int x, const T* data) const + { + return saturate_cast(data[idx_col(x)]); + } + + int width; + }; + + template struct BrdColWrap + { + typedef D result_type; + + explicit __host__ __device__ __forceinline__ BrdColWrap(int height_) : height(height_) {} + template __host__ __device__ __forceinline__ BrdColWrap(int height_, U) : height(height_) {} + + __device__ __forceinline__ int idx_row_low(int y) const + { + return (y >= 0) * y + (y < 0) * (y - ((y - height + 1) / height) * height); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return (y < height) * y + (y >= height) * (y % height); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_high(idx_row_low(y)); + } + + template __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_low(y) * step)); + } + + template __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row_high(y) * step)); + } + + template __device__ __forceinline__ D at(int y, const T* data, size_t step) const + { + return saturate_cast(*(const D*)((const char*)data + idx_row(y) * step)); + } + + int height; + }; + + template struct BrdWrap + { + typedef D result_type; + + __host__ __device__ __forceinline__ BrdWrap(int height_, int width_) : + height(height_), width(width_) + { + } + template + __host__ __device__ __forceinline__ BrdWrap(int height_, int width_, U) : + height(height_), width(width_) + { + } + + __device__ __forceinline__ int idx_row_low(int y) const + { + return (y >= 0) ? y : (y - ((y - height + 1) / height) * height); + } + + __device__ __forceinline__ int idx_row_high(int y) const + { + return (y < height) ? y : (y % height); + } + + __device__ __forceinline__ int idx_row(int y) const + { + return idx_row_high(idx_row_low(y)); + } + + __device__ __forceinline__ int idx_col_low(int x) const + { + return (x >= 0) ? x : (x - ((x - width + 1) / width) * width); + } + + __device__ __forceinline__ int idx_col_high(int x) const + { + return (x < width) ? x : (x % width); + } + + __device__ __forceinline__ int idx_col(int x) const + { + return idx_col_high(idx_col_low(x)); + } + + template __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const + { + return saturate_cast(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]); + } + + template __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const + { + return saturate_cast(src(idx_row(y), idx_col(x))); + } + + int height; + int width; + }; + + ////////////////////////////////////////////////////////////// + // BorderReader + + template struct BorderReader + { + typedef typename B::result_type elem_type; + typedef typename Ptr2D::index_type index_type; + + __host__ __device__ __forceinline__ BorderReader(const Ptr2D& ptr_, const B& b_) : ptr(ptr_), b(b_) {} + + __device__ __forceinline__ elem_type operator ()(index_type y, index_type x) const + { + return b.at(y, x, ptr); + } + + Ptr2D ptr; + B b; + }; + + // under win32 there is some bug with templated types that passed as kernel parameters + // with this specialization all works fine + template struct BorderReader< Ptr2D, BrdConstant > + { + typedef typename BrdConstant::result_type elem_type; + typedef typename Ptr2D::index_type index_type; + + __host__ __device__ __forceinline__ BorderReader(const Ptr2D& src_, const BrdConstant& b) : + src(src_), height(b.height), width(b.width), val(b.val) + { + } + + __device__ __forceinline__ D operator ()(index_type y, index_type x) const + { + return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast(src(y, x)) : val; + } + + Ptr2D src; + int height; + int width; + D val; + }; +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_BORDER_INTERPOLATE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/color.hpp b/3rdparty/opencv/include/opencv2/core/cuda/color.hpp new file mode 100644 index 00000000..dcce2802 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/color.hpp @@ -0,0 +1,309 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_COLOR_HPP +#define OPENCV_CUDA_COLOR_HPP + +#include "detail/color_detail.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + // All OPENCV_CUDA_IMPLEMENT_*_TRAITS(ColorSpace1_to_ColorSpace2, ...) macros implements + // template class ColorSpace1_to_ColorSpace2_traits + // { + // typedef ... functor_type; + // static __host__ __device__ functor_type create_functor(); + // }; + + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_rgba, 4, 4, 2) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgr_to_bgr555, 3, 0, 5) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgr_to_bgr565, 3, 0, 6) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgb_to_bgr555, 3, 2, 5) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgb_to_bgr565, 3, 2, 6) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgra_to_bgr555, 4, 0, 5) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgra_to_bgr565, 4, 0, 6) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgba_to_bgr555, 4, 2, 5) + OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgba_to_bgr565, 4, 2, 6) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_rgb, 3, 2, 5) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_rgb, 3, 2, 6) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_bgr, 3, 0, 5) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_bgr, 3, 0, 6) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_rgba, 4, 2, 5) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_rgba, 4, 2, 6) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_bgra, 4, 0, 5) + OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_bgra, 4, 0, 6) + + #undef OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS(gray_to_bgr, 3) + OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS(gray_to_bgra, 4) + + #undef OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS(gray_to_bgr555, 5) + OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS(gray_to_bgr565, 6) + + #undef OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS(bgr555_to_gray, 5) + OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS(bgr565_to_gray, 6) + + #undef OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(rgb_to_gray, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(bgr_to_gray, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(rgba_to_gray, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(bgra_to_gray, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgb_to_yuv, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgba_to_yuv, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgb_to_yuv4, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgba_to_yuv4, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgr_to_yuv, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgra_to_yuv, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgr_to_yuv4, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgra_to_yuv4, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS + + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_rgba, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_bgr, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_bgra, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgb_to_YCrCb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgba_to_YCrCb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgb_to_YCrCb4, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgba_to_YCrCb4, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgr_to_YCrCb, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgra_to_YCrCb, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgr_to_YCrCb4, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgra_to_YCrCb4, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS + + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_rgba, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_bgr, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_bgra, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgb_to_xyz, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgba_to_xyz, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgb_to_xyz4, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgba_to_xyz4, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgr_to_xyz, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgra_to_xyz, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgr_to_xyz4, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgra_to_xyz4, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS + + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_rgba, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_bgr, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_bgra, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgb_to_hsv, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgba_to_hsv, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgb_to_hsv4, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgba_to_hsv4, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgr_to_hsv, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgra_to_hsv, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgr_to_hsv4, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgra_to_hsv4, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS + + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_rgba, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_bgr, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_bgra, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgb_to_hls, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgba_to_hls, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgb_to_hls4, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgba_to_hls4, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgr_to_hls, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgra_to_hls, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgr_to_hls4, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgra_to_hls4, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS + + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_rgb, 3, 3, 2) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_rgba, 3, 4, 2) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_rgb, 4, 3, 2) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_rgba, 4, 4, 2) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_bgr, 3, 3, 0) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_bgra, 3, 4, 0) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_bgr, 4, 3, 0) + OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_bgra, 4, 4, 0) + + #undef OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgb_to_lab, 3, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgba_to_lab, 4, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgb_to_lab4, 3, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgba_to_lab4, 4, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgr_to_lab, 3, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgra_to_lab, 4, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgr_to_lab4, 3, 4, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgra_to_lab4, 4, 4, true, 0) + + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgb_to_lab, 3, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgba_to_lab, 4, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgb_to_lab4, 3, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgba_to_lab4, 4, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgr_to_lab, 3, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgra_to_lab, 4, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgr_to_lab4, 3, 4, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgra_to_lab4, 4, 4, false, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS + + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_rgb, 3, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_rgb, 4, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_rgba, 3, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_rgba, 4, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_bgr, 3, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_bgr, 4, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_bgra, 3, 4, true, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_bgra, 4, 4, true, 0) + + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lrgb, 3, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lrgb, 4, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lrgba, 3, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lrgba, 4, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lbgr, 3, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lbgr, 4, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lbgra, 3, 4, false, 0) + OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lbgra, 4, 4, false, 0) + + #undef OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS + + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgb_to_luv, 3, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgba_to_luv, 4, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgb_to_luv4, 3, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgba_to_luv4, 4, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgr_to_luv, 3, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgra_to_luv, 4, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgr_to_luv4, 3, 4, true, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgra_to_luv4, 4, 4, true, 0) + + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgb_to_luv, 3, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgba_to_luv, 4, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgb_to_luv4, 3, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgba_to_luv4, 4, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgr_to_luv, 3, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgra_to_luv, 4, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgr_to_luv4, 3, 4, false, 0) + OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgra_to_luv4, 4, 4, false, 0) + + #undef OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS + + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_rgb, 3, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_rgb, 4, 3, true, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_rgba, 3, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_rgba, 4, 4, true, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_bgr, 3, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_bgr, 4, 3, true, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_bgra, 3, 4, true, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_bgra, 4, 4, true, 0) + + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lrgb, 3, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lrgb, 4, 3, false, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lrgba, 3, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lrgba, 4, 4, false, 2) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lbgr, 3, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lbgr, 4, 3, false, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lbgra, 3, 4, false, 0) + OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lbgra, 4, 4, false, 0) + + #undef OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_COLOR_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/common.hpp b/3rdparty/opencv/include/opencv2/core/cuda/common.hpp new file mode 100644 index 00000000..14b1f3f5 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/common.hpp @@ -0,0 +1,109 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_COMMON_HPP +#define OPENCV_CUDA_COMMON_HPP + +#include +#include "opencv2/core/cuda_types.hpp" +#include "opencv2/core/cvdef.h" +#include "opencv2/core/base.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +#ifndef CV_PI_F + #ifndef CV_PI + #define CV_PI_F 3.14159265f + #else + #define CV_PI_F ((float)CV_PI) + #endif +#endif + +namespace cv { namespace cuda { + static inline void checkCudaError(cudaError_t err, const char* file, const int line, const char* func) + { + if (cudaSuccess != err) + cv::error(cv::Error::GpuApiCallError, cudaGetErrorString(err), func, file, line); + } +}} + +#ifndef cudaSafeCall + #define cudaSafeCall(expr) cv::cuda::checkCudaError(expr, __FILE__, __LINE__, CV_Func) +#endif + +namespace cv { namespace cuda +{ + template static inline bool isAligned(const T* ptr, size_t size) + { + return reinterpret_cast(ptr) % size == 0; + } + + static inline bool isAligned(size_t step, size_t size) + { + return step % size == 0; + } +}} + +namespace cv { namespace cuda +{ + namespace device + { + __host__ __device__ __forceinline__ int divUp(int total, int grain) + { + return (total + grain - 1) / grain; + } + + template inline void bindTexture(const textureReference* tex, const PtrStepSz& img) + { + cudaChannelFormatDesc desc = cudaCreateChannelDesc(); + cudaSafeCall( cudaBindTexture2D(0, tex, img.ptr(), &desc, img.cols, img.rows, img.step) ); + } + } +}} + +//! @endcond + +#endif // OPENCV_CUDA_COMMON_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/datamov_utils.hpp b/3rdparty/opencv/include/opencv2/core/cuda/datamov_utils.hpp new file mode 100644 index 00000000..6820d0fd --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/datamov_utils.hpp @@ -0,0 +1,113 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_DATAMOV_UTILS_HPP +#define OPENCV_CUDA_DATAMOV_UTILS_HPP + +#include "common.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 200 + + // for Fermi memory space is detected automatically + template struct ForceGlob + { + __device__ __forceinline__ static void Load(const T* ptr, int offset, T& val) { val = ptr[offset]; } + }; + + #else // __CUDA_ARCH__ >= 200 + + #if defined(_WIN64) || defined(__LP64__) + // 64-bit register modifier for inlined asm + #define OPENCV_CUDA_ASM_PTR "l" + #else + // 32-bit register modifier for inlined asm + #define OPENCV_CUDA_ASM_PTR "r" + #endif + + template struct ForceGlob; + + #define OPENCV_CUDA_DEFINE_FORCE_GLOB(base_type, ptx_type, reg_mod) \ + template <> struct ForceGlob \ + { \ + __device__ __forceinline__ static void Load(const base_type* ptr, int offset, base_type& val) \ + { \ + asm("ld.global."#ptx_type" %0, [%1];" : "="#reg_mod(val) : OPENCV_CUDA_ASM_PTR(ptr + offset)); \ + } \ + }; + + #define OPENCV_CUDA_DEFINE_FORCE_GLOB_B(base_type, ptx_type) \ + template <> struct ForceGlob \ + { \ + __device__ __forceinline__ static void Load(const base_type* ptr, int offset, base_type& val) \ + { \ + asm("ld.global."#ptx_type" %0, [%1];" : "=r"(*reinterpret_cast(&val)) : OPENCV_CUDA_ASM_PTR(ptr + offset)); \ + } \ + }; + + OPENCV_CUDA_DEFINE_FORCE_GLOB_B(uchar, u8) + OPENCV_CUDA_DEFINE_FORCE_GLOB_B(schar, s8) + OPENCV_CUDA_DEFINE_FORCE_GLOB_B(char, b8) + OPENCV_CUDA_DEFINE_FORCE_GLOB (ushort, u16, h) + OPENCV_CUDA_DEFINE_FORCE_GLOB (short, s16, h) + OPENCV_CUDA_DEFINE_FORCE_GLOB (uint, u32, r) + OPENCV_CUDA_DEFINE_FORCE_GLOB (int, s32, r) + OPENCV_CUDA_DEFINE_FORCE_GLOB (float, f32, f) + OPENCV_CUDA_DEFINE_FORCE_GLOB (double, f64, d) + + #undef OPENCV_CUDA_DEFINE_FORCE_GLOB + #undef OPENCV_CUDA_DEFINE_FORCE_GLOB_B + #undef OPENCV_CUDA_ASM_PTR + + #endif // __CUDA_ARCH__ >= 200 +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_DATAMOV_UTILS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/color_detail.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/color_detail.hpp new file mode 100644 index 00000000..bfb40550 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/color_detail.hpp @@ -0,0 +1,1980 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_COLOR_DETAIL_HPP +#define OPENCV_CUDA_COLOR_DETAIL_HPP + +#include "../common.hpp" +#include "../vec_traits.hpp" +#include "../saturate_cast.hpp" +#include "../limits.hpp" +#include "../functional.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + #ifndef CV_DESCALE + #define CV_DESCALE(x, n) (((x) + (1 << ((n)-1))) >> (n)) + #endif + + namespace color_detail + { + template struct ColorChannel + { + typedef float worktype_f; + static __device__ __forceinline__ T max() { return numeric_limits::max(); } + static __device__ __forceinline__ T half() { return (T)(max()/2 + 1); } + }; + + template<> struct ColorChannel + { + typedef float worktype_f; + static __device__ __forceinline__ float max() { return 1.f; } + static __device__ __forceinline__ float half() { return 0.5f; } + }; + + template static __device__ __forceinline__ void setAlpha(typename TypeVec::vec_type& vec, T val) + { + } + + template static __device__ __forceinline__ void setAlpha(typename TypeVec::vec_type& vec, T val) + { + vec.w = val; + } + + template static __device__ __forceinline__ T getAlpha(const typename TypeVec::vec_type& vec) + { + return ColorChannel::max(); + } + + template static __device__ __forceinline__ T getAlpha(const typename TypeVec::vec_type& vec) + { + return vec.w; + } + + enum + { + yuv_shift = 14, + xyz_shift = 12, + R2Y = 4899, + G2Y = 9617, + B2Y = 1868, + BLOCK_SIZE = 256 + }; + } + +////////////////// Various 3/4-channel to 3/4-channel RGB transformations ///////////////// + + namespace color_detail + { + template struct RGB2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + dst.x = (&src.x)[bidx]; + dst.y = src.y; + dst.z = (&src.x)[bidx^2]; + setAlpha(dst, getAlpha(src)); + + return dst; + } + + __host__ __device__ __forceinline__ RGB2RGB() {} + __host__ __device__ __forceinline__ RGB2RGB(const RGB2RGB&) {} + }; + + template <> struct RGB2RGB : unary_function + { + __device__ uint operator()(uint src) const + { + uint dst = 0; + + dst |= (0xffu & (src >> 16)); + dst |= (0xffu & (src >> 8)) << 8; + dst |= (0xffu & (src)) << 16; + dst |= (0xffu & (src >> 24)) << 24; + + return dst; + } + + __host__ __device__ __forceinline__ RGB2RGB() {} + __host__ __device__ __forceinline__ RGB2RGB(const RGB2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +/////////// Transforming 16-bit (565 or 555) RGB to/from 24/32-bit (888[8]) RGB ////////// + + namespace color_detail + { + template struct RGB2RGB5x5Converter; + template struct RGB2RGB5x5Converter<6, bidx> + { + static __device__ __forceinline__ ushort cvt(const uchar3& src) + { + return (ushort)(((&src.x)[bidx] >> 3) | ((src.y & ~3) << 3) | (((&src.x)[bidx^2] & ~7) << 8)); + } + + static __device__ __forceinline__ ushort cvt(uint src) + { + uint b = 0xffu & (src >> (bidx * 8)); + uint g = 0xffu & (src >> 8); + uint r = 0xffu & (src >> ((bidx ^ 2) * 8)); + return (ushort)((b >> 3) | ((g & ~3) << 3) | ((r & ~7) << 8)); + } + }; + + template struct RGB2RGB5x5Converter<5, bidx> + { + static __device__ __forceinline__ ushort cvt(const uchar3& src) + { + return (ushort)(((&src.x)[bidx] >> 3) | ((src.y & ~7) << 2) | (((&src.x)[bidx^2] & ~7) << 7)); + } + + static __device__ __forceinline__ ushort cvt(uint src) + { + uint b = 0xffu & (src >> (bidx * 8)); + uint g = 0xffu & (src >> 8); + uint r = 0xffu & (src >> ((bidx ^ 2) * 8)); + uint a = 0xffu & (src >> 24); + return (ushort)((b >> 3) | ((g & ~7) << 2) | ((r & ~7) << 7) | (a * 0x8000)); + } + }; + + template struct RGB2RGB5x5; + + template struct RGB2RGB5x5<3, bidx,green_bits> : unary_function + { + __device__ __forceinline__ ushort operator()(const uchar3& src) const + { + return RGB2RGB5x5Converter::cvt(src); + } + + __host__ __device__ __forceinline__ RGB2RGB5x5() {} + __host__ __device__ __forceinline__ RGB2RGB5x5(const RGB2RGB5x5&) {} + }; + + template struct RGB2RGB5x5<4, bidx,green_bits> : unary_function + { + __device__ __forceinline__ ushort operator()(uint src) const + { + return RGB2RGB5x5Converter::cvt(src); + } + + __host__ __device__ __forceinline__ RGB2RGB5x5() {} + __host__ __device__ __forceinline__ RGB2RGB5x5(const RGB2RGB5x5&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(name, scn, bidx, green_bits) \ + struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2RGB5x5 functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + template struct RGB5x52RGBConverter; + + template struct RGB5x52RGBConverter<5, bidx> + { + static __device__ __forceinline__ void cvt(uint src, uchar3& dst) + { + (&dst.x)[bidx] = src << 3; + dst.y = (src >> 2) & ~7; + (&dst.x)[bidx ^ 2] = (src >> 7) & ~7; + } + + static __device__ __forceinline__ void cvt(uint src, uint& dst) + { + dst = 0; + + dst |= (0xffu & (src << 3)) << (bidx * 8); + dst |= (0xffu & ((src >> 2) & ~7)) << 8; + dst |= (0xffu & ((src >> 7) & ~7)) << ((bidx ^ 2) * 8); + dst |= ((src & 0x8000) * 0xffu) << 24; + } + }; + + template struct RGB5x52RGBConverter<6, bidx> + { + static __device__ __forceinline__ void cvt(uint src, uchar3& dst) + { + (&dst.x)[bidx] = src << 3; + dst.y = (src >> 3) & ~3; + (&dst.x)[bidx ^ 2] = (src >> 8) & ~7; + } + + static __device__ __forceinline__ void cvt(uint src, uint& dst) + { + dst = 0xffu << 24; + + dst |= (0xffu & (src << 3)) << (bidx * 8); + dst |= (0xffu &((src >> 3) & ~3)) << 8; + dst |= (0xffu & ((src >> 8) & ~7)) << ((bidx ^ 2) * 8); + } + }; + + template struct RGB5x52RGB; + + template struct RGB5x52RGB<3, bidx, green_bits> : unary_function + { + __device__ __forceinline__ uchar3 operator()(ushort src) const + { + uchar3 dst; + RGB5x52RGBConverter::cvt(src, dst); + return dst; + } + __host__ __device__ __forceinline__ RGB5x52RGB() {} + __host__ __device__ __forceinline__ RGB5x52RGB(const RGB5x52RGB&) {} + + }; + + template struct RGB5x52RGB<4, bidx, green_bits> : unary_function + { + __device__ __forceinline__ uint operator()(ushort src) const + { + uint dst; + RGB5x52RGBConverter::cvt(src, dst); + return dst; + } + __host__ __device__ __forceinline__ RGB5x52RGB() {} + __host__ __device__ __forceinline__ RGB5x52RGB(const RGB5x52RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(name, dcn, bidx, green_bits) \ + struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB5x52RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////// Grayscale to Color //////////////////////////////// + + namespace color_detail + { + template struct Gray2RGB : unary_function::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(T src) const + { + typename TypeVec::vec_type dst; + + dst.z = dst.y = dst.x = src; + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ Gray2RGB() {} + __host__ __device__ __forceinline__ Gray2RGB(const Gray2RGB&) {} + }; + + template <> struct Gray2RGB : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + uint dst = 0xffu << 24; + + dst |= src; + dst |= src << 8; + dst |= src << 16; + + return dst; + } + __host__ __device__ __forceinline__ Gray2RGB() {} + __host__ __device__ __forceinline__ Gray2RGB(const Gray2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS(name, dcn) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::Gray2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + template struct Gray2RGB5x5Converter; + template<> struct Gray2RGB5x5Converter<6> + { + static __device__ __forceinline__ ushort cvt(uint t) + { + return (ushort)((t >> 3) | ((t & ~3) << 3) | ((t & ~7) << 8)); + } + }; + + template<> struct Gray2RGB5x5Converter<5> + { + static __device__ __forceinline__ ushort cvt(uint t) + { + t >>= 3; + return (ushort)(t | (t << 5) | (t << 10)); + } + }; + + template struct Gray2RGB5x5 : unary_function + { + __device__ __forceinline__ ushort operator()(uint src) const + { + return Gray2RGB5x5Converter::cvt(src); + } + + __host__ __device__ __forceinline__ Gray2RGB5x5() {} + __host__ __device__ __forceinline__ Gray2RGB5x5(const Gray2RGB5x5&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS(name, green_bits) \ + struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::Gray2RGB5x5 functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////// Color to Grayscale //////////////////////////////// + + namespace color_detail + { + template struct RGB5x52GrayConverter; + template <> struct RGB5x52GrayConverter<6> + { + static __device__ __forceinline__ uchar cvt(uint t) + { + return (uchar)CV_DESCALE(((t << 3) & 0xf8) * B2Y + ((t >> 3) & 0xfc) * G2Y + ((t >> 8) & 0xf8) * R2Y, yuv_shift); + } + }; + + template <> struct RGB5x52GrayConverter<5> + { + static __device__ __forceinline__ uchar cvt(uint t) + { + return (uchar)CV_DESCALE(((t << 3) & 0xf8) * B2Y + ((t >> 2) & 0xf8) * G2Y + ((t >> 7) & 0xf8) * R2Y, yuv_shift); + } + }; + + template struct RGB5x52Gray : unary_function + { + __device__ __forceinline__ uchar operator()(uint src) const + { + return RGB5x52GrayConverter::cvt(src); + } + __host__ __device__ __forceinline__ RGB5x52Gray() {} + __host__ __device__ __forceinline__ RGB5x52Gray(const RGB5x52Gray&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS(name, green_bits) \ + struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB5x52Gray functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + template static __device__ __forceinline__ T RGB2GrayConvert(const T* src) + { + return (T)CV_DESCALE((unsigned)(src[bidx] * B2Y + src[1] * G2Y + src[bidx^2] * R2Y), yuv_shift); + } + + template static __device__ __forceinline__ uchar RGB2GrayConvert(uint src) + { + uint b = 0xffu & (src >> (bidx * 8)); + uint g = 0xffu & (src >> 8); + uint r = 0xffu & (src >> ((bidx ^ 2) * 8)); + return CV_DESCALE((uint)(b * B2Y + g * G2Y + r * R2Y), yuv_shift); + } + + template static __device__ __forceinline__ float RGB2GrayConvert(const float* src) + { + return src[bidx] * 0.114f + src[1] * 0.587f + src[bidx^2] * 0.299f; + } + + template struct RGB2Gray : unary_function::vec_type, T> + { + __device__ __forceinline__ T operator()(const typename TypeVec::vec_type& src) const + { + return RGB2GrayConvert(&src.x); + } + __host__ __device__ __forceinline__ RGB2Gray() {} + __host__ __device__ __forceinline__ RGB2Gray(const RGB2Gray&) {} + }; + + template struct RGB2Gray : unary_function + { + __device__ __forceinline__ uchar operator()(uint src) const + { + return RGB2GrayConvert(src); + } + __host__ __device__ __forceinline__ RGB2Gray() {} + __host__ __device__ __forceinline__ RGB2Gray(const RGB2Gray&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(name, scn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2Gray functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////////// RGB <-> YUV ////////////////////////////////////// + + namespace color_detail + { + __constant__ float c_RGB2YUVCoeffs_f[5] = { 0.114f, 0.587f, 0.299f, 0.492f, 0.877f }; + __constant__ int c_RGB2YUVCoeffs_i[5] = { B2Y, G2Y, R2Y, 8061, 14369 }; + + template static __device__ void RGB2YUVConvert(const T* src, D& dst) + { + const int delta = ColorChannel::half() * (1 << yuv_shift); + + const int Y = CV_DESCALE(src[0] * c_RGB2YUVCoeffs_i[bidx^2] + src[1] * c_RGB2YUVCoeffs_i[1] + src[2] * c_RGB2YUVCoeffs_i[bidx], yuv_shift); + const int Cr = CV_DESCALE((src[bidx^2] - Y) * c_RGB2YUVCoeffs_i[3] + delta, yuv_shift); + const int Cb = CV_DESCALE((src[bidx] - Y) * c_RGB2YUVCoeffs_i[4] + delta, yuv_shift); + + dst.x = saturate_cast(Y); + dst.y = saturate_cast(Cr); + dst.z = saturate_cast(Cb); + } + + template static __device__ __forceinline__ void RGB2YUVConvert(const float* src, D& dst) + { + dst.x = src[0] * c_RGB2YUVCoeffs_f[bidx^2] + src[1] * c_RGB2YUVCoeffs_f[1] + src[2] * c_RGB2YUVCoeffs_f[bidx]; + dst.y = (src[bidx^2] - dst.x) * c_RGB2YUVCoeffs_f[3] + ColorChannel::half(); + dst.z = (src[bidx] - dst.x) * c_RGB2YUVCoeffs_f[4] + ColorChannel::half(); + } + + template struct RGB2YUV + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + RGB2YUVConvert(&src.x, dst); + return dst; + } + __host__ __device__ __forceinline__ RGB2YUV() {} + __host__ __device__ __forceinline__ RGB2YUV(const RGB2YUV&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2YUV functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ float c_YUV2RGBCoeffs_f[5] = { 2.032f, -0.395f, -0.581f, 1.140f }; + __constant__ int c_YUV2RGBCoeffs_i[5] = { 33292, -6472, -9519, 18678 }; + + template static __device__ void YUV2RGBConvert(const T& src, D* dst) + { + const int b = src.x + CV_DESCALE((src.z - ColorChannel::half()) * c_YUV2RGBCoeffs_i[3], yuv_shift); + + const int g = src.x + CV_DESCALE((src.z - ColorChannel::half()) * c_YUV2RGBCoeffs_i[2] + + (src.y - ColorChannel::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift); + + const int r = src.x + CV_DESCALE((src.y - ColorChannel::half()) * c_YUV2RGBCoeffs_i[0], yuv_shift); + + dst[bidx] = saturate_cast(b); + dst[1] = saturate_cast(g); + dst[bidx^2] = saturate_cast(r); + } + + template static __device__ uint YUV2RGBConvert(uint src) + { + const int x = 0xff & (src); + const int y = 0xff & (src >> 8); + const int z = 0xff & (src >> 16); + + const int b = x + CV_DESCALE((z - ColorChannel::half()) * c_YUV2RGBCoeffs_i[3], yuv_shift); + + const int g = x + CV_DESCALE((z - ColorChannel::half()) * c_YUV2RGBCoeffs_i[2] + + (y - ColorChannel::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift); + + const int r = x + CV_DESCALE((y - ColorChannel::half()) * c_YUV2RGBCoeffs_i[0], yuv_shift); + + uint dst = 0xffu << 24; + + dst |= saturate_cast(b) << (bidx * 8); + dst |= saturate_cast(g) << 8; + dst |= saturate_cast(r) << ((bidx ^ 2) * 8); + + return dst; + } + + template static __device__ __forceinline__ void YUV2RGBConvert(const T& src, float* dst) + { + dst[bidx] = src.x + (src.z - ColorChannel::half()) * c_YUV2RGBCoeffs_f[3]; + + dst[1] = src.x + (src.z - ColorChannel::half()) * c_YUV2RGBCoeffs_f[2] + + (src.y - ColorChannel::half()) * c_YUV2RGBCoeffs_f[1]; + + dst[bidx^2] = src.x + (src.y - ColorChannel::half()) * c_YUV2RGBCoeffs_f[0]; + } + + template struct YUV2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + YUV2RGBConvert(src, &dst.x); + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ YUV2RGB() {} + __host__ __device__ __forceinline__ YUV2RGB(const YUV2RGB&) {} + }; + + template struct YUV2RGB : unary_function + { + __device__ __forceinline__ uint operator ()(uint src) const + { + return YUV2RGBConvert(src); + } + __host__ __device__ __forceinline__ YUV2RGB() {} + __host__ __device__ __forceinline__ YUV2RGB(const YUV2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::YUV2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////////// RGB <-> YCrCb ////////////////////////////////////// + + namespace color_detail + { + __constant__ float c_RGB2YCrCbCoeffs_f[5] = {0.299f, 0.587f, 0.114f, 0.713f, 0.564f}; + __constant__ int c_RGB2YCrCbCoeffs_i[5] = {R2Y, G2Y, B2Y, 11682, 9241}; + + template static __device__ void RGB2YCrCbConvert(const T* src, D& dst) + { + const int delta = ColorChannel::half() * (1 << yuv_shift); + + const int Y = CV_DESCALE(src[0] * c_RGB2YCrCbCoeffs_i[bidx^2] + src[1] * c_RGB2YCrCbCoeffs_i[1] + src[2] * c_RGB2YCrCbCoeffs_i[bidx], yuv_shift); + const int Cr = CV_DESCALE((src[bidx^2] - Y) * c_RGB2YCrCbCoeffs_i[3] + delta, yuv_shift); + const int Cb = CV_DESCALE((src[bidx] - Y) * c_RGB2YCrCbCoeffs_i[4] + delta, yuv_shift); + + dst.x = saturate_cast(Y); + dst.y = saturate_cast(Cr); + dst.z = saturate_cast(Cb); + } + + template static __device__ uint RGB2YCrCbConvert(uint src) + { + const int delta = ColorChannel::half() * (1 << yuv_shift); + + const int Y = CV_DESCALE((0xffu & src) * c_RGB2YCrCbCoeffs_i[bidx^2] + (0xffu & (src >> 8)) * c_RGB2YCrCbCoeffs_i[1] + (0xffu & (src >> 16)) * c_RGB2YCrCbCoeffs_i[bidx], yuv_shift); + const int Cr = CV_DESCALE(((0xffu & (src >> ((bidx ^ 2) * 8))) - Y) * c_RGB2YCrCbCoeffs_i[3] + delta, yuv_shift); + const int Cb = CV_DESCALE(((0xffu & (src >> (bidx * 8))) - Y) * c_RGB2YCrCbCoeffs_i[4] + delta, yuv_shift); + + uint dst = 0; + + dst |= saturate_cast(Y); + dst |= saturate_cast(Cr) << 8; + dst |= saturate_cast(Cb) << 16; + + return dst; + } + + template static __device__ __forceinline__ void RGB2YCrCbConvert(const float* src, D& dst) + { + dst.x = src[0] * c_RGB2YCrCbCoeffs_f[bidx^2] + src[1] * c_RGB2YCrCbCoeffs_f[1] + src[2] * c_RGB2YCrCbCoeffs_f[bidx]; + dst.y = (src[bidx^2] - dst.x) * c_RGB2YCrCbCoeffs_f[3] + ColorChannel::half(); + dst.z = (src[bidx] - dst.x) * c_RGB2YCrCbCoeffs_f[4] + ColorChannel::half(); + } + + template struct RGB2YCrCb + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + RGB2YCrCbConvert(&src.x, dst); + return dst; + } + __host__ __device__ __forceinline__ RGB2YCrCb() {} + __host__ __device__ __forceinline__ RGB2YCrCb(const RGB2YCrCb&) {} + }; + + template struct RGB2YCrCb : unary_function + { + __device__ __forceinline__ uint operator ()(uint src) const + { + return RGB2YCrCbConvert(src); + } + + __host__ __device__ __forceinline__ RGB2YCrCb() {} + __host__ __device__ __forceinline__ RGB2YCrCb(const RGB2YCrCb&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2YCrCb functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ float c_YCrCb2RGBCoeffs_f[5] = {1.403f, -0.714f, -0.344f, 1.773f}; + __constant__ int c_YCrCb2RGBCoeffs_i[5] = {22987, -11698, -5636, 29049}; + + template static __device__ void YCrCb2RGBConvert(const T& src, D* dst) + { + const int b = src.x + CV_DESCALE((src.z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[3], yuv_shift); + const int g = src.x + CV_DESCALE((src.z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[2] + (src.y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[1], yuv_shift); + const int r = src.x + CV_DESCALE((src.y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[0], yuv_shift); + + dst[bidx] = saturate_cast(b); + dst[1] = saturate_cast(g); + dst[bidx^2] = saturate_cast(r); + } + + template static __device__ uint YCrCb2RGBConvert(uint src) + { + const int x = 0xff & (src); + const int y = 0xff & (src >> 8); + const int z = 0xff & (src >> 16); + + const int b = x + CV_DESCALE((z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[3], yuv_shift); + const int g = x + CV_DESCALE((z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[2] + (y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[1], yuv_shift); + const int r = x + CV_DESCALE((y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_i[0], yuv_shift); + + uint dst = 0xffu << 24; + + dst |= saturate_cast(b) << (bidx * 8); + dst |= saturate_cast(g) << 8; + dst |= saturate_cast(r) << ((bidx ^ 2) * 8); + + return dst; + } + + template __device__ __forceinline__ void YCrCb2RGBConvert(const T& src, float* dst) + { + dst[bidx] = src.x + (src.z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_f[3]; + dst[1] = src.x + (src.z - ColorChannel::half()) * c_YCrCb2RGBCoeffs_f[2] + (src.y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_f[1]; + dst[bidx^2] = src.x + (src.y - ColorChannel::half()) * c_YCrCb2RGBCoeffs_f[0]; + } + + template struct YCrCb2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + YCrCb2RGBConvert(src, &dst.x); + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ YCrCb2RGB() {} + __host__ __device__ __forceinline__ YCrCb2RGB(const YCrCb2RGB&) {} + }; + + template struct YCrCb2RGB : unary_function + { + __device__ __forceinline__ uint operator ()(uint src) const + { + return YCrCb2RGBConvert(src); + } + __host__ __device__ __forceinline__ YCrCb2RGB() {} + __host__ __device__ __forceinline__ YCrCb2RGB(const YCrCb2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::YCrCb2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +////////////////////////////////////// RGB <-> XYZ /////////////////////////////////////// + + namespace color_detail + { + __constant__ float c_RGB2XYZ_D65f[9] = { 0.412453f, 0.357580f, 0.180423f, 0.212671f, 0.715160f, 0.072169f, 0.019334f, 0.119193f, 0.950227f }; + __constant__ int c_RGB2XYZ_D65i[9] = { 1689, 1465, 739, 871, 2929, 296, 79, 488, 3892 }; + + template static __device__ __forceinline__ void RGB2XYZConvert(const T* src, D& dst) + { + dst.z = saturate_cast(CV_DESCALE(src[bidx^2] * c_RGB2XYZ_D65i[6] + src[1] * c_RGB2XYZ_D65i[7] + src[bidx] * c_RGB2XYZ_D65i[8], xyz_shift)); + dst.x = saturate_cast(CV_DESCALE(src[bidx^2] * c_RGB2XYZ_D65i[0] + src[1] * c_RGB2XYZ_D65i[1] + src[bidx] * c_RGB2XYZ_D65i[2], xyz_shift)); + dst.y = saturate_cast(CV_DESCALE(src[bidx^2] * c_RGB2XYZ_D65i[3] + src[1] * c_RGB2XYZ_D65i[4] + src[bidx] * c_RGB2XYZ_D65i[5], xyz_shift)); + } + + template static __device__ __forceinline__ uint RGB2XYZConvert(uint src) + { + const uint b = 0xffu & (src >> (bidx * 8)); + const uint g = 0xffu & (src >> 8); + const uint r = 0xffu & (src >> ((bidx ^ 2) * 8)); + + const uint x = saturate_cast(CV_DESCALE(r * c_RGB2XYZ_D65i[0] + g * c_RGB2XYZ_D65i[1] + b * c_RGB2XYZ_D65i[2], xyz_shift)); + const uint y = saturate_cast(CV_DESCALE(r * c_RGB2XYZ_D65i[3] + g * c_RGB2XYZ_D65i[4] + b * c_RGB2XYZ_D65i[5], xyz_shift)); + const uint z = saturate_cast(CV_DESCALE(r * c_RGB2XYZ_D65i[6] + g * c_RGB2XYZ_D65i[7] + b * c_RGB2XYZ_D65i[8], xyz_shift)); + + uint dst = 0; + + dst |= x; + dst |= y << 8; + dst |= z << 16; + + return dst; + } + + template static __device__ __forceinline__ void RGB2XYZConvert(const float* src, D& dst) + { + dst.x = src[bidx^2] * c_RGB2XYZ_D65f[0] + src[1] * c_RGB2XYZ_D65f[1] + src[bidx] * c_RGB2XYZ_D65f[2]; + dst.y = src[bidx^2] * c_RGB2XYZ_D65f[3] + src[1] * c_RGB2XYZ_D65f[4] + src[bidx] * c_RGB2XYZ_D65f[5]; + dst.z = src[bidx^2] * c_RGB2XYZ_D65f[6] + src[1] * c_RGB2XYZ_D65f[7] + src[bidx] * c_RGB2XYZ_D65f[8]; + } + + template struct RGB2XYZ + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2XYZConvert(&src.x, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2XYZ() {} + __host__ __device__ __forceinline__ RGB2XYZ(const RGB2XYZ&) {} + }; + + template struct RGB2XYZ : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return RGB2XYZConvert(src); + } + __host__ __device__ __forceinline__ RGB2XYZ() {} + __host__ __device__ __forceinline__ RGB2XYZ(const RGB2XYZ&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2XYZ functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ float c_XYZ2sRGB_D65f[9] = { 3.240479f, -1.53715f, -0.498535f, -0.969256f, 1.875991f, 0.041556f, 0.055648f, -0.204043f, 1.057311f }; + __constant__ int c_XYZ2sRGB_D65i[9] = { 13273, -6296, -2042, -3970, 7684, 170, 228, -836, 4331 }; + + template static __device__ __forceinline__ void XYZ2RGBConvert(const T& src, D* dst) + { + dst[bidx^2] = saturate_cast(CV_DESCALE(src.x * c_XYZ2sRGB_D65i[0] + src.y * c_XYZ2sRGB_D65i[1] + src.z * c_XYZ2sRGB_D65i[2], xyz_shift)); + dst[1] = saturate_cast(CV_DESCALE(src.x * c_XYZ2sRGB_D65i[3] + src.y * c_XYZ2sRGB_D65i[4] + src.z * c_XYZ2sRGB_D65i[5], xyz_shift)); + dst[bidx] = saturate_cast(CV_DESCALE(src.x * c_XYZ2sRGB_D65i[6] + src.y * c_XYZ2sRGB_D65i[7] + src.z * c_XYZ2sRGB_D65i[8], xyz_shift)); + } + + template static __device__ __forceinline__ uint XYZ2RGBConvert(uint src) + { + const int x = 0xff & src; + const int y = 0xff & (src >> 8); + const int z = 0xff & (src >> 16); + + const uint r = saturate_cast(CV_DESCALE(x * c_XYZ2sRGB_D65i[0] + y * c_XYZ2sRGB_D65i[1] + z * c_XYZ2sRGB_D65i[2], xyz_shift)); + const uint g = saturate_cast(CV_DESCALE(x * c_XYZ2sRGB_D65i[3] + y * c_XYZ2sRGB_D65i[4] + z * c_XYZ2sRGB_D65i[5], xyz_shift)); + const uint b = saturate_cast(CV_DESCALE(x * c_XYZ2sRGB_D65i[6] + y * c_XYZ2sRGB_D65i[7] + z * c_XYZ2sRGB_D65i[8], xyz_shift)); + + uint dst = 0xffu << 24; + + dst |= b << (bidx * 8); + dst |= g << 8; + dst |= r << ((bidx ^ 2) * 8); + + return dst; + } + + template static __device__ __forceinline__ void XYZ2RGBConvert(const T& src, float* dst) + { + dst[bidx^2] = src.x * c_XYZ2sRGB_D65f[0] + src.y * c_XYZ2sRGB_D65f[1] + src.z * c_XYZ2sRGB_D65f[2]; + dst[1] = src.x * c_XYZ2sRGB_D65f[3] + src.y * c_XYZ2sRGB_D65f[4] + src.z * c_XYZ2sRGB_D65f[5]; + dst[bidx] = src.x * c_XYZ2sRGB_D65f[6] + src.y * c_XYZ2sRGB_D65f[7] + src.z * c_XYZ2sRGB_D65f[8]; + } + + template struct XYZ2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + XYZ2RGBConvert(src, &dst.x); + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ XYZ2RGB() {} + __host__ __device__ __forceinline__ XYZ2RGB(const XYZ2RGB&) {} + }; + + template struct XYZ2RGB : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return XYZ2RGBConvert(src); + } + __host__ __device__ __forceinline__ XYZ2RGB() {} + __host__ __device__ __forceinline__ XYZ2RGB(const XYZ2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::XYZ2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +////////////////////////////////////// RGB <-> HSV /////////////////////////////////////// + + namespace color_detail + { + __constant__ int c_HsvDivTable [256] = {0, 1044480, 522240, 348160, 261120, 208896, 174080, 149211, 130560, 116053, 104448, 94953, 87040, 80345, 74606, 69632, 65280, 61440, 58027, 54973, 52224, 49737, 47476, 45412, 43520, 41779, 40172, 38684, 37303, 36017, 34816, 33693, 32640, 31651, 30720, 29842, 29013, 28229, 27486, 26782, 26112, 25475, 24869, 24290, 23738, 23211, 22706, 22223, 21760, 21316, 20890, 20480, 20086, 19707, 19342, 18991, 18651, 18324, 18008, 17703, 17408, 17123, 16846, 16579, 16320, 16069, 15825, 15589, 15360, 15137, 14921, 14711, 14507, 14308, 14115, 13926, 13743, 13565, 13391, 13221, 13056, 12895, 12738, 12584, 12434, 12288, 12145, 12006, 11869, 11736, 11605, 11478, 11353, 11231, 11111, 10995, 10880, 10768, 10658, 10550, 10445, 10341, 10240, 10141, 10043, 9947, 9854, 9761, 9671, 9582, 9495, 9410, 9326, 9243, 9162, 9082, 9004, 8927, 8852, 8777, 8704, 8632, 8561, 8492, 8423, 8356, 8290, 8224, 8160, 8097, 8034, 7973, 7913, 7853, 7795, 7737, 7680, 7624, 7569, 7514, 7461, 7408, 7355, 7304, 7253, 7203, 7154, 7105, 7057, 7010, 6963, 6917, 6872, 6827, 6782, 6739, 6695, 6653, 6611, 6569, 6528, 6487, 6447, 6408, 6369, 6330, 6292, 6254, 6217, 6180, 6144, 6108, 6073, 6037, 6003, 5968, 5935, 5901, 5868, 5835, 5803, 5771, 5739, 5708, 5677, 5646, 5615, 5585, 5556, 5526, 5497, 5468, 5440, 5412, 5384, 5356, 5329, 5302, 5275, 5249, 5222, 5196, 5171, 5145, 5120, 5095, 5070, 5046, 5022, 4998, 4974, 4950, 4927, 4904, 4881, 4858, 4836, 4813, 4791, 4769, 4748, 4726, 4705, 4684, 4663, 4642, 4622, 4601, 4581, 4561, 4541, 4522, 4502, 4483, 4464, 4445, 4426, 4407, 4389, 4370, 4352, 4334, 4316, 4298, 4281, 4263, 4246, 4229, 4212, 4195, 4178, 4161, 4145, 4128, 4112, 4096}; + __constant__ int c_HsvDivTable180[256] = {0, 122880, 61440, 40960, 30720, 24576, 20480, 17554, 15360, 13653, 12288, 11171, 10240, 9452, 8777, 8192, 7680, 7228, 6827, 6467, 6144, 5851, 5585, 5343, 5120, 4915, 4726, 4551, 4389, 4237, 4096, 3964, 3840, 3724, 3614, 3511, 3413, 3321, 3234, 3151, 3072, 2997, 2926, 2858, 2793, 2731, 2671, 2614, 2560, 2508, 2458, 2409, 2363, 2318, 2276, 2234, 2194, 2156, 2119, 2083, 2048, 2014, 1982, 1950, 1920, 1890, 1862, 1834, 1807, 1781, 1755, 1731, 1707, 1683, 1661, 1638, 1617, 1596, 1575, 1555, 1536, 1517, 1499, 1480, 1463, 1446, 1429, 1412, 1396, 1381, 1365, 1350, 1336, 1321, 1307, 1293, 1280, 1267, 1254, 1241, 1229, 1217, 1205, 1193, 1182, 1170, 1159, 1148, 1138, 1127, 1117, 1107, 1097, 1087, 1078, 1069, 1059, 1050, 1041, 1033, 1024, 1016, 1007, 999, 991, 983, 975, 968, 960, 953, 945, 938, 931, 924, 917, 910, 904, 897, 890, 884, 878, 871, 865, 859, 853, 847, 842, 836, 830, 825, 819, 814, 808, 803, 798, 793, 788, 783, 778, 773, 768, 763, 759, 754, 749, 745, 740, 736, 731, 727, 723, 719, 714, 710, 706, 702, 698, 694, 690, 686, 683, 679, 675, 671, 668, 664, 661, 657, 654, 650, 647, 643, 640, 637, 633, 630, 627, 624, 621, 617, 614, 611, 608, 605, 602, 599, 597, 594, 591, 588, 585, 582, 580, 577, 574, 572, 569, 566, 564, 561, 559, 556, 554, 551, 549, 546, 544, 541, 539, 537, 534, 532, 530, 527, 525, 523, 521, 518, 516, 514, 512, 510, 508, 506, 504, 502, 500, 497, 495, 493, 492, 490, 488, 486, 484, 482}; + __constant__ int c_HsvDivTable256[256] = {0, 174763, 87381, 58254, 43691, 34953, 29127, 24966, 21845, 19418, 17476, 15888, 14564, 13443, 12483, 11651, 10923, 10280, 9709, 9198, 8738, 8322, 7944, 7598, 7282, 6991, 6722, 6473, 6242, 6026, 5825, 5638, 5461, 5296, 5140, 4993, 4855, 4723, 4599, 4481, 4369, 4263, 4161, 4064, 3972, 3884, 3799, 3718, 3641, 3567, 3495, 3427, 3361, 3297, 3236, 3178, 3121, 3066, 3013, 2962, 2913, 2865, 2819, 2774, 2731, 2689, 2648, 2608, 2570, 2533, 2497, 2461, 2427, 2394, 2362, 2330, 2300, 2270, 2241, 2212, 2185, 2158, 2131, 2106, 2081, 2056, 2032, 2009, 1986, 1964, 1942, 1920, 1900, 1879, 1859, 1840, 1820, 1802, 1783, 1765, 1748, 1730, 1713, 1697, 1680, 1664, 1649, 1633, 1618, 1603, 1589, 1574, 1560, 1547, 1533, 1520, 1507, 1494, 1481, 1469, 1456, 1444, 1432, 1421, 1409, 1398, 1387, 1376, 1365, 1355, 1344, 1334, 1324, 1314, 1304, 1295, 1285, 1276, 1266, 1257, 1248, 1239, 1231, 1222, 1214, 1205, 1197, 1189, 1181, 1173, 1165, 1157, 1150, 1142, 1135, 1128, 1120, 1113, 1106, 1099, 1092, 1085, 1079, 1072, 1066, 1059, 1053, 1046, 1040, 1034, 1028, 1022, 1016, 1010, 1004, 999, 993, 987, 982, 976, 971, 966, 960, 955, 950, 945, 940, 935, 930, 925, 920, 915, 910, 906, 901, 896, 892, 887, 883, 878, 874, 869, 865, 861, 857, 853, 848, 844, 840, 836, 832, 828, 824, 820, 817, 813, 809, 805, 802, 798, 794, 791, 787, 784, 780, 777, 773, 770, 767, 763, 760, 757, 753, 750, 747, 744, 741, 737, 734, 731, 728, 725, 722, 719, 716, 713, 710, 708, 705, 702, 699, 696, 694, 691, 688, 685}; + + template static __device__ void RGB2HSVConvert(const uchar* src, D& dst) + { + const int hsv_shift = 12; + const int* hdiv_table = hr == 180 ? c_HsvDivTable180 : c_HsvDivTable256; + + int b = src[bidx], g = src[1], r = src[bidx^2]; + int h, s, v = b; + int vmin = b, diff; + int vr, vg; + + v = ::max(v, g); + v = ::max(v, r); + vmin = ::min(vmin, g); + vmin = ::min(vmin, r); + + diff = v - vmin; + vr = (v == r) * -1; + vg = (v == g) * -1; + + s = (diff * c_HsvDivTable[v] + (1 << (hsv_shift-1))) >> hsv_shift; + h = (vr & (g - b)) + (~vr & ((vg & (b - r + 2 * diff)) + ((~vg) & (r - g + 4 * diff)))); + h = (h * hdiv_table[diff] + (1 << (hsv_shift-1))) >> hsv_shift; + h += (h < 0) * hr; + + dst.x = saturate_cast(h); + dst.y = (uchar)s; + dst.z = (uchar)v; + } + + template static __device__ uint RGB2HSVConvert(uint src) + { + const int hsv_shift = 12; + const int* hdiv_table = hr == 180 ? c_HsvDivTable180 : c_HsvDivTable256; + + const int b = 0xff & (src >> (bidx * 8)); + const int g = 0xff & (src >> 8); + const int r = 0xff & (src >> ((bidx ^ 2) * 8)); + + int h, s, v = b; + int vmin = b, diff; + int vr, vg; + + v = ::max(v, g); + v = ::max(v, r); + vmin = ::min(vmin, g); + vmin = ::min(vmin, r); + + diff = v - vmin; + vr = (v == r) * -1; + vg = (v == g) * -1; + + s = (diff * c_HsvDivTable[v] + (1 << (hsv_shift-1))) >> hsv_shift; + h = (vr & (g - b)) + (~vr & ((vg & (b - r + 2 * diff)) + ((~vg) & (r - g + 4 * diff)))); + h = (h * hdiv_table[diff] + (1 << (hsv_shift-1))) >> hsv_shift; + h += (h < 0) * hr; + + uint dst = 0; + + dst |= saturate_cast(h); + dst |= (0xffu & s) << 8; + dst |= (0xffu & v) << 16; + + return dst; + } + + template static __device__ void RGB2HSVConvert(const float* src, D& dst) + { + const float hscale = hr * (1.f / 360.f); + + float b = src[bidx], g = src[1], r = src[bidx^2]; + float h, s, v; + + float vmin, diff; + + v = vmin = r; + v = fmax(v, g); + v = fmax(v, b); + vmin = fmin(vmin, g); + vmin = fmin(vmin, b); + + diff = v - vmin; + s = diff / (float)(::fabs(v) + numeric_limits::epsilon()); + diff = (float)(60. / (diff + numeric_limits::epsilon())); + + h = (v == r) * (g - b) * diff; + h += (v != r && v == g) * ((b - r) * diff + 120.f); + h += (v != r && v != g) * ((r - g) * diff + 240.f); + h += (h < 0) * 360.f; + + dst.x = h * hscale; + dst.y = s; + dst.z = v; + } + + template struct RGB2HSV + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2HSVConvert(&src.x, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2HSV() {} + __host__ __device__ __forceinline__ RGB2HSV(const RGB2HSV&) {} + }; + + template struct RGB2HSV : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return RGB2HSVConvert(src); + } + __host__ __device__ __forceinline__ RGB2HSV() {} + __host__ __device__ __forceinline__ RGB2HSV(const RGB2HSV&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HSV functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HSV functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HSV functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HSV functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ int c_HsvSectorData[6][3] = { {1,3,0}, {1,0,2}, {3,0,1}, {0,2,1}, {0,1,3}, {2,1,0} }; + + template static __device__ void HSV2RGBConvert(const T& src, float* dst) + { + const float hscale = 6.f / hr; + + float h = src.x, s = src.y, v = src.z; + float b = v, g = v, r = v; + + if (s != 0) + { + h *= hscale; + + if( h < 0 ) + do h += 6; while( h < 0 ); + else if( h >= 6 ) + do h -= 6; while( h >= 6 ); + + int sector = __float2int_rd(h); + h -= sector; + + if ( (unsigned)sector >= 6u ) + { + sector = 0; + h = 0.f; + } + + float tab[4]; + tab[0] = v; + tab[1] = v * (1.f - s); + tab[2] = v * (1.f - s * h); + tab[3] = v * (1.f - s * (1.f - h)); + + b = tab[c_HsvSectorData[sector][0]]; + g = tab[c_HsvSectorData[sector][1]]; + r = tab[c_HsvSectorData[sector][2]]; + } + + dst[bidx] = b; + dst[1] = g; + dst[bidx^2] = r; + } + + template static __device__ void HSV2RGBConvert(const T& src, uchar* dst) + { + float3 buf; + + buf.x = src.x; + buf.y = src.y * (1.f / 255.f); + buf.z = src.z * (1.f / 255.f); + + HSV2RGBConvert(buf, &buf.x); + + dst[0] = saturate_cast(buf.x * 255.f); + dst[1] = saturate_cast(buf.y * 255.f); + dst[2] = saturate_cast(buf.z * 255.f); + } + + template static __device__ uint HSV2RGBConvert(uint src) + { + float3 buf; + + buf.x = src & 0xff; + buf.y = ((src >> 8) & 0xff) * (1.f/255.f); + buf.z = ((src >> 16) & 0xff) * (1.f/255.f); + + HSV2RGBConvert(buf, &buf.x); + + uint dst = 0xffu << 24; + + dst |= saturate_cast(buf.x * 255.f); + dst |= saturate_cast(buf.y * 255.f) << 8; + dst |= saturate_cast(buf.z * 255.f) << 16; + + return dst; + } + + template struct HSV2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + HSV2RGBConvert(src, &dst.x); + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ HSV2RGB() {} + __host__ __device__ __forceinline__ HSV2RGB(const HSV2RGB&) {} + }; + + template struct HSV2RGB : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return HSV2RGBConvert(src); + } + __host__ __device__ __forceinline__ HSV2RGB() {} + __host__ __device__ __forceinline__ HSV2RGB(const HSV2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::HSV2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::HSV2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::HSV2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::HSV2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +/////////////////////////////////////// RGB <-> HLS //////////////////////////////////////// + + namespace color_detail + { + template static __device__ void RGB2HLSConvert(const float* src, D& dst) + { + const float hscale = hr * (1.f / 360.f); + + float b = src[bidx], g = src[1], r = src[bidx^2]; + float h = 0.f, s = 0.f, l; + float vmin, vmax, diff; + + vmax = vmin = r; + vmax = fmax(vmax, g); + vmax = fmax(vmax, b); + vmin = fmin(vmin, g); + vmin = fmin(vmin, b); + + diff = vmax - vmin; + l = (vmax + vmin) * 0.5f; + + if (diff > numeric_limits::epsilon()) + { + s = (l < 0.5f) * diff / (vmax + vmin); + s += (l >= 0.5f) * diff / (2.0f - vmax - vmin); + + diff = 60.f / diff; + + h = (vmax == r) * (g - b) * diff; + h += (vmax != r && vmax == g) * ((b - r) * diff + 120.f); + h += (vmax != r && vmax != g) * ((r - g) * diff + 240.f); + h += (h < 0.f) * 360.f; + } + + dst.x = h * hscale; + dst.y = l; + dst.z = s; + } + + template static __device__ void RGB2HLSConvert(const uchar* src, D& dst) + { + float3 buf; + + buf.x = src[0] * (1.f / 255.f); + buf.y = src[1] * (1.f / 255.f); + buf.z = src[2] * (1.f / 255.f); + + RGB2HLSConvert(&buf.x, buf); + + dst.x = saturate_cast(buf.x); + dst.y = saturate_cast(buf.y*255.f); + dst.z = saturate_cast(buf.z*255.f); + } + + template static __device__ uint RGB2HLSConvert(uint src) + { + float3 buf; + + buf.x = (0xff & src) * (1.f / 255.f); + buf.y = (0xff & (src >> 8)) * (1.f / 255.f); + buf.z = (0xff & (src >> 16)) * (1.f / 255.f); + + RGB2HLSConvert(&buf.x, buf); + + uint dst = 0xffu << 24; + + dst |= saturate_cast(buf.x); + dst |= saturate_cast(buf.y * 255.f) << 8; + dst |= saturate_cast(buf.z * 255.f) << 16; + + return dst; + } + + template struct RGB2HLS + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2HLSConvert(&src.x, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2HLS() {} + __host__ __device__ __forceinline__ RGB2HLS(const RGB2HLS&) {} + }; + + template struct RGB2HLS : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return RGB2HLSConvert(src); + } + __host__ __device__ __forceinline__ RGB2HLS() {} + __host__ __device__ __forceinline__ RGB2HLS(const RGB2HLS&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HLS functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HLS functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HLS functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2HLS functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ int c_HlsSectorData[6][3] = { {1,3,0}, {1,0,2}, {3,0,1}, {0,2,1}, {0,1,3}, {2,1,0} }; + + template static __device__ void HLS2RGBConvert(const T& src, float* dst) + { + const float hscale = 6.0f / hr; + + float h = src.x, l = src.y, s = src.z; + float b = l, g = l, r = l; + + if (s != 0) + { + float p2 = (l <= 0.5f) * l * (1 + s); + p2 += (l > 0.5f) * (l + s - l * s); + float p1 = 2 * l - p2; + + h *= hscale; + + if( h < 0 ) + do h += 6; while( h < 0 ); + else if( h >= 6 ) + do h -= 6; while( h >= 6 ); + + int sector; + sector = __float2int_rd(h); + + h -= sector; + + float tab[4]; + tab[0] = p2; + tab[1] = p1; + tab[2] = p1 + (p2 - p1) * (1 - h); + tab[3] = p1 + (p2 - p1) * h; + + b = tab[c_HlsSectorData[sector][0]]; + g = tab[c_HlsSectorData[sector][1]]; + r = tab[c_HlsSectorData[sector][2]]; + } + + dst[bidx] = b; + dst[1] = g; + dst[bidx^2] = r; + } + + template static __device__ void HLS2RGBConvert(const T& src, uchar* dst) + { + float3 buf; + + buf.x = src.x; + buf.y = src.y * (1.f / 255.f); + buf.z = src.z * (1.f / 255.f); + + HLS2RGBConvert(buf, &buf.x); + + dst[0] = saturate_cast(buf.x * 255.f); + dst[1] = saturate_cast(buf.y * 255.f); + dst[2] = saturate_cast(buf.z * 255.f); + } + + template static __device__ uint HLS2RGBConvert(uint src) + { + float3 buf; + + buf.x = 0xff & src; + buf.y = (0xff & (src >> 8)) * (1.f / 255.f); + buf.z = (0xff & (src >> 16)) * (1.f / 255.f); + + HLS2RGBConvert(buf, &buf.x); + + uint dst = 0xffu << 24; + + dst |= saturate_cast(buf.x * 255.f); + dst |= saturate_cast(buf.y * 255.f) << 8; + dst |= saturate_cast(buf.z * 255.f) << 16; + + return dst; + } + + template struct HLS2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + HLS2RGBConvert(src, &dst.x); + setAlpha(dst, ColorChannel::max()); + + return dst; + } + __host__ __device__ __forceinline__ HLS2RGB() {} + __host__ __device__ __forceinline__ HLS2RGB(const HLS2RGB&) {} + }; + + template struct HLS2RGB : unary_function + { + __device__ __forceinline__ uint operator()(uint src) const + { + return HLS2RGBConvert(src); + } + __host__ __device__ __forceinline__ HLS2RGB() {} + __host__ __device__ __forceinline__ HLS2RGB(const HLS2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(name, scn, dcn, bidx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::HLS2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::HLS2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::HLS2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; \ + template <> struct name ## _full_traits \ + { \ + typedef ::cv::cuda::device::color_detail::HLS2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////////// RGB <-> Lab ///////////////////////////////////// + + namespace color_detail + { + enum + { + LAB_CBRT_TAB_SIZE = 1024, + GAMMA_TAB_SIZE = 1024, + lab_shift = xyz_shift, + gamma_shift = 3, + lab_shift2 = (lab_shift + gamma_shift), + LAB_CBRT_TAB_SIZE_B = (256 * 3 / 2 * (1 << gamma_shift)) + }; + + __constant__ ushort c_sRGBGammaTab_b[] = {0,1,1,2,2,3,4,4,5,6,6,7,8,8,9,10,11,11,12,13,14,15,16,17,19,20,21,22,24,25,26,28,29,31,33,34,36,38,40,41,43,45,47,49,51,54,56,58,60,63,65,68,70,73,75,78,81,83,86,89,92,95,98,101,105,108,111,115,118,121,125,129,132,136,140,144,147,151,155,160,164,168,172,176,181,185,190,194,199,204,209,213,218,223,228,233,239,244,249,255,260,265,271,277,282,288,294,300,306,312,318,324,331,337,343,350,356,363,370,376,383,390,397,404,411,418,426,433,440,448,455,463,471,478,486,494,502,510,518,527,535,543,552,560,569,578,586,595,604,613,622,631,641,650,659,669,678,688,698,707,717,727,737,747,757,768,778,788,799,809,820,831,842,852,863,875,886,897,908,920,931,943,954,966,978,990,1002,1014,1026,1038,1050,1063,1075,1088,1101,1113,1126,1139,1152,1165,1178,1192,1205,1218,1232,1245,1259,1273,1287,1301,1315,1329,1343,1357,1372,1386,1401,1415,1430,1445,1460,1475,1490,1505,1521,1536,1551,1567,1583,1598,1614,1630,1646,1662,1678,1695,1711,1728,1744,1761,1778,1794,1811,1828,1846,1863,1880,1897,1915,1933,1950,1968,1986,2004,2022,2040}; + + __device__ __forceinline__ int LabCbrt_b(int i) + { + float x = i * (1.f / (255.f * (1 << gamma_shift))); + return (1 << lab_shift2) * (x < 0.008856f ? x * 7.787f + 0.13793103448275862f : ::cbrtf(x)); + } + + template + __device__ __forceinline__ void RGB2LabConvert_b(const T& src, D& dst) + { + const int Lscale = (116 * 255 + 50) / 100; + const int Lshift = -((16 * 255 * (1 << lab_shift2) + 50) / 100); + + int B = blueIdx == 0 ? src.x : src.z; + int G = src.y; + int R = blueIdx == 0 ? src.z : src.x; + + if (srgb) + { + B = c_sRGBGammaTab_b[B]; + G = c_sRGBGammaTab_b[G]; + R = c_sRGBGammaTab_b[R]; + } + else + { + B <<= 3; + G <<= 3; + R <<= 3; + } + + int fX = LabCbrt_b(CV_DESCALE(B * 778 + G * 1541 + R * 1777, lab_shift)); + int fY = LabCbrt_b(CV_DESCALE(B * 296 + G * 2929 + R * 871, lab_shift)); + int fZ = LabCbrt_b(CV_DESCALE(B * 3575 + G * 448 + R * 73, lab_shift)); + + int L = CV_DESCALE(Lscale * fY + Lshift, lab_shift2); + int a = CV_DESCALE(500 * (fX - fY) + 128 * (1 << lab_shift2), lab_shift2); + int b = CV_DESCALE(200 * (fY - fZ) + 128 * (1 << lab_shift2), lab_shift2); + + dst.x = saturate_cast(L); + dst.y = saturate_cast(a); + dst.z = saturate_cast(b); + } + + __device__ __forceinline__ float splineInterpolate(float x, const float* tab, int n) + { + int ix = ::min(::max(int(x), 0), n-1); + x -= ix; + tab += ix * 4; + return ((tab[3] * x + tab[2]) * x + tab[1]) * x + tab[0]; + } + + __constant__ float c_sRGBGammaTab[] = 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+ + template + __device__ __forceinline__ void RGB2LabConvert_f(const T& src, D& dst) + { + const float _1_3 = 1.0f / 3.0f; + const float _a = 16.0f / 116.0f; + + float B = blueIdx == 0 ? src.x : src.z; + float G = src.y; + float R = blueIdx == 0 ? src.z : src.x; + + if (srgb) + { + B = splineInterpolate(B * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + G = splineInterpolate(G * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + R = splineInterpolate(R * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + } + + float X = B * 0.189828f + G * 0.376219f + R * 0.433953f; + float Y = B * 0.072169f + G * 0.715160f + R * 0.212671f; + float Z = B * 0.872766f + G * 0.109477f + R * 0.017758f; + + float FX = X > 0.008856f ? ::powf(X, _1_3) : (7.787f * X + _a); + float FY = Y > 0.008856f ? ::powf(Y, _1_3) : (7.787f * Y + _a); + float FZ = Z > 0.008856f ? ::powf(Z, _1_3) : (7.787f * Z + _a); + + float L = Y > 0.008856f ? (116.f * FY - 16.f) : (903.3f * Y); + float a = 500.f * (FX - FY); + float b = 200.f * (FY - FZ); + + dst.x = L; + dst.y = a; + dst.z = b; + } + + template struct RGB2Lab; + template + struct RGB2Lab + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2LabConvert_b(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2Lab() {} + __host__ __device__ __forceinline__ RGB2Lab(const RGB2Lab&) {} + }; + template + struct RGB2Lab + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2LabConvert_f(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2Lab() {} + __host__ __device__ __forceinline__ RGB2Lab(const RGB2Lab&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(name, scn, dcn, srgb, blueIdx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2Lab functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + __constant__ float c_sRGBInvGammaTab[] = 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+ + template + __device__ __forceinline__ void Lab2RGBConvert_f(const T& src, D& dst) + { + const float lThresh = 0.008856f * 903.3f; + const float fThresh = 7.787f * 0.008856f + 16.0f / 116.0f; + + float Y, fy; + + if (src.x <= lThresh) + { + Y = src.x / 903.3f; + fy = 7.787f * Y + 16.0f / 116.0f; + } + else + { + fy = (src.x + 16.0f) / 116.0f; + Y = fy * fy * fy; + } + + float X = src.y / 500.0f + fy; + float Z = fy - src.z / 200.0f; + + if (X <= fThresh) + X = (X - 16.0f / 116.0f) / 7.787f; + else + X = X * X * X; + + if (Z <= fThresh) + Z = (Z - 16.0f / 116.0f) / 7.787f; + else + Z = Z * Z * Z; + + float B = 0.052891f * X - 0.204043f * Y + 1.151152f * Z; + float G = -0.921235f * X + 1.875991f * Y + 0.045244f * Z; + float R = 3.079933f * X - 1.537150f * Y - 0.542782f * Z; + + if (srgb) + { + B = splineInterpolate(B * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + G = splineInterpolate(G * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + R = splineInterpolate(R * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + } + + dst.x = blueIdx == 0 ? B : R; + dst.y = G; + dst.z = blueIdx == 0 ? R : B; + setAlpha(dst, ColorChannel::max()); + } + + template + __device__ __forceinline__ void Lab2RGBConvert_b(const T& src, D& dst) + { + float3 srcf, dstf; + + srcf.x = src.x * (100.f / 255.f); + srcf.y = src.y - 128; + srcf.z = src.z - 128; + + Lab2RGBConvert_f(srcf, dstf); + + dst.x = saturate_cast(dstf.x * 255.f); + dst.y = saturate_cast(dstf.y * 255.f); + dst.z = saturate_cast(dstf.z * 255.f); + setAlpha(dst, ColorChannel::max()); + } + + template struct Lab2RGB; + template + struct Lab2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + Lab2RGBConvert_b(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ Lab2RGB() {} + __host__ __device__ __forceinline__ Lab2RGB(const Lab2RGB&) {} + }; + template + struct Lab2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + Lab2RGBConvert_f(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ Lab2RGB() {} + __host__ __device__ __forceinline__ Lab2RGB(const Lab2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(name, scn, dcn, srgb, blueIdx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::Lab2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + +///////////////////////////////////// RGB <-> Luv ///////////////////////////////////// + + namespace color_detail + { + __constant__ float c_LabCbrtTab[] = 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+ + template + __device__ __forceinline__ void RGB2LuvConvert_f(const T& src, D& dst) + { + const float _d = 1.f / (0.950456f + 15 + 1.088754f * 3); + const float _un = 13 * (4 * 0.950456f * _d); + const float _vn = 13 * (9 * _d); + + float B = blueIdx == 0 ? src.x : src.z; + float G = src.y; + float R = blueIdx == 0 ? src.z : src.x; + + if (srgb) + { + B = splineInterpolate(B * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + G = splineInterpolate(G * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + R = splineInterpolate(R * GAMMA_TAB_SIZE, c_sRGBGammaTab, GAMMA_TAB_SIZE); + } + + float X = R * 0.412453f + G * 0.357580f + B * 0.180423f; + float Y = R * 0.212671f + G * 0.715160f + B * 0.072169f; + float Z = R * 0.019334f + G * 0.119193f + B * 0.950227f; + + float L = splineInterpolate(Y * (LAB_CBRT_TAB_SIZE / 1.5f), c_LabCbrtTab, LAB_CBRT_TAB_SIZE); + L = 116.f * L - 16.f; + + const float d = (4 * 13) / ::fmaxf(X + 15 * Y + 3 * Z, numeric_limits::epsilon()); + float u = L * (X * d - _un); + float v = L * ((9 * 0.25f) * Y * d - _vn); + + dst.x = L; + dst.y = u; + dst.z = v; + } + + template + __device__ __forceinline__ void RGB2LuvConvert_b(const T& src, D& dst) + { + float3 srcf, dstf; + + srcf.x = src.x * (1.f / 255.f); + srcf.y = src.y * (1.f / 255.f); + srcf.z = src.z * (1.f / 255.f); + + RGB2LuvConvert_f(srcf, dstf); + + dst.x = saturate_cast(dstf.x * 2.55f); + dst.y = saturate_cast(dstf.y * 0.72033898305084743f + 96.525423728813564f); + dst.z = saturate_cast(dstf.z * 0.9732824427480916f + 136.259541984732824f); + } + + template struct RGB2Luv; + template + struct RGB2Luv + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2LuvConvert_b(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2Luv() {} + __host__ __device__ __forceinline__ RGB2Luv(const RGB2Luv&) {} + }; + template + struct RGB2Luv + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + RGB2LuvConvert_f(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ RGB2Luv() {} + __host__ __device__ __forceinline__ RGB2Luv(const RGB2Luv&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(name, scn, dcn, srgb, blueIdx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::RGB2Luv functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + namespace color_detail + { + template + __device__ __forceinline__ void Luv2RGBConvert_f(const T& src, D& dst) + { + const float _d = 1.f / (0.950456f + 15 + 1.088754f * 3); + const float _un = 4 * 0.950456f * _d; + const float _vn = 9 * _d; + + float L = src.x; + float u = src.y; + float v = src.z; + + float Y = (L + 16.f) * (1.f / 116.f); + Y = Y * Y * Y; + + float d = (1.f / 13.f) / L; + u = u * d + _un; + v = v * d + _vn; + + float iv = 1.f / v; + float X = 2.25f * u * Y * iv; + float Z = (12 - 3 * u - 20 * v) * Y * 0.25f * iv; + + float B = 0.055648f * X - 0.204043f * Y + 1.057311f * Z; + float G = -0.969256f * X + 1.875991f * Y + 0.041556f * Z; + float R = 3.240479f * X - 1.537150f * Y - 0.498535f * Z; + + if (srgb) + { + B = splineInterpolate(B * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + G = splineInterpolate(G * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + R = splineInterpolate(R * GAMMA_TAB_SIZE, c_sRGBInvGammaTab, GAMMA_TAB_SIZE); + } + + dst.x = blueIdx == 0 ? B : R; + dst.y = G; + dst.z = blueIdx == 0 ? R : B; + setAlpha(dst, ColorChannel::max()); + } + + template + __device__ __forceinline__ void Luv2RGBConvert_b(const T& src, D& dst) + { + float3 srcf, dstf; + + srcf.x = src.x * (100.f / 255.f); + srcf.y = src.y * 1.388235294117647f - 134.f; + srcf.z = src.z * 1.027450980392157f - 140.f; + + Luv2RGBConvert_f(srcf, dstf); + + dst.x = saturate_cast(dstf.x * 255.f); + dst.y = saturate_cast(dstf.y * 255.f); + dst.z = saturate_cast(dstf.z * 255.f); + setAlpha(dst, ColorChannel::max()); + } + + template struct Luv2RGB; + template + struct Luv2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + Luv2RGBConvert_b(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ Luv2RGB() {} + __host__ __device__ __forceinline__ Luv2RGB(const Luv2RGB&) {} + }; + template + struct Luv2RGB + : unary_function::vec_type, typename TypeVec::vec_type> + { + __device__ __forceinline__ typename TypeVec::vec_type operator ()(const typename TypeVec::vec_type& src) const + { + typename TypeVec::vec_type dst; + + Luv2RGBConvert_f(src, dst); + + return dst; + } + __host__ __device__ __forceinline__ Luv2RGB() {} + __host__ __device__ __forceinline__ Luv2RGB(const Luv2RGB&) {} + }; + } + +#define OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(name, scn, dcn, srgb, blueIdx) \ + template struct name ## _traits \ + { \ + typedef ::cv::cuda::device::color_detail::Luv2RGB functor_type; \ + static __host__ __device__ __forceinline__ functor_type create_functor() \ + { \ + return functor_type(); \ + } \ + }; + + #undef CV_DESCALE + +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_COLOR_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce.hpp new file mode 100644 index 00000000..8af20b0d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce.hpp @@ -0,0 +1,365 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_REDUCE_DETAIL_HPP +#define OPENCV_CUDA_REDUCE_DETAIL_HPP + +#include +#include "../warp.hpp" +#include "../warp_shuffle.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + namespace reduce_detail + { + template struct GetType; + template struct GetType + { + typedef T type; + }; + template struct GetType + { + typedef T type; + }; + template struct GetType + { + typedef T type; + }; + + template + struct For + { + template + static __device__ void loadToSmem(const PointerTuple& smem, const ValTuple& val, unsigned int tid) + { + thrust::get(smem)[tid] = thrust::get(val); + + For::loadToSmem(smem, val, tid); + } + template + static __device__ void loadFromSmem(const PointerTuple& smem, const ValTuple& val, unsigned int tid) + { + thrust::get(val) = thrust::get(smem)[tid]; + + For::loadFromSmem(smem, val, tid); + } + + template + static __device__ void merge(const PointerTuple& smem, const ValTuple& val, unsigned int tid, unsigned int delta, const OpTuple& op) + { + typename GetType::type>::type reg = thrust::get(smem)[tid + delta]; + thrust::get(smem)[tid] = thrust::get(val) = thrust::get(op)(thrust::get(val), reg); + + For::merge(smem, val, tid, delta, op); + } + template + static __device__ void mergeShfl(const ValTuple& val, unsigned int delta, unsigned int width, const OpTuple& op) + { + typename GetType::type>::type reg = shfl_down(thrust::get(val), delta, width); + thrust::get(val) = thrust::get(op)(thrust::get(val), reg); + + For::mergeShfl(val, delta, width, op); + } + }; + template + struct For + { + template + static __device__ void loadToSmem(const PointerTuple&, const ValTuple&, unsigned int) + { + } + template + static __device__ void loadFromSmem(const PointerTuple&, const ValTuple&, unsigned int) + { + } + + template + static __device__ void merge(const PointerTuple&, const ValTuple&, unsigned int, unsigned int, const OpTuple&) + { + } + template + static __device__ void mergeShfl(const ValTuple&, unsigned int, unsigned int, const OpTuple&) + { + } + }; + + template + __device__ __forceinline__ void loadToSmem(volatile T* smem, T& val, unsigned int tid) + { + smem[tid] = val; + } + template + __device__ __forceinline__ void loadFromSmem(volatile T* smem, T& val, unsigned int tid) + { + val = smem[tid]; + } + template + __device__ __forceinline__ void loadToSmem(const thrust::tuple& smem, + const thrust::tuple& val, + unsigned int tid) + { + For<0, thrust::tuple_size >::value>::loadToSmem(smem, val, tid); + } + template + __device__ __forceinline__ void loadFromSmem(const thrust::tuple& smem, + const thrust::tuple& val, + unsigned int tid) + { + For<0, thrust::tuple_size >::value>::loadFromSmem(smem, val, tid); + } + + template + __device__ __forceinline__ void merge(volatile T* smem, T& val, unsigned int tid, unsigned int delta, const Op& op) + { + T reg = smem[tid + delta]; + smem[tid] = val = op(val, reg); + } + template + __device__ __forceinline__ void mergeShfl(T& val, unsigned int delta, unsigned int width, const Op& op) + { + T reg = shfl_down(val, delta, width); + val = op(val, reg); + } + template + __device__ __forceinline__ void merge(const thrust::tuple& smem, + const thrust::tuple& val, + unsigned int tid, + unsigned int delta, + const thrust::tuple& op) + { + For<0, thrust::tuple_size >::value>::merge(smem, val, tid, delta, op); + } + template + __device__ __forceinline__ void mergeShfl(const thrust::tuple& val, + unsigned int delta, + unsigned int width, + const thrust::tuple& op) + { + For<0, thrust::tuple_size >::value>::mergeShfl(val, delta, width, op); + } + + template struct Generic + { + template + static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op) + { + loadToSmem(smem, val, tid); + if (N >= 32) + __syncthreads(); + + if (N >= 2048) + { + if (tid < 1024) + merge(smem, val, tid, 1024, op); + + __syncthreads(); + } + if (N >= 1024) + { + if (tid < 512) + merge(smem, val, tid, 512, op); + + __syncthreads(); + } + if (N >= 512) + { + if (tid < 256) + merge(smem, val, tid, 256, op); + + __syncthreads(); + } + if (N >= 256) + { + if (tid < 128) + merge(smem, val, tid, 128, op); + + __syncthreads(); + } + if (N >= 128) + { + if (tid < 64) + merge(smem, val, tid, 64, op); + + __syncthreads(); + } + if (N >= 64) + { + if (tid < 32) + merge(smem, val, tid, 32, op); + } + + if (tid < 16) + { + merge(smem, val, tid, 16, op); + merge(smem, val, tid, 8, op); + merge(smem, val, tid, 4, op); + merge(smem, val, tid, 2, op); + merge(smem, val, tid, 1, op); + } + } + }; + + template + struct Unroll + { + static __device__ void loopShfl(Reference val, Op op, unsigned int N) + { + mergeShfl(val, I, N, op); + Unroll::loopShfl(val, op, N); + } + static __device__ void loop(Pointer smem, Reference val, unsigned int tid, Op op) + { + merge(smem, val, tid, I, op); + Unroll::loop(smem, val, tid, op); + } + }; + template + struct Unroll<0, Pointer, Reference, Op> + { + static __device__ void loopShfl(Reference, Op, unsigned int) + { + } + static __device__ void loop(Pointer, Reference, unsigned int, Op) + { + } + }; + + template struct WarpOptimized + { + template + static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + CV_UNUSED(smem); + CV_UNUSED(tid); + + Unroll::loopShfl(val, op, N); + #else + loadToSmem(smem, val, tid); + + if (tid < N / 2) + Unroll::loop(smem, val, tid, op); + #endif + } + }; + + template struct GenericOptimized32 + { + enum { M = N / 32 }; + + template + static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op) + { + const unsigned int laneId = Warp::laneId(); + + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + Unroll<16, Pointer, Reference, Op>::loopShfl(val, op, warpSize); + + if (laneId == 0) + loadToSmem(smem, val, tid / 32); + #else + loadToSmem(smem, val, tid); + + if (laneId < 16) + Unroll<16, Pointer, Reference, Op>::loop(smem, val, tid, op); + + __syncthreads(); + + if (laneId == 0) + loadToSmem(smem, val, tid / 32); + #endif + + __syncthreads(); + + loadFromSmem(smem, val, tid); + + if (tid < 32) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + Unroll::loopShfl(val, op, M); + #else + Unroll::loop(smem, val, tid, op); + #endif + } + } + }; + + template struct StaticIf; + template struct StaticIf + { + typedef T1 type; + }; + template struct StaticIf + { + typedef T2 type; + }; + + template struct IsPowerOf2 + { + enum { value = ((N != 0) && !(N & (N - 1))) }; + }; + + template struct Dispatcher + { + typedef typename StaticIf< + (N <= 32) && IsPowerOf2::value, + WarpOptimized, + typename StaticIf< + (N <= 1024) && IsPowerOf2::value, + GenericOptimized32, + Generic + >::type + >::type reductor; + }; + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_REDUCE_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce_key_val.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce_key_val.hpp new file mode 100644 index 00000000..df37c173 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/reduce_key_val.hpp @@ -0,0 +1,502 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP +#define OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP + +#include +#include "../warp.hpp" +#include "../warp_shuffle.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + namespace reduce_key_val_detail + { + template struct GetType; + template struct GetType + { + typedef T type; + }; + template struct GetType + { + typedef T type; + }; + template struct GetType + { + typedef T type; + }; + + template + struct For + { + template + static __device__ void loadToSmem(const PointerTuple& smem, const ReferenceTuple& data, unsigned int tid) + { + thrust::get(smem)[tid] = thrust::get(data); + + For::loadToSmem(smem, data, tid); + } + template + static __device__ void loadFromSmem(const PointerTuple& smem, const ReferenceTuple& data, unsigned int tid) + { + thrust::get(data) = thrust::get(smem)[tid]; + + For::loadFromSmem(smem, data, tid); + } + + template + static __device__ void copyShfl(const ReferenceTuple& val, unsigned int delta, int width) + { + thrust::get(val) = shfl_down(thrust::get(val), delta, width); + + For::copyShfl(val, delta, width); + } + template + static __device__ void copy(const PointerTuple& svals, const ReferenceTuple& val, unsigned int tid, unsigned int delta) + { + thrust::get(svals)[tid] = thrust::get(val) = thrust::get(svals)[tid + delta]; + + For::copy(svals, val, tid, delta); + } + + template + static __device__ void mergeShfl(const KeyReferenceTuple& key, const ValReferenceTuple& val, const CmpTuple& cmp, unsigned int delta, int width) + { + typename GetType::type>::type reg = shfl_down(thrust::get(key), delta, width); + + if (thrust::get(cmp)(reg, thrust::get(key))) + { + thrust::get(key) = reg; + thrust::get(val) = shfl_down(thrust::get(val), delta, width); + } + + For::mergeShfl(key, val, cmp, delta, width); + } + template + static __device__ void merge(const KeyPointerTuple& skeys, const KeyReferenceTuple& key, + const ValPointerTuple& svals, const ValReferenceTuple& val, + const CmpTuple& cmp, + unsigned int tid, unsigned int delta) + { + typename GetType::type>::type reg = thrust::get(skeys)[tid + delta]; + + if (thrust::get(cmp)(reg, thrust::get(key))) + { + thrust::get(skeys)[tid] = thrust::get(key) = reg; + thrust::get(svals)[tid] = thrust::get(val) = thrust::get(svals)[tid + delta]; + } + + For::merge(skeys, key, svals, val, cmp, tid, delta); + } + }; + template + struct For + { + template + static __device__ void loadToSmem(const PointerTuple&, const ReferenceTuple&, unsigned int) + { + } + template + static __device__ void loadFromSmem(const PointerTuple&, const ReferenceTuple&, unsigned int) + { + } + + template + static __device__ void copyShfl(const ReferenceTuple&, unsigned int, int) + { + } + template + static __device__ void copy(const PointerTuple&, const ReferenceTuple&, unsigned int, unsigned int) + { + } + + template + static __device__ void mergeShfl(const KeyReferenceTuple&, const ValReferenceTuple&, const CmpTuple&, unsigned int, int) + { + } + template + static __device__ void merge(const KeyPointerTuple&, const KeyReferenceTuple&, + const ValPointerTuple&, const ValReferenceTuple&, + const CmpTuple&, + unsigned int, unsigned int) + { + } + }; + + ////////////////////////////////////////////////////// + // loadToSmem + + template + __device__ __forceinline__ void loadToSmem(volatile T* smem, T& data, unsigned int tid) + { + smem[tid] = data; + } + template + __device__ __forceinline__ void loadFromSmem(volatile T* smem, T& data, unsigned int tid) + { + data = smem[tid]; + } + template + __device__ __forceinline__ void loadToSmem(const thrust::tuple& smem, + const thrust::tuple& data, + unsigned int tid) + { + For<0, thrust::tuple_size >::value>::loadToSmem(smem, data, tid); + } + template + __device__ __forceinline__ void loadFromSmem(const thrust::tuple& smem, + const thrust::tuple& data, + unsigned int tid) + { + For<0, thrust::tuple_size >::value>::loadFromSmem(smem, data, tid); + } + + ////////////////////////////////////////////////////// + // copyVals + + template + __device__ __forceinline__ void copyValsShfl(V& val, unsigned int delta, int width) + { + val = shfl_down(val, delta, width); + } + template + __device__ __forceinline__ void copyVals(volatile V* svals, V& val, unsigned int tid, unsigned int delta) + { + svals[tid] = val = svals[tid + delta]; + } + template + __device__ __forceinline__ void copyValsShfl(const thrust::tuple& val, + unsigned int delta, + int width) + { + For<0, thrust::tuple_size >::value>::copyShfl(val, delta, width); + } + template + __device__ __forceinline__ void copyVals(const thrust::tuple& svals, + const thrust::tuple& val, + unsigned int tid, unsigned int delta) + { + For<0, thrust::tuple_size >::value>::copy(svals, val, tid, delta); + } + + ////////////////////////////////////////////////////// + // merge + + template + __device__ __forceinline__ void mergeShfl(K& key, V& val, const Cmp& cmp, unsigned int delta, int width) + { + K reg = shfl_down(key, delta, width); + + if (cmp(reg, key)) + { + key = reg; + copyValsShfl(val, delta, width); + } + } + template + __device__ __forceinline__ void merge(volatile K* skeys, K& key, volatile V* svals, V& val, const Cmp& cmp, unsigned int tid, unsigned int delta) + { + K reg = skeys[tid + delta]; + + if (cmp(reg, key)) + { + skeys[tid] = key = reg; + copyVals(svals, val, tid, delta); + } + } + template + __device__ __forceinline__ void mergeShfl(K& key, + const thrust::tuple& val, + const Cmp& cmp, + unsigned int delta, int width) + { + K reg = shfl_down(key, delta, width); + + if (cmp(reg, key)) + { + key = reg; + copyValsShfl(val, delta, width); + } + } + template + __device__ __forceinline__ void merge(volatile K* skeys, K& key, + const thrust::tuple& svals, + const thrust::tuple& val, + const Cmp& cmp, unsigned int tid, unsigned int delta) + { + K reg = skeys[tid + delta]; + + if (cmp(reg, key)) + { + skeys[tid] = key = reg; + copyVals(svals, val, tid, delta); + } + } + template + __device__ __forceinline__ void mergeShfl(const thrust::tuple& key, + const thrust::tuple& val, + const thrust::tuple& cmp, + unsigned int delta, int width) + { + For<0, thrust::tuple_size >::value>::mergeShfl(key, val, cmp, delta, width); + } + template + __device__ __forceinline__ void merge(const thrust::tuple& skeys, + const thrust::tuple& key, + const thrust::tuple& svals, + const thrust::tuple& val, + const thrust::tuple& cmp, + unsigned int tid, unsigned int delta) + { + For<0, thrust::tuple_size >::value>::merge(skeys, key, svals, val, cmp, tid, delta); + } + + ////////////////////////////////////////////////////// + // Generic + + template struct Generic + { + template + static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp) + { + loadToSmem(skeys, key, tid); + loadValsToSmem(svals, val, tid); + if (N >= 32) + __syncthreads(); + + if (N >= 2048) + { + if (tid < 1024) + merge(skeys, key, svals, val, cmp, tid, 1024); + + __syncthreads(); + } + if (N >= 1024) + { + if (tid < 512) + merge(skeys, key, svals, val, cmp, tid, 512); + + __syncthreads(); + } + if (N >= 512) + { + if (tid < 256) + merge(skeys, key, svals, val, cmp, tid, 256); + + __syncthreads(); + } + if (N >= 256) + { + if (tid < 128) + merge(skeys, key, svals, val, cmp, tid, 128); + + __syncthreads(); + } + if (N >= 128) + { + if (tid < 64) + merge(skeys, key, svals, val, cmp, tid, 64); + + __syncthreads(); + } + if (N >= 64) + { + if (tid < 32) + merge(skeys, key, svals, val, cmp, tid, 32); + } + + if (tid < 16) + { + merge(skeys, key, svals, val, cmp, tid, 16); + merge(skeys, key, svals, val, cmp, tid, 8); + merge(skeys, key, svals, val, cmp, tid, 4); + merge(skeys, key, svals, val, cmp, tid, 2); + merge(skeys, key, svals, val, cmp, tid, 1); + } + } + }; + + template + struct Unroll + { + static __device__ void loopShfl(KR key, VR val, Cmp cmp, unsigned int N) + { + mergeShfl(key, val, cmp, I, N); + Unroll::loopShfl(key, val, cmp, N); + } + static __device__ void loop(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp) + { + merge(skeys, key, svals, val, cmp, tid, I); + Unroll::loop(skeys, key, svals, val, tid, cmp); + } + }; + template + struct Unroll<0, KP, KR, VP, VR, Cmp> + { + static __device__ void loopShfl(KR, VR, Cmp, unsigned int) + { + } + static __device__ void loop(KP, KR, VP, VR, unsigned int, Cmp) + { + } + }; + + template struct WarpOptimized + { + template + static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp) + { + #if 0 // __CUDA_ARCH__ >= 300 + CV_UNUSED(skeys); + CV_UNUSED(svals); + CV_UNUSED(tid); + + Unroll::loopShfl(key, val, cmp, N); + #else + loadToSmem(skeys, key, tid); + loadToSmem(svals, val, tid); + + if (tid < N / 2) + Unroll::loop(skeys, key, svals, val, tid, cmp); + #endif + } + }; + + template struct GenericOptimized32 + { + enum { M = N / 32 }; + + template + static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp) + { + const unsigned int laneId = Warp::laneId(); + + #if 0 // __CUDA_ARCH__ >= 300 + Unroll<16, KP, KR, VP, VR, Cmp>::loopShfl(key, val, cmp, warpSize); + + if (laneId == 0) + { + loadToSmem(skeys, key, tid / 32); + loadToSmem(svals, val, tid / 32); + } + #else + loadToSmem(skeys, key, tid); + loadToSmem(svals, val, tid); + + if (laneId < 16) + Unroll<16, KP, KR, VP, VR, Cmp>::loop(skeys, key, svals, val, tid, cmp); + + __syncthreads(); + + if (laneId == 0) + { + loadToSmem(skeys, key, tid / 32); + loadToSmem(svals, val, tid / 32); + } + #endif + + __syncthreads(); + + loadFromSmem(skeys, key, tid); + + if (tid < 32) + { + #if 0 // __CUDA_ARCH__ >= 300 + loadFromSmem(svals, val, tid); + + Unroll::loopShfl(key, val, cmp, M); + #else + Unroll::loop(skeys, key, svals, val, tid, cmp); + #endif + } + } + }; + + template struct StaticIf; + template struct StaticIf + { + typedef T1 type; + }; + template struct StaticIf + { + typedef T2 type; + }; + + template struct IsPowerOf2 + { + enum { value = ((N != 0) && !(N & (N - 1))) }; + }; + + template struct Dispatcher + { + typedef typename StaticIf< + (N <= 32) && IsPowerOf2::value, + WarpOptimized, + typename StaticIf< + (N <= 1024) && IsPowerOf2::value, + GenericOptimized32, + Generic + >::type + >::type reductor; + }; + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/transform_detail.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/transform_detail.hpp new file mode 100644 index 00000000..19198488 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/transform_detail.hpp @@ -0,0 +1,392 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_TRANSFORM_DETAIL_HPP +#define OPENCV_CUDA_TRANSFORM_DETAIL_HPP + +#include "../common.hpp" +#include "../vec_traits.hpp" +#include "../functional.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + namespace transform_detail + { + //! Read Write Traits + + template struct UnaryReadWriteTraits + { + typedef typename TypeVec::vec_type read_type; + typedef typename TypeVec::vec_type write_type; + }; + + template struct BinaryReadWriteTraits + { + typedef typename TypeVec::vec_type read_type1; + typedef typename TypeVec::vec_type read_type2; + typedef typename TypeVec::vec_type write_type; + }; + + //! Transform kernels + + template struct OpUnroller; + template <> struct OpUnroller<1> + { + template + static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, UnOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src.x); + } + + template + static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, BinOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src1.x, src2.x); + } + }; + template <> struct OpUnroller<2> + { + template + static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, UnOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src.y); + } + + template + static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, BinOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src1.x, src2.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src1.y, src2.y); + } + }; + template <> struct OpUnroller<3> + { + template + static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src.y); + if (mask(y, x_shifted + 2)) + dst.z = op(src.z); + } + + template + static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src1.x, src2.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src1.y, src2.y); + if (mask(y, x_shifted + 2)) + dst.z = op(src1.z, src2.z); + } + }; + template <> struct OpUnroller<4> + { + template + static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src.y); + if (mask(y, x_shifted + 2)) + dst.z = op(src.z); + if (mask(y, x_shifted + 3)) + dst.w = op(src.w); + } + + template + static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.x = op(src1.x, src2.x); + if (mask(y, x_shifted + 1)) + dst.y = op(src1.y, src2.y); + if (mask(y, x_shifted + 2)) + dst.z = op(src1.z, src2.z); + if (mask(y, x_shifted + 3)) + dst.w = op(src1.w, src2.w); + } + }; + template <> struct OpUnroller<8> + { + template + static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.a0 = op(src.a0); + if (mask(y, x_shifted + 1)) + dst.a1 = op(src.a1); + if (mask(y, x_shifted + 2)) + dst.a2 = op(src.a2); + if (mask(y, x_shifted + 3)) + dst.a3 = op(src.a3); + if (mask(y, x_shifted + 4)) + dst.a4 = op(src.a4); + if (mask(y, x_shifted + 5)) + dst.a5 = op(src.a5); + if (mask(y, x_shifted + 6)) + dst.a6 = op(src.a6); + if (mask(y, x_shifted + 7)) + dst.a7 = op(src.a7); + } + + template + static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y) + { + if (mask(y, x_shifted)) + dst.a0 = op(src1.a0, src2.a0); + if (mask(y, x_shifted + 1)) + dst.a1 = op(src1.a1, src2.a1); + if (mask(y, x_shifted + 2)) + dst.a2 = op(src1.a2, src2.a2); + if (mask(y, x_shifted + 3)) + dst.a3 = op(src1.a3, src2.a3); + if (mask(y, x_shifted + 4)) + dst.a4 = op(src1.a4, src2.a4); + if (mask(y, x_shifted + 5)) + dst.a5 = op(src1.a5, src2.a5); + if (mask(y, x_shifted + 6)) + dst.a6 = op(src1.a6, src2.a6); + if (mask(y, x_shifted + 7)) + dst.a7 = op(src1.a7, src2.a7); + } + }; + + template + static __global__ void transformSmart(const PtrStepSz src_, PtrStep dst_, const Mask mask, const UnOp op) + { + typedef TransformFunctorTraits ft; + typedef typename UnaryReadWriteTraits::read_type read_type; + typedef typename UnaryReadWriteTraits::write_type write_type; + + const int x = threadIdx.x + blockIdx.x * blockDim.x; + const int y = threadIdx.y + blockIdx.y * blockDim.y; + const int x_shifted = x * ft::smart_shift; + + if (y < src_.rows) + { + const T* src = src_.ptr(y); + D* dst = dst_.ptr(y); + + if (x_shifted + ft::smart_shift - 1 < src_.cols) + { + const read_type src_n_el = ((const read_type*)src)[x]; + OpUnroller::unroll(src_n_el, ((write_type*)dst)[x], mask, op, x_shifted, y); + } + else + { + for (int real_x = x_shifted; real_x < src_.cols; ++real_x) + { + if (mask(y, real_x)) + dst[real_x] = op(src[real_x]); + } + } + } + } + + template + __global__ static void transformSimple(const PtrStepSz src, PtrStep dst, const Mask mask, const UnOp op) + { + const int x = blockDim.x * blockIdx.x + threadIdx.x; + const int y = blockDim.y * blockIdx.y + threadIdx.y; + + if (x < src.cols && y < src.rows && mask(y, x)) + { + dst.ptr(y)[x] = op(src.ptr(y)[x]); + } + } + + template + static __global__ void transformSmart(const PtrStepSz src1_, const PtrStep src2_, PtrStep dst_, + const Mask mask, const BinOp op) + { + typedef TransformFunctorTraits ft; + typedef typename BinaryReadWriteTraits::read_type1 read_type1; + typedef typename BinaryReadWriteTraits::read_type2 read_type2; + typedef typename BinaryReadWriteTraits::write_type write_type; + + const int x = threadIdx.x + blockIdx.x * blockDim.x; + const int y = threadIdx.y + blockIdx.y * blockDim.y; + const int x_shifted = x * ft::smart_shift; + + if (y < src1_.rows) + { + const T1* src1 = src1_.ptr(y); + const T2* src2 = src2_.ptr(y); + D* dst = dst_.ptr(y); + + if (x_shifted + ft::smart_shift - 1 < src1_.cols) + { + const read_type1 src1_n_el = ((const read_type1*)src1)[x]; + const read_type2 src2_n_el = ((const read_type2*)src2)[x]; + + OpUnroller::unroll(src1_n_el, src2_n_el, ((write_type*)dst)[x], mask, op, x_shifted, y); + } + else + { + for (int real_x = x_shifted; real_x < src1_.cols; ++real_x) + { + if (mask(y, real_x)) + dst[real_x] = op(src1[real_x], src2[real_x]); + } + } + } + } + + template + static __global__ void transformSimple(const PtrStepSz src1, const PtrStep src2, PtrStep dst, + const Mask mask, const BinOp op) + { + const int x = blockDim.x * blockIdx.x + threadIdx.x; + const int y = blockDim.y * blockIdx.y + threadIdx.y; + + if (x < src1.cols && y < src1.rows && mask(y, x)) + { + const T1 src1_data = src1.ptr(y)[x]; + const T2 src2_data = src2.ptr(y)[x]; + dst.ptr(y)[x] = op(src1_data, src2_data); + } + } + + template struct TransformDispatcher; + template<> struct TransformDispatcher + { + template + static void call(PtrStepSz src, PtrStepSz dst, UnOp op, Mask mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + + const dim3 threads(ft::simple_block_dim_x, ft::simple_block_dim_y, 1); + const dim3 grid(divUp(src.cols, threads.x), divUp(src.rows, threads.y), 1); + + transformSimple<<>>(src, dst, mask, op); + cudaSafeCall( cudaGetLastError() ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } + + template + static void call(PtrStepSz src1, PtrStepSz src2, PtrStepSz dst, BinOp op, Mask mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + + const dim3 threads(ft::simple_block_dim_x, ft::simple_block_dim_y, 1); + const dim3 grid(divUp(src1.cols, threads.x), divUp(src1.rows, threads.y), 1); + + transformSimple<<>>(src1, src2, dst, mask, op); + cudaSafeCall( cudaGetLastError() ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } + }; + template<> struct TransformDispatcher + { + template + static void call(PtrStepSz src, PtrStepSz dst, UnOp op, Mask mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + + CV_StaticAssert(ft::smart_shift != 1, ""); + + if (!isAligned(src.data, ft::smart_shift * sizeof(T)) || !isAligned(src.step, ft::smart_shift * sizeof(T)) || + !isAligned(dst.data, ft::smart_shift * sizeof(D)) || !isAligned(dst.step, ft::smart_shift * sizeof(D))) + { + TransformDispatcher::call(src, dst, op, mask, stream); + return; + } + + const dim3 threads(ft::smart_block_dim_x, ft::smart_block_dim_y, 1); + const dim3 grid(divUp(src.cols, threads.x * ft::smart_shift), divUp(src.rows, threads.y), 1); + + transformSmart<<>>(src, dst, mask, op); + cudaSafeCall( cudaGetLastError() ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } + + template + static void call(PtrStepSz src1, PtrStepSz src2, PtrStepSz dst, BinOp op, Mask mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + + CV_StaticAssert(ft::smart_shift != 1, ""); + + if (!isAligned(src1.data, ft::smart_shift * sizeof(T1)) || !isAligned(src1.step, ft::smart_shift * sizeof(T1)) || + !isAligned(src2.data, ft::smart_shift * sizeof(T2)) || !isAligned(src2.step, ft::smart_shift * sizeof(T2)) || + !isAligned(dst.data, ft::smart_shift * sizeof(D)) || !isAligned(dst.step, ft::smart_shift * sizeof(D))) + { + TransformDispatcher::call(src1, src2, dst, op, mask, stream); + return; + } + + const dim3 threads(ft::smart_block_dim_x, ft::smart_block_dim_y, 1); + const dim3 grid(divUp(src1.cols, threads.x * ft::smart_shift), divUp(src1.rows, threads.y), 1); + + transformSmart<<>>(src1, src2, dst, mask, op); + cudaSafeCall( cudaGetLastError() ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } + }; + } // namespace transform_detail +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_TRANSFORM_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/type_traits_detail.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/type_traits_detail.hpp new file mode 100644 index 00000000..a78bd2c0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/type_traits_detail.hpp @@ -0,0 +1,191 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP +#define OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP + +#include "../common.hpp" +#include "../vec_traits.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + namespace type_traits_detail + { + template struct Select { typedef T1 type; }; + template struct Select { typedef T2 type; }; + + template struct IsSignedIntergral { enum {value = 0}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + template <> struct IsSignedIntergral { enum {value = 1}; }; + + template struct IsUnsignedIntegral { enum {value = 0}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + template <> struct IsUnsignedIntegral { enum {value = 1}; }; + + template struct IsIntegral { enum {value = IsSignedIntergral::value || IsUnsignedIntegral::value}; }; + template <> struct IsIntegral { enum {value = 1}; }; + template <> struct IsIntegral { enum {value = 1}; }; + + template struct IsFloat { enum {value = 0}; }; + template <> struct IsFloat { enum {value = 1}; }; + template <> struct IsFloat { enum {value = 1}; }; + + template struct IsVec { enum {value = 0}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + template <> struct IsVec { enum {value = 1}; }; + + template struct AddParameterType { typedef const U& type; }; + template struct AddParameterType { typedef U& type; }; + template <> struct AddParameterType { typedef void type; }; + + template struct ReferenceTraits + { + enum { value = false }; + typedef U type; + }; + template struct ReferenceTraits + { + enum { value = true }; + typedef U type; + }; + + template struct PointerTraits + { + enum { value = false }; + typedef void type; + }; + template struct PointerTraits + { + enum { value = true }; + typedef U type; + }; + template struct PointerTraits + { + enum { value = true }; + typedef U type; + }; + + template struct UnConst + { + typedef U type; + enum { value = 0 }; + }; + template struct UnConst + { + typedef U type; + enum { value = 1 }; + }; + template struct UnConst + { + typedef U& type; + enum { value = 1 }; + }; + + template struct UnVolatile + { + typedef U type; + enum { value = 0 }; + }; + template struct UnVolatile + { + typedef U type; + enum { value = 1 }; + }; + template struct UnVolatile + { + typedef U& type; + enum { value = 1 }; + }; + } // namespace type_traits_detail +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/detail/vec_distance_detail.hpp b/3rdparty/opencv/include/opencv2/core/cuda/detail/vec_distance_detail.hpp new file mode 100644 index 00000000..8283a995 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/detail/vec_distance_detail.hpp @@ -0,0 +1,121 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP +#define OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP + +#include "../datamov_utils.hpp" + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + namespace vec_distance_detail + { + template struct UnrollVecDiffCached + { + template + static __device__ void calcCheck(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int ind) + { + if (ind < len) + { + T1 val1 = *vecCached++; + + T2 val2; + ForceGlob::Load(vecGlob, ind, val2); + + dist.reduceIter(val1, val2); + + UnrollVecDiffCached::calcCheck(vecCached, vecGlob, len, dist, ind + THREAD_DIM); + } + } + + template + static __device__ void calcWithoutCheck(const T1* vecCached, const T2* vecGlob, Dist& dist) + { + T1 val1 = *vecCached++; + + T2 val2; + ForceGlob::Load(vecGlob, 0, val2); + vecGlob += THREAD_DIM; + + dist.reduceIter(val1, val2); + + UnrollVecDiffCached::calcWithoutCheck(vecCached, vecGlob, dist); + } + }; + template struct UnrollVecDiffCached + { + template + static __device__ __forceinline__ void calcCheck(const T1*, const T2*, int, Dist&, int) + { + } + + template + static __device__ __forceinline__ void calcWithoutCheck(const T1*, const T2*, Dist&) + { + } + }; + + template struct VecDiffCachedCalculator; + template struct VecDiffCachedCalculator + { + template + static __device__ __forceinline__ void calc(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int tid) + { + UnrollVecDiffCached::calcCheck(vecCached, vecGlob, len, dist, tid); + } + }; + template struct VecDiffCachedCalculator + { + template + static __device__ __forceinline__ void calc(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int tid) + { + UnrollVecDiffCached::calcWithoutCheck(vecCached, vecGlob + tid, dist); + } + }; + } // namespace vec_distance_detail +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/dynamic_smem.hpp b/3rdparty/opencv/include/opencv2/core/cuda/dynamic_smem.hpp new file mode 100644 index 00000000..42570c68 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/dynamic_smem.hpp @@ -0,0 +1,88 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_DYNAMIC_SMEM_HPP +#define OPENCV_CUDA_DYNAMIC_SMEM_HPP + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template struct DynamicSharedMem + { + __device__ __forceinline__ operator T*() + { + extern __shared__ int __smem[]; + return (T*)__smem; + } + + __device__ __forceinline__ operator const T*() const + { + extern __shared__ int __smem[]; + return (T*)__smem; + } + }; + + // specialize for double to avoid unaligned memory access compile errors + template<> struct DynamicSharedMem + { + __device__ __forceinline__ operator double*() + { + extern __shared__ double __smem_d[]; + return (double*)__smem_d; + } + + __device__ __forceinline__ operator const double*() const + { + extern __shared__ double __smem_d[]; + return (double*)__smem_d; + } + }; +}}} + +//! @endcond + +#endif // OPENCV_CUDA_DYNAMIC_SMEM_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/emulation.hpp b/3rdparty/opencv/include/opencv2/core/cuda/emulation.hpp new file mode 100644 index 00000000..17dc1171 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/emulation.hpp @@ -0,0 +1,269 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_EMULATION_HPP_ +#define OPENCV_CUDA_EMULATION_HPP_ + +#include "common.hpp" +#include "warp_reduce.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + struct Emulation + { + + static __device__ __forceinline__ int syncthreadsOr(int pred) + { +#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 200) + // just campilation stab + return 0; +#else + return __syncthreads_or(pred); +#endif + } + + template + static __forceinline__ __device__ int Ballot(int predicate) + { +#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200) + return __ballot(predicate); +#else + __shared__ volatile int cta_buffer[CTA_SIZE]; + + int tid = threadIdx.x; + cta_buffer[tid] = predicate ? (1 << (tid & 31)) : 0; + return warp_reduce(cta_buffer); +#endif + } + + struct smem + { + enum { TAG_MASK = (1U << ( (sizeof(unsigned int) << 3) - 5U)) - 1U }; + + template + static __device__ __forceinline__ T atomicInc(T* address, T val) + { +#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120) + T count; + unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U); + do + { + count = *address & TAG_MASK; + count = tag | (count + 1); + *address = count; + } while (*address != count); + + return (count & TAG_MASK) - 1; +#else + return ::atomicInc(address, val); +#endif + } + + template + static __device__ __forceinline__ T atomicAdd(T* address, T val) + { +#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120) + T count; + unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U); + do + { + count = *address & TAG_MASK; + count = tag | (count + val); + *address = count; + } while (*address != count); + + return (count & TAG_MASK) - val; +#else + return ::atomicAdd(address, val); +#endif + } + + template + static __device__ __forceinline__ T atomicMin(T* address, T val) + { +#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120) + T count = ::min(*address, val); + do + { + *address = count; + } while (*address > count); + + return count; +#else + return ::atomicMin(address, val); +#endif + } + }; // struct cmem + + struct glob + { + static __device__ __forceinline__ int atomicAdd(int* address, int val) + { + return ::atomicAdd(address, val); + } + static __device__ __forceinline__ unsigned int atomicAdd(unsigned int* address, unsigned int val) + { + return ::atomicAdd(address, val); + } + static __device__ __forceinline__ float atomicAdd(float* address, float val) + { + #if __CUDA_ARCH__ >= 200 + return ::atomicAdd(address, val); + #else + int* address_as_i = (int*) address; + int old = *address_as_i, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_i, assumed, + __float_as_int(val + __int_as_float(assumed))); + } while (assumed != old); + return __int_as_float(old); + #endif + } + static __device__ __forceinline__ double atomicAdd(double* address, double val) + { + #if __CUDA_ARCH__ >= 130 + unsigned long long int* address_as_ull = (unsigned long long int*) address; + unsigned long long int old = *address_as_ull, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_ull, assumed, + __double_as_longlong(val + __longlong_as_double(assumed))); + } while (assumed != old); + return __longlong_as_double(old); + #else + CV_UNUSED(address); + CV_UNUSED(val); + return 0.0; + #endif + } + + static __device__ __forceinline__ int atomicMin(int* address, int val) + { + return ::atomicMin(address, val); + } + static __device__ __forceinline__ float atomicMin(float* address, float val) + { + #if __CUDA_ARCH__ >= 120 + int* address_as_i = (int*) address; + int old = *address_as_i, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_i, assumed, + __float_as_int(::fminf(val, __int_as_float(assumed)))); + } while (assumed != old); + return __int_as_float(old); + #else + CV_UNUSED(address); + CV_UNUSED(val); + return 0.0f; + #endif + } + static __device__ __forceinline__ double atomicMin(double* address, double val) + { + #if __CUDA_ARCH__ >= 130 + unsigned long long int* address_as_ull = (unsigned long long int*) address; + unsigned long long int old = *address_as_ull, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_ull, assumed, + __double_as_longlong(::fmin(val, __longlong_as_double(assumed)))); + } while (assumed != old); + return __longlong_as_double(old); + #else + CV_UNUSED(address); + CV_UNUSED(val); + return 0.0; + #endif + } + + static __device__ __forceinline__ int atomicMax(int* address, int val) + { + return ::atomicMax(address, val); + } + static __device__ __forceinline__ float atomicMax(float* address, float val) + { + #if __CUDA_ARCH__ >= 120 + int* address_as_i = (int*) address; + int old = *address_as_i, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_i, assumed, + __float_as_int(::fmaxf(val, __int_as_float(assumed)))); + } while (assumed != old); + return __int_as_float(old); + #else + CV_UNUSED(address); + CV_UNUSED(val); + return 0.0f; + #endif + } + static __device__ __forceinline__ double atomicMax(double* address, double val) + { + #if __CUDA_ARCH__ >= 130 + unsigned long long int* address_as_ull = (unsigned long long int*) address; + unsigned long long int old = *address_as_ull, assumed; + do { + assumed = old; + old = ::atomicCAS(address_as_ull, assumed, + __double_as_longlong(::fmax(val, __longlong_as_double(assumed)))); + } while (assumed != old); + return __longlong_as_double(old); + #else + CV_UNUSED(address); + CV_UNUSED(val); + return 0.0; + #endif + } + }; + }; //struct Emulation +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif /* OPENCV_CUDA_EMULATION_HPP_ */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/filters.hpp b/3rdparty/opencv/include/opencv2/core/cuda/filters.hpp new file mode 100644 index 00000000..bb942122 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/filters.hpp @@ -0,0 +1,286 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_FILTERS_HPP +#define OPENCV_CUDA_FILTERS_HPP + +#include "saturate_cast.hpp" +#include "vec_traits.hpp" +#include "vec_math.hpp" +#include "type_traits.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template struct PointFilter + { + typedef typename Ptr2D::elem_type elem_type; + typedef float index_type; + + explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) + : src(src_) + { + CV_UNUSED(fx); + CV_UNUSED(fy); + } + + __device__ __forceinline__ elem_type operator ()(float y, float x) const + { + return src(__float2int_rz(y), __float2int_rz(x)); + } + + Ptr2D src; + }; + + template struct LinearFilter + { + typedef typename Ptr2D::elem_type elem_type; + typedef float index_type; + + explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) + : src(src_) + { + CV_UNUSED(fx); + CV_UNUSED(fy); + } + __device__ __forceinline__ elem_type operator ()(float y, float x) const + { + typedef typename TypeVec::cn>::vec_type work_type; + + work_type out = VecTraits::all(0); + + const int x1 = __float2int_rd(x); + const int y1 = __float2int_rd(y); + const int x2 = x1 + 1; + const int y2 = y1 + 1; + + elem_type src_reg = src(y1, x1); + out = out + src_reg * ((x2 - x) * (y2 - y)); + + src_reg = src(y1, x2); + out = out + src_reg * ((x - x1) * (y2 - y)); + + src_reg = src(y2, x1); + out = out + src_reg * ((x2 - x) * (y - y1)); + + src_reg = src(y2, x2); + out = out + src_reg * ((x - x1) * (y - y1)); + + return saturate_cast(out); + } + + Ptr2D src; + }; + + template struct CubicFilter + { + typedef typename Ptr2D::elem_type elem_type; + typedef float index_type; + typedef typename TypeVec::cn>::vec_type work_type; + + explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) + : src(src_) + { + CV_UNUSED(fx); + CV_UNUSED(fy); + } + + static __device__ __forceinline__ float bicubicCoeff(float x_) + { + float x = fabsf(x_); + if (x <= 1.0f) + { + return x * x * (1.5f * x - 2.5f) + 1.0f; + } + else if (x < 2.0f) + { + return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f; + } + else + { + return 0.0f; + } + } + + __device__ elem_type operator ()(float y, float x) const + { + const float xmin = ::ceilf(x - 2.0f); + const float xmax = ::floorf(x + 2.0f); + + const float ymin = ::ceilf(y - 2.0f); + const float ymax = ::floorf(y + 2.0f); + + work_type sum = VecTraits::all(0); + float wsum = 0.0f; + + for (float cy = ymin; cy <= ymax; cy += 1.0f) + { + for (float cx = xmin; cx <= xmax; cx += 1.0f) + { + const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy); + sum = sum + w * src(__float2int_rd(cy), __float2int_rd(cx)); + wsum += w; + } + } + + work_type res = (!wsum)? VecTraits::all(0) : sum / wsum; + + return saturate_cast(res); + } + + Ptr2D src; + }; + // for integer scaling + template struct IntegerAreaFilter + { + typedef typename Ptr2D::elem_type elem_type; + typedef float index_type; + + explicit __host__ __device__ __forceinline__ IntegerAreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_) + : src(src_), scale_x(scale_x_), scale_y(scale_y_), scale(1.f / (scale_x * scale_y)) {} + + __device__ __forceinline__ elem_type operator ()(float y, float x) const + { + float fsx1 = x * scale_x; + float fsx2 = fsx1 + scale_x; + + int sx1 = __float2int_ru(fsx1); + int sx2 = __float2int_rd(fsx2); + + float fsy1 = y * scale_y; + float fsy2 = fsy1 + scale_y; + + int sy1 = __float2int_ru(fsy1); + int sy2 = __float2int_rd(fsy2); + + typedef typename TypeVec::cn>::vec_type work_type; + work_type out = VecTraits::all(0.f); + + for(int dy = sy1; dy < sy2; ++dy) + for(int dx = sx1; dx < sx2; ++dx) + { + out = out + src(dy, dx) * scale; + } + + return saturate_cast(out); + } + + Ptr2D src; + float scale_x, scale_y ,scale; + }; + + template struct AreaFilter + { + typedef typename Ptr2D::elem_type elem_type; + typedef float index_type; + + explicit __host__ __device__ __forceinline__ AreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_) + : src(src_), scale_x(scale_x_), scale_y(scale_y_){} + + __device__ __forceinline__ elem_type operator ()(float y, float x) const + { + float fsx1 = x * scale_x; + float fsx2 = fsx1 + scale_x; + + int sx1 = __float2int_ru(fsx1); + int sx2 = __float2int_rd(fsx2); + + float fsy1 = y * scale_y; + float fsy2 = fsy1 + scale_y; + + int sy1 = __float2int_ru(fsy1); + int sy2 = __float2int_rd(fsy2); + + float scale = 1.f / (fminf(scale_x, src.width - fsx1) * fminf(scale_y, src.height - fsy1)); + + typedef typename TypeVec::cn>::vec_type work_type; + work_type out = VecTraits::all(0.f); + + for (int dy = sy1; dy < sy2; ++dy) + { + for (int dx = sx1; dx < sx2; ++dx) + out = out + src(dy, dx) * scale; + + if (sx1 > fsx1) + out = out + src(dy, (sx1 -1) ) * ((sx1 - fsx1) * scale); + + if (sx2 < fsx2) + out = out + src(dy, sx2) * ((fsx2 -sx2) * scale); + } + + if (sy1 > fsy1) + for (int dx = sx1; dx < sx2; ++dx) + out = out + src( (sy1 - 1) , dx) * ((sy1 -fsy1) * scale); + + if (sy2 < fsy2) + for (int dx = sx1; dx < sx2; ++dx) + out = out + src(sy2, dx) * ((fsy2 -sy2) * scale); + + if ((sy1 > fsy1) && (sx1 > fsx1)) + out = out + src( (sy1 - 1) , (sx1 - 1)) * ((sy1 -fsy1) * (sx1 -fsx1) * scale); + + if ((sy1 > fsy1) && (sx2 < fsx2)) + out = out + src( (sy1 - 1) , sx2) * ((sy1 -fsy1) * (fsx2 -sx2) * scale); + + if ((sy2 < fsy2) && (sx2 < fsx2)) + out = out + src(sy2, sx2) * ((fsy2 -sy2) * (fsx2 -sx2) * scale); + + if ((sy2 < fsy2) && (sx1 > fsx1)) + out = out + src(sy2, (sx1 - 1)) * ((fsy2 -sy2) * (sx1 -fsx1) * scale); + + return saturate_cast(out); + } + + Ptr2D src; + float scale_x, scale_y; + int width, haight; + }; +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_FILTERS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/funcattrib.hpp b/3rdparty/opencv/include/opencv2/core/cuda/funcattrib.hpp new file mode 100644 index 00000000..f5820804 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/funcattrib.hpp @@ -0,0 +1,79 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP +#define OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP + +#include + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template + void printFuncAttrib(Func& func) + { + + cudaFuncAttributes attrs; + cudaFuncGetAttributes(&attrs, func); + + printf("=== Function stats ===\n"); + printf("Name: \n"); + printf("sharedSizeBytes = %d\n", attrs.sharedSizeBytes); + printf("constSizeBytes = %d\n", attrs.constSizeBytes); + printf("localSizeBytes = %d\n", attrs.localSizeBytes); + printf("maxThreadsPerBlock = %d\n", attrs.maxThreadsPerBlock); + printf("numRegs = %d\n", attrs.numRegs); + printf("ptxVersion = %d\n", attrs.ptxVersion); + printf("binaryVersion = %d\n", attrs.binaryVersion); + printf("\n"); + fflush(stdout); + } +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif /* OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/functional.hpp b/3rdparty/opencv/include/opencv2/core/cuda/functional.hpp new file mode 100644 index 00000000..3b531a13 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/functional.hpp @@ -0,0 +1,810 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_FUNCTIONAL_HPP +#define OPENCV_CUDA_FUNCTIONAL_HPP + +#include +#include "saturate_cast.hpp" +#include "vec_traits.hpp" +#include "type_traits.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + // Function Objects +#ifdef CV_CXX11 + template struct unary_function + { + typedef Argument argument_type; + typedef Result result_type; + }; + template struct binary_function + { + typedef Argument1 first_argument_type; + typedef Argument2 second_argument_type; + typedef Result result_type; + }; +#else + template struct unary_function : public std::unary_function {}; + template struct binary_function : public std::binary_function {}; +#endif + + // Arithmetic Operations + template struct plus : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a + b; + } + __host__ __device__ __forceinline__ plus() {} + __host__ __device__ __forceinline__ plus(const plus&) {} + }; + + template struct minus : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a - b; + } + __host__ __device__ __forceinline__ minus() {} + __host__ __device__ __forceinline__ minus(const minus&) {} + }; + + template struct multiplies : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a * b; + } + __host__ __device__ __forceinline__ multiplies() {} + __host__ __device__ __forceinline__ multiplies(const multiplies&) {} + }; + + template struct divides : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a / b; + } + __host__ __device__ __forceinline__ divides() {} + __host__ __device__ __forceinline__ divides(const divides&) {} + }; + + template struct modulus : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a % b; + } + __host__ __device__ __forceinline__ modulus() {} + __host__ __device__ __forceinline__ modulus(const modulus&) {} + }; + + template struct negate : unary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a) const + { + return -a; + } + __host__ __device__ __forceinline__ negate() {} + __host__ __device__ __forceinline__ negate(const negate&) {} + }; + + // Comparison Operations + template struct equal_to : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a == b; + } + __host__ __device__ __forceinline__ equal_to() {} + __host__ __device__ __forceinline__ equal_to(const equal_to&) {} + }; + + template struct not_equal_to : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a != b; + } + __host__ __device__ __forceinline__ not_equal_to() {} + __host__ __device__ __forceinline__ not_equal_to(const not_equal_to&) {} + }; + + template struct greater : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a > b; + } + __host__ __device__ __forceinline__ greater() {} + __host__ __device__ __forceinline__ greater(const greater&) {} + }; + + template struct less : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a < b; + } + __host__ __device__ __forceinline__ less() {} + __host__ __device__ __forceinline__ less(const less&) {} + }; + + template struct greater_equal : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a >= b; + } + __host__ __device__ __forceinline__ greater_equal() {} + __host__ __device__ __forceinline__ greater_equal(const greater_equal&) {} + }; + + template struct less_equal : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a <= b; + } + __host__ __device__ __forceinline__ less_equal() {} + __host__ __device__ __forceinline__ less_equal(const less_equal&) {} + }; + + // Logical Operations + template struct logical_and : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a && b; + } + __host__ __device__ __forceinline__ logical_and() {} + __host__ __device__ __forceinline__ logical_and(const logical_and&) {} + }; + + template struct logical_or : binary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a || b; + } + __host__ __device__ __forceinline__ logical_or() {} + __host__ __device__ __forceinline__ logical_or(const logical_or&) {} + }; + + template struct logical_not : unary_function + { + __device__ __forceinline__ bool operator ()(typename TypeTraits::ParameterType a) const + { + return !a; + } + __host__ __device__ __forceinline__ logical_not() {} + __host__ __device__ __forceinline__ logical_not(const logical_not&) {} + }; + + // Bitwise Operations + template struct bit_and : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a & b; + } + __host__ __device__ __forceinline__ bit_and() {} + __host__ __device__ __forceinline__ bit_and(const bit_and&) {} + }; + + template struct bit_or : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a | b; + } + __host__ __device__ __forceinline__ bit_or() {} + __host__ __device__ __forceinline__ bit_or(const bit_or&) {} + }; + + template struct bit_xor : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType a, + typename TypeTraits::ParameterType b) const + { + return a ^ b; + } + __host__ __device__ __forceinline__ bit_xor() {} + __host__ __device__ __forceinline__ bit_xor(const bit_xor&) {} + }; + + template struct bit_not : unary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType v) const + { + return ~v; + } + __host__ __device__ __forceinline__ bit_not() {} + __host__ __device__ __forceinline__ bit_not(const bit_not&) {} + }; + + // Generalized Identity Operations + template struct identity : unary_function + { + __device__ __forceinline__ typename TypeTraits::ParameterType operator()(typename TypeTraits::ParameterType x) const + { + return x; + } + __host__ __device__ __forceinline__ identity() {} + __host__ __device__ __forceinline__ identity(const identity&) {} + }; + + template struct project1st : binary_function + { + __device__ __forceinline__ typename TypeTraits::ParameterType operator()(typename TypeTraits::ParameterType lhs, typename TypeTraits::ParameterType rhs) const + { + return lhs; + } + __host__ __device__ __forceinline__ project1st() {} + __host__ __device__ __forceinline__ project1st(const project1st&) {} + }; + + template struct project2nd : binary_function + { + __device__ __forceinline__ typename TypeTraits::ParameterType operator()(typename TypeTraits::ParameterType lhs, typename TypeTraits::ParameterType rhs) const + { + return rhs; + } + __host__ __device__ __forceinline__ project2nd() {} + __host__ __device__ __forceinline__ project2nd(const project2nd&) {} + }; + + // Min/Max Operations + +#define OPENCV_CUDA_IMPLEMENT_MINMAX(name, type, op) \ + template <> struct name : binary_function \ + { \ + __device__ __forceinline__ type operator()(type lhs, type rhs) const {return op(lhs, rhs);} \ + __host__ __device__ __forceinline__ name() {}\ + __host__ __device__ __forceinline__ name(const name&) {}\ + }; + + template struct maximum : binary_function + { + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType lhs, typename TypeTraits::ParameterType rhs) const + { + return max(lhs, rhs); + } + __host__ __device__ __forceinline__ maximum() {} + __host__ __device__ __forceinline__ maximum(const maximum&) {} + }; + + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, uchar, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, schar, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, char, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, ushort, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, short, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, int, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, uint, ::max) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, float, ::fmax) + OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, double, ::fmax) + + template struct minimum : binary_function + { + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType lhs, typename TypeTraits::ParameterType rhs) const + { + return min(lhs, rhs); + } + __host__ __device__ __forceinline__ minimum() {} + __host__ __device__ __forceinline__ minimum(const minimum&) {} + }; + + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, uchar, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, schar, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, char, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, ushort, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, short, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, int, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, uint, ::min) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, float, ::fmin) + OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, double, ::fmin) + +#undef OPENCV_CUDA_IMPLEMENT_MINMAX + + // Math functions + + template struct abs_func : unary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType x) const + { + return abs(x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ unsigned char operator ()(unsigned char x) const + { + return x; + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ signed char operator ()(signed char x) const + { + return ::abs((int)x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ char operator ()(char x) const + { + return ::abs((int)x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ unsigned short operator ()(unsigned short x) const + { + return x; + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ short operator ()(short x) const + { + return ::abs((int)x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ unsigned int operator ()(unsigned int x) const + { + return x; + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ int operator ()(int x) const + { + return ::abs(x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ float operator ()(float x) const + { + return ::fabsf(x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + template <> struct abs_func : unary_function + { + __device__ __forceinline__ double operator ()(double x) const + { + return ::fabs(x); + } + + __host__ __device__ __forceinline__ abs_func() {} + __host__ __device__ __forceinline__ abs_func(const abs_func&) {} + }; + +#define OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(name, func) \ + template struct name ## _func : unary_function \ + { \ + __device__ __forceinline__ float operator ()(typename TypeTraits::ParameterType v) const \ + { \ + return func ## f(v); \ + } \ + __host__ __device__ __forceinline__ name ## _func() {} \ + __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \ + }; \ + template <> struct name ## _func : unary_function \ + { \ + __device__ __forceinline__ double operator ()(double v) const \ + { \ + return func(v); \ + } \ + __host__ __device__ __forceinline__ name ## _func() {} \ + __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \ + }; + +#define OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(name, func) \ + template struct name ## _func : binary_function \ + { \ + __device__ __forceinline__ float operator ()(typename TypeTraits::ParameterType v1, typename TypeTraits::ParameterType v2) const \ + { \ + return func ## f(v1, v2); \ + } \ + __host__ __device__ __forceinline__ name ## _func() {} \ + __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \ + }; \ + template <> struct name ## _func : binary_function \ + { \ + __device__ __forceinline__ double operator ()(double v1, double v2) const \ + { \ + return func(v1, v2); \ + } \ + __host__ __device__ __forceinline__ name ## _func() {} \ + __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \ + }; + + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sqrt, ::sqrt) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp, ::exp) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp2, ::exp2) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp10, ::exp10) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log, ::log) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log2, ::log2) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log10, ::log10) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sin, ::sin) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(cos, ::cos) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(tan, ::tan) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(asin, ::asin) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(acos, ::acos) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(atan, ::atan) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sinh, ::sinh) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(cosh, ::cosh) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(tanh, ::tanh) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(asinh, ::asinh) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(acosh, ::acosh) + OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(atanh, ::atanh) + + OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(hypot, ::hypot) + OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(atan2, ::atan2) + OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(pow, ::pow) + + #undef OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR + #undef OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR_NO_DOUBLE + #undef OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR + + template struct hypot_sqr_func : binary_function + { + __device__ __forceinline__ T operator ()(typename TypeTraits::ParameterType src1, typename TypeTraits::ParameterType src2) const + { + return src1 * src1 + src2 * src2; + } + __host__ __device__ __forceinline__ hypot_sqr_func() {} + __host__ __device__ __forceinline__ hypot_sqr_func(const hypot_sqr_func&) {} + }; + + // Saturate Cast Functor + template struct saturate_cast_func : unary_function + { + __device__ __forceinline__ D operator ()(typename TypeTraits::ParameterType v) const + { + return saturate_cast(v); + } + __host__ __device__ __forceinline__ saturate_cast_func() {} + __host__ __device__ __forceinline__ saturate_cast_func(const saturate_cast_func&) {} + }; + + // Threshold Functors + template struct thresh_binary_func : unary_function + { + __host__ __device__ __forceinline__ thresh_binary_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {} + + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType src) const + { + return (src > thresh) * maxVal; + } + + __host__ __device__ __forceinline__ thresh_binary_func() {} + __host__ __device__ __forceinline__ thresh_binary_func(const thresh_binary_func& other) + : thresh(other.thresh), maxVal(other.maxVal) {} + + T thresh; + T maxVal; + }; + + template struct thresh_binary_inv_func : unary_function + { + __host__ __device__ __forceinline__ thresh_binary_inv_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {} + + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType src) const + { + return (src <= thresh) * maxVal; + } + + __host__ __device__ __forceinline__ thresh_binary_inv_func() {} + __host__ __device__ __forceinline__ thresh_binary_inv_func(const thresh_binary_inv_func& other) + : thresh(other.thresh), maxVal(other.maxVal) {} + + T thresh; + T maxVal; + }; + + template struct thresh_trunc_func : unary_function + { + explicit __host__ __device__ __forceinline__ thresh_trunc_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);} + + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType src) const + { + return minimum()(src, thresh); + } + + __host__ __device__ __forceinline__ thresh_trunc_func() {} + __host__ __device__ __forceinline__ thresh_trunc_func(const thresh_trunc_func& other) + : thresh(other.thresh) {} + + T thresh; + }; + + template struct thresh_to_zero_func : unary_function + { + explicit __host__ __device__ __forceinline__ thresh_to_zero_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);} + + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType src) const + { + return (src > thresh) * src; + } + + __host__ __device__ __forceinline__ thresh_to_zero_func() {} + __host__ __device__ __forceinline__ thresh_to_zero_func(const thresh_to_zero_func& other) + : thresh(other.thresh) {} + + T thresh; + }; + + template struct thresh_to_zero_inv_func : unary_function + { + explicit __host__ __device__ __forceinline__ thresh_to_zero_inv_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);} + + __device__ __forceinline__ T operator()(typename TypeTraits::ParameterType src) const + { + return (src <= thresh) * src; + } + + __host__ __device__ __forceinline__ thresh_to_zero_inv_func() {} + __host__ __device__ __forceinline__ thresh_to_zero_inv_func(const thresh_to_zero_inv_func& other) + : thresh(other.thresh) {} + + T thresh; + }; + + // Function Object Adaptors + template struct unary_negate : unary_function + { + explicit __host__ __device__ __forceinline__ unary_negate(const Predicate& p) : pred(p) {} + + __device__ __forceinline__ bool operator()(typename TypeTraits::ParameterType x) const + { + return !pred(x); + } + + __host__ __device__ __forceinline__ unary_negate() {} + __host__ __device__ __forceinline__ unary_negate(const unary_negate& other) : pred(other.pred) {} + + Predicate pred; + }; + + template __host__ __device__ __forceinline__ unary_negate not1(const Predicate& pred) + { + return unary_negate(pred); + } + + template struct binary_negate : binary_function + { + explicit __host__ __device__ __forceinline__ binary_negate(const Predicate& p) : pred(p) {} + + __device__ __forceinline__ bool operator()(typename TypeTraits::ParameterType x, + typename TypeTraits::ParameterType y) const + { + return !pred(x,y); + } + + __host__ __device__ __forceinline__ binary_negate() {} + __host__ __device__ __forceinline__ binary_negate(const binary_negate& other) : pred(other.pred) {} + + Predicate pred; + }; + + template __host__ __device__ __forceinline__ binary_negate not2(const BinaryPredicate& pred) + { + return binary_negate(pred); + } + + template struct binder1st : unary_function + { + __host__ __device__ __forceinline__ binder1st(const Op& op_, const typename Op::first_argument_type& arg1_) : op(op_), arg1(arg1_) {} + + __device__ __forceinline__ typename Op::result_type operator ()(typename TypeTraits::ParameterType a) const + { + return op(arg1, a); + } + + __host__ __device__ __forceinline__ binder1st() {} + __host__ __device__ __forceinline__ binder1st(const binder1st& other) : op(other.op), arg1(other.arg1) {} + + Op op; + typename Op::first_argument_type arg1; + }; + + template __host__ __device__ __forceinline__ binder1st bind1st(const Op& op, const T& x) + { + return binder1st(op, typename Op::first_argument_type(x)); + } + + template struct binder2nd : unary_function + { + __host__ __device__ __forceinline__ binder2nd(const Op& op_, const typename Op::second_argument_type& arg2_) : op(op_), arg2(arg2_) {} + + __forceinline__ __device__ typename Op::result_type operator ()(typename TypeTraits::ParameterType a) const + { + return op(a, arg2); + } + + __host__ __device__ __forceinline__ binder2nd() {} + __host__ __device__ __forceinline__ binder2nd(const binder2nd& other) : op(other.op), arg2(other.arg2) {} + + Op op; + typename Op::second_argument_type arg2; + }; + + template __host__ __device__ __forceinline__ binder2nd bind2nd(const Op& op, const T& x) + { + return binder2nd(op, typename Op::second_argument_type(x)); + } + + // Functor Traits + template struct IsUnaryFunction + { + typedef char Yes; + struct No {Yes a[2];}; + + template static Yes check(unary_function); + static No check(...); + + static F makeF(); + + enum { value = (sizeof(check(makeF())) == sizeof(Yes)) }; + }; + + template struct IsBinaryFunction + { + typedef char Yes; + struct No {Yes a[2];}; + + template static Yes check(binary_function); + static No check(...); + + static F makeF(); + + enum { value = (sizeof(check(makeF())) == sizeof(Yes)) }; + }; + + namespace functional_detail + { + template struct UnOpShift { enum { shift = 1 }; }; + template struct UnOpShift { enum { shift = 4 }; }; + template struct UnOpShift { enum { shift = 2 }; }; + + template struct DefaultUnaryShift + { + enum { shift = UnOpShift::shift }; + }; + + template struct BinOpShift { enum { shift = 1 }; }; + template struct BinOpShift { enum { shift = 4 }; }; + template struct BinOpShift { enum { shift = 2 }; }; + + template struct DefaultBinaryShift + { + enum { shift = BinOpShift::shift }; + }; + + template ::value> struct ShiftDispatcher; + template struct ShiftDispatcher + { + enum { shift = DefaultUnaryShift::shift }; + }; + template struct ShiftDispatcher + { + enum { shift = DefaultBinaryShift::shift }; + }; + } + + template struct DefaultTransformShift + { + enum { shift = functional_detail::ShiftDispatcher::shift }; + }; + + template struct DefaultTransformFunctorTraits + { + enum { simple_block_dim_x = 16 }; + enum { simple_block_dim_y = 16 }; + + enum { smart_block_dim_x = 16 }; + enum { smart_block_dim_y = 16 }; + enum { smart_shift = DefaultTransformShift::shift }; + }; + + template struct TransformFunctorTraits : DefaultTransformFunctorTraits {}; + +#define OPENCV_CUDA_TRANSFORM_FUNCTOR_TRAITS(type) \ + template <> struct TransformFunctorTraits< type > : DefaultTransformFunctorTraits< type > +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_FUNCTIONAL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/limits.hpp b/3rdparty/opencv/include/opencv2/core/cuda/limits.hpp new file mode 100644 index 00000000..7e15ed62 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/limits.hpp @@ -0,0 +1,128 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_LIMITS_HPP +#define OPENCV_CUDA_LIMITS_HPP + +#include +#include +#include "common.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ +template struct numeric_limits; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static bool min() { return false; } + __device__ __forceinline__ static bool max() { return true; } + static const bool is_signed = false; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static signed char min() { return SCHAR_MIN; } + __device__ __forceinline__ static signed char max() { return SCHAR_MAX; } + static const bool is_signed = true; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static unsigned char min() { return 0; } + __device__ __forceinline__ static unsigned char max() { return UCHAR_MAX; } + static const bool is_signed = false; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static short min() { return SHRT_MIN; } + __device__ __forceinline__ static short max() { return SHRT_MAX; } + static const bool is_signed = true; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static unsigned short min() { return 0; } + __device__ __forceinline__ static unsigned short max() { return USHRT_MAX; } + static const bool is_signed = false; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static int min() { return INT_MIN; } + __device__ __forceinline__ static int max() { return INT_MAX; } + static const bool is_signed = true; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static unsigned int min() { return 0; } + __device__ __forceinline__ static unsigned int max() { return UINT_MAX; } + static const bool is_signed = false; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static float min() { return FLT_MIN; } + __device__ __forceinline__ static float max() { return FLT_MAX; } + __device__ __forceinline__ static float epsilon() { return FLT_EPSILON; } + static const bool is_signed = true; +}; + +template <> struct numeric_limits +{ + __device__ __forceinline__ static double min() { return DBL_MIN; } + __device__ __forceinline__ static double max() { return DBL_MAX; } + __device__ __forceinline__ static double epsilon() { return DBL_EPSILON; } + static const bool is_signed = true; +}; +}}} // namespace cv { namespace cuda { namespace cudev { + +//! @endcond + +#endif // OPENCV_CUDA_LIMITS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/reduce.hpp b/3rdparty/opencv/include/opencv2/core/cuda/reduce.hpp new file mode 100644 index 00000000..5de36508 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/reduce.hpp @@ -0,0 +1,209 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_REDUCE_HPP +#define OPENCV_CUDA_REDUCE_HPP + +#ifndef THRUST_DEBUG // eliminate -Wundef warning +#define THRUST_DEBUG 0 +#endif + +#include +#include "detail/reduce.hpp" +#include "detail/reduce_key_val.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template + __device__ __forceinline__ void reduce(volatile T* smem, T& val, unsigned int tid, const Op& op) + { + reduce_detail::Dispatcher::reductor::template reduce(smem, val, tid, op); + } + template + __device__ __forceinline__ void reduce(const thrust::tuple& smem, + const thrust::tuple& val, + unsigned int tid, + const thrust::tuple& op) + { + reduce_detail::Dispatcher::reductor::template reduce< + const thrust::tuple&, + const thrust::tuple&, + const thrust::tuple&>(smem, val, tid, op); + } + + template + __device__ __forceinline__ void reduceKeyVal(volatile K* skeys, K& key, volatile V* svals, V& val, unsigned int tid, const Cmp& cmp) + { + reduce_key_val_detail::Dispatcher::reductor::template reduce(skeys, key, svals, val, tid, cmp); + } + template + __device__ __forceinline__ void reduceKeyVal(volatile K* skeys, K& key, + const thrust::tuple& svals, + const thrust::tuple& val, + unsigned int tid, const Cmp& cmp) + { + reduce_key_val_detail::Dispatcher::reductor::template reduce&, + const thrust::tuple&, + const Cmp&>(skeys, key, svals, val, tid, cmp); + } + template + __device__ __forceinline__ void reduceKeyVal(const thrust::tuple& skeys, + const thrust::tuple& key, + const thrust::tuple& svals, + const thrust::tuple& val, + unsigned int tid, + const thrust::tuple& cmp) + { + reduce_key_val_detail::Dispatcher::reductor::template reduce< + const thrust::tuple&, + const thrust::tuple&, + const thrust::tuple&, + const thrust::tuple&, + const thrust::tuple& + >(skeys, key, svals, val, tid, cmp); + } + + // smem_tuple + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0) + { + return thrust::make_tuple((volatile T0*) t0); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7, T8* t8) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7, (volatile T8*) t8); + } + + template + __device__ __forceinline__ + thrust::tuple + smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7, T8* t8, T9* t9) + { + return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7, (volatile T8*) t8, (volatile T9*) t9); + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_REDUCE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/saturate_cast.hpp b/3rdparty/opencv/include/opencv2/core/cuda/saturate_cast.hpp new file mode 100644 index 00000000..c3a3d1cb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/saturate_cast.hpp @@ -0,0 +1,292 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_SATURATE_CAST_HPP +#define OPENCV_CUDA_SATURATE_CAST_HPP + +#include "common.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template __device__ __forceinline__ _Tp saturate_cast(uchar v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(schar v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(ushort v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(short v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(uint v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(int v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(float v) { return _Tp(v); } + template __device__ __forceinline__ _Tp saturate_cast(double v) { return _Tp(v); } + + template<> __device__ __forceinline__ uchar saturate_cast(schar v) + { + uint res = 0; + int vi = v; + asm("cvt.sat.u8.s8 %0, %1;" : "=r"(res) : "r"(vi)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(short v) + { + uint res = 0; + asm("cvt.sat.u8.s16 %0, %1;" : "=r"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(ushort v) + { + uint res = 0; + asm("cvt.sat.u8.u16 %0, %1;" : "=r"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(int v) + { + uint res = 0; + asm("cvt.sat.u8.s32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(uint v) + { + uint res = 0; + asm("cvt.sat.u8.u32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(float v) + { + uint res = 0; + asm("cvt.rni.sat.u8.f32 %0, %1;" : "=r"(res) : "f"(v)); + return res; + } + template<> __device__ __forceinline__ uchar saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + uint res = 0; + asm("cvt.rni.sat.u8.f64 %0, %1;" : "=r"(res) : "d"(v)); + return res; + #else + return saturate_cast((float)v); + #endif + } + + template<> __device__ __forceinline__ schar saturate_cast(uchar v) + { + uint res = 0; + uint vi = v; + asm("cvt.sat.s8.u8 %0, %1;" : "=r"(res) : "r"(vi)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(short v) + { + uint res = 0; + asm("cvt.sat.s8.s16 %0, %1;" : "=r"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(ushort v) + { + uint res = 0; + asm("cvt.sat.s8.u16 %0, %1;" : "=r"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(int v) + { + uint res = 0; + asm("cvt.sat.s8.s32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(uint v) + { + uint res = 0; + asm("cvt.sat.s8.u32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(float v) + { + uint res = 0; + asm("cvt.rni.sat.s8.f32 %0, %1;" : "=r"(res) : "f"(v)); + return res; + } + template<> __device__ __forceinline__ schar saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + uint res = 0; + asm("cvt.rni.sat.s8.f64 %0, %1;" : "=r"(res) : "d"(v)); + return res; + #else + return saturate_cast((float)v); + #endif + } + + template<> __device__ __forceinline__ ushort saturate_cast(schar v) + { + ushort res = 0; + int vi = v; + asm("cvt.sat.u16.s8 %0, %1;" : "=h"(res) : "r"(vi)); + return res; + } + template<> __device__ __forceinline__ ushort saturate_cast(short v) + { + ushort res = 0; + asm("cvt.sat.u16.s16 %0, %1;" : "=h"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ ushort saturate_cast(int v) + { + ushort res = 0; + asm("cvt.sat.u16.s32 %0, %1;" : "=h"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ ushort saturate_cast(uint v) + { + ushort res = 0; + asm("cvt.sat.u16.u32 %0, %1;" : "=h"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ ushort saturate_cast(float v) + { + ushort res = 0; + asm("cvt.rni.sat.u16.f32 %0, %1;" : "=h"(res) : "f"(v)); + return res; + } + template<> __device__ __forceinline__ ushort saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + ushort res = 0; + asm("cvt.rni.sat.u16.f64 %0, %1;" : "=h"(res) : "d"(v)); + return res; + #else + return saturate_cast((float)v); + #endif + } + + template<> __device__ __forceinline__ short saturate_cast(ushort v) + { + short res = 0; + asm("cvt.sat.s16.u16 %0, %1;" : "=h"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ short saturate_cast(int v) + { + short res = 0; + asm("cvt.sat.s16.s32 %0, %1;" : "=h"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ short saturate_cast(uint v) + { + short res = 0; + asm("cvt.sat.s16.u32 %0, %1;" : "=h"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ short saturate_cast(float v) + { + short res = 0; + asm("cvt.rni.sat.s16.f32 %0, %1;" : "=h"(res) : "f"(v)); + return res; + } + template<> __device__ __forceinline__ short saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + short res = 0; + asm("cvt.rni.sat.s16.f64 %0, %1;" : "=h"(res) : "d"(v)); + return res; + #else + return saturate_cast((float)v); + #endif + } + + template<> __device__ __forceinline__ int saturate_cast(uint v) + { + int res = 0; + asm("cvt.sat.s32.u32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ int saturate_cast(float v) + { + return __float2int_rn(v); + } + template<> __device__ __forceinline__ int saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + return __double2int_rn(v); + #else + return saturate_cast((float)v); + #endif + } + + template<> __device__ __forceinline__ uint saturate_cast(schar v) + { + uint res = 0; + int vi = v; + asm("cvt.sat.u32.s8 %0, %1;" : "=r"(res) : "r"(vi)); + return res; + } + template<> __device__ __forceinline__ uint saturate_cast(short v) + { + uint res = 0; + asm("cvt.sat.u32.s16 %0, %1;" : "=r"(res) : "h"(v)); + return res; + } + template<> __device__ __forceinline__ uint saturate_cast(int v) + { + uint res = 0; + asm("cvt.sat.u32.s32 %0, %1;" : "=r"(res) : "r"(v)); + return res; + } + template<> __device__ __forceinline__ uint saturate_cast(float v) + { + return __float2uint_rn(v); + } + template<> __device__ __forceinline__ uint saturate_cast(double v) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130 + return __double2uint_rn(v); + #else + return saturate_cast((float)v); + #endif + } +}}} + +//! @endcond + +#endif /* OPENCV_CUDA_SATURATE_CAST_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/scan.hpp b/3rdparty/opencv/include/opencv2/core/cuda/scan.hpp new file mode 100644 index 00000000..e128fb09 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/scan.hpp @@ -0,0 +1,258 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_SCAN_HPP +#define OPENCV_CUDA_SCAN_HPP + +#include "opencv2/core/cuda/common.hpp" +#include "opencv2/core/cuda/utility.hpp" +#include "opencv2/core/cuda/warp.hpp" +#include "opencv2/core/cuda/warp_shuffle.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + enum ScanKind { EXCLUSIVE = 0, INCLUSIVE = 1 }; + + template struct WarpScan + { + __device__ __forceinline__ WarpScan() {} + __device__ __forceinline__ WarpScan(const WarpScan& other) { CV_UNUSED(other); } + + __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx) + { + const unsigned int lane = idx & 31; + F op; + + if ( lane >= 1) ptr [idx ] = op(ptr [idx - 1], ptr [idx]); + if ( lane >= 2) ptr [idx ] = op(ptr [idx - 2], ptr [idx]); + if ( lane >= 4) ptr [idx ] = op(ptr [idx - 4], ptr [idx]); + if ( lane >= 8) ptr [idx ] = op(ptr [idx - 8], ptr [idx]); + if ( lane >= 16) ptr [idx ] = op(ptr [idx - 16], ptr [idx]); + + if( Kind == INCLUSIVE ) + return ptr [idx]; + else + return (lane > 0) ? ptr [idx - 1] : 0; + } + + __device__ __forceinline__ unsigned int index(const unsigned int tid) + { + return tid; + } + + __device__ __forceinline__ void init(volatile T *ptr){} + + static const int warp_offset = 0; + + typedef WarpScan merge; + }; + + template struct WarpScanNoComp + { + __device__ __forceinline__ WarpScanNoComp() {} + __device__ __forceinline__ WarpScanNoComp(const WarpScanNoComp& other) { CV_UNUSED(other); } + + __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx) + { + const unsigned int lane = threadIdx.x & 31; + F op; + + ptr [idx ] = op(ptr [idx - 1], ptr [idx]); + ptr [idx ] = op(ptr [idx - 2], ptr [idx]); + ptr [idx ] = op(ptr [idx - 4], ptr [idx]); + ptr [idx ] = op(ptr [idx - 8], ptr [idx]); + ptr [idx ] = op(ptr [idx - 16], ptr [idx]); + + if( Kind == INCLUSIVE ) + return ptr [idx]; + else + return (lane > 0) ? ptr [idx - 1] : 0; + } + + __device__ __forceinline__ unsigned int index(const unsigned int tid) + { + return (tid >> warp_log) * warp_smem_stride + 16 + (tid & warp_mask); + } + + __device__ __forceinline__ void init(volatile T *ptr) + { + ptr[threadIdx.x] = 0; + } + + static const int warp_smem_stride = 32 + 16 + 1; + static const int warp_offset = 16; + static const int warp_log = 5; + static const int warp_mask = 31; + + typedef WarpScanNoComp merge; + }; + + template struct BlockScan + { + __device__ __forceinline__ BlockScan() {} + __device__ __forceinline__ BlockScan(const BlockScan& other) { CV_UNUSED(other); } + + __device__ __forceinline__ T operator()(volatile T *ptr) + { + const unsigned int tid = threadIdx.x; + const unsigned int lane = tid & warp_mask; + const unsigned int warp = tid >> warp_log; + + Sc scan; + typename Sc::merge merge_scan; + const unsigned int idx = scan.index(tid); + + T val = scan(ptr, idx); + __syncthreads (); + + if( warp == 0) + scan.init(ptr); + __syncthreads (); + + if( lane == 31 ) + ptr [scan.warp_offset + warp ] = (Kind == INCLUSIVE) ? val : ptr [idx]; + __syncthreads (); + + if( warp == 0 ) + merge_scan(ptr, idx); + __syncthreads(); + + if ( warp > 0) + val = ptr [scan.warp_offset + warp - 1] + val; + __syncthreads (); + + ptr[idx] = val; + __syncthreads (); + + return val ; + } + + static const int warp_log = 5; + static const int warp_mask = 31; + }; + + template + __device__ T warpScanInclusive(T idata, volatile T* s_Data, unsigned int tid) + { + #if __CUDA_ARCH__ >= 300 + const unsigned int laneId = cv::cuda::device::Warp::laneId(); + + // scan on shuffl functions + #pragma unroll + for (int i = 1; i <= (OPENCV_CUDA_WARP_SIZE / 2); i *= 2) + { + const T n = cv::cuda::device::shfl_up(idata, i); + if (laneId >= i) + idata += n; + } + + return idata; + #else + unsigned int pos = 2 * tid - (tid & (OPENCV_CUDA_WARP_SIZE - 1)); + s_Data[pos] = 0; + pos += OPENCV_CUDA_WARP_SIZE; + s_Data[pos] = idata; + + s_Data[pos] += s_Data[pos - 1]; + s_Data[pos] += s_Data[pos - 2]; + s_Data[pos] += s_Data[pos - 4]; + s_Data[pos] += s_Data[pos - 8]; + s_Data[pos] += s_Data[pos - 16]; + + return s_Data[pos]; + #endif + } + + template + __device__ __forceinline__ T warpScanExclusive(T idata, volatile T* s_Data, unsigned int tid) + { + return warpScanInclusive(idata, s_Data, tid) - idata; + } + + template + __device__ T blockScanInclusive(T idata, volatile T* s_Data, unsigned int tid) + { + if (tiNumScanThreads > OPENCV_CUDA_WARP_SIZE) + { + //Bottom-level inclusive warp scan + T warpResult = warpScanInclusive(idata, s_Data, tid); + + //Save top elements of each warp for exclusive warp scan + //sync to wait for warp scans to complete (because s_Data is being overwritten) + __syncthreads(); + if ((tid & (OPENCV_CUDA_WARP_SIZE - 1)) == (OPENCV_CUDA_WARP_SIZE - 1)) + { + s_Data[tid >> OPENCV_CUDA_LOG_WARP_SIZE] = warpResult; + } + + //wait for warp scans to complete + __syncthreads(); + + if (tid < (tiNumScanThreads / OPENCV_CUDA_WARP_SIZE) ) + { + //grab top warp elements + T val = s_Data[tid]; + //calculate exclusive scan and write back to shared memory + s_Data[tid] = warpScanExclusive(val, s_Data, tid); + } + + //return updated warp scans with exclusive scan results + __syncthreads(); + + return warpResult + s_Data[tid >> OPENCV_CUDA_LOG_WARP_SIZE]; + } + else + { + return warpScanInclusive(idata, s_Data, tid); + } + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_SCAN_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/simd_functions.hpp b/3rdparty/opencv/include/opencv2/core/cuda/simd_functions.hpp new file mode 100644 index 00000000..3d8c2e0d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/simd_functions.hpp @@ -0,0 +1,869 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +/* + * Copyright (c) 2013 NVIDIA Corporation. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions are met: + * + * Redistributions of source code must retain the above copyright notice, + * this list of conditions and the following disclaimer. + * + * Redistributions in binary form must reproduce the above copyright notice, + * this list of conditions and the following disclaimer in the documentation + * and/or other materials provided with the distribution. + * + * Neither the name of NVIDIA Corporation nor the names of its contributors + * may be used to endorse or promote products derived from this software + * without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" + * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE + * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE + * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS + * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN + * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) + * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + * POSSIBILITY OF SUCH DAMAGE. + */ + +#ifndef OPENCV_CUDA_SIMD_FUNCTIONS_HPP +#define OPENCV_CUDA_SIMD_FUNCTIONS_HPP + +#include "common.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + // 2 + + static __device__ __forceinline__ unsigned int vadd2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vadd2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vadd.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vadd.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s; + s = a ^ b; // sum bits + r = a + b; // actual sum + s = s ^ r; // determine carry-ins for each bit position + s = s & 0x00010000; // carry-in to high word (= carry-out from low word) + r = r - s; // subtract out carry-out from low word + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsub2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vsub2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vsub.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vsub.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s; + s = a ^ b; // sum bits + r = a - b; // actual sum + s = s ^ r; // determine carry-ins for each bit position + s = s & 0x00010000; // borrow to high word + r = r + s; // compensate for borrow from low word + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vabsdiff2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vabsdiff2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vabsdiff.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vabsdiff.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s, t, u, v; + s = a & 0x0000ffff; // extract low halfword + r = b & 0x0000ffff; // extract low halfword + u = ::max(r, s); // maximum of low halfwords + v = ::min(r, s); // minimum of low halfwords + s = a & 0xffff0000; // extract high halfword + r = b & 0xffff0000; // extract high halfword + t = ::max(r, s); // maximum of high halfwords + s = ::min(r, s); // minimum of high halfwords + r = u | t; // maximum of both halfwords + s = v | s; // minimum of both halfwords + r = r - s; // |a - b| = max(a,b) - min(a,b); + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vavg2(unsigned int a, unsigned int b) + { + unsigned int r, s; + + // HAKMEM #23: a + b = 2 * (a & b) + (a ^ b) ==> + // (a + b) / 2 = (a & b) + ((a ^ b) >> 1) + s = a ^ b; + r = a & b; + s = s & 0xfffefffe; // ensure shift doesn't cross halfword boundaries + s = s >> 1; + s = r + s; + + return s; + } + + static __device__ __forceinline__ unsigned int vavrg2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vavrg2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // HAKMEM #23: a + b = 2 * (a | b) - (a ^ b) ==> + // (a + b + 1) / 2 = (a | b) - ((a ^ b) >> 1) + unsigned int s; + s = a ^ b; + r = a | b; + s = s & 0xfffefffe; // ensure shift doesn't cross half-word boundaries + s = s >> 1; + r = r - s; + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vseteq2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset2.u32.u32.eq %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + unsigned int c; + r = a ^ b; // 0x0000 if a == b + c = r | 0x80008000; // set msbs, to catch carry out + r = r ^ c; // extract msbs, msb = 1 if r < 0x8000 + c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000 + c = r & ~c; // msb = 1, if r was 0x0000 + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpeq2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vseteq2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + r = a ^ b; // 0x0000 if a == b + c = r | 0x80008000; // set msbs, to catch carry out + r = r ^ c; // extract msbs, msb = 1 if r < 0x8000 + c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000 + c = r & ~c; // msb = 1, if r was 0x0000 + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetge2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset2.u32.u32.ge %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavrg2(a, b); // (a + ~b + 1) / 2 = (a - b) / 2 + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpge2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetge2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavrg2(a, b); // (a + ~b + 1) / 2 = (a - b) / 2 + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetgt2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset2.u32.u32.gt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavg2(a, b); // (a + ~b) / 2 = (a - b) / 2 [rounded down] + c = c & 0x80008000; // msbs = carry-outs + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpgt2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetgt2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavg2(a, b); // (a + ~b) / 2 = (a - b) / 2 [rounded down] + c = c & 0x80008000; // msbs = carry-outs + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetle2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset2.u32.u32.le %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavrg2(a, b); // (b + ~a + 1) / 2 = (b - a) / 2 + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmple2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetle2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavrg2(a, b); // (b + ~a + 1) / 2 = (b - a) / 2 + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetlt2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset2.u32.u32.lt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavg2(a, b); // (b + ~a) / 2 = (b - a) / 2 [rounded down] + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmplt2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetlt2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavg2(a, b); // (b + ~a) / 2 = (b - a) / 2 [rounded down] + c = c & 0x80008000; // msb = carry-outs + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetne2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm ("vset2.u32.u32.ne %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + unsigned int c; + r = a ^ b; // 0x0000 if a == b + c = r | 0x80008000; // set msbs, to catch carry out + c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000 + c = r | c; // msb = 1, if r was not 0x0000 + c = c & 0x80008000; // extract msbs + r = c >> 15; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpne2(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetne2(a, b); + c = r << 16; // convert bool + r = c - r; // into mask + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + r = a ^ b; // 0x0000 if a == b + c = r | 0x80008000; // set msbs, to catch carry out + c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000 + c = r | c; // msb = 1, if r was not 0x0000 + c = c & 0x80008000; // extract msbs + r = c >> 15; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vmax2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vmax2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vmax.u32.u32.u32 %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmax.u32.u32.u32 %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s, t, u; + r = a & 0x0000ffff; // extract low halfword + s = b & 0x0000ffff; // extract low halfword + t = ::max(r, s); // maximum of low halfwords + r = a & 0xffff0000; // extract high halfword + s = b & 0xffff0000; // extract high halfword + u = ::max(r, s); // maximum of high halfwords + r = t | u; // combine halfword maximums + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vmin2(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vmin2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vmin.u32.u32.u32 %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmin.u32.u32.u32 %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s, t, u; + r = a & 0x0000ffff; // extract low halfword + s = b & 0x0000ffff; // extract low halfword + t = ::min(r, s); // minimum of low halfwords + r = a & 0xffff0000; // extract high halfword + s = b & 0xffff0000; // extract high halfword + u = ::min(r, s); // minimum of high halfwords + r = t | u; // combine halfword minimums + #endif + + return r; + } + + // 4 + + static __device__ __forceinline__ unsigned int vadd4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vadd4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vadd.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vadd.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vadd.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vadd.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s, t; + s = a ^ b; // sum bits + r = a & 0x7f7f7f7f; // clear msbs + t = b & 0x7f7f7f7f; // clear msbs + s = s & 0x80808080; // msb sum bits + r = r + t; // add without msbs, record carry-out in msbs + r = r ^ s; // sum of msb sum and carry-in bits, w/o carry-out + #endif /* __CUDA_ARCH__ >= 300 */ + + return r; + } + + static __device__ __forceinline__ unsigned int vsub4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vsub4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vsub.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vsub.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vsub.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vsub.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s, t; + s = a ^ ~b; // inverted sum bits + r = a | 0x80808080; // set msbs + t = b & 0x7f7f7f7f; // clear msbs + s = s & 0x80808080; // inverted msb sum bits + r = r - t; // subtract w/o msbs, record inverted borrows in msb + r = r ^ s; // combine inverted msb sum bits and borrows + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vavg4(unsigned int a, unsigned int b) + { + unsigned int r, s; + + // HAKMEM #23: a + b = 2 * (a & b) + (a ^ b) ==> + // (a + b) / 2 = (a & b) + ((a ^ b) >> 1) + s = a ^ b; + r = a & b; + s = s & 0xfefefefe; // ensure following shift doesn't cross byte boundaries + s = s >> 1; + s = r + s; + + return s; + } + + static __device__ __forceinline__ unsigned int vavrg4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vavrg4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // HAKMEM #23: a + b = 2 * (a | b) - (a ^ b) ==> + // (a + b + 1) / 2 = (a | b) - ((a ^ b) >> 1) + unsigned int c; + c = a ^ b; + r = a | b; + c = c & 0xfefefefe; // ensure following shift doesn't cross byte boundaries + c = c >> 1; + r = r - c; + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vseteq4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.eq %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + unsigned int c; + r = a ^ b; // 0x00 if a == b + c = r | 0x80808080; // set msbs, to catch carry out + r = r ^ c; // extract msbs, msb = 1 if r < 0x80 + c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80 + c = r & ~c; // msb = 1, if r was 0x00 + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpeq4(unsigned int a, unsigned int b) + { + unsigned int r, t; + + #if __CUDA_ARCH__ >= 300 + r = vseteq4(a, b); + t = r << 8; // convert bool + r = t - r; // to mask + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + t = a ^ b; // 0x00 if a == b + r = t | 0x80808080; // set msbs, to catch carry out + t = t ^ r; // extract msbs, msb = 1 if t < 0x80 + r = r - 0x01010101; // msb = 0, if t was 0x00 or 0x80 + r = t & ~r; // msb = 1, if t was 0x00 + t = r >> 7; // build mask + t = r - t; // from + r = t | r; // msbs + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetle4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.le %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavrg4(a, b); // (b + ~a + 1) / 2 = (b - a) / 2 + c = c & 0x80808080; // msb = carry-outs + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmple4(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetle4(a, b); + c = r << 8; // convert bool + r = c - r; // to mask + #else + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavrg4(a, b); // (b + ~a + 1) / 2 = (b - a) / 2 + c = c & 0x80808080; // msbs = carry-outs + r = c >> 7; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetlt4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.lt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavg4(a, b); // (b + ~a) / 2 = (b - a) / 2 [rounded down] + c = c & 0x80808080; // msb = carry-outs + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmplt4(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetlt4(a, b); + c = r << 8; // convert bool + r = c - r; // to mask + #else + asm("not.b32 %0, %0;" : "+r"(a)); + c = vavg4(a, b); // (b + ~a) / 2 = (b - a) / 2 [rounded down] + c = c & 0x80808080; // msbs = carry-outs + r = c >> 7; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetge4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.ge %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavrg4(a, b); // (a + ~b + 1) / 2 = (a - b) / 2 + c = c & 0x80808080; // msb = carry-outs + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpge4(unsigned int a, unsigned int b) + { + unsigned int r, s; + + #if __CUDA_ARCH__ >= 300 + r = vsetge4(a, b); + s = r << 8; // convert bool + r = s - r; // to mask + #else + asm ("not.b32 %0,%0;" : "+r"(b)); + r = vavrg4 (a, b); // (a + ~b + 1) / 2 = (a - b) / 2 + r = r & 0x80808080; // msb = carry-outs + s = r >> 7; // build mask + s = r - s; // from + r = s | r; // msbs + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetgt4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.gt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int c; + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavg4(a, b); // (a + ~b) / 2 = (a - b) / 2 [rounded down] + c = c & 0x80808080; // msb = carry-outs + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpgt4(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetgt4(a, b); + c = r << 8; // convert bool + r = c - r; // to mask + #else + asm("not.b32 %0, %0;" : "+r"(b)); + c = vavg4(a, b); // (a + ~b) / 2 = (a - b) / 2 [rounded down] + c = c & 0x80808080; // msb = carry-outs + r = c >> 7; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vsetne4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vset4.u32.u32.ne %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + unsigned int c; + r = a ^ b; // 0x00 if a == b + c = r | 0x80808080; // set msbs, to catch carry out + c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80 + c = r | c; // msb = 1, if r was not 0x00 + c = c & 0x80808080; // extract msbs + r = c >> 7; // convert to bool + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vcmpne4(unsigned int a, unsigned int b) + { + unsigned int r, c; + + #if __CUDA_ARCH__ >= 300 + r = vsetne4(a, b); + c = r << 8; // convert bool + r = c - r; // to mask + #else + // inspired by Alan Mycroft's null-byte detection algorithm: + // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080)) + r = a ^ b; // 0x00 if a == b + c = r | 0x80808080; // set msbs, to catch carry out + c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80 + c = r | c; // msb = 1, if r was not 0x00 + c = c & 0x80808080; // extract msbs + r = c >> 7; // convert + r = c - r; // msbs to + r = c | r; // mask + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vabsdiff4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vabsdiff4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vabsdiff.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vabsdiff.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vabsdiff.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vabsdiff.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s; + s = vcmpge4(a, b); // mask = 0xff if a >= b + r = a ^ b; // + s = (r & s) ^ b; // select a when a >= b, else select b => max(a,b) + r = s ^ r; // select a when b >= a, else select b => min(a,b) + r = s - r; // |a - b| = max(a,b) - min(a,b); + #endif + + return r; + } + + static __device__ __forceinline__ unsigned int vmax4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vmax4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vmax.u32.u32.u32 %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmax.u32.u32.u32 %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmax.u32.u32.u32 %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmax.u32.u32.u32 %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s; + s = vcmpge4(a, b); // mask = 0xff if a >= b + r = a & s; // select a when b >= a + s = b & ~s; // select b when b < a + r = r | s; // combine byte selections + #endif + + return r; // byte-wise unsigned maximum + } + + static __device__ __forceinline__ unsigned int vmin4(unsigned int a, unsigned int b) + { + unsigned int r = 0; + + #if __CUDA_ARCH__ >= 300 + asm("vmin4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #elif __CUDA_ARCH__ >= 200 + asm("vmin.u32.u32.u32 %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmin.u32.u32.u32 %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmin.u32.u32.u32 %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + asm("vmin.u32.u32.u32 %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r)); + #else + unsigned int s; + s = vcmpge4(b, a); // mask = 0xff if a >= b + r = a & s; // select a when b >= a + s = b & ~s; // select b when b < a + r = r | s; // combine byte selections + #endif + + return r; + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_SIMD_FUNCTIONS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/transform.hpp b/3rdparty/opencv/include/opencv2/core/cuda/transform.hpp new file mode 100644 index 00000000..42aa6ea1 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/transform.hpp @@ -0,0 +1,75 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_TRANSFORM_HPP +#define OPENCV_CUDA_TRANSFORM_HPP + +#include "common.hpp" +#include "utility.hpp" +#include "detail/transform_detail.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template + static inline void transform(PtrStepSz src, PtrStepSz dst, UnOp op, const Mask& mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + transform_detail::TransformDispatcher::cn == 1 && VecTraits::cn == 1 && ft::smart_shift != 1>::call(src, dst, op, mask, stream); + } + + template + static inline void transform(PtrStepSz src1, PtrStepSz src2, PtrStepSz dst, BinOp op, const Mask& mask, cudaStream_t stream) + { + typedef TransformFunctorTraits ft; + transform_detail::TransformDispatcher::cn == 1 && VecTraits::cn == 1 && VecTraits::cn == 1 && ft::smart_shift != 1>::call(src1, src2, dst, op, mask, stream); + } +}}} + +//! @endcond + +#endif // OPENCV_CUDA_TRANSFORM_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/type_traits.hpp b/3rdparty/opencv/include/opencv2/core/cuda/type_traits.hpp new file mode 100644 index 00000000..8b7a3fd1 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/type_traits.hpp @@ -0,0 +1,90 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_TYPE_TRAITS_HPP +#define OPENCV_CUDA_TYPE_TRAITS_HPP + +#include "detail/type_traits_detail.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template struct IsSimpleParameter + { + enum {value = type_traits_detail::IsIntegral::value || type_traits_detail::IsFloat::value || + type_traits_detail::PointerTraits::type>::value}; + }; + + template struct TypeTraits + { + typedef typename type_traits_detail::UnConst::type NonConstType; + typedef typename type_traits_detail::UnVolatile::type NonVolatileType; + typedef typename type_traits_detail::UnVolatile::type>::type UnqualifiedType; + typedef typename type_traits_detail::PointerTraits::type PointeeType; + typedef typename type_traits_detail::ReferenceTraits::type ReferredType; + + enum { isConst = type_traits_detail::UnConst::value }; + enum { isVolatile = type_traits_detail::UnVolatile::value }; + + enum { isReference = type_traits_detail::ReferenceTraits::value }; + enum { isPointer = type_traits_detail::PointerTraits::type>::value }; + + enum { isUnsignedInt = type_traits_detail::IsUnsignedIntegral::value }; + enum { isSignedInt = type_traits_detail::IsSignedIntergral::value }; + enum { isIntegral = type_traits_detail::IsIntegral::value }; + enum { isFloat = type_traits_detail::IsFloat::value }; + enum { isArith = isIntegral || isFloat }; + enum { isVec = type_traits_detail::IsVec::value }; + + typedef typename type_traits_detail::Select::value, + T, typename type_traits_detail::AddParameterType::type>::type ParameterType; + }; +}}} + +//! @endcond + +#endif // OPENCV_CUDA_TYPE_TRAITS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/utility.hpp b/3rdparty/opencv/include/opencv2/core/cuda/utility.hpp new file mode 100644 index 00000000..7f5db48a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/utility.hpp @@ -0,0 +1,230 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_UTILITY_HPP +#define OPENCV_CUDA_UTILITY_HPP + +#include "saturate_cast.hpp" +#include "datamov_utils.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + struct CV_EXPORTS ThrustAllocator + { + typedef uchar value_type; + virtual ~ThrustAllocator(); + virtual __device__ __host__ uchar* allocate(size_t numBytes) = 0; + virtual __device__ __host__ void deallocate(uchar* ptr, size_t numBytes) = 0; + static ThrustAllocator& getAllocator(); + static void setAllocator(ThrustAllocator* allocator); + }; + #define OPENCV_CUDA_LOG_WARP_SIZE (5) + #define OPENCV_CUDA_WARP_SIZE (1 << OPENCV_CUDA_LOG_WARP_SIZE) + #define OPENCV_CUDA_LOG_MEM_BANKS ((__CUDA_ARCH__ >= 200) ? 5 : 4) // 32 banks on fermi, 16 on tesla + #define OPENCV_CUDA_MEM_BANKS (1 << OPENCV_CUDA_LOG_MEM_BANKS) + + /////////////////////////////////////////////////////////////////////////////// + // swap + + template void __device__ __host__ __forceinline__ swap(T& a, T& b) + { + const T temp = a; + a = b; + b = temp; + } + + /////////////////////////////////////////////////////////////////////////////// + // Mask Reader + + struct SingleMask + { + explicit __host__ __device__ __forceinline__ SingleMask(PtrStepb mask_) : mask(mask_) {} + __host__ __device__ __forceinline__ SingleMask(const SingleMask& mask_): mask(mask_.mask){} + + __device__ __forceinline__ bool operator()(int y, int x) const + { + return mask.ptr(y)[x] != 0; + } + + PtrStepb mask; + }; + + struct SingleMaskChannels + { + __host__ __device__ __forceinline__ SingleMaskChannels(PtrStepb mask_, int channels_) + : mask(mask_), channels(channels_) {} + __host__ __device__ __forceinline__ SingleMaskChannels(const SingleMaskChannels& mask_) + :mask(mask_.mask), channels(mask_.channels){} + + __device__ __forceinline__ bool operator()(int y, int x) const + { + return mask.ptr(y)[x / channels] != 0; + } + + PtrStepb mask; + int channels; + }; + + struct MaskCollection + { + explicit __host__ __device__ __forceinline__ MaskCollection(PtrStepb* maskCollection_) + : maskCollection(maskCollection_) {} + + __device__ __forceinline__ MaskCollection(const MaskCollection& masks_) + : maskCollection(masks_.maskCollection), curMask(masks_.curMask){} + + __device__ __forceinline__ void next() + { + curMask = *maskCollection++; + } + __device__ __forceinline__ void setMask(int z) + { + curMask = maskCollection[z]; + } + + __device__ __forceinline__ bool operator()(int y, int x) const + { + uchar val; + return curMask.data == 0 || (ForceGlob::Load(curMask.ptr(y), x, val), (val != 0)); + } + + const PtrStepb* maskCollection; + PtrStepb curMask; + }; + + struct WithOutMask + { + __host__ __device__ __forceinline__ WithOutMask(){} + __host__ __device__ __forceinline__ WithOutMask(const WithOutMask&){} + + __device__ __forceinline__ void next() const + { + } + __device__ __forceinline__ void setMask(int) const + { + } + + __device__ __forceinline__ bool operator()(int, int) const + { + return true; + } + + __device__ __forceinline__ bool operator()(int, int, int) const + { + return true; + } + + static __device__ __forceinline__ bool check(int, int) + { + return true; + } + + static __device__ __forceinline__ bool check(int, int, int) + { + return true; + } + }; + + /////////////////////////////////////////////////////////////////////////////// + // Solve linear system + + // solve 2x2 linear system Ax=b + template __device__ __forceinline__ bool solve2x2(const T A[2][2], const T b[2], T x[2]) + { + T det = A[0][0] * A[1][1] - A[1][0] * A[0][1]; + + if (det != 0) + { + double invdet = 1.0 / det; + + x[0] = saturate_cast(invdet * (b[0] * A[1][1] - b[1] * A[0][1])); + + x[1] = saturate_cast(invdet * (A[0][0] * b[1] - A[1][0] * b[0])); + + return true; + } + + return false; + } + + // solve 3x3 linear system Ax=b + template __device__ __forceinline__ bool solve3x3(const T A[3][3], const T b[3], T x[3]) + { + T det = A[0][0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) + - A[0][1] * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) + + A[0][2] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]); + + if (det != 0) + { + double invdet = 1.0 / det; + + x[0] = saturate_cast(invdet * + (b[0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) - + A[0][1] * (b[1] * A[2][2] - A[1][2] * b[2] ) + + A[0][2] * (b[1] * A[2][1] - A[1][1] * b[2] ))); + + x[1] = saturate_cast(invdet * + (A[0][0] * (b[1] * A[2][2] - A[1][2] * b[2] ) - + b[0] * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) + + A[0][2] * (A[1][0] * b[2] - b[1] * A[2][0]))); + + x[2] = saturate_cast(invdet * + (A[0][0] * (A[1][1] * b[2] - b[1] * A[2][1]) - + A[0][1] * (A[1][0] * b[2] - b[1] * A[2][0]) + + b[0] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]))); + + return true; + } + + return false; + } +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_UTILITY_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/vec_distance.hpp b/3rdparty/opencv/include/opencv2/core/cuda/vec_distance.hpp new file mode 100644 index 00000000..ef6e5108 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/vec_distance.hpp @@ -0,0 +1,232 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_VEC_DISTANCE_HPP +#define OPENCV_CUDA_VEC_DISTANCE_HPP + +#include "reduce.hpp" +#include "functional.hpp" +#include "detail/vec_distance_detail.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template struct L1Dist + { + typedef int value_type; + typedef int result_type; + + __device__ __forceinline__ L1Dist() : mySum(0) {} + + __device__ __forceinline__ void reduceIter(int val1, int val2) + { + mySum = __sad(val1, val2, mySum); + } + + template __device__ __forceinline__ void reduceAll(int* smem, int tid) + { + reduce(smem, mySum, tid, plus()); + } + + __device__ __forceinline__ operator int() const + { + return mySum; + } + + int mySum; + }; + template <> struct L1Dist + { + typedef float value_type; + typedef float result_type; + + __device__ __forceinline__ L1Dist() : mySum(0.0f) {} + + __device__ __forceinline__ void reduceIter(float val1, float val2) + { + mySum += ::fabs(val1 - val2); + } + + template __device__ __forceinline__ void reduceAll(float* smem, int tid) + { + reduce(smem, mySum, tid, plus()); + } + + __device__ __forceinline__ operator float() const + { + return mySum; + } + + float mySum; + }; + + struct L2Dist + { + typedef float value_type; + typedef float result_type; + + __device__ __forceinline__ L2Dist() : mySum(0.0f) {} + + __device__ __forceinline__ void reduceIter(float val1, float val2) + { + float reg = val1 - val2; + mySum += reg * reg; + } + + template __device__ __forceinline__ void reduceAll(float* smem, int tid) + { + reduce(smem, mySum, tid, plus()); + } + + __device__ __forceinline__ operator float() const + { + return sqrtf(mySum); + } + + float mySum; + }; + + struct HammingDist + { + typedef int value_type; + typedef int result_type; + + __device__ __forceinline__ HammingDist() : mySum(0) {} + + __device__ __forceinline__ void reduceIter(int val1, int val2) + { + mySum += __popc(val1 ^ val2); + } + + template __device__ __forceinline__ void reduceAll(int* smem, int tid) + { + reduce(smem, mySum, tid, plus()); + } + + __device__ __forceinline__ operator int() const + { + return mySum; + } + + int mySum; + }; + + // calc distance between two vectors in global memory + template + __device__ void calcVecDiffGlobal(const T1* vec1, const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid) + { + for (int i = tid; i < len; i += THREAD_DIM) + { + T1 val1; + ForceGlob::Load(vec1, i, val1); + + T2 val2; + ForceGlob::Load(vec2, i, val2); + + dist.reduceIter(val1, val2); + } + + dist.reduceAll(smem, tid); + } + + // calc distance between two vectors, first vector is cached in register or shared memory, second vector is in global memory + template + __device__ __forceinline__ void calcVecDiffCached(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, typename Dist::result_type* smem, int tid) + { + vec_distance_detail::VecDiffCachedCalculator::calc(vecCached, vecGlob, len, dist, tid); + + dist.reduceAll(smem, tid); + } + + // calc distance between two vectors in global memory + template struct VecDiffGlobal + { + explicit __device__ __forceinline__ VecDiffGlobal(const T1* vec1_, int = 0, void* = 0, int = 0, int = 0) + { + vec1 = vec1_; + } + + template + __device__ __forceinline__ void calc(const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid) const + { + calcVecDiffGlobal(vec1, vec2, len, dist, smem, tid); + } + + const T1* vec1; + }; + + // calc distance between two vectors, first vector is cached in register memory, second vector is in global memory + template struct VecDiffCachedRegister + { + template __device__ __forceinline__ VecDiffCachedRegister(const T1* vec1, int len, U* smem, int glob_tid, int tid) + { + if (glob_tid < len) + smem[glob_tid] = vec1[glob_tid]; + __syncthreads(); + + U* vec1ValsPtr = vec1Vals; + + #pragma unroll + for (int i = tid; i < MAX_LEN; i += THREAD_DIM) + *vec1ValsPtr++ = smem[i]; + + __syncthreads(); + } + + template + __device__ __forceinline__ void calc(const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid) const + { + calcVecDiffCached(vec1Vals, vec2, len, dist, smem, tid); + } + + U vec1Vals[MAX_LEN / THREAD_DIM]; + }; +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_VEC_DISTANCE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/vec_math.hpp b/3rdparty/opencv/include/opencv2/core/cuda/vec_math.hpp new file mode 100644 index 00000000..9085b923 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/vec_math.hpp @@ -0,0 +1,930 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_VECMATH_HPP +#define OPENCV_CUDA_VECMATH_HPP + +#include "vec_traits.hpp" +#include "saturate_cast.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + +// saturate_cast + +namespace vec_math_detail +{ + template struct SatCastHelper; + template struct SatCastHelper<1, VecD> + { + template static __device__ __forceinline__ VecD cast(const VecS& v) + { + typedef typename VecTraits::elem_type D; + return VecTraits::make(saturate_cast(v.x)); + } + }; + template struct SatCastHelper<2, VecD> + { + template static __device__ __forceinline__ VecD cast(const VecS& v) + { + typedef typename VecTraits::elem_type D; + return VecTraits::make(saturate_cast(v.x), saturate_cast(v.y)); + } + }; + template struct SatCastHelper<3, VecD> + { + template static __device__ __forceinline__ VecD cast(const VecS& v) + { + typedef typename VecTraits::elem_type D; + return VecTraits::make(saturate_cast(v.x), saturate_cast(v.y), saturate_cast(v.z)); + } + }; + template struct SatCastHelper<4, VecD> + { + template static __device__ __forceinline__ VecD cast(const VecS& v) + { + typedef typename VecTraits::elem_type D; + return VecTraits::make(saturate_cast(v.x), saturate_cast(v.y), saturate_cast(v.z), saturate_cast(v.w)); + } + }; + + template static __device__ __forceinline__ VecD saturate_cast_helper(const VecS& v) + { + return SatCastHelper::cn, VecD>::cast(v); + } +} + +template static __device__ __forceinline__ T saturate_cast(const uchar1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const char1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const ushort1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const short1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const uint1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const int1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const float1& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const double1& v) {return vec_math_detail::saturate_cast_helper(v);} + +template static __device__ __forceinline__ T saturate_cast(const uchar2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const char2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const ushort2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const short2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const uint2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const int2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const float2& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const double2& v) {return vec_math_detail::saturate_cast_helper(v);} + +template static __device__ __forceinline__ T saturate_cast(const uchar3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const char3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const ushort3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const short3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const uint3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const int3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const float3& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const double3& v) {return vec_math_detail::saturate_cast_helper(v);} + +template static __device__ __forceinline__ T saturate_cast(const uchar4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const char4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const ushort4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const short4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const uint4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const int4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const float4& v) {return vec_math_detail::saturate_cast_helper(v);} +template static __device__ __forceinline__ T saturate_cast(const double4& v) {return vec_math_detail::saturate_cast_helper(v);} + +// unary operators + +#define CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(op, input_type, output_type) \ + __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a) \ + { \ + return VecTraits::make(op (a.x)); \ + } \ + __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a) \ + { \ + return VecTraits::make(op (a.x), op (a.y)); \ + } \ + __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a) \ + { \ + return VecTraits::make(op (a.x), op (a.y), op (a.z)); \ + } \ + __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a) \ + { \ + return VecTraits::make(op (a.x), op (a.y), op (a.z), op (a.w)); \ + } + +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, char, char) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, short, short) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, int, int) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, char, char) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, short, short) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, int, int) +CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, uint, uint) + +#undef CV_CUDEV_IMPLEMENT_VEC_UNARY_OP + +// unary functions + +#define CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(func_name, func, input_type, output_type) \ + __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a) \ + { \ + return VecTraits::make(func (a.x)); \ + } \ + __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a) \ + { \ + return VecTraits::make(func (a.x), func (a.y)); \ + } \ + __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a) \ + { \ + return VecTraits::make(func (a.x), func (a.y), func (a.z)); \ + } \ + __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a) \ + { \ + return VecTraits::make(func (a.x), func (a.y), func (a.z), func (a.w)); \ + } + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, /*::abs*/, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::abs, char, char) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, /*::abs*/, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::abs, short, short) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::abs, int, int) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, /*::abs*/, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::fabsf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::fabs, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrt, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::exp, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::log, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sin, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cos, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tan, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asin, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acos, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atan, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinh, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::cosh, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanh, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinh, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acosh, double, double) + +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, char, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, short, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, int, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, float, float) +CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanh, double, double) + +#undef CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC + +// binary operators (vec & vec) + +#define CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(op, input_type, output_type) \ + __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a, const input_type ## 1 & b) \ + { \ + return VecTraits::make(a.x op b.x); \ + } \ + __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a, const input_type ## 2 & b) \ + { \ + return VecTraits::make(a.x op b.x, a.y op b.y); \ + } \ + __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a, const input_type ## 3 & b) \ + { \ + return VecTraits::make(a.x op b.x, a.y op b.y, a.z op b.z); \ + } \ + __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a, const input_type ## 4 & b) \ + { \ + return VecTraits::make(a.x op b.x, a.y op b.y, a.z op b.z, a.w op b.w); \ + } + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, uchar, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, char, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, ushort, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, short, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, uchar, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, char, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, ushort, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, short, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, uchar, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, char, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, ushort, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, short, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, uchar, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, char, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, ushort, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, short, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, char, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, ushort, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, short, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, int, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, uint, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, float, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, double, uchar) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, char, char) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, short, short) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, uint, uint) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, char, char) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, short, short) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, uint, uint) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, char, char) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, short, short) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, uint, uint) + +#undef CV_CUDEV_IMPLEMENT_VEC_BINARY_OP + +// binary operators (vec & scalar) + +#define CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(op, input_type, scalar_type, output_type) \ + __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a, scalar_type s) \ + { \ + return VecTraits::make(a.x op s); \ + } \ + __device__ __forceinline__ output_type ## 1 operator op(scalar_type s, const input_type ## 1 & b) \ + { \ + return VecTraits::make(s op b.x); \ + } \ + __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a, scalar_type s) \ + { \ + return VecTraits::make(a.x op s, a.y op s); \ + } \ + __device__ __forceinline__ output_type ## 2 operator op(scalar_type s, const input_type ## 2 & b) \ + { \ + return VecTraits::make(s op b.x, s op b.y); \ + } \ + __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a, scalar_type s) \ + { \ + return VecTraits::make(a.x op s, a.y op s, a.z op s); \ + } \ + __device__ __forceinline__ output_type ## 3 operator op(scalar_type s, const input_type ## 3 & b) \ + { \ + return VecTraits::make(s op b.x, s op b.y, s op b.z); \ + } \ + __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a, scalar_type s) \ + { \ + return VecTraits::make(a.x op s, a.y op s, a.z op s, a.w op s); \ + } \ + __device__ __forceinline__ output_type ## 4 operator op(scalar_type s, const input_type ## 4 & b) \ + { \ + return VecTraits::make(s op b.x, s op b.y, s op b.z, s op b.w); \ + } + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, char, char, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, ushort, ushort, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, short, short, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, int, int, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, uint, uint, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, float, float, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, double, double, uchar) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, char, char, char) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, ushort, ushort, ushort) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, short, short, short) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, uint, uint, uint) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, char, char, char) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, ushort, ushort, ushort) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, short, short, short) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, uint, uint, uint) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, char, char, char) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, ushort, ushort, ushort) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, short, short, short) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, uint, uint, uint) + +#undef CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP + +// binary function (vec & vec) + +#define CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(func_name, func, input_type, output_type) \ + __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a, const input_type ## 1 & b) \ + { \ + return VecTraits::make(func (a.x, b.x)); \ + } \ + __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a, const input_type ## 2 & b) \ + { \ + return VecTraits::make(func (a.x, b.x), func (a.y, b.y)); \ + } \ + __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a, const input_type ## 3 & b) \ + { \ + return VecTraits::make(func (a.x, b.x), func (a.y, b.y), func (a.z, b.z)); \ + } \ + __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a, const input_type ## 4 & b) \ + { \ + return VecTraits::make(func (a.x, b.x), func (a.y, b.y), func (a.z, b.z), func (a.w, b.w)); \ + } + +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, char, char) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, short, short) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::fmaxf, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::fmax, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, uchar, uchar) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, char, char) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, ushort, ushort) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, short, short) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, uint, uint) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, int, int) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::fminf, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::fmin, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, char, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, short, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, uint, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, int, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypot, double, double) + +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, uchar, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, char, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, ushort, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, short, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, uint, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, int, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, float, float) +CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2, double, double) + +#undef CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC + +// binary function (vec & scalar) + +#define CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(func_name, func, input_type, scalar_type, output_type) \ + __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a, scalar_type s) \ + { \ + return VecTraits::make(func ((output_type) a.x, (output_type) s)); \ + } \ + __device__ __forceinline__ output_type ## 1 func_name(scalar_type s, const input_type ## 1 & b) \ + { \ + return VecTraits::make(func ((output_type) s, (output_type) b.x)); \ + } \ + __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a, scalar_type s) \ + { \ + return VecTraits::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s)); \ + } \ + __device__ __forceinline__ output_type ## 2 func_name(scalar_type s, const input_type ## 2 & b) \ + { \ + return VecTraits::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y)); \ + } \ + __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a, scalar_type s) \ + { \ + return VecTraits::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s), func ((output_type) a.z, (output_type) s)); \ + } \ + __device__ __forceinline__ output_type ## 3 func_name(scalar_type s, const input_type ## 3 & b) \ + { \ + return VecTraits::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y), func ((output_type) s, (output_type) b.z)); \ + } \ + __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a, scalar_type s) \ + { \ + return VecTraits::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s), func ((output_type) a.z, (output_type) s), func ((output_type) a.w, (output_type) s)); \ + } \ + __device__ __forceinline__ output_type ## 4 func_name(scalar_type s, const input_type ## 4 & b) \ + { \ + return VecTraits::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y), func ((output_type) s, (output_type) b.z), func ((output_type) s, (output_type) b.w)); \ + } + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, char, char, char) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, ushort, ushort, ushort) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, short, short, short) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, uchar, uchar, uchar) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, char, char, char) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, ushort, ushort, ushort) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, short, short, short) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, uint, uint, uint) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, int, int, int) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, double, double, double) + +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, uchar, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, uchar, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, char, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, char, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, ushort, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, ushort, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, short, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, short, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, uint, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, uint, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, int, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, int, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, float, float, float) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, float, double, double) +CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, double, double, double) + +#undef CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC + +}}} // namespace cv { namespace cuda { namespace device + +//! @endcond + +#endif // OPENCV_CUDA_VECMATH_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/vec_traits.hpp b/3rdparty/opencv/include/opencv2/core/cuda/vec_traits.hpp new file mode 100644 index 00000000..b5ff281a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/vec_traits.hpp @@ -0,0 +1,288 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_VEC_TRAITS_HPP +#define OPENCV_CUDA_VEC_TRAITS_HPP + +#include "common.hpp" + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template struct TypeVec; + + struct __align__(8) uchar8 + { + uchar a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ uchar8 make_uchar8(uchar a0, uchar a1, uchar a2, uchar a3, uchar a4, uchar a5, uchar a6, uchar a7) + { + uchar8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(8) char8 + { + schar a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ char8 make_char8(schar a0, schar a1, schar a2, schar a3, schar a4, schar a5, schar a6, schar a7) + { + char8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(16) ushort8 + { + ushort a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ ushort8 make_ushort8(ushort a0, ushort a1, ushort a2, ushort a3, ushort a4, ushort a5, ushort a6, ushort a7) + { + ushort8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(16) short8 + { + short a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ short8 make_short8(short a0, short a1, short a2, short a3, short a4, short a5, short a6, short a7) + { + short8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(32) uint8 + { + uint a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ uint8 make_uint8(uint a0, uint a1, uint a2, uint a3, uint a4, uint a5, uint a6, uint a7) + { + uint8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(32) int8 + { + int a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ int8 make_int8(int a0, int a1, int a2, int a3, int a4, int a5, int a6, int a7) + { + int8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct __align__(32) float8 + { + float a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ float8 make_float8(float a0, float a1, float a2, float a3, float a4, float a5, float a6, float a7) + { + float8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + struct double8 + { + double a0, a1, a2, a3, a4, a5, a6, a7; + }; + static __host__ __device__ __forceinline__ double8 make_double8(double a0, double a1, double a2, double a3, double a4, double a5, double a6, double a7) + { + double8 val = {a0, a1, a2, a3, a4, a5, a6, a7}; + return val; + } + +#define OPENCV_CUDA_IMPLEMENT_TYPE_VEC(type) \ + template<> struct TypeVec { typedef type vec_type; }; \ + template<> struct TypeVec { typedef type ## 1 vec_type; }; \ + template<> struct TypeVec { typedef type ## 2 vec_type; }; \ + template<> struct TypeVec { typedef type ## 2 vec_type; }; \ + template<> struct TypeVec { typedef type ## 3 vec_type; }; \ + template<> struct TypeVec { typedef type ## 3 vec_type; }; \ + template<> struct TypeVec { typedef type ## 4 vec_type; }; \ + template<> struct TypeVec { typedef type ## 4 vec_type; }; \ + template<> struct TypeVec { typedef type ## 8 vec_type; }; \ + template<> struct TypeVec { typedef type ## 8 vec_type; }; + + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(uchar) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(char) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(ushort) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(short) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(int) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(uint) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(float) + OPENCV_CUDA_IMPLEMENT_TYPE_VEC(double) + + #undef OPENCV_CUDA_IMPLEMENT_TYPE_VEC + + template<> struct TypeVec { typedef schar vec_type; }; + template<> struct TypeVec { typedef char2 vec_type; }; + template<> struct TypeVec { typedef char3 vec_type; }; + template<> struct TypeVec { typedef char4 vec_type; }; + template<> struct TypeVec { typedef char8 vec_type; }; + + template<> struct TypeVec { typedef uchar vec_type; }; + template<> struct TypeVec { typedef uchar2 vec_type; }; + template<> struct TypeVec { typedef uchar3 vec_type; }; + template<> struct TypeVec { typedef uchar4 vec_type; }; + template<> struct TypeVec { typedef uchar8 vec_type; }; + + template struct VecTraits; + +#define OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(type) \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=1}; \ + static __device__ __host__ __forceinline__ type all(type v) {return v;} \ + static __device__ __host__ __forceinline__ type make(type x) {return x;} \ + static __device__ __host__ __forceinline__ type make(const type* v) {return *v;} \ + }; \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=1}; \ + static __device__ __host__ __forceinline__ type ## 1 all(type v) {return make_ ## type ## 1(v);} \ + static __device__ __host__ __forceinline__ type ## 1 make(type x) {return make_ ## type ## 1(x);} \ + static __device__ __host__ __forceinline__ type ## 1 make(const type* v) {return make_ ## type ## 1(*v);} \ + }; \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=2}; \ + static __device__ __host__ __forceinline__ type ## 2 all(type v) {return make_ ## type ## 2(v, v);} \ + static __device__ __host__ __forceinline__ type ## 2 make(type x, type y) {return make_ ## type ## 2(x, y);} \ + static __device__ __host__ __forceinline__ type ## 2 make(const type* v) {return make_ ## type ## 2(v[0], v[1]);} \ + }; \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=3}; \ + static __device__ __host__ __forceinline__ type ## 3 all(type v) {return make_ ## type ## 3(v, v, v);} \ + static __device__ __host__ __forceinline__ type ## 3 make(type x, type y, type z) {return make_ ## type ## 3(x, y, z);} \ + static __device__ __host__ __forceinline__ type ## 3 make(const type* v) {return make_ ## type ## 3(v[0], v[1], v[2]);} \ + }; \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=4}; \ + static __device__ __host__ __forceinline__ type ## 4 all(type v) {return make_ ## type ## 4(v, v, v, v);} \ + static __device__ __host__ __forceinline__ type ## 4 make(type x, type y, type z, type w) {return make_ ## type ## 4(x, y, z, w);} \ + static __device__ __host__ __forceinline__ type ## 4 make(const type* v) {return make_ ## type ## 4(v[0], v[1], v[2], v[3]);} \ + }; \ + template<> struct VecTraits \ + { \ + typedef type elem_type; \ + enum {cn=8}; \ + static __device__ __host__ __forceinline__ type ## 8 all(type v) {return make_ ## type ## 8(v, v, v, v, v, v, v, v);} \ + static __device__ __host__ __forceinline__ type ## 8 make(type a0, type a1, type a2, type a3, type a4, type a5, type a6, type a7) {return make_ ## type ## 8(a0, a1, a2, a3, a4, a5, a6, a7);} \ + static __device__ __host__ __forceinline__ type ## 8 make(const type* v) {return make_ ## type ## 8(v[0], v[1], v[2], v[3], v[4], v[5], v[6], v[7]);} \ + }; + + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(uchar) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(ushort) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(short) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(int) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(uint) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(float) + OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(double) + + #undef OPENCV_CUDA_IMPLEMENT_VEC_TRAITS + + template<> struct VecTraits + { + typedef char elem_type; + enum {cn=1}; + static __device__ __host__ __forceinline__ char all(char v) {return v;} + static __device__ __host__ __forceinline__ char make(char x) {return x;} + static __device__ __host__ __forceinline__ char make(const char* x) {return *x;} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=1}; + static __device__ __host__ __forceinline__ schar all(schar v) {return v;} + static __device__ __host__ __forceinline__ schar make(schar x) {return x;} + static __device__ __host__ __forceinline__ schar make(const schar* x) {return *x;} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=1}; + static __device__ __host__ __forceinline__ char1 all(schar v) {return make_char1(v);} + static __device__ __host__ __forceinline__ char1 make(schar x) {return make_char1(x);} + static __device__ __host__ __forceinline__ char1 make(const schar* v) {return make_char1(v[0]);} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=2}; + static __device__ __host__ __forceinline__ char2 all(schar v) {return make_char2(v, v);} + static __device__ __host__ __forceinline__ char2 make(schar x, schar y) {return make_char2(x, y);} + static __device__ __host__ __forceinline__ char2 make(const schar* v) {return make_char2(v[0], v[1]);} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=3}; + static __device__ __host__ __forceinline__ char3 all(schar v) {return make_char3(v, v, v);} + static __device__ __host__ __forceinline__ char3 make(schar x, schar y, schar z) {return make_char3(x, y, z);} + static __device__ __host__ __forceinline__ char3 make(const schar* v) {return make_char3(v[0], v[1], v[2]);} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=4}; + static __device__ __host__ __forceinline__ char4 all(schar v) {return make_char4(v, v, v, v);} + static __device__ __host__ __forceinline__ char4 make(schar x, schar y, schar z, schar w) {return make_char4(x, y, z, w);} + static __device__ __host__ __forceinline__ char4 make(const schar* v) {return make_char4(v[0], v[1], v[2], v[3]);} + }; + template<> struct VecTraits + { + typedef schar elem_type; + enum {cn=8}; + static __device__ __host__ __forceinline__ char8 all(schar v) {return make_char8(v, v, v, v, v, v, v, v);} + static __device__ __host__ __forceinline__ char8 make(schar a0, schar a1, schar a2, schar a3, schar a4, schar a5, schar a6, schar a7) {return make_char8(a0, a1, a2, a3, a4, a5, a6, a7);} + static __device__ __host__ __forceinline__ char8 make(const schar* v) {return make_char8(v[0], v[1], v[2], v[3], v[4], v[5], v[6], v[7]);} + }; +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif // OPENCV_CUDA_VEC_TRAITS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda/warp.hpp b/3rdparty/opencv/include/opencv2/core/cuda/warp.hpp new file mode 100644 index 00000000..8af7e6a2 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/warp.hpp @@ -0,0 +1,139 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_DEVICE_WARP_HPP +#define OPENCV_CUDA_DEVICE_WARP_HPP + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + struct Warp + { + enum + { + LOG_WARP_SIZE = 5, + WARP_SIZE = 1 << LOG_WARP_SIZE, + STRIDE = WARP_SIZE + }; + + /** \brief Returns the warp lane ID of the calling thread. */ + static __device__ __forceinline__ unsigned int laneId() + { + unsigned int ret; + asm("mov.u32 %0, %%laneid;" : "=r"(ret) ); + return ret; + } + + template + static __device__ __forceinline__ void fill(It beg, It end, const T& value) + { + for(It t = beg + laneId(); t < end; t += STRIDE) + *t = value; + } + + template + static __device__ __forceinline__ OutIt copy(InIt beg, InIt end, OutIt out) + { + for(InIt t = beg + laneId(); t < end; t += STRIDE, out += STRIDE) + *out = *t; + return out; + } + + template + static __device__ __forceinline__ OutIt transform(InIt beg, InIt end, OutIt out, UnOp op) + { + for(InIt t = beg + laneId(); t < end; t += STRIDE, out += STRIDE) + *out = op(*t); + return out; + } + + template + static __device__ __forceinline__ OutIt transform(InIt1 beg1, InIt1 end1, InIt2 beg2, OutIt out, BinOp op) + { + unsigned int lane = laneId(); + + InIt1 t1 = beg1 + lane; + InIt2 t2 = beg2 + lane; + for(; t1 < end1; t1 += STRIDE, t2 += STRIDE, out += STRIDE) + *out = op(*t1, *t2); + return out; + } + + template + static __device__ __forceinline__ T reduce(volatile T *ptr, BinOp op) + { + const unsigned int lane = laneId(); + + if (lane < 16) + { + T partial = ptr[lane]; + + ptr[lane] = partial = op(partial, ptr[lane + 16]); + ptr[lane] = partial = op(partial, ptr[lane + 8]); + ptr[lane] = partial = op(partial, ptr[lane + 4]); + ptr[lane] = partial = op(partial, ptr[lane + 2]); + ptr[lane] = partial = op(partial, ptr[lane + 1]); + } + + return *ptr; + } + + template + static __device__ __forceinline__ void yota(OutIt beg, OutIt end, T value) + { + unsigned int lane = laneId(); + value += lane; + + for(OutIt t = beg + lane; t < end; t += STRIDE, value += STRIDE) + *t = value; + } + }; +}}} // namespace cv { namespace cuda { namespace cudev + +//! @endcond + +#endif /* OPENCV_CUDA_DEVICE_WARP_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/warp_reduce.hpp b/3rdparty/opencv/include/opencv2/core/cuda/warp_reduce.hpp new file mode 100644 index 00000000..530303d2 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/warp_reduce.hpp @@ -0,0 +1,76 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_WARP_REDUCE_HPP__ +#define OPENCV_CUDA_WARP_REDUCE_HPP__ + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ + template + __device__ __forceinline__ T warp_reduce(volatile T *ptr , const unsigned int tid = threadIdx.x) + { + const unsigned int lane = tid & 31; // index of thread in warp (0..31) + + if (lane < 16) + { + T partial = ptr[tid]; + + ptr[tid] = partial = partial + ptr[tid + 16]; + ptr[tid] = partial = partial + ptr[tid + 8]; + ptr[tid] = partial = partial + ptr[tid + 4]; + ptr[tid] = partial = partial + ptr[tid + 2]; + ptr[tid] = partial = partial + ptr[tid + 1]; + } + + return ptr[tid - lane]; + } +}}} // namespace cv { namespace cuda { namespace cudev { + +//! @endcond + +#endif /* OPENCV_CUDA_WARP_REDUCE_HPP__ */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda/warp_shuffle.hpp b/3rdparty/opencv/include/opencv2/core/cuda/warp_shuffle.hpp new file mode 100644 index 00000000..0da54aee --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda/warp_shuffle.hpp @@ -0,0 +1,162 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CUDA_WARP_SHUFFLE_HPP +#define OPENCV_CUDA_WARP_SHUFFLE_HPP + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +namespace cv { namespace cuda { namespace device +{ +#if __CUDACC_VER_MAJOR__ >= 9 +# define __shfl(x, y, z) __shfl_sync(0xFFFFFFFFU, x, y, z) +# define __shfl_up(x, y, z) __shfl_up_sync(0xFFFFFFFFU, x, y, z) +# define __shfl_down(x, y, z) __shfl_down_sync(0xFFFFFFFFU, x, y, z) +#endif + template + __device__ __forceinline__ T shfl(T val, int srcLane, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return __shfl(val, srcLane, width); + #else + return T(); + #endif + } + __device__ __forceinline__ unsigned int shfl(unsigned int val, int srcLane, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return (unsigned int) __shfl((int) val, srcLane, width); + #else + return 0; + #endif + } + __device__ __forceinline__ double shfl(double val, int srcLane, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + int lo = __double2loint(val); + int hi = __double2hiint(val); + + lo = __shfl(lo, srcLane, width); + hi = __shfl(hi, srcLane, width); + + return __hiloint2double(hi, lo); + #else + return 0.0; + #endif + } + + template + __device__ __forceinline__ T shfl_down(T val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return __shfl_down(val, delta, width); + #else + return T(); + #endif + } + __device__ __forceinline__ unsigned int shfl_down(unsigned int val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return (unsigned int) __shfl_down((int) val, delta, width); + #else + return 0; + #endif + } + __device__ __forceinline__ double shfl_down(double val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + int lo = __double2loint(val); + int hi = __double2hiint(val); + + lo = __shfl_down(lo, delta, width); + hi = __shfl_down(hi, delta, width); + + return __hiloint2double(hi, lo); + #else + return 0.0; + #endif + } + + template + __device__ __forceinline__ T shfl_up(T val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return __shfl_up(val, delta, width); + #else + return T(); + #endif + } + __device__ __forceinline__ unsigned int shfl_up(unsigned int val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + return (unsigned int) __shfl_up((int) val, delta, width); + #else + return 0; + #endif + } + __device__ __forceinline__ double shfl_up(double val, unsigned int delta, int width = warpSize) + { + #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300 + int lo = __double2loint(val); + int hi = __double2hiint(val); + + lo = __shfl_up(lo, delta, width); + hi = __shfl_up(hi, delta, width); + + return __hiloint2double(hi, lo); + #else + return 0.0; + #endif + } +}}} + +# undef __shfl +# undef __shfl_up +# undef __shfl_down + +//! @endcond + +#endif // OPENCV_CUDA_WARP_SHUFFLE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cuda_stream_accessor.hpp b/3rdparty/opencv/include/opencv2/core/cuda_stream_accessor.hpp new file mode 100644 index 00000000..deaf356f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda_stream_accessor.hpp @@ -0,0 +1,86 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP +#define OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP + +#ifndef __cplusplus +# error cuda_stream_accessor.hpp header must be compiled as C++ +#endif + +/** @file cuda_stream_accessor.hpp + * This is only header file that depends on CUDA Runtime API. All other headers are independent. + */ + +#include +#include "opencv2/core/cuda.hpp" + +namespace cv +{ + namespace cuda + { + +//! @addtogroup cudacore_struct +//! @{ + + /** @brief Class that enables getting cudaStream_t from cuda::Stream + */ + struct StreamAccessor + { + CV_EXPORTS static cudaStream_t getStream(const Stream& stream); + CV_EXPORTS static Stream wrapStream(cudaStream_t stream); + }; + + /** @brief Class that enables getting cudaEvent_t from cuda::Event + */ + struct EventAccessor + { + CV_EXPORTS static cudaEvent_t getEvent(const Event& event); + CV_EXPORTS static Event wrapEvent(cudaEvent_t event); + }; + +//! @} + + } +} + +#endif /* OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cuda_types.hpp b/3rdparty/opencv/include/opencv2/core/cuda_types.hpp new file mode 100644 index 00000000..45dc2cad --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cuda_types.hpp @@ -0,0 +1,144 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CUDA_TYPES_HPP +#define OPENCV_CORE_CUDA_TYPES_HPP + +#ifndef __cplusplus +# error cuda_types.hpp header must be compiled as C++ +#endif + +#if defined(__OPENCV_BUILD) && defined(__clang__) +#pragma clang diagnostic ignored "-Winconsistent-missing-override" +#endif +#if defined(__OPENCV_BUILD) && defined(__GNUC__) && __GNUC__ >= 5 +#pragma GCC diagnostic ignored "-Wsuggest-override" +#endif + +/** @file + * @deprecated Use @ref cudev instead. + */ + +//! @cond IGNORED + +#ifdef __CUDACC__ + #define __CV_CUDA_HOST_DEVICE__ __host__ __device__ __forceinline__ +#else + #define __CV_CUDA_HOST_DEVICE__ +#endif + +namespace cv +{ + namespace cuda + { + + // Simple lightweight structures that encapsulates information about an image on device. + // It is intended to pass to nvcc-compiled code. GpuMat depends on headers that nvcc can't compile + + template struct DevPtr + { + typedef T elem_type; + typedef int index_type; + + enum { elem_size = sizeof(elem_type) }; + + T* data; + + __CV_CUDA_HOST_DEVICE__ DevPtr() : data(0) {} + __CV_CUDA_HOST_DEVICE__ DevPtr(T* data_) : data(data_) {} + + __CV_CUDA_HOST_DEVICE__ size_t elemSize() const { return elem_size; } + __CV_CUDA_HOST_DEVICE__ operator T*() { return data; } + __CV_CUDA_HOST_DEVICE__ operator const T*() const { return data; } + }; + + template struct PtrSz : public DevPtr + { + __CV_CUDA_HOST_DEVICE__ PtrSz() : size(0) {} + __CV_CUDA_HOST_DEVICE__ PtrSz(T* data_, size_t size_) : DevPtr(data_), size(size_) {} + + size_t size; + }; + + template struct PtrStep : public DevPtr + { + __CV_CUDA_HOST_DEVICE__ PtrStep() : step(0) {} + __CV_CUDA_HOST_DEVICE__ PtrStep(T* data_, size_t step_) : DevPtr(data_), step(step_) {} + + size_t step; + + __CV_CUDA_HOST_DEVICE__ T* ptr(int y = 0) { return ( T*)( ( char*)DevPtr::data + y * step); } + __CV_CUDA_HOST_DEVICE__ const T* ptr(int y = 0) const { return (const T*)( (const char*)DevPtr::data + y * step); } + + __CV_CUDA_HOST_DEVICE__ T& operator ()(int y, int x) { return ptr(y)[x]; } + __CV_CUDA_HOST_DEVICE__ const T& operator ()(int y, int x) const { return ptr(y)[x]; } + }; + + template struct PtrStepSz : public PtrStep + { + __CV_CUDA_HOST_DEVICE__ PtrStepSz() : cols(0), rows(0) {} + __CV_CUDA_HOST_DEVICE__ PtrStepSz(int rows_, int cols_, T* data_, size_t step_) + : PtrStep(data_, step_), cols(cols_), rows(rows_) {} + + template + explicit PtrStepSz(const PtrStepSz& d) : PtrStep((T*)d.data, d.step), cols(d.cols), rows(d.rows){} + + int cols; + int rows; + }; + + typedef PtrStepSz PtrStepSzb; + typedef PtrStepSz PtrStepSzus; + typedef PtrStepSz PtrStepSzf; + typedef PtrStepSz PtrStepSzi; + + typedef PtrStep PtrStepb; + typedef PtrStep PtrStepus; + typedef PtrStep PtrStepf; + typedef PtrStep PtrStepi; + + } +} + +//! @endcond + +#endif /* OPENCV_CORE_CUDA_TYPES_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/cv_cpu_dispatch.h b/3rdparty/opencv/include/opencv2/core/cv_cpu_dispatch.h new file mode 100644 index 00000000..7f6d6b0f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cv_cpu_dispatch.h @@ -0,0 +1,252 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#if defined __OPENCV_BUILD \ + +#include "cv_cpu_config.h" +#include "cv_cpu_helper.h" + +#ifdef CV_CPU_DISPATCH_MODE +#define CV_CPU_OPTIMIZATION_NAMESPACE __CV_CAT(opt_, CV_CPU_DISPATCH_MODE) +#define CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN namespace __CV_CAT(opt_, CV_CPU_DISPATCH_MODE) { +#define CV_CPU_OPTIMIZATION_NAMESPACE_END } +#else +#define CV_CPU_OPTIMIZATION_NAMESPACE cpu_baseline +#define CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN namespace cpu_baseline { +#define CV_CPU_OPTIMIZATION_NAMESPACE_END } +#define CV_CPU_BASELINE_MODE 1 +#endif + + +#define __CV_CPU_DISPATCH_CHAIN_END(fn, args, mode, ...) /* done */ +#define __CV_CPU_DISPATCH(fn, args, mode, ...) __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) +#define __CV_CPU_DISPATCH_EXPAND(fn, args, ...) __CV_EXPAND(__CV_CPU_DISPATCH(fn, args, __VA_ARGS__)) +#define CV_CPU_DISPATCH(fn, args, ...) __CV_CPU_DISPATCH_EXPAND(fn, args, __VA_ARGS__, END) // expand macros + + +#if defined CV_ENABLE_INTRINSICS \ + && !defined CV_DISABLE_OPTIMIZATION \ + && !defined __CUDACC__ /* do not include SSE/AVX/NEON headers for NVCC compiler */ \ + +#ifdef CV_CPU_COMPILE_SSE2 +# include +# define CV_MMX 1 +# define CV_SSE 1 +# define CV_SSE2 1 +#endif +#ifdef CV_CPU_COMPILE_SSE3 +# include +# define CV_SSE3 1 +#endif +#ifdef CV_CPU_COMPILE_SSSE3 +# include +# define CV_SSSE3 1 +#endif +#ifdef CV_CPU_COMPILE_SSE4_1 +# include +# define CV_SSE4_1 1 +#endif +#ifdef CV_CPU_COMPILE_SSE4_2 +# include +# define CV_SSE4_2 1 +#endif +#ifdef CV_CPU_COMPILE_POPCNT +# ifdef _MSC_VER +# include +# if defined(_M_X64) +# define CV_POPCNT_U64 _mm_popcnt_u64 +# endif +# define CV_POPCNT_U32 _mm_popcnt_u32 +# else +# include +# if defined(__x86_64__) +# define CV_POPCNT_U64 __builtin_popcountll +# endif +# define CV_POPCNT_U32 __builtin_popcount +# endif +# define CV_POPCNT 1 +#endif +#ifdef CV_CPU_COMPILE_AVX +# include +# define CV_AVX 1 +#endif +#ifdef CV_CPU_COMPILE_FP16 +# if defined(__arm__) || defined(__aarch64__) || defined(_M_ARM) +# include +# else +# include +# endif +# define CV_FP16 1 +#endif +#ifdef CV_CPU_COMPILE_AVX2 +# include +# define CV_AVX2 1 +#endif +#ifdef CV_CPU_COMPILE_AVX_512F +# include +# define CV_AVX_512F 1 +#endif +#ifdef CV_CPU_COMPILE_AVX512_SKX +# include +# define CV_AVX512_SKX 1 +#endif +#ifdef CV_CPU_COMPILE_FMA3 +# define CV_FMA3 1 +#endif + +#if defined _WIN32 && defined(_M_ARM) +# include +# include +# define CV_NEON 1 +#elif defined(__ARM_NEON__) || (defined (__ARM_NEON) && defined(__aarch64__)) +# include +# define CV_NEON 1 +#endif + +#if defined(__ARM_NEON__) || defined(__aarch64__) +# include +#endif + +#ifdef CV_CPU_COMPILE_VSX +# include +# undef vector +# undef pixel +# undef bool +# define CV_VSX 1 +#endif + +#ifdef CV_CPU_COMPILE_VSX3 +# define CV_VSX3 1 +#endif + +#endif // CV_ENABLE_INTRINSICS && !CV_DISABLE_OPTIMIZATION && !__CUDACC__ + +#if defined CV_CPU_COMPILE_AVX && !defined CV_CPU_BASELINE_COMPILE_AVX +struct VZeroUpperGuard { +#ifdef __GNUC__ + __attribute__((always_inline)) +#endif + inline VZeroUpperGuard() { _mm256_zeroupper(); } +#ifdef __GNUC__ + __attribute__((always_inline)) +#endif + inline ~VZeroUpperGuard() { _mm256_zeroupper(); } +}; +#define __CV_AVX_GUARD VZeroUpperGuard __vzeroupper_guard; CV_UNUSED(__vzeroupper_guard); +#endif + +#ifdef __CV_AVX_GUARD +#define CV_AVX_GUARD __CV_AVX_GUARD +#else +#define CV_AVX_GUARD +#endif + +#endif // __OPENCV_BUILD + + + +#if !defined __OPENCV_BUILD /* Compatibility code */ \ + && !defined __CUDACC__ /* do not include SSE/AVX/NEON headers for NVCC compiler */ +#if defined __SSE2__ || defined _M_X64 || (defined _M_IX86_FP && _M_IX86_FP >= 2) +# include +# define CV_MMX 1 +# define CV_SSE 1 +# define CV_SSE2 1 +#elif defined _WIN32 && defined(_M_ARM) +# include +# include +# define CV_NEON 1 +#elif defined(__ARM_NEON__) || (defined (__ARM_NEON) && defined(__aarch64__)) +# include +# define CV_NEON 1 +#elif defined(__VSX__) && defined(__PPC64__) && defined(__LITTLE_ENDIAN__) +# include +# undef vector +# undef pixel +# undef bool +# define CV_VSX 1 +#endif + +#endif // !__OPENCV_BUILD && !__CUDACC (Compatibility code) + + + +#ifndef CV_MMX +# define CV_MMX 0 +#endif +#ifndef CV_SSE +# define CV_SSE 0 +#endif +#ifndef CV_SSE2 +# define CV_SSE2 0 +#endif +#ifndef CV_SSE3 +# define CV_SSE3 0 +#endif +#ifndef CV_SSSE3 +# define CV_SSSE3 0 +#endif +#ifndef CV_SSE4_1 +# define CV_SSE4_1 0 +#endif +#ifndef CV_SSE4_2 +# define CV_SSE4_2 0 +#endif +#ifndef CV_POPCNT +# define CV_POPCNT 0 +#endif +#ifndef CV_AVX +# define CV_AVX 0 +#endif +#ifndef CV_FP16 +# define CV_FP16 0 +#endif +#ifndef CV_AVX2 +# define CV_AVX2 0 +#endif +#ifndef CV_FMA3 +# define CV_FMA3 0 +#endif +#ifndef CV_AVX_512F +# define CV_AVX_512F 0 +#endif +#ifndef CV_AVX_512BW +# define CV_AVX_512BW 0 +#endif +#ifndef CV_AVX_512CD +# define CV_AVX_512CD 0 +#endif +#ifndef CV_AVX_512DQ +# define CV_AVX_512DQ 0 +#endif +#ifndef CV_AVX_512ER +# define CV_AVX_512ER 0 +#endif +#ifndef CV_AVX_512IFMA512 +# define CV_AVX_512IFMA512 0 +#endif +#ifndef CV_AVX_512PF +# define CV_AVX_512PF 0 +#endif +#ifndef CV_AVX_512VBMI +# define CV_AVX_512VBMI 0 +#endif +#ifndef CV_AVX_512VL +# define CV_AVX_512VL 0 +#endif +#ifndef CV_AVX512_SKX +# define CV_AVX512_SKX 0 +#endif + +#ifndef CV_NEON +# define CV_NEON 0 +#endif + +#ifndef CV_VSX +# define CV_VSX 0 +#endif + +#ifndef CV_VSX3 +# define CV_VSX3 0 +#endif diff --git a/3rdparty/opencv/include/opencv2/core/cv_cpu_helper.h b/3rdparty/opencv/include/opencv2/core/cv_cpu_helper.h new file mode 100644 index 00000000..ad133979 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cv_cpu_helper.h @@ -0,0 +1,340 @@ +// AUTOGENERATED, DO NOT EDIT + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE +# define CV_TRY_SSE 1 +# define CV_CPU_FORCE_SSE 1 +# define CV_CPU_HAS_SUPPORT_SSE 1 +# define CV_CPU_CALL_SSE(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSE_(fn, args) return (opt_SSE::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE +# define CV_TRY_SSE 1 +# define CV_CPU_FORCE_SSE 0 +# define CV_CPU_HAS_SUPPORT_SSE (cv::checkHardwareSupport(CV_CPU_SSE)) +# define CV_CPU_CALL_SSE(fn, args) if (CV_CPU_HAS_SUPPORT_SSE) return (opt_SSE::fn args) +# define CV_CPU_CALL_SSE_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE) return (opt_SSE::fn args) +#else +# define CV_TRY_SSE 0 +# define CV_CPU_FORCE_SSE 0 +# define CV_CPU_HAS_SUPPORT_SSE 0 +# define CV_CPU_CALL_SSE(fn, args) +# define CV_CPU_CALL_SSE_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSE(fn, args, mode, ...) CV_CPU_CALL_SSE(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE2 +# define CV_TRY_SSE2 1 +# define CV_CPU_FORCE_SSE2 1 +# define CV_CPU_HAS_SUPPORT_SSE2 1 +# define CV_CPU_CALL_SSE2(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSE2_(fn, args) return (opt_SSE2::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE2 +# define CV_TRY_SSE2 1 +# define CV_CPU_FORCE_SSE2 0 +# define CV_CPU_HAS_SUPPORT_SSE2 (cv::checkHardwareSupport(CV_CPU_SSE2)) +# define CV_CPU_CALL_SSE2(fn, args) if (CV_CPU_HAS_SUPPORT_SSE2) return (opt_SSE2::fn args) +# define CV_CPU_CALL_SSE2_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE2) return (opt_SSE2::fn args) +#else +# define CV_TRY_SSE2 0 +# define CV_CPU_FORCE_SSE2 0 +# define CV_CPU_HAS_SUPPORT_SSE2 0 +# define CV_CPU_CALL_SSE2(fn, args) +# define CV_CPU_CALL_SSE2_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSE2(fn, args, mode, ...) CV_CPU_CALL_SSE2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE3 +# define CV_TRY_SSE3 1 +# define CV_CPU_FORCE_SSE3 1 +# define CV_CPU_HAS_SUPPORT_SSE3 1 +# define CV_CPU_CALL_SSE3(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSE3_(fn, args) return (opt_SSE3::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE3 +# define CV_TRY_SSE3 1 +# define CV_CPU_FORCE_SSE3 0 +# define CV_CPU_HAS_SUPPORT_SSE3 (cv::checkHardwareSupport(CV_CPU_SSE3)) +# define CV_CPU_CALL_SSE3(fn, args) if (CV_CPU_HAS_SUPPORT_SSE3) return (opt_SSE3::fn args) +# define CV_CPU_CALL_SSE3_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE3) return (opt_SSE3::fn args) +#else +# define CV_TRY_SSE3 0 +# define CV_CPU_FORCE_SSE3 0 +# define CV_CPU_HAS_SUPPORT_SSE3 0 +# define CV_CPU_CALL_SSE3(fn, args) +# define CV_CPU_CALL_SSE3_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSE3(fn, args, mode, ...) CV_CPU_CALL_SSE3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSSE3 +# define CV_TRY_SSSE3 1 +# define CV_CPU_FORCE_SSSE3 1 +# define CV_CPU_HAS_SUPPORT_SSSE3 1 +# define CV_CPU_CALL_SSSE3(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSSE3_(fn, args) return (opt_SSSE3::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSSE3 +# define CV_TRY_SSSE3 1 +# define CV_CPU_FORCE_SSSE3 0 +# define CV_CPU_HAS_SUPPORT_SSSE3 (cv::checkHardwareSupport(CV_CPU_SSSE3)) +# define CV_CPU_CALL_SSSE3(fn, args) if (CV_CPU_HAS_SUPPORT_SSSE3) return (opt_SSSE3::fn args) +# define CV_CPU_CALL_SSSE3_(fn, args) if (CV_CPU_HAS_SUPPORT_SSSE3) return (opt_SSSE3::fn args) +#else +# define CV_TRY_SSSE3 0 +# define CV_CPU_FORCE_SSSE3 0 +# define CV_CPU_HAS_SUPPORT_SSSE3 0 +# define CV_CPU_CALL_SSSE3(fn, args) +# define CV_CPU_CALL_SSSE3_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSSE3(fn, args, mode, ...) CV_CPU_CALL_SSSE3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE4_1 +# define CV_TRY_SSE4_1 1 +# define CV_CPU_FORCE_SSE4_1 1 +# define CV_CPU_HAS_SUPPORT_SSE4_1 1 +# define CV_CPU_CALL_SSE4_1(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSE4_1_(fn, args) return (opt_SSE4_1::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE4_1 +# define CV_TRY_SSE4_1 1 +# define CV_CPU_FORCE_SSE4_1 0 +# define CV_CPU_HAS_SUPPORT_SSE4_1 (cv::checkHardwareSupport(CV_CPU_SSE4_1)) +# define CV_CPU_CALL_SSE4_1(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_1) return (opt_SSE4_1::fn args) +# define CV_CPU_CALL_SSE4_1_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_1) return (opt_SSE4_1::fn args) +#else +# define CV_TRY_SSE4_1 0 +# define CV_CPU_FORCE_SSE4_1 0 +# define CV_CPU_HAS_SUPPORT_SSE4_1 0 +# define CV_CPU_CALL_SSE4_1(fn, args) +# define CV_CPU_CALL_SSE4_1_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSE4_1(fn, args, mode, ...) CV_CPU_CALL_SSE4_1(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE4_2 +# define CV_TRY_SSE4_2 1 +# define CV_CPU_FORCE_SSE4_2 1 +# define CV_CPU_HAS_SUPPORT_SSE4_2 1 +# define CV_CPU_CALL_SSE4_2(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_SSE4_2_(fn, args) return (opt_SSE4_2::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE4_2 +# define CV_TRY_SSE4_2 1 +# define CV_CPU_FORCE_SSE4_2 0 +# define CV_CPU_HAS_SUPPORT_SSE4_2 (cv::checkHardwareSupport(CV_CPU_SSE4_2)) +# define CV_CPU_CALL_SSE4_2(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_2) return (opt_SSE4_2::fn args) +# define CV_CPU_CALL_SSE4_2_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_2) return (opt_SSE4_2::fn args) +#else +# define CV_TRY_SSE4_2 0 +# define CV_CPU_FORCE_SSE4_2 0 +# define CV_CPU_HAS_SUPPORT_SSE4_2 0 +# define CV_CPU_CALL_SSE4_2(fn, args) +# define CV_CPU_CALL_SSE4_2_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_SSE4_2(fn, args, mode, ...) CV_CPU_CALL_SSE4_2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_POPCNT +# define CV_TRY_POPCNT 1 +# define CV_CPU_FORCE_POPCNT 1 +# define CV_CPU_HAS_SUPPORT_POPCNT 1 +# define CV_CPU_CALL_POPCNT(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_POPCNT_(fn, args) return (opt_POPCNT::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_POPCNT +# define CV_TRY_POPCNT 1 +# define CV_CPU_FORCE_POPCNT 0 +# define CV_CPU_HAS_SUPPORT_POPCNT (cv::checkHardwareSupport(CV_CPU_POPCNT)) +# define CV_CPU_CALL_POPCNT(fn, args) if (CV_CPU_HAS_SUPPORT_POPCNT) return (opt_POPCNT::fn args) +# define CV_CPU_CALL_POPCNT_(fn, args) if (CV_CPU_HAS_SUPPORT_POPCNT) return (opt_POPCNT::fn args) +#else +# define CV_TRY_POPCNT 0 +# define CV_CPU_FORCE_POPCNT 0 +# define CV_CPU_HAS_SUPPORT_POPCNT 0 +# define CV_CPU_CALL_POPCNT(fn, args) +# define CV_CPU_CALL_POPCNT_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_POPCNT(fn, args, mode, ...) CV_CPU_CALL_POPCNT(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX +# define CV_TRY_AVX 1 +# define CV_CPU_FORCE_AVX 1 +# define CV_CPU_HAS_SUPPORT_AVX 1 +# define CV_CPU_CALL_AVX(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_AVX_(fn, args) return (opt_AVX::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX +# define CV_TRY_AVX 1 +# define CV_CPU_FORCE_AVX 0 +# define CV_CPU_HAS_SUPPORT_AVX (cv::checkHardwareSupport(CV_CPU_AVX)) +# define CV_CPU_CALL_AVX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX) return (opt_AVX::fn args) +# define CV_CPU_CALL_AVX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX) return (opt_AVX::fn args) +#else +# define CV_TRY_AVX 0 +# define CV_CPU_FORCE_AVX 0 +# define CV_CPU_HAS_SUPPORT_AVX 0 +# define CV_CPU_CALL_AVX(fn, args) +# define CV_CPU_CALL_AVX_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_AVX(fn, args, mode, ...) CV_CPU_CALL_AVX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_FP16 +# define CV_TRY_FP16 1 +# define CV_CPU_FORCE_FP16 1 +# define CV_CPU_HAS_SUPPORT_FP16 1 +# define CV_CPU_CALL_FP16(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_FP16_(fn, args) return (opt_FP16::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_FP16 +# define CV_TRY_FP16 1 +# define CV_CPU_FORCE_FP16 0 +# define CV_CPU_HAS_SUPPORT_FP16 (cv::checkHardwareSupport(CV_CPU_FP16)) +# define CV_CPU_CALL_FP16(fn, args) if (CV_CPU_HAS_SUPPORT_FP16) return (opt_FP16::fn args) +# define CV_CPU_CALL_FP16_(fn, args) if (CV_CPU_HAS_SUPPORT_FP16) return (opt_FP16::fn args) +#else +# define CV_TRY_FP16 0 +# define CV_CPU_FORCE_FP16 0 +# define CV_CPU_HAS_SUPPORT_FP16 0 +# define CV_CPU_CALL_FP16(fn, args) +# define CV_CPU_CALL_FP16_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_FP16(fn, args, mode, ...) CV_CPU_CALL_FP16(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX2 +# define CV_TRY_AVX2 1 +# define CV_CPU_FORCE_AVX2 1 +# define CV_CPU_HAS_SUPPORT_AVX2 1 +# define CV_CPU_CALL_AVX2(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_AVX2_(fn, args) return (opt_AVX2::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX2 +# define CV_TRY_AVX2 1 +# define CV_CPU_FORCE_AVX2 0 +# define CV_CPU_HAS_SUPPORT_AVX2 (cv::checkHardwareSupport(CV_CPU_AVX2)) +# define CV_CPU_CALL_AVX2(fn, args) if (CV_CPU_HAS_SUPPORT_AVX2) return (opt_AVX2::fn args) +# define CV_CPU_CALL_AVX2_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX2) return (opt_AVX2::fn args) +#else +# define CV_TRY_AVX2 0 +# define CV_CPU_FORCE_AVX2 0 +# define CV_CPU_HAS_SUPPORT_AVX2 0 +# define CV_CPU_CALL_AVX2(fn, args) +# define CV_CPU_CALL_AVX2_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_AVX2(fn, args, mode, ...) CV_CPU_CALL_AVX2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_FMA3 +# define CV_TRY_FMA3 1 +# define CV_CPU_FORCE_FMA3 1 +# define CV_CPU_HAS_SUPPORT_FMA3 1 +# define CV_CPU_CALL_FMA3(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_FMA3_(fn, args) return (opt_FMA3::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_FMA3 +# define CV_TRY_FMA3 1 +# define CV_CPU_FORCE_FMA3 0 +# define CV_CPU_HAS_SUPPORT_FMA3 (cv::checkHardwareSupport(CV_CPU_FMA3)) +# define CV_CPU_CALL_FMA3(fn, args) if (CV_CPU_HAS_SUPPORT_FMA3) return (opt_FMA3::fn args) +# define CV_CPU_CALL_FMA3_(fn, args) if (CV_CPU_HAS_SUPPORT_FMA3) return (opt_FMA3::fn args) +#else +# define CV_TRY_FMA3 0 +# define CV_CPU_FORCE_FMA3 0 +# define CV_CPU_HAS_SUPPORT_FMA3 0 +# define CV_CPU_CALL_FMA3(fn, args) +# define CV_CPU_CALL_FMA3_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_FMA3(fn, args, mode, ...) CV_CPU_CALL_FMA3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX_512F +# define CV_TRY_AVX_512F 1 +# define CV_CPU_FORCE_AVX_512F 1 +# define CV_CPU_HAS_SUPPORT_AVX_512F 1 +# define CV_CPU_CALL_AVX_512F(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_AVX_512F_(fn, args) return (opt_AVX_512F::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX_512F +# define CV_TRY_AVX_512F 1 +# define CV_CPU_FORCE_AVX_512F 0 +# define CV_CPU_HAS_SUPPORT_AVX_512F (cv::checkHardwareSupport(CV_CPU_AVX_512F)) +# define CV_CPU_CALL_AVX_512F(fn, args) if (CV_CPU_HAS_SUPPORT_AVX_512F) return (opt_AVX_512F::fn args) +# define CV_CPU_CALL_AVX_512F_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX_512F) return (opt_AVX_512F::fn args) +#else +# define CV_TRY_AVX_512F 0 +# define CV_CPU_FORCE_AVX_512F 0 +# define CV_CPU_HAS_SUPPORT_AVX_512F 0 +# define CV_CPU_CALL_AVX_512F(fn, args) +# define CV_CPU_CALL_AVX_512F_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_AVX_512F(fn, args, mode, ...) CV_CPU_CALL_AVX_512F(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_SKX +# define CV_TRY_AVX512_SKX 1 +# define CV_CPU_FORCE_AVX512_SKX 1 +# define CV_CPU_HAS_SUPPORT_AVX512_SKX 1 +# define CV_CPU_CALL_AVX512_SKX(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_AVX512_SKX_(fn, args) return (opt_AVX512_SKX::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_SKX +# define CV_TRY_AVX512_SKX 1 +# define CV_CPU_FORCE_AVX512_SKX 0 +# define CV_CPU_HAS_SUPPORT_AVX512_SKX (cv::checkHardwareSupport(CV_CPU_AVX512_SKX)) +# define CV_CPU_CALL_AVX512_SKX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_SKX) return (opt_AVX512_SKX::fn args) +# define CV_CPU_CALL_AVX512_SKX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_SKX) return (opt_AVX512_SKX::fn args) +#else +# define CV_TRY_AVX512_SKX 0 +# define CV_CPU_FORCE_AVX512_SKX 0 +# define CV_CPU_HAS_SUPPORT_AVX512_SKX 0 +# define CV_CPU_CALL_AVX512_SKX(fn, args) +# define CV_CPU_CALL_AVX512_SKX_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_AVX512_SKX(fn, args, mode, ...) CV_CPU_CALL_AVX512_SKX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON +# define CV_TRY_NEON 1 +# define CV_CPU_FORCE_NEON 1 +# define CV_CPU_HAS_SUPPORT_NEON 1 +# define CV_CPU_CALL_NEON(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_NEON_(fn, args) return (opt_NEON::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON +# define CV_TRY_NEON 1 +# define CV_CPU_FORCE_NEON 0 +# define CV_CPU_HAS_SUPPORT_NEON (cv::checkHardwareSupport(CV_CPU_NEON)) +# define CV_CPU_CALL_NEON(fn, args) if (CV_CPU_HAS_SUPPORT_NEON) return (opt_NEON::fn args) +# define CV_CPU_CALL_NEON_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON) return (opt_NEON::fn args) +#else +# define CV_TRY_NEON 0 +# define CV_CPU_FORCE_NEON 0 +# define CV_CPU_HAS_SUPPORT_NEON 0 +# define CV_CPU_CALL_NEON(fn, args) +# define CV_CPU_CALL_NEON_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_NEON(fn, args, mode, ...) CV_CPU_CALL_NEON(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_VSX +# define CV_TRY_VSX 1 +# define CV_CPU_FORCE_VSX 1 +# define CV_CPU_HAS_SUPPORT_VSX 1 +# define CV_CPU_CALL_VSX(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_VSX_(fn, args) return (opt_VSX::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_VSX +# define CV_TRY_VSX 1 +# define CV_CPU_FORCE_VSX 0 +# define CV_CPU_HAS_SUPPORT_VSX (cv::checkHardwareSupport(CV_CPU_VSX)) +# define CV_CPU_CALL_VSX(fn, args) if (CV_CPU_HAS_SUPPORT_VSX) return (opt_VSX::fn args) +# define CV_CPU_CALL_VSX_(fn, args) if (CV_CPU_HAS_SUPPORT_VSX) return (opt_VSX::fn args) +#else +# define CV_TRY_VSX 0 +# define CV_CPU_FORCE_VSX 0 +# define CV_CPU_HAS_SUPPORT_VSX 0 +# define CV_CPU_CALL_VSX(fn, args) +# define CV_CPU_CALL_VSX_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_VSX(fn, args, mode, ...) CV_CPU_CALL_VSX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_VSX3 +# define CV_TRY_VSX3 1 +# define CV_CPU_FORCE_VSX3 1 +# define CV_CPU_HAS_SUPPORT_VSX3 1 +# define CV_CPU_CALL_VSX3(fn, args) return (cpu_baseline::fn args) +# define CV_CPU_CALL_VSX3_(fn, args) return (opt_VSX3::fn args) +#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_VSX3 +# define CV_TRY_VSX3 1 +# define CV_CPU_FORCE_VSX3 0 +# define CV_CPU_HAS_SUPPORT_VSX3 (cv::checkHardwareSupport(CV_CPU_VSX3)) +# define CV_CPU_CALL_VSX3(fn, args) if (CV_CPU_HAS_SUPPORT_VSX3) return (opt_VSX3::fn args) +# define CV_CPU_CALL_VSX3_(fn, args) if (CV_CPU_HAS_SUPPORT_VSX3) return (opt_VSX3::fn args) +#else +# define CV_TRY_VSX3 0 +# define CV_CPU_FORCE_VSX3 0 +# define CV_CPU_HAS_SUPPORT_VSX3 0 +# define CV_CPU_CALL_VSX3(fn, args) +# define CV_CPU_CALL_VSX3_(fn, args) +#endif +#define __CV_CPU_DISPATCH_CHAIN_VSX3(fn, args, mode, ...) CV_CPU_CALL_VSX3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__)) + +#define CV_CPU_CALL_BASELINE(fn, args) return (cpu_baseline::fn args) +#define __CV_CPU_DISPATCH_CHAIN_BASELINE(fn, args, mode, ...) CV_CPU_CALL_BASELINE(fn, args) /* last in sequence */ diff --git a/3rdparty/opencv/include/opencv2/core/cvdef.h b/3rdparty/opencv/include/opencv2/core/cvdef.h new file mode 100644 index 00000000..be7da7a4 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cvdef.h @@ -0,0 +1,763 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CVDEF_H +#define OPENCV_CORE_CVDEF_H + +//! @addtogroup core_utils +//! @{ + +#if !defined CV_DOXYGEN && !defined CV_IGNORE_DEBUG_BUILD_GUARD +#if (defined(_MSC_VER) && (defined(DEBUG) || defined(_DEBUG))) || \ + (defined(_GLIBCXX_DEBUG) || defined(_GLIBCXX_DEBUG_PEDANTIC)) +// Guard to prevent using of binary incompatible binaries / runtimes +// https://github.com/opencv/opencv/pull/9161 +#define CV__DEBUG_NS_BEGIN namespace debug_build_guard { +#define CV__DEBUG_NS_END } +namespace cv { namespace debug_build_guard { } using namespace debug_build_guard; } +#endif +#endif + +#ifndef CV__DEBUG_NS_BEGIN +#define CV__DEBUG_NS_BEGIN +#define CV__DEBUG_NS_END +#endif + + +#ifdef __OPENCV_BUILD +#include "cvconfig.h" +#endif + +#ifndef __CV_EXPAND +#define __CV_EXPAND(x) x +#endif + +#ifndef __CV_CAT +#define __CV_CAT__(x, y) x ## y +#define __CV_CAT_(x, y) __CV_CAT__(x, y) +#define __CV_CAT(x, y) __CV_CAT_(x, y) +#endif + +#define __CV_VA_NUM_ARGS_HELPER(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N +#define __CV_VA_NUM_ARGS(...) __CV_VA_NUM_ARGS_HELPER(__VA_ARGS__, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0) + +#if defined __GNUC__ +#define CV_Func __func__ +#elif defined _MSC_VER +#define CV_Func __FUNCTION__ +#else +#define CV_Func "" +#endif + +//! @cond IGNORED + +//////////////// static assert ///////////////// +#define CVAUX_CONCAT_EXP(a, b) a##b +#define CVAUX_CONCAT(a, b) CVAUX_CONCAT_EXP(a,b) + +#if defined(__clang__) +# ifndef __has_extension +# define __has_extension __has_feature /* compatibility, for older versions of clang */ +# endif +# if __has_extension(cxx_static_assert) +# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition) +# elif __has_extension(c_static_assert) +# define CV_StaticAssert(condition, reason) _Static_assert((condition), reason " " #condition) +# endif +#elif defined(__GNUC__) +# if (defined(__GXX_EXPERIMENTAL_CXX0X__) || __cplusplus >= 201103L) +# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition) +# endif +#elif defined(_MSC_VER) +# if _MSC_VER >= 1600 /* MSVC 10 */ +# define CV_StaticAssert(condition, reason) static_assert((condition), reason " " #condition) +# endif +#endif +#ifndef CV_StaticAssert +# if !defined(__clang__) && defined(__GNUC__) && (__GNUC__*100 + __GNUC_MINOR__ > 302) +# define CV_StaticAssert(condition, reason) ({ extern int __attribute__((error("CV_StaticAssert: " reason " " #condition))) CV_StaticAssert(); ((condition) ? 0 : CV_StaticAssert()); }) +# else + template struct CV_StaticAssert_failed; + template <> struct CV_StaticAssert_failed { enum { val = 1 }; }; + template struct CV_StaticAssert_test {}; +# define CV_StaticAssert(condition, reason)\ + typedef cv::CV_StaticAssert_test< sizeof(cv::CV_StaticAssert_failed< static_cast(condition) >) > CVAUX_CONCAT(CV_StaticAssert_failed_at_, __LINE__) +# endif +#endif + +// Suppress warning "-Wdeprecated-declarations" / C4996 +#if defined(_MSC_VER) + #define CV_DO_PRAGMA(x) __pragma(x) +#elif defined(__GNUC__) + #define CV_DO_PRAGMA(x) _Pragma (#x) +#else + #define CV_DO_PRAGMA(x) +#endif + +#ifdef _MSC_VER +#define CV_SUPPRESS_DEPRECATED_START \ + CV_DO_PRAGMA(warning(push)) \ + CV_DO_PRAGMA(warning(disable: 4996)) +#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(warning(pop)) +#elif defined (__clang__) || ((__GNUC__) && (__GNUC__*100 + __GNUC_MINOR__ > 405)) +#define CV_SUPPRESS_DEPRECATED_START \ + CV_DO_PRAGMA(GCC diagnostic push) \ + CV_DO_PRAGMA(GCC diagnostic ignored "-Wdeprecated-declarations") +#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(GCC diagnostic pop) +#else +#define CV_SUPPRESS_DEPRECATED_START +#define CV_SUPPRESS_DEPRECATED_END +#endif + +#define CV_UNUSED(name) (void)name + +#if defined __GNUC__ && !defined __EXCEPTIONS +#define CV_TRY +#define CV_CATCH(A, B) for (A B; false; ) +#define CV_CATCH_ALL if (false) +#define CV_THROW(A) abort() +#define CV_RETHROW() abort() +#else +#define CV_TRY try +#define CV_CATCH(A, B) catch(const A & B) +#define CV_CATCH_ALL catch(...) +#define CV_THROW(A) throw A +#define CV_RETHROW() throw +#endif + +//! @endcond + +// undef problematic defines sometimes defined by system headers (windows.h in particular) +#undef small +#undef min +#undef max +#undef abs +#undef Complex + +#include +#include "opencv2/core/hal/interface.h" + +#if defined __ICL +# define CV_ICC __ICL +#elif defined __ICC +# define CV_ICC __ICC +#elif defined __ECL +# define CV_ICC __ECL +#elif defined __ECC +# define CV_ICC __ECC +#elif defined __INTEL_COMPILER +# define CV_ICC __INTEL_COMPILER +#endif + +#ifndef CV_INLINE +# if defined __cplusplus +# define CV_INLINE static inline +# elif defined _MSC_VER +# define CV_INLINE __inline +# else +# define CV_INLINE static +# endif +#endif + +#ifndef CV_ALWAYS_INLINE +#if defined(__GNUC__) && (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 1)) +#define CV_ALWAYS_INLINE inline __attribute__((always_inline)) +#elif defined(_MSC_VER) +#define CV_ALWAYS_INLINE __forceinline +#else +#define CV_ALWAYS_INLINE inline +#endif +#endif + +#if defined CV_DISABLE_OPTIMIZATION || (defined CV_ICC && !defined CV_ENABLE_UNROLLED) +# define CV_ENABLE_UNROLLED 0 +#else +# define CV_ENABLE_UNROLLED 1 +#endif + +#ifdef __GNUC__ +# define CV_DECL_ALIGNED(x) __attribute__ ((aligned (x))) +#elif defined _MSC_VER +# define CV_DECL_ALIGNED(x) __declspec(align(x)) +#else +# define CV_DECL_ALIGNED(x) +#endif + +/* CPU features and intrinsics support */ +#define CV_CPU_NONE 0 +#define CV_CPU_MMX 1 +#define CV_CPU_SSE 2 +#define CV_CPU_SSE2 3 +#define CV_CPU_SSE3 4 +#define CV_CPU_SSSE3 5 +#define CV_CPU_SSE4_1 6 +#define CV_CPU_SSE4_2 7 +#define CV_CPU_POPCNT 8 +#define CV_CPU_FP16 9 +#define CV_CPU_AVX 10 +#define CV_CPU_AVX2 11 +#define CV_CPU_FMA3 12 + +#define CV_CPU_AVX_512F 13 +#define CV_CPU_AVX_512BW 14 +#define CV_CPU_AVX_512CD 15 +#define CV_CPU_AVX_512DQ 16 +#define CV_CPU_AVX_512ER 17 +#define CV_CPU_AVX_512IFMA512 18 // deprecated +#define CV_CPU_AVX_512IFMA 18 +#define CV_CPU_AVX_512PF 19 +#define CV_CPU_AVX_512VBMI 20 +#define CV_CPU_AVX_512VL 21 + +#define CV_CPU_NEON 100 + +#define CV_CPU_VSX 200 +#define CV_CPU_VSX3 201 + +// CPU features groups +#define CV_CPU_AVX512_SKX 256 + +// when adding to this list remember to update the following enum +#define CV_HARDWARE_MAX_FEATURE 512 + +/** @brief Available CPU features. +*/ +enum CpuFeatures { + CPU_MMX = 1, + CPU_SSE = 2, + CPU_SSE2 = 3, + CPU_SSE3 = 4, + CPU_SSSE3 = 5, + CPU_SSE4_1 = 6, + CPU_SSE4_2 = 7, + CPU_POPCNT = 8, + CPU_FP16 = 9, + CPU_AVX = 10, + CPU_AVX2 = 11, + CPU_FMA3 = 12, + + CPU_AVX_512F = 13, + CPU_AVX_512BW = 14, + CPU_AVX_512CD = 15, + CPU_AVX_512DQ = 16, + CPU_AVX_512ER = 17, + CPU_AVX_512IFMA512 = 18, // deprecated + CPU_AVX_512IFMA = 18, + CPU_AVX_512PF = 19, + CPU_AVX_512VBMI = 20, + CPU_AVX_512VL = 21, + + CPU_NEON = 100, + + CPU_VSX = 200, + CPU_VSX3 = 201, + + CPU_AVX512_SKX = 256, //!< Skylake-X with AVX-512F/CD/BW/DQ/VL + + CPU_MAX_FEATURE = 512 // see CV_HARDWARE_MAX_FEATURE +}; + + +#include "cv_cpu_dispatch.h" + + +/* fundamental constants */ +#define CV_PI 3.1415926535897932384626433832795 +#define CV_2PI 6.283185307179586476925286766559 +#define CV_LOG2 0.69314718055994530941723212145818 + +#if defined __ARM_FP16_FORMAT_IEEE \ + && !defined __CUDACC__ +# define CV_FP16_TYPE 1 +#else +# define CV_FP16_TYPE 0 +#endif + +typedef union Cv16suf +{ + short i; + ushort u; +#if CV_FP16_TYPE + __fp16 h; +#endif +} +Cv16suf; + +typedef union Cv32suf +{ + int i; + unsigned u; + float f; +} +Cv32suf; + +typedef union Cv64suf +{ + int64 i; + uint64 u; + double f; +} +Cv64suf; + +#define OPENCV_ABI_COMPATIBILITY 300 + +#ifdef __OPENCV_BUILD +# define DISABLE_OPENCV_24_COMPATIBILITY +# define OPENCV_DISABLE_DEPRECATED_COMPATIBILITY +#endif + +#ifdef CVAPI_EXPORTS +# if (defined _WIN32 || defined WINCE || defined __CYGWIN__) +# define CV_EXPORTS __declspec(dllexport) +# elif defined __GNUC__ && __GNUC__ >= 4 +# define CV_EXPORTS __attribute__ ((visibility ("default"))) +# endif +#endif + +#ifndef CV_EXPORTS +# define CV_EXPORTS +#endif + +#ifdef _MSC_VER +# define CV_EXPORTS_TEMPLATE +#else +# define CV_EXPORTS_TEMPLATE CV_EXPORTS +#endif + +#ifndef CV_DEPRECATED +# if defined(__GNUC__) +# define CV_DEPRECATED __attribute__ ((deprecated)) +# elif defined(_MSC_VER) +# define CV_DEPRECATED __declspec(deprecated) +# else +# define CV_DEPRECATED +# endif +#endif + +#ifndef CV_DEPRECATED_EXTERNAL +# if defined(__OPENCV_BUILD) +# define CV_DEPRECATED_EXTERNAL /* nothing */ +# else +# define CV_DEPRECATED_EXTERNAL CV_DEPRECATED +# endif +#endif + + +#ifndef CV_EXTERN_C +# ifdef __cplusplus +# define CV_EXTERN_C extern "C" +# else +# define CV_EXTERN_C +# endif +#endif + +/* special informative macros for wrapper generators */ +#define CV_EXPORTS_W CV_EXPORTS +#define CV_EXPORTS_W_SIMPLE CV_EXPORTS +#define CV_EXPORTS_AS(synonym) CV_EXPORTS +#define CV_EXPORTS_W_MAP CV_EXPORTS +#define CV_IN_OUT +#define CV_OUT +#define CV_PROP +#define CV_PROP_RW +#define CV_WRAP +#define CV_WRAP_AS(synonym) + +/****************************************************************************************\ +* Matrix type (Mat) * +\****************************************************************************************/ + +#define CV_MAT_CN_MASK ((CV_CN_MAX - 1) << CV_CN_SHIFT) +#define CV_MAT_CN(flags) ((((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1) +#define CV_MAT_TYPE_MASK (CV_DEPTH_MAX*CV_CN_MAX - 1) +#define CV_MAT_TYPE(flags) ((flags) & CV_MAT_TYPE_MASK) +#define CV_MAT_CONT_FLAG_SHIFT 14 +#define CV_MAT_CONT_FLAG (1 << CV_MAT_CONT_FLAG_SHIFT) +#define CV_IS_MAT_CONT(flags) ((flags) & CV_MAT_CONT_FLAG) +#define CV_IS_CONT_MAT CV_IS_MAT_CONT +#define CV_SUBMAT_FLAG_SHIFT 15 +#define CV_SUBMAT_FLAG (1 << CV_SUBMAT_FLAG_SHIFT) +#define CV_IS_SUBMAT(flags) ((flags) & CV_MAT_SUBMAT_FLAG) + +/** Size of each channel item, + 0x8442211 = 1000 0100 0100 0010 0010 0001 0001 ~ array of sizeof(arr_type_elem) */ +#define CV_ELEM_SIZE1(type) \ + ((((sizeof(size_t)<<28)|0x8442211) >> CV_MAT_DEPTH(type)*4) & 15) + +/** 0x3a50 = 11 10 10 01 01 00 00 ~ array of log2(sizeof(arr_type_elem)) */ +#define CV_ELEM_SIZE(type) \ + (CV_MAT_CN(type) << ((((sizeof(size_t)/4+1)*16384|0x3a50) >> CV_MAT_DEPTH(type)*2) & 3)) + +#ifndef MIN +# define MIN(a,b) ((a) > (b) ? (b) : (a)) +#endif + +#ifndef MAX +# define MAX(a,b) ((a) < (b) ? (b) : (a)) +#endif + +/****************************************************************************************\ +* static analysys * +\****************************************************************************************/ + +// In practice, some macro are not processed correctly (noreturn is not detected). +// We need to use simplified definition for them. +#ifndef CV_STATIC_ANALYSIS +# if defined(__KLOCWORK__) || defined(__clang_analyzer__) || defined(__COVERITY__) +# define CV_STATIC_ANALYSIS 1 +# endif +#else +# if defined(CV_STATIC_ANALYSIS) && !(__CV_CAT(1, CV_STATIC_ANALYSIS) == 1) // defined and not empty +# if 0 == CV_STATIC_ANALYSIS +# undef CV_STATIC_ANALYSIS +# endif +# endif +#endif + +/****************************************************************************************\ +* Thread sanitizer * +\****************************************************************************************/ +#ifndef CV_THREAD_SANITIZER +# if defined(__has_feature) +# if __has_feature(thread_sanitizer) +# define CV_THREAD_SANITIZER +# endif +# endif +#endif + +/****************************************************************************************\ +* exchange-add operation for atomic operations on reference counters * +\****************************************************************************************/ + +#ifdef CV_XADD + // allow to use user-defined macro +#elif defined __GNUC__ || defined __clang__ +# if defined __clang__ && __clang_major__ >= 3 && !defined __ANDROID__ && !defined __EMSCRIPTEN__ && !defined(__CUDACC__) && !defined __INTEL_COMPILER +# ifdef __ATOMIC_ACQ_REL +# define CV_XADD(addr, delta) __c11_atomic_fetch_add((_Atomic(int)*)(addr), delta, __ATOMIC_ACQ_REL) +# else +# define CV_XADD(addr, delta) __atomic_fetch_add((_Atomic(int)*)(addr), delta, 4) +# endif +# else +# if defined __ATOMIC_ACQ_REL && !defined __clang__ + // version for gcc >= 4.7 +# define CV_XADD(addr, delta) (int)__atomic_fetch_add((unsigned*)(addr), (unsigned)(delta), __ATOMIC_ACQ_REL) +# else +# define CV_XADD(addr, delta) (int)__sync_fetch_and_add((unsigned*)(addr), (unsigned)(delta)) +# endif +# endif +#elif defined _MSC_VER && !defined RC_INVOKED +# include +# define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd((long volatile*)addr, delta) +#else + CV_INLINE CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; } +#endif + + +/****************************************************************************************\ +* CV_NORETURN attribute * +\****************************************************************************************/ + +#ifndef CV_NORETURN +# if defined(__GNUC__) +# define CV_NORETURN __attribute__((__noreturn__)) +# elif defined(_MSC_VER) && (_MSC_VER >= 1300) +# define CV_NORETURN __declspec(noreturn) +# else +# define CV_NORETURN /* nothing by default */ +# endif +#endif + + +/****************************************************************************************\ +* CV_NODISCARD attribute * +* encourages the compiler to issue a warning if the return value is discarded (C++17) * +\****************************************************************************************/ +#ifndef CV_NODISCARD +# if defined(__GNUC__) +# define CV_NODISCARD __attribute__((__warn_unused_result__)) // at least available with GCC 3.4 +# elif defined(__clang__) && defined(__has_attribute) +# if __has_attribute(__warn_unused_result__) +# define CV_NODISCARD __attribute__((__warn_unused_result__)) +# endif +# endif +#endif +#ifndef CV_NODISCARD +# define CV_NODISCARD /* nothing by default */ +#endif + + +/****************************************************************************************\ +* C++ 11 * +\****************************************************************************************/ +#ifndef CV_CXX11 +# if __cplusplus >= 201103L || (defined(_MSC_VER) && _MSC_VER >= 1800) +# define CV_CXX11 1 +# endif +#else +# if CV_CXX11 == 0 +# undef CV_CXX11 +# endif +#endif + + +/****************************************************************************************\ +* C++ Move semantics * +\****************************************************************************************/ + +#ifndef CV_CXX_MOVE_SEMANTICS +# if __cplusplus >= 201103L || defined(__GXX_EXPERIMENTAL_CXX0X__) || (defined(_MSC_VER) && _MSC_VER >= 1600) +# define CV_CXX_MOVE_SEMANTICS 1 +# elif defined(__clang) +# if __has_feature(cxx_rvalue_references) +# define CV_CXX_MOVE_SEMANTICS 1 +# endif +# endif +#else +# if CV_CXX_MOVE_SEMANTICS == 0 +# undef CV_CXX_MOVE_SEMANTICS +# endif +#endif + +/****************************************************************************************\ +* C++11 std::array * +\****************************************************************************************/ + +#ifndef CV_CXX_STD_ARRAY +# if __cplusplus >= 201103L || (defined(__cplusplus) && defined(_MSC_VER) && _MSC_VER >= 1900/*MSVS 2015*/) +# define CV_CXX_STD_ARRAY 1 +# include +# endif +#else +# if CV_CXX_STD_ARRAY == 0 +# undef CV_CXX_STD_ARRAY +# endif +#endif + + +/****************************************************************************************\ +* C++11 override / final * +\****************************************************************************************/ + +#ifndef CV_OVERRIDE +# ifdef CV_CXX11 +# define CV_OVERRIDE override +# endif +#endif +#ifndef CV_OVERRIDE +# define CV_OVERRIDE +#endif + +#ifndef CV_FINAL +# ifdef CV_CXX11 +# define CV_FINAL final +# endif +#endif +#ifndef CV_FINAL +# define CV_FINAL +#endif + + + +// Integer types portatibility +#ifdef OPENCV_STDINT_HEADER +#include OPENCV_STDINT_HEADER +#elif defined(__cplusplus) +#if defined(_MSC_VER) && _MSC_VER < 1600 /* MSVS 2010 */ +namespace cv { +typedef signed char int8_t; +typedef unsigned char uint8_t; +typedef signed short int16_t; +typedef unsigned short uint16_t; +typedef signed int int32_t; +typedef unsigned int uint32_t; +typedef signed __int64 int64_t; +typedef unsigned __int64 uint64_t; +} +#elif defined(_MSC_VER) || __cplusplus >= 201103L +#include +namespace cv { +using std::int8_t; +using std::uint8_t; +using std::int16_t; +using std::uint16_t; +using std::int32_t; +using std::uint32_t; +using std::int64_t; +using std::uint64_t; +} +#else +#include +namespace cv { +typedef ::int8_t int8_t; +typedef ::uint8_t uint8_t; +typedef ::int16_t int16_t; +typedef ::uint16_t uint16_t; +typedef ::int32_t int32_t; +typedef ::uint32_t uint32_t; +typedef ::int64_t int64_t; +typedef ::uint64_t uint64_t; +} +#endif +#else // pure C +#include +#endif + +#ifdef __cplusplus +namespace cv +{ + +class float16_t +{ +public: +#if CV_FP16_TYPE + + float16_t() {} + explicit float16_t(float x) { h = (__fp16)x; } + operator float() const { return (float)h; } + static float16_t fromBits(ushort w) + { + Cv16suf u; + u.u = w; + float16_t result; + result.h = u.h; + return result; + } + static float16_t zero() + { + float16_t result; + result.h = (__fp16)0; + return result; + } + ushort bits() const + { + Cv16suf u; + u.h = h; + return u.u; + } +protected: + __fp16 h; + +#else + float16_t() {} + explicit float16_t(float x) + { + #if CV_AVX2 + __m128 v = _mm_load_ss(&x); + w = (ushort)_mm_cvtsi128_si32(_mm_cvtps_ph(v, 0)); + #else + Cv32suf in; + in.f = x; + unsigned sign = in.u & 0x80000000; + in.u ^= sign; + + if( in.u >= 0x47800000 ) + w = (ushort)(in.u > 0x7f800000 ? 0x7e00 : 0x7c00); + else + { + if (in.u < 0x38800000) + { + in.f += 0.5f; + w = (ushort)(in.u - 0x3f000000); + } + else + { + unsigned t = in.u + 0xc8000fff; + w = (ushort)((t + ((in.u >> 13) & 1)) >> 13); + } + } + + w = (ushort)(w | (sign >> 16)); + #endif + } + + operator float() const + { + #if CV_AVX2 + float f; + _mm_store_ss(&f, _mm_cvtph_ps(_mm_cvtsi32_si128(w))); + return f; + #else + Cv32suf out; + + unsigned t = ((w & 0x7fff) << 13) + 0x38000000; + unsigned sign = (w & 0x8000) << 16; + unsigned e = w & 0x7c00; + + out.u = t + (1 << 23); + out.u = (e >= 0x7c00 ? t + 0x38000000 : + e == 0 ? (out.f -= 6.103515625e-05f, out.u) : t) | sign; + return out.f; + #endif + } + + static float16_t fromBits(ushort b) + { + float16_t result; + result.w = b; + return result; + } + static float16_t zero() + { + float16_t result; + result.w = (ushort)0; + return result; + } + ushort bits() const { return w; } +protected: + ushort w; + +#endif +}; + +} +#endif + +//! @} + +#ifndef __cplusplus +#include "opencv2/core/fast_math.hpp" // define cvRound(double) +#endif + +#endif // OPENCV_CORE_CVDEF_H diff --git a/3rdparty/opencv/include/opencv2/core/cvstd.hpp b/3rdparty/opencv/include/opencv2/core/cvstd.hpp new file mode 100644 index 00000000..8af1162b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cvstd.hpp @@ -0,0 +1,1040 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CVSTD_HPP +#define OPENCV_CORE_CVSTD_HPP + +#ifndef __cplusplus +# error cvstd.hpp header must be compiled as C++ +#endif + +#include "opencv2/core/cvdef.h" +#include +#include +#include + +#include + +// import useful primitives from stl +# include +# include +# include //for abs(int) +# include + +namespace cv +{ + static inline uchar abs(uchar a) { return a; } + static inline ushort abs(ushort a) { return a; } + static inline unsigned abs(unsigned a) { return a; } + static inline uint64 abs(uint64 a) { return a; } + + using std::min; + using std::max; + using std::abs; + using std::swap; + using std::sqrt; + using std::exp; + using std::pow; + using std::log; +} + +namespace cv { + +//! @addtogroup core_utils +//! @{ + +//////////////////////////// memory management functions //////////////////////////// + +/** @brief Allocates an aligned memory buffer. + +The function allocates the buffer of the specified size and returns it. When the buffer size is 16 +bytes or more, the returned buffer is aligned to 16 bytes. +@param bufSize Allocated buffer size. + */ +CV_EXPORTS void* fastMalloc(size_t bufSize); + +/** @brief Deallocates a memory buffer. + +The function deallocates the buffer allocated with fastMalloc . If NULL pointer is passed, the +function does nothing. C version of the function clears the pointer *pptr* to avoid problems with +double memory deallocation. +@param ptr Pointer to the allocated buffer. + */ +CV_EXPORTS void fastFree(void* ptr); + +/*! + The STL-compliant memory Allocator based on cv::fastMalloc() and cv::fastFree() +*/ +template class Allocator +{ +public: + typedef _Tp value_type; + typedef value_type* pointer; + typedef const value_type* const_pointer; + typedef value_type& reference; + typedef const value_type& const_reference; + typedef size_t size_type; + typedef ptrdiff_t difference_type; + template class rebind { typedef Allocator other; }; + + explicit Allocator() {} + ~Allocator() {} + explicit Allocator(Allocator const&) {} + template + explicit Allocator(Allocator const&) {} + + // address + pointer address(reference r) { return &r; } + const_pointer address(const_reference r) { return &r; } + + pointer allocate(size_type count, const void* =0) { return reinterpret_cast(fastMalloc(count * sizeof (_Tp))); } + void deallocate(pointer p, size_type) { fastFree(p); } + + void construct(pointer p, const _Tp& v) { new(static_cast(p)) _Tp(v); } + void destroy(pointer p) { p->~_Tp(); } + + size_type max_size() const { return cv::max(static_cast<_Tp>(-1)/sizeof(_Tp), 1); } +}; + +//! @} core_utils + +//! @cond IGNORED + +namespace detail +{ + +// Metafunction to avoid taking a reference to void. +template +struct RefOrVoid { typedef T& type; }; + +template<> +struct RefOrVoid{ typedef void type; }; + +template<> +struct RefOrVoid{ typedef const void type; }; + +template<> +struct RefOrVoid{ typedef volatile void type; }; + +template<> +struct RefOrVoid{ typedef const volatile void type; }; + +// This class would be private to Ptr, if it didn't have to be a non-template. +struct PtrOwner; + +} + +template +struct DefaultDeleter +{ + void operator () (Y* p) const; +}; + +//! @endcond + +//! @addtogroup core_basic +//! @{ + +/** @brief Template class for smart pointers with shared ownership + +A Ptr\ pretends to be a pointer to an object of type T. Unlike an ordinary pointer, however, the +object will be automatically cleaned up once all Ptr instances pointing to it are destroyed. + +Ptr is similar to boost::shared_ptr that is part of the Boost library +() and std::shared_ptr from +the [C++11](http://en.wikipedia.org/wiki/C++11) standard. + +This class provides the following advantages: +- Default constructor, copy constructor, and assignment operator for an arbitrary C++ class or C + structure. For some objects, like files, windows, mutexes, sockets, and others, a copy + constructor or an assignment operator are difficult to define. For some other objects, like + complex classifiers in OpenCV, copy constructors are absent and not easy to implement. Finally, + some of complex OpenCV and your own data structures may be written in C. However, copy + constructors and default constructors can simplify programming a lot. Besides, they are often + required (for example, by STL containers). By using a Ptr to such an object instead of the + object itself, you automatically get all of the necessary constructors and the assignment + operator. +- *O(1)* complexity of the above-mentioned operations. While some structures, like std::vector, + provide a copy constructor and an assignment operator, the operations may take a considerable + amount of time if the data structures are large. But if the structures are put into a Ptr, the + overhead is small and independent of the data size. +- Automatic and customizable cleanup, even for C structures. See the example below with FILE\*. +- Heterogeneous collections of objects. The standard STL and most other C++ and OpenCV containers + can store only objects of the same type and the same size. The classical solution to store + objects of different types in the same container is to store pointers to the base class (Base\*) + instead but then you lose the automatic memory management. Again, by using Ptr\ instead + of raw pointers, you can solve the problem. + +A Ptr is said to *own* a pointer - that is, for each Ptr there is a pointer that will be deleted +once all Ptr instances that own it are destroyed. The owned pointer may be null, in which case +nothing is deleted. Each Ptr also *stores* a pointer. The stored pointer is the pointer the Ptr +pretends to be; that is, the one you get when you use Ptr::get or the conversion to T\*. It's +usually the same as the owned pointer, but if you use casts or the general shared-ownership +constructor, the two may diverge: the Ptr will still own the original pointer, but will itself point +to something else. + +The owned pointer is treated as a black box. The only thing Ptr needs to know about it is how to +delete it. This knowledge is encapsulated in the *deleter* - an auxiliary object that is associated +with the owned pointer and shared between all Ptr instances that own it. The default deleter is an +instance of DefaultDeleter, which uses the standard C++ delete operator; as such it will work with +any pointer allocated with the standard new operator. + +However, if the pointer must be deleted in a different way, you must specify a custom deleter upon +Ptr construction. A deleter is simply a callable object that accepts the pointer as its sole +argument. For example, if you want to wrap FILE, you may do so as follows: +@code + Ptr f(fopen("myfile.txt", "w"), fclose); + if(!f) throw ...; + fprintf(f, ....); + ... + // the file will be closed automatically by f's destructor. +@endcode +Alternatively, if you want all pointers of a particular type to be deleted the same way, you can +specialize DefaultDeleter::operator() for that type, like this: +@code + namespace cv { + template<> void DefaultDeleter::operator ()(FILE * obj) const + { + fclose(obj); + } + } +@endcode +For convenience, the following types from the OpenCV C API already have such a specialization that +calls the appropriate release function: +- CvCapture +- CvFileStorage +- CvHaarClassifierCascade +- CvMat +- CvMatND +- CvMemStorage +- CvSparseMat +- CvVideoWriter +- IplImage +@note The shared ownership mechanism is implemented with reference counting. As such, cyclic +ownership (e.g. when object a contains a Ptr to object b, which contains a Ptr to object a) will +lead to all involved objects never being cleaned up. Avoid such situations. +@note It is safe to concurrently read (but not write) a Ptr instance from multiple threads and +therefore it is normally safe to use it in multi-threaded applications. The same is true for Mat and +other C++ OpenCV classes that use internal reference counts. +*/ +template +struct Ptr +{ + /** Generic programming support. */ + typedef T element_type; + + /** The default constructor creates a null Ptr - one that owns and stores a null pointer. + */ + Ptr(); + + /** + If p is null, these are equivalent to the default constructor. + Otherwise, these constructors assume ownership of p - that is, the created Ptr owns and stores p + and assumes it is the sole owner of it. Don't use them if p is already owned by another Ptr, or + else p will get deleted twice. + With the first constructor, DefaultDeleter\() becomes the associated deleter (so p will + eventually be deleted with the standard delete operator). Y must be a complete type at the point + of invocation. + With the second constructor, d becomes the associated deleter. + Y\* must be convertible to T\*. + @param p Pointer to own. + @note It is often easier to use makePtr instead. + */ + template +#ifdef DISABLE_OPENCV_24_COMPATIBILITY + explicit +#endif + Ptr(Y* p); + + /** @overload + @param d Deleter to use for the owned pointer. + @param p Pointer to own. + */ + template + Ptr(Y* p, D d); + + /** + These constructors create a Ptr that shares ownership with another Ptr - that is, own the same + pointer as o. + With the first two, the same pointer is stored, as well; for the second, Y\* must be convertible + to T\*. + With the third, p is stored, and Y may be any type. This constructor allows to have completely + unrelated owned and stored pointers, and should be used with care to avoid confusion. A relatively + benign use is to create a non-owning Ptr, like this: + @code + ptr = Ptr(Ptr(), dont_delete_me); // owns nothing; will not delete the pointer. + @endcode + @param o Ptr to share ownership with. + */ + Ptr(const Ptr& o); + + /** @overload + @param o Ptr to share ownership with. + */ + template + Ptr(const Ptr& o); + + /** @overload + @param o Ptr to share ownership with. + @param p Pointer to store. + */ + template + Ptr(const Ptr& o, T* p); + + /** The destructor is equivalent to calling Ptr::release. */ + ~Ptr(); + + /** + Assignment replaces the current Ptr instance with one that owns and stores same pointers as o and + then destroys the old instance. + @param o Ptr to share ownership with. + */ + Ptr& operator = (const Ptr& o); + + /** @overload */ + template + Ptr& operator = (const Ptr& o); + + /** If no other Ptr instance owns the owned pointer, deletes it with the associated deleter. Then sets + both the owned and the stored pointers to NULL. + */ + void release(); + + /** + `ptr.reset(...)` is equivalent to `ptr = Ptr(...)`. + @param p Pointer to own. + */ + template + void reset(Y* p); + + /** @overload + @param d Deleter to use for the owned pointer. + @param p Pointer to own. + */ + template + void reset(Y* p, D d); + + /** + Swaps the owned and stored pointers (and deleters, if any) of this and o. + @param o Ptr to swap with. + */ + void swap(Ptr& o); + + /** Returns the stored pointer. */ + T* get() const; + + /** Ordinary pointer emulation. */ + typename detail::RefOrVoid::type operator * () const; + + /** Ordinary pointer emulation. */ + T* operator -> () const; + + /** Equivalent to get(). */ + operator T* () const; + + /** ptr.empty() is equivalent to `!ptr.get()`. */ + bool empty() const; + + /** Returns a Ptr that owns the same pointer as this, and stores the same + pointer as this, except converted via static_cast to Y*. + */ + template + Ptr staticCast() const; + + /** Ditto for const_cast. */ + template + Ptr constCast() const; + + /** Ditto for dynamic_cast. */ + template + Ptr dynamicCast() const; + +#ifdef CV_CXX_MOVE_SEMANTICS + Ptr(Ptr&& o); + Ptr& operator = (Ptr&& o); +#endif + +private: + detail::PtrOwner* owner; + T* stored; + + template + friend struct Ptr; // have to do this for the cross-type copy constructor +}; + +/** Equivalent to ptr1.swap(ptr2). Provided to help write generic algorithms. */ +template +void swap(Ptr& ptr1, Ptr& ptr2); + +/** Return whether ptr1.get() and ptr2.get() are equal and not equal, respectively. */ +template +bool operator == (const Ptr& ptr1, const Ptr& ptr2); +template +bool operator != (const Ptr& ptr1, const Ptr& ptr2); + +/** `makePtr(...)` is equivalent to `Ptr(new T(...))`. It is shorter than the latter, and it's +marginally safer than using a constructor or Ptr::reset, since it ensures that the owned pointer +is new and thus not owned by any other Ptr instance. +Unfortunately, perfect forwarding is impossible to implement in C++03, and so makePtr is limited +to constructors of T that have up to 10 arguments, none of which are non-const references. + */ +template +Ptr makePtr(); +/** @overload */ +template +Ptr makePtr(const A1& a1); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9); +/** @overload */ +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9, const A10& a10); + +//////////////////////////////// string class //////////////////////////////// + +class CV_EXPORTS FileNode; //for string constructor from FileNode + +class CV_EXPORTS String +{ +public: + typedef char value_type; + typedef char& reference; + typedef const char& const_reference; + typedef char* pointer; + typedef const char* const_pointer; + typedef ptrdiff_t difference_type; + typedef size_t size_type; + typedef char* iterator; + typedef const char* const_iterator; + + static const size_t npos = size_t(-1); + + String(); + String(const String& str); + String(const String& str, size_t pos, size_t len = npos); + String(const char* s); + String(const char* s, size_t n); + String(size_t n, char c); + String(const char* first, const char* last); + template String(Iterator first, Iterator last); + explicit String(const FileNode& fn); + ~String(); + + String& operator=(const String& str); + String& operator=(const char* s); + String& operator=(char c); + + String& operator+=(const String& str); + String& operator+=(const char* s); + String& operator+=(char c); + + size_t size() const; + size_t length() const; + + char operator[](size_t idx) const; + char operator[](int idx) const; + + const char* begin() const; + const char* end() const; + + const char* c_str() const; + + bool empty() const; + void clear(); + + int compare(const char* s) const; + int compare(const String& str) const; + + void swap(String& str); + String substr(size_t pos = 0, size_t len = npos) const; + + size_t find(const char* s, size_t pos, size_t n) const; + size_t find(char c, size_t pos = 0) const; + size_t find(const String& str, size_t pos = 0) const; + size_t find(const char* s, size_t pos = 0) const; + + size_t rfind(const char* s, size_t pos, size_t n) const; + size_t rfind(char c, size_t pos = npos) const; + size_t rfind(const String& str, size_t pos = npos) const; + size_t rfind(const char* s, size_t pos = npos) const; + + size_t find_first_of(const char* s, size_t pos, size_t n) const; + size_t find_first_of(char c, size_t pos = 0) const; + size_t find_first_of(const String& str, size_t pos = 0) const; + size_t find_first_of(const char* s, size_t pos = 0) const; + + size_t find_last_of(const char* s, size_t pos, size_t n) const; + size_t find_last_of(char c, size_t pos = npos) const; + size_t find_last_of(const String& str, size_t pos = npos) const; + size_t find_last_of(const char* s, size_t pos = npos) const; + + friend String operator+ (const String& lhs, const String& rhs); + friend String operator+ (const String& lhs, const char* rhs); + friend String operator+ (const char* lhs, const String& rhs); + friend String operator+ (const String& lhs, char rhs); + friend String operator+ (char lhs, const String& rhs); + + String toLowerCase() const; + + String(const std::string& str); + String(const std::string& str, size_t pos, size_t len = npos); + String& operator=(const std::string& str); + String& operator+=(const std::string& str); + operator std::string() const; + + friend String operator+ (const String& lhs, const std::string& rhs); + friend String operator+ (const std::string& lhs, const String& rhs); + +private: + char* cstr_; + size_t len_; + + char* allocate(size_t len); // len without trailing 0 + void deallocate(); + + String(int); // disabled and invalid. Catch invalid usages like, commandLineParser.has(0) problem +}; + +//! @} core_basic + +////////////////////////// cv::String implementation ///////////////////////// + +//! @cond IGNORED + +inline +String::String() + : cstr_(0), len_(0) +{} + +inline +String::String(const String& str) + : cstr_(str.cstr_), len_(str.len_) +{ + if (cstr_) + CV_XADD(((int*)cstr_)-1, 1); +} + +inline +String::String(const String& str, size_t pos, size_t len) + : cstr_(0), len_(0) +{ + pos = min(pos, str.len_); + len = min(str.len_ - pos, len); + if (!len) return; + if (len == str.len_) + { + CV_XADD(((int*)str.cstr_)-1, 1); + cstr_ = str.cstr_; + len_ = str.len_; + return; + } + memcpy(allocate(len), str.cstr_ + pos, len); +} + +inline +String::String(const char* s) + : cstr_(0), len_(0) +{ + if (!s) return; + size_t len = strlen(s); + if (!len) return; + memcpy(allocate(len), s, len); +} + +inline +String::String(const char* s, size_t n) + : cstr_(0), len_(0) +{ + if (!n) return; + if (!s) return; + memcpy(allocate(n), s, n); +} + +inline +String::String(size_t n, char c) + : cstr_(0), len_(0) +{ + if (!n) return; + memset(allocate(n), c, n); +} + +inline +String::String(const char* first, const char* last) + : cstr_(0), len_(0) +{ + size_t len = (size_t)(last - first); + if (!len) return; + memcpy(allocate(len), first, len); +} + +template inline +String::String(Iterator first, Iterator last) + : cstr_(0), len_(0) +{ + size_t len = (size_t)(last - first); + if (!len) return; + char* str = allocate(len); + while (first != last) + { + *str++ = *first; + ++first; + } +} + +inline +String::~String() +{ + deallocate(); +} + +inline +String& String::operator=(const String& str) +{ + if (&str == this) return *this; + + deallocate(); + if (str.cstr_) CV_XADD(((int*)str.cstr_)-1, 1); + cstr_ = str.cstr_; + len_ = str.len_; + return *this; +} + +inline +String& String::operator=(const char* s) +{ + deallocate(); + if (!s) return *this; + size_t len = strlen(s); + if (len) memcpy(allocate(len), s, len); + return *this; +} + +inline +String& String::operator=(char c) +{ + deallocate(); + allocate(1)[0] = c; + return *this; +} + +inline +String& String::operator+=(const String& str) +{ + *this = *this + str; + return *this; +} + +inline +String& String::operator+=(const char* s) +{ + *this = *this + s; + return *this; +} + +inline +String& String::operator+=(char c) +{ + *this = *this + c; + return *this; +} + +inline +size_t String::size() const +{ + return len_; +} + +inline +size_t String::length() const +{ + return len_; +} + +inline +char String::operator[](size_t idx) const +{ + return cstr_[idx]; +} + +inline +char String::operator[](int idx) const +{ + return cstr_[idx]; +} + +inline +const char* String::begin() const +{ + return cstr_; +} + +inline +const char* String::end() const +{ + return len_ ? cstr_ + len_ : NULL; +} + +inline +bool String::empty() const +{ + return len_ == 0; +} + +inline +const char* String::c_str() const +{ + return cstr_ ? cstr_ : ""; +} + +inline +void String::swap(String& str) +{ + cv::swap(cstr_, str.cstr_); + cv::swap(len_, str.len_); +} + +inline +void String::clear() +{ + deallocate(); +} + +inline +int String::compare(const char* s) const +{ + if (cstr_ == s) return 0; + return strcmp(c_str(), s); +} + +inline +int String::compare(const String& str) const +{ + if (cstr_ == str.cstr_) return 0; + return strcmp(c_str(), str.c_str()); +} + +inline +String String::substr(size_t pos, size_t len) const +{ + return String(*this, pos, len); +} + +inline +size_t String::find(const char* s, size_t pos, size_t n) const +{ + if (n == 0 || pos + n > len_) return npos; + const char* lmax = cstr_ + len_ - n; + for (const char* i = cstr_ + pos; i <= lmax; ++i) + { + size_t j = 0; + while (j < n && s[j] == i[j]) ++j; + if (j == n) return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::find(char c, size_t pos) const +{ + return find(&c, pos, 1); +} + +inline +size_t String::find(const String& str, size_t pos) const +{ + return find(str.c_str(), pos, str.len_); +} + +inline +size_t String::find(const char* s, size_t pos) const +{ + if (pos >= len_ || !s[0]) return npos; + const char* lmax = cstr_ + len_; + for (const char* i = cstr_ + pos; i < lmax; ++i) + { + size_t j = 0; + while (s[j] && s[j] == i[j]) + { if(i + j >= lmax) return npos; + ++j; + } + if (!s[j]) return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::rfind(const char* s, size_t pos, size_t n) const +{ + if (n > len_) return npos; + if (pos > len_ - n) pos = len_ - n; + for (const char* i = cstr_ + pos; i >= cstr_; --i) + { + size_t j = 0; + while (j < n && s[j] == i[j]) ++j; + if (j == n) return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::rfind(char c, size_t pos) const +{ + return rfind(&c, pos, 1); +} + +inline +size_t String::rfind(const String& str, size_t pos) const +{ + return rfind(str.c_str(), pos, str.len_); +} + +inline +size_t String::rfind(const char* s, size_t pos) const +{ + return rfind(s, pos, strlen(s)); +} + +inline +size_t String::find_first_of(const char* s, size_t pos, size_t n) const +{ + if (n == 0 || pos + n > len_) return npos; + const char* lmax = cstr_ + len_; + for (const char* i = cstr_ + pos; i < lmax; ++i) + { + for (size_t j = 0; j < n; ++j) + if (s[j] == *i) + return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::find_first_of(char c, size_t pos) const +{ + return find_first_of(&c, pos, 1); +} + +inline +size_t String::find_first_of(const String& str, size_t pos) const +{ + return find_first_of(str.c_str(), pos, str.len_); +} + +inline +size_t String::find_first_of(const char* s, size_t pos) const +{ + if (len_ == 0) return npos; + if (pos >= len_ || !s[0]) return npos; + const char* lmax = cstr_ + len_; + for (const char* i = cstr_ + pos; i < lmax; ++i) + { + for (size_t j = 0; s[j]; ++j) + if (s[j] == *i) + return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::find_last_of(const char* s, size_t pos, size_t n) const +{ + if (len_ == 0) return npos; + if (pos >= len_) pos = len_ - 1; + for (const char* i = cstr_ + pos; i >= cstr_; --i) + { + for (size_t j = 0; j < n; ++j) + if (s[j] == *i) + return (size_t)(i - cstr_); + } + return npos; +} + +inline +size_t String::find_last_of(char c, size_t pos) const +{ + return find_last_of(&c, pos, 1); +} + +inline +size_t String::find_last_of(const String& str, size_t pos) const +{ + return find_last_of(str.c_str(), pos, str.len_); +} + +inline +size_t String::find_last_of(const char* s, size_t pos) const +{ + if (len_ == 0) return npos; + if (pos >= len_) pos = len_ - 1; + for (const char* i = cstr_ + pos; i >= cstr_; --i) + { + for (size_t j = 0; s[j]; ++j) + if (s[j] == *i) + return (size_t)(i - cstr_); + } + return npos; +} + +inline +String String::toLowerCase() const +{ + if (!cstr_) + return String(); + String res(cstr_, len_); + for (size_t i = 0; i < len_; ++i) + res.cstr_[i] = (char) ::tolower(cstr_[i]); + + return res; +} + +//! @endcond + +// ************************* cv::String non-member functions ************************* + +//! @relates cv::String +//! @{ + +inline +String operator + (const String& lhs, const String& rhs) +{ + String s; + s.allocate(lhs.len_ + rhs.len_); + if (lhs.len_) memcpy(s.cstr_, lhs.cstr_, lhs.len_); + if (rhs.len_) memcpy(s.cstr_ + lhs.len_, rhs.cstr_, rhs.len_); + return s; +} + +inline +String operator + (const String& lhs, const char* rhs) +{ + String s; + size_t rhslen = strlen(rhs); + s.allocate(lhs.len_ + rhslen); + if (lhs.len_) memcpy(s.cstr_, lhs.cstr_, lhs.len_); + if (rhslen) memcpy(s.cstr_ + lhs.len_, rhs, rhslen); + return s; +} + +inline +String operator + (const char* lhs, const String& rhs) +{ + String s; + size_t lhslen = strlen(lhs); + s.allocate(lhslen + rhs.len_); + if (lhslen) memcpy(s.cstr_, lhs, lhslen); + if (rhs.len_) memcpy(s.cstr_ + lhslen, rhs.cstr_, rhs.len_); + return s; +} + +inline +String operator + (const String& lhs, char rhs) +{ + String s; + s.allocate(lhs.len_ + 1); + if (lhs.len_) memcpy(s.cstr_, lhs.cstr_, lhs.len_); + s.cstr_[lhs.len_] = rhs; + return s; +} + +inline +String operator + (char lhs, const String& rhs) +{ + String s; + s.allocate(rhs.len_ + 1); + s.cstr_[0] = lhs; + if (rhs.len_) memcpy(s.cstr_ + 1, rhs.cstr_, rhs.len_); + return s; +} + +static inline bool operator== (const String& lhs, const String& rhs) { return 0 == lhs.compare(rhs); } +static inline bool operator== (const char* lhs, const String& rhs) { return 0 == rhs.compare(lhs); } +static inline bool operator== (const String& lhs, const char* rhs) { return 0 == lhs.compare(rhs); } +static inline bool operator!= (const String& lhs, const String& rhs) { return 0 != lhs.compare(rhs); } +static inline bool operator!= (const char* lhs, const String& rhs) { return 0 != rhs.compare(lhs); } +static inline bool operator!= (const String& lhs, const char* rhs) { return 0 != lhs.compare(rhs); } +static inline bool operator< (const String& lhs, const String& rhs) { return lhs.compare(rhs) < 0; } +static inline bool operator< (const char* lhs, const String& rhs) { return rhs.compare(lhs) > 0; } +static inline bool operator< (const String& lhs, const char* rhs) { return lhs.compare(rhs) < 0; } +static inline bool operator<= (const String& lhs, const String& rhs) { return lhs.compare(rhs) <= 0; } +static inline bool operator<= (const char* lhs, const String& rhs) { return rhs.compare(lhs) >= 0; } +static inline bool operator<= (const String& lhs, const char* rhs) { return lhs.compare(rhs) <= 0; } +static inline bool operator> (const String& lhs, const String& rhs) { return lhs.compare(rhs) > 0; } +static inline bool operator> (const char* lhs, const String& rhs) { return rhs.compare(lhs) < 0; } +static inline bool operator> (const String& lhs, const char* rhs) { return lhs.compare(rhs) > 0; } +static inline bool operator>= (const String& lhs, const String& rhs) { return lhs.compare(rhs) >= 0; } +static inline bool operator>= (const char* lhs, const String& rhs) { return rhs.compare(lhs) <= 0; } +static inline bool operator>= (const String& lhs, const char* rhs) { return lhs.compare(rhs) >= 0; } + +//! @} relates cv::String + +} // cv + +namespace std +{ + static inline void swap(cv::String& a, cv::String& b) { a.swap(b); } +} + +#include "opencv2/core/ptr.inl.hpp" + +#endif //OPENCV_CORE_CVSTD_HPP diff --git a/3rdparty/opencv/include/opencv2/core/cvstd.inl.hpp b/3rdparty/opencv/include/opencv2/core/cvstd.inl.hpp new file mode 100644 index 00000000..ed37cacb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/cvstd.inl.hpp @@ -0,0 +1,285 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_CVSTDINL_HPP +#define OPENCV_CORE_CVSTDINL_HPP + +#include +#include + +//! @cond IGNORED + +#ifdef _MSC_VER +#pragma warning( push ) +#pragma warning( disable: 4127 ) +#endif + +namespace cv +{ + +template class DataType< std::complex<_Tp> > +{ +public: + typedef std::complex<_Tp> value_type; + typedef value_type work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + depth = DataType::depth, + channels = 2, + fmt = DataType::fmt + ((channels - 1) << 8), + type = CV_MAKETYPE(depth, channels) }; + + typedef Vec vec_type; +}; + +inline +String::String(const std::string& str) + : cstr_(0), len_(0) +{ + size_t len = str.size(); + if (len) memcpy(allocate(len), str.c_str(), len); +} + +inline +String::String(const std::string& str, size_t pos, size_t len) + : cstr_(0), len_(0) +{ + size_t strlen = str.size(); + pos = min(pos, strlen); + len = min(strlen - pos, len); + if (!len) return; + memcpy(allocate(len), str.c_str() + pos, len); +} + +inline +String& String::operator = (const std::string& str) +{ + deallocate(); + size_t len = str.size(); + if (len) memcpy(allocate(len), str.c_str(), len); + return *this; +} + +inline +String& String::operator += (const std::string& str) +{ + *this = *this + str; + return *this; +} + +inline +String::operator std::string() const +{ + return std::string(cstr_, len_); +} + +inline +String operator + (const String& lhs, const std::string& rhs) +{ + String s; + size_t rhslen = rhs.size(); + s.allocate(lhs.len_ + rhslen); + if (lhs.len_) memcpy(s.cstr_, lhs.cstr_, lhs.len_); + if (rhslen) memcpy(s.cstr_ + lhs.len_, rhs.c_str(), rhslen); + return s; +} + +inline +String operator + (const std::string& lhs, const String& rhs) +{ + String s; + size_t lhslen = lhs.size(); + s.allocate(lhslen + rhs.len_); + if (lhslen) memcpy(s.cstr_, lhs.c_str(), lhslen); + if (rhs.len_) memcpy(s.cstr_ + lhslen, rhs.cstr_, rhs.len_); + return s; +} + +inline +FileNode::operator std::string() const +{ + String value; + read(*this, value, value); + return value; +} + +template<> inline +void operator >> (const FileNode& n, std::string& value) +{ + read(n, value, std::string()); +} + +template<> inline +FileStorage& operator << (FileStorage& fs, const std::string& value) +{ + return fs << cv::String(value); +} + +static inline +std::ostream& operator << (std::ostream& os, const String& str) +{ + return os << str.c_str(); +} + +static inline +std::ostream& operator << (std::ostream& out, Ptr fmtd) +{ + fmtd->reset(); + for(const char* str = fmtd->next(); str; str = fmtd->next()) + out << str; + return out; +} + +static inline +std::ostream& operator << (std::ostream& out, const Mat& mtx) +{ + return out << Formatter::get()->format(mtx); +} + +static inline +std::ostream& operator << (std::ostream& out, const UMat& m) +{ + return out << m.getMat(ACCESS_READ); +} + +template static inline +std::ostream& operator << (std::ostream& out, const Complex<_Tp>& c) +{ + return out << "(" << c.re << "," << c.im << ")"; +} + +template static inline +std::ostream& operator << (std::ostream& out, const std::vector >& vec) +{ + return out << Formatter::get()->format(Mat(vec)); +} + + +template static inline +std::ostream& operator << (std::ostream& out, const std::vector >& vec) +{ + return out << Formatter::get()->format(Mat(vec)); +} + + +template static inline +std::ostream& operator << (std::ostream& out, const Matx<_Tp, m, n>& matx) +{ + return out << Formatter::get()->format(Mat(matx)); +} + +template static inline +std::ostream& operator << (std::ostream& out, const Point_<_Tp>& p) +{ + out << "[" << p.x << ", " << p.y << "]"; + return out; +} + +template static inline +std::ostream& operator << (std::ostream& out, const Point3_<_Tp>& p) +{ + out << "[" << p.x << ", " << p.y << ", " << p.z << "]"; + return out; +} + +template static inline +std::ostream& operator << (std::ostream& out, const Vec<_Tp, n>& vec) +{ + out << "["; + if (cv::traits::Depth<_Tp>::value <= CV_32S) + { + for (int i = 0; i < n - 1; ++i) { + out << (int)vec[i] << ", "; + } + out << (int)vec[n-1] << "]"; + } + else + { + for (int i = 0; i < n - 1; ++i) { + out << vec[i] << ", "; + } + out << vec[n-1] << "]"; + } + + return out; +} + +template static inline +std::ostream& operator << (std::ostream& out, const Size_<_Tp>& size) +{ + return out << "[" << size.width << " x " << size.height << "]"; +} + +template static inline +std::ostream& operator << (std::ostream& out, const Rect_<_Tp>& rect) +{ + return out << "[" << rect.width << " x " << rect.height << " from (" << rect.x << ", " << rect.y << ")]"; +} + +static inline std::ostream& operator << (std::ostream& out, const MatSize& msize) +{ + int i, dims = msize.dims(); + for( i = 0; i < dims; i++ ) + { + out << msize[i]; + if( i < dims-1 ) + out << " x "; + } + return out; +} + +static inline std::ostream &operator<< (std::ostream &s, cv::Range &r) +{ + return s << "[" << r.start << " : " << r.end << ")"; +} + +} // cv + +#ifdef _MSC_VER +#pragma warning( pop ) +#endif + +//! @endcond + +#endif // OPENCV_CORE_CVSTDINL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/directx.hpp b/3rdparty/opencv/include/opencv2/core/directx.hpp new file mode 100644 index 00000000..056a85a1 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/directx.hpp @@ -0,0 +1,184 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors as is and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the copyright holders or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_DIRECTX_HPP +#define OPENCV_CORE_DIRECTX_HPP + +#include "mat.hpp" +#include "ocl.hpp" + +#if !defined(__d3d11_h__) +struct ID3D11Device; +struct ID3D11Texture2D; +#endif + +#if !defined(__d3d10_h__) +struct ID3D10Device; +struct ID3D10Texture2D; +#endif + +#if !defined(_D3D9_H_) +struct IDirect3DDevice9; +struct IDirect3DDevice9Ex; +struct IDirect3DSurface9; +#endif + + +namespace cv { namespace directx { + +namespace ocl { +using namespace cv::ocl; + +//! @addtogroup core_directx +// This section describes OpenCL and DirectX interoperability. +// +// To enable DirectX support, configure OpenCV using CMake with WITH_DIRECTX=ON . Note, DirectX is +// supported only on Windows. +// +// To use OpenCL functionality you should first initialize OpenCL context from DirectX resource. +// +//! @{ + +// TODO static functions in the Context class +//! @brief Creates OpenCL context from D3D11 device +// +//! @param pD3D11Device - pointer to D3D11 device +//! @return Returns reference to OpenCL Context +CV_EXPORTS Context& initializeContextFromD3D11Device(ID3D11Device* pD3D11Device); + +//! @brief Creates OpenCL context from D3D10 device +// +//! @param pD3D10Device - pointer to D3D10 device +//! @return Returns reference to OpenCL Context +CV_EXPORTS Context& initializeContextFromD3D10Device(ID3D10Device* pD3D10Device); + +//! @brief Creates OpenCL context from Direct3DDevice9Ex device +// +//! @param pDirect3DDevice9Ex - pointer to Direct3DDevice9Ex device +//! @return Returns reference to OpenCL Context +CV_EXPORTS Context& initializeContextFromDirect3DDevice9Ex(IDirect3DDevice9Ex* pDirect3DDevice9Ex); + +//! @brief Creates OpenCL context from Direct3DDevice9 device +// +//! @param pDirect3DDevice9 - pointer to Direct3Device9 device +//! @return Returns reference to OpenCL Context +CV_EXPORTS Context& initializeContextFromDirect3DDevice9(IDirect3DDevice9* pDirect3DDevice9); + +//! @} + +} // namespace cv::directx::ocl + +//! @addtogroup core_directx +//! @{ + +//! @brief Converts InputArray to ID3D11Texture2D. If destination texture format is DXGI_FORMAT_NV12 then +//! input UMat expected to be in BGR format and data will be downsampled and color-converted to NV12. +// +//! @note Note: Destination texture must be allocated by application. Function does memory copy from src to +//! pD3D11Texture2D +// +//! @param src - source InputArray +//! @param pD3D11Texture2D - destination D3D11 texture +CV_EXPORTS void convertToD3D11Texture2D(InputArray src, ID3D11Texture2D* pD3D11Texture2D); + +//! @brief Converts ID3D11Texture2D to OutputArray. If input texture format is DXGI_FORMAT_NV12 then +//! data will be upsampled and color-converted to BGR format. +// +//! @note Note: Destination matrix will be re-allocated if it has not enough memory to match texture size. +//! function does memory copy from pD3D11Texture2D to dst +// +//! @param pD3D11Texture2D - source D3D11 texture +//! @param dst - destination OutputArray +CV_EXPORTS void convertFromD3D11Texture2D(ID3D11Texture2D* pD3D11Texture2D, OutputArray dst); + +//! @brief Converts InputArray to ID3D10Texture2D +// +//! @note Note: function does memory copy from src to +//! pD3D10Texture2D +// +//! @param src - source InputArray +//! @param pD3D10Texture2D - destination D3D10 texture +CV_EXPORTS void convertToD3D10Texture2D(InputArray src, ID3D10Texture2D* pD3D10Texture2D); + +//! @brief Converts ID3D10Texture2D to OutputArray +// +//! @note Note: function does memory copy from pD3D10Texture2D +//! to dst +// +//! @param pD3D10Texture2D - source D3D10 texture +//! @param dst - destination OutputArray +CV_EXPORTS void convertFromD3D10Texture2D(ID3D10Texture2D* pD3D10Texture2D, OutputArray dst); + +//! @brief Converts InputArray to IDirect3DSurface9 +// +//! @note Note: function does memory copy from src to +//! pDirect3DSurface9 +// +//! @param src - source InputArray +//! @param pDirect3DSurface9 - destination D3D10 texture +//! @param surfaceSharedHandle - shared handle +CV_EXPORTS void convertToDirect3DSurface9(InputArray src, IDirect3DSurface9* pDirect3DSurface9, void* surfaceSharedHandle = NULL); + +//! @brief Converts IDirect3DSurface9 to OutputArray +// +//! @note Note: function does memory copy from pDirect3DSurface9 +//! to dst +// +//! @param pDirect3DSurface9 - source D3D10 texture +//! @param dst - destination OutputArray +//! @param surfaceSharedHandle - shared handle +CV_EXPORTS void convertFromDirect3DSurface9(IDirect3DSurface9* pDirect3DSurface9, OutputArray dst, void* surfaceSharedHandle = NULL); + +//! @brief Get OpenCV type from DirectX type +//! @param iDXGI_FORMAT - enum DXGI_FORMAT for D3D10/D3D11 +//! @return OpenCV type or -1 if there is no equivalent +CV_EXPORTS int getTypeFromDXGI_FORMAT(const int iDXGI_FORMAT); // enum DXGI_FORMAT for D3D10/D3D11 + +//! @brief Get OpenCV type from DirectX type +//! @param iD3DFORMAT - enum D3DTYPE for D3D9 +//! @return OpenCV type or -1 if there is no equivalent +CV_EXPORTS int getTypeFromD3DFORMAT(const int iD3DFORMAT); // enum D3DTYPE for D3D9 + +//! @} + +} } // namespace cv::directx + +#endif // OPENCV_CORE_DIRECTX_HPP diff --git a/3rdparty/opencv/include/opencv2/core/eigen.hpp b/3rdparty/opencv/include/opencv2/core/eigen.hpp new file mode 100644 index 00000000..741648ed --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/eigen.hpp @@ -0,0 +1,280 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + + +#ifndef OPENCV_CORE_EIGEN_HPP +#define OPENCV_CORE_EIGEN_HPP + +#include "opencv2/core.hpp" + +#if defined _MSC_VER && _MSC_VER >= 1200 +#pragma warning( disable: 4714 ) //__forceinline is not inlined +#pragma warning( disable: 4127 ) //conditional expression is constant +#pragma warning( disable: 4244 ) //conversion from '__int64' to 'int', possible loss of data +#endif + +namespace cv +{ + +//! @addtogroup core_eigen +//! @{ + +template static inline +void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src, OutputArray dst ) +{ + if( !(src.Flags & Eigen::RowMajorBit) ) + { + Mat _src(src.cols(), src.rows(), traits::Type<_Tp>::value, + (void*)src.data(), src.outerStride()*sizeof(_Tp)); + transpose(_src, dst); + } + else + { + Mat _src(src.rows(), src.cols(), traits::Type<_Tp>::value, + (void*)src.data(), src.outerStride()*sizeof(_Tp)); + _src.copyTo(dst); + } +} + +// Matx case +template static inline +void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src, + Matx<_Tp, _rows, _cols>& dst ) +{ + if( !(src.Flags & Eigen::RowMajorBit) ) + { + dst = Matx<_Tp, _cols, _rows>(static_cast(src.data())).t(); + } + else + { + dst = Matx<_Tp, _rows, _cols>(static_cast(src.data())); + } +} + +template static inline +void cv2eigen( const Mat& src, + Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst ) +{ + CV_DbgAssert(src.rows == _rows && src.cols == _cols); + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + if( src.type() == _dst.type() ) + transpose(src, _dst); + else if( src.cols == src.rows ) + { + src.convertTo(_dst, _dst.type()); + transpose(_dst, _dst); + } + else + Mat(src.t()).convertTo(_dst, _dst.type()); + } + else + { + const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + src.convertTo(_dst, _dst.type()); + } +} + +// Matx case +template static inline +void cv2eigen( const Matx<_Tp, _rows, _cols>& src, + Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst ) +{ + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(_cols, _rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + transpose(src, _dst); + } + else + { + const Mat _dst(_rows, _cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + Mat(src).copyTo(_dst); + } +} + +template static inline +void cv2eigen( const Mat& src, + Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst ) +{ + dst.resize(src.rows, src.cols); + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + if( src.type() == _dst.type() ) + transpose(src, _dst); + else if( src.cols == src.rows ) + { + src.convertTo(_dst, _dst.type()); + transpose(_dst, _dst); + } + else + Mat(src.t()).convertTo(_dst, _dst.type()); + } + else + { + const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + src.convertTo(_dst, _dst.type()); + } +} + +// Matx case +template static inline +void cv2eigen( const Matx<_Tp, _rows, _cols>& src, + Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst ) +{ + dst.resize(_rows, _cols); + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(_cols, _rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + transpose(src, _dst); + } + else + { + const Mat _dst(_rows, _cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + Mat(src).copyTo(_dst); + } +} + +template static inline +void cv2eigen( const Mat& src, + Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst ) +{ + CV_Assert(src.cols == 1); + dst.resize(src.rows); + + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + if( src.type() == _dst.type() ) + transpose(src, _dst); + else + Mat(src.t()).convertTo(_dst, _dst.type()); + } + else + { + const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + src.convertTo(_dst, _dst.type()); + } +} + +// Matx case +template static inline +void cv2eigen( const Matx<_Tp, _rows, 1>& src, + Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst ) +{ + dst.resize(_rows); + + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(1, _rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + transpose(src, _dst); + } + else + { + const Mat _dst(_rows, 1, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + src.copyTo(_dst); + } +} + + +template static inline +void cv2eigen( const Mat& src, + Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst ) +{ + CV_Assert(src.rows == 1); + dst.resize(src.cols); + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + if( src.type() == _dst.type() ) + transpose(src, _dst); + else + Mat(src.t()).convertTo(_dst, _dst.type()); + } + else + { + const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + src.convertTo(_dst, _dst.type()); + } +} + +//Matx +template static inline +void cv2eigen( const Matx<_Tp, 1, _cols>& src, + Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst ) +{ + dst.resize(_cols); + if( !(dst.Flags & Eigen::RowMajorBit) ) + { + const Mat _dst(_cols, 1, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + transpose(src, _dst); + } + else + { + const Mat _dst(1, _cols, traits::Type<_Tp>::value, + dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp))); + Mat(src).copyTo(_dst); + } +} + +//! @} + +} // cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/fast_math.hpp b/3rdparty/opencv/include/opencv2/core/fast_math.hpp new file mode 100644 index 00000000..d9ea28e6 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/fast_math.hpp @@ -0,0 +1,271 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_FAST_MATH_HPP +#define OPENCV_CORE_FAST_MATH_HPP + +#include "opencv2/core/cvdef.h" + +#if ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ \ + && defined __SSE2__ && !defined __APPLE__)) && !defined(__CUDACC__) +#include +#endif + + +//! @addtogroup core_utils +//! @{ + +/****************************************************************************************\ +* fast math * +\****************************************************************************************/ + +#ifdef __cplusplus +# include +#else +# ifdef __BORLANDC__ +# include +# else +# include +# endif +#endif + +#ifdef HAVE_TEGRA_OPTIMIZATION +# include "tegra_round.hpp" +#endif + +#if defined __GNUC__ && defined __arm__ && (defined __ARM_PCS_VFP || defined __ARM_VFPV3__ || defined __ARM_NEON__) && !defined __SOFTFP__ && !defined(__CUDACC__) + // 1. general scheme + #define ARM_ROUND(_value, _asm_string) \ + int res; \ + float temp; \ + CV_UNUSED(temp); \ + __asm__(_asm_string : [res] "=r" (res), [temp] "=w" (temp) : [value] "w" (_value)); \ + return res + // 2. version for double + #ifdef __clang__ + #define ARM_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %[value] \n vmov %[res], %[temp]") + #else + #define ARM_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %P[value] \n vmov %[res], %[temp]") + #endif + // 3. version for float + #define ARM_ROUND_FLT(value) ARM_ROUND(value, "vcvtr.s32.f32 %[temp], %[value]\n vmov %[res], %[temp]") +#endif + +/** @brief Rounds floating-point number to the nearest integer + + @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the + result is not defined. + */ +CV_INLINE int +cvRound( double value ) +{ +#if ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ \ + && defined __SSE2__ && !defined __APPLE__) || CV_SSE2) && !defined(__CUDACC__) + __m128d t = _mm_set_sd( value ); + return _mm_cvtsd_si32(t); +#elif defined _MSC_VER && defined _M_IX86 + int t; + __asm + { + fld value; + fistp t; + } + return t; +#elif ((defined _MSC_VER && defined _M_ARM) || defined CV_ICC || \ + defined __GNUC__) && defined HAVE_TEGRA_OPTIMIZATION + TEGRA_ROUND_DBL(value); +#elif defined CV_ICC || defined __GNUC__ +# if defined ARM_ROUND_DBL + ARM_ROUND_DBL(value); +# else + return (int)lrint(value); +# endif +#else + /* it's ok if round does not comply with IEEE754 standard; + the tests should allow +/-1 difference when the tested functions use round */ + return (int)(value + (value >= 0 ? 0.5 : -0.5)); +#endif +} + + +/** @brief Rounds floating-point number to the nearest integer not larger than the original. + + The function computes an integer i such that: + \f[i \le \texttt{value} < i+1\f] + @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the + result is not defined. + */ +CV_INLINE int cvFloor( double value ) +{ + int i = (int)value; + return i - (i > value); +} + +/** @brief Rounds floating-point number to the nearest integer not smaller than the original. + + The function computes an integer i such that: + \f[i \le \texttt{value} < i+1\f] + @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the + result is not defined. + */ +CV_INLINE int cvCeil( double value ) +{ + int i = (int)value; + return i + (i < value); +} + +/** @brief Determines if the argument is Not A Number. + + @param value The input floating-point value + + The function returns 1 if the argument is Not A Number (as defined by IEEE754 standard), 0 + otherwise. */ +CV_INLINE int cvIsNaN( double value ) +{ + Cv64suf ieee754; + ieee754.f = value; + return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) + + ((unsigned)ieee754.u != 0) > 0x7ff00000; +} + +/** @brief Determines if the argument is Infinity. + + @param value The input floating-point value + + The function returns 1 if the argument is a plus or minus infinity (as defined by IEEE754 standard) + and 0 otherwise. */ +CV_INLINE int cvIsInf( double value ) +{ + Cv64suf ieee754; + ieee754.f = value; + return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) == 0x7ff00000 && + (unsigned)ieee754.u == 0; +} + +#ifdef __cplusplus + +/** @overload */ +CV_INLINE int cvRound(float value) +{ +#if ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __x86_64__ \ + && defined __SSE2__ && !defined __APPLE__) || CV_SSE2) && !defined(__CUDACC__) + __m128 t = _mm_set_ss( value ); + return _mm_cvtss_si32(t); +#elif defined _MSC_VER && defined _M_IX86 + int t; + __asm + { + fld value; + fistp t; + } + return t; +#elif ((defined _MSC_VER && defined _M_ARM) || defined CV_ICC || \ + defined __GNUC__) && defined HAVE_TEGRA_OPTIMIZATION + TEGRA_ROUND_FLT(value); +#elif defined CV_ICC || defined __GNUC__ +# if defined ARM_ROUND_FLT + ARM_ROUND_FLT(value); +# else + return (int)lrintf(value); +# endif +#else + /* it's ok if round does not comply with IEEE754 standard; + the tests should allow +/-1 difference when the tested functions use round */ + return (int)(value + (value >= 0 ? 0.5f : -0.5f)); +#endif +} + +/** @overload */ +CV_INLINE int cvRound( int value ) +{ + return value; +} + +/** @overload */ +CV_INLINE int cvFloor( float value ) +{ + int i = (int)value; + return i - (i > value); +} + +/** @overload */ +CV_INLINE int cvFloor( int value ) +{ + return value; +} + +/** @overload */ +CV_INLINE int cvCeil( float value ) +{ + int i = (int)value; + return i + (i < value); +} + +/** @overload */ +CV_INLINE int cvCeil( int value ) +{ + return value; +} + +/** @overload */ +CV_INLINE int cvIsNaN( float value ) +{ + Cv32suf ieee754; + ieee754.f = value; + return (ieee754.u & 0x7fffffff) > 0x7f800000; +} + +/** @overload */ +CV_INLINE int cvIsInf( float value ) +{ + Cv32suf ieee754; + ieee754.f = value; + return (ieee754.u & 0x7fffffff) == 0x7f800000; +} + +#endif // __cplusplus + +//! @} core_utils + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/hal.hpp b/3rdparty/opencv/include/opencv2/core/hal/hal.hpp new file mode 100644 index 00000000..68900ec4 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/hal.hpp @@ -0,0 +1,250 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_HPP +#define OPENCV_HAL_HPP + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/cvstd.hpp" +#include "opencv2/core/hal/interface.h" + +namespace cv { namespace hal { + +//! @addtogroup core_hal_functions +//! @{ + +CV_EXPORTS int normHamming(const uchar* a, int n); +CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n); + +CV_EXPORTS int normHamming(const uchar* a, int n, int cellSize); +CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n, int cellSize); + +CV_EXPORTS int LU32f(float* A, size_t astep, int m, float* b, size_t bstep, int n); +CV_EXPORTS int LU64f(double* A, size_t astep, int m, double* b, size_t bstep, int n); +CV_EXPORTS bool Cholesky32f(float* A, size_t astep, int m, float* b, size_t bstep, int n); +CV_EXPORTS bool Cholesky64f(double* A, size_t astep, int m, double* b, size_t bstep, int n); +CV_EXPORTS void SVD32f(float* At, size_t astep, float* W, float* U, size_t ustep, float* Vt, size_t vstep, int m, int n, int flags); +CV_EXPORTS void SVD64f(double* At, size_t astep, double* W, double* U, size_t ustep, double* Vt, size_t vstep, int m, int n, int flags); +CV_EXPORTS int QR32f(float* A, size_t astep, int m, int n, int k, float* b, size_t bstep, float* hFactors); +CV_EXPORTS int QR64f(double* A, size_t astep, int m, int n, int k, double* b, size_t bstep, double* hFactors); + +CV_EXPORTS void gemm32f(const float* src1, size_t src1_step, const float* src2, size_t src2_step, + float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step, + int m_a, int n_a, int n_d, int flags); +CV_EXPORTS void gemm64f(const double* src1, size_t src1_step, const double* src2, size_t src2_step, + double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step, + int m_a, int n_a, int n_d, int flags); +CV_EXPORTS void gemm32fc(const float* src1, size_t src1_step, const float* src2, size_t src2_step, + float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step, + int m_a, int n_a, int n_d, int flags); +CV_EXPORTS void gemm64fc(const double* src1, size_t src1_step, const double* src2, size_t src2_step, + double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step, + int m_a, int n_a, int n_d, int flags); + +CV_EXPORTS int normL1_(const uchar* a, const uchar* b, int n); +CV_EXPORTS float normL1_(const float* a, const float* b, int n); +CV_EXPORTS float normL2Sqr_(const float* a, const float* b, int n); + +CV_EXPORTS void exp32f(const float* src, float* dst, int n); +CV_EXPORTS void exp64f(const double* src, double* dst, int n); +CV_EXPORTS void log32f(const float* src, float* dst, int n); +CV_EXPORTS void log64f(const double* src, double* dst, int n); + +CV_EXPORTS void fastAtan32f(const float* y, const float* x, float* dst, int n, bool angleInDegrees); +CV_EXPORTS void fastAtan64f(const double* y, const double* x, double* dst, int n, bool angleInDegrees); +CV_EXPORTS void magnitude32f(const float* x, const float* y, float* dst, int n); +CV_EXPORTS void magnitude64f(const double* x, const double* y, double* dst, int n); +CV_EXPORTS void sqrt32f(const float* src, float* dst, int len); +CV_EXPORTS void sqrt64f(const double* src, double* dst, int len); +CV_EXPORTS void invSqrt32f(const float* src, float* dst, int len); +CV_EXPORTS void invSqrt64f(const double* src, double* dst, int len); + +CV_EXPORTS void split8u(const uchar* src, uchar** dst, int len, int cn ); +CV_EXPORTS void split16u(const ushort* src, ushort** dst, int len, int cn ); +CV_EXPORTS void split32s(const int* src, int** dst, int len, int cn ); +CV_EXPORTS void split64s(const int64* src, int64** dst, int len, int cn ); + +CV_EXPORTS void merge8u(const uchar** src, uchar* dst, int len, int cn ); +CV_EXPORTS void merge16u(const ushort** src, ushort* dst, int len, int cn ); +CV_EXPORTS void merge32s(const int** src, int* dst, int len, int cn ); +CV_EXPORTS void merge64s(const int64** src, int64* dst, int len, int cn ); + +CV_EXPORTS void add8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void add64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void sub8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void sub64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void max8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void max64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void min8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void min64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void absdiff8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void absdiff64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void and8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void or8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void xor8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); +CV_EXPORTS void not8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* ); + +CV_EXPORTS void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp32s(const int* src1, size_t step1, const int* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); +CV_EXPORTS void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop); + +CV_EXPORTS void mul8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void mul64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale); + +CV_EXPORTS void div8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void div64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale); + +CV_EXPORTS void recip8u( const uchar *, size_t, const uchar * src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip8s( const schar *, size_t, const schar * src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip16u( const ushort *, size_t, const ushort * src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip16s( const short *, size_t, const short * src2, size_t step2, short* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip32s( const int *, size_t, const int * src2, size_t step2, int* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip32f( const float *, size_t, const float * src2, size_t step2, float* dst, size_t step, int width, int height, void* scale); +CV_EXPORTS void recip64f( const double *, size_t, const double * src2, size_t step2, double* dst, size_t step, int width, int height, void* scale); + +CV_EXPORTS void addWeighted8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _scalars ); +CV_EXPORTS void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scalars ); +CV_EXPORTS void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scalars ); +CV_EXPORTS void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scalars ); +CV_EXPORTS void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scalars ); +CV_EXPORTS void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scalars ); +CV_EXPORTS void addWeighted64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scalars ); + +struct CV_EXPORTS DFT1D +{ + static Ptr create(int len, int count, int depth, int flags, bool * useBuffer = 0); + virtual void apply(const uchar *src, uchar *dst) = 0; + virtual ~DFT1D() {} +}; + +struct CV_EXPORTS DFT2D +{ + static Ptr create(int width, int height, int depth, + int src_channels, int dst_channels, + int flags, int nonzero_rows = 0); + virtual void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) = 0; + virtual ~DFT2D() {} +}; + +struct CV_EXPORTS DCT2D +{ + static Ptr create(int width, int height, int depth, int flags); + virtual void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) = 0; + virtual ~DCT2D() {} +}; + +//! @} core_hal + +//============================================================================= +// for binary compatibility with 3.0 + +//! @cond IGNORED + +CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n); +CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n); +CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n); +CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n); + +CV_EXPORTS void exp(const float* src, float* dst, int n); +CV_EXPORTS void exp(const double* src, double* dst, int n); +CV_EXPORTS void log(const float* src, float* dst, int n); +CV_EXPORTS void log(const double* src, double* dst, int n); + +CV_EXPORTS void fastAtan2(const float* y, const float* x, float* dst, int n, bool angleInDegrees); +CV_EXPORTS void magnitude(const float* x, const float* y, float* dst, int n); +CV_EXPORTS void magnitude(const double* x, const double* y, double* dst, int n); +CV_EXPORTS void sqrt(const float* src, float* dst, int len); +CV_EXPORTS void sqrt(const double* src, double* dst, int len); +CV_EXPORTS void invSqrt(const float* src, float* dst, int len); +CV_EXPORTS void invSqrt(const double* src, double* dst, int len); + +//! @endcond + +}} //cv::hal + +#endif //OPENCV_HAL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/hal/interface.h b/3rdparty/opencv/include/opencv2/core/hal/interface.h new file mode 100644 index 00000000..8f640254 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/interface.h @@ -0,0 +1,182 @@ +#ifndef OPENCV_CORE_HAL_INTERFACE_H +#define OPENCV_CORE_HAL_INTERFACE_H + +//! @addtogroup core_hal_interface +//! @{ + +//! @name Return codes +//! @{ +#define CV_HAL_ERROR_OK 0 +#define CV_HAL_ERROR_NOT_IMPLEMENTED 1 +#define CV_HAL_ERROR_UNKNOWN -1 +//! @} + +#ifdef __cplusplus +#include +#else +#include +#include +#endif + +//! @name Data types +//! primitive types +//! - schar - signed 1 byte integer +//! - uchar - unsigned 1 byte integer +//! - short - signed 2 byte integer +//! - ushort - unsigned 2 byte integer +//! - int - signed 4 byte integer +//! - uint - unsigned 4 byte integer +//! - int64 - signed 8 byte integer +//! - uint64 - unsigned 8 byte integer +//! @{ +#if !defined _MSC_VER && !defined __BORLANDC__ +# if defined __cplusplus && __cplusplus >= 201103L && !defined __APPLE__ +# include +# ifdef __NEWLIB__ + typedef unsigned int uint; +# else + typedef std::uint32_t uint; +# endif +# else +# include + typedef uint32_t uint; +# endif +#else + typedef unsigned uint; +#endif + +typedef signed char schar; + +#ifndef __IPL_H__ + typedef unsigned char uchar; + typedef unsigned short ushort; +#endif + +#if defined _MSC_VER || defined __BORLANDC__ + typedef __int64 int64; + typedef unsigned __int64 uint64; +# define CV_BIG_INT(n) n##I64 +# define CV_BIG_UINT(n) n##UI64 +#else + typedef int64_t int64; + typedef uint64_t uint64; +# define CV_BIG_INT(n) n##LL +# define CV_BIG_UINT(n) n##ULL +#endif + +#define CV_CN_MAX 512 +#define CV_CN_SHIFT 3 +#define CV_DEPTH_MAX (1 << CV_CN_SHIFT) + +#define CV_8U 0 +#define CV_8S 1 +#define CV_16U 2 +#define CV_16S 3 +#define CV_32S 4 +#define CV_32F 5 +#define CV_64F 6 +#define CV_USRTYPE1 7 + +#define CV_MAT_DEPTH_MASK (CV_DEPTH_MAX - 1) +#define CV_MAT_DEPTH(flags) ((flags) & CV_MAT_DEPTH_MASK) + +#define CV_MAKETYPE(depth,cn) (CV_MAT_DEPTH(depth) + (((cn)-1) << CV_CN_SHIFT)) +#define CV_MAKE_TYPE CV_MAKETYPE + +#define CV_8UC1 CV_MAKETYPE(CV_8U,1) +#define CV_8UC2 CV_MAKETYPE(CV_8U,2) +#define CV_8UC3 CV_MAKETYPE(CV_8U,3) +#define CV_8UC4 CV_MAKETYPE(CV_8U,4) +#define CV_8UC(n) CV_MAKETYPE(CV_8U,(n)) + +#define CV_8SC1 CV_MAKETYPE(CV_8S,1) +#define CV_8SC2 CV_MAKETYPE(CV_8S,2) +#define CV_8SC3 CV_MAKETYPE(CV_8S,3) +#define CV_8SC4 CV_MAKETYPE(CV_8S,4) +#define CV_8SC(n) CV_MAKETYPE(CV_8S,(n)) + +#define CV_16UC1 CV_MAKETYPE(CV_16U,1) +#define CV_16UC2 CV_MAKETYPE(CV_16U,2) +#define CV_16UC3 CV_MAKETYPE(CV_16U,3) +#define CV_16UC4 CV_MAKETYPE(CV_16U,4) +#define CV_16UC(n) CV_MAKETYPE(CV_16U,(n)) + +#define CV_16SC1 CV_MAKETYPE(CV_16S,1) +#define CV_16SC2 CV_MAKETYPE(CV_16S,2) +#define CV_16SC3 CV_MAKETYPE(CV_16S,3) +#define CV_16SC4 CV_MAKETYPE(CV_16S,4) +#define CV_16SC(n) CV_MAKETYPE(CV_16S,(n)) + +#define CV_32SC1 CV_MAKETYPE(CV_32S,1) +#define CV_32SC2 CV_MAKETYPE(CV_32S,2) +#define CV_32SC3 CV_MAKETYPE(CV_32S,3) +#define CV_32SC4 CV_MAKETYPE(CV_32S,4) +#define CV_32SC(n) CV_MAKETYPE(CV_32S,(n)) + +#define CV_32FC1 CV_MAKETYPE(CV_32F,1) +#define CV_32FC2 CV_MAKETYPE(CV_32F,2) +#define CV_32FC3 CV_MAKETYPE(CV_32F,3) +#define CV_32FC4 CV_MAKETYPE(CV_32F,4) +#define CV_32FC(n) CV_MAKETYPE(CV_32F,(n)) + +#define CV_64FC1 CV_MAKETYPE(CV_64F,1) +#define CV_64FC2 CV_MAKETYPE(CV_64F,2) +#define CV_64FC3 CV_MAKETYPE(CV_64F,3) +#define CV_64FC4 CV_MAKETYPE(CV_64F,4) +#define CV_64FC(n) CV_MAKETYPE(CV_64F,(n)) +//! @} + +//! @name Comparison operation +//! @sa cv::CmpTypes +//! @{ +#define CV_HAL_CMP_EQ 0 +#define CV_HAL_CMP_GT 1 +#define CV_HAL_CMP_GE 2 +#define CV_HAL_CMP_LT 3 +#define CV_HAL_CMP_LE 4 +#define CV_HAL_CMP_NE 5 +//! @} + +//! @name Border processing modes +//! @sa cv::BorderTypes +//! @{ +#define CV_HAL_BORDER_CONSTANT 0 +#define CV_HAL_BORDER_REPLICATE 1 +#define CV_HAL_BORDER_REFLECT 2 +#define CV_HAL_BORDER_WRAP 3 +#define CV_HAL_BORDER_REFLECT_101 4 +#define CV_HAL_BORDER_TRANSPARENT 5 +#define CV_HAL_BORDER_ISOLATED 16 +//! @} + +//! @name DFT flags +//! @{ +#define CV_HAL_DFT_INVERSE 1 +#define CV_HAL_DFT_SCALE 2 +#define CV_HAL_DFT_ROWS 4 +#define CV_HAL_DFT_COMPLEX_OUTPUT 16 +#define CV_HAL_DFT_REAL_OUTPUT 32 +#define CV_HAL_DFT_TWO_STAGE 64 +#define CV_HAL_DFT_STAGE_COLS 128 +#define CV_HAL_DFT_IS_CONTINUOUS 512 +#define CV_HAL_DFT_IS_INPLACE 1024 +//! @} + +//! @name SVD flags +//! @{ +#define CV_HAL_SVD_NO_UV 1 +#define CV_HAL_SVD_SHORT_UV 2 +#define CV_HAL_SVD_MODIFY_A 4 +#define CV_HAL_SVD_FULL_UV 8 +//! @} + +//! @name Gemm flags +//! @{ +#define CV_HAL_GEMM_1_T 1 +#define CV_HAL_GEMM_2_T 2 +#define CV_HAL_GEMM_3_T 4 +//! @} + +//! @} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin.hpp new file mode 100644 index 00000000..460c5c59 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin.hpp @@ -0,0 +1,429 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_INTRIN_HPP +#define OPENCV_HAL_INTRIN_HPP + +#include +#include +#include +#include "opencv2/core/cvdef.h" + +#define OPENCV_HAL_ADD(a, b) ((a) + (b)) +#define OPENCV_HAL_AND(a, b) ((a) & (b)) +#define OPENCV_HAL_NOP(a) (a) +#define OPENCV_HAL_1ST(a, b) (a) + +// unlike HAL API, which is in cv::hal, +// we put intrinsics into cv namespace to make its +// access from within opencv code more accessible +namespace cv { + +namespace hal { + +enum StoreMode +{ + STORE_UNALIGNED = 0, + STORE_ALIGNED = 1, + STORE_ALIGNED_NOCACHE = 2 +}; + +} + +template struct V_TypeTraits +{ +}; + +#define CV_INTRIN_DEF_TYPE_TRAITS(type, int_type_, uint_type_, abs_type_, w_type_, q_type_, sum_type_, nlanes128_) \ + template<> struct V_TypeTraits \ + { \ + typedef type value_type; \ + typedef int_type_ int_type; \ + typedef abs_type_ abs_type; \ + typedef uint_type_ uint_type; \ + typedef w_type_ w_type; \ + typedef q_type_ q_type; \ + typedef sum_type_ sum_type; \ + enum { nlanes128 = nlanes128_ }; \ + \ + static inline int_type reinterpret_int(type x) \ + { \ + union { type l; int_type i; } v; \ + v.l = x; \ + return v.i; \ + } \ + \ + static inline type reinterpret_from_int(int_type x) \ + { \ + union { type l; int_type i; } v; \ + v.i = x; \ + return v.l; \ + } \ + } + +CV_INTRIN_DEF_TYPE_TRAITS(uchar, schar, uchar, uchar, ushort, unsigned, unsigned, 16); +CV_INTRIN_DEF_TYPE_TRAITS(schar, schar, uchar, uchar, short, int, int, 16); +CV_INTRIN_DEF_TYPE_TRAITS(ushort, short, ushort, ushort, unsigned, uint64, unsigned, 8); +CV_INTRIN_DEF_TYPE_TRAITS(short, short, ushort, ushort, int, int64, int, 8); +CV_INTRIN_DEF_TYPE_TRAITS(unsigned, int, unsigned, unsigned, uint64, void, unsigned, 4); +CV_INTRIN_DEF_TYPE_TRAITS(int, int, unsigned, unsigned, int64, void, int, 4); +CV_INTRIN_DEF_TYPE_TRAITS(float, int, unsigned, float, double, void, float, 4); +CV_INTRIN_DEF_TYPE_TRAITS(uint64, int64, uint64, uint64, void, void, uint64, 2); +CV_INTRIN_DEF_TYPE_TRAITS(int64, int64, uint64, uint64, void, void, int64, 2); +CV_INTRIN_DEF_TYPE_TRAITS(double, int64, uint64, double, void, void, double, 2); + +#ifndef CV_DOXYGEN + +#ifdef CV_CPU_DISPATCH_MODE + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE __CV_CAT(hal_, CV_CPU_DISPATCH_MODE) + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN namespace __CV_CAT(hal_, CV_CPU_DISPATCH_MODE) { + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END } +#else + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE hal_baseline + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN namespace hal_baseline { + #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END } +#endif + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END +using namespace CV_CPU_OPTIMIZATION_HAL_NAMESPACE; +#endif +} + +#ifdef CV_DOXYGEN +# undef CV_AVX2 +# undef CV_SSE2 +# undef CV_NEON +# undef CV_VSX +# undef CV_FP16 +#endif + +#if CV_SSE2 || CV_NEON || CV_VSX +#define CV__SIMD_FORWARD 128 +#include "opencv2/core/hal/intrin_forward.hpp" +#endif + +#if CV_SSE2 + +#include "opencv2/core/hal/intrin_sse_em.hpp" +#include "opencv2/core/hal/intrin_sse.hpp" + +#elif CV_NEON + +#include "opencv2/core/hal/intrin_neon.hpp" + +#elif CV_VSX + +#include "opencv2/core/hal/intrin_vsx.hpp" + +#else + +#define CV_SIMD128_CPP 1 +#include "opencv2/core/hal/intrin_cpp.hpp" + +#endif + +// AVX2 can be used together with SSE2, so +// we define those two sets of intrinsics at once. +// Most of the intrinsics do not conflict (the proper overloaded variant is +// resolved by the argument types, e.g. v_float32x4 ~ SSE2, v_float32x8 ~ AVX2), +// but some of AVX2 intrinsics get v256_ prefix instead of v_, e.g. v256_load() vs v_load(). +// Correspondingly, the wide intrinsics (which are mapped to the "widest" +// available instruction set) will get vx_ prefix +// (and will be mapped to v256_ counterparts) (e.g. vx_load() => v256_load()) +#if CV_AVX2 + +#define CV__SIMD_FORWARD 256 +#include "opencv2/core/hal/intrin_forward.hpp" +#include "opencv2/core/hal/intrin_avx.hpp" + +#endif + +//! @cond IGNORED + +namespace cv { + +#ifndef CV_DOXYGEN +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN +#endif + +#ifndef CV_SIMD128 +#define CV_SIMD128 0 +#endif + +#ifndef CV_SIMD128_64F +#define CV_SIMD128_64F 0 +#endif + +#ifndef CV_SIMD256 +#define CV_SIMD256 0 +#endif + +#ifndef CV_SIMD256_64F +#define CV_SIMD256_64F 0 +#endif + +#ifndef CV_SIMD512 +#define CV_SIMD512 0 +#endif + +#ifndef CV_SIMD512_64F +#define CV_SIMD512_64F 0 +#endif + +#ifndef CV_SIMD128_FP16 +#define CV_SIMD128_FP16 0 +#endif + +#ifndef CV_SIMD256_FP16 +#define CV_SIMD256_FP16 0 +#endif + +#ifndef CV_SIMD512_FP16 +#define CV_SIMD512_FP16 0 +#endif + +//================================================================================================== + +#define CV_INTRIN_DEFINE_WIDE_INTRIN(typ, vtyp, short_typ, prefix, loadsfx) \ + inline vtyp vx_setall_##short_typ(typ v) { return prefix##_setall_##short_typ(v); } \ + inline vtyp vx_setzero_##short_typ() { return prefix##_setzero_##short_typ(); } \ + inline vtyp vx_##loadsfx(const typ* ptr) { return prefix##_##loadsfx(ptr); } \ + inline vtyp vx_##loadsfx##_aligned(const typ* ptr) { return prefix##_##loadsfx##_aligned(ptr); } \ + inline vtyp vx_##loadsfx##_low(const typ* ptr) { return prefix##_##loadsfx##_low(ptr); } \ + inline vtyp vx_##loadsfx##_halves(const typ* ptr0, const typ* ptr1) { return prefix##_##loadsfx##_halves(ptr0, ptr1); } \ + inline void vx_store(typ* ptr, const vtyp& v) { return v_store(ptr, v); } \ + inline void vx_store_aligned(typ* ptr, const vtyp& v) { return v_store_aligned(ptr, v); } \ + inline vtyp vx_lut(const typ* ptr, const int* idx) { return prefix##_lut(ptr, idx); } \ + inline vtyp vx_lut_pairs(const typ* ptr, const int* idx) { return prefix##_lut_pairs(ptr, idx); } + +#define CV_INTRIN_DEFINE_WIDE_LUT_QUAD(typ, vtyp, prefix) \ + inline vtyp vx_lut_quads(const typ* ptr, const int* idx) { return prefix##_lut_quads(ptr, idx); } + +#define CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(typ, wtyp, prefix) \ + inline wtyp vx_load_expand(const typ* ptr) { return prefix##_load_expand(ptr); } + +#define CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND_Q(typ, qtyp, prefix) \ + inline qtyp vx_load_expand_q(const typ* ptr) { return prefix##_load_expand_q(ptr); } + +#define CV_INTRIN_DEFINE_WIDE_INTRIN_WITH_EXPAND(typ, vtyp, short_typ, wtyp, qtyp, prefix, loadsfx) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(typ, vtyp, short_typ, prefix, loadsfx) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(typ, vtyp, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(typ, wtyp, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND_Q(typ, qtyp, prefix) + +#define CV_INTRIN_DEFINE_WIDE_INTRIN_ALL_TYPES(prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN_WITH_EXPAND(uchar, v_uint8, u8, v_uint16, v_uint32, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_INTRIN_WITH_EXPAND(schar, v_int8, s8, v_int16, v_int32, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(ushort, v_uint16, u16, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(ushort, v_uint16, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(ushort, v_uint32, prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(short, v_int16, s16, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(short, v_int16, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(short, v_int32, prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(int, v_int32, s32, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(int, v_int32, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(int, v_int64, prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(unsigned, v_uint32, u32, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(unsigned, v_uint32, prefix) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(unsigned, v_uint64, prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(float, v_float32, f32, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LUT_QUAD(float, v_float32, prefix) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(int64, v_int64, s64, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_INTRIN(uint64, v_uint64, u64, prefix, load) \ + CV_INTRIN_DEFINE_WIDE_LOAD_EXPAND(float16_t, v_float32, prefix) + +template struct V_RegTraits +{ +}; + +#define CV_DEF_REG_TRAITS(prefix, _reg, lane_type, suffix, _u_reg, _w_reg, _q_reg, _int_reg, _round_reg) \ + template<> struct V_RegTraits<_reg> \ + { \ + typedef _reg reg; \ + typedef _u_reg u_reg; \ + typedef _w_reg w_reg; \ + typedef _q_reg q_reg; \ + typedef _int_reg int_reg; \ + typedef _round_reg round_reg; \ + } + +#if CV_SIMD128 || CV_SIMD128_CPP + CV_DEF_REG_TRAITS(v, v_uint8x16, uchar, u8, v_uint8x16, v_uint16x8, v_uint32x4, v_int8x16, void); + CV_DEF_REG_TRAITS(v, v_int8x16, schar, s8, v_uint8x16, v_int16x8, v_int32x4, v_int8x16, void); + CV_DEF_REG_TRAITS(v, v_uint16x8, ushort, u16, v_uint16x8, v_uint32x4, v_uint64x2, v_int16x8, void); + CV_DEF_REG_TRAITS(v, v_int16x8, short, s16, v_uint16x8, v_int32x4, v_int64x2, v_int16x8, void); + CV_DEF_REG_TRAITS(v, v_uint32x4, unsigned, u32, v_uint32x4, v_uint64x2, void, v_int32x4, void); + CV_DEF_REG_TRAITS(v, v_int32x4, int, s32, v_uint32x4, v_int64x2, void, v_int32x4, void); +#if CV_SIMD128_64F + CV_DEF_REG_TRAITS(v, v_float32x4, float, f32, v_float32x4, v_float64x2, void, v_int32x4, v_int32x4); +#else + CV_DEF_REG_TRAITS(v, v_float32x4, float, f32, v_float32x4, void, void, v_int32x4, v_int32x4); +#endif + CV_DEF_REG_TRAITS(v, v_uint64x2, uint64, u64, v_uint64x2, void, void, v_int64x2, void); + CV_DEF_REG_TRAITS(v, v_int64x2, int64, s64, v_uint64x2, void, void, v_int64x2, void); +#if CV_SIMD128_64F + CV_DEF_REG_TRAITS(v, v_float64x2, double, f64, v_float64x2, void, void, v_int64x2, v_int32x4); +#endif +#endif + +#if CV_SIMD256 + CV_DEF_REG_TRAITS(v256, v_uint8x32, uchar, u8, v_uint8x32, v_uint16x16, v_uint32x8, v_int8x32, void); + CV_DEF_REG_TRAITS(v256, v_int8x32, schar, s8, v_uint8x32, v_int16x16, v_int32x8, v_int8x32, void); + CV_DEF_REG_TRAITS(v256, v_uint16x16, ushort, u16, v_uint16x16, v_uint32x8, v_uint64x4, v_int16x16, void); + CV_DEF_REG_TRAITS(v256, v_int16x16, short, s16, v_uint16x16, v_int32x8, v_int64x4, v_int16x16, void); + CV_DEF_REG_TRAITS(v256, v_uint32x8, unsigned, u32, v_uint32x8, v_uint64x4, void, v_int32x8, void); + CV_DEF_REG_TRAITS(v256, v_int32x8, int, s32, v_uint32x8, v_int64x4, void, v_int32x8, void); + CV_DEF_REG_TRAITS(v256, v_float32x8, float, f32, v_float32x8, v_float64x4, void, v_int32x8, v_int32x8); + CV_DEF_REG_TRAITS(v256, v_uint64x4, uint64, u64, v_uint64x4, void, void, v_int64x4, void); + CV_DEF_REG_TRAITS(v256, v_int64x4, int64, s64, v_uint64x4, void, void, v_int64x4, void); + CV_DEF_REG_TRAITS(v256, v_float64x4, double, f64, v_float64x4, void, void, v_int64x4, v_int32x8); +#endif + +#if CV_SIMD512 && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 512) +#define CV__SIMD_NAMESPACE simd512 +namespace CV__SIMD_NAMESPACE { + #define CV_SIMD 1 + #define CV_SIMD_64F CV_SIMD512_64F + #define CV_SIMD_WIDTH 64 + // TODO typedef v_uint8 / v_int32 / etc types here +} // namespace +using namespace CV__SIMD_NAMESPACE; +#elif CV_SIMD256 && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 256) +#define CV__SIMD_NAMESPACE simd256 +namespace CV__SIMD_NAMESPACE { + #define CV_SIMD 1 + #define CV_SIMD_64F CV_SIMD256_64F + #define CV_SIMD_FP16 CV_SIMD256_FP16 + #define CV_SIMD_WIDTH 32 + typedef v_uint8x32 v_uint8; + typedef v_int8x32 v_int8; + typedef v_uint16x16 v_uint16; + typedef v_int16x16 v_int16; + typedef v_uint32x8 v_uint32; + typedef v_int32x8 v_int32; + typedef v_uint64x4 v_uint64; + typedef v_int64x4 v_int64; + typedef v_float32x8 v_float32; + CV_INTRIN_DEFINE_WIDE_INTRIN_ALL_TYPES(v256) + #if CV_SIMD256_64F + typedef v_float64x4 v_float64; + CV_INTRIN_DEFINE_WIDE_INTRIN(double, v_float64, f64, v256, load) + #endif + inline void vx_cleanup() { v256_cleanup(); } +} // namespace +using namespace CV__SIMD_NAMESPACE; +#elif (CV_SIMD128 || CV_SIMD128_CPP) && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 128) +#define CV__SIMD_NAMESPACE simd128 +namespace CV__SIMD_NAMESPACE { + #define CV_SIMD CV_SIMD128 + #define CV_SIMD_64F CV_SIMD128_64F + #define CV_SIMD_WIDTH 16 + typedef v_uint8x16 v_uint8; + typedef v_int8x16 v_int8; + typedef v_uint16x8 v_uint16; + typedef v_int16x8 v_int16; + typedef v_uint32x4 v_uint32; + typedef v_int32x4 v_int32; + typedef v_uint64x2 v_uint64; + typedef v_int64x2 v_int64; + typedef v_float32x4 v_float32; + CV_INTRIN_DEFINE_WIDE_INTRIN_ALL_TYPES(v) + #if CV_SIMD128_64F + typedef v_float64x2 v_float64; + CV_INTRIN_DEFINE_WIDE_INTRIN(double, v_float64, f64, v, load) + #endif + inline void vx_cleanup() { v_cleanup(); } +} // namespace +using namespace CV__SIMD_NAMESPACE; +#endif + +inline unsigned int trailingZeros32(unsigned int value) { +#if defined(_MSC_VER) +#if (_MSC_VER < 1700) || defined(_M_ARM) + unsigned long index = 0; + _BitScanForward(&index, value); + return (unsigned int)index; +#elif defined(__clang__) + // clang-cl doesn't export _tzcnt_u32 for non BMI systems + return value ? __builtin_ctz(value) : 32; +#else + return _tzcnt_u32(value); +#endif +#elif defined(__GNUC__) || defined(__GNUG__) + return __builtin_ctz(value); +#elif defined(__ICC) || defined(__INTEL_COMPILER) + return _bit_scan_forward(value); +#elif defined(__clang__) + return llvm.cttz.i32(value, true); +#else + static const int MultiplyDeBruijnBitPosition[32] = { + 0, 1, 28, 2, 29, 14, 24, 3, 30, 22, 20, 15, 25, 17, 4, 8, + 31, 27, 13, 23, 21, 19, 16, 7, 26, 12, 18, 6, 11, 5, 10, 9 }; + return MultiplyDeBruijnBitPosition[((uint32_t)((value & -value) * 0x077CB531U)) >> 27]; +#endif +} + +#ifndef CV_DOXYGEN +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END +#endif + +#ifndef CV_SIMD_64F +#define CV_SIMD_64F 0 +#endif + +#ifndef CV_SIMD_FP16 +#define CV_SIMD_FP16 0 //!< Defined to 1 on native support of operations with float16x8_t / float16x16_t (SIMD256) types +#endif + + +#ifndef CV_SIMD +#define CV_SIMD 0 +#endif + +} // cv:: + +//! @endcond + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_avx.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_avx.hpp new file mode 100644 index 00000000..58db7146 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_avx.hpp @@ -0,0 +1,2772 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +#ifndef OPENCV_HAL_INTRIN_AVX_HPP +#define OPENCV_HAL_INTRIN_AVX_HPP + +#define CV_SIMD256 1 +#define CV_SIMD256_64F 1 +#define CV_SIMD256_FP16 0 // no native operations with FP16 type. Only load/store from float32x8 are available (if CV_FP16 == 1) + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +///////// Utils //////////// + +inline __m256i _v256_combine(const __m128i& lo, const __m128i& hi) +{ return _mm256_inserti128_si256(_mm256_castsi128_si256(lo), hi, 1); } + +inline __m256 _v256_combine(const __m128& lo, const __m128& hi) +{ return _mm256_insertf128_ps(_mm256_castps128_ps256(lo), hi, 1); } + +inline __m256d _v256_combine(const __m128d& lo, const __m128d& hi) +{ return _mm256_insertf128_pd(_mm256_castpd128_pd256(lo), hi, 1); } + +inline int _v_cvtsi256_si32(const __m256i& a) +{ return _mm_cvtsi128_si32(_mm256_castsi256_si128(a)); } + +inline __m256i _v256_shuffle_odd_64(const __m256i& v) +{ return _mm256_permute4x64_epi64(v, _MM_SHUFFLE(3, 1, 2, 0)); } + +inline __m256d _v256_shuffle_odd_64(const __m256d& v) +{ return _mm256_permute4x64_pd(v, _MM_SHUFFLE(3, 1, 2, 0)); } + +template +inline __m256i _v256_permute2x128(const __m256i& a, const __m256i& b) +{ return _mm256_permute2x128_si256(a, b, imm); } + +template +inline __m256 _v256_permute2x128(const __m256& a, const __m256& b) +{ return _mm256_permute2f128_ps(a, b, imm); } + +template +inline __m256d _v256_permute2x128(const __m256d& a, const __m256d& b) +{ return _mm256_permute2f128_pd(a, b, imm); } + +template +inline _Tpvec v256_permute2x128(const _Tpvec& a, const _Tpvec& b) +{ return _Tpvec(_v256_permute2x128(a.val, b.val)); } + +template +inline __m256i _v256_permute4x64(const __m256i& a) +{ return _mm256_permute4x64_epi64(a, imm); } + +template +inline __m256d _v256_permute4x64(const __m256d& a) +{ return _mm256_permute4x64_pd(a, imm); } + +template +inline _Tpvec v256_permute4x64(const _Tpvec& a) +{ return _Tpvec(_v256_permute4x64(a.val)); } + +inline __m128i _v256_extract_high(const __m256i& v) +{ return _mm256_extracti128_si256(v, 1); } + +inline __m128 _v256_extract_high(const __m256& v) +{ return _mm256_extractf128_ps(v, 1); } + +inline __m128d _v256_extract_high(const __m256d& v) +{ return _mm256_extractf128_pd(v, 1); } + +inline __m128i _v256_extract_low(const __m256i& v) +{ return _mm256_castsi256_si128(v); } + +inline __m128 _v256_extract_low(const __m256& v) +{ return _mm256_castps256_ps128(v); } + +inline __m128d _v256_extract_low(const __m256d& v) +{ return _mm256_castpd256_pd128(v); } + +inline __m256i _v256_packs_epu32(const __m256i& a, const __m256i& b) +{ + const __m256i m = _mm256_set1_epi32(65535); + __m256i am = _mm256_min_epu32(a, m); + __m256i bm = _mm256_min_epu32(b, m); + return _mm256_packus_epi32(am, bm); +} + +///////// Types //////////// + +struct v_uint8x32 +{ + typedef uchar lane_type; + enum { nlanes = 32 }; + __m256i val; + + explicit v_uint8x32(__m256i v) : val(v) {} + v_uint8x32(uchar v0, uchar v1, uchar v2, uchar v3, + uchar v4, uchar v5, uchar v6, uchar v7, + uchar v8, uchar v9, uchar v10, uchar v11, + uchar v12, uchar v13, uchar v14, uchar v15, + uchar v16, uchar v17, uchar v18, uchar v19, + uchar v20, uchar v21, uchar v22, uchar v23, + uchar v24, uchar v25, uchar v26, uchar v27, + uchar v28, uchar v29, uchar v30, uchar v31) + { + val = _mm256_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3, + (char)v4, (char)v5, (char)v6 , (char)v7, (char)v8, (char)v9, + (char)v10, (char)v11, (char)v12, (char)v13, (char)v14, (char)v15, + (char)v16, (char)v17, (char)v18, (char)v19, (char)v20, (char)v21, + (char)v22, (char)v23, (char)v24, (char)v25, (char)v26, (char)v27, + (char)v28, (char)v29, (char)v30, (char)v31); + } + v_uint8x32() : val(_mm256_setzero_si256()) {} + uchar get0() const { return (uchar)_v_cvtsi256_si32(val); } +}; + +struct v_int8x32 +{ + typedef schar lane_type; + enum { nlanes = 32 }; + __m256i val; + + explicit v_int8x32(__m256i v) : val(v) {} + v_int8x32(schar v0, schar v1, schar v2, schar v3, + schar v4, schar v5, schar v6, schar v7, + schar v8, schar v9, schar v10, schar v11, + schar v12, schar v13, schar v14, schar v15, + schar v16, schar v17, schar v18, schar v19, + schar v20, schar v21, schar v22, schar v23, + schar v24, schar v25, schar v26, schar v27, + schar v28, schar v29, schar v30, schar v31) + { + val = _mm256_setr_epi8(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, + v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, + v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31); + } + v_int8x32() : val(_mm256_setzero_si256()) {} + schar get0() const { return (schar)_v_cvtsi256_si32(val); } +}; + +struct v_uint16x16 +{ + typedef ushort lane_type; + enum { nlanes = 16 }; + __m256i val; + + explicit v_uint16x16(__m256i v) : val(v) {} + v_uint16x16(ushort v0, ushort v1, ushort v2, ushort v3, + ushort v4, ushort v5, ushort v6, ushort v7, + ushort v8, ushort v9, ushort v10, ushort v11, + ushort v12, ushort v13, ushort v14, ushort v15) + { + val = _mm256_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3, + (short)v4, (short)v5, (short)v6, (short)v7, (short)v8, (short)v9, + (short)v10, (short)v11, (short)v12, (short)v13, (short)v14, (short)v15); + } + v_uint16x16() : val(_mm256_setzero_si256()) {} + ushort get0() const { return (ushort)_v_cvtsi256_si32(val); } +}; + +struct v_int16x16 +{ + typedef short lane_type; + enum { nlanes = 16 }; + __m256i val; + + explicit v_int16x16(__m256i v) : val(v) {} + v_int16x16(short v0, short v1, short v2, short v3, + short v4, short v5, short v6, short v7, + short v8, short v9, short v10, short v11, + short v12, short v13, short v14, short v15) + { + val = _mm256_setr_epi16(v0, v1, v2, v3, v4, v5, v6, v7, + v8, v9, v10, v11, v12, v13, v14, v15); + } + v_int16x16() : val(_mm256_setzero_si256()) {} + short get0() const { return (short)_v_cvtsi256_si32(val); } +}; + +struct v_uint32x8 +{ + typedef unsigned lane_type; + enum { nlanes = 8 }; + __m256i val; + + explicit v_uint32x8(__m256i v) : val(v) {} + v_uint32x8(unsigned v0, unsigned v1, unsigned v2, unsigned v3, + unsigned v4, unsigned v5, unsigned v6, unsigned v7) + { + val = _mm256_setr_epi32((unsigned)v0, (unsigned)v1, (unsigned)v2, + (unsigned)v3, (unsigned)v4, (unsigned)v5, (unsigned)v6, (unsigned)v7); + } + v_uint32x8() : val(_mm256_setzero_si256()) {} + unsigned get0() const { return (unsigned)_v_cvtsi256_si32(val); } +}; + +struct v_int32x8 +{ + typedef int lane_type; + enum { nlanes = 8 }; + __m256i val; + + explicit v_int32x8(__m256i v) : val(v) {} + v_int32x8(int v0, int v1, int v2, int v3, + int v4, int v5, int v6, int v7) + { + val = _mm256_setr_epi32(v0, v1, v2, v3, v4, v5, v6, v7); + } + v_int32x8() : val(_mm256_setzero_si256()) {} + int get0() const { return _v_cvtsi256_si32(val); } +}; + +struct v_float32x8 +{ + typedef float lane_type; + enum { nlanes = 8 }; + __m256 val; + + explicit v_float32x8(__m256 v) : val(v) {} + v_float32x8(float v0, float v1, float v2, float v3, + float v4, float v5, float v6, float v7) + { + val = _mm256_setr_ps(v0, v1, v2, v3, v4, v5, v6, v7); + } + v_float32x8() : val(_mm256_setzero_ps()) {} + float get0() const { return _mm_cvtss_f32(_mm256_castps256_ps128(val)); } +}; + +struct v_uint64x4 +{ + typedef uint64 lane_type; + enum { nlanes = 4 }; + __m256i val; + + explicit v_uint64x4(__m256i v) : val(v) {} + v_uint64x4(uint64 v0, uint64 v1, uint64 v2, uint64 v3) + { val = _mm256_setr_epi64x((int64)v0, (int64)v1, (int64)v2, (int64)v3); } + v_uint64x4() : val(_mm256_setzero_si256()) {} + uint64 get0() const + { + #if defined __x86_64__ || defined _M_X64 + return (uint64)_mm_cvtsi128_si64(_mm256_castsi256_si128(val)); + #else + int a = _mm_cvtsi128_si32(_mm256_castsi256_si128(val)); + int b = _mm_cvtsi128_si32(_mm256_castsi256_si128(_mm256_srli_epi64(val, 32))); + return (unsigned)a | ((uint64)(unsigned)b << 32); + #endif + } +}; + +struct v_int64x4 +{ + typedef int64 lane_type; + enum { nlanes = 4 }; + __m256i val; + + explicit v_int64x4(__m256i v) : val(v) {} + v_int64x4(int64 v0, int64 v1, int64 v2, int64 v3) + { val = _mm256_setr_epi64x(v0, v1, v2, v3); } + v_int64x4() : val(_mm256_setzero_si256()) {} + + int64 get0() const + { + #if defined __x86_64__ || defined _M_X64 + return (int64)_mm_cvtsi128_si64(_mm256_castsi256_si128(val)); + #else + int a = _mm_cvtsi128_si32(_mm256_castsi256_si128(val)); + int b = _mm_cvtsi128_si32(_mm256_castsi256_si128(_mm256_srli_epi64(val, 32))); + return (int64)((unsigned)a | ((uint64)(unsigned)b << 32)); + #endif + } +}; + +struct v_float64x4 +{ + typedef double lane_type; + enum { nlanes = 4 }; + __m256d val; + + explicit v_float64x4(__m256d v) : val(v) {} + v_float64x4(double v0, double v1, double v2, double v3) + { val = _mm256_setr_pd(v0, v1, v2, v3); } + v_float64x4() : val(_mm256_setzero_pd()) {} + double get0() const { return _mm_cvtsd_f64(_mm256_castpd256_pd128(val)); } +}; + +//////////////// Load and store operations /////////////// + +#define OPENCV_HAL_IMPL_AVX_LOADSTORE(_Tpvec, _Tp) \ + inline _Tpvec v256_load(const _Tp* ptr) \ + { return _Tpvec(_mm256_loadu_si256((const __m256i*)ptr)); } \ + inline _Tpvec v256_load_aligned(const _Tp* ptr) \ + { return _Tpvec(_mm256_load_si256((const __m256i*)ptr)); } \ + inline _Tpvec v256_load_low(const _Tp* ptr) \ + { \ + __m128i v128 = _mm_loadu_si128((const __m128i*)ptr); \ + return _Tpvec(_mm256_castsi128_si256(v128)); \ + } \ + inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ + { \ + __m128i vlo = _mm_loadu_si128((const __m128i*)ptr0); \ + __m128i vhi = _mm_loadu_si128((const __m128i*)ptr1); \ + return _Tpvec(_v256_combine(vlo, vhi)); \ + } \ + inline void v_store(_Tp* ptr, const _Tpvec& a) \ + { _mm256_storeu_si256((__m256i*)ptr, a.val); } \ + inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \ + { _mm256_store_si256((__m256i*)ptr, a.val); } \ + inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \ + { _mm256_stream_si256((__m256i*)ptr, a.val); } \ + inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \ + { \ + if( mode == hal::STORE_UNALIGNED ) \ + _mm256_storeu_si256((__m256i*)ptr, a.val); \ + else if( mode == hal::STORE_ALIGNED_NOCACHE ) \ + _mm256_stream_si256((__m256i*)ptr, a.val); \ + else \ + _mm256_store_si256((__m256i*)ptr, a.val); \ + } \ + inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ + { _mm_storeu_si128((__m128i*)ptr, _v256_extract_low(a.val)); } \ + inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ + { _mm_storeu_si128((__m128i*)ptr, _v256_extract_high(a.val)); } + +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint8x32, uchar) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int8x32, schar) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint16x16, ushort) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int16x16, short) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint32x8, unsigned) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int32x8, int) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint64x4, uint64) +OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int64x4, int64) + +#define OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(_Tpvec, _Tp, suffix, halfreg) \ + inline _Tpvec v256_load(const _Tp* ptr) \ + { return _Tpvec(_mm256_loadu_##suffix(ptr)); } \ + inline _Tpvec v256_load_aligned(const _Tp* ptr) \ + { return _Tpvec(_mm256_load_##suffix(ptr)); } \ + inline _Tpvec v256_load_low(const _Tp* ptr) \ + { \ + return _Tpvec(_mm256_cast##suffix##128_##suffix##256 \ + (_mm_loadu_##suffix(ptr))); \ + } \ + inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ + { \ + halfreg vlo = _mm_loadu_##suffix(ptr0); \ + halfreg vhi = _mm_loadu_##suffix(ptr1); \ + return _Tpvec(_v256_combine(vlo, vhi)); \ + } \ + inline void v_store(_Tp* ptr, const _Tpvec& a) \ + { _mm256_storeu_##suffix(ptr, a.val); } \ + inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \ + { _mm256_store_##suffix(ptr, a.val); } \ + inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \ + { _mm256_stream_##suffix(ptr, a.val); } \ + inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \ + { \ + if( mode == hal::STORE_UNALIGNED ) \ + _mm256_storeu_##suffix(ptr, a.val); \ + else if( mode == hal::STORE_ALIGNED_NOCACHE ) \ + _mm256_stream_##suffix(ptr, a.val); \ + else \ + _mm256_store_##suffix(ptr, a.val); \ + } \ + inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ + { _mm_storeu_##suffix(ptr, _v256_extract_low(a.val)); } \ + inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ + { _mm_storeu_##suffix(ptr, _v256_extract_high(a.val)); } + +OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(v_float32x8, float, ps, __m128) +OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(v_float64x4, double, pd, __m128d) + +#define OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, _Tpvecf, suffix, cast) \ + inline _Tpvec v_reinterpret_as_##suffix(const _Tpvecf& a) \ + { return _Tpvec(cast(a.val)); } + +#define OPENCV_HAL_IMPL_AVX_INIT(_Tpvec, _Tp, suffix, ssuffix, ctype_s) \ + inline _Tpvec v256_setzero_##suffix() \ + { return _Tpvec(_mm256_setzero_si256()); } \ + inline _Tpvec v256_setall_##suffix(_Tp v) \ + { return _Tpvec(_mm256_set1_##ssuffix((ctype_s)v)); } \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint8x32, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int8x32, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint16x16, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int16x16, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint32x8, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int32x8, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint64x4, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int64x4, suffix, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_float32x8, suffix, _mm256_castps_si256) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_float64x4, suffix, _mm256_castpd_si256) + +OPENCV_HAL_IMPL_AVX_INIT(v_uint8x32, uchar, u8, epi8, char) +OPENCV_HAL_IMPL_AVX_INIT(v_int8x32, schar, s8, epi8, char) +OPENCV_HAL_IMPL_AVX_INIT(v_uint16x16, ushort, u16, epi16, short) +OPENCV_HAL_IMPL_AVX_INIT(v_int16x16, short, s16, epi16, short) +OPENCV_HAL_IMPL_AVX_INIT(v_uint32x8, unsigned, u32, epi32, int) +OPENCV_HAL_IMPL_AVX_INIT(v_int32x8, int, s32, epi32, int) +OPENCV_HAL_IMPL_AVX_INIT(v_uint64x4, uint64, u64, epi64x, int64) +OPENCV_HAL_IMPL_AVX_INIT(v_int64x4, int64, s64, epi64x, int64) + +#define OPENCV_HAL_IMPL_AVX_INIT_FLT(_Tpvec, _Tp, suffix, zsuffix, cast) \ + inline _Tpvec v256_setzero_##suffix() \ + { return _Tpvec(_mm256_setzero_##zsuffix()); } \ + inline _Tpvec v256_setall_##suffix(_Tp v) \ + { return _Tpvec(_mm256_set1_##zsuffix(v)); } \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint8x32, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int8x32, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint16x16, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int16x16, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint32x8, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int32x8, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint64x4, suffix, cast) \ + OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int64x4, suffix, cast) + +OPENCV_HAL_IMPL_AVX_INIT_FLT(v_float32x8, float, f32, ps, _mm256_castsi256_ps) +OPENCV_HAL_IMPL_AVX_INIT_FLT(v_float64x4, double, f64, pd, _mm256_castsi256_pd) + +inline v_float32x8 v_reinterpret_as_f32(const v_float32x8& a) +{ return a; } +inline v_float32x8 v_reinterpret_as_f32(const v_float64x4& a) +{ return v_float32x8(_mm256_castpd_ps(a.val)); } + +inline v_float64x4 v_reinterpret_as_f64(const v_float64x4& a) +{ return a; } +inline v_float64x4 v_reinterpret_as_f64(const v_float32x8& a) +{ return v_float64x4(_mm256_castps_pd(a.val)); } + +#if CV_FP16 +inline v_float32x8 v256_load_fp16_f32(const short* ptr) +{ + return v_float32x8(_mm256_cvtph_ps(_mm_loadu_si128((const __m128i*)ptr))); +} + +inline void v_store_fp16(short* ptr, const v_float32x8& a) +{ + __m128i fp16_value = _mm256_cvtps_ph(a.val, 0); + _mm_store_si128((__m128i*)ptr, fp16_value); +} +#endif + +/* Recombine */ +/*#define OPENCV_HAL_IMPL_AVX_COMBINE(_Tpvec, perm) \ + inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(perm(a.val, b.val, 0x20)); } \ + inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(perm(a.val, b.val, 0x31)); } \ + inline void v_recombine(const _Tpvec& a, const _Tpvec& b, \ + _Tpvec& c, _Tpvec& d) \ + { c = v_combine_low(a, b); d = v_combine_high(a, b); } + +#define OPENCV_HAL_IMPL_AVX_UNPACKS(_Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_COMBINE(_Tpvec, _mm256_permute2x128_si256) \ + inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, \ + _Tpvec& b0, _Tpvec& b1) \ + { \ + __m256i v0 = _v256_shuffle_odd_64(a0.val); \ + __m256i v1 = _v256_shuffle_odd_64(a1.val); \ + b0.val = _mm256_unpacklo_##suffix(v0, v1); \ + b1.val = _mm256_unpackhi_##suffix(v0, v1); \ + } + +OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint8x32, epi8) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_int8x32, epi8) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint16x16, epi16) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_int16x16, epi16) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint32x8, epi32) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_int32x8, epi32) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint64x4, epi64) +OPENCV_HAL_IMPL_AVX_UNPACKS(v_int64x4, epi64) +OPENCV_HAL_IMPL_AVX_COMBINE(v_float32x8, _mm256_permute2f128_ps) +OPENCV_HAL_IMPL_AVX_COMBINE(v_float64x4, _mm256_permute2f128_pd) + +inline void v_zip(const v_float32x8& a0, const v_float32x8& a1, v_float32x8& b0, v_float32x8& b1) +{ + __m256 v0 = _mm256_unpacklo_ps(a0.val, a1.val); + __m256 v1 = _mm256_unpackhi_ps(a0.val, a1.val); + v_recombine(v_float32x8(v0), v_float32x8(v1), b0, b1); +} + +inline void v_zip(const v_float64x4& a0, const v_float64x4& a1, v_float64x4& b0, v_float64x4& b1) +{ + __m256d v0 = _v_shuffle_odd_64(a0.val); + __m256d v1 = _v_shuffle_odd_64(a1.val); + b0.val = _mm256_unpacklo_pd(v0, v1); + b1.val = _mm256_unpackhi_pd(v0, v1); +}*/ + +//////////////// Variant Value reordering /////////////// + +// unpacks +#define OPENCV_HAL_IMPL_AVX_UNPACK(_Tpvec, suffix) \ + inline _Tpvec v256_unpacklo(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_unpacklo_##suffix(a.val, b.val)); } \ + inline _Tpvec v256_unpackhi(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_unpackhi_##suffix(a.val, b.val)); } + +OPENCV_HAL_IMPL_AVX_UNPACK(v_uint8x32, epi8) +OPENCV_HAL_IMPL_AVX_UNPACK(v_int8x32, epi8) +OPENCV_HAL_IMPL_AVX_UNPACK(v_uint16x16, epi16) +OPENCV_HAL_IMPL_AVX_UNPACK(v_int16x16, epi16) +OPENCV_HAL_IMPL_AVX_UNPACK(v_uint32x8, epi32) +OPENCV_HAL_IMPL_AVX_UNPACK(v_int32x8, epi32) +OPENCV_HAL_IMPL_AVX_UNPACK(v_uint64x4, epi64) +OPENCV_HAL_IMPL_AVX_UNPACK(v_int64x4, epi64) +OPENCV_HAL_IMPL_AVX_UNPACK(v_float32x8, ps) +OPENCV_HAL_IMPL_AVX_UNPACK(v_float64x4, pd) + +// blend +#define OPENCV_HAL_IMPL_AVX_BLEND(_Tpvec, suffix) \ + template \ + inline _Tpvec v256_blend(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_blend_##suffix(a.val, b.val, m)); } + +OPENCV_HAL_IMPL_AVX_BLEND(v_uint16x16, epi16) +OPENCV_HAL_IMPL_AVX_BLEND(v_int16x16, epi16) +OPENCV_HAL_IMPL_AVX_BLEND(v_uint32x8, epi32) +OPENCV_HAL_IMPL_AVX_BLEND(v_int32x8, epi32) +OPENCV_HAL_IMPL_AVX_BLEND(v_float32x8, ps) +OPENCV_HAL_IMPL_AVX_BLEND(v_float64x4, pd) + +template +inline v_uint64x4 v256_blend(const v_uint64x4& a, const v_uint64x4& b) +{ + enum {M0 = m}; + enum {M1 = (M0 | (M0 << 2)) & 0x33}; + enum {M2 = (M1 | (M1 << 1)) & 0x55}; + enum {MM = M2 | (M2 << 1)}; + return v_uint64x4(_mm256_blend_epi32(a.val, b.val, MM)); +} +template +inline v_int64x4 v256_blend(const v_int64x4& a, const v_int64x4& b) +{ return v_int64x4(v256_blend(v_uint64x4(a.val), v_uint64x4(b.val)).val); } + +// shuffle +// todo: emluate 64bit +#define OPENCV_HAL_IMPL_AVX_SHUFFLE(_Tpvec, intrin) \ + template \ + inline _Tpvec v256_shuffle(const _Tpvec& a) \ + { return _Tpvec(_mm256_##intrin(a.val, m)); } + +OPENCV_HAL_IMPL_AVX_SHUFFLE(v_uint32x8, shuffle_epi32) +OPENCV_HAL_IMPL_AVX_SHUFFLE(v_int32x8, shuffle_epi32) +OPENCV_HAL_IMPL_AVX_SHUFFLE(v_float32x8, permute_ps) +OPENCV_HAL_IMPL_AVX_SHUFFLE(v_float64x4, permute_pd) + +template +inline void v256_zip(const _Tpvec& a, const _Tpvec& b, _Tpvec& ab0, _Tpvec& ab1) +{ + ab0 = v256_unpacklo(a, b); + ab1 = v256_unpackhi(a, b); +} + +template +inline _Tpvec v256_combine_diagonal(const _Tpvec& a, const _Tpvec& b) +{ return _Tpvec(_mm256_blend_epi32(a.val, b.val, 0xf0)); } + +inline v_float32x8 v256_combine_diagonal(const v_float32x8& a, const v_float32x8& b) +{ return v256_blend<0xf0>(a, b); } + +inline v_float64x4 v256_combine_diagonal(const v_float64x4& a, const v_float64x4& b) +{ return v256_blend<0xc>(a, b); } + +template +inline _Tpvec v256_alignr_128(const _Tpvec& a, const _Tpvec& b) +{ return v256_permute2x128<0x21>(a, b); } + +template +inline _Tpvec v256_alignr_64(const _Tpvec& a, const _Tpvec& b) +{ return _Tpvec(_mm256_alignr_epi8(a.val, b.val, 8)); } +inline v_float64x4 v256_alignr_64(const v_float64x4& a, const v_float64x4& b) +{ return v_float64x4(_mm256_shuffle_pd(b.val, a.val, _MM_SHUFFLE(0, 0, 1, 1))); } +// todo: emulate float32 + +template +inline _Tpvec v256_swap_halves(const _Tpvec& a) +{ return v256_permute2x128<1>(a, a); } + +template +inline _Tpvec v256_reverse_64(const _Tpvec& a) +{ return v256_permute4x64<_MM_SHUFFLE(0, 1, 2, 3)>(a); } + +// ZIP +#define OPENCV_HAL_IMPL_AVX_ZIP(_Tpvec) \ + inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \ + { return v256_permute2x128<0x20>(a, b); } \ + inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \ + { return v256_permute2x128<0x31>(a, b); } \ + inline void v_recombine(const _Tpvec& a, const _Tpvec& b, \ + _Tpvec& c, _Tpvec& d) \ + { \ + _Tpvec a1b0 = v256_alignr_128(a, b); \ + c = v256_combine_diagonal(a, a1b0); \ + d = v256_combine_diagonal(a1b0, b); \ + } \ + inline void v_zip(const _Tpvec& a, const _Tpvec& b, \ + _Tpvec& ab0, _Tpvec& ab1) \ + { \ + _Tpvec ab0ab2, ab1ab3; \ + v256_zip(a, b, ab0ab2, ab1ab3); \ + v_recombine(ab0ab2, ab1ab3, ab0, ab1); \ + } + +OPENCV_HAL_IMPL_AVX_ZIP(v_uint8x32) +OPENCV_HAL_IMPL_AVX_ZIP(v_int8x32) +OPENCV_HAL_IMPL_AVX_ZIP(v_uint16x16) +OPENCV_HAL_IMPL_AVX_ZIP(v_int16x16) +OPENCV_HAL_IMPL_AVX_ZIP(v_uint32x8) +OPENCV_HAL_IMPL_AVX_ZIP(v_int32x8) +OPENCV_HAL_IMPL_AVX_ZIP(v_uint64x4) +OPENCV_HAL_IMPL_AVX_ZIP(v_int64x4) +OPENCV_HAL_IMPL_AVX_ZIP(v_float32x8) +OPENCV_HAL_IMPL_AVX_ZIP(v_float64x4) + +////////// Arithmetic, bitwise and comparison operations ///////// + +/* Element-wise binary and unary operations */ + +/** Arithmetics **/ +#define OPENCV_HAL_IMPL_AVX_BIN_OP(bin_op, _Tpvec, intrin) \ + inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(intrin(a.val, b.val)); } \ + inline _Tpvec& operator bin_op##= (_Tpvec& a, const _Tpvec& b) \ + { a.val = intrin(a.val, b.val); return a; } + +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_uint8x32, _mm256_adds_epu8) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_uint8x32, _mm256_subs_epu8) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_int8x32, _mm256_adds_epi8) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_int8x32, _mm256_subs_epi8) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_uint16x16, _mm256_adds_epu16) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_uint16x16, _mm256_subs_epu16) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_int16x16, _mm256_adds_epi16) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_int16x16, _mm256_subs_epi16) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_uint32x8, _mm256_add_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_uint32x8, _mm256_sub_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(*, v_uint32x8, _mm256_mullo_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_int32x8, _mm256_add_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_int32x8, _mm256_sub_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(*, v_int32x8, _mm256_mullo_epi32) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_uint64x4, _mm256_add_epi64) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_uint64x4, _mm256_sub_epi64) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_int64x4, _mm256_add_epi64) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_int64x4, _mm256_sub_epi64) + +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_float32x8, _mm256_add_ps) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_float32x8, _mm256_sub_ps) +OPENCV_HAL_IMPL_AVX_BIN_OP(*, v_float32x8, _mm256_mul_ps) +OPENCV_HAL_IMPL_AVX_BIN_OP(/, v_float32x8, _mm256_div_ps) +OPENCV_HAL_IMPL_AVX_BIN_OP(+, v_float64x4, _mm256_add_pd) +OPENCV_HAL_IMPL_AVX_BIN_OP(-, v_float64x4, _mm256_sub_pd) +OPENCV_HAL_IMPL_AVX_BIN_OP(*, v_float64x4, _mm256_mul_pd) +OPENCV_HAL_IMPL_AVX_BIN_OP(/, v_float64x4, _mm256_div_pd) + +// saturating multiply 8-bit, 16-bit +inline v_uint8x32 operator * (const v_uint8x32& a, const v_uint8x32& b) +{ + v_uint16x16 c, d; + v_mul_expand(a, b, c, d); + return v_pack(c, d); +} +inline v_int8x32 operator * (const v_int8x32& a, const v_int8x32& b) +{ + v_int16x16 c, d; + v_mul_expand(a, b, c, d); + return v_pack(c, d); +} +inline v_uint16x16 operator * (const v_uint16x16& a, const v_uint16x16& b) +{ + __m256i pl = _mm256_mullo_epi16(a.val, b.val); + __m256i ph = _mm256_mulhi_epu16(a.val, b.val); + __m256i p0 = _mm256_unpacklo_epi16(pl, ph); + __m256i p1 = _mm256_unpackhi_epi16(pl, ph); + return v_uint16x16(_v256_packs_epu32(p0, p1)); +} +inline v_int16x16 operator * (const v_int16x16& a, const v_int16x16& b) +{ + __m256i pl = _mm256_mullo_epi16(a.val, b.val); + __m256i ph = _mm256_mulhi_epi16(a.val, b.val); + __m256i p0 = _mm256_unpacklo_epi16(pl, ph); + __m256i p1 = _mm256_unpackhi_epi16(pl, ph); + return v_int16x16(_mm256_packs_epi32(p0, p1)); +} +inline v_uint8x32& operator *= (v_uint8x32& a, const v_uint8x32& b) +{ a = a * b; return a; } +inline v_int8x32& operator *= (v_int8x32& a, const v_int8x32& b) +{ a = a * b; return a; } +inline v_uint16x16& operator *= (v_uint16x16& a, const v_uint16x16& b) +{ a = a * b; return a; } +inline v_int16x16& operator *= (v_int16x16& a, const v_int16x16& b) +{ a = a * b; return a; } + +/** Non-saturating arithmetics **/ +#define OPENCV_HAL_IMPL_AVX_BIN_FUNC(func, _Tpvec, intrin) \ + inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(intrin(a.val, b.val)); } + +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_uint8x32, _mm256_add_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_int8x32, _mm256_add_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_uint16x16, _mm256_add_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_int16x16, _mm256_add_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_uint8x32, _mm256_sub_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_int8x32, _mm256_sub_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_uint16x16, _mm256_sub_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_int16x16, _mm256_sub_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_mul_wrap, v_uint16x16, _mm256_mullo_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_mul_wrap, v_int16x16, _mm256_mullo_epi16) + +inline v_uint8x32 v_mul_wrap(const v_uint8x32& a, const v_uint8x32& b) +{ + __m256i ad = _mm256_srai_epi16(a.val, 8); + __m256i bd = _mm256_srai_epi16(b.val, 8); + __m256i p0 = _mm256_mullo_epi16(a.val, b.val); // even + __m256i p1 = _mm256_slli_epi16(_mm256_mullo_epi16(ad, bd), 8); // odd + + const __m256i b01 = _mm256_set1_epi32(0xFF00FF00); + return v_uint8x32(_mm256_blendv_epi8(p0, p1, b01)); +} +inline v_int8x32 v_mul_wrap(const v_int8x32& a, const v_int8x32& b) +{ + return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b))); +} + +// Multiply and expand +inline void v_mul_expand(const v_uint8x32& a, const v_uint8x32& b, + v_uint16x16& c, v_uint16x16& d) +{ + v_uint16x16 a0, a1, b0, b1; + v_expand(a, a0, a1); + v_expand(b, b0, b1); + c = v_mul_wrap(a0, b0); + d = v_mul_wrap(a1, b1); +} + +inline void v_mul_expand(const v_int8x32& a, const v_int8x32& b, + v_int16x16& c, v_int16x16& d) +{ + v_int16x16 a0, a1, b0, b1; + v_expand(a, a0, a1); + v_expand(b, b0, b1); + c = v_mul_wrap(a0, b0); + d = v_mul_wrap(a1, b1); +} + +inline void v_mul_expand(const v_int16x16& a, const v_int16x16& b, + v_int32x8& c, v_int32x8& d) +{ + v_int16x16 vhi = v_int16x16(_mm256_mulhi_epi16(a.val, b.val)); + + v_int16x16 v0, v1; + v_zip(v_mul_wrap(a, b), vhi, v0, v1); + + c = v_reinterpret_as_s32(v0); + d = v_reinterpret_as_s32(v1); +} + +inline void v_mul_expand(const v_uint16x16& a, const v_uint16x16& b, + v_uint32x8& c, v_uint32x8& d) +{ + v_uint16x16 vhi = v_uint16x16(_mm256_mulhi_epu16(a.val, b.val)); + + v_uint16x16 v0, v1; + v_zip(v_mul_wrap(a, b), vhi, v0, v1); + + c = v_reinterpret_as_u32(v0); + d = v_reinterpret_as_u32(v1); +} + +inline void v_mul_expand(const v_uint32x8& a, const v_uint32x8& b, + v_uint64x4& c, v_uint64x4& d) +{ + __m256i v0 = _mm256_mul_epu32(a.val, b.val); + __m256i v1 = _mm256_mul_epu32(_mm256_srli_epi64(a.val, 32), _mm256_srli_epi64(b.val, 32)); + v_zip(v_uint64x4(v0), v_uint64x4(v1), c, d); +} + +inline v_int16x16 v_mul_hi(const v_int16x16& a, const v_int16x16& b) { return v_int16x16(_mm256_mulhi_epi16(a.val, b.val)); } +inline v_uint16x16 v_mul_hi(const v_uint16x16& a, const v_uint16x16& b) { return v_uint16x16(_mm256_mulhi_epu16(a.val, b.val)); } + +/** Bitwise shifts **/ +#define OPENCV_HAL_IMPL_AVX_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai) \ + inline _Tpuvec operator << (const _Tpuvec& a, int imm) \ + { return _Tpuvec(_mm256_slli_##suffix(a.val, imm)); } \ + inline _Tpsvec operator << (const _Tpsvec& a, int imm) \ + { return _Tpsvec(_mm256_slli_##suffix(a.val, imm)); } \ + inline _Tpuvec operator >> (const _Tpuvec& a, int imm) \ + { return _Tpuvec(_mm256_srli_##suffix(a.val, imm)); } \ + inline _Tpsvec operator >> (const _Tpsvec& a, int imm) \ + { return _Tpsvec(srai(a.val, imm)); } \ + template \ + inline _Tpuvec v_shl(const _Tpuvec& a) \ + { return _Tpuvec(_mm256_slli_##suffix(a.val, imm)); } \ + template \ + inline _Tpsvec v_shl(const _Tpsvec& a) \ + { return _Tpsvec(_mm256_slli_##suffix(a.val, imm)); } \ + template \ + inline _Tpuvec v_shr(const _Tpuvec& a) \ + { return _Tpuvec(_mm256_srli_##suffix(a.val, imm)); } \ + template \ + inline _Tpsvec v_shr(const _Tpsvec& a) \ + { return _Tpsvec(srai(a.val, imm)); } + +OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint16x16, v_int16x16, epi16, _mm256_srai_epi16) +OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint32x8, v_int32x8, epi32, _mm256_srai_epi32) + +inline __m256i _mm256_srai_epi64xx(const __m256i a, int imm) +{ + __m256i d = _mm256_set1_epi64x((int64)1 << 63); + __m256i r = _mm256_srli_epi64(_mm256_add_epi64(a, d), imm); + return _mm256_sub_epi64(r, _mm256_srli_epi64(d, imm)); +} +OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint64x4, v_int64x4, epi64, _mm256_srai_epi64xx) + + +/** Bitwise logic **/ +#define OPENCV_HAL_IMPL_AVX_LOGIC_OP(_Tpvec, suffix, not_const) \ + OPENCV_HAL_IMPL_AVX_BIN_OP(&, _Tpvec, _mm256_and_##suffix) \ + OPENCV_HAL_IMPL_AVX_BIN_OP(|, _Tpvec, _mm256_or_##suffix) \ + OPENCV_HAL_IMPL_AVX_BIN_OP(^, _Tpvec, _mm256_xor_##suffix) \ + inline _Tpvec operator ~ (const _Tpvec& a) \ + { return _Tpvec(_mm256_xor_##suffix(a.val, not_const)); } + +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint8x32, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int8x32, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint16x16, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int16x16, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint32x8, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int32x8, si256, _mm256_set1_epi32(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint64x4, si256, _mm256_set1_epi64x(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int64x4, si256, _mm256_set1_epi64x(-1)) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_float32x8, ps, _mm256_castsi256_ps(_mm256_set1_epi32(-1))) +OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_float64x4, pd, _mm256_castsi256_pd(_mm256_set1_epi32(-1))) + +/** Select **/ +#define OPENCV_HAL_IMPL_AVX_SELECT(_Tpvec, suffix) \ + inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_blendv_##suffix(b.val, a.val, mask.val)); } + +OPENCV_HAL_IMPL_AVX_SELECT(v_uint8x32, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_int8x32, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_uint16x16, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_int16x16, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_uint32x8, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_int32x8, epi8) +OPENCV_HAL_IMPL_AVX_SELECT(v_float32x8, ps) +OPENCV_HAL_IMPL_AVX_SELECT(v_float64x4, pd) + +/** Comparison **/ +#define OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpvec) \ + inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ + { return ~(a == b); } \ + inline _Tpvec operator < (const _Tpvec& a, const _Tpvec& b) \ + { return b > a; } \ + inline _Tpvec operator >= (const _Tpvec& a, const _Tpvec& b) \ + { return ~(a < b); } \ + inline _Tpvec operator <= (const _Tpvec& a, const _Tpvec& b) \ + { return b >= a; } + +#define OPENCV_HAL_IMPL_AVX_CMP_OP_INT(_Tpuvec, _Tpsvec, suffix, sbit) \ + inline _Tpuvec operator == (const _Tpuvec& a, const _Tpuvec& b) \ + { return _Tpuvec(_mm256_cmpeq_##suffix(a.val, b.val)); } \ + inline _Tpuvec operator > (const _Tpuvec& a, const _Tpuvec& b) \ + { \ + __m256i smask = _mm256_set1_##suffix(sbit); \ + return _Tpuvec(_mm256_cmpgt_##suffix( \ + _mm256_xor_si256(a.val, smask), \ + _mm256_xor_si256(b.val, smask))); \ + } \ + inline _Tpsvec operator == (const _Tpsvec& a, const _Tpsvec& b) \ + { return _Tpsvec(_mm256_cmpeq_##suffix(a.val, b.val)); } \ + inline _Tpsvec operator > (const _Tpsvec& a, const _Tpsvec& b) \ + { return _Tpsvec(_mm256_cmpgt_##suffix(a.val, b.val)); } \ + OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpuvec) \ + OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpsvec) + +OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint8x32, v_int8x32, epi8, (char)-128) +OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint16x16, v_int16x16, epi16, (short)-32768) +OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint32x8, v_int32x8, epi32, (int)0x80000000) + +#define OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(_Tpvec) \ + inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_cmpeq_epi64(a.val, b.val)); } \ + inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ + { return ~(a == b); } + +OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_uint64x4) +OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_int64x4) + +#define OPENCV_HAL_IMPL_AVX_CMP_FLT(bin_op, imm8, _Tpvec, suffix) \ + inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \ + { return _Tpvec(_mm256_cmp_##suffix(a.val, b.val, imm8)); } + +#define OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(_Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(==, _CMP_EQ_OQ, _Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(!=, _CMP_NEQ_OQ, _Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(<, _CMP_LT_OQ, _Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(>, _CMP_GT_OQ, _Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(<=, _CMP_LE_OQ, _Tpvec, suffix) \ + OPENCV_HAL_IMPL_AVX_CMP_FLT(>=, _CMP_GE_OQ, _Tpvec, suffix) + +OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float32x8, ps) +OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float64x4, pd) + +inline v_float32x8 v_not_nan(const v_float32x8& a) +{ return v_float32x8(_mm256_cmp_ps(a.val, a.val, _CMP_ORD_Q)); } +inline v_float64x4 v_not_nan(const v_float64x4& a) +{ return v_float64x4(_mm256_cmp_pd(a.val, a.val, _CMP_ORD_Q)); } + +/** min/max **/ +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint8x32, _mm256_min_epu8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint8x32, _mm256_max_epu8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int8x32, _mm256_min_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int8x32, _mm256_max_epi8) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint16x16, _mm256_min_epu16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint16x16, _mm256_max_epu16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int16x16, _mm256_min_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int16x16, _mm256_max_epi16) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint32x8, _mm256_min_epu32) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint32x8, _mm256_max_epu32) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int32x8, _mm256_min_epi32) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int32x8, _mm256_max_epi32) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_float32x8, _mm256_min_ps) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_float32x8, _mm256_max_ps) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_float64x4, _mm256_min_pd) +OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_float64x4, _mm256_max_pd) + +/** Rotate **/ +template +inline v_uint8x32 v_rotate_left(const v_uint8x32& a, const v_uint8x32& b) +{ + enum {IMM_R = (16 - imm) & 0xFF}; + enum {IMM_R2 = (32 - imm) & 0xFF}; + + if (imm == 0) return a; + if (imm == 32) return b; + if (imm > 32) return v_uint8x32(); + + __m256i swap = _mm256_permute2x128_si256(a.val, b.val, 0x03); + if (imm == 16) return v_uint8x32(swap); + if (imm < 16) return v_uint8x32(_mm256_alignr_epi8(a.val, swap, IMM_R)); + return v_uint8x32(_mm256_alignr_epi8(swap, b.val, IMM_R2)); // imm < 32 +} + +template +inline v_uint8x32 v_rotate_right(const v_uint8x32& a, const v_uint8x32& b) +{ + enum {IMM_L = (imm - 16) & 0xFF}; + + if (imm == 0) return a; + if (imm == 32) return b; + if (imm > 32) return v_uint8x32(); + + __m256i swap = _mm256_permute2x128_si256(a.val, b.val, 0x21); + if (imm == 16) return v_uint8x32(swap); + if (imm < 16) return v_uint8x32(_mm256_alignr_epi8(swap, a.val, imm)); + return v_uint8x32(_mm256_alignr_epi8(b.val, swap, IMM_L)); +} + +template +inline v_uint8x32 v_rotate_left(const v_uint8x32& a) +{ + enum {IMM_L = (imm - 16) & 0xFF}; + enum {IMM_R = (16 - imm) & 0xFF}; + + if (imm == 0) return a; + if (imm > 32) return v_uint8x32(); + + // ESAC control[3] ? [127:0] = 0 + __m256i swapz = _mm256_permute2x128_si256(a.val, a.val, _MM_SHUFFLE(0, 0, 2, 0)); + if (imm == 16) return v_uint8x32(swapz); + if (imm < 16) return v_uint8x32(_mm256_alignr_epi8(a.val, swapz, IMM_R)); + return v_uint8x32(_mm256_slli_si256(swapz, IMM_L)); +} + +template +inline v_uint8x32 v_rotate_right(const v_uint8x32& a) +{ + enum {IMM_L = (imm - 16) & 0xFF}; + + if (imm == 0) return a; + if (imm > 32) return v_uint8x32(); + + // ESAC control[3] ? [127:0] = 0 + __m256i swapz = _mm256_permute2x128_si256(a.val, a.val, _MM_SHUFFLE(2, 0, 0, 1)); + if (imm == 16) return v_uint8x32(swapz); + if (imm < 16) return v_uint8x32(_mm256_alignr_epi8(swapz, a.val, imm)); + return v_uint8x32(_mm256_srli_si256(swapz, IMM_L)); +} + +#define OPENCV_HAL_IMPL_AVX_ROTATE_CAST(intrin, _Tpvec, cast) \ + template \ + inline _Tpvec intrin(const _Tpvec& a, const _Tpvec& b) \ + { \ + enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)}; \ + v_uint8x32 ret = intrin(v_reinterpret_as_u8(a), \ + v_reinterpret_as_u8(b)); \ + return _Tpvec(cast(ret.val)); \ + } \ + template \ + inline _Tpvec intrin(const _Tpvec& a) \ + { \ + enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)}; \ + v_uint8x32 ret = intrin(v_reinterpret_as_u8(a)); \ + return _Tpvec(cast(ret.val)); \ + } + +#define OPENCV_HAL_IMPL_AVX_ROTATE(_Tpvec) \ + OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left, _Tpvec, OPENCV_HAL_NOP) \ + OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, _Tpvec, OPENCV_HAL_NOP) + +OPENCV_HAL_IMPL_AVX_ROTATE(v_int8x32) +OPENCV_HAL_IMPL_AVX_ROTATE(v_uint16x16) +OPENCV_HAL_IMPL_AVX_ROTATE(v_int16x16) +OPENCV_HAL_IMPL_AVX_ROTATE(v_uint32x8) +OPENCV_HAL_IMPL_AVX_ROTATE(v_int32x8) +OPENCV_HAL_IMPL_AVX_ROTATE(v_uint64x4) +OPENCV_HAL_IMPL_AVX_ROTATE(v_int64x4) + +OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left, v_float32x8, _mm256_castsi256_ps) +OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, v_float32x8, _mm256_castsi256_ps) +OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left, v_float64x4, _mm256_castsi256_pd) +OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, v_float64x4, _mm256_castsi256_pd) + +////////// Reduce and mask ///////// + +/** Reduce **/ +#define OPENCV_HAL_IMPL_AVX_REDUCE_16(_Tpvec, sctype, func, intrin) \ + inline sctype v_reduce_##func(const _Tpvec& a) \ + { \ + __m128i v0 = _v256_extract_low(a.val); \ + __m128i v1 = _v256_extract_high(a.val); \ + v0 = intrin(v0, v1); \ + v0 = intrin(v0, _mm_srli_si128(v0, 8)); \ + v0 = intrin(v0, _mm_srli_si128(v0, 4)); \ + v0 = intrin(v0, _mm_srli_si128(v0, 2)); \ + return (sctype) _mm_cvtsi128_si32(v0); \ + } + +OPENCV_HAL_IMPL_AVX_REDUCE_16(v_uint16x16, ushort, min, _mm_min_epu16) +OPENCV_HAL_IMPL_AVX_REDUCE_16(v_int16x16, short, min, _mm_min_epi16) +OPENCV_HAL_IMPL_AVX_REDUCE_16(v_uint16x16, ushort, max, _mm_max_epu16) +OPENCV_HAL_IMPL_AVX_REDUCE_16(v_int16x16, short, max, _mm_max_epi16) + +#define OPENCV_HAL_IMPL_AVX_REDUCE_8(_Tpvec, sctype, func, intrin) \ + inline sctype v_reduce_##func(const _Tpvec& a) \ + { \ + __m128i v0 = _v256_extract_low(a.val); \ + __m128i v1 = _v256_extract_high(a.val); \ + v0 = intrin(v0, v1); \ + v0 = intrin(v0, _mm_srli_si128(v0, 8)); \ + v0 = intrin(v0, _mm_srli_si128(v0, 4)); \ + return (sctype) _mm_cvtsi128_si32(v0); \ + } + +OPENCV_HAL_IMPL_AVX_REDUCE_8(v_uint32x8, unsigned, min, _mm_min_epu32) +OPENCV_HAL_IMPL_AVX_REDUCE_8(v_int32x8, int, min, _mm_min_epi32) +OPENCV_HAL_IMPL_AVX_REDUCE_8(v_uint32x8, unsigned, max, _mm_max_epu32) +OPENCV_HAL_IMPL_AVX_REDUCE_8(v_int32x8, int, max, _mm_max_epi32) + +#define OPENCV_HAL_IMPL_AVX_REDUCE_FLT(func, intrin) \ + inline float v_reduce_##func(const v_float32x8& a) \ + { \ + __m128 v0 = _v256_extract_low(a.val); \ + __m128 v1 = _v256_extract_high(a.val); \ + v0 = intrin(v0, v1); \ + v0 = intrin(v0, _mm_permute_ps(v0, _MM_SHUFFLE(0, 0, 3, 2))); \ + v0 = intrin(v0, _mm_permute_ps(v0, _MM_SHUFFLE(0, 0, 0, 3))); \ + return _mm_cvtss_f32(v0); \ + } + +OPENCV_HAL_IMPL_AVX_REDUCE_FLT(min, _mm_min_ps) +OPENCV_HAL_IMPL_AVX_REDUCE_FLT(max, _mm_max_ps) + +inline ushort v_reduce_sum(const v_uint16x16& a) +{ + __m128i a0 = _v256_extract_low(a.val); + __m128i a1 = _v256_extract_high(a.val); + + __m128i s0 = _mm_adds_epu16(a0, a1); + s0 = _mm_adds_epu16(s0, _mm_srli_si128(s0, 8)); + s0 = _mm_adds_epu16(s0, _mm_srli_si128(s0, 4)); + s0 = _mm_adds_epu16(s0, _mm_srli_si128(s0, 2)); + + return (ushort)_mm_cvtsi128_si32(s0); +} + +inline short v_reduce_sum(const v_int16x16& a) +{ + __m256i s0 = _mm256_hadds_epi16(a.val, a.val); + s0 = _mm256_hadds_epi16(s0, s0); + s0 = _mm256_hadds_epi16(s0, s0); + + __m128i s1 = _v256_extract_high(s0); + s1 = _mm_adds_epi16(_v256_extract_low(s0), s1); + + return (short)_mm_cvtsi128_si32(s1); +} + +inline int v_reduce_sum(const v_int32x8& a) +{ + __m256i s0 = _mm256_hadd_epi32(a.val, a.val); + s0 = _mm256_hadd_epi32(s0, s0); + + __m128i s1 = _v256_extract_high(s0); + s1 = _mm_add_epi32(_v256_extract_low(s0), s1); + + return _mm_cvtsi128_si32(s1); +} + +inline unsigned v_reduce_sum(const v_uint32x8& a) +{ return v_reduce_sum(v_reinterpret_as_s32(a)); } + +inline float v_reduce_sum(const v_float32x8& a) +{ + __m256 s0 = _mm256_hadd_ps(a.val, a.val); + s0 = _mm256_hadd_ps(s0, s0); + + __m128 s1 = _v256_extract_high(s0); + s1 = _mm_add_ps(_v256_extract_low(s0), s1); + + return _mm_cvtss_f32(s1); +} + +inline double v_reduce_sum(const v_float64x4& a) +{ + __m256d s0 = _mm256_hadd_pd(a.val, a.val); + return _mm_cvtsd_f64(_mm_add_pd(_v256_extract_low(s0), _v256_extract_high(s0))); +} + +inline v_float32x8 v_reduce_sum4(const v_float32x8& a, const v_float32x8& b, + const v_float32x8& c, const v_float32x8& d) +{ + __m256 ab = _mm256_hadd_ps(a.val, b.val); + __m256 cd = _mm256_hadd_ps(c.val, d.val); + return v_float32x8(_mm256_hadd_ps(ab, cd)); +} + +inline unsigned v_reduce_sad(const v_uint8x32& a, const v_uint8x32& b) +{ + return (unsigned)_v_cvtsi256_si32(_mm256_sad_epu8(a.val, b.val)); +} +inline unsigned v_reduce_sad(const v_int8x32& a, const v_int8x32& b) +{ + __m256i half = _mm256_set1_epi8(0x7f); + return (unsigned)_v_cvtsi256_si32(_mm256_sad_epu8(_mm256_add_epi8(a.val, half), _mm256_add_epi8(b.val, half))); +} +inline unsigned v_reduce_sad(const v_uint16x16& a, const v_uint16x16& b) +{ + v_uint32x8 l, h; + v_expand(v_add_wrap(a - b, b - a), l, h); + return v_reduce_sum(l + h); +} +inline unsigned v_reduce_sad(const v_int16x16& a, const v_int16x16& b) +{ + v_uint32x8 l, h; + v_expand(v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))), l, h); + return v_reduce_sum(l + h); +} +inline unsigned v_reduce_sad(const v_uint32x8& a, const v_uint32x8& b) +{ + return v_reduce_sum(v_max(a, b) - v_min(a, b)); +} +inline unsigned v_reduce_sad(const v_int32x8& a, const v_int32x8& b) +{ + v_int32x8 m = a < b; + return v_reduce_sum(v_reinterpret_as_u32(((a - b) ^ m) - m)); +} +inline float v_reduce_sad(const v_float32x8& a, const v_float32x8& b) +{ + return v_reduce_sum((a - b) & v_float32x8(_mm256_castsi256_ps(_mm256_set1_epi32(0x7fffffff)))); +} + +/** Popcount **/ +#define OPENCV_HAL_IMPL_AVX_POPCOUNT(_Tpvec) \ + inline v_uint32x8 v_popcount(const _Tpvec& a) \ + { \ + const v_uint32x8 m1 = v256_setall_u32(0x55555555); \ + const v_uint32x8 m2 = v256_setall_u32(0x33333333); \ + const v_uint32x8 m4 = v256_setall_u32(0x0f0f0f0f); \ + v_uint32x8 p = v_reinterpret_as_u32(a); \ + p = ((p >> 1) & m1) + (p & m1); \ + p = ((p >> 2) & m2) + (p & m2); \ + p = ((p >> 4) & m4) + (p & m4); \ + p.val = _mm256_sad_epu8(p.val, _mm256_setzero_si256()); \ + return p; \ + } + +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_uint8x32) +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_int8x32) +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_uint16x16) +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_int16x16) +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_uint32x8) +OPENCV_HAL_IMPL_AVX_POPCOUNT(v_int32x8) + +/** Mask **/ +inline int v_signmask(const v_int8x32& a) +{ return _mm256_movemask_epi8(a.val); } +inline int v_signmask(const v_uint8x32& a) +{ return v_signmask(v_reinterpret_as_s8(a)); } + +inline int v_signmask(const v_int16x16& a) +{ + v_int8x32 v = v_int8x32(_mm256_packs_epi16(a.val, a.val)); + return v_signmask(v) & 255; +} +inline int v_signmask(const v_uint16x16& a) +{ return v_signmask(v_reinterpret_as_s16(a)); } + +inline int v_signmask(const v_int32x8& a) +{ + __m256i a16 = _mm256_packs_epi32(a.val, a.val); + v_int8x32 v = v_int8x32(_mm256_packs_epi16(a16, a16)); + return v_signmask(v) & 15; +} +inline int v_signmask(const v_uint32x8& a) +{ return v_signmask(v_reinterpret_as_s32(a)); } + +inline int v_signmask(const v_float32x8& a) +{ return _mm256_movemask_ps(a.val); } +inline int v_signmask(const v_float64x4& a) +{ return _mm256_movemask_pd(a.val); } + +/** Checks **/ +#define OPENCV_HAL_IMPL_AVX_CHECK(_Tpvec, and_op, allmask) \ + inline bool v_check_all(const _Tpvec& a) \ + { \ + int mask = v_signmask(v_reinterpret_as_s8(a)); \ + return and_op(mask, allmask) == allmask; \ + } \ + inline bool v_check_any(const _Tpvec& a) \ + { \ + int mask = v_signmask(v_reinterpret_as_s8(a)); \ + return and_op(mask, allmask) != 0; \ + } + +OPENCV_HAL_IMPL_AVX_CHECK(v_uint8x32, OPENCV_HAL_1ST, -1) +OPENCV_HAL_IMPL_AVX_CHECK(v_int8x32, OPENCV_HAL_1ST, -1) +OPENCV_HAL_IMPL_AVX_CHECK(v_uint16x16, OPENCV_HAL_AND, (int)0xaaaa) +OPENCV_HAL_IMPL_AVX_CHECK(v_int16x16, OPENCV_HAL_AND, (int)0xaaaa) +OPENCV_HAL_IMPL_AVX_CHECK(v_uint32x8, OPENCV_HAL_AND, (int)0x8888) +OPENCV_HAL_IMPL_AVX_CHECK(v_int32x8, OPENCV_HAL_AND, (int)0x8888) + +#define OPENCV_HAL_IMPL_AVX_CHECK_FLT(_Tpvec, allmask) \ + inline bool v_check_all(const _Tpvec& a) \ + { \ + int mask = v_signmask(a); \ + return mask == allmask; \ + } \ + inline bool v_check_any(const _Tpvec& a) \ + { \ + int mask = v_signmask(a); \ + return mask != 0; \ + } + +OPENCV_HAL_IMPL_AVX_CHECK_FLT(v_float32x8, 255) +OPENCV_HAL_IMPL_AVX_CHECK_FLT(v_float64x4, 15) + + +////////// Other math ///////// + +/** Some frequent operations **/ +#define OPENCV_HAL_IMPL_AVX_MULADD(_Tpvec, suffix) \ + inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \ + { return _Tpvec(_mm256_fmadd_##suffix(a.val, b.val, c.val)); } \ + inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \ + { return _Tpvec(_mm256_fmadd_##suffix(a.val, b.val, c.val)); } \ + inline _Tpvec v_sqrt(const _Tpvec& x) \ + { return _Tpvec(_mm256_sqrt_##suffix(x.val)); } \ + inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b) \ + { return v_fma(a, a, b * b); } \ + inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b) \ + { return v_sqrt(v_fma(a, a, b*b)); } + +OPENCV_HAL_IMPL_AVX_MULADD(v_float32x8, ps) +OPENCV_HAL_IMPL_AVX_MULADD(v_float64x4, pd) + +inline v_int32x8 v_fma(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c) +{ + return a * b + c; +} + +inline v_int32x8 v_muladd(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c) +{ + return v_fma(a, b, c); +} + +inline v_float32x8 v_invsqrt(const v_float32x8& x) +{ + v_float32x8 half = x * v256_setall_f32(0.5); + v_float32x8 t = v_float32x8(_mm256_rsqrt_ps(x.val)); + // todo: _mm256_fnmsub_ps + t *= v256_setall_f32(1.5) - ((t * t) * half); + return t; +} + +inline v_float64x4 v_invsqrt(const v_float64x4& x) +{ + return v256_setall_f64(1.) / v_sqrt(x); +} + +/** Absolute values **/ +#define OPENCV_HAL_IMPL_AVX_ABS(_Tpvec, suffix) \ + inline v_u##_Tpvec v_abs(const v_##_Tpvec& x) \ + { return v_u##_Tpvec(_mm256_abs_##suffix(x.val)); } + +OPENCV_HAL_IMPL_AVX_ABS(int8x32, epi8) +OPENCV_HAL_IMPL_AVX_ABS(int16x16, epi16) +OPENCV_HAL_IMPL_AVX_ABS(int32x8, epi32) + +inline v_float32x8 v_abs(const v_float32x8& x) +{ return x & v_float32x8(_mm256_castsi256_ps(_mm256_set1_epi32(0x7fffffff))); } +inline v_float64x4 v_abs(const v_float64x4& x) +{ return x & v_float64x4(_mm256_castsi256_pd(_mm256_srli_epi64(_mm256_set1_epi64x(-1), 1))); } + +/** Absolute difference **/ +inline v_uint8x32 v_absdiff(const v_uint8x32& a, const v_uint8x32& b) +{ return v_add_wrap(a - b, b - a); } +inline v_uint16x16 v_absdiff(const v_uint16x16& a, const v_uint16x16& b) +{ return v_add_wrap(a - b, b - a); } +inline v_uint32x8 v_absdiff(const v_uint32x8& a, const v_uint32x8& b) +{ return v_max(a, b) - v_min(a, b); } + +inline v_uint8x32 v_absdiff(const v_int8x32& a, const v_int8x32& b) +{ + v_int8x32 d = v_sub_wrap(a, b); + v_int8x32 m = a < b; + return v_reinterpret_as_u8(v_sub_wrap(d ^ m, m)); +} + +inline v_uint16x16 v_absdiff(const v_int16x16& a, const v_int16x16& b) +{ return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); } + +inline v_uint32x8 v_absdiff(const v_int32x8& a, const v_int32x8& b) +{ + v_int32x8 d = a - b; + v_int32x8 m = a < b; + return v_reinterpret_as_u32((d ^ m) - m); +} + +inline v_float32x8 v_absdiff(const v_float32x8& a, const v_float32x8& b) +{ return v_abs(a - b); } + +inline v_float64x4 v_absdiff(const v_float64x4& a, const v_float64x4& b) +{ return v_abs(a - b); } + +/** Saturating absolute difference **/ +inline v_int8x32 v_absdiffs(const v_int8x32& a, const v_int8x32& b) +{ + v_int8x32 d = a - b; + v_int8x32 m = a < b; + return (d ^ m) - m; +} +inline v_int16x16 v_absdiffs(const v_int16x16& a, const v_int16x16& b) +{ return v_max(a, b) - v_min(a, b); } + +////////// Conversions ///////// + +/** Rounding **/ +inline v_int32x8 v_round(const v_float32x8& a) +{ return v_int32x8(_mm256_cvtps_epi32(a.val)); } + +inline v_int32x8 v_round(const v_float64x4& a) +{ return v_int32x8(_mm256_castsi128_si256(_mm256_cvtpd_epi32(a.val))); } + +inline v_int32x8 v_round(const v_float64x4& a, const v_float64x4& b) +{ + __m128i ai = _mm256_cvtpd_epi32(a.val), bi = _mm256_cvtpd_epi32(b.val); + return v_int32x8(_v256_combine(ai, bi)); +} + +inline v_int32x8 v_trunc(const v_float32x8& a) +{ return v_int32x8(_mm256_cvttps_epi32(a.val)); } + +inline v_int32x8 v_trunc(const v_float64x4& a) +{ return v_int32x8(_mm256_castsi128_si256(_mm256_cvttpd_epi32(a.val))); } + +inline v_int32x8 v_floor(const v_float32x8& a) +{ return v_int32x8(_mm256_cvttps_epi32(_mm256_floor_ps(a.val))); } + +inline v_int32x8 v_floor(const v_float64x4& a) +{ return v_trunc(v_float64x4(_mm256_floor_pd(a.val))); } + +inline v_int32x8 v_ceil(const v_float32x8& a) +{ return v_int32x8(_mm256_cvttps_epi32(_mm256_ceil_ps(a.val))); } + +inline v_int32x8 v_ceil(const v_float64x4& a) +{ return v_trunc(v_float64x4(_mm256_ceil_pd(a.val))); } + +/** To float **/ +inline v_float32x8 v_cvt_f32(const v_int32x8& a) +{ return v_float32x8(_mm256_cvtepi32_ps(a.val)); } + +inline v_float32x8 v_cvt_f32(const v_float64x4& a) +{ return v_float32x8(_mm256_castps128_ps256(_mm256_cvtpd_ps(a.val))); } + +inline v_float32x8 v_cvt_f32(const v_float64x4& a, const v_float64x4& b) +{ + __m128 af = _mm256_cvtpd_ps(a.val), bf = _mm256_cvtpd_ps(b.val); + return v_float32x8(_mm256_insertf128_ps(_mm256_castps128_ps256(af), bf, 1)); +} + +inline v_float64x4 v_cvt_f64(const v_int32x8& a) +{ return v_float64x4(_mm256_cvtepi32_pd(_v256_extract_low(a.val))); } + +inline v_float64x4 v_cvt_f64_high(const v_int32x8& a) +{ return v_float64x4(_mm256_cvtepi32_pd(_v256_extract_high(a.val))); } + +inline v_float64x4 v_cvt_f64(const v_float32x8& a) +{ return v_float64x4(_mm256_cvtps_pd(_v256_extract_low(a.val))); } + +inline v_float64x4 v_cvt_f64_high(const v_float32x8& a) +{ return v_float64x4(_mm256_cvtps_pd(_v256_extract_high(a.val))); } + +////////////// Lookup table access //////////////////// + +inline v_int8x32 v256_lut(const schar* tab, const int* idx) +{ + return v_int8x32(_mm256_setr_epi8(tab[idx[ 0]], tab[idx[ 1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]], + tab[idx[ 8]], tab[idx[ 9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]], + tab[idx[16]], tab[idx[17]], tab[idx[18]], tab[idx[19]], tab[idx[20]], tab[idx[21]], tab[idx[22]], tab[idx[23]], + tab[idx[24]], tab[idx[25]], tab[idx[26]], tab[idx[27]], tab[idx[28]], tab[idx[29]], tab[idx[30]], tab[idx[31]])); +} +inline v_int8x32 v256_lut_pairs(const schar* tab, const int* idx) +{ + return v_int8x32(_mm256_setr_epi16(*(const short*)(tab + idx[ 0]), *(const short*)(tab + idx[ 1]), *(const short*)(tab + idx[ 2]), *(const short*)(tab + idx[ 3]), + *(const short*)(tab + idx[ 4]), *(const short*)(tab + idx[ 5]), *(const short*)(tab + idx[ 6]), *(const short*)(tab + idx[ 7]), + *(const short*)(tab + idx[ 8]), *(const short*)(tab + idx[ 9]), *(const short*)(tab + idx[10]), *(const short*)(tab + idx[11]), + *(const short*)(tab + idx[12]), *(const short*)(tab + idx[13]), *(const short*)(tab + idx[14]), *(const short*)(tab + idx[15]))); +} +inline v_int8x32 v256_lut_quads(const schar* tab, const int* idx) +{ + return v_int8x32(_mm256_i32gather_epi32((const int*)tab, _mm256_loadu_si256((const __m256i*)idx), 1)); +} +inline v_uint8x32 v256_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut((const schar *)tab, idx)); } +inline v_uint8x32 v256_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_pairs((const schar *)tab, idx)); } +inline v_uint8x32 v256_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_quads((const schar *)tab, idx)); } + +inline v_int16x16 v256_lut(const short* tab, const int* idx) +{ + return v_int16x16(_mm256_setr_epi16(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]], + tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]])); +} +inline v_int16x16 v256_lut_pairs(const short* tab, const int* idx) +{ + return v_int16x16(_mm256_i32gather_epi32((const int*)tab, _mm256_loadu_si256((const __m256i*)idx), 2)); +} +inline v_int16x16 v256_lut_quads(const short* tab, const int* idx) +{ +#if defined(__GNUC__) + return v_int16x16(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 2));//Looks like intrinsic has wrong definition +#else + return v_int16x16(_mm256_i32gather_epi64((const int64*)tab, _mm_loadu_si128((const __m128i*)idx), 2)); +#endif +} +inline v_uint16x16 v256_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut((const short *)tab, idx)); } +inline v_uint16x16 v256_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_pairs((const short *)tab, idx)); } +inline v_uint16x16 v256_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_quads((const short *)tab, idx)); } + +inline v_int32x8 v256_lut(const int* tab, const int* idx) +{ + return v_int32x8(_mm256_i32gather_epi32(tab, _mm256_loadu_si256((const __m256i*)idx), 4)); +} +inline v_int32x8 v256_lut_pairs(const int* tab, const int* idx) +{ +#if defined(__GNUC__) + return v_int32x8(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 4)); +#else + return v_int32x8(_mm256_i32gather_epi64((const int64*)tab, _mm_loadu_si128((const __m128i*)idx), 4)); +#endif +} +inline v_int32x8 v256_lut_quads(const int* tab, const int* idx) +{ + return v_int32x8(_mm256_insertf128_si256(_mm256_castsi128_si256(_mm_loadu_si128((const __m128i*)(tab + idx[0]))), _mm_loadu_si128((const __m128i*)(tab + idx[1])), 0x1)); +} +inline v_uint32x8 v256_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut((const int *)tab, idx)); } +inline v_uint32x8 v256_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_pairs((const int *)tab, idx)); } +inline v_uint32x8 v256_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_quads((const int *)tab, idx)); } + +inline v_int64x4 v256_lut(const int64* tab, const int* idx) +{ +#if defined(__GNUC__) + return v_int64x4(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 8)); +#else + return v_int64x4(_mm256_i32gather_epi64(tab, _mm_loadu_si128((const __m128i*)idx), 8)); +#endif +} +inline v_int64x4 v256_lut_pairs(const int64* tab, const int* idx) +{ + return v_int64x4(_mm256_insertf128_si256(_mm256_castsi128_si256(_mm_loadu_si128((const __m128i*)(tab + idx[0]))), _mm_loadu_si128((const __m128i*)(tab + idx[1])), 0x1)); +} +inline v_uint64x4 v256_lut(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut((const int64 *)tab, idx)); } +inline v_uint64x4 v256_lut_pairs(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut_pairs((const int64 *)tab, idx)); } + +inline v_float32x8 v256_lut(const float* tab, const int* idx) +{ + return v_float32x8(_mm256_i32gather_ps(tab, _mm256_loadu_si256((const __m256i*)idx), 4)); +} +inline v_float32x8 v256_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_pairs((const int *)tab, idx)); } +inline v_float32x8 v256_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_quads((const int *)tab, idx)); } + +inline v_float64x4 v256_lut(const double* tab, const int* idx) +{ + return v_float64x4(_mm256_i32gather_pd(tab, _mm_loadu_si128((const __m128i*)idx), 8)); +} +inline v_float64x4 v256_lut_pairs(const double* tab, const int* idx) { return v_float64x4(_mm256_insertf128_pd(_mm256_castpd128_pd256(_mm_loadu_pd(tab + idx[0])), _mm_loadu_pd(tab + idx[1]), 0x1)); } + +inline v_int32x8 v_lut(const int* tab, const v_int32x8& idxvec) +{ + return v_int32x8(_mm256_i32gather_epi32(tab, idxvec.val, 4)); +} + +inline v_uint32x8 v_lut(const unsigned* tab, const v_int32x8& idxvec) +{ + return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec)); +} + +inline v_float32x8 v_lut(const float* tab, const v_int32x8& idxvec) +{ + return v_float32x8(_mm256_i32gather_ps(tab, idxvec.val, 4)); +} + +inline v_float64x4 v_lut(const double* tab, const v_int32x8& idxvec) +{ + return v_float64x4(_mm256_i32gather_pd(tab, _mm256_castsi256_si128(idxvec.val), 8)); +} + +inline void v_lut_deinterleave(const float* tab, const v_int32x8& idxvec, v_float32x8& x, v_float32x8& y) +{ + int CV_DECL_ALIGNED(32) idx[8]; + v_store_aligned(idx, idxvec); + __m128 z = _mm_setzero_ps(); + __m128 xy01, xy45, xy23, xy67; + xy01 = _mm_loadl_pi(z, (const __m64*)(tab + idx[0])); + xy01 = _mm_loadh_pi(xy01, (const __m64*)(tab + idx[1])); + xy45 = _mm_loadl_pi(z, (const __m64*)(tab + idx[4])); + xy45 = _mm_loadh_pi(xy45, (const __m64*)(tab + idx[5])); + __m256 xy0145 = _v256_combine(xy01, xy45); + xy23 = _mm_loadl_pi(z, (const __m64*)(tab + idx[2])); + xy23 = _mm_loadh_pi(xy23, (const __m64*)(tab + idx[3])); + xy67 = _mm_loadl_pi(z, (const __m64*)(tab + idx[6])); + xy67 = _mm_loadh_pi(xy67, (const __m64*)(tab + idx[7])); + __m256 xy2367 = _v256_combine(xy23, xy67); + + __m256 xxyy0145 = _mm256_unpacklo_ps(xy0145, xy2367); + __m256 xxyy2367 = _mm256_unpackhi_ps(xy0145, xy2367); + + x = v_float32x8(_mm256_unpacklo_ps(xxyy0145, xxyy2367)); + y = v_float32x8(_mm256_unpackhi_ps(xxyy0145, xxyy2367)); +} + +inline void v_lut_deinterleave(const double* tab, const v_int32x8& idxvec, v_float64x4& x, v_float64x4& y) +{ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_low(idx, idxvec); + __m128d xy0 = _mm_loadu_pd(tab + idx[0]); + __m128d xy2 = _mm_loadu_pd(tab + idx[2]); + __m128d xy1 = _mm_loadu_pd(tab + idx[1]); + __m128d xy3 = _mm_loadu_pd(tab + idx[3]); + __m256d xy02 = _v256_combine(xy0, xy2); + __m256d xy13 = _v256_combine(xy1, xy3); + + x = v_float64x4(_mm256_unpacklo_pd(xy02, xy13)); + y = v_float64x4(_mm256_unpackhi_pd(xy02, xy13)); +} + +inline v_int8x32 v_interleave_pairs(const v_int8x32& vec) +{ + return v_int8x32(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0d0e0c0b090a08, 0x0705060403010200, 0x0f0d0e0c0b090a08, 0x0705060403010200))); +} +inline v_uint8x32 v_interleave_pairs(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); } +inline v_int8x32 v_interleave_quads(const v_int8x32& vec) +{ + return v_int8x32(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0b0e0a0d090c08, 0x0703060205010400, 0x0f0b0e0a0d090c08, 0x0703060205010400))); +} +inline v_uint8x32 v_interleave_quads(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); } + +inline v_int16x16 v_interleave_pairs(const v_int16x16& vec) +{ + return v_int16x16(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0e0b0a0d0c0908, 0x0706030205040100, 0x0f0e0b0a0d0c0908, 0x0706030205040100))); +} +inline v_uint16x16 v_interleave_pairs(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); } +inline v_int16x16 v_interleave_quads(const v_int16x16& vec) +{ + return v_int16x16(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0e07060d0c0504, 0x0b0a030209080100, 0x0f0e07060d0c0504, 0x0b0a030209080100))); +} +inline v_uint16x16 v_interleave_quads(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); } + +inline v_int32x8 v_interleave_pairs(const v_int32x8& vec) +{ + return v_int32x8(_mm256_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0))); +} +inline v_uint32x8 v_interleave_pairs(const v_uint32x8& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } +inline v_float32x8 v_interleave_pairs(const v_float32x8& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } + +inline v_int8x32 v_pack_triplets(const v_int8x32& vec) +{ + return v_int8x32(_mm256_permutevar8x32_epi32(_mm256_shuffle_epi8(vec.val, _mm256_broadcastsi128_si256(_mm_set_epi64x(0xffffff0f0e0d0c0a, 0x0908060504020100))), + _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000))); +} +inline v_uint8x32 v_pack_triplets(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); } + +inline v_int16x16 v_pack_triplets(const v_int16x16& vec) +{ + return v_int16x16(_mm256_permutevar8x32_epi32(_mm256_shuffle_epi8(vec.val, _mm256_broadcastsi128_si256(_mm_set_epi64x(0xffff0f0e0d0c0b0a, 0x0908050403020100))), + _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000))); +} +inline v_uint16x16 v_pack_triplets(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); } + +inline v_int32x8 v_pack_triplets(const v_int32x8& vec) +{ + return v_int32x8(_mm256_permutevar8x32_epi32(vec.val, _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000))); +} +inline v_uint32x8 v_pack_triplets(const v_uint32x8& vec) { return v_reinterpret_as_u32(v_pack_triplets(v_reinterpret_as_s32(vec))); } +inline v_float32x8 v_pack_triplets(const v_float32x8& vec) +{ + return v_float32x8(_mm256_permutevar8x32_ps(vec.val, _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000))); +} + +////////// Matrix operations ///////// + +inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b) +{ return v_int32x8(_mm256_madd_epi16(a.val, b.val)); } + +inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b, const v_int32x8& c) +{ return v_dotprod(a, b) + c; } + +#define OPENCV_HAL_AVX_SPLAT2_PS(a, im) \ + v_float32x8(_mm256_permute_ps(a.val, _MM_SHUFFLE(im, im, im, im))) + +inline v_float32x8 v_matmul(const v_float32x8& v, const v_float32x8& m0, + const v_float32x8& m1, const v_float32x8& m2, + const v_float32x8& m3) +{ + v_float32x8 v04 = OPENCV_HAL_AVX_SPLAT2_PS(v, 0); + v_float32x8 v15 = OPENCV_HAL_AVX_SPLAT2_PS(v, 1); + v_float32x8 v26 = OPENCV_HAL_AVX_SPLAT2_PS(v, 2); + v_float32x8 v37 = OPENCV_HAL_AVX_SPLAT2_PS(v, 3); + return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, v37 * m3))); +} + +inline v_float32x8 v_matmuladd(const v_float32x8& v, const v_float32x8& m0, + const v_float32x8& m1, const v_float32x8& m2, + const v_float32x8& a) +{ + v_float32x8 v04 = OPENCV_HAL_AVX_SPLAT2_PS(v, 0); + v_float32x8 v15 = OPENCV_HAL_AVX_SPLAT2_PS(v, 1); + v_float32x8 v26 = OPENCV_HAL_AVX_SPLAT2_PS(v, 2); + return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, a))); +} + +#define OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(_Tpvec, suffix, cast_from, cast_to) \ + inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \ + const _Tpvec& a2, const _Tpvec& a3, \ + _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3) \ + { \ + __m256i t0 = cast_from(_mm256_unpacklo_##suffix(a0.val, a1.val)); \ + __m256i t1 = cast_from(_mm256_unpacklo_##suffix(a2.val, a3.val)); \ + __m256i t2 = cast_from(_mm256_unpackhi_##suffix(a0.val, a1.val)); \ + __m256i t3 = cast_from(_mm256_unpackhi_##suffix(a2.val, a3.val)); \ + b0.val = cast_to(_mm256_unpacklo_epi64(t0, t1)); \ + b1.val = cast_to(_mm256_unpackhi_epi64(t0, t1)); \ + b2.val = cast_to(_mm256_unpacklo_epi64(t2, t3)); \ + b3.val = cast_to(_mm256_unpackhi_epi64(t2, t3)); \ + } + +OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_uint32x8, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_int32x8, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_float32x8, ps, _mm256_castps_si256, _mm256_castsi256_ps) + +//////////////// Value reordering /////////////// + +/* Expand */ +#define OPENCV_HAL_IMPL_AVX_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin) \ + inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \ + { \ + b0.val = intrin(_v256_extract_low(a.val)); \ + b1.val = intrin(_v256_extract_high(a.val)); \ + } \ + inline _Tpwvec v_expand_low(const _Tpvec& a) \ + { return _Tpwvec(intrin(_v256_extract_low(a.val))); } \ + inline _Tpwvec v_expand_high(const _Tpvec& a) \ + { return _Tpwvec(intrin(_v256_extract_high(a.val))); } \ + inline _Tpwvec v256_load_expand(const _Tp* ptr) \ + { \ + __m128i a = _mm_loadu_si128((const __m128i*)ptr); \ + return _Tpwvec(intrin(a)); \ + } + +OPENCV_HAL_IMPL_AVX_EXPAND(v_uint8x32, v_uint16x16, uchar, _mm256_cvtepu8_epi16) +OPENCV_HAL_IMPL_AVX_EXPAND(v_int8x32, v_int16x16, schar, _mm256_cvtepi8_epi16) +OPENCV_HAL_IMPL_AVX_EXPAND(v_uint16x16, v_uint32x8, ushort, _mm256_cvtepu16_epi32) +OPENCV_HAL_IMPL_AVX_EXPAND(v_int16x16, v_int32x8, short, _mm256_cvtepi16_epi32) +OPENCV_HAL_IMPL_AVX_EXPAND(v_uint32x8, v_uint64x4, unsigned, _mm256_cvtepu32_epi64) +OPENCV_HAL_IMPL_AVX_EXPAND(v_int32x8, v_int64x4, int, _mm256_cvtepi32_epi64) + +#define OPENCV_HAL_IMPL_AVX_EXPAND_Q(_Tpvec, _Tp, intrin) \ + inline _Tpvec v256_load_expand_q(const _Tp* ptr) \ + { \ + __m128i a = _mm_loadl_epi64((const __m128i*)ptr); \ + return _Tpvec(intrin(a)); \ + } + +OPENCV_HAL_IMPL_AVX_EXPAND_Q(v_uint32x8, uchar, _mm256_cvtepu8_epi32) +OPENCV_HAL_IMPL_AVX_EXPAND_Q(v_int32x8, schar, _mm256_cvtepi8_epi32) + +/* pack */ +// 16 +inline v_int8x32 v_pack(const v_int16x16& a, const v_int16x16& b) +{ return v_int8x32(_v256_shuffle_odd_64(_mm256_packs_epi16(a.val, b.val))); } + +inline v_uint8x32 v_pack(const v_uint16x16& a, const v_uint16x16& b) +{ + __m256i t = _mm256_set1_epi16(255); + __m256i a1 = _mm256_min_epu16(a.val, t); + __m256i b1 = _mm256_min_epu16(b.val, t); + return v_uint8x32(_v256_shuffle_odd_64(_mm256_packus_epi16(a1, b1))); +} + +inline v_uint8x32 v_pack_u(const v_int16x16& a, const v_int16x16& b) +{ + return v_uint8x32(_v256_shuffle_odd_64(_mm256_packus_epi16(a.val, b.val))); +} + +inline void v_pack_store(schar* ptr, const v_int16x16& a) +{ v_store_low(ptr, v_pack(a, a)); } + +inline void v_pack_store(uchar* ptr, const v_uint16x16& a) +{ + const __m256i m = _mm256_set1_epi16(255); + __m256i am = _mm256_min_epu16(a.val, m); + am = _v256_shuffle_odd_64(_mm256_packus_epi16(am, am)); + v_store_low(ptr, v_uint8x32(am)); +} + +inline void v_pack_u_store(uchar* ptr, const v_int16x16& a) +{ v_store_low(ptr, v_pack_u(a, a)); } + +template inline +v_uint8x32 v_rshr_pack(const v_uint16x16& a, const v_uint16x16& b) +{ + // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers. + v_uint16x16 delta = v256_setall_u16((short)(1 << (n-1))); + return v_pack_u(v_reinterpret_as_s16((a + delta) >> n), + v_reinterpret_as_s16((b + delta) >> n)); +} + +template inline +void v_rshr_pack_store(uchar* ptr, const v_uint16x16& a) +{ + v_uint16x16 delta = v256_setall_u16((short)(1 << (n-1))); + v_pack_u_store(ptr, v_reinterpret_as_s16((a + delta) >> n)); +} + +template inline +v_uint8x32 v_rshr_pack_u(const v_int16x16& a, const v_int16x16& b) +{ + v_int16x16 delta = v256_setall_s16((short)(1 << (n-1))); + return v_pack_u((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_u_store(uchar* ptr, const v_int16x16& a) +{ + v_int16x16 delta = v256_setall_s16((short)(1 << (n-1))); + v_pack_u_store(ptr, (a + delta) >> n); +} + +template inline +v_int8x32 v_rshr_pack(const v_int16x16& a, const v_int16x16& b) +{ + v_int16x16 delta = v256_setall_s16((short)(1 << (n-1))); + return v_pack((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_store(schar* ptr, const v_int16x16& a) +{ + v_int16x16 delta = v256_setall_s16((short)(1 << (n-1))); + v_pack_store(ptr, (a + delta) >> n); +} + +// 32 +inline v_int16x16 v_pack(const v_int32x8& a, const v_int32x8& b) +{ return v_int16x16(_v256_shuffle_odd_64(_mm256_packs_epi32(a.val, b.val))); } + +inline v_uint16x16 v_pack(const v_uint32x8& a, const v_uint32x8& b) +{ return v_uint16x16(_v256_shuffle_odd_64(_v256_packs_epu32(a.val, b.val))); } + +inline v_uint16x16 v_pack_u(const v_int32x8& a, const v_int32x8& b) +{ return v_uint16x16(_v256_shuffle_odd_64(_mm256_packus_epi32(a.val, b.val))); } + +inline void v_pack_store(short* ptr, const v_int32x8& a) +{ v_store_low(ptr, v_pack(a, a)); } + +inline void v_pack_store(ushort* ptr, const v_uint32x8& a) +{ + const __m256i m = _mm256_set1_epi32(65535); + __m256i am = _mm256_min_epu32(a.val, m); + am = _v256_shuffle_odd_64(_mm256_packus_epi32(am, am)); + v_store_low(ptr, v_uint16x16(am)); +} + +inline void v_pack_u_store(ushort* ptr, const v_int32x8& a) +{ v_store_low(ptr, v_pack_u(a, a)); } + + +template inline +v_uint16x16 v_rshr_pack(const v_uint32x8& a, const v_uint32x8& b) +{ + // we assume that n > 0, and so the shifted 32-bit values can be treated as signed numbers. + v_uint32x8 delta = v256_setall_u32(1 << (n-1)); + return v_pack_u(v_reinterpret_as_s32((a + delta) >> n), + v_reinterpret_as_s32((b + delta) >> n)); +} + +template inline +void v_rshr_pack_store(ushort* ptr, const v_uint32x8& a) +{ + v_uint32x8 delta = v256_setall_u32(1 << (n-1)); + v_pack_u_store(ptr, v_reinterpret_as_s32((a + delta) >> n)); +} + +template inline +v_uint16x16 v_rshr_pack_u(const v_int32x8& a, const v_int32x8& b) +{ + v_int32x8 delta = v256_setall_s32(1 << (n-1)); + return v_pack_u((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_u_store(ushort* ptr, const v_int32x8& a) +{ + v_int32x8 delta = v256_setall_s32(1 << (n-1)); + v_pack_u_store(ptr, (a + delta) >> n); +} + +template inline +v_int16x16 v_rshr_pack(const v_int32x8& a, const v_int32x8& b) +{ + v_int32x8 delta = v256_setall_s32(1 << (n-1)); + return v_pack((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_store(short* ptr, const v_int32x8& a) +{ + v_int32x8 delta = v256_setall_s32(1 << (n-1)); + v_pack_store(ptr, (a + delta) >> n); +} + +// 64 +// Non-saturating pack +inline v_uint32x8 v_pack(const v_uint64x4& a, const v_uint64x4& b) +{ + __m256i a0 = _mm256_shuffle_epi32(a.val, _MM_SHUFFLE(0, 0, 2, 0)); + __m256i b0 = _mm256_shuffle_epi32(b.val, _MM_SHUFFLE(0, 0, 2, 0)); + __m256i ab = _mm256_unpacklo_epi64(a0, b0); // a0, a1, b0, b1, a2, a3, b2, b3 + return v_uint32x8(_v256_shuffle_odd_64(ab)); +} + +inline v_int32x8 v_pack(const v_int64x4& a, const v_int64x4& b) +{ return v_reinterpret_as_s32(v_pack(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b))); } + +inline void v_pack_store(unsigned* ptr, const v_uint64x4& a) +{ + __m256i a0 = _mm256_shuffle_epi32(a.val, _MM_SHUFFLE(0, 0, 2, 0)); + v_store_low(ptr, v_uint32x8(_v256_shuffle_odd_64(a0))); +} + +inline void v_pack_store(int* ptr, const v_int64x4& b) +{ v_pack_store((unsigned*)ptr, v_reinterpret_as_u64(b)); } + +template inline +v_uint32x8 v_rshr_pack(const v_uint64x4& a, const v_uint64x4& b) +{ + v_uint64x4 delta = v256_setall_u64((uint64)1 << (n-1)); + return v_pack((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_store(unsigned* ptr, const v_uint64x4& a) +{ + v_uint64x4 delta = v256_setall_u64((uint64)1 << (n-1)); + v_pack_store(ptr, (a + delta) >> n); +} + +template inline +v_int32x8 v_rshr_pack(const v_int64x4& a, const v_int64x4& b) +{ + v_int64x4 delta = v256_setall_s64((int64)1 << (n-1)); + return v_pack((a + delta) >> n, (b + delta) >> n); +} + +template inline +void v_rshr_pack_store(int* ptr, const v_int64x4& a) +{ + v_int64x4 delta = v256_setall_s64((int64)1 << (n-1)); + v_pack_store(ptr, (a + delta) >> n); +} + +// pack boolean +inline v_uint8x32 v_pack_b(const v_uint16x16& a, const v_uint16x16& b) +{ + __m256i ab = _mm256_packs_epi16(a.val, b.val); + return v_uint8x32(_v256_shuffle_odd_64(ab)); +} + +inline v_uint8x32 v_pack_b(const v_uint32x8& a, const v_uint32x8& b, + const v_uint32x8& c, const v_uint32x8& d) +{ + __m256i ab = _mm256_packs_epi32(a.val, b.val); + __m256i cd = _mm256_packs_epi32(c.val, d.val); + + __m256i abcd = _v256_shuffle_odd_64(_mm256_packs_epi16(ab, cd)); + return v_uint8x32(_mm256_shuffle_epi32(abcd, _MM_SHUFFLE(3, 1, 2, 0))); +} + +inline v_uint8x32 v_pack_b(const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c, + const v_uint64x4& d, const v_uint64x4& e, const v_uint64x4& f, + const v_uint64x4& g, const v_uint64x4& h) +{ + __m256i ab = _mm256_packs_epi32(a.val, b.val); + __m256i cd = _mm256_packs_epi32(c.val, d.val); + __m256i ef = _mm256_packs_epi32(e.val, f.val); + __m256i gh = _mm256_packs_epi32(g.val, h.val); + + __m256i abcd = _mm256_packs_epi32(ab, cd); + __m256i efgh = _mm256_packs_epi32(ef, gh); + __m256i pkall = _v256_shuffle_odd_64(_mm256_packs_epi16(abcd, efgh)); + + __m256i rev = _mm256_alignr_epi8(pkall, pkall, 8); + return v_uint8x32(_mm256_unpacklo_epi16(pkall, rev)); +} + +/* Recombine */ +// its up there with load and store operations + +/* Extract */ +#define OPENCV_HAL_IMPL_AVX_EXTRACT(_Tpvec) \ + template \ + inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) \ + { return v_rotate_right(a, b); } + +OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint8x32) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_int8x32) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint16x16) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_int16x16) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint32x8) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_int32x8) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint64x4) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_int64x4) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_float32x8) +OPENCV_HAL_IMPL_AVX_EXTRACT(v_float64x4) + + +///////////////////// load deinterleave ///////////////////////////// + +inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b ) +{ + __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 32)); + + const __m256i sh = _mm256_setr_epi8(0, 2, 4, 6, 8, 10, 12, 14, 1, 3, 5, 7, 9, 11, 13, 15, + 0, 2, 4, 6, 8, 10, 12, 14, 1, 3, 5, 7, 9, 11, 13, 15); + __m256i p0 = _mm256_shuffle_epi8(ab0, sh); + __m256i p1 = _mm256_shuffle_epi8(ab1, sh); + __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16); + __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16); + __m256i a0 = _mm256_unpacklo_epi64(pl, ph); + __m256i b0 = _mm256_unpackhi_epi64(pl, ph); + a = v_uint8x32(a0); + b = v_uint8x32(b0); +} + +inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b ) +{ + __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 16)); + + const __m256i sh = _mm256_setr_epi8(0, 1, 4, 5, 8, 9, 12, 13, 2, 3, 6, 7, 10, 11, 14, 15, + 0, 1, 4, 5, 8, 9, 12, 13, 2, 3, 6, 7, 10, 11, 14, 15); + __m256i p0 = _mm256_shuffle_epi8(ab0, sh); + __m256i p1 = _mm256_shuffle_epi8(ab1, sh); + __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16); + __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16); + __m256i a0 = _mm256_unpacklo_epi64(pl, ph); + __m256i b0 = _mm256_unpackhi_epi64(pl, ph); + a = v_uint16x16(a0); + b = v_uint16x16(b0); +} + +inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b ) +{ + __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 8)); + + const int sh = 0+2*4+1*16+3*64; + __m256i p0 = _mm256_shuffle_epi32(ab0, sh); + __m256i p1 = _mm256_shuffle_epi32(ab1, sh); + __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16); + __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16); + __m256i a0 = _mm256_unpacklo_epi64(pl, ph); + __m256i b0 = _mm256_unpackhi_epi64(pl, ph); + a = v_uint32x8(a0); + b = v_uint32x8(b0); +} + +inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b ) +{ + __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 4)); + + __m256i pl = _mm256_permute2x128_si256(ab0, ab1, 0 + 2*16); + __m256i ph = _mm256_permute2x128_si256(ab0, ab1, 1 + 3*16); + __m256i a0 = _mm256_unpacklo_epi64(pl, ph); + __m256i b0 = _mm256_unpackhi_epi64(pl, ph); + a = v_uint64x4(a0); + b = v_uint64x4(b0); +} + +inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 32)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 64)); + + __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16); + __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16); + + const __m256i m0 = _mm256_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, + 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0); + const __m256i m1 = _mm256_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, + -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1); + + __m256i b0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_low, s02_high, m0), bgr1, m1); + __m256i g0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_high, s02_low, m1), bgr1, m0); + __m256i r0 = _mm256_blendv_epi8(_mm256_blendv_epi8(bgr1, s02_low, m0), s02_high, m1); + + const __m256i + sh_b = _mm256_setr_epi8(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13, + 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13), + sh_g = _mm256_setr_epi8(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, + 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14), + sh_r = _mm256_setr_epi8(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, + 2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15); + b0 = _mm256_shuffle_epi8(b0, sh_b); + g0 = _mm256_shuffle_epi8(g0, sh_g); + r0 = _mm256_shuffle_epi8(r0, sh_r); + + a = v_uint8x32(b0); + b = v_uint8x32(g0); + c = v_uint8x32(r0); +} + +inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 16)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 32)); + + __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16); + __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16); + + const __m256i m0 = _mm256_setr_epi8(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, + 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0); + const __m256i m1 = _mm256_setr_epi8(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, + -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0); + __m256i b0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_low, s02_high, m0), bgr1, m1); + __m256i g0 = _mm256_blendv_epi8(_mm256_blendv_epi8(bgr1, s02_low, m0), s02_high, m1); + __m256i r0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_high, s02_low, m1), bgr1, m0); + const __m256i sh_b = _mm256_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11, + 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11); + const __m256i sh_g = _mm256_setr_epi8(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13, + 2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13); + const __m256i sh_r = _mm256_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, + 4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15); + b0 = _mm256_shuffle_epi8(b0, sh_b); + g0 = _mm256_shuffle_epi8(g0, sh_g); + r0 = _mm256_shuffle_epi8(r0, sh_r); + + a = v_uint16x16(b0); + b = v_uint16x16(g0); + c = v_uint16x16(r0); +} + +inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 8)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 16)); + + __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16); + __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16); + + __m256i b0 = _mm256_blend_epi32(_mm256_blend_epi32(s02_low, s02_high, 0x24), bgr1, 0x92); + __m256i g0 = _mm256_blend_epi32(_mm256_blend_epi32(s02_high, s02_low, 0x92), bgr1, 0x24); + __m256i r0 = _mm256_blend_epi32(_mm256_blend_epi32(bgr1, s02_low, 0x24), s02_high, 0x92); + + b0 = _mm256_shuffle_epi32(b0, 0x6c); + g0 = _mm256_shuffle_epi32(g0, 0xb1); + r0 = _mm256_shuffle_epi32(r0, 0xc6); + + a = v_uint32x8(b0); + b = v_uint32x8(g0); + c = v_uint32x8(r0); +} + +inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 4)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 8)); + + __m256i s01 = _mm256_blend_epi32(bgr0, bgr1, 0xf0); + __m256i s12 = _mm256_blend_epi32(bgr1, bgr2, 0xf0); + __m256i s20r = _mm256_permute4x64_epi64(_mm256_blend_epi32(bgr2, bgr0, 0xf0), 0x1b); + __m256i b0 = _mm256_unpacklo_epi64(s01, s20r); + __m256i g0 = _mm256_alignr_epi8(s12, s01, 8); + __m256i r0 = _mm256_unpackhi_epi64(s20r, s12); + + a = v_uint64x4(b0); + b = v_uint64x4(g0); + c = v_uint64x4(r0); +} + +inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c, v_uint8x32& d ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 32)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 64)); + __m256i bgr3 = _mm256_loadu_si256((const __m256i*)(ptr + 96)); + const __m256i sh = _mm256_setr_epi8(0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15, + 0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15); + + __m256i p0 = _mm256_shuffle_epi8(bgr0, sh); + __m256i p1 = _mm256_shuffle_epi8(bgr1, sh); + __m256i p2 = _mm256_shuffle_epi8(bgr2, sh); + __m256i p3 = _mm256_shuffle_epi8(bgr3, sh); + + __m256i p01l = _mm256_unpacklo_epi32(p0, p1); + __m256i p01h = _mm256_unpackhi_epi32(p0, p1); + __m256i p23l = _mm256_unpacklo_epi32(p2, p3); + __m256i p23h = _mm256_unpackhi_epi32(p2, p3); + + __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16); + __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16); + __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16); + __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16); + + __m256i b0 = _mm256_unpacklo_epi32(pll, plh); + __m256i g0 = _mm256_unpackhi_epi32(pll, plh); + __m256i r0 = _mm256_unpacklo_epi32(phl, phh); + __m256i a0 = _mm256_unpackhi_epi32(phl, phh); + + a = v_uint8x32(b0); + b = v_uint8x32(g0); + c = v_uint8x32(r0); + d = v_uint8x32(a0); +} + +inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c, v_uint16x16& d ) +{ + __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 16)); + __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 32)); + __m256i bgr3 = _mm256_loadu_si256((const __m256i*)(ptr + 48)); + const __m256i sh = _mm256_setr_epi8(0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15, + 0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15); + __m256i p0 = _mm256_shuffle_epi8(bgr0, sh); + __m256i p1 = _mm256_shuffle_epi8(bgr1, sh); + __m256i p2 = _mm256_shuffle_epi8(bgr2, sh); + __m256i p3 = _mm256_shuffle_epi8(bgr3, sh); + + __m256i p01l = _mm256_unpacklo_epi32(p0, p1); + __m256i p01h = _mm256_unpackhi_epi32(p0, p1); + __m256i p23l = _mm256_unpacklo_epi32(p2, p3); + __m256i p23h = _mm256_unpackhi_epi32(p2, p3); + + __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16); + __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16); + __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16); + __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16); + + __m256i b0 = _mm256_unpacklo_epi32(pll, plh); + __m256i g0 = _mm256_unpackhi_epi32(pll, plh); + __m256i r0 = _mm256_unpacklo_epi32(phl, phh); + __m256i a0 = _mm256_unpackhi_epi32(phl, phh); + + a = v_uint16x16(b0); + b = v_uint16x16(g0); + c = v_uint16x16(r0); + d = v_uint16x16(a0); +} + +inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c, v_uint32x8& d ) +{ + __m256i p0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i p1 = _mm256_loadu_si256((const __m256i*)(ptr + 8)); + __m256i p2 = _mm256_loadu_si256((const __m256i*)(ptr + 16)); + __m256i p3 = _mm256_loadu_si256((const __m256i*)(ptr + 24)); + + __m256i p01l = _mm256_unpacklo_epi32(p0, p1); + __m256i p01h = _mm256_unpackhi_epi32(p0, p1); + __m256i p23l = _mm256_unpacklo_epi32(p2, p3); + __m256i p23h = _mm256_unpackhi_epi32(p2, p3); + + __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16); + __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16); + __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16); + __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16); + + __m256i b0 = _mm256_unpacklo_epi32(pll, plh); + __m256i g0 = _mm256_unpackhi_epi32(pll, plh); + __m256i r0 = _mm256_unpacklo_epi32(phl, phh); + __m256i a0 = _mm256_unpackhi_epi32(phl, phh); + + a = v_uint32x8(b0); + b = v_uint32x8(g0); + c = v_uint32x8(r0); + d = v_uint32x8(a0); +} + +inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c, v_uint64x4& d ) +{ + __m256i bgra0 = _mm256_loadu_si256((const __m256i*)ptr); + __m256i bgra1 = _mm256_loadu_si256((const __m256i*)(ptr + 4)); + __m256i bgra2 = _mm256_loadu_si256((const __m256i*)(ptr + 8)); + __m256i bgra3 = _mm256_loadu_si256((const __m256i*)(ptr + 12)); + + __m256i l02 = _mm256_permute2x128_si256(bgra0, bgra2, 0 + 2*16); + __m256i h02 = _mm256_permute2x128_si256(bgra0, bgra2, 1 + 3*16); + __m256i l13 = _mm256_permute2x128_si256(bgra1, bgra3, 0 + 2*16); + __m256i h13 = _mm256_permute2x128_si256(bgra1, bgra3, 1 + 3*16); + + __m256i b0 = _mm256_unpacklo_epi64(l02, l13); + __m256i g0 = _mm256_unpackhi_epi64(l02, l13); + __m256i r0 = _mm256_unpacklo_epi64(h02, h13); + __m256i a0 = _mm256_unpackhi_epi64(h02, h13); + + a = v_uint64x4(b0); + b = v_uint64x4(g0); + c = v_uint64x4(r0); + d = v_uint64x4(a0); +} + +///////////////////////////// store interleave ///////////////////////////////////// + +inline void v_store_interleave( uchar* ptr, const v_uint8x32& x, const v_uint8x32& y, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i xy_l = _mm256_unpacklo_epi8(x.val, y.val); + __m256i xy_h = _mm256_unpackhi_epi8(x.val, y.val); + + __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16); + __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, xy0); + _mm256_stream_si256((__m256i*)(ptr + 32), xy1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, xy0); + _mm256_store_si256((__m256i*)(ptr + 32), xy1); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, xy0); + _mm256_storeu_si256((__m256i*)(ptr + 32), xy1); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x16& x, const v_uint16x16& y, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i xy_l = _mm256_unpacklo_epi16(x.val, y.val); + __m256i xy_h = _mm256_unpackhi_epi16(x.val, y.val); + + __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16); + __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, xy0); + _mm256_stream_si256((__m256i*)(ptr + 16), xy1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, xy0); + _mm256_store_si256((__m256i*)(ptr + 16), xy1); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, xy0); + _mm256_storeu_si256((__m256i*)(ptr + 16), xy1); + } +} + +inline void v_store_interleave( unsigned* ptr, const v_uint32x8& x, const v_uint32x8& y, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i xy_l = _mm256_unpacklo_epi32(x.val, y.val); + __m256i xy_h = _mm256_unpackhi_epi32(x.val, y.val); + + __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16); + __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, xy0); + _mm256_stream_si256((__m256i*)(ptr + 8), xy1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, xy0); + _mm256_store_si256((__m256i*)(ptr + 8), xy1); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, xy0); + _mm256_storeu_si256((__m256i*)(ptr + 8), xy1); + } +} + +inline void v_store_interleave( uint64* ptr, const v_uint64x4& x, const v_uint64x4& y, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i xy_l = _mm256_unpacklo_epi64(x.val, y.val); + __m256i xy_h = _mm256_unpackhi_epi64(x.val, y.val); + + __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16); + __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, xy0); + _mm256_stream_si256((__m256i*)(ptr + 4), xy1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, xy0); + _mm256_store_si256((__m256i*)(ptr + 4), xy1); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, xy0); + _mm256_storeu_si256((__m256i*)(ptr + 4), xy1); + } +} + +inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b, const v_uint8x32& c, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + const __m256i sh_b = _mm256_setr_epi8( + 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5, + 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5); + const __m256i sh_g = _mm256_setr_epi8( + 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, + 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10); + const __m256i sh_r = _mm256_setr_epi8( + 10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, + 10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15); + + __m256i b0 = _mm256_shuffle_epi8(a.val, sh_b); + __m256i g0 = _mm256_shuffle_epi8(b.val, sh_g); + __m256i r0 = _mm256_shuffle_epi8(c.val, sh_r); + + const __m256i m0 = _mm256_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, + 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0); + const __m256i m1 = _mm256_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, + 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0); + + __m256i p0 = _mm256_blendv_epi8(_mm256_blendv_epi8(b0, g0, m0), r0, m1); + __m256i p1 = _mm256_blendv_epi8(_mm256_blendv_epi8(g0, r0, m0), b0, m1); + __m256i p2 = _mm256_blendv_epi8(_mm256_blendv_epi8(r0, b0, m0), g0, m1); + + __m256i bgr0 = _mm256_permute2x128_si256(p0, p1, 0 + 2*16); + __m256i bgr1 = _mm256_permute2x128_si256(p2, p0, 0 + 3*16); + __m256i bgr2 = _mm256_permute2x128_si256(p1, p2, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgr0); + _mm256_stream_si256((__m256i*)(ptr + 32), bgr1); + _mm256_stream_si256((__m256i*)(ptr + 64), bgr2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgr0); + _mm256_store_si256((__m256i*)(ptr + 32), bgr1); + _mm256_store_si256((__m256i*)(ptr + 64), bgr2); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgr0); + _mm256_storeu_si256((__m256i*)(ptr + 32), bgr1); + _mm256_storeu_si256((__m256i*)(ptr + 64), bgr2); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b, const v_uint16x16& c, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + const __m256i sh_b = _mm256_setr_epi8( + 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11, + 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11); + const __m256i sh_g = _mm256_setr_epi8( + 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, + 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5); + const __m256i sh_r = _mm256_setr_epi8( + 4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, + 4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15); + + __m256i b0 = _mm256_shuffle_epi8(a.val, sh_b); + __m256i g0 = _mm256_shuffle_epi8(b.val, sh_g); + __m256i r0 = _mm256_shuffle_epi8(c.val, sh_r); + + const __m256i m0 = _mm256_setr_epi8(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, + 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0); + const __m256i m1 = _mm256_setr_epi8(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, + -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0); + + __m256i p0 = _mm256_blendv_epi8(_mm256_blendv_epi8(b0, g0, m0), r0, m1); + __m256i p1 = _mm256_blendv_epi8(_mm256_blendv_epi8(g0, r0, m0), b0, m1); + __m256i p2 = _mm256_blendv_epi8(_mm256_blendv_epi8(r0, b0, m0), g0, m1); + + __m256i bgr0 = _mm256_permute2x128_si256(p0, p2, 0 + 2*16); + //__m256i bgr1 = p1; + __m256i bgr2 = _mm256_permute2x128_si256(p0, p2, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgr0); + _mm256_stream_si256((__m256i*)(ptr + 16), p1); + _mm256_stream_si256((__m256i*)(ptr + 32), bgr2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgr0); + _mm256_store_si256((__m256i*)(ptr + 16), p1); + _mm256_store_si256((__m256i*)(ptr + 32), bgr2); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgr0); + _mm256_storeu_si256((__m256i*)(ptr + 16), p1); + _mm256_storeu_si256((__m256i*)(ptr + 32), bgr2); + } +} + +inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b, const v_uint32x8& c, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i b0 = _mm256_shuffle_epi32(a.val, 0x6c); + __m256i g0 = _mm256_shuffle_epi32(b.val, 0xb1); + __m256i r0 = _mm256_shuffle_epi32(c.val, 0xc6); + + __m256i p0 = _mm256_blend_epi32(_mm256_blend_epi32(b0, g0, 0x92), r0, 0x24); + __m256i p1 = _mm256_blend_epi32(_mm256_blend_epi32(g0, r0, 0x92), b0, 0x24); + __m256i p2 = _mm256_blend_epi32(_mm256_blend_epi32(r0, b0, 0x92), g0, 0x24); + + __m256i bgr0 = _mm256_permute2x128_si256(p0, p1, 0 + 2*16); + //__m256i bgr1 = p2; + __m256i bgr2 = _mm256_permute2x128_si256(p0, p1, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgr0); + _mm256_stream_si256((__m256i*)(ptr + 8), p2); + _mm256_stream_si256((__m256i*)(ptr + 16), bgr2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgr0); + _mm256_store_si256((__m256i*)(ptr + 8), p2); + _mm256_store_si256((__m256i*)(ptr + 16), bgr2); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgr0); + _mm256_storeu_si256((__m256i*)(ptr + 8), p2); + _mm256_storeu_si256((__m256i*)(ptr + 16), bgr2); + } +} + +inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i s01 = _mm256_unpacklo_epi64(a.val, b.val); + __m256i s12 = _mm256_unpackhi_epi64(b.val, c.val); + __m256i s20 = _mm256_blend_epi32(c.val, a.val, 0xcc); + + __m256i bgr0 = _mm256_permute2x128_si256(s01, s20, 0 + 2*16); + __m256i bgr1 = _mm256_blend_epi32(s01, s12, 0x0f); + __m256i bgr2 = _mm256_permute2x128_si256(s20, s12, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgr0); + _mm256_stream_si256((__m256i*)(ptr + 4), bgr1); + _mm256_stream_si256((__m256i*)(ptr + 8), bgr2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgr0); + _mm256_store_si256((__m256i*)(ptr + 4), bgr1); + _mm256_store_si256((__m256i*)(ptr + 8), bgr2); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgr0); + _mm256_storeu_si256((__m256i*)(ptr + 4), bgr1); + _mm256_storeu_si256((__m256i*)(ptr + 8), bgr2); + } +} + +inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b, + const v_uint8x32& c, const v_uint8x32& d, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i bg0 = _mm256_unpacklo_epi8(a.val, b.val); + __m256i bg1 = _mm256_unpackhi_epi8(a.val, b.val); + __m256i ra0 = _mm256_unpacklo_epi8(c.val, d.val); + __m256i ra1 = _mm256_unpackhi_epi8(c.val, d.val); + + __m256i bgra0_ = _mm256_unpacklo_epi16(bg0, ra0); + __m256i bgra1_ = _mm256_unpackhi_epi16(bg0, ra0); + __m256i bgra2_ = _mm256_unpacklo_epi16(bg1, ra1); + __m256i bgra3_ = _mm256_unpackhi_epi16(bg1, ra1); + + __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16); + __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16); + __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16); + __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgra0); + _mm256_stream_si256((__m256i*)(ptr + 32), bgra1); + _mm256_stream_si256((__m256i*)(ptr + 64), bgra2); + _mm256_stream_si256((__m256i*)(ptr + 96), bgra3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgra0); + _mm256_store_si256((__m256i*)(ptr + 32), bgra1); + _mm256_store_si256((__m256i*)(ptr + 64), bgra2); + _mm256_store_si256((__m256i*)(ptr + 96), bgra3); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgra0); + _mm256_storeu_si256((__m256i*)(ptr + 32), bgra1); + _mm256_storeu_si256((__m256i*)(ptr + 64), bgra2); + _mm256_storeu_si256((__m256i*)(ptr + 96), bgra3); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b, + const v_uint16x16& c, const v_uint16x16& d, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i bg0 = _mm256_unpacklo_epi16(a.val, b.val); + __m256i bg1 = _mm256_unpackhi_epi16(a.val, b.val); + __m256i ra0 = _mm256_unpacklo_epi16(c.val, d.val); + __m256i ra1 = _mm256_unpackhi_epi16(c.val, d.val); + + __m256i bgra0_ = _mm256_unpacklo_epi32(bg0, ra0); + __m256i bgra1_ = _mm256_unpackhi_epi32(bg0, ra0); + __m256i bgra2_ = _mm256_unpacklo_epi32(bg1, ra1); + __m256i bgra3_ = _mm256_unpackhi_epi32(bg1, ra1); + + __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16); + __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16); + __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16); + __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgra0); + _mm256_stream_si256((__m256i*)(ptr + 16), bgra1); + _mm256_stream_si256((__m256i*)(ptr + 32), bgra2); + _mm256_stream_si256((__m256i*)(ptr + 48), bgra3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgra0); + _mm256_store_si256((__m256i*)(ptr + 16), bgra1); + _mm256_store_si256((__m256i*)(ptr + 32), bgra2); + _mm256_store_si256((__m256i*)(ptr + 48), bgra3); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgra0); + _mm256_storeu_si256((__m256i*)(ptr + 16), bgra1); + _mm256_storeu_si256((__m256i*)(ptr + 32), bgra2); + _mm256_storeu_si256((__m256i*)(ptr + 48), bgra3); + } +} + +inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b, + const v_uint32x8& c, const v_uint32x8& d, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i bg0 = _mm256_unpacklo_epi32(a.val, b.val); + __m256i bg1 = _mm256_unpackhi_epi32(a.val, b.val); + __m256i ra0 = _mm256_unpacklo_epi32(c.val, d.val); + __m256i ra1 = _mm256_unpackhi_epi32(c.val, d.val); + + __m256i bgra0_ = _mm256_unpacklo_epi64(bg0, ra0); + __m256i bgra1_ = _mm256_unpackhi_epi64(bg0, ra0); + __m256i bgra2_ = _mm256_unpacklo_epi64(bg1, ra1); + __m256i bgra3_ = _mm256_unpackhi_epi64(bg1, ra1); + + __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16); + __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16); + __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16); + __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgra0); + _mm256_stream_si256((__m256i*)(ptr + 8), bgra1); + _mm256_stream_si256((__m256i*)(ptr + 16), bgra2); + _mm256_stream_si256((__m256i*)(ptr + 24), bgra3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgra0); + _mm256_store_si256((__m256i*)(ptr + 8), bgra1); + _mm256_store_si256((__m256i*)(ptr + 16), bgra2); + _mm256_store_si256((__m256i*)(ptr + 24), bgra3); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgra0); + _mm256_storeu_si256((__m256i*)(ptr + 8), bgra1); + _mm256_storeu_si256((__m256i*)(ptr + 16), bgra2); + _mm256_storeu_si256((__m256i*)(ptr + 24), bgra3); + } +} + +inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b, + const v_uint64x4& c, const v_uint64x4& d, + hal::StoreMode mode=hal::STORE_UNALIGNED ) +{ + __m256i bg0 = _mm256_unpacklo_epi64(a.val, b.val); + __m256i bg1 = _mm256_unpackhi_epi64(a.val, b.val); + __m256i ra0 = _mm256_unpacklo_epi64(c.val, d.val); + __m256i ra1 = _mm256_unpackhi_epi64(c.val, d.val); + + __m256i bgra0 = _mm256_permute2x128_si256(bg0, ra0, 0 + 2*16); + __m256i bgra1 = _mm256_permute2x128_si256(bg1, ra1, 0 + 2*16); + __m256i bgra2 = _mm256_permute2x128_si256(bg0, ra0, 1 + 3*16); + __m256i bgra3 = _mm256_permute2x128_si256(bg1, ra1, 1 + 3*16); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm256_stream_si256((__m256i*)ptr, bgra0); + _mm256_stream_si256((__m256i*)(ptr + 4), bgra1); + _mm256_stream_si256((__m256i*)(ptr + 8), bgra2); + _mm256_stream_si256((__m256i*)(ptr + 12), bgra3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm256_store_si256((__m256i*)ptr, bgra0); + _mm256_store_si256((__m256i*)(ptr + 4), bgra1); + _mm256_store_si256((__m256i*)(ptr + 8), bgra2); + _mm256_store_si256((__m256i*)(ptr + 12), bgra3); + } + else + { + _mm256_storeu_si256((__m256i*)ptr, bgra0); + _mm256_storeu_si256((__m256i*)(ptr + 4), bgra1); + _mm256_storeu_si256((__m256i*)(ptr + 8), bgra2); + _mm256_storeu_si256((__m256i*)(ptr + 12), bgra3); + } +} + +#define OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \ +{ \ + _Tpvec1 a1, b1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ +} \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \ +{ \ + _Tpvec1 a1, b1, c1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ + c0 = v_reinterpret_as_##suffix0(c1); \ +} \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \ +{ \ + _Tpvec1 a1, b1, c1, d1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ + c0 = v_reinterpret_as_##suffix0(c1); \ + d0 = v_reinterpret_as_##suffix0(d1); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \ + hal::StoreMode mode=hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, mode); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, const _Tpvec0& c0, \ + hal::StoreMode mode=hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \ + const _Tpvec0& c0, const _Tpvec0& d0, \ + hal::StoreMode mode=hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \ + _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \ +} + +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int8x32, schar, s8, v_uint8x32, uchar, u8) +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int16x16, short, s16, v_uint16x16, ushort, u16) +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int32x8, int, s32, v_uint32x8, unsigned, u32) +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_float32x8, float, f32, v_uint32x8, unsigned, u32) +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int64x4, int64, s64, v_uint64x4, uint64, u64) +OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_float64x4, double, f64, v_uint64x4, uint64, u64) + +// FP16 +inline v_float32x8 v256_load_expand(const float16_t* ptr) +{ + return v_float32x8(_mm256_cvtph_ps(_mm_loadu_si128((const __m128i*)ptr))); +} + +inline void v_pack_store(float16_t* ptr, const v_float32x8& a) +{ + __m128i ah = _mm256_cvtps_ph(a.val, 0); + _mm_storeu_si128((__m128i*)ptr, ah); +} + +inline void v256_cleanup() { _mm256_zeroall(); } + +//! @name Check SIMD256 support +//! @{ +//! @brief Check CPU capability of SIMD operation +static inline bool hasSIMD256() +{ + return (CV_CPU_HAS_SUPPORT_AVX2) ? true : false; +} +//! @} + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} // cv:: + +#endif // OPENCV_HAL_INTRIN_AVX_HPP diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_cpp.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_cpp.hpp new file mode 100644 index 00000000..757c67b3 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_cpp.hpp @@ -0,0 +1,2382 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_INTRIN_CPP_HPP +#define OPENCV_HAL_INTRIN_CPP_HPP + +#include +#include +#include +#include "opencv2/core/saturate.hpp" + +namespace cv +{ + +#ifndef CV_DOXYGEN +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN +#endif + +/** @addtogroup core_hal_intrin + +"Universal intrinsics" is a types and functions set intended to simplify vectorization of code on +different platforms. Currently there are two supported SIMD extensions: __SSE/SSE2__ on x86 +architectures and __NEON__ on ARM architectures, both allow working with 128 bit registers +containing packed values of different types. In case when there is no SIMD extension available +during compilation, fallback C++ implementation of intrinsics will be chosen and code will work as +expected although it could be slower. + +### Types + +There are several types representing 128-bit register as a vector of packed values, each type is +implemented as a structure based on a one SIMD register. + +- cv::v_uint8x16 and cv::v_int8x16: sixteen 8-bit integer values (unsigned/signed) - char +- cv::v_uint16x8 and cv::v_int16x8: eight 16-bit integer values (unsigned/signed) - short +- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsgined/signed) - int +- cv::v_uint64x2 and cv::v_int64x2: two 64-bit integer values (unsigned/signed) - int64 +- cv::v_float32x4: four 32-bit floating point values (signed) - float +- cv::v_float64x2: two 64-bit floating point valies (signed) - double + +@note +cv::v_float64x2 is not implemented in NEON variant, if you want to use this type, don't forget to +check the CV_SIMD128_64F preprocessor definition: +@code +#if CV_SIMD128_64F +//... +#endif +@endcode + +### Load and store operations + +These operations allow to set contents of the register explicitly or by loading it from some memory +block and to save contents of the register to memory block. + +- Constructors: +@ref v_reg::v_reg(const _Tp *ptr) "from memory", +@ref v_reg::v_reg(_Tp s0, _Tp s1) "from two values", ... +- Other create methods: +@ref v_setall_s8, @ref v_setall_u8, ..., +@ref v_setzero_u8, @ref v_setzero_s8, ... +- Memory operations: +@ref v_load, @ref v_load_aligned, @ref v_load_low, @ref v_load_halves, +@ref v_store, @ref v_store_aligned, +@ref v_store_high, @ref v_store_low + +### Value reordering + +These operations allow to reorder or recombine elements in one or multiple vectors. + +- Interleave, deinterleave (2, 3 and 4 channels): @ref v_load_deinterleave, @ref v_store_interleave +- Expand: @ref v_load_expand, @ref v_load_expand_q, @ref v_expand, @ref v_expand_low, @ref v_expand_high +- Pack: @ref v_pack, @ref v_pack_u, @ref v_pack_b, @ref v_rshr_pack, @ref v_rshr_pack_u, +@ref v_pack_store, @ref v_pack_u_store, @ref v_rshr_pack_store, @ref v_rshr_pack_u_store +- Recombine: @ref v_zip, @ref v_recombine, @ref v_combine_low, @ref v_combine_high +- Extract: @ref v_extract + + +### Arithmetic, bitwise and comparison operations + +Element-wise binary and unary operations. + +- Arithmetics: +@ref operator +(const v_reg &a, const v_reg &b) "+", +@ref operator -(const v_reg &a, const v_reg &b) "-", +@ref operator *(const v_reg &a, const v_reg &b) "*", +@ref operator /(const v_reg &a, const v_reg &b) "/", +@ref v_mul_expand + +- Non-saturating arithmetics: @ref v_add_wrap, @ref v_sub_wrap + +- Bitwise shifts: +@ref operator <<(const v_reg &a, int s) "<<", +@ref operator >>(const v_reg &a, int s) ">>", +@ref v_shl, @ref v_shr + +- Bitwise logic: +@ref operator&(const v_reg &a, const v_reg &b) "&", +@ref operator |(const v_reg &a, const v_reg &b) "|", +@ref operator ^(const v_reg &a, const v_reg &b) "^", +@ref operator ~(const v_reg &a) "~" + +- Comparison: +@ref operator >(const v_reg &a, const v_reg &b) ">", +@ref operator >=(const v_reg &a, const v_reg &b) ">=", +@ref operator <(const v_reg &a, const v_reg &b) "<", +@ref operator <=(const v_reg &a, const v_reg &b) "<=", +@ref operator==(const v_reg &a, const v_reg &b) "==", +@ref operator !=(const v_reg &a, const v_reg &b) "!=" + +- min/max: @ref v_min, @ref v_max + +### Reduce and mask + +Most of these operations return only one value. + +- Reduce: @ref v_reduce_min, @ref v_reduce_max, @ref v_reduce_sum, @ref v_popcount +- Mask: @ref v_signmask, @ref v_check_all, @ref v_check_any, @ref v_select + +### Other math + +- Some frequent operations: @ref v_sqrt, @ref v_invsqrt, @ref v_magnitude, @ref v_sqr_magnitude +- Absolute values: @ref v_abs, @ref v_absdiff, @ref v_absdiffs + +### Conversions + +Different type conversions and casts: + +- Rounding: @ref v_round, @ref v_floor, @ref v_ceil, @ref v_trunc, +- To float: @ref v_cvt_f32, @ref v_cvt_f64 +- Reinterpret: @ref v_reinterpret_as_u8, @ref v_reinterpret_as_s8, ... + +### Matrix operations + +In these operations vectors represent matrix rows/columns: @ref v_dotprod, @ref v_matmul, @ref v_transpose4x4 + +### Usability + +Most operations are implemented only for some subset of the available types, following matrices +shows the applicability of different operations to the types. + +Regular integers: + +| Operations\\Types | uint 8x16 | int 8x16 | uint 16x8 | int 16x8 | uint 32x4 | int 32x4 | +|-------------------|:-:|:-:|:-:|:-:|:-:|:-:| +|load, store | x | x | x | x | x | x | +|interleave | x | x | x | x | x | x | +|expand | x | x | x | x | x | x | +|expand_low | x | x | x | x | x | x | +|expand_high | x | x | x | x | x | x | +|expand_q | x | x | | | | | +|add, sub | x | x | x | x | x | x | +|add_wrap, sub_wrap | x | x | x | x | | | +|mul_wrap | x | x | x | x | | | +|mul | x | x | x | x | x | x | +|mul_expand | x | x | x | x | x | | +|compare | x | x | x | x | x | x | +|shift | | | x | x | x | x | +|dotprod | | | | x | | | +|logical | x | x | x | x | x | x | +|min, max | x | x | x | x | x | x | +|absdiff | x | x | x | x | x | x | +|absdiffs | | x | | x | | | +|reduce | | | | | x | x | +|mask | x | x | x | x | x | x | +|pack | x | x | x | x | x | x | +|pack_u | x | | x | | | | +|pack_b | x | | | | | | +|unpack | x | x | x | x | x | x | +|extract | x | x | x | x | x | x | +|rotate (lanes) | x | x | x | x | x | x | +|cvt_flt32 | | | | | | x | +|cvt_flt64 | | | | | | x | +|transpose4x4 | | | | | x | x | + +Big integers: + +| Operations\\Types | uint 64x2 | int 64x2 | +|-------------------|:-:|:-:| +|load, store | x | x | +|add, sub | x | x | +|shift | x | x | +|logical | x | x | +|extract | x | x | +|rotate (lanes) | x | x | + +Floating point: + +| Operations\\Types | float 32x4 | float 64x2 | +|-------------------|:-:|:-:| +|load, store | x | x | +|interleave | x | | +|add, sub | x | x | +|mul | x | x | +|div | x | x | +|compare | x | x | +|min, max | x | x | +|absdiff | x | x | +|reduce | x | | +|mask | x | x | +|unpack | x | x | +|cvt_flt32 | | x | +|cvt_flt64 | x | | +|sqrt, abs | x | x | +|float math | x | x | +|transpose4x4 | x | | +|extract | x | x | +|rotate (lanes) | x | x | + + @{ */ + +template struct v_reg +{ +//! @cond IGNORED + typedef _Tp lane_type; + enum { nlanes = n }; +// !@endcond + + /** @brief Constructor + + Initializes register with data from memory + @param ptr pointer to memory block with data for register */ + explicit v_reg(const _Tp* ptr) { for( int i = 0; i < n; i++ ) s[i] = ptr[i]; } + + /** @brief Constructor + + Initializes register with two 64-bit values */ + v_reg(_Tp s0, _Tp s1) { s[0] = s0; s[1] = s1; } + + /** @brief Constructor + + Initializes register with four 32-bit values */ + v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3) { s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; } + + /** @brief Constructor + + Initializes register with eight 16-bit values */ + v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3, + _Tp s4, _Tp s5, _Tp s6, _Tp s7) + { + s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; + s[4] = s4; s[5] = s5; s[6] = s6; s[7] = s7; + } + + /** @brief Constructor + + Initializes register with sixteen 8-bit values */ + v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3, + _Tp s4, _Tp s5, _Tp s6, _Tp s7, + _Tp s8, _Tp s9, _Tp s10, _Tp s11, + _Tp s12, _Tp s13, _Tp s14, _Tp s15) + { + s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; + s[4] = s4; s[5] = s5; s[6] = s6; s[7] = s7; + s[8] = s8; s[9] = s9; s[10] = s10; s[11] = s11; + s[12] = s12; s[13] = s13; s[14] = s14; s[15] = s15; + } + + /** @brief Default constructor + + Does not initialize anything*/ + v_reg() {} + + /** @brief Copy constructor */ + v_reg(const v_reg<_Tp, n> & r) + { + for( int i = 0; i < n; i++ ) + s[i] = r.s[i]; + } + /** @brief Access first value + + Returns value of the first lane according to register type, for example: + @code{.cpp} + v_int32x4 r(1, 2, 3, 4); + int v = r.get0(); // returns 1 + v_uint64x2 r(1, 2); + uint64_t v = r.get0(); // returns 1 + @endcode + */ + _Tp get0() const { return s[0]; } + +//! @cond IGNORED + _Tp get(const int i) const { return s[i]; } + v_reg<_Tp, n> high() const + { + v_reg<_Tp, n> c; + int i; + for( i = 0; i < n/2; i++ ) + { + c.s[i] = s[i+(n/2)]; + c.s[i+(n/2)] = 0; + } + return c; + } + + static v_reg<_Tp, n> zero() + { + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = (_Tp)0; + return c; + } + + static v_reg<_Tp, n> all(_Tp s) + { + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = s; + return c; + } + + template v_reg<_Tp2, n2> reinterpret_as() const + { + size_t bytes = std::min(sizeof(_Tp2)*n2, sizeof(_Tp)*n); + v_reg<_Tp2, n2> c; + std::memcpy(&c.s[0], &s[0], bytes); + return c; + } + + _Tp s[n]; +//! @endcond +}; + +/** @brief Sixteen 8-bit unsigned integer values */ +typedef v_reg v_uint8x16; +/** @brief Sixteen 8-bit signed integer values */ +typedef v_reg v_int8x16; +/** @brief Eight 16-bit unsigned integer values */ +typedef v_reg v_uint16x8; +/** @brief Eight 16-bit signed integer values */ +typedef v_reg v_int16x8; +/** @brief Four 32-bit unsigned integer values */ +typedef v_reg v_uint32x4; +/** @brief Four 32-bit signed integer values */ +typedef v_reg v_int32x4; +/** @brief Four 32-bit floating point values (single precision) */ +typedef v_reg v_float32x4; +/** @brief Two 64-bit floating point values (double precision) */ +typedef v_reg v_float64x2; +/** @brief Two 64-bit unsigned integer values */ +typedef v_reg v_uint64x2; +/** @brief Two 64-bit signed integer values */ +typedef v_reg v_int64x2; + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_BIN_OP(bin_op) \ +template inline v_reg<_Tp, n> \ + operator bin_op (const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + v_reg<_Tp, n> c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = saturate_cast<_Tp>(a.s[i] bin_op b.s[i]); \ + return c; \ +} \ +template inline v_reg<_Tp, n>& \ + operator bin_op##= (v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + for( int i = 0; i < n; i++ ) \ + a.s[i] = saturate_cast<_Tp>(a.s[i] bin_op b.s[i]); \ + return a; \ +} + +/** @brief Add values + +For all types. */ +OPENCV_HAL_IMPL_BIN_OP(+) + +/** @brief Subtract values + +For all types. */ +OPENCV_HAL_IMPL_BIN_OP(-) + +/** @brief Multiply values + +For 16- and 32-bit integer types and floating types. */ +OPENCV_HAL_IMPL_BIN_OP(*) + +/** @brief Divide values + +For floating types only. */ +OPENCV_HAL_IMPL_BIN_OP(/) + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_BIT_OP(bit_op) \ +template inline v_reg<_Tp, n> operator bit_op \ + (const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + v_reg<_Tp, n> c; \ + typedef typename V_TypeTraits<_Tp>::int_type itype; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int((itype)(V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) bit_op \ + V_TypeTraits<_Tp>::reinterpret_int(b.s[i]))); \ + return c; \ +} \ +template inline v_reg<_Tp, n>& operator \ + bit_op##= (v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + typedef typename V_TypeTraits<_Tp>::int_type itype; \ + for( int i = 0; i < n; i++ ) \ + a.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int((itype)(V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) bit_op \ + V_TypeTraits<_Tp>::reinterpret_int(b.s[i]))); \ + return a; \ +} + +/** @brief Bitwise AND + +Only for integer types. */ +OPENCV_HAL_IMPL_BIT_OP(&) + +/** @brief Bitwise OR + +Only for integer types. */ +OPENCV_HAL_IMPL_BIT_OP(|) + +/** @brief Bitwise XOR + +Only for integer types.*/ +OPENCV_HAL_IMPL_BIT_OP(^) + +/** @brief Bitwise NOT + +Only for integer types.*/ +template inline v_reg<_Tp, n> operator ~ (const v_reg<_Tp, n>& a) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int(~V_TypeTraits<_Tp>::reinterpret_int(a.s[i])); + } + return c; +} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_MATH_FUNC(func, cfunc, _Tp2) \ +template inline v_reg<_Tp2, n> func(const v_reg<_Tp, n>& a) \ +{ \ + v_reg<_Tp2, n> c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = cfunc(a.s[i]); \ + return c; \ +} + +/** @brief Square root of elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_sqrt, std::sqrt, _Tp) + +//! @cond IGNORED +OPENCV_HAL_IMPL_MATH_FUNC(v_sin, std::sin, _Tp) +OPENCV_HAL_IMPL_MATH_FUNC(v_cos, std::cos, _Tp) +OPENCV_HAL_IMPL_MATH_FUNC(v_exp, std::exp, _Tp) +OPENCV_HAL_IMPL_MATH_FUNC(v_log, std::log, _Tp) +//! @endcond + +/** @brief Absolute value of elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_abs, (typename V_TypeTraits<_Tp>::abs_type)std::abs, + typename V_TypeTraits<_Tp>::abs_type) + +/** @brief Round elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_round, cvRound, int) + +/** @brief Floor elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_floor, cvFloor, int) + +/** @brief Ceil elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_ceil, cvCeil, int) + +/** @brief Truncate elements + +Only for floating point types.*/ +OPENCV_HAL_IMPL_MATH_FUNC(v_trunc, int, int) + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_MINMAX_FUNC(func, cfunc) \ +template inline v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + v_reg<_Tp, n> c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = cfunc(a.s[i], b.s[i]); \ + return c; \ +} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(func, cfunc) \ +template inline _Tp func(const v_reg<_Tp, n>& a) \ +{ \ + _Tp c = a.s[0]; \ + for( int i = 1; i < n; i++ ) \ + c = cfunc(c, a.s[i]); \ + return c; \ +} + +/** @brief Choose min values for each pair + +Scheme: +@code +{A1 A2 ...} +{B1 B2 ...} +-------------- +{min(A1,B1) min(A2,B2) ...} +@endcode +For all types except 64-bit integer. */ +OPENCV_HAL_IMPL_MINMAX_FUNC(v_min, std::min) + +/** @brief Choose max values for each pair + +Scheme: +@code +{A1 A2 ...} +{B1 B2 ...} +-------------- +{max(A1,B1) max(A2,B2) ...} +@endcode +For all types except 64-bit integer. */ +OPENCV_HAL_IMPL_MINMAX_FUNC(v_max, std::max) + +/** @brief Find one min value + +Scheme: +@code +{A1 A2 A3 ...} => min(A1,A2,A3,...) +@endcode +For 32-bit integer and 32-bit floating point types. */ +OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(v_reduce_min, std::min) + +/** @brief Find one max value + +Scheme: +@code +{A1 A2 A3 ...} => max(A1,A2,A3,...) +@endcode +For 32-bit integer and 32-bit floating point types. */ +OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(v_reduce_max, std::max) + +static const unsigned char popCountTable[] = +{ + 0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8, +}; +/** @brief Count the 1 bits in the vector and return 4 values + +Scheme: +@code +{A1 A2 A3 ...} => popcount(A1) +@endcode +Any types but result will be in v_uint32x4*/ +template inline v_uint32x4 v_popcount(const v_reg<_Tp, n>& a) +{ + v_uint8x16 b; + b = v_reinterpret_as_u8(a); + for( int i = 0; i < v_uint8x16::nlanes; i++ ) + { + b.s[i] = popCountTable[b.s[i]]; + } + v_uint32x4 c; + for( int i = 0; i < v_uint32x4::nlanes; i++ ) + { + c.s[i] = b.s[i*4] + b.s[i*4+1] + b.s[i*4+2] + b.s[i*4+3]; + } + return c; +} + + +//! @cond IGNORED +template +inline void v_minmax( const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, + v_reg<_Tp, n>& minval, v_reg<_Tp, n>& maxval ) +{ + for( int i = 0; i < n; i++ ) + { + minval.s[i] = std::min(a.s[i], b.s[i]); + maxval.s[i] = std::max(a.s[i], b.s[i]); + } +} +//! @endcond + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_CMP_OP(cmp_op) \ +template \ +inline v_reg<_Tp, n> operator cmp_op(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + typedef typename V_TypeTraits<_Tp>::int_type itype; \ + v_reg<_Tp, n> c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int((itype)-(int)(a.s[i] cmp_op b.s[i])); \ + return c; \ +} + +/** @brief Less-than comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(<) + +/** @brief Greater-than comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(>) + +/** @brief Less-than or equal comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(<=) + +/** @brief Greater-than or equal comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(>=) + +/** @brief Equal comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(==) + +/** @brief Not equal comparison + +For all types except 64-bit integer values. */ +OPENCV_HAL_IMPL_CMP_OP(!=) + +template +inline v_reg v_not_nan(const v_reg& a) +{ + typedef typename V_TypeTraits::int_type itype; + v_reg c; + for (int i = 0; i < n; i++) + c.s[i] = V_TypeTraits::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i])); + return c; +} +template +inline v_reg v_not_nan(const v_reg& a) +{ + typedef typename V_TypeTraits::int_type itype; + v_reg c; + for (int i = 0; i < n; i++) + c.s[i] = V_TypeTraits::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i])); + return c; +} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_ARITHM_OP(func, bin_op, cast_op, _Tp2) \ +template \ +inline v_reg<_Tp2, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + typedef _Tp2 rtype; \ + v_reg c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = cast_op(a.s[i] bin_op b.s[i]); \ + return c; \ +} + +/** @brief Add values without saturation + +For 8- and 16-bit integer values. */ +OPENCV_HAL_IMPL_ARITHM_OP(v_add_wrap, +, (_Tp), _Tp) + +/** @brief Subtract values without saturation + +For 8- and 16-bit integer values. */ +OPENCV_HAL_IMPL_ARITHM_OP(v_sub_wrap, -, (_Tp), _Tp) + +/** @brief Multiply values without saturation + +For 8- and 16-bit integer values. */ +OPENCV_HAL_IMPL_ARITHM_OP(v_mul_wrap, *, (_Tp), _Tp) + +//! @cond IGNORED +template inline T _absdiff(T a, T b) +{ + return a > b ? a - b : b - a; +} +//! @endcond + +/** @brief Absolute difference + +Returns \f$ |a - b| \f$ converted to corresponding unsigned type. +Example: +@code{.cpp} +v_int32x4 a, b; // {1, 2, 3, 4} and {4, 3, 2, 1} +v_uint32x4 c = v_absdiff(a, b); // result is {3, 1, 1, 3} +@endcode +For 8-, 16-, 32-bit integer source types. */ +template +inline v_reg::abs_type, n> v_absdiff(const v_reg<_Tp, n>& a, const v_reg<_Tp, n> & b) +{ + typedef typename V_TypeTraits<_Tp>::abs_type rtype; + v_reg c; + const rtype mask = (rtype)(std::numeric_limits<_Tp>::is_signed ? (1 << (sizeof(rtype)*8 - 1)) : 0); + for( int i = 0; i < n; i++ ) + { + rtype ua = a.s[i] ^ mask; + rtype ub = b.s[i] ^ mask; + c.s[i] = _absdiff(ua, ub); + } + return c; +} + +/** @overload + +For 32-bit floating point values */ +inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b) +{ + v_float32x4 c; + for( int i = 0; i < c.nlanes; i++ ) + c.s[i] = _absdiff(a.s[i], b.s[i]); + return c; +} + +/** @overload + +For 64-bit floating point values */ +inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b) +{ + v_float64x2 c; + for( int i = 0; i < c.nlanes; i++ ) + c.s[i] = _absdiff(a.s[i], b.s[i]); + return c; +} + +/** @brief Saturating absolute difference + +Returns \f$ saturate(|a - b|) \f$ . +For 8-, 16-bit signed integer source types. */ +template +inline v_reg<_Tp, n> v_absdiffs(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++) + c.s[i] = saturate_cast<_Tp>(std::abs(a.s[i] - b.s[i])); + return c; +} + +/** @brief Inversed square root + +Returns \f$ 1/sqrt(a) \f$ +For floating point types only. */ +template +inline v_reg<_Tp, n> v_invsqrt(const v_reg<_Tp, n>& a) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = 1.f/std::sqrt(a.s[i]); + return c; +} + +/** @brief Magnitude + +Returns \f$ sqrt(a^2 + b^2) \f$ +For floating point types only. */ +template +inline v_reg<_Tp, n> v_magnitude(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = std::sqrt(a.s[i]*a.s[i] + b.s[i]*b.s[i]); + return c; +} + +/** @brief Square of the magnitude + +Returns \f$ a^2 + b^2 \f$ +For floating point types only. */ +template +inline v_reg<_Tp, n> v_sqr_magnitude(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = a.s[i]*a.s[i] + b.s[i]*b.s[i]; + return c; +} + +/** @brief Multiply and add + + Returns \f$ a*b + c \f$ + For floating point types and signed 32bit int only. */ +template +inline v_reg<_Tp, n> v_fma(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, + const v_reg<_Tp, n>& c) +{ + v_reg<_Tp, n> d; + for( int i = 0; i < n; i++ ) + d.s[i] = a.s[i]*b.s[i] + c.s[i]; + return d; +} + +/** @brief A synonym for v_fma */ +template +inline v_reg<_Tp, n> v_muladd(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, + const v_reg<_Tp, n>& c) +{ + return v_fma(a, b, c); +} + +/** @brief Dot product of elements + +Multiply values in two registers and sum adjacent result pairs. +Scheme: +@code + {A1 A2 ...} // 16-bit +x {B1 B2 ...} // 16-bit +------------- +{A1B1+A2B2 ...} // 32-bit +@endcode +Implemented only for 16-bit signed source type (v_int16x8). +*/ +template inline v_reg::w_type, n/2> + v_dotprod(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + v_reg c; + for( int i = 0; i < (n/2); i++ ) + c.s[i] = (w_type)a.s[i*2]*b.s[i*2] + (w_type)a.s[i*2+1]*b.s[i*2+1]; + return c; +} + +/** @brief Dot product of elements + +Same as cv::v_dotprod, but add a third element to the sum of adjacent pairs. +Scheme: +@code + {A1 A2 ...} // 16-bit +x {B1 B2 ...} // 16-bit +------------- + {A1B1+A2B2+C1 ...} // 32-bit + +@endcode +Implemented only for 16-bit signed source type (v_int16x8). +*/ +template inline v_reg::w_type, n/2> + v_dotprod(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, const v_reg::w_type, n / 2>& c) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + v_reg s; + for( int i = 0; i < (n/2); i++ ) + s.s[i] = (w_type)a.s[i*2]*b.s[i*2] + (w_type)a.s[i*2+1]*b.s[i*2+1] + c.s[i]; + return s; +} + +/** @brief Multiply and expand + +Multiply values two registers and store results in two registers with wider pack type. +Scheme: +@code + {A B C D} // 32-bit +x {E F G H} // 32-bit +--------------- +{AE BF} // 64-bit + {CG DH} // 64-bit +@endcode +Example: +@code{.cpp} +v_uint32x4 a, b; // {1,2,3,4} and {2,2,2,2} +v_uint64x2 c, d; // results +v_mul_expand(a, b, c, d); // c, d = {2,4}, {6, 8} +@endcode +Implemented only for 16- and unsigned 32-bit source types (v_int16x8, v_uint16x8, v_uint32x4). +*/ +template inline void v_mul_expand(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, + v_reg::w_type, n/2>& c, + v_reg::w_type, n/2>& d) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + for( int i = 0; i < (n/2); i++ ) + { + c.s[i] = (w_type)a.s[i]*b.s[i]; + d.s[i] = (w_type)a.s[i+(n/2)]*b.s[i+(n/2)]; + } +} + +/** @brief Multiply and extract high part + +Multiply values two registers and store high part of the results. +Implemented only for 16-bit source types (v_int16x8, v_uint16x8). Returns \f$ a*b >> 16 \f$ +*/ +template inline v_reg<_Tp, n> v_mul_hi(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + v_reg<_Tp, n> c; + for (int i = 0; i < n; i++) + c.s[i] = (_Tp)(((w_type)a.s[i] * b.s[i]) >> sizeof(_Tp)*8); + return c; +} + +//! @cond IGNORED +template inline void v_hsum(const v_reg<_Tp, n>& a, + v_reg::w_type, n/2>& c) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + for( int i = 0; i < (n/2); i++ ) + { + c.s[i] = (w_type)a.s[i*2] + a.s[i*2+1]; + } +} +//! @endcond + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_SHIFT_OP(shift_op) \ +template inline v_reg<_Tp, n> operator shift_op(const v_reg<_Tp, n>& a, int imm) \ +{ \ + v_reg<_Tp, n> c; \ + for( int i = 0; i < n; i++ ) \ + c.s[i] = (_Tp)(a.s[i] shift_op imm); \ + return c; \ +} + +/** @brief Bitwise shift left + +For 16-, 32- and 64-bit integer values. */ +OPENCV_HAL_IMPL_SHIFT_OP(<< ) + +/** @brief Bitwise shift right + +For 16-, 32- and 64-bit integer values. */ +OPENCV_HAL_IMPL_SHIFT_OP(>> ) + +/** @brief Element shift left among vector + +For all type */ +#define OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(suffix,opA,opB) \ +template inline v_reg<_Tp, n> v_rotate_##suffix(const v_reg<_Tp, n>& a) \ +{ \ + v_reg<_Tp, n> b; \ + for (int i = 0; i < n; i++) \ + { \ + int sIndex = i opA imm; \ + if (0 <= sIndex && sIndex < n) \ + { \ + b.s[i] = a.s[sIndex]; \ + } \ + else \ + { \ + b.s[i] = 0; \ + } \ + } \ + return b; \ +} \ +template inline v_reg<_Tp, n> v_rotate_##suffix(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \ +{ \ + v_reg<_Tp, n> c; \ + for (int i = 0; i < n; i++) \ + { \ + int aIndex = i opA imm; \ + int bIndex = i opA imm opB n; \ + if (0 <= bIndex && bIndex < n) \ + { \ + c.s[i] = b.s[bIndex]; \ + } \ + else if (0 <= aIndex && aIndex < n) \ + { \ + c.s[i] = a.s[aIndex]; \ + } \ + else \ + { \ + c.s[i] = 0; \ + } \ + } \ + return c; \ +} + +OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(left, -, +) +OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(right, +, -) + +/** @brief Sum packed values + +Scheme: +@code +{A1 A2 A3 ...} => sum{A1,A2,A3,...} +@endcode +For 32-bit integer and 32-bit floating point types.*/ +template inline typename V_TypeTraits<_Tp>::sum_type v_reduce_sum(const v_reg<_Tp, n>& a) +{ + typename V_TypeTraits<_Tp>::sum_type c = a.s[0]; + for( int i = 1; i < n; i++ ) + c += a.s[i]; + return c; +} + +/** @brief Sums all elements of each input vector, returns the vector of sums + + Scheme: + @code + result[0] = a[0] + a[1] + a[2] + a[3] + result[1] = b[0] + b[1] + b[2] + b[3] + result[2] = c[0] + c[1] + c[2] + c[3] + result[3] = d[0] + d[1] + d[2] + d[3] + @endcode +*/ +inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, const v_float32x4& d) +{ + v_float32x4 r; + r.s[0] = a.s[0] + a.s[1] + a.s[2] + a.s[3]; + r.s[1] = b.s[0] + b.s[1] + b.s[2] + b.s[3]; + r.s[2] = c.s[0] + c.s[1] + c.s[2] + c.s[3]; + r.s[3] = d.s[0] + d.s[1] + d.s[2] + d.s[3]; + return r; +} + +/** @brief Sum absolute differences of values + +Scheme: +@code +{A1 A2 A3 ...} {B1 B2 B3 ...} => sum{ABS(A1-B1),abs(A2-B2),abs(A3-B3),...} +@endcode +For all types except 64-bit types.*/ +template inline typename V_TypeTraits< typename V_TypeTraits<_Tp>::abs_type >::sum_type v_reduce_sad(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + typename V_TypeTraits< typename V_TypeTraits<_Tp>::abs_type >::sum_type c = _absdiff(a.s[0], b.s[0]); + for (int i = 1; i < n; i++) + c += _absdiff(a.s[i], b.s[i]); + return c; +} + +/** @brief Get negative values mask + +Returned value is a bit mask with bits set to 1 on places corresponding to negative packed values indexes. +Example: +@code{.cpp} +v_int32x4 r; // set to {-1, -1, 1, 1} +int mask = v_signmask(r); // mask = 3 <== 00000000 00000000 00000000 00000011 +@endcode +For all types except 64-bit. */ +template inline int v_signmask(const v_reg<_Tp, n>& a) +{ + int mask = 0; + for( int i = 0; i < n; i++ ) + mask |= (V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) < 0) << i; + return mask; +} + +/** @brief Check if all packed values are less than zero + +Unsigned values will be casted to signed: `uchar 254 => char -2`. +For all types except 64-bit. */ +template inline bool v_check_all(const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < n; i++ ) + if( V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) >= 0 ) + return false; + return true; +} + +/** @brief Check if any of packed values is less than zero + +Unsigned values will be casted to signed: `uchar 254 => char -2`. +For all types except 64-bit. */ +template inline bool v_check_any(const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < n; i++ ) + if( V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) < 0 ) + return true; + return false; +} + +/** @brief Per-element select (blend operation) + +Return value will be built by combining values _a_ and _b_ using the following scheme: + result[i] = mask[i] ? a[i] : b[i]; + +@note: _mask_ element values are restricted to these values: +- 0: select element from _b_ +- 0xff/0xffff/etc: select element from _a_ +(fully compatible with bitwise-based operator) +*/ +template inline v_reg<_Tp, n> v_select(const v_reg<_Tp, n>& mask, + const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + typedef V_TypeTraits<_Tp> Traits; + typedef typename Traits::int_type int_type; + v_reg<_Tp, n> c; + for( int i = 0; i < n; i++ ) + { + int_type m = Traits::reinterpret_int(mask.s[i]); + CV_DbgAssert(m == 0 || m == (~(int_type)0)); // restrict mask values: 0 or 0xff/0xffff/etc + c.s[i] = m ? a.s[i] : b.s[i]; + } + return c; +} + +/** @brief Expand values to the wider pack type + +Copy contents of register to two registers with 2x wider pack type. +Scheme: +@code + int32x4 int64x2 int64x2 +{A B C D} ==> {A B} , {C D} +@endcode */ +template inline void v_expand(const v_reg<_Tp, n>& a, + v_reg::w_type, n/2>& b0, + v_reg::w_type, n/2>& b1) +{ + for( int i = 0; i < (n/2); i++ ) + { + b0.s[i] = a.s[i]; + b1.s[i] = a.s[i+(n/2)]; + } +} + +/** @brief Expand lower values to the wider pack type + +Same as cv::v_expand, but return lower half of the vector. + +Scheme: +@code + int32x4 int64x2 +{A B C D} ==> {A B} +@endcode */ +template +inline v_reg::w_type, n/2> +v_expand_low(const v_reg<_Tp, n>& a) +{ + v_reg::w_type, n/2> b; + for( int i = 0; i < (n/2); i++ ) + b.s[i] = a.s[i]; + return b; +} + +/** @brief Expand higher values to the wider pack type + +Same as cv::v_expand_low, but expand higher half of the vector instead. + +Scheme: +@code + int32x4 int64x2 +{A B C D} ==> {C D} +@endcode */ +template +inline v_reg::w_type, n/2> +v_expand_high(const v_reg<_Tp, n>& a) +{ + v_reg::w_type, n/2> b; + for( int i = 0; i < (n/2); i++ ) + b.s[i] = a.s[i+(n/2)]; + return b; +} + +//! @cond IGNORED +template inline v_reg::int_type, n> + v_reinterpret_as_int(const v_reg<_Tp, n>& a) +{ + v_reg::int_type, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = V_TypeTraits<_Tp>::reinterpret_int(a.s[i]); + return c; +} + +template inline v_reg::uint_type, n> + v_reinterpret_as_uint(const v_reg<_Tp, n>& a) +{ + v_reg::uint_type, n> c; + for( int i = 0; i < n; i++ ) + c.s[i] = V_TypeTraits<_Tp>::reinterpret_uint(a.s[i]); + return c; +} +//! @endcond + +/** @brief Interleave two vectors + +Scheme: +@code + {A1 A2 A3 A4} + {B1 B2 B3 B4} +--------------- + {A1 B1 A2 B2} and {A3 B3 A4 B4} +@endcode +For all types except 64-bit. +*/ +template inline void v_zip( const v_reg<_Tp, n>& a0, const v_reg<_Tp, n>& a1, + v_reg<_Tp, n>& b0, v_reg<_Tp, n>& b1 ) +{ + int i; + for( i = 0; i < n/2; i++ ) + { + b0.s[i*2] = a0.s[i]; + b0.s[i*2+1] = a1.s[i]; + } + for( ; i < n; i++ ) + { + b1.s[i*2-n] = a0.s[i]; + b1.s[i*2-n+1] = a1.s[i]; + } +} + +/** @brief Load register contents from memory + +@param ptr pointer to memory block with data +@return register object + +@note Returned type will be detected from passed pointer type, for example uchar ==> cv::v_uint8x16, int ==> cv::v_int32x4, etc. + */ +template +inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_load(const _Tp* ptr) +{ + return v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128>(ptr); +} + +/** @brief Load register contents from memory (aligned) + +similar to cv::v_load, but source memory block should be aligned (to 16-byte boundary) + */ +template +inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_load_aligned(const _Tp* ptr) +{ + return v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128>(ptr); +} + +/** @brief Load 64-bits of data to lower part (high part is undefined). + +@param ptr memory block containing data for first half (0..n/2) + +@code{.cpp} +int lo[2] = { 1, 2 }; +v_int32x4 r = v_load_low(lo); +@endcode + */ +template +inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_load_low(const _Tp* ptr) +{ + v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> c; + for( int i = 0; i < c.nlanes/2; i++ ) + { + c.s[i] = ptr[i]; + } + return c; +} + +/** @brief Load register contents from two memory blocks + +@param loptr memory block containing data for first half (0..n/2) +@param hiptr memory block containing data for second half (n/2..n) + +@code{.cpp} +int lo[2] = { 1, 2 }, hi[2] = { 3, 4 }; +v_int32x4 r = v_load_halves(lo, hi); +@endcode + */ +template +inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_load_halves(const _Tp* loptr, const _Tp* hiptr) +{ + v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> c; + for( int i = 0; i < c.nlanes/2; i++ ) + { + c.s[i] = loptr[i]; + c.s[i+c.nlanes/2] = hiptr[i]; + } + return c; +} + +/** @brief Load register contents from memory with double expand + +Same as cv::v_load, but result pack type will be 2x wider than memory type. + +@code{.cpp} +short buf[4] = {1, 2, 3, 4}; // type is int16 +v_int32x4 r = v_load_expand(buf); // r = {1, 2, 3, 4} - type is int32 +@endcode +For 8-, 16-, 32-bit integer source types. */ +template +inline v_reg::w_type, V_TypeTraits<_Tp>::nlanes128 / 2> +v_load_expand(const _Tp* ptr) +{ + typedef typename V_TypeTraits<_Tp>::w_type w_type; + v_reg::nlanes128> c; + for( int i = 0; i < c.nlanes; i++ ) + { + c.s[i] = ptr[i]; + } + return c; +} + +/** @brief Load register contents from memory with quad expand + +Same as cv::v_load_expand, but result type is 4 times wider than source. +@code{.cpp} +char buf[4] = {1, 2, 3, 4}; // type is int8 +v_int32x4 r = v_load_q(buf); // r = {1, 2, 3, 4} - type is int32 +@endcode +For 8-bit integer source types. */ +template +inline v_reg::q_type, V_TypeTraits<_Tp>::nlanes128 / 4> +v_load_expand_q(const _Tp* ptr) +{ + typedef typename V_TypeTraits<_Tp>::q_type q_type; + v_reg::nlanes128> c; + for( int i = 0; i < c.nlanes; i++ ) + { + c.s[i] = ptr[i]; + } + return c; +} + +/** @brief Load and deinterleave (2 channels) + +Load data from memory deinterleave and store to 2 registers. +Scheme: +@code +{A1 B1 A2 B2 ...} ==> {A1 A2 ...}, {B1 B2 ...} +@endcode +For all types except 64-bit. */ +template inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a, + v_reg<_Tp, n>& b) +{ + int i, i2; + for( i = i2 = 0; i < n; i++, i2 += 2 ) + { + a.s[i] = ptr[i2]; + b.s[i] = ptr[i2+1]; + } +} + +/** @brief Load and deinterleave (3 channels) + +Load data from memory deinterleave and store to 3 registers. +Scheme: +@code +{A1 B1 C1 A2 B2 C2 ...} ==> {A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...} +@endcode +For all types except 64-bit. */ +template inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a, + v_reg<_Tp, n>& b, v_reg<_Tp, n>& c) +{ + int i, i3; + for( i = i3 = 0; i < n; i++, i3 += 3 ) + { + a.s[i] = ptr[i3]; + b.s[i] = ptr[i3+1]; + c.s[i] = ptr[i3+2]; + } +} + +/** @brief Load and deinterleave (4 channels) + +Load data from memory deinterleave and store to 4 registers. +Scheme: +@code +{A1 B1 C1 D1 A2 B2 C2 D2 ...} ==> {A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...}, {D1 D2 ...} +@endcode +For all types except 64-bit. */ +template +inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a, + v_reg<_Tp, n>& b, v_reg<_Tp, n>& c, + v_reg<_Tp, n>& d) +{ + int i, i4; + for( i = i4 = 0; i < n; i++, i4 += 4 ) + { + a.s[i] = ptr[i4]; + b.s[i] = ptr[i4+1]; + c.s[i] = ptr[i4+2]; + d.s[i] = ptr[i4+3]; + } +} + +/** @brief Interleave and store (2 channels) + +Interleave and store data from 2 registers to memory. +Scheme: +@code +{A1 A2 ...}, {B1 B2 ...} ==> {A1 B1 A2 B2 ...} +@endcode +For all types except 64-bit. */ +template +inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a, + const v_reg<_Tp, n>& b, + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) +{ + int i, i2; + for( i = i2 = 0; i < n; i++, i2 += 2 ) + { + ptr[i2] = a.s[i]; + ptr[i2+1] = b.s[i]; + } +} + +/** @brief Interleave and store (3 channels) + +Interleave and store data from 3 registers to memory. +Scheme: +@code +{A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...} ==> {A1 B1 C1 A2 B2 C2 ...} +@endcode +For all types except 64-bit. */ +template +inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a, + const v_reg<_Tp, n>& b, const v_reg<_Tp, n>& c, + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) +{ + int i, i3; + for( i = i3 = 0; i < n; i++, i3 += 3 ) + { + ptr[i3] = a.s[i]; + ptr[i3+1] = b.s[i]; + ptr[i3+2] = c.s[i]; + } +} + +/** @brief Interleave and store (4 channels) + +Interleave and store data from 4 registers to memory. +Scheme: +@code +{A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...}, {D1 D2 ...} ==> {A1 B1 C1 D1 A2 B2 C2 D2 ...} +@endcode +For all types except 64-bit. */ +template inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a, + const v_reg<_Tp, n>& b, const v_reg<_Tp, n>& c, + const v_reg<_Tp, n>& d, + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) +{ + int i, i4; + for( i = i4 = 0; i < n; i++, i4 += 4 ) + { + ptr[i4] = a.s[i]; + ptr[i4+1] = b.s[i]; + ptr[i4+2] = c.s[i]; + ptr[i4+3] = d.s[i]; + } +} + +/** @brief Store data to memory + +Store register contents to memory. +Scheme: +@code + REG {A B C D} ==> MEM {A B C D} +@endcode +Pointer can be unaligned. */ +template +inline void v_store(_Tp* ptr, const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < n; i++ ) + ptr[i] = a.s[i]; +} + +/** @brief Store data to memory (lower half) + +Store lower half of register contents to memory. +Scheme: +@code + REG {A B C D} ==> MEM {A B} +@endcode */ +template +inline void v_store_low(_Tp* ptr, const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < (n/2); i++ ) + ptr[i] = a.s[i]; +} + +/** @brief Store data to memory (higher half) + +Store higher half of register contents to memory. +Scheme: +@code + REG {A B C D} ==> MEM {C D} +@endcode */ +template +inline void v_store_high(_Tp* ptr, const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < (n/2); i++ ) + ptr[i] = a.s[i+(n/2)]; +} + +/** @brief Store data to memory (aligned) + +Store register contents to memory. +Scheme: +@code + REG {A B C D} ==> MEM {A B C D} +@endcode +Pointer __should__ be aligned by 16-byte boundary. */ +template +inline void v_store_aligned(_Tp* ptr, const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < n; i++ ) + ptr[i] = a.s[i]; +} + +template +inline void v_store_aligned_nocache(_Tp* ptr, const v_reg<_Tp, n>& a) +{ + for( int i = 0; i < n; i++ ) + ptr[i] = a.s[i]; +} + +template +inline void v_store_aligned(_Tp* ptr, const v_reg<_Tp, n>& a, hal::StoreMode /*mode*/) +{ + for( int i = 0; i < n; i++ ) + ptr[i] = a.s[i]; +} + +/** @brief Combine vector from first elements of two vectors + +Scheme: +@code + {A1 A2 A3 A4} + {B1 B2 B3 B4} +--------------- + {A1 A2 B1 B2} +@endcode +For all types except 64-bit. */ +template +inline v_reg<_Tp, n> v_combine_low(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < (n/2); i++ ) + { + c.s[i] = a.s[i]; + c.s[i+(n/2)] = b.s[i]; + } + return c; +} + +/** @brief Combine vector from last elements of two vectors + +Scheme: +@code + {A1 A2 A3 A4} + {B1 B2 B3 B4} +--------------- + {A3 A4 B3 B4} +@endcode +For all types except 64-bit. */ +template +inline v_reg<_Tp, n> v_combine_high(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> c; + for( int i = 0; i < (n/2); i++ ) + { + c.s[i] = a.s[i+(n/2)]; + c.s[i+(n/2)] = b.s[i+(n/2)]; + } + return c; +} + +/** @brief Combine two vectors from lower and higher parts of two other vectors + +@code{.cpp} +low = cv::v_combine_low(a, b); +high = cv::v_combine_high(a, b); +@endcode */ +template +inline void v_recombine(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b, + v_reg<_Tp, n>& low, v_reg<_Tp, n>& high) +{ + for( int i = 0; i < (n/2); i++ ) + { + low.s[i] = a.s[i]; + low.s[i+(n/2)] = b.s[i]; + high.s[i] = a.s[i+(n/2)]; + high.s[i+(n/2)] = b.s[i+(n/2)]; + } +} + +/** @brief Vector extract + +Scheme: +@code + {A1 A2 A3 A4} + {B1 B2 B3 B4} +======================== +shift = 1 {A2 A3 A4 B1} +shift = 2 {A3 A4 B1 B2} +shift = 3 {A4 B1 B2 B3} +@endcode +Restriction: 0 <= shift < nlanes + +Usage: +@code +v_int32x4 a, b, c; +c = v_extract<2>(a, b); +@endcode +For all types. */ +template +inline v_reg<_Tp, n> v_extract(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + v_reg<_Tp, n> r; + const int shift = n - s; + int i = 0; + for (; i < shift; ++i) + r.s[i] = a.s[i+s]; + for (; i < n; ++i) + r.s[i] = b.s[i-shift]; + return r; +} + +/** @brief Round + +Rounds each value. Input type is float vector ==> output type is int vector.*/ +template inline v_reg v_round(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = cvRound(a.s[i]); + return c; +} + +/** @overload */ +template inline v_reg v_round(const v_reg& a, const v_reg& b) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = cvRound(a.s[i]); + c.s[i+n] = cvRound(b.s[i]); + } + return c; +} + +/** @brief Floor + +Floor each value. Input type is float vector ==> output type is int vector.*/ +template inline v_reg v_floor(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = cvFloor(a.s[i]); + return c; +} + +/** @brief Ceil + +Ceil each value. Input type is float vector ==> output type is int vector.*/ +template inline v_reg v_ceil(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = cvCeil(a.s[i]); + return c; +} + +/** @brief Trunc + +Truncate each value. Input type is float vector ==> output type is int vector.*/ +template inline v_reg v_trunc(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = (int)(a.s[i]); + return c; +} + +/** @overload */ +template inline v_reg v_round(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = cvRound(a.s[i]); + c.s[i+n] = 0; + } + return c; +} + +/** @overload */ +template inline v_reg v_floor(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = cvFloor(a.s[i]); + c.s[i+n] = 0; + } + return c; +} + +/** @overload */ +template inline v_reg v_ceil(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = cvCeil(a.s[i]); + c.s[i+n] = 0; + } + return c; +} + +/** @overload */ +template inline v_reg v_trunc(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = cvCeil(a.s[i]); + c.s[i+n] = 0; + } + return c; +} + +/** @brief Convert to float + +Supported input type is cv::v_int32x4. */ +template inline v_reg v_cvt_f32(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = (float)a.s[i]; + return c; +} + +template inline v_reg v_cvt_f32(const v_reg& a, const v_reg& b) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + { + c.s[i] = (float)a.s[i]; + c.s[i+n] = (float)b.s[i]; + } + return c; +} + +/** @brief Convert to double + +Supported input type is cv::v_int32x4. */ +template inline v_reg v_cvt_f64(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = (double)a.s[i]; + return c; +} + +/** @brief Convert to double + +Supported input type is cv::v_float32x4. */ +template inline v_reg v_cvt_f64(const v_reg& a) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = (double)a.s[i]; + return c; +} + +template inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_lut(const _Tp* tab, const int* idx) +{ + v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> c; + for (int i = 0; i < V_TypeTraits<_Tp>::nlanes128; i++) + c.s[i] = tab[idx[i]]; + return c; +} +template inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_lut_pairs(const _Tp* tab, const int* idx) +{ + v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> c; + for (int i = 0; i < V_TypeTraits<_Tp>::nlanes128; i++) + c.s[i] = tab[idx[i / 2] + i % 2]; + return c; +} +template inline v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> v_lut_quads(const _Tp* tab, const int* idx) +{ + v_reg<_Tp, V_TypeTraits<_Tp>::nlanes128> c; + for (int i = 0; i < V_TypeTraits<_Tp>::nlanes128; i++) + c.s[i] = tab[idx[i / 4] + i % 4]; + return c; +} + +template inline v_reg v_lut(const int* tab, const v_reg& idx) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = tab[idx.s[i]]; + return c; +} + +template inline v_reg v_lut(const unsigned* tab, const v_reg& idx) +{ + v_reg c; + for (int i = 0; i < n; i++) + c.s[i] = tab[idx.s[i]]; + return c; +} + +template inline v_reg v_lut(const float* tab, const v_reg& idx) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = tab[idx.s[i]]; + return c; +} + +template inline v_reg v_lut(const double* tab, const v_reg& idx) +{ + v_reg c; + for( int i = 0; i < n; i++ ) + c.s[i] = tab[idx.s[i]]; + return c; +} + +template inline void v_lut_deinterleave(const float* tab, const v_reg& idx, + v_reg& x, v_reg& y) +{ + for( int i = 0; i < n; i++ ) + { + int j = idx.s[i]; + x.s[i] = tab[j]; + y.s[i] = tab[j+1]; + } +} + +template inline void v_lut_deinterleave(const double* tab, const v_reg& idx, + v_reg& x, v_reg& y) +{ + for( int i = 0; i < n; i++ ) + { + int j = idx.s[i]; + x.s[i] = tab[j]; + y.s[i] = tab[j+1]; + } +} + +template inline v_reg<_Tp, n> v_interleave_pairs(const v_reg<_Tp, n>& vec) +{ + v_reg c; + for (int i = 0; i < n/4; i++) + { + c.s[4*i ] = vec.s[4*i ]; + c.s[4*i+1] = vec.s[4*i+2]; + c.s[4*i+2] = vec.s[4*i+1]; + c.s[4*i+3] = vec.s[4*i+3]; + } + return c; +} + +template inline v_reg<_Tp, n> v_interleave_quads(const v_reg<_Tp, n>& vec) +{ + v_reg c; + for (int i = 0; i < n/8; i++) + { + c.s[8*i ] = vec.s[8*i ]; + c.s[8*i+1] = vec.s[8*i+4]; + c.s[8*i+2] = vec.s[8*i+1]; + c.s[8*i+3] = vec.s[8*i+5]; + c.s[8*i+4] = vec.s[8*i+2]; + c.s[8*i+5] = vec.s[8*i+6]; + c.s[8*i+6] = vec.s[8*i+3]; + c.s[8*i+7] = vec.s[8*i+7]; + } + return c; +} + +template inline v_reg<_Tp, n> v_pack_triplets(const v_reg<_Tp, n>& vec) +{ + v_reg c; + for (int i = 0; i < n/4; i++) + { + c.s[3*i ] = vec.s[4*i ]; + c.s[3*i+1] = vec.s[4*i+1]; + c.s[3*i+2] = vec.s[4*i+2]; + } + return c; +} + +/** @brief Transpose 4x4 matrix + +Scheme: +@code +a0 {A1 A2 A3 A4} +a1 {B1 B2 B3 B4} +a2 {C1 C2 C3 C4} +a3 {D1 D2 D3 D4} +=============== +b0 {A1 B1 C1 D1} +b1 {A2 B2 C2 D2} +b2 {A3 B3 C3 D3} +b3 {A4 B4 C4 D4} +@endcode +*/ +template +inline void v_transpose4x4( v_reg<_Tp, 4>& a0, const v_reg<_Tp, 4>& a1, + const v_reg<_Tp, 4>& a2, const v_reg<_Tp, 4>& a3, + v_reg<_Tp, 4>& b0, v_reg<_Tp, 4>& b1, + v_reg<_Tp, 4>& b2, v_reg<_Tp, 4>& b3 ) +{ + b0 = v_reg<_Tp, 4>(a0.s[0], a1.s[0], a2.s[0], a3.s[0]); + b1 = v_reg<_Tp, 4>(a0.s[1], a1.s[1], a2.s[1], a3.s[1]); + b2 = v_reg<_Tp, 4>(a0.s[2], a1.s[2], a2.s[2], a3.s[2]); + b3 = v_reg<_Tp, 4>(a0.s[3], a1.s[3], a2.s[3], a3.s[3]); +} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_INIT_ZERO(_Tpvec, _Tp, suffix) \ +inline _Tpvec v_setzero_##suffix() { return _Tpvec::zero(); } + +//! @name Init with zero +//! @{ +//! @brief Create new vector with zero elements +OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint8x16, uchar, u8) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_int8x16, schar, s8) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint16x8, ushort, u16) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_int16x8, short, s16) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_int32x4, int, s32) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_float32x4, float, f32) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_float64x2, double, f64) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint64x2, uint64, u64) +OPENCV_HAL_IMPL_C_INIT_ZERO(v_int64x2, int64, s64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_INIT_VAL(_Tpvec, _Tp, suffix) \ +inline _Tpvec v_setall_##suffix(_Tp val) { return _Tpvec::all(val); } + +//! @name Init with value +//! @{ +//! @brief Create new vector with elements set to a specific value +OPENCV_HAL_IMPL_C_INIT_VAL(v_uint8x16, uchar, u8) +OPENCV_HAL_IMPL_C_INIT_VAL(v_int8x16, schar, s8) +OPENCV_HAL_IMPL_C_INIT_VAL(v_uint16x8, ushort, u16) +OPENCV_HAL_IMPL_C_INIT_VAL(v_int16x8, short, s16) +OPENCV_HAL_IMPL_C_INIT_VAL(v_uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_C_INIT_VAL(v_int32x4, int, s32) +OPENCV_HAL_IMPL_C_INIT_VAL(v_float32x4, float, f32) +OPENCV_HAL_IMPL_C_INIT_VAL(v_float64x2, double, f64) +OPENCV_HAL_IMPL_C_INIT_VAL(v_uint64x2, uint64, u64) +OPENCV_HAL_IMPL_C_INIT_VAL(v_int64x2, int64, s64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_REINTERPRET(_Tpvec, _Tp, suffix) \ +template inline _Tpvec \ + v_reinterpret_as_##suffix(const v_reg<_Tp0, n0>& a) \ +{ return a.template reinterpret_as<_Tp, _Tpvec::nlanes>(); } + +//! @name Reinterpret +//! @{ +//! @brief Convert vector to different type without modifying underlying data. +OPENCV_HAL_IMPL_C_REINTERPRET(v_uint8x16, uchar, u8) +OPENCV_HAL_IMPL_C_REINTERPRET(v_int8x16, schar, s8) +OPENCV_HAL_IMPL_C_REINTERPRET(v_uint16x8, ushort, u16) +OPENCV_HAL_IMPL_C_REINTERPRET(v_int16x8, short, s16) +OPENCV_HAL_IMPL_C_REINTERPRET(v_uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_C_REINTERPRET(v_int32x4, int, s32) +OPENCV_HAL_IMPL_C_REINTERPRET(v_float32x4, float, f32) +OPENCV_HAL_IMPL_C_REINTERPRET(v_float64x2, double, f64) +OPENCV_HAL_IMPL_C_REINTERPRET(v_uint64x2, uint64, u64) +OPENCV_HAL_IMPL_C_REINTERPRET(v_int64x2, int64, s64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_SHIFTL(_Tpvec, _Tp) \ +template inline _Tpvec v_shl(const _Tpvec& a) \ +{ return a << n; } + +//! @name Left shift +//! @{ +//! @brief Shift left +OPENCV_HAL_IMPL_C_SHIFTL(v_uint16x8, ushort) +OPENCV_HAL_IMPL_C_SHIFTL(v_int16x8, short) +OPENCV_HAL_IMPL_C_SHIFTL(v_uint32x4, unsigned) +OPENCV_HAL_IMPL_C_SHIFTL(v_int32x4, int) +OPENCV_HAL_IMPL_C_SHIFTL(v_uint64x2, uint64) +OPENCV_HAL_IMPL_C_SHIFTL(v_int64x2, int64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_SHIFTR(_Tpvec, _Tp) \ +template inline _Tpvec v_shr(const _Tpvec& a) \ +{ return a >> n; } + +//! @name Right shift +//! @{ +//! @brief Shift right +OPENCV_HAL_IMPL_C_SHIFTR(v_uint16x8, ushort) +OPENCV_HAL_IMPL_C_SHIFTR(v_int16x8, short) +OPENCV_HAL_IMPL_C_SHIFTR(v_uint32x4, unsigned) +OPENCV_HAL_IMPL_C_SHIFTR(v_int32x4, int) +OPENCV_HAL_IMPL_C_SHIFTR(v_uint64x2, uint64) +OPENCV_HAL_IMPL_C_SHIFTR(v_int64x2, int64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_RSHIFTR(_Tpvec, _Tp) \ +template inline _Tpvec v_rshr(const _Tpvec& a) \ +{ \ + _Tpvec c; \ + for( int i = 0; i < _Tpvec::nlanes; i++ ) \ + c.s[i] = (_Tp)((a.s[i] + ((_Tp)1 << (n - 1))) >> n); \ + return c; \ +} + +//! @name Rounding shift +//! @{ +//! @brief Rounding shift right +OPENCV_HAL_IMPL_C_RSHIFTR(v_uint16x8, ushort) +OPENCV_HAL_IMPL_C_RSHIFTR(v_int16x8, short) +OPENCV_HAL_IMPL_C_RSHIFTR(v_uint32x4, unsigned) +OPENCV_HAL_IMPL_C_RSHIFTR(v_int32x4, int) +OPENCV_HAL_IMPL_C_RSHIFTR(v_uint64x2, uint64) +OPENCV_HAL_IMPL_C_RSHIFTR(v_int64x2, int64) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_PACK(_Tpvec, _Tpnvec, _Tpn, pack_suffix, cast) \ +inline _Tpnvec v_##pack_suffix(const _Tpvec& a, const _Tpvec& b) \ +{ \ + _Tpnvec c; \ + for( int i = 0; i < _Tpvec::nlanes; i++ ) \ + { \ + c.s[i] = cast<_Tpn>(a.s[i]); \ + c.s[i+_Tpvec::nlanes] = cast<_Tpn>(b.s[i]); \ + } \ + return c; \ +} + +//! @name Pack +//! @{ +//! @brief Pack values from two vectors to one +//! +//! Return vector type have twice more elements than input vector types. Variant with _u_ suffix also +//! converts to corresponding unsigned type. +//! +//! - pack: for 16-, 32- and 64-bit integer input types +//! - pack_u: for 16- and 32-bit signed integer input types +//! +//! @note All variants except 64-bit use saturation. +OPENCV_HAL_IMPL_C_PACK(v_uint16x8, v_uint8x16, uchar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK(v_int16x8, v_int8x16, schar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK(v_uint32x4, v_uint16x8, ushort, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK(v_int32x4, v_int16x8, short, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK(v_uint64x2, v_uint32x4, unsigned, pack, static_cast) +OPENCV_HAL_IMPL_C_PACK(v_int64x2, v_int32x4, int, pack, static_cast) +OPENCV_HAL_IMPL_C_PACK(v_int16x8, v_uint8x16, uchar, pack_u, saturate_cast) +OPENCV_HAL_IMPL_C_PACK(v_int32x4, v_uint16x8, ushort, pack_u, saturate_cast) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_RSHR_PACK(_Tpvec, _Tp, _Tpnvec, _Tpn, pack_suffix, cast) \ +template inline _Tpnvec v_rshr_##pack_suffix(const _Tpvec& a, const _Tpvec& b) \ +{ \ + _Tpnvec c; \ + for( int i = 0; i < _Tpvec::nlanes; i++ ) \ + { \ + c.s[i] = cast<_Tpn>((a.s[i] + ((_Tp)1 << (n - 1))) >> n); \ + c.s[i+_Tpvec::nlanes] = cast<_Tpn>((b.s[i] + ((_Tp)1 << (n - 1))) >> n); \ + } \ + return c; \ +} + +//! @name Pack with rounding shift +//! @{ +//! @brief Pack values from two vectors to one with rounding shift +//! +//! Values from the input vectors will be shifted right by _n_ bits with rounding, converted to narrower +//! type and returned in the result vector. Variant with _u_ suffix converts to unsigned type. +//! +//! - pack: for 16-, 32- and 64-bit integer input types +//! - pack_u: for 16- and 32-bit signed integer input types +//! +//! @note All variants except 64-bit use saturation. +OPENCV_HAL_IMPL_C_RSHR_PACK(v_uint16x8, ushort, v_uint8x16, uchar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_int16x8, short, v_int8x16, schar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_uint32x4, unsigned, v_uint16x8, ushort, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_int32x4, int, v_int16x8, short, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_uint64x2, uint64, v_uint32x4, unsigned, pack, static_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_int64x2, int64, v_int32x4, int, pack, static_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_int16x8, short, v_uint8x16, uchar, pack_u, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK(v_int32x4, int, v_uint16x8, ushort, pack_u, saturate_cast) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_PACK_STORE(_Tpvec, _Tp, _Tpnvec, _Tpn, pack_suffix, cast) \ +inline void v_##pack_suffix##_store(_Tpn* ptr, const _Tpvec& a) \ +{ \ + for( int i = 0; i < _Tpvec::nlanes; i++ ) \ + ptr[i] = cast<_Tpn>(a.s[i]); \ +} + +//! @name Pack and store +//! @{ +//! @brief Store values from the input vector into memory with pack +//! +//! Values will be stored into memory with conversion to narrower type. +//! Variant with _u_ suffix converts to corresponding unsigned type. +//! +//! - pack: for 16-, 32- and 64-bit integer input types +//! - pack_u: for 16- and 32-bit signed integer input types +//! +//! @note All variants except 64-bit use saturation. +OPENCV_HAL_IMPL_C_PACK_STORE(v_uint16x8, ushort, v_uint8x16, uchar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_int16x8, short, v_int8x16, schar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_uint32x4, unsigned, v_uint16x8, ushort, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_int32x4, int, v_int16x8, short, pack, saturate_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_uint64x2, uint64, v_uint32x4, unsigned, pack, static_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_int64x2, int64, v_int32x4, int, pack, static_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_int16x8, short, v_uint8x16, uchar, pack_u, saturate_cast) +OPENCV_HAL_IMPL_C_PACK_STORE(v_int32x4, int, v_uint16x8, ushort, pack_u, saturate_cast) +//! @} + +//! @brief Helper macro +//! @ingroup core_hal_intrin_impl +#define OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(_Tpvec, _Tp, _Tpnvec, _Tpn, pack_suffix, cast) \ +template inline void v_rshr_##pack_suffix##_store(_Tpn* ptr, const _Tpvec& a) \ +{ \ + for( int i = 0; i < _Tpvec::nlanes; i++ ) \ + ptr[i] = cast<_Tpn>((a.s[i] + ((_Tp)1 << (n - 1))) >> n); \ +} + +//! @name Pack and store with rounding shift +//! @{ +//! @brief Store values from the input vector into memory with pack +//! +//! Values will be shifted _n_ bits right with rounding, converted to narrower type and stored into +//! memory. Variant with _u_ suffix converts to unsigned type. +//! +//! - pack: for 16-, 32- and 64-bit integer input types +//! - pack_u: for 16- and 32-bit signed integer input types +//! +//! @note All variants except 64-bit use saturation. +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_uint16x8, ushort, v_uint8x16, uchar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_int16x8, short, v_int8x16, schar, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_uint32x4, unsigned, v_uint16x8, ushort, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_int32x4, int, v_int16x8, short, pack, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_uint64x2, uint64, v_uint32x4, unsigned, pack, static_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_int64x2, int64, v_int32x4, int, pack, static_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_int16x8, short, v_uint8x16, uchar, pack_u, saturate_cast) +OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(v_int32x4, int, v_uint16x8, ushort, pack_u, saturate_cast) +//! @} + +//! @cond IGNORED +template +inline void _pack_b(_Tpm* mptr, const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) +{ + for (int i = 0; i < n; ++i) + { + mptr[i] = (_Tpm)a.s[i]; + mptr[i + n] = (_Tpm)b.s[i]; + } +} +//! @endcond + +//! @name Pack boolean values +//! @{ +//! @brief Pack boolean values from multiple vectors to one unsigned 8-bit integer vector +//! +//! @note Must provide valid boolean values to guarantee same result for all architectures. + +/** @brief +//! For 16-bit boolean values + +Scheme: +@code +a {0xFFFF 0 0 0xFFFF 0 0xFFFF 0xFFFF 0} +b {0xFFFF 0 0xFFFF 0 0 0xFFFF 0 0xFFFF} +=============== +{ + 0xFF 0 0 0xFF 0 0xFF 0xFF 0 + 0xFF 0 0xFF 0 0 0xFF 0 0xFF +} +@endcode */ + +inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b) +{ + v_uint8x16 mask; + _pack_b(mask.s, a, b); + return mask; +} + +/** @overload +For 32-bit boolean values + +Scheme: +@code +a {0xFFFF.. 0 0 0xFFFF..} +b {0 0xFFFF.. 0xFFFF.. 0} +c {0xFFFF.. 0 0xFFFF.. 0} +d {0 0xFFFF.. 0 0xFFFF..} +=============== +{ + 0xFF 0 0 0xFF 0 0xFF 0xFF 0 + 0xFF 0 0xFF 0 0 0xFF 0 0xFF +} +@endcode */ + +inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, const v_uint32x4& d) +{ + v_uint8x16 mask; + _pack_b(mask.s, a, b); + _pack_b(mask.s + 8, c, d); + return mask; +} + +/** @overload +For 64-bit boolean values + +Scheme: +@code +a {0xFFFF.. 0} +b {0 0xFFFF..} +c {0xFFFF.. 0} +d {0 0xFFFF..} + +e {0xFFFF.. 0} +f {0xFFFF.. 0} +g {0 0xFFFF..} +h {0 0xFFFF..} +=============== +{ + 0xFF 0 0 0xFF 0xFF 0 0 0xFF + 0xFF 0 0xFF 0 0 0xFF 0 0xFF +} +@endcode */ +inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c, + const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f, + const v_uint64x2& g, const v_uint64x2& h) +{ + v_uint8x16 mask; + _pack_b(mask.s, a, b); + _pack_b(mask.s + 4, c, d); + _pack_b(mask.s + 8, e, f); + _pack_b(mask.s + 12, g, h); + return mask; +} +//! @} + +/** @brief Matrix multiplication + +Scheme: +@code +{A0 A1 A2 A3} |V0| +{B0 B1 B2 B3} |V1| +{C0 C1 C2 C3} |V2| +{D0 D1 D2 D3} x |V3| +==================== +{R0 R1 R2 R3}, where: +R0 = A0V0 + A1V1 + A2V2 + A3V3, +R1 = B0V0 + B1V1 + B2V2 + B3V3 +... +@endcode +*/ +inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& m3) +{ + return v_float32x4(v.s[0]*m0.s[0] + v.s[1]*m1.s[0] + v.s[2]*m2.s[0] + v.s[3]*m3.s[0], + v.s[0]*m0.s[1] + v.s[1]*m1.s[1] + v.s[2]*m2.s[1] + v.s[3]*m3.s[1], + v.s[0]*m0.s[2] + v.s[1]*m1.s[2] + v.s[2]*m2.s[2] + v.s[3]*m3.s[2], + v.s[0]*m0.s[3] + v.s[1]*m1.s[3] + v.s[2]*m2.s[3] + v.s[3]*m3.s[3]); +} + +/** @brief Matrix multiplication and add + +Scheme: +@code +{A0 A1 A2 } |V0| |D0| +{B0 B1 B2 } |V1| |D1| +{C0 C1 C2 } x |V2| + |D2| +==================== +{R0 R1 R2 R3}, where: +R0 = A0V0 + A1V1 + A2V2 + D0, +R1 = B0V0 + B1V1 + B2V2 + D1 +... +@endcode +*/ +inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& m3) +{ + return v_float32x4(v.s[0]*m0.s[0] + v.s[1]*m1.s[0] + v.s[2]*m2.s[0] + m3.s[0], + v.s[0]*m0.s[1] + v.s[1]*m1.s[1] + v.s[2]*m2.s[1] + m3.s[1], + v.s[0]*m0.s[2] + v.s[1]*m1.s[2] + v.s[2]*m2.s[2] + m3.s[2], + v.s[0]*m0.s[3] + v.s[1]*m1.s[3] + v.s[2]*m2.s[3] + m3.s[3]); +} + +////// FP16 support /////// + +inline v_reg::nlanes128> +v_load_expand(const float16_t* ptr) +{ + v_reg::nlanes128> v; + for( int i = 0; i < v.nlanes; i++ ) + { + v.s[i] = ptr[i]; + } + return v; +} + +inline void +v_pack_store(float16_t* ptr, v_reg::nlanes128>& v) +{ + for( int i = 0; i < v.nlanes; i++ ) + { + ptr[i] = float16_t(v.s[i]); + } +} + +inline void v_cleanup() {} + +//! @} + +//! @name Check SIMD support +//! @{ +//! @brief Check CPU capability of SIMD operation +static inline bool hasSIMD128() +{ + return false; +} + +//! @} + +#ifndef CV_DOXYGEN +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END +#endif +} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_forward.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_forward.hpp new file mode 100644 index 00000000..46185529 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_forward.hpp @@ -0,0 +1,158 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +#ifndef CV__SIMD_FORWARD +#error "Need to pre-define forward width" +#endif + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +/** Types **/ +#if CV__SIMD_FORWARD == 512 +// [todo] 512 +#error "AVX512 Not implemented yet" +#elif CV__SIMD_FORWARD == 256 +// 256 +#define __CV_VX(fun) v256_##fun +#define __CV_V_UINT8 v_uint8x32 +#define __CV_V_INT8 v_int8x32 +#define __CV_V_UINT16 v_uint16x16 +#define __CV_V_INT16 v_int16x16 +#define __CV_V_UINT32 v_uint32x8 +#define __CV_V_INT32 v_int32x8 +#define __CV_V_UINT64 v_uint64x4 +#define __CV_V_INT64 v_int64x4 +#define __CV_V_FLOAT32 v_float32x8 +#define __CV_V_FLOAT64 v_float64x4 +struct v_uint8x32; +struct v_int8x32; +struct v_uint16x16; +struct v_int16x16; +struct v_uint32x8; +struct v_int32x8; +struct v_uint64x4; +struct v_int64x4; +struct v_float32x8; +struct v_float64x4; +#else +// 128 +#define __CV_VX(fun) v_##fun +#define __CV_V_UINT8 v_uint8x16 +#define __CV_V_INT8 v_int8x16 +#define __CV_V_UINT16 v_uint16x8 +#define __CV_V_INT16 v_int16x8 +#define __CV_V_UINT32 v_uint32x4 +#define __CV_V_INT32 v_int32x4 +#define __CV_V_UINT64 v_uint64x2 +#define __CV_V_INT64 v_int64x2 +#define __CV_V_FLOAT32 v_float32x4 +#define __CV_V_FLOAT64 v_float64x2 +struct v_uint8x16; +struct v_int8x16; +struct v_uint16x8; +struct v_int16x8; +struct v_uint32x4; +struct v_int32x4; +struct v_uint64x2; +struct v_int64x2; +struct v_float32x4; +struct v_float64x2; +#endif + +/** Value reordering **/ + +// Expansion +void v_expand(const __CV_V_UINT8&, __CV_V_UINT16&, __CV_V_UINT16&); +void v_expand(const __CV_V_INT8&, __CV_V_INT16&, __CV_V_INT16&); +void v_expand(const __CV_V_UINT16&, __CV_V_UINT32&, __CV_V_UINT32&); +void v_expand(const __CV_V_INT16&, __CV_V_INT32&, __CV_V_INT32&); +void v_expand(const __CV_V_UINT32&, __CV_V_UINT64&, __CV_V_UINT64&); +void v_expand(const __CV_V_INT32&, __CV_V_INT64&, __CV_V_INT64&); +// Low Expansion +__CV_V_UINT16 v_expand_low(const __CV_V_UINT8&); +__CV_V_INT16 v_expand_low(const __CV_V_INT8&); +__CV_V_UINT32 v_expand_low(const __CV_V_UINT16&); +__CV_V_INT32 v_expand_low(const __CV_V_INT16&); +__CV_V_UINT64 v_expand_low(const __CV_V_UINT32&); +__CV_V_INT64 v_expand_low(const __CV_V_INT32&); +// High Expansion +__CV_V_UINT16 v_expand_high(const __CV_V_UINT8&); +__CV_V_INT16 v_expand_high(const __CV_V_INT8&); +__CV_V_UINT32 v_expand_high(const __CV_V_UINT16&); +__CV_V_INT32 v_expand_high(const __CV_V_INT16&); +__CV_V_UINT64 v_expand_high(const __CV_V_UINT32&); +__CV_V_INT64 v_expand_high(const __CV_V_INT32&); +// Load & Low Expansion +__CV_V_UINT16 __CV_VX(load_expand)(const uchar*); +__CV_V_INT16 __CV_VX(load_expand)(const schar*); +__CV_V_UINT32 __CV_VX(load_expand)(const ushort*); +__CV_V_INT32 __CV_VX(load_expand)(const short*); +__CV_V_UINT64 __CV_VX(load_expand)(const uint*); +__CV_V_INT64 __CV_VX(load_expand)(const int*); +// Load lower 8-bit and expand into 32-bit +__CV_V_UINT32 __CV_VX(load_expand_q)(const uchar*); +__CV_V_INT32 __CV_VX(load_expand_q)(const schar*); + +// Saturating Pack +__CV_V_UINT8 v_pack(const __CV_V_UINT16&, const __CV_V_UINT16&); +__CV_V_INT8 v_pack(const __CV_V_INT16&, const __CV_V_INT16&); +__CV_V_UINT16 v_pack(const __CV_V_UINT32&, const __CV_V_UINT32&); +__CV_V_INT16 v_pack(const __CV_V_INT32&, const __CV_V_INT32&); +// Non-saturating Pack +__CV_V_UINT32 v_pack(const __CV_V_UINT64&, const __CV_V_UINT64&); +__CV_V_INT32 v_pack(const __CV_V_INT64&, const __CV_V_INT64&); +// Pack signed integers with unsigned saturation +__CV_V_UINT8 v_pack_u(const __CV_V_INT16&, const __CV_V_INT16&); +__CV_V_UINT16 v_pack_u(const __CV_V_INT32&, const __CV_V_INT32&); + +/** Arithmetic, bitwise and comparison operations **/ + +// Non-saturating multiply +#if CV_VSX +template +Tvec v_mul_wrap(const Tvec& a, const Tvec& b); +#else +__CV_V_UINT8 v_mul_wrap(const __CV_V_UINT8&, const __CV_V_UINT8&); +__CV_V_INT8 v_mul_wrap(const __CV_V_INT8&, const __CV_V_INT8&); +__CV_V_UINT16 v_mul_wrap(const __CV_V_UINT16&, const __CV_V_UINT16&); +__CV_V_INT16 v_mul_wrap(const __CV_V_INT16&, const __CV_V_INT16&); +#endif + +// Multiply and expand +#if CV_VSX +template +void v_mul_expand(const Tvec& a, const Tvec& b, Twvec& c, Twvec& d); +#else +void v_mul_expand(const __CV_V_UINT8&, const __CV_V_UINT8&, __CV_V_UINT16&, __CV_V_UINT16&); +void v_mul_expand(const __CV_V_INT8&, const __CV_V_INT8&, __CV_V_INT16&, __CV_V_INT16&); +void v_mul_expand(const __CV_V_UINT16&, const __CV_V_UINT16&, __CV_V_UINT32&, __CV_V_UINT32&); +void v_mul_expand(const __CV_V_INT16&, const __CV_V_INT16&, __CV_V_INT32&, __CV_V_INT32&); +void v_mul_expand(const __CV_V_UINT32&, const __CV_V_UINT32&, __CV_V_UINT64&, __CV_V_UINT64&); +void v_mul_expand(const __CV_V_INT32&, const __CV_V_INT32&, __CV_V_INT64&, __CV_V_INT64&); +#endif + +/** Cleanup **/ +#undef CV__SIMD_FORWARD +#undef __CV_VX +#undef __CV_V_UINT8 +#undef __CV_V_INT8 +#undef __CV_V_UINT16 +#undef __CV_V_INT16 +#undef __CV_V_UINT32 +#undef __CV_V_INT32 +#undef __CV_V_UINT64 +#undef __CV_V_INT64 +#undef __CV_V_FLOAT32 +#undef __CV_V_FLOAT64 + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} // cv:: \ No newline at end of file diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_neon.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_neon.hpp new file mode 100644 index 00000000..3b946ff7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_neon.hpp @@ -0,0 +1,1943 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_INTRIN_NEON_HPP +#define OPENCV_HAL_INTRIN_NEON_HPP + +#include +#include "opencv2/core/utility.hpp" + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +#define CV_SIMD128 1 +#if defined(__aarch64__) +#define CV_SIMD128_64F 1 +#else +#define CV_SIMD128_64F 0 +#endif + +#if CV_SIMD128_64F +#define OPENCV_HAL_IMPL_NEON_REINTERPRET(_Tpv, suffix) \ +template static inline \ +_Tpv vreinterpretq_##suffix##_f64(T a) { return (_Tpv) a; } \ +template static inline \ +float64x2_t vreinterpretq_f64_##suffix(T a) { return (float64x2_t) a; } +OPENCV_HAL_IMPL_NEON_REINTERPRET(uint8x16_t, u8) +OPENCV_HAL_IMPL_NEON_REINTERPRET(int8x16_t, s8) +OPENCV_HAL_IMPL_NEON_REINTERPRET(uint16x8_t, u16) +OPENCV_HAL_IMPL_NEON_REINTERPRET(int16x8_t, s16) +OPENCV_HAL_IMPL_NEON_REINTERPRET(uint32x4_t, u32) +OPENCV_HAL_IMPL_NEON_REINTERPRET(int32x4_t, s32) +OPENCV_HAL_IMPL_NEON_REINTERPRET(uint64x2_t, u64) +OPENCV_HAL_IMPL_NEON_REINTERPRET(int64x2_t, s64) +OPENCV_HAL_IMPL_NEON_REINTERPRET(float32x4_t, f32) +#endif + +struct v_uint8x16 +{ + typedef uchar lane_type; + enum { nlanes = 16 }; + + v_uint8x16() {} + explicit v_uint8x16(uint8x16_t v) : val(v) {} + v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7, + uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15) + { + uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15}; + val = vld1q_u8(v); + } + uchar get0() const + { + return vgetq_lane_u8(val, 0); + } + + uint8x16_t val; +}; + +struct v_int8x16 +{ + typedef schar lane_type; + enum { nlanes = 16 }; + + v_int8x16() {} + explicit v_int8x16(int8x16_t v) : val(v) {} + v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7, + schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15) + { + schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15}; + val = vld1q_s8(v); + } + schar get0() const + { + return vgetq_lane_s8(val, 0); + } + + int8x16_t val; +}; + +struct v_uint16x8 +{ + typedef ushort lane_type; + enum { nlanes = 8 }; + + v_uint16x8() {} + explicit v_uint16x8(uint16x8_t v) : val(v) {} + v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7) + { + ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7}; + val = vld1q_u16(v); + } + ushort get0() const + { + return vgetq_lane_u16(val, 0); + } + + uint16x8_t val; +}; + +struct v_int16x8 +{ + typedef short lane_type; + enum { nlanes = 8 }; + + v_int16x8() {} + explicit v_int16x8(int16x8_t v) : val(v) {} + v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7) + { + short v[] = {v0, v1, v2, v3, v4, v5, v6, v7}; + val = vld1q_s16(v); + } + short get0() const + { + return vgetq_lane_s16(val, 0); + } + + int16x8_t val; +}; + +struct v_uint32x4 +{ + typedef unsigned lane_type; + enum { nlanes = 4 }; + + v_uint32x4() {} + explicit v_uint32x4(uint32x4_t v) : val(v) {} + v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3) + { + unsigned v[] = {v0, v1, v2, v3}; + val = vld1q_u32(v); + } + unsigned get0() const + { + return vgetq_lane_u32(val, 0); + } + + uint32x4_t val; +}; + +struct v_int32x4 +{ + typedef int lane_type; + enum { nlanes = 4 }; + + v_int32x4() {} + explicit v_int32x4(int32x4_t v) : val(v) {} + v_int32x4(int v0, int v1, int v2, int v3) + { + int v[] = {v0, v1, v2, v3}; + val = vld1q_s32(v); + } + int get0() const + { + return vgetq_lane_s32(val, 0); + } + int32x4_t val; +}; + +struct v_float32x4 +{ + typedef float lane_type; + enum { nlanes = 4 }; + + v_float32x4() {} + explicit v_float32x4(float32x4_t v) : val(v) {} + v_float32x4(float v0, float v1, float v2, float v3) + { + float v[] = {v0, v1, v2, v3}; + val = vld1q_f32(v); + } + float get0() const + { + return vgetq_lane_f32(val, 0); + } + float32x4_t val; +}; + +struct v_uint64x2 +{ + typedef uint64 lane_type; + enum { nlanes = 2 }; + + v_uint64x2() {} + explicit v_uint64x2(uint64x2_t v) : val(v) {} + v_uint64x2(uint64 v0, uint64 v1) + { + uint64 v[] = {v0, v1}; + val = vld1q_u64(v); + } + uint64 get0() const + { + return vgetq_lane_u64(val, 0); + } + uint64x2_t val; +}; + +struct v_int64x2 +{ + typedef int64 lane_type; + enum { nlanes = 2 }; + + v_int64x2() {} + explicit v_int64x2(int64x2_t v) : val(v) {} + v_int64x2(int64 v0, int64 v1) + { + int64 v[] = {v0, v1}; + val = vld1q_s64(v); + } + int64 get0() const + { + return vgetq_lane_s64(val, 0); + } + int64x2_t val; +}; + +#if CV_SIMD128_64F +struct v_float64x2 +{ + typedef double lane_type; + enum { nlanes = 2 }; + + v_float64x2() {} + explicit v_float64x2(float64x2_t v) : val(v) {} + v_float64x2(double v0, double v1) + { + double v[] = {v0, v1}; + val = vld1q_f64(v); + } + double get0() const + { + return vgetq_lane_f64(val, 0); + } + float64x2_t val; +}; +#endif + +#if CV_FP16 +// Workaround for old compilers +static inline int16x4_t vreinterpret_s16_f16(float16x4_t a) { return (int16x4_t)a; } +static inline float16x4_t vreinterpret_f16_s16(int16x4_t a) { return (float16x4_t)a; } + +static inline float16x4_t cv_vld1_f16(const void* ptr) +{ +#ifndef vld1_f16 // APPLE compiler defines vld1_f16 as macro + return vreinterpret_f16_s16(vld1_s16((const short*)ptr)); +#else + return vld1_f16((const __fp16*)ptr); +#endif +} +static inline void cv_vst1_f16(void* ptr, float16x4_t a) +{ +#ifndef vst1_f16 // APPLE compiler defines vst1_f16 as macro + vst1_s16((short*)ptr, vreinterpret_s16_f16(a)); +#else + vst1_f16((__fp16*)ptr, a); +#endif +} + +#ifndef vdup_n_f16 + #define vdup_n_f16(v) (float16x4_t){v, v, v, v} +#endif + +#endif // CV_FP16 + +#if CV_FP16 +inline v_float32x4 v128_load_fp16_f32(const short* ptr) +{ + float16x4_t a = cv_vld1_f16((const __fp16*)ptr); + return v_float32x4(vcvt_f32_f16(a)); +} + +inline void v_store_fp16(short* ptr, const v_float32x4& a) +{ + float16x4_t fp16 = vcvt_f16_f32(a.val); + cv_vst1_f16((short*)ptr, fp16); +} +#endif + +#define OPENCV_HAL_IMPL_NEON_INIT(_Tpv, _Tp, suffix) \ +inline v_##_Tpv v_setzero_##suffix() { return v_##_Tpv(vdupq_n_##suffix((_Tp)0)); } \ +inline v_##_Tpv v_setall_##suffix(_Tp v) { return v_##_Tpv(vdupq_n_##suffix(v)); } \ +inline _Tpv##_t vreinterpretq_##suffix##_##suffix(_Tpv##_t v) { return v; } \ +inline v_uint8x16 v_reinterpret_as_u8(const v_##_Tpv& v) { return v_uint8x16(vreinterpretq_u8_##suffix(v.val)); } \ +inline v_int8x16 v_reinterpret_as_s8(const v_##_Tpv& v) { return v_int8x16(vreinterpretq_s8_##suffix(v.val)); } \ +inline v_uint16x8 v_reinterpret_as_u16(const v_##_Tpv& v) { return v_uint16x8(vreinterpretq_u16_##suffix(v.val)); } \ +inline v_int16x8 v_reinterpret_as_s16(const v_##_Tpv& v) { return v_int16x8(vreinterpretq_s16_##suffix(v.val)); } \ +inline v_uint32x4 v_reinterpret_as_u32(const v_##_Tpv& v) { return v_uint32x4(vreinterpretq_u32_##suffix(v.val)); } \ +inline v_int32x4 v_reinterpret_as_s32(const v_##_Tpv& v) { return v_int32x4(vreinterpretq_s32_##suffix(v.val)); } \ +inline v_uint64x2 v_reinterpret_as_u64(const v_##_Tpv& v) { return v_uint64x2(vreinterpretq_u64_##suffix(v.val)); } \ +inline v_int64x2 v_reinterpret_as_s64(const v_##_Tpv& v) { return v_int64x2(vreinterpretq_s64_##suffix(v.val)); } \ +inline v_float32x4 v_reinterpret_as_f32(const v_##_Tpv& v) { return v_float32x4(vreinterpretq_f32_##suffix(v.val)); } + +OPENCV_HAL_IMPL_NEON_INIT(uint8x16, uchar, u8) +OPENCV_HAL_IMPL_NEON_INIT(int8x16, schar, s8) +OPENCV_HAL_IMPL_NEON_INIT(uint16x8, ushort, u16) +OPENCV_HAL_IMPL_NEON_INIT(int16x8, short, s16) +OPENCV_HAL_IMPL_NEON_INIT(uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_NEON_INIT(int32x4, int, s32) +OPENCV_HAL_IMPL_NEON_INIT(uint64x2, uint64, u64) +OPENCV_HAL_IMPL_NEON_INIT(int64x2, int64, s64) +OPENCV_HAL_IMPL_NEON_INIT(float32x4, float, f32) +#if CV_SIMD128_64F +#define OPENCV_HAL_IMPL_NEON_INIT_64(_Tpv, suffix) \ +inline v_float64x2 v_reinterpret_as_f64(const v_##_Tpv& v) { return v_float64x2(vreinterpretq_f64_##suffix(v.val)); } +OPENCV_HAL_IMPL_NEON_INIT(float64x2, double, f64) +OPENCV_HAL_IMPL_NEON_INIT_64(uint8x16, u8) +OPENCV_HAL_IMPL_NEON_INIT_64(int8x16, s8) +OPENCV_HAL_IMPL_NEON_INIT_64(uint16x8, u16) +OPENCV_HAL_IMPL_NEON_INIT_64(int16x8, s16) +OPENCV_HAL_IMPL_NEON_INIT_64(uint32x4, u32) +OPENCV_HAL_IMPL_NEON_INIT_64(int32x4, s32) +OPENCV_HAL_IMPL_NEON_INIT_64(uint64x2, u64) +OPENCV_HAL_IMPL_NEON_INIT_64(int64x2, s64) +OPENCV_HAL_IMPL_NEON_INIT_64(float32x4, f32) +OPENCV_HAL_IMPL_NEON_INIT_64(float64x2, f64) +#endif + +#define OPENCV_HAL_IMPL_NEON_PACK(_Tpvec, _Tp, hreg, suffix, _Tpwvec, pack, mov, rshr) \ +inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b) \ +{ \ + hreg a1 = mov(a.val), b1 = mov(b.val); \ + return _Tpvec(vcombine_##suffix(a1, b1)); \ +} \ +inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a) \ +{ \ + hreg a1 = mov(a.val); \ + vst1_##suffix(ptr, a1); \ +} \ +template inline \ +_Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b) \ +{ \ + hreg a1 = rshr(a.val, n); \ + hreg b1 = rshr(b.val, n); \ + return _Tpvec(vcombine_##suffix(a1, b1)); \ +} \ +template inline \ +void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a) \ +{ \ + hreg a1 = rshr(a.val, n); \ + vst1_##suffix(ptr, a1); \ +} + +OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_uint16x8, pack, vqmovn_u16, vqrshrn_n_u16) +OPENCV_HAL_IMPL_NEON_PACK(v_int8x16, schar, int8x8_t, s8, v_int16x8, pack, vqmovn_s16, vqrshrn_n_s16) +OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_uint32x4, pack, vqmovn_u32, vqrshrn_n_u32) +OPENCV_HAL_IMPL_NEON_PACK(v_int16x8, short, int16x4_t, s16, v_int32x4, pack, vqmovn_s32, vqrshrn_n_s32) +OPENCV_HAL_IMPL_NEON_PACK(v_uint32x4, unsigned, uint32x2_t, u32, v_uint64x2, pack, vmovn_u64, vrshrn_n_u64) +OPENCV_HAL_IMPL_NEON_PACK(v_int32x4, int, int32x2_t, s32, v_int64x2, pack, vmovn_s64, vrshrn_n_s64) + +OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_int16x8, pack_u, vqmovun_s16, vqrshrun_n_s16) +OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_int32x4, pack_u, vqmovun_s32, vqrshrun_n_s32) + +// pack boolean +inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b) +{ + uint8x16_t ab = vcombine_u8(vmovn_u16(a.val), vmovn_u16(b.val)); + return v_uint8x16(ab); +} + +inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, const v_uint32x4& d) +{ + uint16x8_t nab = vcombine_u16(vmovn_u32(a.val), vmovn_u32(b.val)); + uint16x8_t ncd = vcombine_u16(vmovn_u32(c.val), vmovn_u32(d.val)); + return v_uint8x16(vcombine_u8(vmovn_u16(nab), vmovn_u16(ncd))); +} + +inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c, + const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f, + const v_uint64x2& g, const v_uint64x2& h) +{ + uint32x4_t ab = vcombine_u32(vmovn_u64(a.val), vmovn_u64(b.val)); + uint32x4_t cd = vcombine_u32(vmovn_u64(c.val), vmovn_u64(d.val)); + uint32x4_t ef = vcombine_u32(vmovn_u64(e.val), vmovn_u64(f.val)); + uint32x4_t gh = vcombine_u32(vmovn_u64(g.val), vmovn_u64(h.val)); + + uint16x8_t abcd = vcombine_u16(vmovn_u32(ab), vmovn_u32(cd)); + uint16x8_t efgh = vcombine_u16(vmovn_u32(ef), vmovn_u32(gh)); + return v_uint8x16(vcombine_u8(vmovn_u16(abcd), vmovn_u16(efgh))); +} + +inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& m3) +{ + float32x2_t vl = vget_low_f32(v.val), vh = vget_high_f32(v.val); + float32x4_t res = vmulq_lane_f32(m0.val, vl, 0); + res = vmlaq_lane_f32(res, m1.val, vl, 1); + res = vmlaq_lane_f32(res, m2.val, vh, 0); + res = vmlaq_lane_f32(res, m3.val, vh, 1); + return v_float32x4(res); +} + +inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& a) +{ + float32x2_t vl = vget_low_f32(v.val), vh = vget_high_f32(v.val); + float32x4_t res = vmulq_lane_f32(m0.val, vl, 0); + res = vmlaq_lane_f32(res, m1.val, vl, 1); + res = vmlaq_lane_f32(res, m2.val, vh, 0); + res = vaddq_f32(res, a.val); + return v_float32x4(res); +} + +#define OPENCV_HAL_IMPL_NEON_BIN_OP(bin_op, _Tpvec, intrin) \ +inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(intrin(a.val, b.val)); \ +} \ +inline _Tpvec& operator bin_op##= (_Tpvec& a, const _Tpvec& b) \ +{ \ + a.val = intrin(a.val, b.val); \ + return a; \ +} + +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint8x16, vqaddq_u8) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint8x16, vqsubq_u8) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int8x16, vqaddq_s8) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int8x16, vqsubq_s8) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint16x8, vqaddq_u16) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint16x8, vqsubq_u16) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int16x8, vqaddq_s16) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int16x8, vqsubq_s16) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int32x4, vaddq_s32) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int32x4, vsubq_s32) +OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_int32x4, vmulq_s32) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint32x4, vaddq_u32) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint32x4, vsubq_u32) +OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_uint32x4, vmulq_u32) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_float32x4, vaddq_f32) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_float32x4, vsubq_f32) +OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_float32x4, vmulq_f32) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_int64x2, vaddq_s64) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_int64x2, vsubq_s64) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_uint64x2, vaddq_u64) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_uint64x2, vsubq_u64) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_BIN_OP(/, v_float32x4, vdivq_f32) +OPENCV_HAL_IMPL_NEON_BIN_OP(+, v_float64x2, vaddq_f64) +OPENCV_HAL_IMPL_NEON_BIN_OP(-, v_float64x2, vsubq_f64) +OPENCV_HAL_IMPL_NEON_BIN_OP(*, v_float64x2, vmulq_f64) +OPENCV_HAL_IMPL_NEON_BIN_OP(/, v_float64x2, vdivq_f64) +#else +inline v_float32x4 operator / (const v_float32x4& a, const v_float32x4& b) +{ + float32x4_t reciprocal = vrecpeq_f32(b.val); + reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal); + reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal); + return v_float32x4(vmulq_f32(a.val, reciprocal)); +} +inline v_float32x4& operator /= (v_float32x4& a, const v_float32x4& b) +{ + float32x4_t reciprocal = vrecpeq_f32(b.val); + reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal); + reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal); + a.val = vmulq_f32(a.val, reciprocal); + return a; +} +#endif + +// saturating multiply 8-bit, 16-bit +#define OPENCV_HAL_IMPL_NEON_MUL_SAT(_Tpvec, _Tpwvec) \ + inline _Tpvec operator * (const _Tpvec& a, const _Tpvec& b) \ + { \ + _Tpwvec c, d; \ + v_mul_expand(a, b, c, d); \ + return v_pack(c, d); \ + } \ + inline _Tpvec& operator *= (_Tpvec& a, const _Tpvec& b) \ + { a = a * b; return a; } + +OPENCV_HAL_IMPL_NEON_MUL_SAT(v_int8x16, v_int16x8) +OPENCV_HAL_IMPL_NEON_MUL_SAT(v_uint8x16, v_uint16x8) +OPENCV_HAL_IMPL_NEON_MUL_SAT(v_int16x8, v_int32x4) +OPENCV_HAL_IMPL_NEON_MUL_SAT(v_uint16x8, v_uint32x4) + +// Multiply and expand +inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b, + v_int16x8& c, v_int16x8& d) +{ + c.val = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val)); + d.val = vmull_s8(vget_high_s8(a.val), vget_high_s8(b.val)); +} + +inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b, + v_uint16x8& c, v_uint16x8& d) +{ + c.val = vmull_u8(vget_low_u8(a.val), vget_low_u8(b.val)); + d.val = vmull_u8(vget_high_u8(a.val), vget_high_u8(b.val)); +} + +inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b, + v_int32x4& c, v_int32x4& d) +{ + c.val = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val)); + d.val = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val)); +} + +inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b, + v_uint32x4& c, v_uint32x4& d) +{ + c.val = vmull_u16(vget_low_u16(a.val), vget_low_u16(b.val)); + d.val = vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val)); +} + +inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b, + v_uint64x2& c, v_uint64x2& d) +{ + c.val = vmull_u32(vget_low_u32(a.val), vget_low_u32(b.val)); + d.val = vmull_u32(vget_high_u32(a.val), vget_high_u32(b.val)); +} + +inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b) +{ + return v_int16x8(vcombine_s16( + vshrn_n_s32(vmull_s16( vget_low_s16(a.val), vget_low_s16(b.val)), 16), + vshrn_n_s32(vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val)), 16) + )); +} +inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b) +{ + return v_uint16x8(vcombine_u16( + vshrn_n_u32(vmull_u16( vget_low_u16(a.val), vget_low_u16(b.val)), 16), + vshrn_n_u32(vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val)), 16) + )); +} + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b) +{ + int32x4_t c = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val)); + int32x4_t d = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val)); + int32x4x2_t cd = vuzpq_s32(c, d); + return v_int32x4(vaddq_s32(cd.val[0], cd.val[1])); +} + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c) +{ + v_int32x4 s = v_dotprod(a, b); + return v_int32x4(vaddq_s32(s.val , c.val)); +} + +#define OPENCV_HAL_IMPL_NEON_LOGIC_OP(_Tpvec, suffix) \ + OPENCV_HAL_IMPL_NEON_BIN_OP(&, _Tpvec, vandq_##suffix) \ + OPENCV_HAL_IMPL_NEON_BIN_OP(|, _Tpvec, vorrq_##suffix) \ + OPENCV_HAL_IMPL_NEON_BIN_OP(^, _Tpvec, veorq_##suffix) \ + inline _Tpvec operator ~ (const _Tpvec& a) \ + { \ + return _Tpvec(vreinterpretq_##suffix##_u8(vmvnq_u8(vreinterpretq_u8_##suffix(a.val)))); \ + } + +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint8x16, u8) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int8x16, s8) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint16x8, u16) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int16x8, s16) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint32x4, u32) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int32x4, s32) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint64x2, u64) +OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int64x2, s64) + +#define OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(bin_op, intrin) \ +inline v_float32x4 operator bin_op (const v_float32x4& a, const v_float32x4& b) \ +{ \ + return v_float32x4(vreinterpretq_f32_s32(intrin(vreinterpretq_s32_f32(a.val), vreinterpretq_s32_f32(b.val)))); \ +} \ +inline v_float32x4& operator bin_op##= (v_float32x4& a, const v_float32x4& b) \ +{ \ + a.val = vreinterpretq_f32_s32(intrin(vreinterpretq_s32_f32(a.val), vreinterpretq_s32_f32(b.val))); \ + return a; \ +} + +OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(&, vandq_s32) +OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(|, vorrq_s32) +OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(^, veorq_s32) + +inline v_float32x4 operator ~ (const v_float32x4& a) +{ + return v_float32x4(vreinterpretq_f32_s32(vmvnq_s32(vreinterpretq_s32_f32(a.val)))); +} + +#if CV_SIMD128_64F +inline v_float32x4 v_sqrt(const v_float32x4& x) +{ + return v_float32x4(vsqrtq_f32(x.val)); +} + +inline v_float32x4 v_invsqrt(const v_float32x4& x) +{ + v_float32x4 one = v_setall_f32(1.0f); + return one / v_sqrt(x); +} +#else +inline v_float32x4 v_sqrt(const v_float32x4& x) +{ + float32x4_t x1 = vmaxq_f32(x.val, vdupq_n_f32(FLT_MIN)); + float32x4_t e = vrsqrteq_f32(x1); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e); + return v_float32x4(vmulq_f32(x.val, e)); +} + +inline v_float32x4 v_invsqrt(const v_float32x4& x) +{ + float32x4_t e = vrsqrteq_f32(x.val); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e); + return v_float32x4(e); +} +#endif + +#define OPENCV_HAL_IMPL_NEON_ABS(_Tpuvec, _Tpsvec, usuffix, ssuffix) \ +inline _Tpuvec v_abs(const _Tpsvec& a) { return v_reinterpret_as_##usuffix(_Tpsvec(vabsq_##ssuffix(a.val))); } + +OPENCV_HAL_IMPL_NEON_ABS(v_uint8x16, v_int8x16, u8, s8) +OPENCV_HAL_IMPL_NEON_ABS(v_uint16x8, v_int16x8, u16, s16) +OPENCV_HAL_IMPL_NEON_ABS(v_uint32x4, v_int32x4, u32, s32) + +inline v_float32x4 v_abs(v_float32x4 x) +{ return v_float32x4(vabsq_f32(x.val)); } + +#if CV_SIMD128_64F +#define OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(bin_op, intrin) \ +inline v_float64x2 operator bin_op (const v_float64x2& a, const v_float64x2& b) \ +{ \ + return v_float64x2(vreinterpretq_f64_s64(intrin(vreinterpretq_s64_f64(a.val), vreinterpretq_s64_f64(b.val)))); \ +} \ +inline v_float64x2& operator bin_op##= (v_float64x2& a, const v_float64x2& b) \ +{ \ + a.val = vreinterpretq_f64_s64(intrin(vreinterpretq_s64_f64(a.val), vreinterpretq_s64_f64(b.val))); \ + return a; \ +} + +OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(&, vandq_s64) +OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(|, vorrq_s64) +OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(^, veorq_s64) + +inline v_float64x2 operator ~ (const v_float64x2& a) +{ + return v_float64x2(vreinterpretq_f64_s32(vmvnq_s32(vreinterpretq_s32_f64(a.val)))); +} + +inline v_float64x2 v_sqrt(const v_float64x2& x) +{ + return v_float64x2(vsqrtq_f64(x.val)); +} + +inline v_float64x2 v_invsqrt(const v_float64x2& x) +{ + v_float64x2 one = v_setall_f64(1.0f); + return one / v_sqrt(x); +} + +inline v_float64x2 v_abs(v_float64x2 x) +{ return v_float64x2(vabsq_f64(x.val)); } +#endif + +// TODO: exp, log, sin, cos + +#define OPENCV_HAL_IMPL_NEON_BIN_FUNC(_Tpvec, func, intrin) \ +inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(intrin(a.val, b.val)); \ +} + +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_min, vminq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_max, vmaxq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_min, vminq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_max, vmaxq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_min, vminq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_max, vmaxq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_min, vminq_s16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_max, vmaxq_s16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_min, vminq_u32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_max, vmaxq_u32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_min, vminq_s32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_max, vmaxq_s32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_min, vminq_f32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_max, vmaxq_f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_min, vminq_f64) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_max, vmaxq_f64) +#endif + +#if CV_SIMD128_64F +inline int64x2_t vmvnq_s64(int64x2_t a) +{ + int64x2_t vx = vreinterpretq_s64_u32(vdupq_n_u32(0xFFFFFFFF)); + return veorq_s64(a, vx); +} +inline uint64x2_t vmvnq_u64(uint64x2_t a) +{ + uint64x2_t vx = vreinterpretq_u64_u32(vdupq_n_u32(0xFFFFFFFF)); + return veorq_u64(a, vx); +} +#endif +#define OPENCV_HAL_IMPL_NEON_INT_CMP_OP(_Tpvec, cast, suffix, not_suffix) \ +inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vceqq_##suffix(a.val, b.val))); } \ +inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vmvnq_##not_suffix(vceqq_##suffix(a.val, b.val)))); } \ +inline _Tpvec operator < (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vcltq_##suffix(a.val, b.val))); } \ +inline _Tpvec operator > (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vcgtq_##suffix(a.val, b.val))); } \ +inline _Tpvec operator <= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vcleq_##suffix(a.val, b.val))); } \ +inline _Tpvec operator >= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(cast(vcgeq_##suffix(a.val, b.val))); } + +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint8x16, OPENCV_HAL_NOP, u8, u8) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int8x16, vreinterpretq_s8_u8, s8, u8) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint16x8, OPENCV_HAL_NOP, u16, u16) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int16x8, vreinterpretq_s16_u16, s16, u16) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint32x4, OPENCV_HAL_NOP, u32, u32) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int32x4, vreinterpretq_s32_u32, s32, u32) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float32x4, vreinterpretq_f32_u32, f32, u32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint64x2, OPENCV_HAL_NOP, u64, u64) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int64x2, vreinterpretq_s64_u64, s64, u64) +OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float64x2, vreinterpretq_f64_u64, f64, u64) +#endif + +inline v_float32x4 v_not_nan(const v_float32x4& a) +{ return v_float32x4(vreinterpretq_f32_u32(vceqq_f32(a.val, a.val))); } +#if CV_SIMD128_64F +inline v_float64x2 v_not_nan(const v_float64x2& a) +{ return v_float64x2(vreinterpretq_f64_u64(vceqq_f64(a.val, a.val))); } +#endif + +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_add_wrap, vaddq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_add_wrap, vaddq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_add_wrap, vaddq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_add_wrap, vaddq_s16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_sub_wrap, vsubq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_sub_wrap, vsubq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_sub_wrap, vsubq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_sub_wrap, vsubq_s16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_mul_wrap, vmulq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_mul_wrap, vmulq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_mul_wrap, vmulq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_mul_wrap, vmulq_s16) + +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_absdiff, vabdq_u8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_absdiff, vabdq_u16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_absdiff, vabdq_u32) +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_absdiff, vabdq_f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_absdiff, vabdq_f64) +#endif + +/** Saturating absolute difference **/ +inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b) +{ return v_int8x16(vqabsq_s8(vqsubq_s8(a.val, b.val))); } +inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b) +{ return v_int16x8(vqabsq_s16(vqsubq_s16(a.val, b.val))); } + +#define OPENCV_HAL_IMPL_NEON_BIN_FUNC2(_Tpvec, _Tpvec2, cast, func, intrin) \ +inline _Tpvec2 func(const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec2(cast(intrin(a.val, b.val))); \ +} + +OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int8x16, v_uint8x16, vreinterpretq_u8_s8, v_absdiff, vabdq_s8) +OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int16x8, v_uint16x8, vreinterpretq_u16_s16, v_absdiff, vabdq_s16) +OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int32x4, v_uint32x4, vreinterpretq_u32_s32, v_absdiff, vabdq_s32) + +inline v_float32x4 v_magnitude(const v_float32x4& a, const v_float32x4& b) +{ + v_float32x4 x(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val)); + return v_sqrt(x); +} + +inline v_float32x4 v_sqr_magnitude(const v_float32x4& a, const v_float32x4& b) +{ + return v_float32x4(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val)); +} + +inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c) +{ +#if CV_SIMD128_64F + // ARMv8, which adds support for 64-bit floating-point (so CV_SIMD128_64F is defined), + // also adds FMA support both for single- and double-precision floating-point vectors + return v_float32x4(vfmaq_f32(c.val, a.val, b.val)); +#else + return v_float32x4(vmlaq_f32(c.val, a.val, b.val)); +#endif +} + +inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c) +{ + return v_int32x4(vmlaq_s32(c.val, a.val, b.val)); +} + +inline v_float32x4 v_muladd(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c) +{ + return v_fma(a, b, c); +} + +inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c) +{ + return v_fma(a, b, c); +} + +#if CV_SIMD128_64F +inline v_float64x2 v_magnitude(const v_float64x2& a, const v_float64x2& b) +{ + v_float64x2 x(vaddq_f64(vmulq_f64(a.val, a.val), vmulq_f64(b.val, b.val))); + return v_sqrt(x); +} + +inline v_float64x2 v_sqr_magnitude(const v_float64x2& a, const v_float64x2& b) +{ + return v_float64x2(vaddq_f64(vmulq_f64(a.val, a.val), vmulq_f64(b.val, b.val))); +} + +inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c) +{ + return v_float64x2(vfmaq_f64(c.val, a.val, b.val)); +} + +inline v_float64x2 v_muladd(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c) +{ + return v_fma(a, b, c); +} +#endif + +// trade efficiency for convenience +#define OPENCV_HAL_IMPL_NEON_SHIFT_OP(_Tpvec, suffix, _Tps, ssuffix) \ +inline _Tpvec operator << (const _Tpvec& a, int n) \ +{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)n))); } \ +inline _Tpvec operator >> (const _Tpvec& a, int n) \ +{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)-n))); } \ +template inline _Tpvec v_shl(const _Tpvec& a) \ +{ return _Tpvec(vshlq_n_##suffix(a.val, n)); } \ +template inline _Tpvec v_shr(const _Tpvec& a) \ +{ return _Tpvec(vshrq_n_##suffix(a.val, n)); } \ +template inline _Tpvec v_rshr(const _Tpvec& a) \ +{ return _Tpvec(vrshrq_n_##suffix(a.val, n)); } + +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint8x16, u8, schar, s8) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int8x16, s8, schar, s8) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint16x8, u16, short, s16) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int16x8, s16, short, s16) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint32x4, u32, int, s32) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int32x4, s32, int, s32) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint64x2, u64, int64, s64) +OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int64x2, s64, int64, s64) + +#define OPENCV_HAL_IMPL_NEON_ROTATE_OP(_Tpvec, suffix) \ +template inline _Tpvec v_rotate_right(const _Tpvec& a) \ +{ return _Tpvec(vextq_##suffix(a.val, vdupq_n_##suffix(0), n)); } \ +template inline _Tpvec v_rotate_left(const _Tpvec& a) \ +{ return _Tpvec(vextq_##suffix(vdupq_n_##suffix(0), a.val, _Tpvec::nlanes - n)); } \ +template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \ +{ return a; } \ +template inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vextq_##suffix(a.val, b.val, n)); } \ +template inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vextq_##suffix(b.val, a.val, _Tpvec::nlanes - n)); } \ +template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \ +{ CV_UNUSED(b); return a; } + +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint8x16, u8) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int8x16, s8) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint16x8, u16) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int16x8, s16) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint32x4, u32) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int32x4, s32) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_float32x4, f32) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint64x2, u64) +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int64x2, s64) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_float64x2, f64) +#endif + +#define OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(_Tpvec, _Tp, suffix) \ +inline _Tpvec v_load(const _Tp* ptr) \ +{ return _Tpvec(vld1q_##suffix(ptr)); } \ +inline _Tpvec v_load_aligned(const _Tp* ptr) \ +{ return _Tpvec(vld1q_##suffix(ptr)); } \ +inline _Tpvec v_load_low(const _Tp* ptr) \ +{ return _Tpvec(vcombine_##suffix(vld1_##suffix(ptr), vdup_n_##suffix((_Tp)0))); } \ +inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ +{ return _Tpvec(vcombine_##suffix(vld1_##suffix(ptr0), vld1_##suffix(ptr1))); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a) \ +{ vst1q_##suffix(ptr, a.val); } \ +inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \ +{ vst1q_##suffix(ptr, a.val); } \ +inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \ +{ vst1q_##suffix(ptr, a.val); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \ +{ vst1q_##suffix(ptr, a.val); } \ +inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ +{ vst1_##suffix(ptr, vget_low_##suffix(a.val)); } \ +inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ +{ vst1_##suffix(ptr, vget_high_##suffix(a.val)); } + +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint8x16, uchar, u8) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int8x16, schar, s8) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint16x8, ushort, u16) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int16x8, short, s16) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int32x4, int, s32) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint64x2, uint64, u64) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int64x2, int64, s64) +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_float32x4, float, f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_float64x2, double, f64) +#endif + +#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \ +inline scalartype v_reduce_##func(const _Tpvec& a) \ +{ \ + _Tpnvec##_t a0 = vp##vectorfunc##_##suffix(vget_low_##suffix(a.val), vget_high_##suffix(a.val)); \ + a0 = vp##vectorfunc##_##suffix(a0, a0); \ + return (scalartype)vget_lane_##suffix(vp##vectorfunc##_##suffix(a0, a0),0); \ +} + +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_uint16x8, uint16x4, unsigned short, sum, add, u16) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_uint16x8, uint16x4, unsigned short, max, max, u16) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_uint16x8, uint16x4, unsigned short, min, min, u16) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_int16x8, int16x4, short, sum, add, s16) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_int16x8, int16x4, short, max, max, s16) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_int16x8, int16x4, short, min, min, s16) + +#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \ +inline scalartype v_reduce_##func(const _Tpvec& a) \ +{ \ + _Tpnvec##_t a0 = vp##vectorfunc##_##suffix(vget_low_##suffix(a.val), vget_high_##suffix(a.val)); \ + return (scalartype)vget_lane_##suffix(vp##vectorfunc##_##suffix(a0, vget_high_##suffix(a.val)),0); \ +} + +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, sum, add, u32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, max, max, u32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, min, min, u32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, sum, add, s32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, max, max, s32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, min, min, s32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, sum, add, f32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, max, max, f32) +OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, min, min, f32) + +#if CV_SIMD128_64F +inline double v_reduce_sum(const v_float64x2& a) +{ + return vgetq_lane_f64(a.val, 0) + vgetq_lane_f64(a.val, 1); +} +#endif + +inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, const v_float32x4& d) +{ + float32x4x2_t ab = vtrnq_f32(a.val, b.val); + float32x4x2_t cd = vtrnq_f32(c.val, d.val); + + float32x4_t u0 = vaddq_f32(ab.val[0], ab.val[1]); // a0+a1 b0+b1 a2+a3 b2+b3 + float32x4_t u1 = vaddq_f32(cd.val[0], cd.val[1]); // c0+c1 d0+d1 c2+c3 d2+d3 + + float32x4_t v0 = vcombine_f32(vget_low_f32(u0), vget_low_f32(u1)); + float32x4_t v1 = vcombine_f32(vget_high_f32(u0), vget_high_f32(u1)); + + return v_float32x4(vaddq_f32(v0, v1)); +} + +inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b) +{ + uint32x4_t t0 = vpaddlq_u16(vpaddlq_u8(vabdq_u8(a.val, b.val))); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b) +{ + uint32x4_t t0 = vpaddlq_u16(vpaddlq_u8(vreinterpretq_u8_s8(vabdq_s8(a.val, b.val)))); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b) +{ + uint32x4_t t0 = vpaddlq_u16(vabdq_u16(a.val, b.val)); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b) +{ + uint32x4_t t0 = vpaddlq_u16(vreinterpretq_u16_s16(vabdq_s16(a.val, b.val))); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b) +{ + uint32x4_t t0 = vabdq_u32(a.val, b.val); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b) +{ + uint32x4_t t0 = vreinterpretq_u32_s32(vabdq_s32(a.val, b.val)); + uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0)); + return vget_lane_u32(vpadd_u32(t1, t1), 0); +} +inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b) +{ + float32x4_t t0 = vabdq_f32(a.val, b.val); + float32x2_t t1 = vpadd_f32(vget_low_f32(t0), vget_high_f32(t0)); + return vget_lane_f32(vpadd_f32(t1, t1), 0); +} + +#define OPENCV_HAL_IMPL_NEON_POPCOUNT(_Tpvec, cast) \ +inline v_uint32x4 v_popcount(const _Tpvec& a) \ +{ \ + uint8x16_t t = vcntq_u8(cast(a.val)); \ + uint16x8_t t0 = vpaddlq_u8(t); /* 16 -> 8 */ \ + uint32x4_t t1 = vpaddlq_u16(t0); /* 8 -> 4 */ \ + return v_uint32x4(t1); \ +} + +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_uint8x16, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_uint16x8, vreinterpretq_u8_u16) +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_uint32x4, vreinterpretq_u8_u32) +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_int8x16, vreinterpretq_u8_s8) +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_int16x8, vreinterpretq_u8_s16) +OPENCV_HAL_IMPL_NEON_POPCOUNT(v_int32x4, vreinterpretq_u8_s32) + +inline int v_signmask(const v_uint8x16& a) +{ + int8x8_t m0 = vcreate_s8(CV_BIG_UINT(0x0706050403020100)); + uint8x16_t v0 = vshlq_u8(vshrq_n_u8(a.val, 7), vcombine_s8(m0, m0)); + uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(vpaddlq_u8(v0))); + return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 8); +} +inline int v_signmask(const v_int8x16& a) +{ return v_signmask(v_reinterpret_as_u8(a)); } + +inline int v_signmask(const v_uint16x8& a) +{ + int16x4_t m0 = vcreate_s16(CV_BIG_UINT(0x0003000200010000)); + uint16x8_t v0 = vshlq_u16(vshrq_n_u16(a.val, 15), vcombine_s16(m0, m0)); + uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(v0)); + return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 4); +} +inline int v_signmask(const v_int16x8& a) +{ return v_signmask(v_reinterpret_as_u16(a)); } + +inline int v_signmask(const v_uint32x4& a) +{ + int32x2_t m0 = vcreate_s32(CV_BIG_UINT(0x0000000100000000)); + uint32x4_t v0 = vshlq_u32(vshrq_n_u32(a.val, 31), vcombine_s32(m0, m0)); + uint64x2_t v1 = vpaddlq_u32(v0); + return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 2); +} +inline int v_signmask(const v_int32x4& a) +{ return v_signmask(v_reinterpret_as_u32(a)); } +inline int v_signmask(const v_float32x4& a) +{ return v_signmask(v_reinterpret_as_u32(a)); } +#if CV_SIMD128_64F +inline int v_signmask(const v_uint64x2& a) +{ + int64x1_t m0 = vdup_n_s64(0); + uint64x2_t v0 = vshlq_u64(vshrq_n_u64(a.val, 63), vcombine_s64(m0, m0)); + return (int)vgetq_lane_u64(v0, 0) + ((int)vgetq_lane_u64(v0, 1) << 1); +} +inline int v_signmask(const v_float64x2& a) +{ return v_signmask(v_reinterpret_as_u64(a)); } +#endif + +#define OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(_Tpvec, suffix, shift) \ +inline bool v_check_all(const v_##_Tpvec& a) \ +{ \ + _Tpvec##_t v0 = vshrq_n_##suffix(vmvnq_##suffix(a.val), shift); \ + uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \ + return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) == 0; \ +} \ +inline bool v_check_any(const v_##_Tpvec& a) \ +{ \ + _Tpvec##_t v0 = vshrq_n_##suffix(a.val, shift); \ + uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \ + return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) != 0; \ +} + +OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint8x16, u8, 7) +OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint16x8, u16, 15) +OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint32x4, u32, 31) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint64x2, u64, 63) +#endif + +inline bool v_check_all(const v_int8x16& a) +{ return v_check_all(v_reinterpret_as_u8(a)); } +inline bool v_check_all(const v_int16x8& a) +{ return v_check_all(v_reinterpret_as_u16(a)); } +inline bool v_check_all(const v_int32x4& a) +{ return v_check_all(v_reinterpret_as_u32(a)); } +inline bool v_check_all(const v_float32x4& a) +{ return v_check_all(v_reinterpret_as_u32(a)); } + +inline bool v_check_any(const v_int8x16& a) +{ return v_check_any(v_reinterpret_as_u8(a)); } +inline bool v_check_any(const v_int16x8& a) +{ return v_check_any(v_reinterpret_as_u16(a)); } +inline bool v_check_any(const v_int32x4& a) +{ return v_check_any(v_reinterpret_as_u32(a)); } +inline bool v_check_any(const v_float32x4& a) +{ return v_check_any(v_reinterpret_as_u32(a)); } + +#if CV_SIMD128_64F +inline bool v_check_all(const v_int64x2& a) +{ return v_check_all(v_reinterpret_as_u64(a)); } +inline bool v_check_all(const v_float64x2& a) +{ return v_check_all(v_reinterpret_as_u64(a)); } +inline bool v_check_any(const v_int64x2& a) +{ return v_check_any(v_reinterpret_as_u64(a)); } +inline bool v_check_any(const v_float64x2& a) +{ return v_check_any(v_reinterpret_as_u64(a)); } +#endif + +#define OPENCV_HAL_IMPL_NEON_SELECT(_Tpvec, suffix, usuffix) \ +inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(vbslq_##suffix(vreinterpretq_##usuffix##_##suffix(mask.val), a.val, b.val)); \ +} + +OPENCV_HAL_IMPL_NEON_SELECT(v_uint8x16, u8, u8) +OPENCV_HAL_IMPL_NEON_SELECT(v_int8x16, s8, u8) +OPENCV_HAL_IMPL_NEON_SELECT(v_uint16x8, u16, u16) +OPENCV_HAL_IMPL_NEON_SELECT(v_int16x8, s16, u16) +OPENCV_HAL_IMPL_NEON_SELECT(v_uint32x4, u32, u32) +OPENCV_HAL_IMPL_NEON_SELECT(v_int32x4, s32, u32) +OPENCV_HAL_IMPL_NEON_SELECT(v_float32x4, f32, u32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_SELECT(v_float64x2, f64, u64) +#endif + +#define OPENCV_HAL_IMPL_NEON_EXPAND(_Tpvec, _Tpwvec, _Tp, suffix) \ +inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \ +{ \ + b0.val = vmovl_##suffix(vget_low_##suffix(a.val)); \ + b1.val = vmovl_##suffix(vget_high_##suffix(a.val)); \ +} \ +inline _Tpwvec v_expand_low(const _Tpvec& a) \ +{ \ + return _Tpwvec(vmovl_##suffix(vget_low_##suffix(a.val))); \ +} \ +inline _Tpwvec v_expand_high(const _Tpvec& a) \ +{ \ + return _Tpwvec(vmovl_##suffix(vget_high_##suffix(a.val))); \ +} \ +inline _Tpwvec v_load_expand(const _Tp* ptr) \ +{ \ + return _Tpwvec(vmovl_##suffix(vld1_##suffix(ptr))); \ +} + +OPENCV_HAL_IMPL_NEON_EXPAND(v_uint8x16, v_uint16x8, uchar, u8) +OPENCV_HAL_IMPL_NEON_EXPAND(v_int8x16, v_int16x8, schar, s8) +OPENCV_HAL_IMPL_NEON_EXPAND(v_uint16x8, v_uint32x4, ushort, u16) +OPENCV_HAL_IMPL_NEON_EXPAND(v_int16x8, v_int32x4, short, s16) +OPENCV_HAL_IMPL_NEON_EXPAND(v_uint32x4, v_uint64x2, uint, u32) +OPENCV_HAL_IMPL_NEON_EXPAND(v_int32x4, v_int64x2, int, s32) + +inline v_uint32x4 v_load_expand_q(const uchar* ptr) +{ + typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint; + uint8x8_t v0 = vcreate_u8(*(unaligned_uint*)ptr); + uint16x4_t v1 = vget_low_u16(vmovl_u8(v0)); + return v_uint32x4(vmovl_u16(v1)); +} + +inline v_int32x4 v_load_expand_q(const schar* ptr) +{ + typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint; + int8x8_t v0 = vcreate_s8(*(unaligned_uint*)ptr); + int16x4_t v1 = vget_low_s16(vmovl_s8(v0)); + return v_int32x4(vmovl_s16(v1)); +} + +#if defined(__aarch64__) +#define OPENCV_HAL_IMPL_NEON_UNPACKS(_Tpvec, suffix) \ +inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \ +{ \ + b0.val = vzip1q_##suffix(a0.val, a1.val); \ + b1.val = vzip2q_##suffix(a0.val, a1.val); \ +} \ +inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \ +{ \ + return v_##_Tpvec(vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val))); \ +} \ +inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \ +{ \ + return v_##_Tpvec(vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val))); \ +} \ +inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \ +{ \ + c.val = vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val)); \ + d.val = vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val)); \ +} +#else +#define OPENCV_HAL_IMPL_NEON_UNPACKS(_Tpvec, suffix) \ +inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \ +{ \ + _Tpvec##x2_t p = vzipq_##suffix(a0.val, a1.val); \ + b0.val = p.val[0]; \ + b1.val = p.val[1]; \ +} \ +inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \ +{ \ + return v_##_Tpvec(vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val))); \ +} \ +inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \ +{ \ + return v_##_Tpvec(vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val))); \ +} \ +inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \ +{ \ + c.val = vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val)); \ + d.val = vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val)); \ +} +#endif + +OPENCV_HAL_IMPL_NEON_UNPACKS(uint8x16, u8) +OPENCV_HAL_IMPL_NEON_UNPACKS(int8x16, s8) +OPENCV_HAL_IMPL_NEON_UNPACKS(uint16x8, u16) +OPENCV_HAL_IMPL_NEON_UNPACKS(int16x8, s16) +OPENCV_HAL_IMPL_NEON_UNPACKS(uint32x4, u32) +OPENCV_HAL_IMPL_NEON_UNPACKS(int32x4, s32) +OPENCV_HAL_IMPL_NEON_UNPACKS(float32x4, f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_UNPACKS(float64x2, f64) +#endif + +#define OPENCV_HAL_IMPL_NEON_EXTRACT(_Tpvec, suffix) \ +template \ +inline v_##_Tpvec v_extract(const v_##_Tpvec& a, const v_##_Tpvec& b) \ +{ \ + return v_##_Tpvec(vextq_##suffix(a.val, b.val, s)); \ +} + +OPENCV_HAL_IMPL_NEON_EXTRACT(uint8x16, u8) +OPENCV_HAL_IMPL_NEON_EXTRACT(int8x16, s8) +OPENCV_HAL_IMPL_NEON_EXTRACT(uint16x8, u16) +OPENCV_HAL_IMPL_NEON_EXTRACT(int16x8, s16) +OPENCV_HAL_IMPL_NEON_EXTRACT(uint32x4, u32) +OPENCV_HAL_IMPL_NEON_EXTRACT(int32x4, s32) +OPENCV_HAL_IMPL_NEON_EXTRACT(uint64x2, u64) +OPENCV_HAL_IMPL_NEON_EXTRACT(int64x2, s64) +OPENCV_HAL_IMPL_NEON_EXTRACT(float32x4, f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_EXTRACT(float64x2, f64) +#endif + +#if CV_SIMD128_64F +inline v_int32x4 v_round(const v_float32x4& a) +{ + float32x4_t a_ = a.val; + int32x4_t result; + __asm__ ("fcvtns %0.4s, %1.4s" + : "=w"(result) + : "w"(a_) + : /* No clobbers */); + return v_int32x4(result); +} +#else +inline v_int32x4 v_round(const v_float32x4& a) +{ + static const int32x4_t v_sign = vdupq_n_s32(1 << 31), + v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f)); + + int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(a.val))); + return v_int32x4(vcvtq_s32_f32(vaddq_f32(a.val, vreinterpretq_f32_s32(v_addition)))); +} +#endif +inline v_int32x4 v_floor(const v_float32x4& a) +{ + int32x4_t a1 = vcvtq_s32_f32(a.val); + uint32x4_t mask = vcgtq_f32(vcvtq_f32_s32(a1), a.val); + return v_int32x4(vaddq_s32(a1, vreinterpretq_s32_u32(mask))); +} + +inline v_int32x4 v_ceil(const v_float32x4& a) +{ + int32x4_t a1 = vcvtq_s32_f32(a.val); + uint32x4_t mask = vcgtq_f32(a.val, vcvtq_f32_s32(a1)); + return v_int32x4(vsubq_s32(a1, vreinterpretq_s32_u32(mask))); +} + +inline v_int32x4 v_trunc(const v_float32x4& a) +{ return v_int32x4(vcvtq_s32_f32(a.val)); } + +#if CV_SIMD128_64F +inline v_int32x4 v_round(const v_float64x2& a) +{ + static const int32x2_t zero = vdup_n_s32(0); + return v_int32x4(vcombine_s32(vmovn_s64(vcvtaq_s64_f64(a.val)), zero)); +} + +inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b) +{ + return v_int32x4(vcombine_s32(vmovn_s64(vcvtaq_s64_f64(a.val)), vmovn_s64(vcvtaq_s64_f64(b.val)))); +} + +inline v_int32x4 v_floor(const v_float64x2& a) +{ + static const int32x2_t zero = vdup_n_s32(0); + int64x2_t a1 = vcvtq_s64_f64(a.val); + uint64x2_t mask = vcgtq_f64(vcvtq_f64_s64(a1), a.val); + a1 = vaddq_s64(a1, vreinterpretq_s64_u64(mask)); + return v_int32x4(vcombine_s32(vmovn_s64(a1), zero)); +} + +inline v_int32x4 v_ceil(const v_float64x2& a) +{ + static const int32x2_t zero = vdup_n_s32(0); + int64x2_t a1 = vcvtq_s64_f64(a.val); + uint64x2_t mask = vcgtq_f64(a.val, vcvtq_f64_s64(a1)); + a1 = vsubq_s64(a1, vreinterpretq_s64_u64(mask)); + return v_int32x4(vcombine_s32(vmovn_s64(a1), zero)); +} + +inline v_int32x4 v_trunc(const v_float64x2& a) +{ + static const int32x2_t zero = vdup_n_s32(0); + return v_int32x4(vcombine_s32(vmovn_s64(vcvtaq_s64_f64(a.val)), zero)); +} +#endif + +#define OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(_Tpvec, suffix) \ +inline void v_transpose4x4(const v_##_Tpvec& a0, const v_##_Tpvec& a1, \ + const v_##_Tpvec& a2, const v_##_Tpvec& a3, \ + v_##_Tpvec& b0, v_##_Tpvec& b1, \ + v_##_Tpvec& b2, v_##_Tpvec& b3) \ +{ \ + /* m00 m01 m02 m03 */ \ + /* m10 m11 m12 m13 */ \ + /* m20 m21 m22 m23 */ \ + /* m30 m31 m32 m33 */ \ + _Tpvec##x2_t t0 = vtrnq_##suffix(a0.val, a1.val); \ + _Tpvec##x2_t t1 = vtrnq_##suffix(a2.val, a3.val); \ + /* m00 m10 m02 m12 */ \ + /* m01 m11 m03 m13 */ \ + /* m20 m30 m22 m32 */ \ + /* m21 m31 m23 m33 */ \ + b0.val = vcombine_##suffix(vget_low_##suffix(t0.val[0]), vget_low_##suffix(t1.val[0])); \ + b1.val = vcombine_##suffix(vget_low_##suffix(t0.val[1]), vget_low_##suffix(t1.val[1])); \ + b2.val = vcombine_##suffix(vget_high_##suffix(t0.val[0]), vget_high_##suffix(t1.val[0])); \ + b3.val = vcombine_##suffix(vget_high_##suffix(t0.val[1]), vget_high_##suffix(t1.val[1])); \ +} + +OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(uint32x4, u32) +OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(int32x4, s32) +OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(float32x4, f32) + +#define OPENCV_HAL_IMPL_NEON_INTERLEAVED(_Tpvec, _Tp, suffix) \ +inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b) \ +{ \ + _Tpvec##x2_t v = vld2q_##suffix(ptr); \ + a.val = v.val[0]; \ + b.val = v.val[1]; \ +} \ +inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, v_##_Tpvec& c) \ +{ \ + _Tpvec##x3_t v = vld3q_##suffix(ptr); \ + a.val = v.val[0]; \ + b.val = v.val[1]; \ + c.val = v.val[2]; \ +} \ +inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, \ + v_##_Tpvec& c, v_##_Tpvec& d) \ +{ \ + _Tpvec##x4_t v = vld4q_##suffix(ptr); \ + a.val = v.val[0]; \ + b.val = v.val[1]; \ + c.val = v.val[2]; \ + d.val = v.val[3]; \ +} \ +inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ \ + _Tpvec##x2_t v; \ + v.val[0] = a.val; \ + v.val[1] = b.val; \ + vst2q_##suffix(ptr, v); \ +} \ +inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \ + const v_##_Tpvec& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ \ + _Tpvec##x3_t v; \ + v.val[0] = a.val; \ + v.val[1] = b.val; \ + v.val[2] = c.val; \ + vst3q_##suffix(ptr, v); \ +} \ +inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \ + const v_##_Tpvec& c, const v_##_Tpvec& d, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec##x4_t v; \ + v.val[0] = a.val; \ + v.val[1] = b.val; \ + v.val[2] = c.val; \ + v.val[3] = d.val; \ + vst4q_##suffix(ptr, v); \ +} + +#define OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(tp, suffix) \ +inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, v_##tp##x2& b ) \ +{ \ + tp##x1_t a0 = vld1_##suffix(ptr); \ + tp##x1_t b0 = vld1_##suffix(ptr + 1); \ + tp##x1_t a1 = vld1_##suffix(ptr + 2); \ + tp##x1_t b1 = vld1_##suffix(ptr + 3); \ + a = v_##tp##x2(vcombine_##suffix(a0, a1)); \ + b = v_##tp##x2(vcombine_##suffix(b0, b1)); \ +} \ + \ +inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, \ + v_##tp##x2& b, v_##tp##x2& c ) \ +{ \ + tp##x1_t a0 = vld1_##suffix(ptr); \ + tp##x1_t b0 = vld1_##suffix(ptr + 1); \ + tp##x1_t c0 = vld1_##suffix(ptr + 2); \ + tp##x1_t a1 = vld1_##suffix(ptr + 3); \ + tp##x1_t b1 = vld1_##suffix(ptr + 4); \ + tp##x1_t c1 = vld1_##suffix(ptr + 5); \ + a = v_##tp##x2(vcombine_##suffix(a0, a1)); \ + b = v_##tp##x2(vcombine_##suffix(b0, b1)); \ + c = v_##tp##x2(vcombine_##suffix(c0, c1)); \ +} \ + \ +inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, v_##tp##x2& b, \ + v_##tp##x2& c, v_##tp##x2& d ) \ +{ \ + tp##x1_t a0 = vld1_##suffix(ptr); \ + tp##x1_t b0 = vld1_##suffix(ptr + 1); \ + tp##x1_t c0 = vld1_##suffix(ptr + 2); \ + tp##x1_t d0 = vld1_##suffix(ptr + 3); \ + tp##x1_t a1 = vld1_##suffix(ptr + 4); \ + tp##x1_t b1 = vld1_##suffix(ptr + 5); \ + tp##x1_t c1 = vld1_##suffix(ptr + 6); \ + tp##x1_t d1 = vld1_##suffix(ptr + 7); \ + a = v_##tp##x2(vcombine_##suffix(a0, a1)); \ + b = v_##tp##x2(vcombine_##suffix(b0, b1)); \ + c = v_##tp##x2(vcombine_##suffix(c0, c1)); \ + d = v_##tp##x2(vcombine_##suffix(d0, d1)); \ +} \ + \ +inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, const v_##tp##x2& b, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ \ + vst1_##suffix(ptr, vget_low_##suffix(a.val)); \ + vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \ + vst1_##suffix(ptr + 2, vget_high_##suffix(a.val)); \ + vst1_##suffix(ptr + 3, vget_high_##suffix(b.val)); \ +} \ + \ +inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, \ + const v_##tp##x2& b, const v_##tp##x2& c, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ \ + vst1_##suffix(ptr, vget_low_##suffix(a.val)); \ + vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \ + vst1_##suffix(ptr + 2, vget_low_##suffix(c.val)); \ + vst1_##suffix(ptr + 3, vget_high_##suffix(a.val)); \ + vst1_##suffix(ptr + 4, vget_high_##suffix(b.val)); \ + vst1_##suffix(ptr + 5, vget_high_##suffix(c.val)); \ +} \ + \ +inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, const v_##tp##x2& b, \ + const v_##tp##x2& c, const v_##tp##x2& d, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ \ + vst1_##suffix(ptr, vget_low_##suffix(a.val)); \ + vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \ + vst1_##suffix(ptr + 2, vget_low_##suffix(c.val)); \ + vst1_##suffix(ptr + 3, vget_low_##suffix(d.val)); \ + vst1_##suffix(ptr + 4, vget_high_##suffix(a.val)); \ + vst1_##suffix(ptr + 5, vget_high_##suffix(b.val)); \ + vst1_##suffix(ptr + 6, vget_high_##suffix(c.val)); \ + vst1_##suffix(ptr + 7, vget_high_##suffix(d.val)); \ +} + +OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint8x16, uchar, u8) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(int8x16, schar, s8) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint16x8, ushort, u16) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(int16x8, short, s16) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(int32x4, int, s32) +OPENCV_HAL_IMPL_NEON_INTERLEAVED(float32x4, float, f32) +#if CV_SIMD128_64F +OPENCV_HAL_IMPL_NEON_INTERLEAVED(float64x2, double, f64) +#endif + +OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(int64, s64) +OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(uint64, u64) + +inline v_float32x4 v_cvt_f32(const v_int32x4& a) +{ + return v_float32x4(vcvtq_f32_s32(a.val)); +} + +#if CV_SIMD128_64F +inline v_float32x4 v_cvt_f32(const v_float64x2& a) +{ + float32x2_t zero = vdup_n_f32(0.0f); + return v_float32x4(vcombine_f32(vcvt_f32_f64(a.val), zero)); +} + +inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b) +{ + return v_float32x4(vcombine_f32(vcvt_f32_f64(a.val), vcvt_f32_f64(b.val))); +} + +inline v_float64x2 v_cvt_f64(const v_int32x4& a) +{ + return v_float64x2(vcvt_f64_f32(vcvt_f32_s32(vget_low_s32(a.val)))); +} + +inline v_float64x2 v_cvt_f64_high(const v_int32x4& a) +{ + return v_float64x2(vcvt_f64_f32(vcvt_f32_s32(vget_high_s32(a.val)))); +} + +inline v_float64x2 v_cvt_f64(const v_float32x4& a) +{ + return v_float64x2(vcvt_f64_f32(vget_low_f32(a.val))); +} + +inline v_float64x2 v_cvt_f64_high(const v_float32x4& a) +{ + return v_float64x2(vcvt_f64_f32(vget_high_f32(a.val))); +} +#endif + +////////////// Lookup table access //////////////////// + +inline v_int8x16 v_lut(const schar* tab, const int* idx) +{ + schar CV_DECL_ALIGNED(32) elems[16] = + { + tab[idx[ 0]], + tab[idx[ 1]], + tab[idx[ 2]], + tab[idx[ 3]], + tab[idx[ 4]], + tab[idx[ 5]], + tab[idx[ 6]], + tab[idx[ 7]], + tab[idx[ 8]], + tab[idx[ 9]], + tab[idx[10]], + tab[idx[11]], + tab[idx[12]], + tab[idx[13]], + tab[idx[14]], + tab[idx[15]] + }; + return v_int8x16(vld1q_s8(elems)); +} +inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx) +{ + schar CV_DECL_ALIGNED(32) elems[16] = + { + tab[idx[0]], + tab[idx[0] + 1], + tab[idx[1]], + tab[idx[1] + 1], + tab[idx[2]], + tab[idx[2] + 1], + tab[idx[3]], + tab[idx[3] + 1], + tab[idx[4]], + tab[idx[4] + 1], + tab[idx[5]], + tab[idx[5] + 1], + tab[idx[6]], + tab[idx[6] + 1], + tab[idx[7]], + tab[idx[7] + 1] + }; + return v_int8x16(vld1q_s8(elems)); +} +inline v_int8x16 v_lut_quads(const schar* tab, const int* idx) +{ + schar CV_DECL_ALIGNED(32) elems[16] = + { + tab[idx[0]], + tab[idx[0] + 1], + tab[idx[0] + 2], + tab[idx[0] + 3], + tab[idx[1]], + tab[idx[1] + 1], + tab[idx[1] + 2], + tab[idx[1] + 3], + tab[idx[2]], + tab[idx[2] + 1], + tab[idx[2] + 2], + tab[idx[2] + 3], + tab[idx[3]], + tab[idx[3] + 1], + tab[idx[3] + 2], + tab[idx[3] + 3] + }; + return v_int8x16(vld1q_s8(elems)); +} +inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((schar*)tab, idx)); } +inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((schar*)tab, idx)); } +inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((schar*)tab, idx)); } + +inline v_int16x8 v_lut(const short* tab, const int* idx) +{ + short CV_DECL_ALIGNED(32) elems[8] = + { + tab[idx[0]], + tab[idx[1]], + tab[idx[2]], + tab[idx[3]], + tab[idx[4]], + tab[idx[5]], + tab[idx[6]], + tab[idx[7]] + }; + return v_int16x8(vld1q_s16(elems)); +} +inline v_int16x8 v_lut_pairs(const short* tab, const int* idx) +{ + short CV_DECL_ALIGNED(32) elems[8] = + { + tab[idx[0]], + tab[idx[0] + 1], + tab[idx[1]], + tab[idx[1] + 1], + tab[idx[2]], + tab[idx[2] + 1], + tab[idx[3]], + tab[idx[3] + 1] + }; + return v_int16x8(vld1q_s16(elems)); +} +inline v_int16x8 v_lut_quads(const short* tab, const int* idx) +{ + return v_int16x8(vcombine_s16(vld1_s16(tab + idx[0]), vld1_s16(tab + idx[1]))); +} +inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((short*)tab, idx)); } +inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((short*)tab, idx)); } +inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((short*)tab, idx)); } + +inline v_int32x4 v_lut(const int* tab, const int* idx) +{ + int CV_DECL_ALIGNED(32) elems[4] = + { + tab[idx[0]], + tab[idx[1]], + tab[idx[2]], + tab[idx[3]] + }; + return v_int32x4(vld1q_s32(elems)); +} +inline v_int32x4 v_lut_pairs(const int* tab, const int* idx) +{ + return v_int32x4(vcombine_s32(vld1_s32(tab + idx[0]), vld1_s32(tab + idx[1]))); +} +inline v_int32x4 v_lut_quads(const int* tab, const int* idx) +{ + return v_int32x4(vld1q_s32(tab + idx[0])); +} +inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((int*)tab, idx)); } +inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((int*)tab, idx)); } +inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((int*)tab, idx)); } + +inline v_int64x2 v_lut(const int64_t* tab, const int* idx) +{ + return v_int64x2(vcombine_s64(vcreate_s64(tab[idx[0]]), vcreate_s64(tab[idx[1]]))); +} +inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx) +{ + return v_int64x2(vld1q_s64(tab + idx[0])); +} +inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); } +inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); } + +inline v_float32x4 v_lut(const float* tab, const int* idx) +{ + float CV_DECL_ALIGNED(32) elems[4] = + { + tab[idx[0]], + tab[idx[1]], + tab[idx[2]], + tab[idx[3]] + }; + return v_float32x4(vld1q_f32(elems)); +} +inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) +{ + uint64 CV_DECL_ALIGNED(32) elems[2] = + { + *(uint64*)(tab + idx[0]), + *(uint64*)(tab + idx[1]) + }; + return v_float32x4(vreinterpretq_f32_u64(vld1q_u64(elems))); +} +inline v_float32x4 v_lut_quads(const float* tab, const int* idx) +{ + return v_float32x4(vld1q_f32(tab + idx[0])); +} + +inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec) +{ + int CV_DECL_ALIGNED(32) elems[4] = + { + tab[vgetq_lane_s32(idxvec.val, 0)], + tab[vgetq_lane_s32(idxvec.val, 1)], + tab[vgetq_lane_s32(idxvec.val, 2)], + tab[vgetq_lane_s32(idxvec.val, 3)] + }; + return v_int32x4(vld1q_s32(elems)); +} + +inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec) +{ + unsigned CV_DECL_ALIGNED(32) elems[4] = + { + tab[vgetq_lane_s32(idxvec.val, 0)], + tab[vgetq_lane_s32(idxvec.val, 1)], + tab[vgetq_lane_s32(idxvec.val, 2)], + tab[vgetq_lane_s32(idxvec.val, 3)] + }; + return v_uint32x4(vld1q_u32(elems)); +} + +inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec) +{ + float CV_DECL_ALIGNED(32) elems[4] = + { + tab[vgetq_lane_s32(idxvec.val, 0)], + tab[vgetq_lane_s32(idxvec.val, 1)], + tab[vgetq_lane_s32(idxvec.val, 2)], + tab[vgetq_lane_s32(idxvec.val, 3)] + }; + return v_float32x4(vld1q_f32(elems)); +} + +inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y) +{ + /*int CV_DECL_ALIGNED(32) idx[4]; + v_store(idx, idxvec); + + float32x4_t xy02 = vcombine_f32(vld1_f32(tab + idx[0]), vld1_f32(tab + idx[2])); + float32x4_t xy13 = vcombine_f32(vld1_f32(tab + idx[1]), vld1_f32(tab + idx[3])); + + float32x4x2_t xxyy = vuzpq_f32(xy02, xy13); + x = v_float32x4(xxyy.val[0]); + y = v_float32x4(xxyy.val[1]);*/ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_aligned(idx, idxvec); + + x = v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); + y = v_float32x4(tab[idx[0]+1], tab[idx[1]+1], tab[idx[2]+1], tab[idx[3]+1]); +} + +inline v_int8x16 v_interleave_pairs(const v_int8x16& vec) +{ + return v_int8x16(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0705060403010200)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0705060403010200)))); +} +inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); } +inline v_int8x16 v_interleave_quads(const v_int8x16& vec) +{ + return v_int8x16(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0703060205010400)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0703060205010400)))); +} +inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_interleave_pairs(const v_int16x8& vec) +{ + return v_int16x8(vreinterpretq_s16_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0706030205040100)), vtbl1_s8(vget_high_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0706030205040100))))); +} +inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); } +inline v_int16x8 v_interleave_quads(const v_int16x8& vec) +{ + int16x4x2_t res = vzip_s16(vget_low_s16(vec.val), vget_high_s16(vec.val)); + return v_int16x8(vcombine_s16(res.val[0], res.val[1])); +} +inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_interleave_pairs(const v_int32x4& vec) +{ + int32x2x2_t res = vzip_s32(vget_low_s32(vec.val), vget_high_s32(vec.val)); + return v_int32x4(vcombine_s32(res.val[0], res.val[1])); +} +inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } +inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } + +inline v_int8x16 v_pack_triplets(const v_int8x16& vec) +{ + return v_int8x16(vextq_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0605040201000000)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0807060504020100))), vdupq_n_s8(0), 2)); +} +inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_pack_triplets(const v_int16x8& vec) +{ + return v_int16x8(vreinterpretq_s16_s8(vextq_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0504030201000000)), vget_high_s8(vreinterpretq_s8_s16(vec.val))), vdupq_n_s8(0), 2))); +} +inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; } +inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; } +inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; } + +#if CV_SIMD128_64F +inline v_float64x2 v_lut(const double* tab, const int* idx) +{ + double CV_DECL_ALIGNED(32) elems[2] = + { + tab[idx[0]], + tab[idx[1]] + }; + return v_float64x2(vld1q_f64(elems)); +} + +inline v_float64x2 v_lut_pairs(const double* tab, const int* idx) +{ + return v_float64x2(vld1q_f64(tab + idx[0])); +} + +inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec) +{ + double CV_DECL_ALIGNED(32) elems[2] = + { + tab[vgetq_lane_s32(idxvec.val, 0)], + tab[vgetq_lane_s32(idxvec.val, 1)], + }; + return v_float64x2(vld1q_f64(elems)); +} + +inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y) +{ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_aligned(idx, idxvec); + + x = v_float64x2(tab[idx[0]], tab[idx[1]]); + y = v_float64x2(tab[idx[0]+1], tab[idx[1]+1]); +} +#endif + +////// FP16 support /////// +#if CV_FP16 +inline v_float32x4 v_load_expand(const float16_t* ptr) +{ + float16x4_t v = + #ifndef vld1_f16 // APPLE compiler defines vld1_f16 as macro + (float16x4_t)vld1_s16((const short*)ptr); + #else + vld1_f16((const __fp16*)ptr); + #endif + return v_float32x4(vcvt_f32_f16(v)); +} + +inline void v_pack_store(float16_t* ptr, const v_float32x4& v) +{ + float16x4_t hv = vcvt_f16_f32(v.val); + + #ifndef vst1_f16 // APPLE compiler defines vst1_f16 as macro + vst1_s16((short*)ptr, (int16x4_t)hv); + #else + vst1_f16((__fp16*)ptr, hv); + #endif +} +#else +inline v_float32x4 v_load_expand(const float16_t* ptr) +{ + const int N = 4; + float buf[N]; + for( int i = 0; i < N; i++ ) buf[i] = (float)ptr[i]; + return v_load(buf); +} + +inline void v_pack_store(float16_t* ptr, const v_float32x4& v) +{ + const int N = 4; + float buf[N]; + v_store(buf, v); + for( int i = 0; i < N; i++ ) ptr[i] = float16_t(buf[i]); +} +#endif + +inline void v_cleanup() {} + +//! @name Check SIMD support +//! @{ +//! @brief Check CPU capability of SIMD operation +static inline bool hasSIMD128() +{ + return (CV_CPU_HAS_SUPPORT_NEON) ? true : false; +} + +//! @} + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_sse.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_sse.hpp new file mode 100644 index 00000000..a5adad04 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_sse.hpp @@ -0,0 +1,3016 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_SSE_HPP +#define OPENCV_HAL_SSE_HPP + +#include +#include "opencv2/core/utility.hpp" + +#define CV_SIMD128 1 +#define CV_SIMD128_64F 1 +#define CV_SIMD128_FP16 0 // no native operations with FP16 type. + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +///////// Types //////////// + +struct v_uint8x16 +{ + typedef uchar lane_type; + typedef __m128i vector_type; + enum { nlanes = 16 }; + + v_uint8x16() : val(_mm_setzero_si128()) {} + explicit v_uint8x16(__m128i v) : val(v) {} + v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7, + uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15) + { + val = _mm_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3, + (char)v4, (char)v5, (char)v6, (char)v7, + (char)v8, (char)v9, (char)v10, (char)v11, + (char)v12, (char)v13, (char)v14, (char)v15); + } + uchar get0() const + { + return (uchar)_mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_int8x16 +{ + typedef schar lane_type; + typedef __m128i vector_type; + enum { nlanes = 16 }; + + v_int8x16() : val(_mm_setzero_si128()) {} + explicit v_int8x16(__m128i v) : val(v) {} + v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7, + schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15) + { + val = _mm_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3, + (char)v4, (char)v5, (char)v6, (char)v7, + (char)v8, (char)v9, (char)v10, (char)v11, + (char)v12, (char)v13, (char)v14, (char)v15); + } + schar get0() const + { + return (schar)_mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_uint16x8 +{ + typedef ushort lane_type; + typedef __m128i vector_type; + enum { nlanes = 8 }; + + v_uint16x8() : val(_mm_setzero_si128()) {} + explicit v_uint16x8(__m128i v) : val(v) {} + v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7) + { + val = _mm_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3, + (short)v4, (short)v5, (short)v6, (short)v7); + } + ushort get0() const + { + return (ushort)_mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_int16x8 +{ + typedef short lane_type; + typedef __m128i vector_type; + enum { nlanes = 8 }; + + v_int16x8() : val(_mm_setzero_si128()) {} + explicit v_int16x8(__m128i v) : val(v) {} + v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7) + { + val = _mm_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3, + (short)v4, (short)v5, (short)v6, (short)v7); + } + short get0() const + { + return (short)_mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_uint32x4 +{ + typedef unsigned lane_type; + typedef __m128i vector_type; + enum { nlanes = 4 }; + + v_uint32x4() : val(_mm_setzero_si128()) {} + explicit v_uint32x4(__m128i v) : val(v) {} + v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3) + { + val = _mm_setr_epi32((int)v0, (int)v1, (int)v2, (int)v3); + } + unsigned get0() const + { + return (unsigned)_mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_int32x4 +{ + typedef int lane_type; + typedef __m128i vector_type; + enum { nlanes = 4 }; + + v_int32x4() : val(_mm_setzero_si128()) {} + explicit v_int32x4(__m128i v) : val(v) {} + v_int32x4(int v0, int v1, int v2, int v3) + { + val = _mm_setr_epi32(v0, v1, v2, v3); + } + int get0() const + { + return _mm_cvtsi128_si32(val); + } + + __m128i val; +}; + +struct v_float32x4 +{ + typedef float lane_type; + typedef __m128 vector_type; + enum { nlanes = 4 }; + + v_float32x4() : val(_mm_setzero_ps()) {} + explicit v_float32x4(__m128 v) : val(v) {} + v_float32x4(float v0, float v1, float v2, float v3) + { + val = _mm_setr_ps(v0, v1, v2, v3); + } + float get0() const + { + return _mm_cvtss_f32(val); + } + + __m128 val; +}; + +struct v_uint64x2 +{ + typedef uint64 lane_type; + typedef __m128i vector_type; + enum { nlanes = 2 }; + + v_uint64x2() : val(_mm_setzero_si128()) {} + explicit v_uint64x2(__m128i v) : val(v) {} + v_uint64x2(uint64 v0, uint64 v1) + { + val = _mm_setr_epi32((int)v0, (int)(v0 >> 32), (int)v1, (int)(v1 >> 32)); + } + uint64 get0() const + { + int a = _mm_cvtsi128_si32(val); + int b = _mm_cvtsi128_si32(_mm_srli_epi64(val, 32)); + return (unsigned)a | ((uint64)(unsigned)b << 32); + } + + __m128i val; +}; + +struct v_int64x2 +{ + typedef int64 lane_type; + typedef __m128i vector_type; + enum { nlanes = 2 }; + + v_int64x2() : val(_mm_setzero_si128()) {} + explicit v_int64x2(__m128i v) : val(v) {} + v_int64x2(int64 v0, int64 v1) + { + val = _mm_setr_epi32((int)v0, (int)(v0 >> 32), (int)v1, (int)(v1 >> 32)); + } + int64 get0() const + { + int a = _mm_cvtsi128_si32(val); + int b = _mm_cvtsi128_si32(_mm_srli_epi64(val, 32)); + return (int64)((unsigned)a | ((uint64)(unsigned)b << 32)); + } + + __m128i val; +}; + +struct v_float64x2 +{ + typedef double lane_type; + typedef __m128d vector_type; + enum { nlanes = 2 }; + + v_float64x2() : val(_mm_setzero_pd()) {} + explicit v_float64x2(__m128d v) : val(v) {} + v_float64x2(double v0, double v1) + { + val = _mm_setr_pd(v0, v1); + } + double get0() const + { + return _mm_cvtsd_f64(val); + } + + __m128d val; +}; + +namespace hal_sse_internal +{ + template + to_sse_type v_sse_reinterpret_as(const from_sse_type& val); + +#define OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(to_sse_type, from_sse_type, sse_cast_intrin) \ + template<> inline \ + to_sse_type v_sse_reinterpret_as(const from_sse_type& a) \ + { return sse_cast_intrin(a); } + + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128i, OPENCV_HAL_NOP) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128, _mm_castps_si128) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128d, _mm_castpd_si128) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128i, _mm_castsi128_ps) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128, OPENCV_HAL_NOP) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128d, _mm_castpd_ps) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128i, _mm_castsi128_pd) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128, _mm_castps_pd) + OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128d, OPENCV_HAL_NOP) +} + +#define OPENCV_HAL_IMPL_SSE_INITVEC(_Tpvec, _Tp, suffix, zsuffix, ssuffix, _Tps, cast) \ +inline _Tpvec v_setzero_##suffix() { return _Tpvec(_mm_setzero_##zsuffix()); } \ +inline _Tpvec v_setall_##suffix(_Tp v) { return _Tpvec(_mm_set1_##ssuffix((_Tps)v)); } \ +template inline _Tpvec v_reinterpret_as_##suffix(const _Tpvec0& a) \ +{ return _Tpvec(cast(a.val)); } + +OPENCV_HAL_IMPL_SSE_INITVEC(v_uint8x16, uchar, u8, si128, epi8, char, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_int8x16, schar, s8, si128, epi8, char, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_uint16x8, ushort, u16, si128, epi16, short, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_int16x8, short, s16, si128, epi16, short, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_uint32x4, unsigned, u32, si128, epi32, int, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_int32x4, int, s32, si128, epi32, int, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_INITVEC(v_float32x4, float, f32, ps, ps, float, _mm_castsi128_ps) +OPENCV_HAL_IMPL_SSE_INITVEC(v_float64x2, double, f64, pd, pd, double, _mm_castsi128_pd) + +inline v_uint64x2 v_setzero_u64() { return v_uint64x2(_mm_setzero_si128()); } +inline v_int64x2 v_setzero_s64() { return v_int64x2(_mm_setzero_si128()); } +inline v_uint64x2 v_setall_u64(uint64 val) { return v_uint64x2(val, val); } +inline v_int64x2 v_setall_s64(int64 val) { return v_int64x2(val, val); } + +template inline +v_uint64x2 v_reinterpret_as_u64(const _Tpvec& a) { return v_uint64x2(a.val); } +template inline +v_int64x2 v_reinterpret_as_s64(const _Tpvec& a) { return v_int64x2(a.val); } +inline v_float32x4 v_reinterpret_as_f32(const v_uint64x2& a) +{ return v_float32x4(_mm_castsi128_ps(a.val)); } +inline v_float32x4 v_reinterpret_as_f32(const v_int64x2& a) +{ return v_float32x4(_mm_castsi128_ps(a.val)); } +inline v_float64x2 v_reinterpret_as_f64(const v_uint64x2& a) +{ return v_float64x2(_mm_castsi128_pd(a.val)); } +inline v_float64x2 v_reinterpret_as_f64(const v_int64x2& a) +{ return v_float64x2(_mm_castsi128_pd(a.val)); } + +#define OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(_Tpvec, suffix) \ +inline _Tpvec v_reinterpret_as_##suffix(const v_float32x4& a) \ +{ return _Tpvec(_mm_castps_si128(a.val)); } \ +inline _Tpvec v_reinterpret_as_##suffix(const v_float64x2& a) \ +{ return _Tpvec(_mm_castpd_si128(a.val)); } + +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint8x16, u8) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int8x16, s8) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint16x8, u16) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int16x8, s16) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint32x4, u32) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int32x4, s32) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint64x2, u64) +OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int64x2, s64) + +inline v_float32x4 v_reinterpret_as_f32(const v_float32x4& a) {return a; } +inline v_float64x2 v_reinterpret_as_f64(const v_float64x2& a) {return a; } +inline v_float32x4 v_reinterpret_as_f32(const v_float64x2& a) {return v_float32x4(_mm_castpd_ps(a.val)); } +inline v_float64x2 v_reinterpret_as_f64(const v_float32x4& a) {return v_float64x2(_mm_castps_pd(a.val)); } + +//////////////// PACK /////////////// +inline v_uint8x16 v_pack(const v_uint16x8& a, const v_uint16x8& b) +{ + __m128i delta = _mm_set1_epi16(255); + return v_uint8x16(_mm_packus_epi16(_mm_subs_epu16(a.val, _mm_subs_epu16(a.val, delta)), + _mm_subs_epu16(b.val, _mm_subs_epu16(b.val, delta)))); +} + +inline void v_pack_store(uchar* ptr, const v_uint16x8& a) +{ + __m128i delta = _mm_set1_epi16(255); + __m128i a1 = _mm_subs_epu16(a.val, _mm_subs_epu16(a.val, delta)); + _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1)); +} + +inline v_uint8x16 v_pack_u(const v_int16x8& a, const v_int16x8& b) +{ return v_uint8x16(_mm_packus_epi16(a.val, b.val)); } + +inline void v_pack_u_store(uchar* ptr, const v_int16x8& a) +{ _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a.val, a.val)); } + +template inline +v_uint8x16 v_rshr_pack(const v_uint16x8& a, const v_uint16x8& b) +{ + // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers. + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + return v_uint8x16(_mm_packus_epi16(_mm_srli_epi16(_mm_adds_epu16(a.val, delta), n), + _mm_srli_epi16(_mm_adds_epu16(b.val, delta), n))); +} + +template inline +void v_rshr_pack_store(uchar* ptr, const v_uint16x8& a) +{ + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + __m128i a1 = _mm_srli_epi16(_mm_adds_epu16(a.val, delta), n); + _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1)); +} + +template inline +v_uint8x16 v_rshr_pack_u(const v_int16x8& a, const v_int16x8& b) +{ + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + return v_uint8x16(_mm_packus_epi16(_mm_srai_epi16(_mm_adds_epi16(a.val, delta), n), + _mm_srai_epi16(_mm_adds_epi16(b.val, delta), n))); +} + +template inline +void v_rshr_pack_u_store(uchar* ptr, const v_int16x8& a) +{ + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + __m128i a1 = _mm_srai_epi16(_mm_adds_epi16(a.val, delta), n); + _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1)); +} + +inline v_int8x16 v_pack(const v_int16x8& a, const v_int16x8& b) +{ return v_int8x16(_mm_packs_epi16(a.val, b.val)); } + +inline void v_pack_store(schar* ptr, const v_int16x8& a) +{ _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi16(a.val, a.val)); } + +template inline +v_int8x16 v_rshr_pack(const v_int16x8& a, const v_int16x8& b) +{ + // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers. + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + return v_int8x16(_mm_packs_epi16(_mm_srai_epi16(_mm_adds_epi16(a.val, delta), n), + _mm_srai_epi16(_mm_adds_epi16(b.val, delta), n))); +} +template inline +void v_rshr_pack_store(schar* ptr, const v_int16x8& a) +{ + // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers. + __m128i delta = _mm_set1_epi16((short)(1 << (n-1))); + __m128i a1 = _mm_srai_epi16(_mm_adds_epi16(a.val, delta), n); + _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi16(a1, a1)); +} + + +// byte-wise "mask ? a : b" +inline __m128i v_select_si128(__m128i mask, __m128i a, __m128i b) +{ +#if CV_SSE4_1 + return _mm_blendv_epi8(b, a, mask); +#else + return _mm_xor_si128(b, _mm_and_si128(_mm_xor_si128(a, b), mask)); +#endif +} + +inline v_uint16x8 v_pack(const v_uint32x4& a, const v_uint32x4& b) +{ return v_uint16x8(_v128_packs_epu32(a.val, b.val)); } + +inline void v_pack_store(ushort* ptr, const v_uint32x4& a) +{ + __m128i z = _mm_setzero_si128(), maxval32 = _mm_set1_epi32(65535), delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(v_select_si128(_mm_cmpgt_epi32(z, a.val), maxval32, a.val), delta32); + __m128i r = _mm_packs_epi32(a1, a1); + _mm_storel_epi64((__m128i*)ptr, _mm_sub_epi16(r, _mm_set1_epi16(-32768))); +} + +template inline +v_uint16x8 v_rshr_pack(const v_uint32x4& a, const v_uint32x4& b) +{ + __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(a.val, delta), n), delta32); + __m128i b1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(b.val, delta), n), delta32); + return v_uint16x8(_mm_sub_epi16(_mm_packs_epi32(a1, b1), _mm_set1_epi16(-32768))); +} + +template inline +void v_rshr_pack_store(ushort* ptr, const v_uint32x4& a) +{ + __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(a.val, delta), n), delta32); + __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768)); + _mm_storel_epi64((__m128i*)ptr, a2); +} + +inline v_uint16x8 v_pack_u(const v_int32x4& a, const v_int32x4& b) +{ +#if CV_SSE4_1 + return v_uint16x8(_mm_packus_epi32(a.val, b.val)); +#else + __m128i delta32 = _mm_set1_epi32(32768); + + // preliminary saturate negative values to zero + __m128i a1 = _mm_and_si128(a.val, _mm_cmpgt_epi32(a.val, _mm_set1_epi32(0))); + __m128i b1 = _mm_and_si128(b.val, _mm_cmpgt_epi32(b.val, _mm_set1_epi32(0))); + + __m128i r = _mm_packs_epi32(_mm_sub_epi32(a1, delta32), _mm_sub_epi32(b1, delta32)); + return v_uint16x8(_mm_sub_epi16(r, _mm_set1_epi16(-32768))); +#endif +} + +inline void v_pack_u_store(ushort* ptr, const v_int32x4& a) +{ +#if CV_SSE4_1 + _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi32(a.val, a.val)); +#else + __m128i delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(a.val, delta32); + __m128i r = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768)); + _mm_storel_epi64((__m128i*)ptr, r); +#endif +} + +template inline +v_uint16x8 v_rshr_pack_u(const v_int32x4& a, const v_int32x4& b) +{ +#if CV_SSE4_1 + __m128i delta = _mm_set1_epi32(1 << (n - 1)); + return v_uint16x8(_mm_packus_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), + _mm_srai_epi32(_mm_add_epi32(b.val, delta), n))); +#else + __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), delta32); + __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768)); + __m128i b1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(b.val, delta), n), delta32); + __m128i b2 = _mm_sub_epi16(_mm_packs_epi32(b1, b1), _mm_set1_epi16(-32768)); + return v_uint16x8(_mm_unpacklo_epi64(a2, b2)); +#endif +} + +template inline +void v_rshr_pack_u_store(ushort* ptr, const v_int32x4& a) +{ +#if CV_SSE4_1 + __m128i delta = _mm_set1_epi32(1 << (n - 1)); + __m128i a1 = _mm_srai_epi32(_mm_add_epi32(a.val, delta), n); + _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi32(a1, a1)); +#else + __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768); + __m128i a1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), delta32); + __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768)); + _mm_storel_epi64((__m128i*)ptr, a2); +#endif +} + +inline v_int16x8 v_pack(const v_int32x4& a, const v_int32x4& b) +{ return v_int16x8(_mm_packs_epi32(a.val, b.val)); } + +inline void v_pack_store(short* ptr, const v_int32x4& a) +{ + _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi32(a.val, a.val)); +} + +template inline +v_int16x8 v_rshr_pack(const v_int32x4& a, const v_int32x4& b) +{ + __m128i delta = _mm_set1_epi32(1 << (n-1)); + return v_int16x8(_mm_packs_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), + _mm_srai_epi32(_mm_add_epi32(b.val, delta), n))); +} + +template inline +void v_rshr_pack_store(short* ptr, const v_int32x4& a) +{ + __m128i delta = _mm_set1_epi32(1 << (n-1)); + __m128i a1 = _mm_srai_epi32(_mm_add_epi32(a.val, delta), n); + _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi32(a1, a1)); +} + + +// [a0 0 | b0 0] [a1 0 | b1 0] +inline v_uint32x4 v_pack(const v_uint64x2& a, const v_uint64x2& b) +{ + __m128i v0 = _mm_unpacklo_epi32(a.val, b.val); // a0 a1 0 0 + __m128i v1 = _mm_unpackhi_epi32(a.val, b.val); // b0 b1 0 0 + return v_uint32x4(_mm_unpacklo_epi32(v0, v1)); +} + +inline void v_pack_store(unsigned* ptr, const v_uint64x2& a) +{ + __m128i a1 = _mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 2, 2, 0)); + _mm_storel_epi64((__m128i*)ptr, a1); +} + +// [a0 0 | b0 0] [a1 0 | b1 0] +inline v_int32x4 v_pack(const v_int64x2& a, const v_int64x2& b) +{ + __m128i v0 = _mm_unpacklo_epi32(a.val, b.val); // a0 a1 0 0 + __m128i v1 = _mm_unpackhi_epi32(a.val, b.val); // b0 b1 0 0 + return v_int32x4(_mm_unpacklo_epi32(v0, v1)); +} + +inline void v_pack_store(int* ptr, const v_int64x2& a) +{ + __m128i a1 = _mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 2, 2, 0)); + _mm_storel_epi64((__m128i*)ptr, a1); +} + +template inline +v_uint32x4 v_rshr_pack(const v_uint64x2& a, const v_uint64x2& b) +{ + uint64 delta = (uint64)1 << (n-1); + v_uint64x2 delta2(delta, delta); + __m128i a1 = _mm_srli_epi64(_mm_add_epi64(a.val, delta2.val), n); + __m128i b1 = _mm_srli_epi64(_mm_add_epi64(b.val, delta2.val), n); + __m128i v0 = _mm_unpacklo_epi32(a1, b1); // a0 a1 0 0 + __m128i v1 = _mm_unpackhi_epi32(a1, b1); // b0 b1 0 0 + return v_uint32x4(_mm_unpacklo_epi32(v0, v1)); +} + +template inline +void v_rshr_pack_store(unsigned* ptr, const v_uint64x2& a) +{ + uint64 delta = (uint64)1 << (n-1); + v_uint64x2 delta2(delta, delta); + __m128i a1 = _mm_srli_epi64(_mm_add_epi64(a.val, delta2.val), n); + __m128i a2 = _mm_shuffle_epi32(a1, _MM_SHUFFLE(0, 2, 2, 0)); + _mm_storel_epi64((__m128i*)ptr, a2); +} + +inline __m128i v_sign_epi64(__m128i a) +{ + return _mm_shuffle_epi32(_mm_srai_epi32(a, 31), _MM_SHUFFLE(3, 3, 1, 1)); // x m0 | x m1 +} + +inline __m128i v_srai_epi64(__m128i a, int imm) +{ + __m128i smask = v_sign_epi64(a); + return _mm_xor_si128(_mm_srli_epi64(_mm_xor_si128(a, smask), imm), smask); +} + +template inline +v_int32x4 v_rshr_pack(const v_int64x2& a, const v_int64x2& b) +{ + int64 delta = (int64)1 << (n-1); + v_int64x2 delta2(delta, delta); + __m128i a1 = v_srai_epi64(_mm_add_epi64(a.val, delta2.val), n); + __m128i b1 = v_srai_epi64(_mm_add_epi64(b.val, delta2.val), n); + __m128i v0 = _mm_unpacklo_epi32(a1, b1); // a0 a1 0 0 + __m128i v1 = _mm_unpackhi_epi32(a1, b1); // b0 b1 0 0 + return v_int32x4(_mm_unpacklo_epi32(v0, v1)); +} + +template inline +void v_rshr_pack_store(int* ptr, const v_int64x2& a) +{ + int64 delta = (int64)1 << (n-1); + v_int64x2 delta2(delta, delta); + __m128i a1 = v_srai_epi64(_mm_add_epi64(a.val, delta2.val), n); + __m128i a2 = _mm_shuffle_epi32(a1, _MM_SHUFFLE(0, 2, 2, 0)); + _mm_storel_epi64((__m128i*)ptr, a2); +} + +// pack boolean +inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b) +{ + __m128i ab = _mm_packs_epi16(a.val, b.val); + return v_uint8x16(ab); +} + +inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, const v_uint32x4& d) +{ + __m128i ab = _mm_packs_epi32(a.val, b.val); + __m128i cd = _mm_packs_epi32(c.val, d.val); + return v_uint8x16(_mm_packs_epi16(ab, cd)); +} + +inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c, + const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f, + const v_uint64x2& g, const v_uint64x2& h) +{ + __m128i ab = _mm_packs_epi32(a.val, b.val); + __m128i cd = _mm_packs_epi32(c.val, d.val); + __m128i ef = _mm_packs_epi32(e.val, f.val); + __m128i gh = _mm_packs_epi32(g.val, h.val); + + __m128i abcd = _mm_packs_epi32(ab, cd); + __m128i efgh = _mm_packs_epi32(ef, gh); + return v_uint8x16(_mm_packs_epi16(abcd, efgh)); +} + +inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& m3) +{ + __m128 v0 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(0, 0, 0, 0)), m0.val); + __m128 v1 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(1, 1, 1, 1)), m1.val); + __m128 v2 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(2, 2, 2, 2)), m2.val); + __m128 v3 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(3, 3, 3, 3)), m3.val); + + return v_float32x4(_mm_add_ps(_mm_add_ps(v0, v1), _mm_add_ps(v2, v3))); +} + +inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& a) +{ + __m128 v0 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(0, 0, 0, 0)), m0.val); + __m128 v1 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(1, 1, 1, 1)), m1.val); + __m128 v2 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(2, 2, 2, 2)), m2.val); + + return v_float32x4(_mm_add_ps(_mm_add_ps(v0, v1), _mm_add_ps(v2, a.val))); +} + +#define OPENCV_HAL_IMPL_SSE_BIN_OP(bin_op, _Tpvec, intrin) \ + inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \ + { \ + return _Tpvec(intrin(a.val, b.val)); \ + } \ + inline _Tpvec& operator bin_op##= (_Tpvec& a, const _Tpvec& b) \ + { \ + a.val = intrin(a.val, b.val); \ + return a; \ + } + +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_uint8x16, _mm_adds_epu8) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_uint8x16, _mm_subs_epu8) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_int8x16, _mm_adds_epi8) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_int8x16, _mm_subs_epi8) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_uint16x8, _mm_adds_epu16) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_uint16x8, _mm_subs_epu16) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_int16x8, _mm_adds_epi16) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_int16x8, _mm_subs_epi16) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_uint32x4, _mm_add_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_uint32x4, _mm_sub_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(*, v_uint32x4, _v128_mullo_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_int32x4, _mm_add_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_int32x4, _mm_sub_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(*, v_int32x4, _v128_mullo_epi32) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_float32x4, _mm_add_ps) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_float32x4, _mm_sub_ps) +OPENCV_HAL_IMPL_SSE_BIN_OP(*, v_float32x4, _mm_mul_ps) +OPENCV_HAL_IMPL_SSE_BIN_OP(/, v_float32x4, _mm_div_ps) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_float64x2, _mm_add_pd) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_float64x2, _mm_sub_pd) +OPENCV_HAL_IMPL_SSE_BIN_OP(*, v_float64x2, _mm_mul_pd) +OPENCV_HAL_IMPL_SSE_BIN_OP(/, v_float64x2, _mm_div_pd) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_uint64x2, _mm_add_epi64) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_uint64x2, _mm_sub_epi64) +OPENCV_HAL_IMPL_SSE_BIN_OP(+, v_int64x2, _mm_add_epi64) +OPENCV_HAL_IMPL_SSE_BIN_OP(-, v_int64x2, _mm_sub_epi64) + +// saturating multiply 8-bit, 16-bit +#define OPENCV_HAL_IMPL_SSE_MUL_SAT(_Tpvec, _Tpwvec) \ + inline _Tpvec operator * (const _Tpvec& a, const _Tpvec& b) \ + { \ + _Tpwvec c, d; \ + v_mul_expand(a, b, c, d); \ + return v_pack(c, d); \ + } \ + inline _Tpvec& operator *= (_Tpvec& a, const _Tpvec& b) \ + { a = a * b; return a; } + +OPENCV_HAL_IMPL_SSE_MUL_SAT(v_uint8x16, v_uint16x8) +OPENCV_HAL_IMPL_SSE_MUL_SAT(v_int8x16, v_int16x8) +OPENCV_HAL_IMPL_SSE_MUL_SAT(v_uint16x8, v_uint32x4) +OPENCV_HAL_IMPL_SSE_MUL_SAT(v_int16x8, v_int32x4) + +// Multiply and expand +inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b, + v_uint16x8& c, v_uint16x8& d) +{ + v_uint16x8 a0, a1, b0, b1; + v_expand(a, a0, a1); + v_expand(b, b0, b1); + c = v_mul_wrap(a0, b0); + d = v_mul_wrap(a1, b1); +} + +inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b, + v_int16x8& c, v_int16x8& d) +{ + v_int16x8 a0, a1, b0, b1; + v_expand(a, a0, a1); + v_expand(b, b0, b1); + c = v_mul_wrap(a0, b0); + d = v_mul_wrap(a1, b1); +} + +inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b, + v_int32x4& c, v_int32x4& d) +{ + __m128i v0 = _mm_mullo_epi16(a.val, b.val); + __m128i v1 = _mm_mulhi_epi16(a.val, b.val); + c.val = _mm_unpacklo_epi16(v0, v1); + d.val = _mm_unpackhi_epi16(v0, v1); +} + +inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b, + v_uint32x4& c, v_uint32x4& d) +{ + __m128i v0 = _mm_mullo_epi16(a.val, b.val); + __m128i v1 = _mm_mulhi_epu16(a.val, b.val); + c.val = _mm_unpacklo_epi16(v0, v1); + d.val = _mm_unpackhi_epi16(v0, v1); +} + +inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b, + v_uint64x2& c, v_uint64x2& d) +{ + __m128i c0 = _mm_mul_epu32(a.val, b.val); + __m128i c1 = _mm_mul_epu32(_mm_srli_epi64(a.val, 32), _mm_srli_epi64(b.val, 32)); + c.val = _mm_unpacklo_epi64(c0, c1); + d.val = _mm_unpackhi_epi64(c0, c1); +} + +inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b) { return v_int16x8(_mm_mulhi_epi16(a.val, b.val)); } +inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b) { return v_uint16x8(_mm_mulhi_epu16(a.val, b.val)); } + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b) +{ + return v_int32x4(_mm_madd_epi16(a.val, b.val)); +} + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c) +{ + return v_int32x4(_mm_add_epi32(_mm_madd_epi16(a.val, b.val), c.val)); +} + +#define OPENCV_HAL_IMPL_SSE_LOGIC_OP(_Tpvec, suffix, not_const) \ + OPENCV_HAL_IMPL_SSE_BIN_OP(&, _Tpvec, _mm_and_##suffix) \ + OPENCV_HAL_IMPL_SSE_BIN_OP(|, _Tpvec, _mm_or_##suffix) \ + OPENCV_HAL_IMPL_SSE_BIN_OP(^, _Tpvec, _mm_xor_##suffix) \ + inline _Tpvec operator ~ (const _Tpvec& a) \ + { \ + return _Tpvec(_mm_xor_##suffix(a.val, not_const)); \ + } + +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint8x16, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int8x16, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint16x8, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int16x8, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint32x4, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int32x4, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint64x2, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int64x2, si128, _mm_set1_epi32(-1)) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_float32x4, ps, _mm_castsi128_ps(_mm_set1_epi32(-1))) +OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_float64x2, pd, _mm_castsi128_pd(_mm_set1_epi32(-1))) + +inline v_float32x4 v_sqrt(const v_float32x4& x) +{ return v_float32x4(_mm_sqrt_ps(x.val)); } + +inline v_float32x4 v_invsqrt(const v_float32x4& x) +{ + const __m128 _0_5 = _mm_set1_ps(0.5f), _1_5 = _mm_set1_ps(1.5f); + __m128 t = x.val; + __m128 h = _mm_mul_ps(t, _0_5); + t = _mm_rsqrt_ps(t); + t = _mm_mul_ps(t, _mm_sub_ps(_1_5, _mm_mul_ps(_mm_mul_ps(t, t), h))); + return v_float32x4(t); +} + +inline v_float64x2 v_sqrt(const v_float64x2& x) +{ return v_float64x2(_mm_sqrt_pd(x.val)); } + +inline v_float64x2 v_invsqrt(const v_float64x2& x) +{ + const __m128d v_1 = _mm_set1_pd(1.); + return v_float64x2(_mm_div_pd(v_1, _mm_sqrt_pd(x.val))); +} + +#define OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(_Tpuvec, _Tpsvec, func, suffix, subWidth) \ +inline _Tpuvec v_abs(const _Tpsvec& x) \ +{ return _Tpuvec(_mm_##func##_ep##suffix(x.val, _mm_sub_ep##subWidth(_mm_setzero_si128(), x.val))); } + +OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(v_uint8x16, v_int8x16, min, u8, i8) +OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(v_uint16x8, v_int16x8, max, i16, i16) +inline v_uint32x4 v_abs(const v_int32x4& x) +{ + __m128i s = _mm_srli_epi32(x.val, 31); + __m128i f = _mm_srai_epi32(x.val, 31); + return v_uint32x4(_mm_add_epi32(_mm_xor_si128(x.val, f), s)); +} +inline v_float32x4 v_abs(const v_float32x4& x) +{ return v_float32x4(_mm_and_ps(x.val, _mm_castsi128_ps(_mm_set1_epi32(0x7fffffff)))); } +inline v_float64x2 v_abs(const v_float64x2& x) +{ + return v_float64x2(_mm_and_pd(x.val, + _mm_castsi128_pd(_mm_srli_epi64(_mm_set1_epi32(-1), 1)))); +} + +// TODO: exp, log, sin, cos + +#define OPENCV_HAL_IMPL_SSE_BIN_FUNC(_Tpvec, func, intrin) \ +inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(intrin(a.val, b.val)); \ +} + +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_min, _mm_min_epu8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_max, _mm_max_epu8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_min, _mm_min_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_max, _mm_max_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float32x4, v_min, _mm_min_ps) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float32x4, v_max, _mm_max_ps) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float64x2, v_min, _mm_min_pd) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float64x2, v_max, _mm_max_pd) + +inline v_int8x16 v_min(const v_int8x16& a, const v_int8x16& b) +{ +#if CV_SSE4_1 + return v_int8x16(_mm_min_epi8(a.val, b.val)); +#else + __m128i delta = _mm_set1_epi8((char)-128); + return v_int8x16(_mm_xor_si128(delta, _mm_min_epu8(_mm_xor_si128(a.val, delta), + _mm_xor_si128(b.val, delta)))); +#endif +} +inline v_int8x16 v_max(const v_int8x16& a, const v_int8x16& b) +{ +#if CV_SSE4_1 + return v_int8x16(_mm_max_epi8(a.val, b.val)); +#else + __m128i delta = _mm_set1_epi8((char)-128); + return v_int8x16(_mm_xor_si128(delta, _mm_max_epu8(_mm_xor_si128(a.val, delta), + _mm_xor_si128(b.val, delta)))); +#endif +} +inline v_uint16x8 v_min(const v_uint16x8& a, const v_uint16x8& b) +{ +#if CV_SSE4_1 + return v_uint16x8(_mm_min_epu16(a.val, b.val)); +#else + return v_uint16x8(_mm_subs_epu16(a.val, _mm_subs_epu16(a.val, b.val))); +#endif +} +inline v_uint16x8 v_max(const v_uint16x8& a, const v_uint16x8& b) +{ +#if CV_SSE4_1 + return v_uint16x8(_mm_max_epu16(a.val, b.val)); +#else + return v_uint16x8(_mm_adds_epu16(_mm_subs_epu16(a.val, b.val), b.val)); +#endif +} +inline v_uint32x4 v_min(const v_uint32x4& a, const v_uint32x4& b) +{ +#if CV_SSE4_1 + return v_uint32x4(_mm_min_epu32(a.val, b.val)); +#else + __m128i delta = _mm_set1_epi32((int)0x80000000); + __m128i mask = _mm_cmpgt_epi32(_mm_xor_si128(a.val, delta), _mm_xor_si128(b.val, delta)); + return v_uint32x4(v_select_si128(mask, b.val, a.val)); +#endif +} +inline v_uint32x4 v_max(const v_uint32x4& a, const v_uint32x4& b) +{ +#if CV_SSE4_1 + return v_uint32x4(_mm_max_epu32(a.val, b.val)); +#else + __m128i delta = _mm_set1_epi32((int)0x80000000); + __m128i mask = _mm_cmpgt_epi32(_mm_xor_si128(a.val, delta), _mm_xor_si128(b.val, delta)); + return v_uint32x4(v_select_si128(mask, a.val, b.val)); +#endif +} +inline v_int32x4 v_min(const v_int32x4& a, const v_int32x4& b) +{ +#if CV_SSE4_1 + return v_int32x4(_mm_min_epi32(a.val, b.val)); +#else + return v_int32x4(v_select_si128(_mm_cmpgt_epi32(a.val, b.val), b.val, a.val)); +#endif +} +inline v_int32x4 v_max(const v_int32x4& a, const v_int32x4& b) +{ +#if CV_SSE4_1 + return v_int32x4(_mm_max_epi32(a.val, b.val)); +#else + return v_int32x4(v_select_si128(_mm_cmpgt_epi32(a.val, b.val), a.val, b.val)); +#endif +} + +#define OPENCV_HAL_IMPL_SSE_INT_CMP_OP(_Tpuvec, _Tpsvec, suffix, sbit) \ +inline _Tpuvec operator == (const _Tpuvec& a, const _Tpuvec& b) \ +{ return _Tpuvec(_mm_cmpeq_##suffix(a.val, b.val)); } \ +inline _Tpuvec operator != (const _Tpuvec& a, const _Tpuvec& b) \ +{ \ + __m128i not_mask = _mm_set1_epi32(-1); \ + return _Tpuvec(_mm_xor_si128(_mm_cmpeq_##suffix(a.val, b.val), not_mask)); \ +} \ +inline _Tpsvec operator == (const _Tpsvec& a, const _Tpsvec& b) \ +{ return _Tpsvec(_mm_cmpeq_##suffix(a.val, b.val)); } \ +inline _Tpsvec operator != (const _Tpsvec& a, const _Tpsvec& b) \ +{ \ + __m128i not_mask = _mm_set1_epi32(-1); \ + return _Tpsvec(_mm_xor_si128(_mm_cmpeq_##suffix(a.val, b.val), not_mask)); \ +} \ +inline _Tpuvec operator < (const _Tpuvec& a, const _Tpuvec& b) \ +{ \ + __m128i smask = _mm_set1_##suffix(sbit); \ + return _Tpuvec(_mm_cmpgt_##suffix(_mm_xor_si128(b.val, smask), _mm_xor_si128(a.val, smask))); \ +} \ +inline _Tpuvec operator > (const _Tpuvec& a, const _Tpuvec& b) \ +{ \ + __m128i smask = _mm_set1_##suffix(sbit); \ + return _Tpuvec(_mm_cmpgt_##suffix(_mm_xor_si128(a.val, smask), _mm_xor_si128(b.val, smask))); \ +} \ +inline _Tpuvec operator <= (const _Tpuvec& a, const _Tpuvec& b) \ +{ \ + __m128i smask = _mm_set1_##suffix(sbit); \ + __m128i not_mask = _mm_set1_epi32(-1); \ + __m128i res = _mm_cmpgt_##suffix(_mm_xor_si128(a.val, smask), _mm_xor_si128(b.val, smask)); \ + return _Tpuvec(_mm_xor_si128(res, not_mask)); \ +} \ +inline _Tpuvec operator >= (const _Tpuvec& a, const _Tpuvec& b) \ +{ \ + __m128i smask = _mm_set1_##suffix(sbit); \ + __m128i not_mask = _mm_set1_epi32(-1); \ + __m128i res = _mm_cmpgt_##suffix(_mm_xor_si128(b.val, smask), _mm_xor_si128(a.val, smask)); \ + return _Tpuvec(_mm_xor_si128(res, not_mask)); \ +} \ +inline _Tpsvec operator < (const _Tpsvec& a, const _Tpsvec& b) \ +{ \ + return _Tpsvec(_mm_cmpgt_##suffix(b.val, a.val)); \ +} \ +inline _Tpsvec operator > (const _Tpsvec& a, const _Tpsvec& b) \ +{ \ + return _Tpsvec(_mm_cmpgt_##suffix(a.val, b.val)); \ +} \ +inline _Tpsvec operator <= (const _Tpsvec& a, const _Tpsvec& b) \ +{ \ + __m128i not_mask = _mm_set1_epi32(-1); \ + return _Tpsvec(_mm_xor_si128(_mm_cmpgt_##suffix(a.val, b.val), not_mask)); \ +} \ +inline _Tpsvec operator >= (const _Tpsvec& a, const _Tpsvec& b) \ +{ \ + __m128i not_mask = _mm_set1_epi32(-1); \ + return _Tpsvec(_mm_xor_si128(_mm_cmpgt_##suffix(b.val, a.val), not_mask)); \ +} + +OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint8x16, v_int8x16, epi8, (char)-128) +OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint16x8, v_int16x8, epi16, (short)-32768) +OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint32x4, v_int32x4, epi32, (int)0x80000000) + +#define OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(_Tpvec, suffix) \ +inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmpeq_##suffix(a.val, b.val)); } \ +inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmpneq_##suffix(a.val, b.val)); } \ +inline _Tpvec operator < (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmplt_##suffix(a.val, b.val)); } \ +inline _Tpvec operator > (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmpgt_##suffix(a.val, b.val)); } \ +inline _Tpvec operator <= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmple_##suffix(a.val, b.val)); } \ +inline _Tpvec operator >= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(_mm_cmpge_##suffix(a.val, b.val)); } + +OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(v_float32x4, ps) +OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(v_float64x2, pd) + +#define OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(_Tpvec, cast) \ +inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \ +{ return cast(v_reinterpret_as_f64(a) == v_reinterpret_as_f64(b)); } \ +inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ +{ return cast(v_reinterpret_as_f64(a) != v_reinterpret_as_f64(b)); } + +OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_uint64x2, v_reinterpret_as_u64) +OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_int64x2, v_reinterpret_as_s64) + +inline v_float32x4 v_not_nan(const v_float32x4& a) +{ return v_float32x4(_mm_cmpord_ps(a.val, a.val)); } +inline v_float64x2 v_not_nan(const v_float64x2& a) +{ return v_float64x2(_mm_cmpord_pd(a.val, a.val)); } + +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_add_wrap, _mm_add_epi8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_add_wrap, _mm_add_epi8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_add_wrap, _mm_add_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_add_wrap, _mm_add_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_sub_wrap, _mm_sub_epi8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_sub_wrap, _mm_sub_epi8) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_sub_wrap, _mm_sub_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_sub_wrap, _mm_sub_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_mul_wrap, _mm_mullo_epi16) +OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_mul_wrap, _mm_mullo_epi16) + +inline v_uint8x16 v_mul_wrap(const v_uint8x16& a, const v_uint8x16& b) +{ + __m128i ad = _mm_srai_epi16(a.val, 8); + __m128i bd = _mm_srai_epi16(b.val, 8); + __m128i p0 = _mm_mullo_epi16(a.val, b.val); // even + __m128i p1 = _mm_slli_epi16(_mm_mullo_epi16(ad, bd), 8); // odd + const __m128i b01 = _mm_set1_epi32(0xFF00FF00); + return v_uint8x16(_v128_blendv_epi8(p0, p1, b01)); +} +inline v_int8x16 v_mul_wrap(const v_int8x16& a, const v_int8x16& b) +{ + return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b))); +} + +/** Absolute difference **/ + +inline v_uint8x16 v_absdiff(const v_uint8x16& a, const v_uint8x16& b) +{ return v_add_wrap(a - b, b - a); } +inline v_uint16x8 v_absdiff(const v_uint16x8& a, const v_uint16x8& b) +{ return v_add_wrap(a - b, b - a); } +inline v_uint32x4 v_absdiff(const v_uint32x4& a, const v_uint32x4& b) +{ return v_max(a, b) - v_min(a, b); } + +inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b) +{ + v_int8x16 d = v_sub_wrap(a, b); + v_int8x16 m = a < b; + return v_reinterpret_as_u8(v_sub_wrap(d ^ m, m)); +} +inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b) +{ + return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); +} +inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b) +{ + v_int32x4 d = a - b; + v_int32x4 m = a < b; + return v_reinterpret_as_u32((d ^ m) - m); +} + +/** Saturating absolute difference **/ +inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b) +{ + v_int8x16 d = a - b; + v_int8x16 m = a < b; + return (d ^ m) - m; + } +inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b) +{ return v_max(a, b) - v_min(a, b); } + + +inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c) +{ + return a * b + c; +} + +inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c) +{ + return v_fma(a, b, c); +} + +inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c) +{ +#if CV_FMA3 + return v_float32x4(_mm_fmadd_ps(a.val, b.val, c.val)); +#else + return v_float32x4(_mm_add_ps(_mm_mul_ps(a.val, b.val), c.val)); +#endif +} + +inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c) +{ +#if CV_FMA3 + return v_float64x2(_mm_fmadd_pd(a.val, b.val, c.val)); +#else + return v_float64x2(_mm_add_pd(_mm_mul_pd(a.val, b.val), c.val)); +#endif +} + +#define OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(_Tpvec, _Tp, _Tpreg, suffix, absmask_vec) \ +inline _Tpvec v_absdiff(const _Tpvec& a, const _Tpvec& b) \ +{ \ + _Tpreg absmask = _mm_castsi128_##suffix(absmask_vec); \ + return _Tpvec(_mm_and_##suffix(_mm_sub_##suffix(a.val, b.val), absmask)); \ +} \ +inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b) \ +{ \ + _Tpvec res = v_fma(a, a, b*b); \ + return _Tpvec(_mm_sqrt_##suffix(res.val)); \ +} \ +inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b) \ +{ \ + return v_fma(a, a, b*b); \ +} \ +inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \ +{ \ + return v_fma(a, b, c); \ +} + +OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(v_float32x4, float, __m128, ps, _mm_set1_epi32((int)0x7fffffff)) +OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(v_float64x2, double, __m128d, pd, _mm_srli_epi64(_mm_set1_epi32(-1), 1)) + +#define OPENCV_HAL_IMPL_SSE_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai) \ +inline _Tpuvec operator << (const _Tpuvec& a, int imm) \ +{ \ + return _Tpuvec(_mm_slli_##suffix(a.val, imm)); \ +} \ +inline _Tpsvec operator << (const _Tpsvec& a, int imm) \ +{ \ + return _Tpsvec(_mm_slli_##suffix(a.val, imm)); \ +} \ +inline _Tpuvec operator >> (const _Tpuvec& a, int imm) \ +{ \ + return _Tpuvec(_mm_srli_##suffix(a.val, imm)); \ +} \ +inline _Tpsvec operator >> (const _Tpsvec& a, int imm) \ +{ \ + return _Tpsvec(srai(a.val, imm)); \ +} \ +template \ +inline _Tpuvec v_shl(const _Tpuvec& a) \ +{ \ + return _Tpuvec(_mm_slli_##suffix(a.val, imm)); \ +} \ +template \ +inline _Tpsvec v_shl(const _Tpsvec& a) \ +{ \ + return _Tpsvec(_mm_slli_##suffix(a.val, imm)); \ +} \ +template \ +inline _Tpuvec v_shr(const _Tpuvec& a) \ +{ \ + return _Tpuvec(_mm_srli_##suffix(a.val, imm)); \ +} \ +template \ +inline _Tpsvec v_shr(const _Tpsvec& a) \ +{ \ + return _Tpsvec(srai(a.val, imm)); \ +} + +OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint16x8, v_int16x8, epi16, _mm_srai_epi16) +OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint32x4, v_int32x4, epi32, _mm_srai_epi32) +OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint64x2, v_int64x2, epi64, v_srai_epi64) + +namespace hal_sse_internal +{ + template 16)), + bool is_first = (imm == 0), + bool is_half = (imm == 8), + bool is_second = (imm == 16), + bool is_other = (((imm > 0) && (imm < 8)) || ((imm > 8) && (imm < 16)))> + class v_sse_palignr_u8_class; + + template + class v_sse_palignr_u8_class; + + template + class v_sse_palignr_u8_class + { + public: + inline __m128i operator()(const __m128i& a, const __m128i&) const + { + return a; + } + }; + + template + class v_sse_palignr_u8_class + { + public: + inline __m128i operator()(const __m128i& a, const __m128i& b) const + { + return _mm_unpacklo_epi64(_mm_unpackhi_epi64(a, a), b); + } + }; + + template + class v_sse_palignr_u8_class + { + public: + inline __m128i operator()(const __m128i&, const __m128i& b) const + { + return b; + } + }; + + template + class v_sse_palignr_u8_class + { +#if CV_SSSE3 + public: + inline __m128i operator()(const __m128i& a, const __m128i& b) const + { + return _mm_alignr_epi8(b, a, imm); + } +#else + public: + inline __m128i operator()(const __m128i& a, const __m128i& b) const + { + enum { imm2 = (sizeof(__m128i) - imm) }; + return _mm_or_si128(_mm_srli_si128(a, imm), _mm_slli_si128(b, imm2)); + } +#endif + }; + + template + inline __m128i v_sse_palignr_u8(const __m128i& a, const __m128i& b) + { + CV_StaticAssert((imm >= 0) && (imm <= 16), "Invalid imm for v_sse_palignr_u8."); + return v_sse_palignr_u8_class()(a, b); + } +} + +template +inline _Tpvec v_rotate_right(const _Tpvec &a) +{ + using namespace hal_sse_internal; + enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) }; + return _Tpvec(v_sse_reinterpret_as( + _mm_srli_si128( + v_sse_reinterpret_as<__m128i>(a.val), imm2))); +} + +template +inline _Tpvec v_rotate_left(const _Tpvec &a) +{ + using namespace hal_sse_internal; + enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) }; + return _Tpvec(v_sse_reinterpret_as( + _mm_slli_si128( + v_sse_reinterpret_as<__m128i>(a.val), imm2))); +} + +template +inline _Tpvec v_rotate_right(const _Tpvec &a, const _Tpvec &b) +{ + using namespace hal_sse_internal; + enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) }; + return _Tpvec(v_sse_reinterpret_as( + v_sse_palignr_u8( + v_sse_reinterpret_as<__m128i>(a.val), + v_sse_reinterpret_as<__m128i>(b.val)))); +} + +template +inline _Tpvec v_rotate_left(const _Tpvec &a, const _Tpvec &b) +{ + using namespace hal_sse_internal; + enum { imm2 = ((_Tpvec::nlanes - imm) * sizeof(typename _Tpvec::lane_type)) }; + return _Tpvec(v_sse_reinterpret_as( + v_sse_palignr_u8( + v_sse_reinterpret_as<__m128i>(b.val), + v_sse_reinterpret_as<__m128i>(a.val)))); +} + +#define OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(_Tpvec, _Tp) \ +inline _Tpvec v_load(const _Tp* ptr) \ +{ return _Tpvec(_mm_loadu_si128((const __m128i*)ptr)); } \ +inline _Tpvec v_load_aligned(const _Tp* ptr) \ +{ return _Tpvec(_mm_load_si128((const __m128i*)ptr)); } \ +inline _Tpvec v_load_low(const _Tp* ptr) \ +{ return _Tpvec(_mm_loadl_epi64((const __m128i*)ptr)); } \ +inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ +{ \ + return _Tpvec(_mm_unpacklo_epi64(_mm_loadl_epi64((const __m128i*)ptr0), \ + _mm_loadl_epi64((const __m128i*)ptr1))); \ +} \ +inline void v_store(_Tp* ptr, const _Tpvec& a) \ +{ _mm_storeu_si128((__m128i*)ptr, a.val); } \ +inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \ +{ _mm_store_si128((__m128i*)ptr, a.val); } \ +inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \ +{ _mm_stream_si128((__m128i*)ptr, a.val); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \ +{ \ + if( mode == hal::STORE_UNALIGNED ) \ + _mm_storeu_si128((__m128i*)ptr, a.val); \ + else if( mode == hal::STORE_ALIGNED_NOCACHE ) \ + _mm_stream_si128((__m128i*)ptr, a.val); \ + else \ + _mm_store_si128((__m128i*)ptr, a.val); \ +} \ +inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ +{ _mm_storel_epi64((__m128i*)ptr, a.val); } \ +inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ +{ _mm_storel_epi64((__m128i*)ptr, _mm_unpackhi_epi64(a.val, a.val)); } + +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint8x16, uchar) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int8x16, schar) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint16x8, ushort) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int16x8, short) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint32x4, unsigned) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int32x4, int) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint64x2, uint64) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int64x2, int64) + +#define OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(_Tpvec, _Tp, suffix) \ +inline _Tpvec v_load(const _Tp* ptr) \ +{ return _Tpvec(_mm_loadu_##suffix(ptr)); } \ +inline _Tpvec v_load_aligned(const _Tp* ptr) \ +{ return _Tpvec(_mm_load_##suffix(ptr)); } \ +inline _Tpvec v_load_low(const _Tp* ptr) \ +{ return _Tpvec(_mm_castsi128_##suffix(_mm_loadl_epi64((const __m128i*)ptr))); } \ +inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ +{ \ + return _Tpvec(_mm_castsi128_##suffix( \ + _mm_unpacklo_epi64(_mm_loadl_epi64((const __m128i*)ptr0), \ + _mm_loadl_epi64((const __m128i*)ptr1)))); \ +} \ +inline void v_store(_Tp* ptr, const _Tpvec& a) \ +{ _mm_storeu_##suffix(ptr, a.val); } \ +inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \ +{ _mm_store_##suffix(ptr, a.val); } \ +inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \ +{ _mm_stream_##suffix(ptr, a.val); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \ +{ \ + if( mode == hal::STORE_UNALIGNED ) \ + _mm_storeu_##suffix(ptr, a.val); \ + else if( mode == hal::STORE_ALIGNED_NOCACHE ) \ + _mm_stream_##suffix(ptr, a.val); \ + else \ + _mm_store_##suffix(ptr, a.val); \ +} \ +inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ +{ _mm_storel_epi64((__m128i*)ptr, _mm_cast##suffix##_si128(a.val)); } \ +inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ +{ \ + __m128i a1 = _mm_cast##suffix##_si128(a.val); \ + _mm_storel_epi64((__m128i*)ptr, _mm_unpackhi_epi64(a1, a1)); \ +} + +OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(v_float32x4, float, ps) +OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(v_float64x2, double, pd) + +#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(_Tpvec, scalartype, func, suffix, sbit) \ +inline scalartype v_reduce_##func(const v_##_Tpvec& a) \ +{ \ + __m128i val = a.val; \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,8)); \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,4)); \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,2)); \ + return (scalartype)_mm_cvtsi128_si32(val); \ +} \ +inline unsigned scalartype v_reduce_##func(const v_u##_Tpvec& a) \ +{ \ + __m128i val = a.val; \ + __m128i smask = _mm_set1_epi16(sbit); \ + val = _mm_xor_si128(val, smask); \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,8)); \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,4)); \ + val = _mm_##func##_##suffix(val, _mm_srli_si128(val,2)); \ + return (unsigned scalartype)(_mm_cvtsi128_si32(val) ^ sbit); \ +} +#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_8_SUM(_Tpvec, scalartype, suffix) \ +inline scalartype v_reduce_sum(const v_##_Tpvec& a) \ +{ \ + __m128i val = a.val; \ + val = _mm_adds_epi##suffix(val, _mm_srli_si128(val, 8)); \ + val = _mm_adds_epi##suffix(val, _mm_srli_si128(val, 4)); \ + val = _mm_adds_epi##suffix(val, _mm_srli_si128(val, 2)); \ + return (scalartype)_mm_cvtsi128_si32(val); \ +} \ +inline unsigned scalartype v_reduce_sum(const v_u##_Tpvec& a) \ +{ \ + __m128i val = a.val; \ + val = _mm_adds_epu##suffix(val, _mm_srli_si128(val, 8)); \ + val = _mm_adds_epu##suffix(val, _mm_srli_si128(val, 4)); \ + val = _mm_adds_epu##suffix(val, _mm_srli_si128(val, 2)); \ + return (unsigned scalartype)_mm_cvtsi128_si32(val); \ +} +OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(int16x8, short, max, epi16, (short)-32768) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(int16x8, short, min, epi16, (short)-32768) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_8_SUM(int16x8, short, 16) + +#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(_Tpvec, scalartype, regtype, suffix, cast_from, cast_to, extract) \ +inline scalartype v_reduce_sum(const _Tpvec& a) \ +{ \ + regtype val = a.val; \ + val = _mm_add_##suffix(val, cast_to(_mm_srli_si128(cast_from(val), 8))); \ + val = _mm_add_##suffix(val, cast_to(_mm_srli_si128(cast_from(val), 4))); \ + return (scalartype)_mm_cvt##extract(val); \ +} + +#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(_Tpvec, scalartype, func, scalar_func) \ +inline scalartype v_reduce_##func(const _Tpvec& a) \ +{ \ + scalartype CV_DECL_ALIGNED(16) buf[4]; \ + v_store_aligned(buf, a); \ + scalartype s0 = scalar_func(buf[0], buf[1]); \ + scalartype s1 = scalar_func(buf[2], buf[3]); \ + return scalar_func(s0, s1); \ +} + +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_uint32x4, unsigned, __m128i, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP, si128_si32) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_int32x4, int, __m128i, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP, si128_si32) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_float32x4, float, __m128, ps, _mm_castps_si128, _mm_castsi128_ps, ss_f32) + +inline double v_reduce_sum(const v_float64x2& a) +{ + double CV_DECL_ALIGNED(32) idx[2]; + v_store_aligned(idx, a); + return idx[0] + idx[1]; +} + +inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, const v_float32x4& d) +{ +#if CV_SSE3 + __m128 ab = _mm_hadd_ps(a.val, b.val); + __m128 cd = _mm_hadd_ps(c.val, d.val); + return v_float32x4(_mm_hadd_ps(ab, cd)); +#else + __m128 ac = _mm_add_ps(_mm_unpacklo_ps(a.val, c.val), _mm_unpackhi_ps(a.val, c.val)); + __m128 bd = _mm_add_ps(_mm_unpacklo_ps(b.val, d.val), _mm_unpackhi_ps(b.val, d.val)); + return v_float32x4(_mm_add_ps(_mm_unpacklo_ps(ac, bd), _mm_unpackhi_ps(ac, bd))); +#endif +} + +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_uint32x4, unsigned, max, std::max) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_uint32x4, unsigned, min, std::min) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_int32x4, int, max, std::max) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_int32x4, int, min, std::min) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_float32x4, float, max, std::max) +OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_float32x4, float, min, std::min) + +inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b) +{ + return (unsigned)_mm_cvtsi128_si32(_mm_sad_epu8(a.val, b.val)); +} +inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b) +{ + __m128i half = _mm_set1_epi8(0x7f); + return (unsigned)_mm_cvtsi128_si32(_mm_sad_epu8(_mm_add_epi8(a.val, half), + _mm_add_epi8(b.val, half))); +} +inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b) +{ + v_uint32x4 l, h; + v_expand(v_absdiff(a, b), l, h); + return v_reduce_sum(l + h); +} +inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b) +{ + v_uint32x4 l, h; + v_expand(v_absdiff(a, b), l, h); + return v_reduce_sum(l + h); +} +inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b) +{ + return v_reduce_sum(v_absdiff(a, b)); +} +inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b) +{ + return v_reduce_sum(v_absdiff(a, b)); +} +inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b) +{ + return v_reduce_sum(v_absdiff(a, b)); +} + +#define OPENCV_HAL_IMPL_SSE_POPCOUNT(_Tpvec) \ +inline v_uint32x4 v_popcount(const _Tpvec& a) \ +{ \ + __m128i m1 = _mm_set1_epi32(0x55555555); \ + __m128i m2 = _mm_set1_epi32(0x33333333); \ + __m128i m4 = _mm_set1_epi32(0x0f0f0f0f); \ + __m128i p = a.val; \ + p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 1), m1), _mm_and_si128(p, m1)); \ + p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 2), m2), _mm_and_si128(p, m2)); \ + p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 4), m4), _mm_and_si128(p, m4)); \ + p = _mm_adds_epi8(p, _mm_srli_si128(p, 1)); \ + p = _mm_adds_epi8(p, _mm_srli_si128(p, 2)); \ + return v_uint32x4(_mm_and_si128(p, _mm_set1_epi32(0x000000ff))); \ +} + +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_uint8x16) +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_uint16x8) +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_uint32x4) +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_int8x16) +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_int16x8) +OPENCV_HAL_IMPL_SSE_POPCOUNT(v_int32x4) + +#define OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(_Tpvec, suffix, pack_op, and_op, signmask, allmask) \ +inline int v_signmask(const _Tpvec& a) \ +{ \ + return and_op(_mm_movemask_##suffix(pack_op(a.val)), signmask); \ +} \ +inline bool v_check_all(const _Tpvec& a) \ +{ return and_op(_mm_movemask_##suffix(a.val), allmask) == allmask; } \ +inline bool v_check_any(const _Tpvec& a) \ +{ return and_op(_mm_movemask_##suffix(a.val), allmask) != 0; } + +#define OPENCV_HAL_PACKS(a) _mm_packs_epi16(a, a) +inline __m128i v_packq_epi32(__m128i a) +{ + __m128i b = _mm_packs_epi32(a, a); + return _mm_packs_epi16(b, b); +} + +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_1ST, 65535, 65535) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_1ST, 65535, 65535) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint16x8, epi8, OPENCV_HAL_PACKS, OPENCV_HAL_AND, 255, (int)0xaaaa) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int16x8, epi8, OPENCV_HAL_PACKS, OPENCV_HAL_AND, 255, (int)0xaaaa) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint32x4, epi8, v_packq_epi32, OPENCV_HAL_AND, 15, (int)0x8888) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int32x4, epi8, v_packq_epi32, OPENCV_HAL_AND, 15, (int)0x8888) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_float32x4, ps, OPENCV_HAL_NOP, OPENCV_HAL_1ST, 15, 15) +OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_float64x2, pd, OPENCV_HAL_NOP, OPENCV_HAL_1ST, 3, 3) + +#if CV_SSE4_1 +#define OPENCV_HAL_IMPL_SSE_SELECT(_Tpvec, cast_ret, cast, suffix) \ +inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(cast_ret(_mm_blendv_##suffix(cast(b.val), cast(a.val), cast(mask.val)))); \ +} + +OPENCV_HAL_IMPL_SSE_SELECT(v_uint8x16, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8) +OPENCV_HAL_IMPL_SSE_SELECT(v_int8x16, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8) +OPENCV_HAL_IMPL_SSE_SELECT(v_uint16x8, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8) +OPENCV_HAL_IMPL_SSE_SELECT(v_int16x8, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8) +OPENCV_HAL_IMPL_SSE_SELECT(v_uint32x4, _mm_castps_si128, _mm_castsi128_ps, ps) +OPENCV_HAL_IMPL_SSE_SELECT(v_int32x4, _mm_castps_si128, _mm_castsi128_ps, ps) +// OPENCV_HAL_IMPL_SSE_SELECT(v_uint64x2, TBD, TBD, pd) +// OPENCV_HAL_IMPL_SSE_SELECT(v_int64x2, TBD, TBD, ps) +OPENCV_HAL_IMPL_SSE_SELECT(v_float32x4, OPENCV_HAL_NOP, OPENCV_HAL_NOP, ps) +OPENCV_HAL_IMPL_SSE_SELECT(v_float64x2, OPENCV_HAL_NOP, OPENCV_HAL_NOP, pd) + +#else // CV_SSE4_1 + +#define OPENCV_HAL_IMPL_SSE_SELECT(_Tpvec, suffix) \ +inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \ +{ \ + return _Tpvec(_mm_xor_##suffix(b.val, _mm_and_##suffix(_mm_xor_##suffix(b.val, a.val), mask.val))); \ +} + +OPENCV_HAL_IMPL_SSE_SELECT(v_uint8x16, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_int8x16, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_uint16x8, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_int16x8, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_uint32x4, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_int32x4, si128) +// OPENCV_HAL_IMPL_SSE_SELECT(v_uint64x2, si128) +// OPENCV_HAL_IMPL_SSE_SELECT(v_int64x2, si128) +OPENCV_HAL_IMPL_SSE_SELECT(v_float32x4, ps) +OPENCV_HAL_IMPL_SSE_SELECT(v_float64x2, pd) +#endif + +/* Expand */ +#define OPENCV_HAL_IMPL_SSE_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin) \ + inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \ + { \ + b0.val = intrin(a.val); \ + b1.val = __CV_CAT(intrin, _high)(a.val); \ + } \ + inline _Tpwvec v_expand_low(const _Tpvec& a) \ + { return _Tpwvec(intrin(a.val)); } \ + inline _Tpwvec v_expand_high(const _Tpvec& a) \ + { return _Tpwvec(__CV_CAT(intrin, _high)(a.val)); } \ + inline _Tpwvec v_load_expand(const _Tp* ptr) \ + { \ + __m128i a = _mm_loadl_epi64((const __m128i*)ptr); \ + return _Tpwvec(intrin(a)); \ + } + +OPENCV_HAL_IMPL_SSE_EXPAND(v_uint8x16, v_uint16x8, uchar, _v128_cvtepu8_epi16) +OPENCV_HAL_IMPL_SSE_EXPAND(v_int8x16, v_int16x8, schar, _v128_cvtepi8_epi16) +OPENCV_HAL_IMPL_SSE_EXPAND(v_uint16x8, v_uint32x4, ushort, _v128_cvtepu16_epi32) +OPENCV_HAL_IMPL_SSE_EXPAND(v_int16x8, v_int32x4, short, _v128_cvtepi16_epi32) +OPENCV_HAL_IMPL_SSE_EXPAND(v_uint32x4, v_uint64x2, unsigned, _v128_cvtepu32_epi64) +OPENCV_HAL_IMPL_SSE_EXPAND(v_int32x4, v_int64x2, int, _v128_cvtepi32_epi64) + +#define OPENCV_HAL_IMPL_SSE_EXPAND_Q(_Tpvec, _Tp, intrin) \ + inline _Tpvec v_load_expand_q(const _Tp* ptr) \ + { \ + __m128i a = _mm_cvtsi32_si128(*(const int*)ptr); \ + return _Tpvec(intrin(a)); \ + } + +OPENCV_HAL_IMPL_SSE_EXPAND_Q(v_uint32x4, uchar, _v128_cvtepu8_epi32) +OPENCV_HAL_IMPL_SSE_EXPAND_Q(v_int32x4, schar, _v128_cvtepi8_epi32) + +#define OPENCV_HAL_IMPL_SSE_UNPACKS(_Tpvec, suffix, cast_from, cast_to) \ +inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) \ +{ \ + b0.val = _mm_unpacklo_##suffix(a0.val, a1.val); \ + b1.val = _mm_unpackhi_##suffix(a0.val, a1.val); \ +} \ +inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \ +{ \ + __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \ + return _Tpvec(cast_to(_mm_unpacklo_epi64(a1, b1))); \ +} \ +inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \ +{ \ + __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \ + return _Tpvec(cast_to(_mm_unpackhi_epi64(a1, b1))); \ +} \ +inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) \ +{ \ + __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \ + c.val = cast_to(_mm_unpacklo_epi64(a1, b1)); \ + d.val = cast_to(_mm_unpackhi_epi64(a1, b1)); \ +} + +OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_int8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint16x8, epi16, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_int16x8, epi16, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_int32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_float32x4, ps, _mm_castps_si128, _mm_castsi128_ps) +OPENCV_HAL_IMPL_SSE_UNPACKS(v_float64x2, pd, _mm_castpd_si128, _mm_castsi128_pd) + +template +inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) +{ + return v_rotate_right(a, b); +} + +inline v_int32x4 v_round(const v_float32x4& a) +{ return v_int32x4(_mm_cvtps_epi32(a.val)); } + +inline v_int32x4 v_floor(const v_float32x4& a) +{ + __m128i a1 = _mm_cvtps_epi32(a.val); + __m128i mask = _mm_castps_si128(_mm_cmpgt_ps(_mm_cvtepi32_ps(a1), a.val)); + return v_int32x4(_mm_add_epi32(a1, mask)); +} + +inline v_int32x4 v_ceil(const v_float32x4& a) +{ + __m128i a1 = _mm_cvtps_epi32(a.val); + __m128i mask = _mm_castps_si128(_mm_cmpgt_ps(a.val, _mm_cvtepi32_ps(a1))); + return v_int32x4(_mm_sub_epi32(a1, mask)); +} + +inline v_int32x4 v_trunc(const v_float32x4& a) +{ return v_int32x4(_mm_cvttps_epi32(a.val)); } + +inline v_int32x4 v_round(const v_float64x2& a) +{ return v_int32x4(_mm_cvtpd_epi32(a.val)); } + +inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b) +{ + __m128i ai = _mm_cvtpd_epi32(a.val), bi = _mm_cvtpd_epi32(b.val); + return v_int32x4(_mm_unpacklo_epi64(ai, bi)); +} + +inline v_int32x4 v_floor(const v_float64x2& a) +{ + __m128i a1 = _mm_cvtpd_epi32(a.val); + __m128i mask = _mm_castpd_si128(_mm_cmpgt_pd(_mm_cvtepi32_pd(a1), a.val)); + mask = _mm_srli_si128(_mm_slli_si128(mask, 4), 8); // m0 m0 m1 m1 => m0 m1 0 0 + return v_int32x4(_mm_add_epi32(a1, mask)); +} + +inline v_int32x4 v_ceil(const v_float64x2& a) +{ + __m128i a1 = _mm_cvtpd_epi32(a.val); + __m128i mask = _mm_castpd_si128(_mm_cmpgt_pd(a.val, _mm_cvtepi32_pd(a1))); + mask = _mm_srli_si128(_mm_slli_si128(mask, 4), 8); // m0 m0 m1 m1 => m0 m1 0 0 + return v_int32x4(_mm_sub_epi32(a1, mask)); +} + +inline v_int32x4 v_trunc(const v_float64x2& a) +{ return v_int32x4(_mm_cvttpd_epi32(a.val)); } + +#define OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(_Tpvec, suffix, cast_from, cast_to) \ +inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \ + const _Tpvec& a2, const _Tpvec& a3, \ + _Tpvec& b0, _Tpvec& b1, \ + _Tpvec& b2, _Tpvec& b3) \ +{ \ + __m128i t0 = cast_from(_mm_unpacklo_##suffix(a0.val, a1.val)); \ + __m128i t1 = cast_from(_mm_unpacklo_##suffix(a2.val, a3.val)); \ + __m128i t2 = cast_from(_mm_unpackhi_##suffix(a0.val, a1.val)); \ + __m128i t3 = cast_from(_mm_unpackhi_##suffix(a2.val, a3.val)); \ +\ + b0.val = cast_to(_mm_unpacklo_epi64(t0, t1)); \ + b1.val = cast_to(_mm_unpackhi_epi64(t0, t1)); \ + b2.val = cast_to(_mm_unpacklo_epi64(t2, t3)); \ + b3.val = cast_to(_mm_unpackhi_epi64(t2, t3)); \ +} + +OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_uint32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_int32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP) +OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_float32x4, ps, _mm_castps_si128, _mm_castsi128_ps) + +// load deinterleave +inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b) +{ + __m128i t00 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 16)); + + __m128i t10 = _mm_unpacklo_epi8(t00, t01); + __m128i t11 = _mm_unpackhi_epi8(t00, t01); + + __m128i t20 = _mm_unpacklo_epi8(t10, t11); + __m128i t21 = _mm_unpackhi_epi8(t10, t11); + + __m128i t30 = _mm_unpacklo_epi8(t20, t21); + __m128i t31 = _mm_unpackhi_epi8(t20, t21); + + a.val = _mm_unpacklo_epi8(t30, t31); + b.val = _mm_unpackhi_epi8(t30, t31); +} + +inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c) +{ +#if CV_SSE4_1 + const __m128i m0 = _mm_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0); + const __m128i m1 = _mm_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0); + __m128i s0 = _mm_loadu_si128((const __m128i*)ptr); + __m128i s1 = _mm_loadu_si128((const __m128i*)(ptr + 16)); + __m128i s2 = _mm_loadu_si128((const __m128i*)(ptr + 32)); + __m128i a0 = _mm_blendv_epi8(_mm_blendv_epi8(s0, s1, m0), s2, m1); + __m128i b0 = _mm_blendv_epi8(_mm_blendv_epi8(s1, s2, m0), s0, m1); + __m128i c0 = _mm_blendv_epi8(_mm_blendv_epi8(s2, s0, m0), s1, m1); + const __m128i sh_b = _mm_setr_epi8(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13); + const __m128i sh_g = _mm_setr_epi8(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14); + const __m128i sh_r = _mm_setr_epi8(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15); + a0 = _mm_shuffle_epi8(a0, sh_b); + b0 = _mm_shuffle_epi8(b0, sh_g); + c0 = _mm_shuffle_epi8(c0, sh_r); + a.val = a0; + b.val = b0; + c.val = c0; +#elif CV_SSSE3 + const __m128i m0 = _mm_setr_epi8(0, 3, 6, 9, 12, 15, 1, 4, 7, 10, 13, 2, 5, 8, 11, 14); + const __m128i m1 = _mm_alignr_epi8(m0, m0, 11); + const __m128i m2 = _mm_alignr_epi8(m0, m0, 6); + + __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 16)); + __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 32)); + + __m128i s0 = _mm_shuffle_epi8(t0, m0); + __m128i s1 = _mm_shuffle_epi8(t1, m1); + __m128i s2 = _mm_shuffle_epi8(t2, m2); + + t0 = _mm_alignr_epi8(s1, _mm_slli_si128(s0, 10), 5); + a.val = _mm_alignr_epi8(s2, t0, 5); + + t1 = _mm_alignr_epi8(_mm_srli_si128(s1, 5), _mm_slli_si128(s0, 5), 6); + b.val = _mm_alignr_epi8(_mm_srli_si128(s2, 5), t1, 5); + + t2 = _mm_alignr_epi8(_mm_srli_si128(s2, 10), s1, 11); + c.val = _mm_alignr_epi8(t2, s0, 11); +#else + __m128i t00 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 16)); + __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 32)); + + __m128i t10 = _mm_unpacklo_epi8(t00, _mm_unpackhi_epi64(t01, t01)); + __m128i t11 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t00, t00), t02); + __m128i t12 = _mm_unpacklo_epi8(t01, _mm_unpackhi_epi64(t02, t02)); + + __m128i t20 = _mm_unpacklo_epi8(t10, _mm_unpackhi_epi64(t11, t11)); + __m128i t21 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t10, t10), t12); + __m128i t22 = _mm_unpacklo_epi8(t11, _mm_unpackhi_epi64(t12, t12)); + + __m128i t30 = _mm_unpacklo_epi8(t20, _mm_unpackhi_epi64(t21, t21)); + __m128i t31 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t20, t20), t22); + __m128i t32 = _mm_unpacklo_epi8(t21, _mm_unpackhi_epi64(t22, t22)); + + a.val = _mm_unpacklo_epi8(t30, _mm_unpackhi_epi64(t31, t31)); + b.val = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t30, t30), t32); + c.val = _mm_unpacklo_epi8(t31, _mm_unpackhi_epi64(t32, t32)); +#endif +} + +inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c, v_uint8x16& d) +{ + __m128i u0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0 c0 d0 a1 b1 c1 d1 ... + __m128i u1 = _mm_loadu_si128((const __m128i*)(ptr + 16)); // a4 b4 c4 d4 ... + __m128i u2 = _mm_loadu_si128((const __m128i*)(ptr + 32)); // a8 b8 c8 d8 ... + __m128i u3 = _mm_loadu_si128((const __m128i*)(ptr + 48)); // a12 b12 c12 d12 ... + + __m128i v0 = _mm_unpacklo_epi8(u0, u2); // a0 a8 b0 b8 ... + __m128i v1 = _mm_unpackhi_epi8(u0, u2); // a2 a10 b2 b10 ... + __m128i v2 = _mm_unpacklo_epi8(u1, u3); // a4 a12 b4 b12 ... + __m128i v3 = _mm_unpackhi_epi8(u1, u3); // a6 a14 b6 b14 ... + + u0 = _mm_unpacklo_epi8(v0, v2); // a0 a4 a8 a12 ... + u1 = _mm_unpacklo_epi8(v1, v3); // a2 a6 a10 a14 ... + u2 = _mm_unpackhi_epi8(v0, v2); // a1 a5 a9 a13 ... + u3 = _mm_unpackhi_epi8(v1, v3); // a3 a7 a11 a15 ... + + v0 = _mm_unpacklo_epi8(u0, u1); // a0 a2 a4 a6 ... + v1 = _mm_unpacklo_epi8(u2, u3); // a1 a3 a5 a7 ... + v2 = _mm_unpackhi_epi8(u0, u1); // c0 c2 c4 c6 ... + v3 = _mm_unpackhi_epi8(u2, u3); // c1 c3 c5 c7 ... + + a.val = _mm_unpacklo_epi8(v0, v1); + b.val = _mm_unpackhi_epi8(v0, v1); + c.val = _mm_unpacklo_epi8(v2, v3); + d.val = _mm_unpackhi_epi8(v2, v3); +} + +inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b) +{ + __m128i v0 = _mm_loadu_si128((__m128i*)(ptr)); // a0 b0 a1 b1 a2 b2 a3 b3 + __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 8)); // a4 b4 a5 b5 a6 b6 a7 b7 + + __m128i v2 = _mm_unpacklo_epi16(v0, v1); // a0 a4 b0 b4 a1 a5 b1 b5 + __m128i v3 = _mm_unpackhi_epi16(v0, v1); // a2 a6 b2 b6 a3 a7 b3 b7 + __m128i v4 = _mm_unpacklo_epi16(v2, v3); // a0 a2 a4 a6 b0 b2 b4 b6 + __m128i v5 = _mm_unpackhi_epi16(v2, v3); // a1 a3 a5 a7 b1 b3 b5 b7 + + a.val = _mm_unpacklo_epi16(v4, v5); // a0 a1 a2 a3 a4 a5 a6 a7 + b.val = _mm_unpackhi_epi16(v4, v5); // b0 b1 ab b3 b4 b5 b6 b7 +} + +inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c) +{ +#if CV_SSE4_1 + __m128i v0 = _mm_loadu_si128((__m128i*)(ptr)); + __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 8)); + __m128i v2 = _mm_loadu_si128((__m128i*)(ptr + 16)); + __m128i a0 = _mm_blend_epi16(_mm_blend_epi16(v0, v1, 0x92), v2, 0x24); + __m128i b0 = _mm_blend_epi16(_mm_blend_epi16(v2, v0, 0x92), v1, 0x24); + __m128i c0 = _mm_blend_epi16(_mm_blend_epi16(v1, v2, 0x92), v0, 0x24); + + const __m128i sh_a = _mm_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11); + const __m128i sh_b = _mm_setr_epi8(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13); + const __m128i sh_c = _mm_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15); + a0 = _mm_shuffle_epi8(a0, sh_a); + b0 = _mm_shuffle_epi8(b0, sh_b); + c0 = _mm_shuffle_epi8(c0, sh_c); + + a.val = a0; + b.val = b0; + c.val = c0; +#else + __m128i t00 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 8)); + __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 16)); + + __m128i t10 = _mm_unpacklo_epi16(t00, _mm_unpackhi_epi64(t01, t01)); + __m128i t11 = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t00, t00), t02); + __m128i t12 = _mm_unpacklo_epi16(t01, _mm_unpackhi_epi64(t02, t02)); + + __m128i t20 = _mm_unpacklo_epi16(t10, _mm_unpackhi_epi64(t11, t11)); + __m128i t21 = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t10, t10), t12); + __m128i t22 = _mm_unpacklo_epi16(t11, _mm_unpackhi_epi64(t12, t12)); + + a.val = _mm_unpacklo_epi16(t20, _mm_unpackhi_epi64(t21, t21)); + b.val = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t20, t20), t22); + c.val = _mm_unpacklo_epi16(t21, _mm_unpackhi_epi64(t22, t22)); +#endif +} + +inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c, v_uint16x8& d) +{ + __m128i u0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0 c0 d0 a1 b1 c1 d1 + __m128i u1 = _mm_loadu_si128((const __m128i*)(ptr + 8)); // a2 b2 c2 d2 ... + __m128i u2 = _mm_loadu_si128((const __m128i*)(ptr + 16)); // a4 b4 c4 d4 ... + __m128i u3 = _mm_loadu_si128((const __m128i*)(ptr + 24)); // a6 b6 c6 d6 ... + + __m128i v0 = _mm_unpacklo_epi16(u0, u2); // a0 a4 b0 b4 ... + __m128i v1 = _mm_unpackhi_epi16(u0, u2); // a1 a5 b1 b5 ... + __m128i v2 = _mm_unpacklo_epi16(u1, u3); // a2 a6 b2 b6 ... + __m128i v3 = _mm_unpackhi_epi16(u1, u3); // a3 a7 b3 b7 ... + + u0 = _mm_unpacklo_epi16(v0, v2); // a0 a2 a4 a6 ... + u1 = _mm_unpacklo_epi16(v1, v3); // a1 a3 a5 a7 ... + u2 = _mm_unpackhi_epi16(v0, v2); // c0 c2 c4 c6 ... + u3 = _mm_unpackhi_epi16(v1, v3); // c1 c3 c5 c7 ... + + a.val = _mm_unpacklo_epi16(u0, u1); + b.val = _mm_unpackhi_epi16(u0, u1); + c.val = _mm_unpacklo_epi16(u2, u3); + d.val = _mm_unpackhi_epi16(u2, u3); +} + +inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b) +{ + __m128i v0 = _mm_loadu_si128((__m128i*)(ptr)); // a0 b0 a1 b1 + __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 4)); // a2 b2 a3 b3 + + __m128i v2 = _mm_unpacklo_epi32(v0, v1); // a0 a2 b0 b2 + __m128i v3 = _mm_unpackhi_epi32(v0, v1); // a1 a3 b1 b3 + + a.val = _mm_unpacklo_epi32(v2, v3); // a0 a1 a2 a3 + b.val = _mm_unpackhi_epi32(v2, v3); // b0 b1 ab b3 +} + +inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c) +{ + __m128i t00 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 4)); + __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 8)); + + __m128i t10 = _mm_unpacklo_epi32(t00, _mm_unpackhi_epi64(t01, t01)); + __m128i t11 = _mm_unpacklo_epi32(_mm_unpackhi_epi64(t00, t00), t02); + __m128i t12 = _mm_unpacklo_epi32(t01, _mm_unpackhi_epi64(t02, t02)); + + a.val = _mm_unpacklo_epi32(t10, _mm_unpackhi_epi64(t11, t11)); + b.val = _mm_unpacklo_epi32(_mm_unpackhi_epi64(t10, t10), t12); + c.val = _mm_unpacklo_epi32(t11, _mm_unpackhi_epi64(t12, t12)); +} + +inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c, v_uint32x4& d) +{ + v_uint32x4 s0(_mm_loadu_si128((const __m128i*)ptr)); // a0 b0 c0 d0 + v_uint32x4 s1(_mm_loadu_si128((const __m128i*)(ptr + 4))); // a1 b1 c1 d1 + v_uint32x4 s2(_mm_loadu_si128((const __m128i*)(ptr + 8))); // a2 b2 c2 d2 + v_uint32x4 s3(_mm_loadu_si128((const __m128i*)(ptr + 12))); // a3 b3 c3 d3 + + v_transpose4x4(s0, s1, s2, s3, a, b, c, d); +} + +inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b) +{ + __m128 u0 = _mm_loadu_ps(ptr); // a0 b0 a1 b1 + __m128 u1 = _mm_loadu_ps((ptr + 4)); // a2 b2 a3 b3 + + a.val = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(2, 0, 2, 0)); // a0 a1 a2 a3 + b.val = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(3, 1, 3, 1)); // b0 b1 ab b3 +} + +inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c) +{ + __m128 t0 = _mm_loadu_ps(ptr + 0); + __m128 t1 = _mm_loadu_ps(ptr + 4); + __m128 t2 = _mm_loadu_ps(ptr + 8); + + __m128 at12 = _mm_shuffle_ps(t1, t2, _MM_SHUFFLE(0, 1, 0, 2)); + a.val = _mm_shuffle_ps(t0, at12, _MM_SHUFFLE(2, 0, 3, 0)); + + __m128 bt01 = _mm_shuffle_ps(t0, t1, _MM_SHUFFLE(0, 0, 0, 1)); + __m128 bt12 = _mm_shuffle_ps(t1, t2, _MM_SHUFFLE(0, 2, 0, 3)); + b.val = _mm_shuffle_ps(bt01, bt12, _MM_SHUFFLE(2, 0, 2, 0)); + + __m128 ct01 = _mm_shuffle_ps(t0, t1, _MM_SHUFFLE(0, 1, 0, 2)); + c.val = _mm_shuffle_ps(ct01, t2, _MM_SHUFFLE(3, 0, 2, 0)); +} + +inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c, v_float32x4& d) +{ + __m128 t0 = _mm_loadu_ps(ptr + 0); + __m128 t1 = _mm_loadu_ps(ptr + 4); + __m128 t2 = _mm_loadu_ps(ptr + 8); + __m128 t3 = _mm_loadu_ps(ptr + 12); + __m128 t02lo = _mm_unpacklo_ps(t0, t2); + __m128 t13lo = _mm_unpacklo_ps(t1, t3); + __m128 t02hi = _mm_unpackhi_ps(t0, t2); + __m128 t13hi = _mm_unpackhi_ps(t1, t3); + a.val = _mm_unpacklo_ps(t02lo, t13lo); + b.val = _mm_unpackhi_ps(t02lo, t13lo); + c.val = _mm_unpacklo_ps(t02hi, t13hi); + d.val = _mm_unpackhi_ps(t02hi, t13hi); +} + +inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b) +{ + __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); + __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2)); + + a = v_uint64x2(_mm_unpacklo_epi64(t0, t1)); + b = v_uint64x2(_mm_unpackhi_epi64(t0, t1)); +} + +inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b, v_uint64x2& c) +{ + __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); // a0, b0 + __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2)); // c0, a1 + __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 4)); // b1, c1 + + t1 = _mm_shuffle_epi32(t1, 0x4e); // a1, c0 + + a = v_uint64x2(_mm_unpacklo_epi64(t0, t1)); + b = v_uint64x2(_mm_unpacklo_epi64(_mm_unpackhi_epi64(t0, t0), t2)); + c = v_uint64x2(_mm_unpackhi_epi64(t1, t2)); +} + +inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, + v_uint64x2& b, v_uint64x2& c, v_uint64x2& d) +{ + __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0 + __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2)); // c0 d0 + __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 4)); // a1 b1 + __m128i t3 = _mm_loadu_si128((const __m128i*)(ptr + 6)); // c1 d1 + + a = v_uint64x2(_mm_unpacklo_epi64(t0, t2)); + b = v_uint64x2(_mm_unpackhi_epi64(t0, t2)); + c = v_uint64x2(_mm_unpacklo_epi64(t1, t3)); + d = v_uint64x2(_mm_unpackhi_epi64(t1, t3)); +} + +// store interleave + +inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi8(a.val, b.val); + __m128i v1 = _mm_unpackhi_epi8(a.val, b.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 16), v1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 16), v1); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 16), v1); + } +} + +inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b, + const v_uint8x16& c, hal::StoreMode mode = hal::STORE_UNALIGNED) +{ +#if CV_SSE4_1 + const __m128i sh_a = _mm_setr_epi8(0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5); + const __m128i sh_b = _mm_setr_epi8(5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10); + const __m128i sh_c = _mm_setr_epi8(10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15); + __m128i a0 = _mm_shuffle_epi8(a.val, sh_a); + __m128i b0 = _mm_shuffle_epi8(b.val, sh_b); + __m128i c0 = _mm_shuffle_epi8(c.val, sh_c); + + const __m128i m0 = _mm_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0); + const __m128i m1 = _mm_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0); + __m128i v0 = _mm_blendv_epi8(_mm_blendv_epi8(a0, b0, m1), c0, m0); + __m128i v1 = _mm_blendv_epi8(_mm_blendv_epi8(b0, c0, m1), a0, m0); + __m128i v2 = _mm_blendv_epi8(_mm_blendv_epi8(c0, a0, m1), b0, m0); +#elif CV_SSSE3 + const __m128i m0 = _mm_setr_epi8(0, 6, 11, 1, 7, 12, 2, 8, 13, 3, 9, 14, 4, 10, 15, 5); + const __m128i m1 = _mm_setr_epi8(5, 11, 0, 6, 12, 1, 7, 13, 2, 8, 14, 3, 9, 15, 4, 10); + const __m128i m2 = _mm_setr_epi8(10, 0, 5, 11, 1, 6, 12, 2, 7, 13, 3, 8, 14, 4, 9, 15); + + __m128i t0 = _mm_alignr_epi8(b.val, _mm_slli_si128(a.val, 10), 5); + t0 = _mm_alignr_epi8(c.val, t0, 5); + __m128i v0 = _mm_shuffle_epi8(t0, m0); + + __m128i t1 = _mm_alignr_epi8(_mm_srli_si128(b.val, 5), _mm_slli_si128(a.val, 5), 6); + t1 = _mm_alignr_epi8(_mm_srli_si128(c.val, 5), t1, 5); + __m128i v1 = _mm_shuffle_epi8(t1, m1); + + __m128i t2 = _mm_alignr_epi8(_mm_srli_si128(c.val, 10), b.val, 11); + t2 = _mm_alignr_epi8(t2, a.val, 11); + __m128i v2 = _mm_shuffle_epi8(t2, m2); +#else + __m128i z = _mm_setzero_si128(); + __m128i ab0 = _mm_unpacklo_epi8(a.val, b.val); + __m128i ab1 = _mm_unpackhi_epi8(a.val, b.val); + __m128i c0 = _mm_unpacklo_epi8(c.val, z); + __m128i c1 = _mm_unpackhi_epi8(c.val, z); + + __m128i p00 = _mm_unpacklo_epi16(ab0, c0); + __m128i p01 = _mm_unpackhi_epi16(ab0, c0); + __m128i p02 = _mm_unpacklo_epi16(ab1, c1); + __m128i p03 = _mm_unpackhi_epi16(ab1, c1); + + __m128i p10 = _mm_unpacklo_epi32(p00, p01); + __m128i p11 = _mm_unpackhi_epi32(p00, p01); + __m128i p12 = _mm_unpacklo_epi32(p02, p03); + __m128i p13 = _mm_unpackhi_epi32(p02, p03); + + __m128i p20 = _mm_unpacklo_epi64(p10, p11); + __m128i p21 = _mm_unpackhi_epi64(p10, p11); + __m128i p22 = _mm_unpacklo_epi64(p12, p13); + __m128i p23 = _mm_unpackhi_epi64(p12, p13); + + p20 = _mm_slli_si128(p20, 1); + p22 = _mm_slli_si128(p22, 1); + + __m128i p30 = _mm_slli_epi64(_mm_unpacklo_epi32(p20, p21), 8); + __m128i p31 = _mm_srli_epi64(_mm_unpackhi_epi32(p20, p21), 8); + __m128i p32 = _mm_slli_epi64(_mm_unpacklo_epi32(p22, p23), 8); + __m128i p33 = _mm_srli_epi64(_mm_unpackhi_epi32(p22, p23), 8); + + __m128i p40 = _mm_unpacklo_epi64(p30, p31); + __m128i p41 = _mm_unpackhi_epi64(p30, p31); + __m128i p42 = _mm_unpacklo_epi64(p32, p33); + __m128i p43 = _mm_unpackhi_epi64(p32, p33); + + __m128i v0 = _mm_or_si128(_mm_srli_si128(p40, 2), _mm_slli_si128(p41, 10)); + __m128i v1 = _mm_or_si128(_mm_srli_si128(p41, 6), _mm_slli_si128(p42, 6)); + __m128i v2 = _mm_or_si128(_mm_srli_si128(p42, 10), _mm_slli_si128(p43, 2)); +#endif + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 16), v1); + _mm_stream_si128((__m128i*)(ptr + 32), v2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 16), v1); + _mm_store_si128((__m128i*)(ptr + 32), v2); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 16), v1); + _mm_storeu_si128((__m128i*)(ptr + 32), v2); + } +} + +inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b, + const v_uint8x16& c, const v_uint8x16& d, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + // a0 a1 a2 a3 .... + // b0 b1 b2 b3 .... + // c0 c1 c2 c3 .... + // d0 d1 d2 d3 .... + __m128i u0 = _mm_unpacklo_epi8(a.val, c.val); // a0 c0 a1 c1 ... + __m128i u1 = _mm_unpackhi_epi8(a.val, c.val); // a8 c8 a9 c9 ... + __m128i u2 = _mm_unpacklo_epi8(b.val, d.val); // b0 d0 b1 d1 ... + __m128i u3 = _mm_unpackhi_epi8(b.val, d.val); // b8 d8 b9 d9 ... + + __m128i v0 = _mm_unpacklo_epi8(u0, u2); // a0 b0 c0 d0 ... + __m128i v1 = _mm_unpackhi_epi8(u0, u2); // a4 b4 c4 d4 ... + __m128i v2 = _mm_unpacklo_epi8(u1, u3); // a8 b8 c8 d8 ... + __m128i v3 = _mm_unpackhi_epi8(u1, u3); // a12 b12 c12 d12 ... + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 16), v1); + _mm_stream_si128((__m128i*)(ptr + 32), v2); + _mm_stream_si128((__m128i*)(ptr + 48), v3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 16), v1); + _mm_store_si128((__m128i*)(ptr + 32), v2); + _mm_store_si128((__m128i*)(ptr + 48), v3); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 16), v1); + _mm_storeu_si128((__m128i*)(ptr + 32), v2); + _mm_storeu_si128((__m128i*)(ptr + 48), v3); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi16(a.val, b.val); + __m128i v1 = _mm_unpackhi_epi16(a.val, b.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 8), v1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 8), v1); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 8), v1); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, + const v_uint16x8& b, const v_uint16x8& c, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ +#if CV_SSE4_1 + const __m128i sh_a = _mm_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11); + const __m128i sh_b = _mm_setr_epi8(10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5); + const __m128i sh_c = _mm_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15); + __m128i a0 = _mm_shuffle_epi8(a.val, sh_a); + __m128i b0 = _mm_shuffle_epi8(b.val, sh_b); + __m128i c0 = _mm_shuffle_epi8(c.val, sh_c); + + __m128i v0 = _mm_blend_epi16(_mm_blend_epi16(a0, b0, 0x92), c0, 0x24); + __m128i v1 = _mm_blend_epi16(_mm_blend_epi16(c0, a0, 0x92), b0, 0x24); + __m128i v2 = _mm_blend_epi16(_mm_blend_epi16(b0, c0, 0x92), a0, 0x24); +#else + __m128i z = _mm_setzero_si128(); + __m128i ab0 = _mm_unpacklo_epi16(a.val, b.val); + __m128i ab1 = _mm_unpackhi_epi16(a.val, b.val); + __m128i c0 = _mm_unpacklo_epi16(c.val, z); + __m128i c1 = _mm_unpackhi_epi16(c.val, z); + + __m128i p10 = _mm_unpacklo_epi32(ab0, c0); + __m128i p11 = _mm_unpackhi_epi32(ab0, c0); + __m128i p12 = _mm_unpacklo_epi32(ab1, c1); + __m128i p13 = _mm_unpackhi_epi32(ab1, c1); + + __m128i p20 = _mm_unpacklo_epi64(p10, p11); + __m128i p21 = _mm_unpackhi_epi64(p10, p11); + __m128i p22 = _mm_unpacklo_epi64(p12, p13); + __m128i p23 = _mm_unpackhi_epi64(p12, p13); + + p20 = _mm_slli_si128(p20, 2); + p22 = _mm_slli_si128(p22, 2); + + __m128i p30 = _mm_unpacklo_epi64(p20, p21); + __m128i p31 = _mm_unpackhi_epi64(p20, p21); + __m128i p32 = _mm_unpacklo_epi64(p22, p23); + __m128i p33 = _mm_unpackhi_epi64(p22, p23); + + __m128i v0 = _mm_or_si128(_mm_srli_si128(p30, 2), _mm_slli_si128(p31, 10)); + __m128i v1 = _mm_or_si128(_mm_srli_si128(p31, 6), _mm_slli_si128(p32, 6)); + __m128i v2 = _mm_or_si128(_mm_srli_si128(p32, 10), _mm_slli_si128(p33, 2)); +#endif + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 8), v1); + _mm_stream_si128((__m128i*)(ptr + 16), v2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 8), v1); + _mm_store_si128((__m128i*)(ptr + 16), v2); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 8), v1); + _mm_storeu_si128((__m128i*)(ptr + 16), v2); + } +} + +inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b, + const v_uint16x8& c, const v_uint16x8& d, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + // a0 a1 a2 a3 .... + // b0 b1 b2 b3 .... + // c0 c1 c2 c3 .... + // d0 d1 d2 d3 .... + __m128i u0 = _mm_unpacklo_epi16(a.val, c.val); // a0 c0 a1 c1 ... + __m128i u1 = _mm_unpackhi_epi16(a.val, c.val); // a4 c4 a5 c5 ... + __m128i u2 = _mm_unpacklo_epi16(b.val, d.val); // b0 d0 b1 d1 ... + __m128i u3 = _mm_unpackhi_epi16(b.val, d.val); // b4 d4 b5 d5 ... + + __m128i v0 = _mm_unpacklo_epi16(u0, u2); // a0 b0 c0 d0 ... + __m128i v1 = _mm_unpackhi_epi16(u0, u2); // a2 b2 c2 d2 ... + __m128i v2 = _mm_unpacklo_epi16(u1, u3); // a4 b4 c4 d4 ... + __m128i v3 = _mm_unpackhi_epi16(u1, u3); // a6 b6 c6 d6 ... + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 8), v1); + _mm_stream_si128((__m128i*)(ptr + 16), v2); + _mm_stream_si128((__m128i*)(ptr + 24), v3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 8), v1); + _mm_store_si128((__m128i*)(ptr + 16), v2); + _mm_store_si128((__m128i*)(ptr + 24), v3); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 8), v1); + _mm_storeu_si128((__m128i*)(ptr + 16), v2); + _mm_storeu_si128((__m128i*)(ptr + 24), v3); + } +} + +inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi32(a.val, b.val); + __m128i v1 = _mm_unpackhi_epi32(a.val, b.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 4), v1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 4), v1); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 4), v1); + } +} + +inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + v_uint32x4 z = v_setzero_u32(), u0, u1, u2, u3; + v_transpose4x4(a, b, c, z, u0, u1, u2, u3); + + __m128i v0 = _mm_or_si128(u0.val, _mm_slli_si128(u1.val, 12)); + __m128i v1 = _mm_or_si128(_mm_srli_si128(u1.val, 4), _mm_slli_si128(u2.val, 8)); + __m128i v2 = _mm_or_si128(_mm_srli_si128(u2.val, 8), _mm_slli_si128(u3.val, 4)); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 4), v1); + _mm_stream_si128((__m128i*)(ptr + 8), v2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 4), v1); + _mm_store_si128((__m128i*)(ptr + 8), v2); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 4), v1); + _mm_storeu_si128((__m128i*)(ptr + 8), v2); + } +} + +inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, const v_uint32x4& d, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + v_uint32x4 v0, v1, v2, v3; + v_transpose4x4(a, b, c, d, v0, v1, v2, v3); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0.val); + _mm_stream_si128((__m128i*)(ptr + 4), v1.val); + _mm_stream_si128((__m128i*)(ptr + 8), v2.val); + _mm_stream_si128((__m128i*)(ptr + 12), v3.val); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0.val); + _mm_store_si128((__m128i*)(ptr + 4), v1.val); + _mm_store_si128((__m128i*)(ptr + 8), v2.val); + _mm_store_si128((__m128i*)(ptr + 12), v3.val); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0.val); + _mm_storeu_si128((__m128i*)(ptr + 4), v1.val); + _mm_storeu_si128((__m128i*)(ptr + 8), v2.val); + _mm_storeu_si128((__m128i*)(ptr + 12), v3.val); + } +} + +// 2-channel, float only +inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128 v0 = _mm_unpacklo_ps(a.val, b.val); // a0 b0 a1 b1 + __m128 v1 = _mm_unpackhi_ps(a.val, b.val); // a2 b2 a3 b3 + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_ps(ptr, v0); + _mm_stream_ps(ptr + 4, v1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_ps(ptr, v0); + _mm_store_ps(ptr + 4, v1); + } + else + { + _mm_storeu_ps(ptr, v0); + _mm_storeu_ps(ptr + 4, v1); + } +} + +inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128 u0 = _mm_shuffle_ps(a.val, b.val, _MM_SHUFFLE(0, 0, 0, 0)); + __m128 u1 = _mm_shuffle_ps(c.val, a.val, _MM_SHUFFLE(1, 1, 0, 0)); + __m128 v0 = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(2, 0, 2, 0)); + __m128 u2 = _mm_shuffle_ps(b.val, c.val, _MM_SHUFFLE(1, 1, 1, 1)); + __m128 u3 = _mm_shuffle_ps(a.val, b.val, _MM_SHUFFLE(2, 2, 2, 2)); + __m128 v1 = _mm_shuffle_ps(u2, u3, _MM_SHUFFLE(2, 0, 2, 0)); + __m128 u4 = _mm_shuffle_ps(c.val, a.val, _MM_SHUFFLE(3, 3, 2, 2)); + __m128 u5 = _mm_shuffle_ps(b.val, c.val, _MM_SHUFFLE(3, 3, 3, 3)); + __m128 v2 = _mm_shuffle_ps(u4, u5, _MM_SHUFFLE(2, 0, 2, 0)); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_ps(ptr, v0); + _mm_stream_ps(ptr + 4, v1); + _mm_stream_ps(ptr + 8, v2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_ps(ptr, v0); + _mm_store_ps(ptr + 4, v1); + _mm_store_ps(ptr + 8, v2); + } + else + { + _mm_storeu_ps(ptr, v0); + _mm_storeu_ps(ptr + 4, v1); + _mm_storeu_ps(ptr + 8, v2); + } +} + +inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, const v_float32x4& d, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128 u0 = _mm_unpacklo_ps(a.val, c.val); + __m128 u1 = _mm_unpacklo_ps(b.val, d.val); + __m128 u2 = _mm_unpackhi_ps(a.val, c.val); + __m128 u3 = _mm_unpackhi_ps(b.val, d.val); + __m128 v0 = _mm_unpacklo_ps(u0, u1); + __m128 v2 = _mm_unpacklo_ps(u2, u3); + __m128 v1 = _mm_unpackhi_ps(u0, u1); + __m128 v3 = _mm_unpackhi_ps(u2, u3); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_ps(ptr, v0); + _mm_stream_ps(ptr + 4, v1); + _mm_stream_ps(ptr + 8, v2); + _mm_stream_ps(ptr + 12, v3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_ps(ptr, v0); + _mm_store_ps(ptr + 4, v1); + _mm_store_ps(ptr + 8, v2); + _mm_store_ps(ptr + 12, v3); + } + else + { + _mm_storeu_ps(ptr, v0); + _mm_storeu_ps(ptr + 4, v1); + _mm_storeu_ps(ptr + 8, v2); + _mm_storeu_ps(ptr + 12, v3); + } +} + +inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi64(a.val, b.val); + __m128i v1 = _mm_unpackhi_epi64(a.val, b.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 2), v1); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 2), v1); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 2), v1); + } +} + +inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b, + const v_uint64x2& c, hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi64(a.val, b.val); + __m128i v1 = _mm_unpacklo_epi64(c.val, _mm_unpackhi_epi64(a.val, a.val)); + __m128i v2 = _mm_unpackhi_epi64(b.val, c.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 2), v1); + _mm_stream_si128((__m128i*)(ptr + 4), v2); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 2), v1); + _mm_store_si128((__m128i*)(ptr + 4), v2); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 2), v1); + _mm_storeu_si128((__m128i*)(ptr + 4), v2); + } +} + +inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b, + const v_uint64x2& c, const v_uint64x2& d, + hal::StoreMode mode = hal::STORE_UNALIGNED) +{ + __m128i v0 = _mm_unpacklo_epi64(a.val, b.val); + __m128i v1 = _mm_unpacklo_epi64(c.val, d.val); + __m128i v2 = _mm_unpackhi_epi64(a.val, b.val); + __m128i v3 = _mm_unpackhi_epi64(c.val, d.val); + + if( mode == hal::STORE_ALIGNED_NOCACHE ) + { + _mm_stream_si128((__m128i*)(ptr), v0); + _mm_stream_si128((__m128i*)(ptr + 2), v1); + _mm_stream_si128((__m128i*)(ptr + 4), v2); + _mm_stream_si128((__m128i*)(ptr + 6), v3); + } + else if( mode == hal::STORE_ALIGNED ) + { + _mm_store_si128((__m128i*)(ptr), v0); + _mm_store_si128((__m128i*)(ptr + 2), v1); + _mm_store_si128((__m128i*)(ptr + 4), v2); + _mm_store_si128((__m128i*)(ptr + 6), v3); + } + else + { + _mm_storeu_si128((__m128i*)(ptr), v0); + _mm_storeu_si128((__m128i*)(ptr + 2), v1); + _mm_storeu_si128((__m128i*)(ptr + 4), v2); + _mm_storeu_si128((__m128i*)(ptr + 6), v3); + } +} + +#define OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \ +{ \ + _Tpvec1 a1, b1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ +} \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \ +{ \ + _Tpvec1 a1, b1, c1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ + c0 = v_reinterpret_as_##suffix0(c1); \ +} \ +inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \ +{ \ + _Tpvec1 a1, b1, c1, d1; \ + v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \ + a0 = v_reinterpret_as_##suffix0(a1); \ + b0 = v_reinterpret_as_##suffix0(b1); \ + c0 = v_reinterpret_as_##suffix0(c1); \ + d0 = v_reinterpret_as_##suffix0(d1); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \ + hal::StoreMode mode = hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, mode); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \ + const _Tpvec0& c0, hal::StoreMode mode = hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode); \ +} \ +inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \ + const _Tpvec0& c0, const _Tpvec0& d0, \ + hal::StoreMode mode = hal::STORE_UNALIGNED ) \ +{ \ + _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \ + _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \ + _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \ + _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \ + v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \ +} + +OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int8x16, schar, s8, v_uint8x16, uchar, u8) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int16x8, short, s16, v_uint16x8, ushort, u16) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int32x4, int, s32, v_uint32x4, unsigned, u32) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int64x2, int64, s64, v_uint64x2, uint64, u64) +OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_float64x2, double, f64, v_uint64x2, uint64, u64) + +inline v_float32x4 v_cvt_f32(const v_int32x4& a) +{ + return v_float32x4(_mm_cvtepi32_ps(a.val)); +} + +inline v_float32x4 v_cvt_f32(const v_float64x2& a) +{ + return v_float32x4(_mm_cvtpd_ps(a.val)); +} + +inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b) +{ + return v_float32x4(_mm_movelh_ps(_mm_cvtpd_ps(a.val), _mm_cvtpd_ps(b.val))); +} + +inline v_float64x2 v_cvt_f64(const v_int32x4& a) +{ + return v_float64x2(_mm_cvtepi32_pd(a.val)); +} + +inline v_float64x2 v_cvt_f64_high(const v_int32x4& a) +{ + return v_float64x2(_mm_cvtepi32_pd(_mm_srli_si128(a.val,8))); +} + +inline v_float64x2 v_cvt_f64(const v_float32x4& a) +{ + return v_float64x2(_mm_cvtps_pd(a.val)); +} + +inline v_float64x2 v_cvt_f64_high(const v_float32x4& a) +{ + return v_float64x2(_mm_cvtps_pd(_mm_movehl_ps(a.val, a.val))); +} + +#if CV_FP16 +inline v_float32x4 v128_load_fp16_f32(const short* ptr) +{ + return v_float32x4(_mm_cvtph_ps(_mm_loadu_si128((const __m128i*)ptr))); +} + +inline void v_store_fp16(short* ptr, const v_float32x4& a) +{ + __m128i fp16_value = _mm_cvtps_ph(a.val, 0); + _mm_storel_epi64((__m128i*)ptr, fp16_value); +} +#endif + +////////////// Lookup table access //////////////////// + +inline v_int8x16 v_lut(const schar* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int8x16(_mm_setr_epi8(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]], + tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]])); +#else + return v_int8x16(_mm_setr_epi64( + _mm_setr_pi8(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]]), + _mm_setr_pi8(tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]) + )); +#endif +} +inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int8x16(_mm_setr_epi16(*(const short*)(tab + idx[0]), *(const short*)(tab + idx[1]), *(const short*)(tab + idx[2]), *(const short*)(tab + idx[3]), + *(const short*)(tab + idx[4]), *(const short*)(tab + idx[5]), *(const short*)(tab + idx[6]), *(const short*)(tab + idx[7]))); +#else + return v_int8x16(_mm_setr_epi64( + _mm_setr_pi16(*(const short*)(tab + idx[0]), *(const short*)(tab + idx[1]), *(const short*)(tab + idx[2]), *(const short*)(tab + idx[3])), + _mm_setr_pi16(*(const short*)(tab + idx[4]), *(const short*)(tab + idx[5]), *(const short*)(tab + idx[6]), *(const short*)(tab + idx[7])) + )); +#endif +} +inline v_int8x16 v_lut_quads(const schar* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int8x16(_mm_setr_epi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]), + *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]))); +#else + return v_int8x16(_mm_setr_epi64( + _mm_setr_pi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1])), + _mm_setr_pi32(*(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])) + )); +#endif +} +inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((const schar *)tab, idx)); } +inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((const schar *)tab, idx)); } +inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((const schar *)tab, idx)); } + +inline v_int16x8 v_lut(const short* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int16x8(_mm_setr_epi16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]], + tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]])); +#else + return v_int16x8(_mm_setr_epi64( + _mm_setr_pi16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]), + _mm_setr_pi16(tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]) + )); +#endif +} +inline v_int16x8 v_lut_pairs(const short* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int16x8(_mm_setr_epi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]), + *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]))); +#else + return v_int16x8(_mm_setr_epi64( + _mm_setr_pi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1])), + _mm_setr_pi32(*(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])) + )); +#endif +} +inline v_int16x8 v_lut_quads(const short* tab, const int* idx) +{ + return v_int16x8(_mm_set_epi64x(*(const int64_t*)(tab + idx[1]), *(const int64_t*)(tab + idx[0]))); +} +inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((const short *)tab, idx)); } +inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((const short *)tab, idx)); } +inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((const short *)tab, idx)); } + +inline v_int32x4 v_lut(const int* tab, const int* idx) +{ +#if defined(_MSC_VER) + return v_int32x4(_mm_setr_epi32(tab[idx[0]], tab[idx[1]], + tab[idx[2]], tab[idx[3]])); +#else + return v_int32x4(_mm_setr_epi64( + _mm_setr_pi32(tab[idx[0]], tab[idx[1]]), + _mm_setr_pi32(tab[idx[2]], tab[idx[3]]) + )); +#endif +} +inline v_int32x4 v_lut_pairs(const int* tab, const int* idx) +{ + return v_int32x4(_mm_set_epi64x(*(const int64_t*)(tab + idx[1]), *(const int64_t*)(tab + idx[0]))); +} +inline v_int32x4 v_lut_quads(const int* tab, const int* idx) +{ + return v_int32x4(_mm_loadu_si128((const __m128i*)(tab + idx[0]))); +} +inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int *)tab, idx)); } +inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int *)tab, idx)); } +inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int *)tab, idx)); } + +inline v_int64x2 v_lut(const int64_t* tab, const int* idx) +{ + return v_int64x2(_mm_set_epi64x(tab[idx[1]], tab[idx[0]])); +} +inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx) +{ + return v_int64x2(_mm_loadu_si128((const __m128i*)(tab + idx[0]))); +} +inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); } +inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); } + +inline v_float32x4 v_lut(const float* tab, const int* idx) +{ + return v_float32x4(_mm_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]])); +} +inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_pairs((const int *)tab, idx)); } +inline v_float32x4 v_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_quads((const int *)tab, idx)); } + +inline v_float64x2 v_lut(const double* tab, const int* idx) +{ + return v_float64x2(_mm_setr_pd(tab[idx[0]], tab[idx[1]])); +} +inline v_float64x2 v_lut_pairs(const double* tab, const int* idx) { return v_float64x2(_mm_castsi128_pd(_mm_loadu_si128((const __m128i*)(tab + idx[0])))); } + +inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec) +{ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_aligned(idx, idxvec); + return v_int32x4(_mm_setr_epi32(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]])); +} + +inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec) +{ + return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec)); +} + +inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec) +{ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_aligned(idx, idxvec); + return v_float32x4(_mm_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]])); +} + +inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec) +{ + int idx[2]; + v_store_low(idx, idxvec); + return v_float64x2(_mm_setr_pd(tab[idx[0]], tab[idx[1]])); +} + +// loads pairs from the table and deinterleaves them, e.g. returns: +// x = (tab[idxvec[0], tab[idxvec[1]], tab[idxvec[2]], tab[idxvec[3]]), +// y = (tab[idxvec[0]+1], tab[idxvec[1]+1], tab[idxvec[2]+1], tab[idxvec[3]+1]) +// note that the indices are float's indices, not the float-pair indices. +// in theory, this function can be used to implement bilinear interpolation, +// when idxvec are the offsets within the image. +inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y) +{ + int CV_DECL_ALIGNED(32) idx[4]; + v_store_aligned(idx, idxvec); + __m128 z = _mm_setzero_ps(); + __m128 xy01 = _mm_loadl_pi(z, (__m64*)(tab + idx[0])); + __m128 xy23 = _mm_loadl_pi(z, (__m64*)(tab + idx[2])); + xy01 = _mm_loadh_pi(xy01, (__m64*)(tab + idx[1])); + xy23 = _mm_loadh_pi(xy23, (__m64*)(tab + idx[3])); + __m128 xxyy02 = _mm_unpacklo_ps(xy01, xy23); + __m128 xxyy13 = _mm_unpackhi_ps(xy01, xy23); + x = v_float32x4(_mm_unpacklo_ps(xxyy02, xxyy13)); + y = v_float32x4(_mm_unpackhi_ps(xxyy02, xxyy13)); +} + +inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y) +{ + int idx[2]; + v_store_low(idx, idxvec); + __m128d xy0 = _mm_loadu_pd(tab + idx[0]); + __m128d xy1 = _mm_loadu_pd(tab + idx[1]); + x = v_float64x2(_mm_unpacklo_pd(xy0, xy1)); + y = v_float64x2(_mm_unpackhi_pd(xy0, xy1)); +} + +inline v_int8x16 v_interleave_pairs(const v_int8x16& vec) +{ +#if CV_SSSE3 + return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0d0e0c0b090a08, 0x0705060403010200))); +#else + __m128i a = _mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(3, 1, 2, 0)); + a = _mm_shufflehi_epi16(a, _MM_SHUFFLE(3, 1, 2, 0)); + a = _mm_shuffle_epi32(a, _MM_SHUFFLE(3, 1, 2, 0)); + return v_int8x16(_mm_unpacklo_epi8(a, _mm_unpackhi_epi64(a, a))); +#endif +} +inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); } +inline v_int8x16 v_interleave_quads(const v_int8x16& vec) +{ +#if CV_SSSE3 + return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0b0e0a0d090c08, 0x0703060205010400))); +#else + __m128i a = _mm_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0)); + return v_int8x16(_mm_unpacklo_epi8(a, _mm_unpackhi_epi64(a, a))); +#endif +} +inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_interleave_pairs(const v_int16x8& vec) +{ +#if CV_SSSE3 + return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0e0b0a0d0c0908, 0x0706030205040100))); +#else + __m128i a = _mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(3, 1, 2, 0)); + return v_int16x8(_mm_shufflehi_epi16(a, _MM_SHUFFLE(3, 1, 2, 0))); +#endif +} +inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); } +inline v_int16x8 v_interleave_quads(const v_int16x8& vec) +{ +#if CV_SSSE3 + return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0e07060d0c0504, 0x0b0a030209080100))); +#else + return v_int16x8(_mm_unpacklo_epi16(vec.val, _mm_unpackhi_epi64(vec.val, vec.val))); +#endif +} +inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_interleave_pairs(const v_int32x4& vec) +{ + return v_int32x4(_mm_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0))); +} +inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } +inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } + +inline v_int8x16 v_pack_triplets(const v_int8x16& vec) +{ +#if CV_SSSE3 + return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0xffffff0f0e0d0c0a, 0x0908060504020100))); +#else + __m128i mask = _mm_set1_epi64x(0x00000000FFFFFFFF); + __m128i a = _mm_srli_si128(_mm_or_si128(_mm_andnot_si128(mask, vec.val), _mm_and_si128(mask, _mm_sll_epi32(vec.val, _mm_set_epi64x(0, 8)))), 1); + return v_int8x16(_mm_srli_si128(_mm_shufflelo_epi16(a, _MM_SHUFFLE(2, 1, 0, 3)), 2)); +#endif +} +inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_pack_triplets(const v_int16x8& vec) +{ +#if CV_SSSE3 + return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0xffff0f0e0d0c0b0a, 0x0908050403020100))); +#else + return v_int16x8(_mm_srli_si128(_mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(2, 1, 0, 3)), 2)); +#endif +} +inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; } +inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; } +inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; } + +////////////// FP16 support /////////////////////////// + +inline v_float32x4 v_load_expand(const float16_t* ptr) +{ + const __m128i z = _mm_setzero_si128(), delta = _mm_set1_epi32(0x38000000); + const __m128i signmask = _mm_set1_epi32(0x80000000), maxexp = _mm_set1_epi32(0x7c000000); + const __m128 deltaf = _mm_castsi128_ps(_mm_set1_epi32(0x38800000)); + __m128i bits = _mm_unpacklo_epi16(z, _mm_loadl_epi64((const __m128i*)ptr)); // h << 16 + __m128i e = _mm_and_si128(bits, maxexp), sign = _mm_and_si128(bits, signmask); + __m128i t = _mm_add_epi32(_mm_srli_epi32(_mm_xor_si128(bits, sign), 3), delta); // ((h & 0x7fff) << 13) + delta + __m128i zt = _mm_castps_si128(_mm_sub_ps(_mm_castsi128_ps(_mm_add_epi32(t, _mm_set1_epi32(1 << 23))), deltaf)); + + t = _mm_add_epi32(t, _mm_and_si128(delta, _mm_cmpeq_epi32(maxexp, e))); + __m128i zmask = _mm_cmpeq_epi32(e, z); + __m128i ft = v_select_si128(zmask, zt, t); + return v_float32x4(_mm_castsi128_ps(_mm_or_si128(ft, sign))); +} + +inline void v_pack_store(float16_t* ptr, const v_float32x4& v) +{ + const __m128i signmask = _mm_set1_epi32(0x80000000); + const __m128i rval = _mm_set1_epi32(0x3f000000); + + __m128i t = _mm_castps_si128(v.val); + __m128i sign = _mm_srai_epi32(_mm_and_si128(t, signmask), 16); + t = _mm_andnot_si128(signmask, t); + + __m128i finitemask = _mm_cmpgt_epi32(_mm_set1_epi32(0x47800000), t); + __m128i isnan = _mm_cmpgt_epi32(t, _mm_set1_epi32(0x7f800000)); + __m128i naninf = v_select_si128(isnan, _mm_set1_epi32(0x7e00), _mm_set1_epi32(0x7c00)); + __m128i tinymask = _mm_cmpgt_epi32(_mm_set1_epi32(0x38800000), t); + __m128i tt = _mm_castps_si128(_mm_add_ps(_mm_castsi128_ps(t), _mm_castsi128_ps(rval))); + tt = _mm_sub_epi32(tt, rval); + __m128i odd = _mm_and_si128(_mm_srli_epi32(t, 13), _mm_set1_epi32(1)); + __m128i nt = _mm_add_epi32(t, _mm_set1_epi32(0xc8000fff)); + nt = _mm_srli_epi32(_mm_add_epi32(nt, odd), 13); + t = v_select_si128(tinymask, tt, nt); + t = v_select_si128(finitemask, t, naninf); + t = _mm_or_si128(t, sign); + t = _mm_packs_epi32(t, t); + _mm_storel_epi64((__m128i*)ptr, t); +} + +inline void v_cleanup() {} + +//! @name Check SIMD support +//! @{ +//! @brief Check CPU capability of SIMD operation +static inline bool hasSIMD128() +{ + return (CV_CPU_HAS_SUPPORT_SSE2) ? true : false; +} + +//! @} + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_sse_em.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_sse_em.hpp new file mode 100644 index 00000000..be276684 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_sse_em.hpp @@ -0,0 +1,167 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +#ifndef OPENCV_HAL_INTRIN_SSE_EM_HPP +#define OPENCV_HAL_INTRIN_SSE_EM_HPP + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +#define OPENCV_HAL_SSE_WRAP_1(fun, tp) \ + inline tp _v128_##fun(const tp& a) \ + { return _mm_##fun(a); } + +#define OPENCV_HAL_SSE_WRAP_2(fun, tp) \ + inline tp _v128_##fun(const tp& a, const tp& b) \ + { return _mm_##fun(a, b); } + +#define OPENCV_HAL_SSE_WRAP_3(fun, tp) \ + inline tp _v128_##fun(const tp& a, const tp& b, const tp& c) \ + { return _mm_##fun(a, b, c); } + +///////////////////////////// XOP ///////////////////////////// + +// [todo] define CV_XOP +#if 1 // CV_XOP +inline __m128i _v128_comgt_epu32(const __m128i& a, const __m128i& b) +{ + const __m128i delta = _mm_set1_epi32((int)0x80000000); + return _mm_cmpgt_epi32(_mm_xor_si128(a, delta), _mm_xor_si128(b, delta)); +} +// wrapping XOP +#else +OPENCV_HAL_SSE_WRAP_2(_v128_comgt_epu32, __m128i) +#endif // !CV_XOP + +///////////////////////////// SSE4.1 ///////////////////////////// + +#if !CV_SSE4_1 + +/** Swizzle **/ +inline __m128i _v128_blendv_epi8(const __m128i& a, const __m128i& b, const __m128i& mask) +{ return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(b, a), mask)); } + +/** Convert **/ +// 8 >> 16 +inline __m128i _v128_cvtepu8_epi16(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpacklo_epi8(a, z); +} +inline __m128i _v128_cvtepi8_epi16(const __m128i& a) +{ return _mm_srai_epi16(_mm_unpacklo_epi8(a, a), 8); } +// 8 >> 32 +inline __m128i _v128_cvtepu8_epi32(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpacklo_epi16(_mm_unpacklo_epi8(a, z), z); +} +inline __m128i _v128_cvtepi8_epi32(const __m128i& a) +{ + __m128i r = _mm_unpacklo_epi8(a, a); + r = _mm_unpacklo_epi8(r, r); + return _mm_srai_epi32(r, 24); +} +// 16 >> 32 +inline __m128i _v128_cvtepu16_epi32(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpacklo_epi16(a, z); +} +inline __m128i _v128_cvtepi16_epi32(const __m128i& a) +{ return _mm_srai_epi32(_mm_unpacklo_epi16(a, a), 16); } +// 32 >> 64 +inline __m128i _v128_cvtepu32_epi64(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpacklo_epi32(a, z); +} +inline __m128i _v128_cvtepi32_epi64(const __m128i& a) +{ return _mm_unpacklo_epi32(a, _mm_srai_epi32(a, 31)); } + +/** Arithmetic **/ +inline __m128i _v128_mullo_epi32(const __m128i& a, const __m128i& b) +{ + __m128i c0 = _mm_mul_epu32(a, b); + __m128i c1 = _mm_mul_epu32(_mm_srli_epi64(a, 32), _mm_srli_epi64(b, 32)); + __m128i d0 = _mm_unpacklo_epi32(c0, c1); + __m128i d1 = _mm_unpackhi_epi32(c0, c1); + return _mm_unpacklo_epi64(d0, d1); +} + +/** Math **/ +inline __m128i _v128_min_epu32(const __m128i& a, const __m128i& b) +{ return _v128_blendv_epi8(a, b, _v128_comgt_epu32(a, b)); } + +// wrapping SSE4.1 +#else +OPENCV_HAL_SSE_WRAP_1(cvtepu8_epi16, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepi8_epi16, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepu8_epi32, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepi8_epi32, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepu16_epi32, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepi16_epi32, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepu32_epi64, __m128i) +OPENCV_HAL_SSE_WRAP_1(cvtepi32_epi64, __m128i) +OPENCV_HAL_SSE_WRAP_2(min_epu32, __m128i) +OPENCV_HAL_SSE_WRAP_2(mullo_epi32, __m128i) +OPENCV_HAL_SSE_WRAP_3(blendv_epi8, __m128i) +#endif // !CV_SSE4_1 + +///////////////////////////// Revolutionary ///////////////////////////// + +/** Convert **/ +// 16 << 8 +inline __m128i _v128_cvtepu8_epi16_high(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpackhi_epi8(a, z); +} +inline __m128i _v128_cvtepi8_epi16_high(const __m128i& a) +{ return _mm_srai_epi16(_mm_unpackhi_epi8(a, a), 8); } +// 32 << 16 +inline __m128i _v128_cvtepu16_epi32_high(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpackhi_epi16(a, z); +} +inline __m128i _v128_cvtepi16_epi32_high(const __m128i& a) +{ return _mm_srai_epi32(_mm_unpackhi_epi16(a, a), 16); } +// 64 << 32 +inline __m128i _v128_cvtepu32_epi64_high(const __m128i& a) +{ + const __m128i z = _mm_setzero_si128(); + return _mm_unpackhi_epi32(a, z); +} +inline __m128i _v128_cvtepi32_epi64_high(const __m128i& a) +{ return _mm_unpackhi_epi32(a, _mm_srai_epi32(a, 31)); } + +/** Miscellaneous **/ +inline __m128i _v128_packs_epu32(const __m128i& a, const __m128i& b) +{ + const __m128i m = _mm_set1_epi32(65535); + __m128i am = _v128_min_epu32(a, m); + __m128i bm = _v128_min_epu32(b, m); +#if CV_SSE4_1 + return _mm_packus_epi32(am, bm); +#else + const __m128i d = _mm_set1_epi32(32768), nd = _mm_set1_epi16(-32768); + am = _mm_sub_epi32(am, d); + bm = _mm_sub_epi32(bm, d); + am = _mm_packs_epi32(am, bm); + return _mm_sub_epi16(am, nd); +#endif +} + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} // cv:: + +#endif // OPENCV_HAL_INTRIN_SSE_EM_HPP \ No newline at end of file diff --git a/3rdparty/opencv/include/opencv2/core/hal/intrin_vsx.hpp b/3rdparty/opencv/include/opencv2/core/hal/intrin_vsx.hpp new file mode 100644 index 00000000..c5ceb113 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/hal/intrin_vsx.hpp @@ -0,0 +1,1328 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +#ifndef OPENCV_HAL_VSX_HPP +#define OPENCV_HAL_VSX_HPP + +#include +#include "opencv2/core/utility.hpp" + +#define CV_SIMD128 1 +#define CV_SIMD128_64F 1 + +namespace cv +{ + +//! @cond IGNORED + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN + +///////// Types //////////// + +struct v_uint8x16 +{ + typedef uchar lane_type; + enum { nlanes = 16 }; + vec_uchar16 val; + + explicit v_uint8x16(const vec_uchar16& v) : val(v) + {} + v_uint8x16() : val(vec_uchar16_z) + {} + v_uint8x16(vec_bchar16 v) : val(vec_uchar16_c(v)) + {} + v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7, + uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15) + : val(vec_uchar16_set(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15)) + {} + uchar get0() const + { return vec_extract(val, 0); } +}; + +struct v_int8x16 +{ + typedef schar lane_type; + enum { nlanes = 16 }; + vec_char16 val; + + explicit v_int8x16(const vec_char16& v) : val(v) + {} + v_int8x16() : val(vec_char16_z) + {} + v_int8x16(vec_bchar16 v) : val(vec_char16_c(v)) + {} + v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7, + schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15) + : val(vec_char16_set(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15)) + {} + schar get0() const + { return vec_extract(val, 0); } +}; + +struct v_uint16x8 +{ + typedef ushort lane_type; + enum { nlanes = 8 }; + vec_ushort8 val; + + explicit v_uint16x8(const vec_ushort8& v) : val(v) + {} + v_uint16x8() : val(vec_ushort8_z) + {} + v_uint16x8(vec_bshort8 v) : val(vec_ushort8_c(v)) + {} + v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7) + : val(vec_ushort8_set(v0, v1, v2, v3, v4, v5, v6, v7)) + {} + ushort get0() const + { return vec_extract(val, 0); } +}; + +struct v_int16x8 +{ + typedef short lane_type; + enum { nlanes = 8 }; + vec_short8 val; + + explicit v_int16x8(const vec_short8& v) : val(v) + {} + v_int16x8() : val(vec_short8_z) + {} + v_int16x8(vec_bshort8 v) : val(vec_short8_c(v)) + {} + v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7) + : val(vec_short8_set(v0, v1, v2, v3, v4, v5, v6, v7)) + {} + short get0() const + { return vec_extract(val, 0); } +}; + +struct v_uint32x4 +{ + typedef unsigned lane_type; + enum { nlanes = 4 }; + vec_uint4 val; + + explicit v_uint32x4(const vec_uint4& v) : val(v) + {} + v_uint32x4() : val(vec_uint4_z) + {} + v_uint32x4(vec_bint4 v) : val(vec_uint4_c(v)) + {} + v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3) : val(vec_uint4_set(v0, v1, v2, v3)) + {} + uint get0() const + { return vec_extract(val, 0); } +}; + +struct v_int32x4 +{ + typedef int lane_type; + enum { nlanes = 4 }; + vec_int4 val; + + explicit v_int32x4(const vec_int4& v) : val(v) + {} + v_int32x4() : val(vec_int4_z) + {} + v_int32x4(vec_bint4 v) : val(vec_int4_c(v)) + {} + v_int32x4(int v0, int v1, int v2, int v3) : val(vec_int4_set(v0, v1, v2, v3)) + {} + int get0() const + { return vec_extract(val, 0); } +}; + +struct v_float32x4 +{ + typedef float lane_type; + enum { nlanes = 4 }; + vec_float4 val; + + explicit v_float32x4(const vec_float4& v) : val(v) + {} + v_float32x4() : val(vec_float4_z) + {} + v_float32x4(vec_bint4 v) : val(vec_float4_c(v)) + {} + v_float32x4(float v0, float v1, float v2, float v3) : val(vec_float4_set(v0, v1, v2, v3)) + {} + float get0() const + { return vec_extract(val, 0); } +}; + +struct v_uint64x2 +{ + typedef uint64 lane_type; + enum { nlanes = 2 }; + vec_udword2 val; + + explicit v_uint64x2(const vec_udword2& v) : val(v) + {} + v_uint64x2() : val(vec_udword2_z) + {} + v_uint64x2(vec_bdword2 v) : val(vec_udword2_c(v)) + {} + v_uint64x2(uint64 v0, uint64 v1) : val(vec_udword2_set(v0, v1)) + {} + uint64 get0() const + { return vec_extract(val, 0); } +}; + +struct v_int64x2 +{ + typedef int64 lane_type; + enum { nlanes = 2 }; + vec_dword2 val; + + explicit v_int64x2(const vec_dword2& v) : val(v) + {} + v_int64x2() : val(vec_dword2_z) + {} + v_int64x2(vec_bdword2 v) : val(vec_dword2_c(v)) + {} + v_int64x2(int64 v0, int64 v1) : val(vec_dword2_set(v0, v1)) + {} + int64 get0() const + { return vec_extract(val, 0); } +}; + +struct v_float64x2 +{ + typedef double lane_type; + enum { nlanes = 2 }; + vec_double2 val; + + explicit v_float64x2(const vec_double2& v) : val(v) + {} + v_float64x2() : val(vec_double2_z) + {} + v_float64x2(vec_bdword2 v) : val(vec_double2_c(v)) + {} + v_float64x2(double v0, double v1) : val(vec_double2_set(v0, v1)) + {} + double get0() const + { return vec_extract(val, 0); } +}; + +//////////////// Load and store operations /////////////// + +/* + * clang-5 aborted during parse "vec_xxx_c" only if it's + * inside a function template which is defined by preprocessor macro. + * + * if vec_xxx_c defined as C++ cast, clang-5 will pass it +*/ +#define OPENCV_HAL_IMPL_VSX_INITVEC(_Tpvec, _Tp, suffix, cast) \ +inline _Tpvec v_setzero_##suffix() { return _Tpvec(); } \ +inline _Tpvec v_setall_##suffix(_Tp v) { return _Tpvec(vec_splats((_Tp)v));} \ +template inline _Tpvec v_reinterpret_as_##suffix(const _Tpvec0 &a) \ +{ return _Tpvec((cast)a.val); } + +OPENCV_HAL_IMPL_VSX_INITVEC(v_uint8x16, uchar, u8, vec_uchar16) +OPENCV_HAL_IMPL_VSX_INITVEC(v_int8x16, schar, s8, vec_char16) +OPENCV_HAL_IMPL_VSX_INITVEC(v_uint16x8, ushort, u16, vec_ushort8) +OPENCV_HAL_IMPL_VSX_INITVEC(v_int16x8, short, s16, vec_short8) +OPENCV_HAL_IMPL_VSX_INITVEC(v_uint32x4, uint, u32, vec_uint4) +OPENCV_HAL_IMPL_VSX_INITVEC(v_int32x4, int, s32, vec_int4) +OPENCV_HAL_IMPL_VSX_INITVEC(v_uint64x2, uint64, u64, vec_udword2) +OPENCV_HAL_IMPL_VSX_INITVEC(v_int64x2, int64, s64, vec_dword2) +OPENCV_HAL_IMPL_VSX_INITVEC(v_float32x4, float, f32, vec_float4) +OPENCV_HAL_IMPL_VSX_INITVEC(v_float64x2, double, f64, vec_double2) + +#define OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, ld, ld_a, st, st_a) \ +inline _Tpvec v_load(const _Tp* ptr) \ +{ return _Tpvec(ld(0, ptr)); } \ +inline _Tpvec v_load_aligned(VSX_UNUSED(const _Tp* ptr)) \ +{ return _Tpvec(ld_a(0, ptr)); } \ +inline _Tpvec v_load_low(const _Tp* ptr) \ +{ return _Tpvec(vec_ld_l8(ptr)); } \ +inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \ +{ return _Tpvec(vec_mergesqh(vec_ld_l8(ptr0), vec_ld_l8(ptr1))); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a) \ +{ st(a.val, 0, ptr); } \ +inline void v_store_aligned(VSX_UNUSED(_Tp* ptr), const _Tpvec& a) \ +{ st_a(a.val, 0, ptr); } \ +inline void v_store_aligned_nocache(VSX_UNUSED(_Tp* ptr), const _Tpvec& a) \ +{ st_a(a.val, 0, ptr); } \ +inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \ +{ if(mode == hal::STORE_UNALIGNED) st(a.val, 0, ptr); else st_a(a.val, 0, ptr); } \ +inline void v_store_low(_Tp* ptr, const _Tpvec& a) \ +{ vec_st_l8(a.val, ptr); } \ +inline void v_store_high(_Tp* ptr, const _Tpvec& a) \ +{ vec_st_h8(a.val, ptr); } + +// working around gcc bug for aligned ld/st +// if runtime check for vec_ld/st fail we failback to unaligned ld/st +// https://github.com/opencv/opencv/issues/13211 +#ifdef CV_COMPILER_VSX_BROKEN_ALIGNED + #define OPENCV_HAL_IMPL_VSX_LOADSTORE(_Tpvec, _Tp) \ + OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, vsx_ld, vsx_ld, vsx_st, vsx_st) +#else + #define OPENCV_HAL_IMPL_VSX_LOADSTORE(_Tpvec, _Tp) \ + OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, vsx_ld, vec_ld, vsx_st, vec_st) +#endif + +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint8x16, uchar) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int8x16, schar) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint16x8, ushort) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int16x8, short) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint32x4, uint) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int32x4, int) +OPENCV_HAL_IMPL_VSX_LOADSTORE(v_float32x4, float) + +OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_float64x2, double, vsx_ld, vsx_ld, vsx_st, vsx_st) +OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_uint64x2, uint64, vsx_ld2, vsx_ld2, vsx_st2, vsx_st2) +OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_int64x2, int64, vsx_ld2, vsx_ld2, vsx_st2, vsx_st2) + +//////////////// Value reordering /////////////// + +/* de&interleave */ +#define OPENCV_HAL_IMPL_VSX_INTERLEAVE(_Tp, _Tpvec) \ +inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a, _Tpvec& b) \ +{ vec_ld_deinterleave(ptr, a.val, b.val);} \ +inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a, \ + _Tpvec& b, _Tpvec& c) \ +{ vec_ld_deinterleave(ptr, a.val, b.val, c.val); } \ +inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a, _Tpvec& b, \ + _Tpvec& c, _Tpvec& d) \ +{ vec_ld_deinterleave(ptr, a.val, b.val, c.val, d.val); } \ +inline void v_store_interleave(_Tp* ptr, const _Tpvec& a, const _Tpvec& b, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ vec_st_interleave(a.val, b.val, ptr); } \ +inline void v_store_interleave(_Tp* ptr, const _Tpvec& a, \ + const _Tpvec& b, const _Tpvec& c, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ vec_st_interleave(a.val, b.val, c.val, ptr); } \ +inline void v_store_interleave(_Tp* ptr, const _Tpvec& a, const _Tpvec& b, \ + const _Tpvec& c, const _Tpvec& d, \ + hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \ +{ vec_st_interleave(a.val, b.val, c.val, d.val, ptr); } + +OPENCV_HAL_IMPL_VSX_INTERLEAVE(uchar, v_uint8x16) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(schar, v_int8x16) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(ushort, v_uint16x8) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(short, v_int16x8) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(uint, v_uint32x4) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(int, v_int32x4) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(float, v_float32x4) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(double, v_float64x2) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(int64, v_int64x2) +OPENCV_HAL_IMPL_VSX_INTERLEAVE(uint64, v_uint64x2) + +/* Expand */ +#define OPENCV_HAL_IMPL_VSX_EXPAND(_Tpvec, _Tpwvec, _Tp, fl, fh) \ +inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \ +{ \ + b0.val = fh(a.val); \ + b1.val = fl(a.val); \ +} \ +inline _Tpwvec v_expand_low(const _Tpvec& a) \ +{ return _Tpwvec(fh(a.val)); } \ +inline _Tpwvec v_expand_high(const _Tpvec& a) \ +{ return _Tpwvec(fl(a.val)); } \ +inline _Tpwvec v_load_expand(const _Tp* ptr) \ +{ return _Tpwvec(fh(vec_ld_l8(ptr))); } + +OPENCV_HAL_IMPL_VSX_EXPAND(v_uint8x16, v_uint16x8, uchar, vec_unpacklu, vec_unpackhu) +OPENCV_HAL_IMPL_VSX_EXPAND(v_int8x16, v_int16x8, schar, vec_unpackl, vec_unpackh) +OPENCV_HAL_IMPL_VSX_EXPAND(v_uint16x8, v_uint32x4, ushort, vec_unpacklu, vec_unpackhu) +OPENCV_HAL_IMPL_VSX_EXPAND(v_int16x8, v_int32x4, short, vec_unpackl, vec_unpackh) +OPENCV_HAL_IMPL_VSX_EXPAND(v_uint32x4, v_uint64x2, uint, vec_unpacklu, vec_unpackhu) +OPENCV_HAL_IMPL_VSX_EXPAND(v_int32x4, v_int64x2, int, vec_unpackl, vec_unpackh) + +inline v_uint32x4 v_load_expand_q(const uchar* ptr) +{ return v_uint32x4(vec_uint4_set(ptr[0], ptr[1], ptr[2], ptr[3])); } + +inline v_int32x4 v_load_expand_q(const schar* ptr) +{ return v_int32x4(vec_int4_set(ptr[0], ptr[1], ptr[2], ptr[3])); } + +/* pack */ +#define OPENCV_HAL_IMPL_VSX_PACK(_Tpvec, _Tp, _Tpwvec, _Tpvn, _Tpdel, sfnc, pkfnc, addfnc, pack) \ +inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b) \ +{ \ + return _Tpvec(pkfnc(a.val, b.val)); \ +} \ +inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a) \ +{ \ + vec_st_l8(pkfnc(a.val, a.val), ptr); \ +} \ +template \ +inline _Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b) \ +{ \ + const __vector _Tpvn vn = vec_splats((_Tpvn)n); \ + const __vector _Tpdel delta = vec_splats((_Tpdel)((_Tpdel)1 << (n-1))); \ + return _Tpvec(pkfnc(sfnc(addfnc(a.val, delta), vn), sfnc(addfnc(b.val, delta), vn))); \ +} \ +template \ +inline void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a) \ +{ \ + const __vector _Tpvn vn = vec_splats((_Tpvn)n); \ + const __vector _Tpdel delta = vec_splats((_Tpdel)((_Tpdel)1 << (n-1))); \ + vec_st_l8(pkfnc(sfnc(addfnc(a.val, delta), vn), delta), ptr); \ +} + +OPENCV_HAL_IMPL_VSX_PACK(v_uint8x16, uchar, v_uint16x8, unsigned short, unsigned short, + vec_sr, vec_packs, vec_adds, pack) +OPENCV_HAL_IMPL_VSX_PACK(v_int8x16, schar, v_int16x8, unsigned short, short, + vec_sra, vec_packs, vec_adds, pack) + +OPENCV_HAL_IMPL_VSX_PACK(v_uint16x8, ushort, v_uint32x4, unsigned int, unsigned int, + vec_sr, vec_packs, vec_add, pack) +OPENCV_HAL_IMPL_VSX_PACK(v_int16x8, short, v_int32x4, unsigned int, int, + vec_sra, vec_packs, vec_add, pack) + +OPENCV_HAL_IMPL_VSX_PACK(v_uint32x4, uint, v_uint64x2, unsigned long long, unsigned long long, + vec_sr, vec_pack, vec_add, pack) +OPENCV_HAL_IMPL_VSX_PACK(v_int32x4, int, v_int64x2, unsigned long long, long long, + vec_sra, vec_pack, vec_add, pack) + +OPENCV_HAL_IMPL_VSX_PACK(v_uint8x16, uchar, v_int16x8, unsigned short, short, + vec_sra, vec_packsu, vec_adds, pack_u) +OPENCV_HAL_IMPL_VSX_PACK(v_uint16x8, ushort, v_int32x4, unsigned int, int, + vec_sra, vec_packsu, vec_add, pack_u) +// Following variant is not implemented on other platforms: +//OPENCV_HAL_IMPL_VSX_PACK(v_uint32x4, uint, v_int64x2, unsigned long long, long long, +// vec_sra, vec_packsu, vec_add, pack_u) + +// pack boolean +inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b) +{ + vec_uchar16 ab = vec_pack(a.val, b.val); + return v_uint8x16(ab); +} + +inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b, + const v_uint32x4& c, const v_uint32x4& d) +{ + vec_ushort8 ab = vec_pack(a.val, b.val); + vec_ushort8 cd = vec_pack(c.val, d.val); + return v_uint8x16(vec_pack(ab, cd)); +} + +inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c, + const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f, + const v_uint64x2& g, const v_uint64x2& h) +{ + vec_uint4 ab = vec_pack(a.val, b.val); + vec_uint4 cd = vec_pack(c.val, d.val); + vec_uint4 ef = vec_pack(e.val, f.val); + vec_uint4 gh = vec_pack(g.val, h.val); + + vec_ushort8 abcd = vec_pack(ab, cd); + vec_ushort8 efgh = vec_pack(ef, gh); + return v_uint8x16(vec_pack(abcd, efgh)); +} + +/* Recombine */ +template +inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) +{ + b0.val = vec_mergeh(a0.val, a1.val); + b1.val = vec_mergel(a0.val, a1.val); +} + +template +inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) +{ return _Tpvec(vec_mergesql(a.val, b.val)); } + +template +inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) +{ return _Tpvec(vec_mergesqh(a.val, b.val)); } + +template +inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) +{ + c.val = vec_mergesqh(a.val, b.val); + d.val = vec_mergesql(a.val, b.val); +} + +////////// Arithmetic, bitwise and comparison operations ///////// + +/* Element-wise binary and unary operations */ +/** Arithmetics **/ +#define OPENCV_HAL_IMPL_VSX_BIN_OP(bin_op, _Tpvec, intrin) \ +inline _Tpvec operator bin_op (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(intrin(a.val, b.val)); } \ +inline _Tpvec& operator bin_op##= (_Tpvec& a, const _Tpvec& b) \ +{ a.val = intrin(a.val, b.val); return a; } + +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_uint8x16, vec_adds) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_uint8x16, vec_subs) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_int8x16, vec_adds) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_int8x16, vec_subs) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_uint16x8, vec_adds) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_uint16x8, vec_subs) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_int16x8, vec_adds) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_int16x8, vec_subs) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_uint32x4, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_uint32x4, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_OP(*, v_uint32x4, vec_mul) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_int32x4, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_int32x4, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_OP(*, v_int32x4, vec_mul) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_float32x4, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_float32x4, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_OP(*, v_float32x4, vec_mul) +OPENCV_HAL_IMPL_VSX_BIN_OP(/, v_float32x4, vec_div) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_float64x2, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_float64x2, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_OP(*, v_float64x2, vec_mul) +OPENCV_HAL_IMPL_VSX_BIN_OP(/, v_float64x2, vec_div) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_uint64x2, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_uint64x2, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_OP(+, v_int64x2, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_OP(-, v_int64x2, vec_sub) + +// saturating multiply +#define OPENCV_HAL_IMPL_VSX_MUL_SAT(_Tpvec, _Tpwvec) \ + inline _Tpvec operator * (const _Tpvec& a, const _Tpvec& b) \ + { \ + _Tpwvec c, d; \ + v_mul_expand(a, b, c, d); \ + return v_pack(c, d); \ + } \ + inline _Tpvec& operator *= (_Tpvec& a, const _Tpvec& b) \ + { a = a * b; return a; } + +OPENCV_HAL_IMPL_VSX_MUL_SAT(v_int8x16, v_int16x8) +OPENCV_HAL_IMPL_VSX_MUL_SAT(v_uint8x16, v_uint16x8) +OPENCV_HAL_IMPL_VSX_MUL_SAT(v_int16x8, v_int32x4) +OPENCV_HAL_IMPL_VSX_MUL_SAT(v_uint16x8, v_uint32x4) + +template +inline void v_mul_expand(const Tvec& a, const Tvec& b, Twvec& c, Twvec& d) +{ + Twvec p0 = Twvec(vec_mule(a.val, b.val)); + Twvec p1 = Twvec(vec_mulo(a.val, b.val)); + v_zip(p0, p1, c, d); +} + +inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b, v_uint64x2& c, v_uint64x2& d) +{ + c.val = vec_mul(vec_unpackhu(a.val), vec_unpackhu(b.val)); + d.val = vec_mul(vec_unpacklu(a.val), vec_unpacklu(b.val)); +} + +inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b) +{ + vec_int4 p0 = vec_mule(a.val, b.val); + vec_int4 p1 = vec_mulo(a.val, b.val); + static const vec_uchar16 perm = {2, 3, 18, 19, 6, 7, 22, 23, 10, 11, 26, 27, 14, 15, 30, 31}; + return v_int16x8(vec_perm(vec_short8_c(p0), vec_short8_c(p1), perm)); +} +inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b) +{ + vec_uint4 p0 = vec_mule(a.val, b.val); + vec_uint4 p1 = vec_mulo(a.val, b.val); + static const vec_uchar16 perm = {2, 3, 18, 19, 6, 7, 22, 23, 10, 11, 26, 27, 14, 15, 30, 31}; + return v_uint16x8(vec_perm(vec_ushort8_c(p0), vec_ushort8_c(p1), perm)); +} + +/** Non-saturating arithmetics **/ +#define OPENCV_HAL_IMPL_VSX_BIN_FUNC(func, intrin) \ +template \ +inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(intrin(a.val, b.val)); } + +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_add_wrap, vec_add) +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_sub_wrap, vec_sub) +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_mul_wrap, vec_mul) + +/** Bitwise shifts **/ +#define OPENCV_HAL_IMPL_VSX_SHIFT_OP(_Tpvec, shr, splfunc) \ +inline _Tpvec operator << (const _Tpvec& a, int imm) \ +{ return _Tpvec(vec_sl(a.val, splfunc(imm))); } \ +inline _Tpvec operator >> (const _Tpvec& a, int imm) \ +{ return _Tpvec(shr(a.val, splfunc(imm))); } \ +template inline _Tpvec v_shl(const _Tpvec& a) \ +{ return _Tpvec(vec_sl(a.val, splfunc(imm))); } \ +template inline _Tpvec v_shr(const _Tpvec& a) \ +{ return _Tpvec(shr(a.val, splfunc(imm))); } + +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint8x16, vec_sr, vec_uchar16_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint16x8, vec_sr, vec_ushort8_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint32x4, vec_sr, vec_uint4_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint64x2, vec_sr, vec_udword2_sp) +// algebraic right shift +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int8x16, vec_sra, vec_uchar16_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int16x8, vec_sra, vec_ushort8_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int32x4, vec_sra, vec_uint4_sp) +OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int64x2, vec_sra, vec_udword2_sp) + +/** Bitwise logic **/ +#define OPENCV_HAL_IMPL_VSX_LOGIC_OP(_Tpvec) \ +OPENCV_HAL_IMPL_VSX_BIN_OP(&, _Tpvec, vec_and) \ +OPENCV_HAL_IMPL_VSX_BIN_OP(|, _Tpvec, vec_or) \ +OPENCV_HAL_IMPL_VSX_BIN_OP(^, _Tpvec, vec_xor) \ +inline _Tpvec operator ~ (const _Tpvec& a) \ +{ return _Tpvec(vec_not(a.val)); } + +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint8x16) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int8x16) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint16x8) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int16x8) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint32x4) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int32x4) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint64x2) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int64x2) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_float32x4) +OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_float64x2) + +/** Bitwise select **/ +#define OPENCV_HAL_IMPL_VSX_SELECT(_Tpvec, cast) \ +inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_sel(b.val, a.val, cast(mask.val))); } + +OPENCV_HAL_IMPL_VSX_SELECT(v_uint8x16, vec_bchar16_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_int8x16, vec_bchar16_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_uint16x8, vec_bshort8_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_int16x8, vec_bshort8_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_uint32x4, vec_bint4_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_int32x4, vec_bint4_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_float32x4, vec_bint4_c) +OPENCV_HAL_IMPL_VSX_SELECT(v_float64x2, vec_bdword2_c) + +/** Comparison **/ +#define OPENCV_HAL_IMPL_VSX_INT_CMP_OP(_Tpvec) \ +inline _Tpvec operator == (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmpeq(a.val, b.val)); } \ +inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmpne(a.val, b.val)); } \ +inline _Tpvec operator < (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmplt(a.val, b.val)); } \ +inline _Tpvec operator > (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmpgt(a.val, b.val)); } \ +inline _Tpvec operator <= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmple(a.val, b.val)); } \ +inline _Tpvec operator >= (const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_cmpge(a.val, b.val)); } + +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint8x16) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int8x16) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint16x8) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int16x8) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint32x4) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int32x4) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float32x4) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float64x2) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint64x2) +OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int64x2) + +inline v_float32x4 v_not_nan(const v_float32x4& a) +{ return v_float32x4(vec_cmpeq(a.val, a.val)); } +inline v_float64x2 v_not_nan(const v_float64x2& a) +{ return v_float64x2(vec_cmpeq(a.val, a.val)); } + +/** min/max **/ +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_min, vec_min) +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_max, vec_max) + +/** Rotate **/ +#define OPENCV_IMPL_VSX_ROTATE(_Tpvec, suffix, shf, cast) \ +template \ +inline _Tpvec v_rotate_##suffix(const _Tpvec& a) \ +{ \ + const int wd = imm * sizeof(typename _Tpvec::lane_type); \ + if (wd > 15) \ + return _Tpvec(); \ + return _Tpvec((cast)shf(vec_uchar16_c(a.val), vec_uchar16_sp(wd << 3))); \ +} + +#define OPENCV_IMPL_VSX_ROTATE_LR(_Tpvec, cast) \ +OPENCV_IMPL_VSX_ROTATE(_Tpvec, left, vec_slo, cast) \ +OPENCV_IMPL_VSX_ROTATE(_Tpvec, right, vec_sro, cast) + +OPENCV_IMPL_VSX_ROTATE_LR(v_uint8x16, vec_uchar16) +OPENCV_IMPL_VSX_ROTATE_LR(v_int8x16, vec_char16) +OPENCV_IMPL_VSX_ROTATE_LR(v_uint16x8, vec_ushort8) +OPENCV_IMPL_VSX_ROTATE_LR(v_int16x8, vec_short8) +OPENCV_IMPL_VSX_ROTATE_LR(v_uint32x4, vec_uint4) +OPENCV_IMPL_VSX_ROTATE_LR(v_int32x4, vec_int4) +OPENCV_IMPL_VSX_ROTATE_LR(v_float32x4, vec_float4) +OPENCV_IMPL_VSX_ROTATE_LR(v_uint64x2, vec_udword2) +OPENCV_IMPL_VSX_ROTATE_LR(v_int64x2, vec_dword2) +OPENCV_IMPL_VSX_ROTATE_LR(v_float64x2, vec_double2) + +template +inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) +{ + enum { CV_SHIFT = 16 - imm * (sizeof(typename _Tpvec::lane_type)) }; + if (CV_SHIFT == 16) + return a; +#ifdef __IBMCPP__ + return _Tpvec(vec_sld(b.val, a.val, CV_SHIFT & 15)); +#else + return _Tpvec(vec_sld(b.val, a.val, CV_SHIFT)); +#endif +} + +template +inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) +{ + enum { CV_SHIFT = imm * (sizeof(typename _Tpvec::lane_type)) }; + if (CV_SHIFT == 16) + return b; + return _Tpvec(vec_sld(a.val, b.val, CV_SHIFT)); +} + +#define OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, suffix, rg1, rg2) \ +template \ +inline _Tpvec v_rotate_##suffix(const _Tpvec& a, const _Tpvec& b) \ +{ \ + if (imm == 1) \ + return _Tpvec(vec_permi(rg1.val, rg2.val, 2)); \ + return imm ? b : a; \ +} + +#define OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(_Tpvec) \ +OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, left, b, a) \ +OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, right, a, b) + +OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_float64x2) +OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_uint64x2) +OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_int64x2) + +/* Extract */ +template +inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) +{ return v_rotate_right(a, b); } + +////////// Reduce and mask ///////// + +/** Reduce **/ +inline short v_reduce_sum(const v_int16x8& a) +{ + const vec_int4 zero = vec_int4_z; + return saturate_cast(vec_extract(vec_sums(vec_sum4s(a.val, zero), zero), 3)); +} +inline ushort v_reduce_sum(const v_uint16x8& a) +{ + const vec_int4 v4 = vec_int4_c(vec_unpackhu(vec_adds(a.val, vec_sld(a.val, a.val, 8)))); + return saturate_cast(vec_extract(vec_sums(v4, vec_int4_z), 3)); +} + +#define OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(_Tpvec, _Tpvec2, scalartype, suffix, func) \ +inline scalartype v_reduce_##suffix(const _Tpvec& a) \ +{ \ + const _Tpvec2 rs = func(a.val, vec_sld(a.val, a.val, 8)); \ + return vec_extract(func(rs, vec_sld(rs, rs, 4)), 0); \ +} +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, sum, vec_add) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, max, vec_max) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, min, vec_min) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, sum, vec_add) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, max, vec_max) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, min, vec_min) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, sum, vec_add) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, max, vec_max) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, min, vec_min) + +inline double v_reduce_sum(const v_float64x2& a) +{ + return vec_extract(vec_add(a.val, vec_permi(a.val, a.val, 3)), 0); +} + +#define OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(_Tpvec, _Tpvec2, scalartype, suffix, func) \ +inline scalartype v_reduce_##suffix(const _Tpvec& a) \ +{ \ + _Tpvec2 rs = func(a.val, vec_sld(a.val, a.val, 8)); \ + rs = func(rs, vec_sld(rs, rs, 4)); \ + return vec_extract(func(rs, vec_sld(rs, rs, 2)), 0); \ +} +OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_uint16x8, vec_ushort8, ushort, max, vec_max) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_uint16x8, vec_ushort8, ushort, min, vec_min) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_int16x8, vec_short8, short, max, vec_max) +OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_int16x8, vec_short8, short, min, vec_min) + +inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b, + const v_float32x4& c, const v_float32x4& d) +{ + vec_float4 ac = vec_add(vec_mergel(a.val, c.val), vec_mergeh(a.val, c.val)); + ac = vec_add(ac, vec_sld(ac, ac, 8)); + + vec_float4 bd = vec_add(vec_mergel(b.val, d.val), vec_mergeh(b.val, d.val)); + bd = vec_add(bd, vec_sld(bd, bd, 8)); + return v_float32x4(vec_mergeh(ac, bd)); +} + +inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b) +{ + const vec_uint4 zero4 = vec_uint4_z; + vec_uint4 sum4 = vec_sum4s(vec_absd(a.val, b.val), zero4); + return (unsigned)vec_extract(vec_sums(vec_int4_c(sum4), vec_int4_c(zero4)), 3); +} +inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b) +{ + const vec_int4 zero4 = vec_int4_z; + vec_char16 ad = vec_abss(vec_subs(a.val, b.val)); + vec_int4 sum4 = vec_sum4s(ad, zero4); + return (unsigned)vec_extract(vec_sums(sum4, zero4), 3); +} +inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b) +{ + vec_ushort8 ad = vec_absd(a.val, b.val); + VSX_UNUSED(vec_int4) sum = vec_sums(vec_int4_c(vec_unpackhu(ad)), vec_int4_c(vec_unpacklu(ad))); + return (unsigned)vec_extract(sum, 3); +} +inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b) +{ + const vec_int4 zero4 = vec_int4_z; + vec_short8 ad = vec_abss(vec_subs(a.val, b.val)); + vec_int4 sum4 = vec_sum4s(ad, zero4); + return (unsigned)vec_extract(vec_sums(sum4, zero4), 3); +} +inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b) +{ + const vec_uint4 ad = vec_absd(a.val, b.val); + const vec_uint4 rd = vec_add(ad, vec_sld(ad, ad, 8)); + return vec_extract(vec_add(rd, vec_sld(rd, rd, 4)), 0); +} +inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b) +{ + vec_int4 ad = vec_abss(vec_sub(a.val, b.val)); + return (unsigned)vec_extract(vec_sums(ad, vec_int4_z), 3); +} +inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b) +{ + const vec_float4 ad = vec_abs(vec_sub(a.val, b.val)); + const vec_float4 rd = vec_add(ad, vec_sld(ad, ad, 8)); + return vec_extract(vec_add(rd, vec_sld(rd, rd, 4)), 0); +} + +/** Popcount **/ +template +inline v_uint32x4 v_popcount(const _Tpvec& a) +{ return v_uint32x4(vec_popcntu(vec_uint4_c(a.val))); } + +/** Mask **/ +inline int v_signmask(const v_uint8x16& a) +{ + vec_uchar16 sv = vec_sr(a.val, vec_uchar16_sp(7)); + static const vec_uchar16 slm = {0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7}; + sv = vec_sl(sv, slm); + vec_uint4 sv4 = vec_sum4s(sv, vec_uint4_z); + static const vec_uint4 slm4 = {0, 0, 8, 8}; + sv4 = vec_sl(sv4, slm4); + return vec_extract(vec_sums((vec_int4) sv4, vec_int4_z), 3); +} +inline int v_signmask(const v_int8x16& a) +{ return v_signmask(v_reinterpret_as_u8(a)); } + +inline int v_signmask(const v_int16x8& a) +{ + static const vec_ushort8 slm = {0, 1, 2, 3, 4, 5, 6, 7}; + vec_short8 sv = vec_sr(a.val, vec_ushort8_sp(15)); + sv = vec_sl(sv, slm); + vec_int4 svi = vec_int4_z; + svi = vec_sums(vec_sum4s(sv, svi), svi); + return vec_extract(svi, 3); +} +inline int v_signmask(const v_uint16x8& a) +{ return v_signmask(v_reinterpret_as_s16(a)); } + +inline int v_signmask(const v_int32x4& a) +{ + static const vec_uint4 slm = {0, 1, 2, 3}; + vec_int4 sv = vec_sr(a.val, vec_uint4_sp(31)); + sv = vec_sl(sv, slm); + sv = vec_sums(sv, vec_int4_z); + return vec_extract(sv, 3); +} +inline int v_signmask(const v_uint32x4& a) +{ return v_signmask(v_reinterpret_as_s32(a)); } +inline int v_signmask(const v_float32x4& a) +{ return v_signmask(v_reinterpret_as_s32(a)); } + +inline int v_signmask(const v_int64x2& a) +{ + VSX_UNUSED(const vec_dword2) sv = vec_sr(a.val, vec_udword2_sp(63)); + return (int)vec_extract(sv, 0) | (int)vec_extract(sv, 1) << 1; +} +inline int v_signmask(const v_uint64x2& a) +{ return v_signmask(v_reinterpret_as_s64(a)); } +inline int v_signmask(const v_float64x2& a) +{ return v_signmask(v_reinterpret_as_s64(a)); } + +template +inline bool v_check_all(const _Tpvec& a) +{ return vec_all_lt(a.val, _Tpvec().val); } +inline bool v_check_all(const v_uint8x16& a) +{ return v_check_all(v_reinterpret_as_s8(a)); } +inline bool v_check_all(const v_uint16x8& a) +{ return v_check_all(v_reinterpret_as_s16(a)); } +inline bool v_check_all(const v_uint32x4& a) +{ return v_check_all(v_reinterpret_as_s32(a)); } +inline bool v_check_all(const v_float32x4& a) +{ return v_check_all(v_reinterpret_as_s32(a)); } +inline bool v_check_all(const v_float64x2& a) +{ return v_check_all(v_reinterpret_as_s64(a)); } + +template +inline bool v_check_any(const _Tpvec& a) +{ return vec_any_lt(a.val, _Tpvec().val); } +inline bool v_check_any(const v_uint8x16& a) +{ return v_check_any(v_reinterpret_as_s8(a)); } +inline bool v_check_any(const v_uint16x8& a) +{ return v_check_any(v_reinterpret_as_s16(a)); } +inline bool v_check_any(const v_uint32x4& a) +{ return v_check_any(v_reinterpret_as_s32(a)); } +inline bool v_check_any(const v_float32x4& a) +{ return v_check_any(v_reinterpret_as_s32(a)); } +inline bool v_check_any(const v_float64x2& a) +{ return v_check_any(v_reinterpret_as_s64(a)); } + +////////// Other math ///////// + +/** Some frequent operations **/ +inline v_float32x4 v_sqrt(const v_float32x4& x) +{ return v_float32x4(vec_sqrt(x.val)); } +inline v_float64x2 v_sqrt(const v_float64x2& x) +{ return v_float64x2(vec_sqrt(x.val)); } + +inline v_float32x4 v_invsqrt(const v_float32x4& x) +{ return v_float32x4(vec_rsqrt(x.val)); } +inline v_float64x2 v_invsqrt(const v_float64x2& x) +{ return v_float64x2(vec_rsqrt(x.val)); } + +#define OPENCV_HAL_IMPL_VSX_MULADD(_Tpvec) \ +inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_sqrt(vec_madd(a.val, a.val, vec_mul(b.val, b.val)))); } \ +inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b) \ +{ return _Tpvec(vec_madd(a.val, a.val, vec_mul(b.val, b.val))); } \ +inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \ +{ return _Tpvec(vec_madd(a.val, b.val, c.val)); } \ +inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \ +{ return _Tpvec(vec_madd(a.val, b.val, c.val)); } + +OPENCV_HAL_IMPL_VSX_MULADD(v_float32x4) +OPENCV_HAL_IMPL_VSX_MULADD(v_float64x2) + +inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c) +{ return a * b + c; } + +// TODO: exp, log, sin, cos + +/** Absolute values **/ +inline v_uint8x16 v_abs(const v_int8x16& x) +{ return v_uint8x16(vec_uchar16_c(vec_abs(x.val))); } + +inline v_uint16x8 v_abs(const v_int16x8& x) +{ return v_uint16x8(vec_ushort8_c(vec_abs(x.val))); } + +inline v_uint32x4 v_abs(const v_int32x4& x) +{ return v_uint32x4(vec_uint4_c(vec_abs(x.val))); } + +inline v_float32x4 v_abs(const v_float32x4& x) +{ return v_float32x4(vec_abs(x.val)); } + +inline v_float64x2 v_abs(const v_float64x2& x) +{ return v_float64x2(vec_abs(x.val)); } + +/** Absolute difference **/ +// unsigned +OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_absdiff, vec_absd) + +inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b) +{ return v_reinterpret_as_u8(v_sub_wrap(v_max(a, b), v_min(a, b))); } +inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b) +{ return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); } +inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b) +{ return v_reinterpret_as_u32(v_max(a, b) - v_min(a, b)); } + +inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b) +{ return v_abs(a - b); } +inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b) +{ return v_abs(a - b); } + +/** Absolute difference for signed integers **/ +inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b) +{ return v_int8x16(vec_abss(vec_subs(a.val, b.val))); } +inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b) +{ return v_int16x8(vec_abss(vec_subs(a.val, b.val))); } + +////////// Conversions ///////// + +/** Rounding **/ +inline v_int32x4 v_round(const v_float32x4& a) +{ return v_int32x4(vec_cts(vec_rint(a.val))); } + +inline v_int32x4 v_round(const v_float64x2& a) +{ return v_int32x4(vec_mergesqo(vec_ctso(vec_rint(a.val)), vec_int4_z)); } + +inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b) +{ return v_int32x4(vec_mergesqo(vec_ctso(vec_rint(a.val)), vec_ctso(vec_rint(b.val)))); } + +inline v_int32x4 v_floor(const v_float32x4& a) +{ return v_int32x4(vec_cts(vec_floor(a.val))); } + +inline v_int32x4 v_floor(const v_float64x2& a) +{ return v_int32x4(vec_mergesqo(vec_ctso(vec_floor(a.val)), vec_int4_z)); } + +inline v_int32x4 v_ceil(const v_float32x4& a) +{ return v_int32x4(vec_cts(vec_ceil(a.val))); } + +inline v_int32x4 v_ceil(const v_float64x2& a) +{ return v_int32x4(vec_mergesqo(vec_ctso(vec_ceil(a.val)), vec_int4_z)); } + +inline v_int32x4 v_trunc(const v_float32x4& a) +{ return v_int32x4(vec_cts(a.val)); } + +inline v_int32x4 v_trunc(const v_float64x2& a) +{ return v_int32x4(vec_mergesqo(vec_ctso(a.val), vec_int4_z)); } + +/** To float **/ +inline v_float32x4 v_cvt_f32(const v_int32x4& a) +{ return v_float32x4(vec_ctf(a.val)); } + +inline v_float32x4 v_cvt_f32(const v_float64x2& a) +{ return v_float32x4(vec_mergesqo(vec_cvfo(a.val), vec_float4_z)); } + +inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b) +{ return v_float32x4(vec_mergesqo(vec_cvfo(a.val), vec_cvfo(b.val))); } + +inline v_float64x2 v_cvt_f64(const v_int32x4& a) +{ return v_float64x2(vec_ctdo(vec_mergeh(a.val, a.val))); } + +inline v_float64x2 v_cvt_f64_high(const v_int32x4& a) +{ return v_float64x2(vec_ctdo(vec_mergel(a.val, a.val))); } + +inline v_float64x2 v_cvt_f64(const v_float32x4& a) +{ return v_float64x2(vec_cvfo(vec_mergeh(a.val, a.val))); } + +inline v_float64x2 v_cvt_f64_high(const v_float32x4& a) +{ return v_float64x2(vec_cvfo(vec_mergel(a.val, a.val))); } + +////////////// Lookup table access //////////////////// + +inline v_int8x16 v_lut(const schar* tab, const int* idx) +{ + return v_int8x16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]], tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]], + tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]); +} +inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx) +{ + return v_reinterpret_as_s8(v_int16x8(*(const short*)(tab+idx[0]), *(const short*)(tab+idx[1]), *(const short*)(tab+idx[2]), *(const short*)(tab+idx[3]), + *(const short*)(tab+idx[4]), *(const short*)(tab+idx[5]), *(const short*)(tab+idx[6]), *(const short*)(tab+idx[7]))); +} +inline v_int8x16 v_lut_quads(const schar* tab, const int* idx) +{ + return v_reinterpret_as_s8(v_int32x4(*(const int*)(tab+idx[0]), *(const int*)(tab+idx[1]), *(const int*)(tab+idx[2]), *(const int*)(tab+idx[3]))); +} +inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((const schar*)tab, idx)); } +inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((const schar*)tab, idx)); } +inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((const schar*)tab, idx)); } + +inline v_int16x8 v_lut(const short* tab, const int* idx) +{ + return v_int16x8(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]], tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]); +} +inline v_int16x8 v_lut_pairs(const short* tab, const int* idx) +{ + return v_reinterpret_as_s16(v_int32x4(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]), *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]))); +} +inline v_int16x8 v_lut_quads(const short* tab, const int* idx) +{ + return v_reinterpret_as_s16(v_int64x2(*(const int64*)(tab + idx[0]), *(const int64*)(tab + idx[1]))); +} +inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((const short*)tab, idx)); } +inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((const short*)tab, idx)); } +inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((const short*)tab, idx)); } + +inline v_int32x4 v_lut(const int* tab, const int* idx) +{ + return v_int32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); +} +inline v_int32x4 v_lut_pairs(const int* tab, const int* idx) +{ + return v_reinterpret_as_s32(v_int64x2(*(const int64*)(tab + idx[0]), *(const int64*)(tab + idx[1]))); +} +inline v_int32x4 v_lut_quads(const int* tab, const int* idx) +{ + return v_int32x4(vsx_ld(0, tab + idx[0])); +} +inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int*)tab, idx)); } +inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int*)tab, idx)); } +inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int*)tab, idx)); } + +inline v_int64x2 v_lut(const int64_t* tab, const int* idx) +{ + return v_int64x2(tab[idx[0]], tab[idx[1]]); +} +inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx) +{ + return v_int64x2(vsx_ld2(0, tab + idx[0])); +} +inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); } +inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); } + +inline v_float32x4 v_lut(const float* tab, const int* idx) +{ + return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); +} +inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_pairs((const int*)tab, idx)); } +inline v_float32x4 v_lut_quads(const float* tab, const int* idx) { return v_load(tab + *idx); } + +inline v_float64x2 v_lut(const double* tab, const int* idx) +{ + return v_float64x2(tab[idx[0]], tab[idx[1]]); +} +inline v_float64x2 v_lut_pairs(const double* tab, const int* idx) { return v_load(tab + *idx); } + +inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec) +{ + const int idx[4] = { + vec_extract(idxvec.val, 0), + vec_extract(idxvec.val, 1), + vec_extract(idxvec.val, 2), + vec_extract(idxvec.val, 3) + }; + return v_int32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); +} + +inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec) +{ + const int idx[4] = { + vec_extract(idxvec.val, 0), + vec_extract(idxvec.val, 1), + vec_extract(idxvec.val, 2), + vec_extract(idxvec.val, 3) + }; + return v_uint32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); +} + +inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec) +{ + const int idx[4] = { + vec_extract(idxvec.val, 0), + vec_extract(idxvec.val, 1), + vec_extract(idxvec.val, 2), + vec_extract(idxvec.val, 3) + }; + return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]); +} + +inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec) +{ + const int idx[2] = { + vec_extract(idxvec.val, 0), + vec_extract(idxvec.val, 1) + }; + return v_float64x2(tab[idx[0]], tab[idx[1]]); +} + +inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y) +{ + vec_float4 xy0 = vec_ld_l8(tab + vec_extract(idxvec.val, 0)); + vec_float4 xy1 = vec_ld_l8(tab + vec_extract(idxvec.val, 1)); + vec_float4 xy2 = vec_ld_l8(tab + vec_extract(idxvec.val, 2)); + vec_float4 xy3 = vec_ld_l8(tab + vec_extract(idxvec.val, 3)); + vec_float4 xy02 = vec_mergeh(xy0, xy2); // x0, x2, y0, y2 + vec_float4 xy13 = vec_mergeh(xy1, xy3); // x1, x3, y1, y3 + x.val = vec_mergeh(xy02, xy13); + y.val = vec_mergel(xy02, xy13); +} +inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y) +{ + vec_double2 xy0 = vsx_ld(vec_extract(idxvec.val, 0), tab); + vec_double2 xy1 = vsx_ld(vec_extract(idxvec.val, 1), tab); + x.val = vec_mergeh(xy0, xy1); + y.val = vec_mergel(xy0, xy1); +} + +inline v_int8x16 v_interleave_pairs(const v_int8x16& vec) +{ + static const vec_uchar16 perm = {0, 2, 1, 3, 4, 6, 5, 7, 8, 10, 9, 11, 12, 14, 13, 15}; + return v_int8x16(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) +{ return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); } + +inline v_int8x16 v_interleave_quads(const v_int8x16& vec) +{ + static const vec_uchar16 perm = {0, 4, 1, 5, 2, 6, 3, 7, 8, 12, 9, 13, 10, 14, 11, 15}; + return v_int8x16(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) +{ return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_interleave_pairs(const v_int16x8& vec) +{ + static const vec_uchar16 perm = {0,1, 4,5, 2,3, 6,7, 8,9, 12,13, 10,11, 14,15}; + return v_int16x8(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) +{ return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); } + +inline v_int16x8 v_interleave_quads(const v_int16x8& vec) +{ + static const vec_uchar16 perm = {0,1, 8,9, 2,3, 10,11, 4,5, 12,13, 6,7, 14,15}; + return v_int16x8(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) +{ return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_interleave_pairs(const v_int32x4& vec) +{ + static const vec_uchar16 perm = {0,1,2,3, 8,9,10,11, 4,5,6,7, 12,13,14,15}; + return v_int32x4(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) +{ return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } +inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) +{ return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); } + +inline v_int8x16 v_pack_triplets(const v_int8x16& vec) +{ + static const vec_uchar16 perm = {0, 1, 2, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 15, 15, 15}; + return v_int8x16(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) +{ return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); } + +inline v_int16x8 v_pack_triplets(const v_int16x8& vec) +{ + static const vec_uchar16 perm = {0,1, 2,3, 4,5, 8,9, 10,11, 12,13, 14,15, 14,15}; + return v_int16x8(vec_perm(vec.val, vec.val, perm)); +} +inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) +{ return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); } + +inline v_int32x4 v_pack_triplets(const v_int32x4& vec) +{ return vec; } +inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) +{ return vec; } +inline v_float32x4 v_pack_triplets(const v_float32x4& vec) +{ return vec; } + +/////// FP16 support //////// + +inline v_float32x4 v_load_expand(const float16_t* ptr) +{ + vec_ushort8 vf16 = vec_ld_l8((const ushort*)ptr); +#if CV_VSX3 && defined(vec_extract_fp_from_shorth) + return v_float32x4(vec_extract_fp_from_shorth(vf16)); +#elif CV_VSX3 && !defined(CV_COMPILER_VSX_BROKEN_ASM) + vec_float4 vf32; + __asm__ __volatile__ ("xvcvhpsp %x0,%x1" : "=wf" (vf32) : "wa" (vec_mergeh(vf16, vf16))); + return v_float32x4(vf32); +#else + const vec_int4 z = vec_int4_z, delta = vec_int4_sp(0x38000000); + const vec_int4 signmask = vec_int4_sp(0x80000000); + const vec_int4 maxexp = vec_int4_sp(0x7c000000); + const vec_float4 deltaf = vec_float4_c(vec_int4_sp(0x38800000)); + + vec_int4 bits = vec_int4_c(vec_mergeh(vec_short8_c(z), vec_short8_c(vf16))); + vec_int4 e = vec_and(bits, maxexp), sign = vec_and(bits, signmask); + vec_int4 t = vec_add(vec_sr(vec_xor(bits, sign), vec_uint4_sp(3)), delta); // ((h & 0x7fff) << 13) + delta + vec_int4 zt = vec_int4_c(vec_sub(vec_float4_c(vec_add(t, vec_int4_sp(1 << 23))), deltaf)); + + t = vec_add(t, vec_and(delta, vec_cmpeq(maxexp, e))); + vec_bint4 zmask = vec_cmpeq(e, z); + vec_int4 ft = vec_sel(t, zt, zmask); + return v_float32x4(vec_float4_c(vec_or(ft, sign))); +#endif +} + +inline void v_pack_store(float16_t* ptr, const v_float32x4& v) +{ +// fixme: Is there any buitin op or intrinsic that cover "xvcvsphp"? +#if CV_VSX3 && !defined(CV_COMPILER_VSX_BROKEN_ASM) + vec_ushort8 vf16; + __asm__ __volatile__ ("xvcvsphp %x0,%x1" : "=wa" (vf16) : "wf" (v.val)); + vec_st_l8(vec_mergesqe(vf16, vf16), ptr); +#else + const vec_int4 signmask = vec_int4_sp(0x80000000); + const vec_int4 rval = vec_int4_sp(0x3f000000); + + vec_int4 t = vec_int4_c(v.val); + vec_int4 sign = vec_sra(vec_and(t, signmask), vec_uint4_sp(16)); + t = vec_and(vec_nor(signmask, signmask), t); + + vec_bint4 finitemask = vec_cmpgt(vec_int4_sp(0x47800000), t); + vec_bint4 isnan = vec_cmpgt(t, vec_int4_sp(0x7f800000)); + vec_int4 naninf = vec_sel(vec_int4_sp(0x7c00), vec_int4_sp(0x7e00), isnan); + vec_bint4 tinymask = vec_cmpgt(vec_int4_sp(0x38800000), t); + vec_int4 tt = vec_int4_c(vec_add(vec_float4_c(t), vec_float4_c(rval))); + tt = vec_sub(tt, rval); + vec_int4 odd = vec_and(vec_sr(t, vec_uint4_sp(13)), vec_int4_sp(1)); + vec_int4 nt = vec_add(t, vec_int4_sp(0xc8000fff)); + nt = vec_sr(vec_add(nt, odd), vec_uint4_sp(13)); + t = vec_sel(nt, tt, tinymask); + t = vec_sel(naninf, t, finitemask); + t = vec_or(t, sign); + vec_st_l8(vec_packs(t, t), ptr); +#endif +} + +inline void v_cleanup() {} + + +/** Reinterpret **/ +/** its up there with load and store operations **/ + +////////// Matrix operations ///////// + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b) +{ return v_int32x4(vec_msum(a.val, b.val, vec_int4_z)); } + +inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c) +{ return v_int32x4(vec_msum(a.val, b.val, c.val)); } + +inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& m3) +{ + const vec_float4 v0 = vec_splat(v.val, 0); + const vec_float4 v1 = vec_splat(v.val, 1); + const vec_float4 v2 = vec_splat(v.val, 2); + VSX_UNUSED(const vec_float4) v3 = vec_splat(v.val, 3); + return v_float32x4(vec_madd(v0, m0.val, vec_madd(v1, m1.val, vec_madd(v2, m2.val, vec_mul(v3, m3.val))))); +} + +inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0, + const v_float32x4& m1, const v_float32x4& m2, + const v_float32x4& a) +{ + const vec_float4 v0 = vec_splat(v.val, 0); + const vec_float4 v1 = vec_splat(v.val, 1); + const vec_float4 v2 = vec_splat(v.val, 2); + return v_float32x4(vec_madd(v0, m0.val, vec_madd(v1, m1.val, vec_madd(v2, m2.val, a.val)))); +} + +#define OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(_Tpvec, _Tpvec2) \ +inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \ + const _Tpvec& a2, const _Tpvec& a3, \ + _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3) \ +{ \ + _Tpvec2 a02 = vec_mergeh(a0.val, a2.val); \ + _Tpvec2 a13 = vec_mergeh(a1.val, a3.val); \ + b0.val = vec_mergeh(a02, a13); \ + b1.val = vec_mergel(a02, a13); \ + a02 = vec_mergel(a0.val, a2.val); \ + a13 = vec_mergel(a1.val, a3.val); \ + b2.val = vec_mergeh(a02, a13); \ + b3.val = vec_mergel(a02, a13); \ +} +OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_uint32x4, vec_uint4) +OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_int32x4, vec_int4) +OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_float32x4, vec_float4) + +//! @name Check SIMD support +//! @{ +//! @brief Check CPU capability of SIMD operation +static inline bool hasSIMD128() +{ + return (CV_CPU_HAS_SUPPORT_VSX) ? true : false; +} + +//! @} + +CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END + +//! @endcond + +} + +#endif // OPENCV_HAL_VSX_HPP diff --git a/3rdparty/opencv/include/opencv2/core/ippasync.hpp b/3rdparty/opencv/include/opencv2/core/ippasync.hpp new file mode 100644 index 00000000..c35d8d81 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/ippasync.hpp @@ -0,0 +1,195 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2015, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_IPPASYNC_HPP +#define OPENCV_CORE_IPPASYNC_HPP + +#ifdef HAVE_IPP_A // this file will be removed in OpenCV 4.0 + +#include "opencv2/core.hpp" +#include +#include + +namespace cv +{ + +namespace hpp +{ + +/** @addtogroup core_ipp +This section describes conversion between OpenCV and [Intel® IPP Asynchronous +C/C++](http://software.intel.com/en-us/intel-ipp-preview) library. [Getting Started +Guide](http://registrationcenter.intel.com/irc_nas/3727/ipp_async_get_started.htm) help you to +install the library, configure header and library build paths. + */ +//! @{ + + //! convert OpenCV data type to hppDataType + inline int toHppType(const int cvType) + { + int depth = CV_MAT_DEPTH(cvType); + int hppType = depth == CV_8U ? HPP_DATA_TYPE_8U : + depth == CV_16U ? HPP_DATA_TYPE_16U : + depth == CV_16S ? HPP_DATA_TYPE_16S : + depth == CV_32S ? HPP_DATA_TYPE_32S : + depth == CV_32F ? HPP_DATA_TYPE_32F : + depth == CV_64F ? HPP_DATA_TYPE_64F : -1; + CV_Assert( hppType >= 0 ); + return hppType; + } + + //! convert hppDataType to OpenCV data type + inline int toCvType(const int hppType) + { + int cvType = hppType == HPP_DATA_TYPE_8U ? CV_8U : + hppType == HPP_DATA_TYPE_16U ? CV_16U : + hppType == HPP_DATA_TYPE_16S ? CV_16S : + hppType == HPP_DATA_TYPE_32S ? CV_32S : + hppType == HPP_DATA_TYPE_32F ? CV_32F : + hppType == HPP_DATA_TYPE_64F ? CV_64F : -1; + CV_Assert( cvType >= 0 ); + return cvType; + } + + /** @brief Convert hppiMatrix to Mat. + + This function allocates and initializes new matrix (if needed) that has the same size and type as + input matrix. Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F. + @param src input hppiMatrix. + @param dst output matrix. + @param accel accelerator instance (see hpp::getHpp for the list of acceleration framework types). + @param cn number of channels. + */ + inline void copyHppToMat(hppiMatrix* src, Mat& dst, hppAccel accel, int cn) + { + hppDataType type; + hpp32u width, height; + hppStatus sts; + + if (src == NULL) + return dst.release(); + + sts = hppiInquireMatrix(src, &type, &width, &height); + + CV_Assert( sts == HPP_STATUS_NO_ERROR); + + int matType = CV_MAKETYPE(toCvType(type), cn); + + CV_Assert(width%cn == 0); + + width /= cn; + + dst.create((int)height, (int)width, (int)matType); + + size_t newSize = (size_t)(height*(hpp32u)(dst.step)); + + sts = hppiGetMatrixData(accel,src,(hpp32u)(dst.step),dst.data,&newSize); + + CV_Assert( sts == HPP_STATUS_NO_ERROR); + } + + /** @brief Create Mat from hppiMatrix. + + This function allocates and initializes the Mat that has the same size and type as input matrix. + Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F. + @param src input hppiMatrix. + @param accel accelerator instance (see hpp::getHpp for the list of acceleration framework types). + @param cn number of channels. + @sa howToUseIPPAconversion, hpp::copyHppToMat, hpp::getHpp. + */ + inline Mat getMat(hppiMatrix* src, hppAccel accel, int cn) + { + Mat dst; + copyHppToMat(src, dst, accel, cn); + return dst; + } + + /** @brief Create hppiMatrix from Mat. + + This function allocates and initializes the hppiMatrix that has the same size and type as input + matrix, returns the hppiMatrix*. + + If you want to use zero-copy for GPU you should to have 4KB aligned matrix data. See details + [hppiCreateSharedMatrix](http://software.intel.com/ru-ru/node/501697). + + Supports CV_8U, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F. + + @note The hppiMatrix pointer to the image buffer in system memory refers to the src.data. Control + the lifetime of the matrix and don't change its data, if there is no special need. + @param src input matrix. + @param accel accelerator instance. Supports type: + - **HPP_ACCEL_TYPE_CPU** - accelerated by optimized CPU instructions. + - **HPP_ACCEL_TYPE_GPU** - accelerated by GPU programmable units or fixed-function + accelerators. + - **HPP_ACCEL_TYPE_ANY** - any acceleration or no acceleration available. + @sa howToUseIPPAconversion, hpp::getMat + */ + inline hppiMatrix* getHpp(const Mat& src, hppAccel accel) + { + int htype = toHppType(src.type()); + int cn = src.channels(); + + CV_Assert(src.data); + hppAccelType accelType = hppQueryAccelType(accel); + + if (accelType!=HPP_ACCEL_TYPE_CPU) + { + hpp32u pitch, size; + hppQueryMatrixAllocParams(accel, src.cols*cn, src.rows, htype, &pitch, &size); + if (pitch!=0 && size!=0) + if ((int)(src.data)%4096==0 && pitch==(hpp32u)(src.step)) + { + return hppiCreateSharedMatrix(htype, src.cols*cn, src.rows, src.data, pitch, size); + } + } + + return hppiCreateMatrix(htype, src.cols*cn, src.rows, src.data, (hpp32s)(src.step));; + } + +//! @} +}} + +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/mat.hpp b/3rdparty/opencv/include/opencv2/core/mat.hpp new file mode 100644 index 00000000..2c23a2ab --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/mat.hpp @@ -0,0 +1,3761 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_MAT_HPP +#define OPENCV_CORE_MAT_HPP + +#ifndef __cplusplus +# error mat.hpp header must be compiled as C++ +#endif + +#include "opencv2/core/matx.hpp" +#include "opencv2/core/types.hpp" + +#include "opencv2/core/bufferpool.hpp" + +#ifdef CV_CXX11 +#include +#endif + +namespace cv +{ + +//! @addtogroup core_basic +//! @{ + +enum { ACCESS_READ=1<<24, ACCESS_WRITE=1<<25, + ACCESS_RW=3<<24, ACCESS_MASK=ACCESS_RW, ACCESS_FAST=1<<26 }; + +CV__DEBUG_NS_BEGIN + +class CV_EXPORTS _OutputArray; + +//////////////////////// Input/Output Array Arguments ///////////////////////////////// + +/** @brief This is the proxy class for passing read-only input arrays into OpenCV functions. + +It is defined as: +@code + typedef const _InputArray& InputArray; +@endcode +where _InputArray is a class that can be constructed from `Mat`, `Mat_`, `Matx`, +`std::vector`, `std::vector >`, `std::vector`, `std::vector >`, +`UMat`, `std::vector` or `double`. It can also be constructed from a matrix expression. + +Since this is mostly implementation-level class, and its interface may change in future versions, we +do not describe it in details. There are a few key things, though, that should be kept in mind: + +- When you see in the reference manual or in OpenCV source code a function that takes + InputArray, it means that you can actually pass `Mat`, `Matx`, `vector` etc. (see above the + complete list). +- Optional input arguments: If some of the input arrays may be empty, pass cv::noArray() (or + simply cv::Mat() as you probably did before). +- The class is designed solely for passing parameters. That is, normally you *should not* + declare class members, local and global variables of this type. +- If you want to design your own function or a class method that can operate of arrays of + multiple types, you can use InputArray (or OutputArray) for the respective parameters. Inside + a function you should use _InputArray::getMat() method to construct a matrix header for the + array (without copying data). _InputArray::kind() can be used to distinguish Mat from + `vector<>` etc., but normally it is not needed. + +Here is how you can use a function that takes InputArray : +@code + std::vector vec; + // points or a circle + for( int i = 0; i < 30; i++ ) + vec.push_back(Point2f((float)(100 + 30*cos(i*CV_PI*2/5)), + (float)(100 - 30*sin(i*CV_PI*2/5)))); + cv::transform(vec, vec, cv::Matx23f(0.707, -0.707, 10, 0.707, 0.707, 20)); +@endcode +That is, we form an STL vector containing points, and apply in-place affine transformation to the +vector using the 2x3 matrix created inline as `Matx` instance. + +Here is how such a function can be implemented (for simplicity, we implement a very specific case of +it, according to the assertion statement inside) : +@code + void myAffineTransform(InputArray _src, OutputArray _dst, InputArray _m) + { + // get Mat headers for input arrays. This is O(1) operation, + // unless _src and/or _m are matrix expressions. + Mat src = _src.getMat(), m = _m.getMat(); + CV_Assert( src.type() == CV_32FC2 && m.type() == CV_32F && m.size() == Size(3, 2) ); + + // [re]create the output array so that it has the proper size and type. + // In case of Mat it calls Mat::create, in case of STL vector it calls vector::resize. + _dst.create(src.size(), src.type()); + Mat dst = _dst.getMat(); + + for( int i = 0; i < src.rows; i++ ) + for( int j = 0; j < src.cols; j++ ) + { + Point2f pt = src.at(i, j); + dst.at(i, j) = Point2f(m.at(0, 0)*pt.x + + m.at(0, 1)*pt.y + + m.at(0, 2), + m.at(1, 0)*pt.x + + m.at(1, 1)*pt.y + + m.at(1, 2)); + } + } +@endcode +There is another related type, InputArrayOfArrays, which is currently defined as a synonym for +InputArray: +@code + typedef InputArray InputArrayOfArrays; +@endcode +It denotes function arguments that are either vectors of vectors or vectors of matrices. A separate +synonym is needed to generate Python/Java etc. wrappers properly. At the function implementation +level their use is similar, but _InputArray::getMat(idx) should be used to get header for the +idx-th component of the outer vector and _InputArray::size().area() should be used to find the +number of components (vectors/matrices) of the outer vector. + +In general, type support is limited to cv::Mat types. Other types are forbidden. +But in some cases we need to support passing of custom non-general Mat types, like arrays of cv::KeyPoint, cv::DMatch, etc. +This data is not intented to be interpreted as an image data, or processed somehow like regular cv::Mat. +To pass such custom type use rawIn() / rawOut() / rawInOut() wrappers. +Custom type is wrapped as Mat-compatible `CV_8UC` values (N = sizeof(T), N <= CV_CN_MAX). + */ +class CV_EXPORTS _InputArray +{ +public: + enum { + KIND_SHIFT = 16, + FIXED_TYPE = 0x8000 << KIND_SHIFT, + FIXED_SIZE = 0x4000 << KIND_SHIFT, + KIND_MASK = 31 << KIND_SHIFT, + + NONE = 0 << KIND_SHIFT, + MAT = 1 << KIND_SHIFT, + MATX = 2 << KIND_SHIFT, + STD_VECTOR = 3 << KIND_SHIFT, + STD_VECTOR_VECTOR = 4 << KIND_SHIFT, + STD_VECTOR_MAT = 5 << KIND_SHIFT, + EXPR = 6 << KIND_SHIFT, + OPENGL_BUFFER = 7 << KIND_SHIFT, + CUDA_HOST_MEM = 8 << KIND_SHIFT, + CUDA_GPU_MAT = 9 << KIND_SHIFT, + UMAT =10 << KIND_SHIFT, + STD_VECTOR_UMAT =11 << KIND_SHIFT, + STD_BOOL_VECTOR =12 << KIND_SHIFT, + STD_VECTOR_CUDA_GPU_MAT = 13 << KIND_SHIFT, + STD_ARRAY =14 << KIND_SHIFT, + STD_ARRAY_MAT =15 << KIND_SHIFT + }; + + _InputArray(); + _InputArray(int _flags, void* _obj); + _InputArray(const Mat& m); + _InputArray(const MatExpr& expr); + _InputArray(const std::vector& vec); + template _InputArray(const Mat_<_Tp>& m); + template _InputArray(const std::vector<_Tp>& vec); + _InputArray(const std::vector& vec); + template _InputArray(const std::vector >& vec); + _InputArray(const std::vector >&); + template _InputArray(const std::vector >& vec); + template _InputArray(const _Tp* vec, int n); + template _InputArray(const Matx<_Tp, m, n>& matx); + _InputArray(const double& val); + _InputArray(const cuda::GpuMat& d_mat); + _InputArray(const std::vector& d_mat_array); + _InputArray(const ogl::Buffer& buf); + _InputArray(const cuda::HostMem& cuda_mem); + template _InputArray(const cudev::GpuMat_<_Tp>& m); + _InputArray(const UMat& um); + _InputArray(const std::vector& umv); + +#ifdef CV_CXX_STD_ARRAY + template _InputArray(const std::array<_Tp, _Nm>& arr); + template _InputArray(const std::array& arr); +#endif + + template static _InputArray rawIn(const std::vector<_Tp>& vec); +#ifdef CV_CXX_STD_ARRAY + template static _InputArray rawIn(const std::array<_Tp, _Nm>& arr); +#endif + + Mat getMat(int idx=-1) const; + Mat getMat_(int idx=-1) const; + UMat getUMat(int idx=-1) const; + void getMatVector(std::vector& mv) const; + void getUMatVector(std::vector& umv) const; + void getGpuMatVector(std::vector& gpumv) const; + cuda::GpuMat getGpuMat() const; + ogl::Buffer getOGlBuffer() const; + + int getFlags() const; + void* getObj() const; + Size getSz() const; + + int kind() const; + int dims(int i=-1) const; + int cols(int i=-1) const; + int rows(int i=-1) const; + Size size(int i=-1) const; + int sizend(int* sz, int i=-1) const; + bool sameSize(const _InputArray& arr) const; + size_t total(int i=-1) const; + int type(int i=-1) const; + int depth(int i=-1) const; + int channels(int i=-1) const; + bool isContinuous(int i=-1) const; + bool isSubmatrix(int i=-1) const; + bool empty() const; + void copyTo(const _OutputArray& arr) const; + void copyTo(const _OutputArray& arr, const _InputArray & mask) const; + size_t offset(int i=-1) const; + size_t step(int i=-1) const; + bool isMat() const; + bool isUMat() const; + bool isMatVector() const; + bool isUMatVector() const; + bool isMatx() const; + bool isVector() const; + bool isGpuMat() const; + bool isGpuMatVector() const; + ~_InputArray(); + +protected: + int flags; + void* obj; + Size sz; + + void init(int _flags, const void* _obj); + void init(int _flags, const void* _obj, Size _sz); +}; + + +/** @brief This type is very similar to InputArray except that it is used for input/output and output function +parameters. + +Just like with InputArray, OpenCV users should not care about OutputArray, they just pass `Mat`, +`vector` etc. to the functions. The same limitation as for `InputArray`: *Do not explicitly +create OutputArray instances* applies here too. + +If you want to make your function polymorphic (i.e. accept different arrays as output parameters), +it is also not very difficult. Take the sample above as the reference. Note that +_OutputArray::create() needs to be called before _OutputArray::getMat(). This way you guarantee +that the output array is properly allocated. + +Optional output parameters. If you do not need certain output array to be computed and returned to +you, pass cv::noArray(), just like you would in the case of optional input array. At the +implementation level, use _OutputArray::needed() to check if certain output array needs to be +computed or not. + +There are several synonyms for OutputArray that are used to assist automatic Python/Java/... wrapper +generators: +@code + typedef OutputArray OutputArrayOfArrays; + typedef OutputArray InputOutputArray; + typedef OutputArray InputOutputArrayOfArrays; +@endcode + */ +class CV_EXPORTS _OutputArray : public _InputArray +{ +public: + enum + { + DEPTH_MASK_8U = 1 << CV_8U, + DEPTH_MASK_8S = 1 << CV_8S, + DEPTH_MASK_16U = 1 << CV_16U, + DEPTH_MASK_16S = 1 << CV_16S, + DEPTH_MASK_32S = 1 << CV_32S, + DEPTH_MASK_32F = 1 << CV_32F, + DEPTH_MASK_64F = 1 << CV_64F, + DEPTH_MASK_ALL = (DEPTH_MASK_64F<<1)-1, + DEPTH_MASK_ALL_BUT_8S = DEPTH_MASK_ALL & ~DEPTH_MASK_8S, + DEPTH_MASK_FLT = DEPTH_MASK_32F + DEPTH_MASK_64F + }; + + _OutputArray(); + _OutputArray(int _flags, void* _obj); + _OutputArray(Mat& m); + _OutputArray(std::vector& vec); + _OutputArray(cuda::GpuMat& d_mat); + _OutputArray(std::vector& d_mat); + _OutputArray(ogl::Buffer& buf); + _OutputArray(cuda::HostMem& cuda_mem); + template _OutputArray(cudev::GpuMat_<_Tp>& m); + template _OutputArray(std::vector<_Tp>& vec); + _OutputArray(std::vector& vec); + template _OutputArray(std::vector >& vec); + _OutputArray(std::vector >&); + template _OutputArray(std::vector >& vec); + template _OutputArray(Mat_<_Tp>& m); + template _OutputArray(_Tp* vec, int n); + template _OutputArray(Matx<_Tp, m, n>& matx); + _OutputArray(UMat& m); + _OutputArray(std::vector& vec); + + _OutputArray(const Mat& m); + _OutputArray(const std::vector& vec); + _OutputArray(const cuda::GpuMat& d_mat); + _OutputArray(const std::vector& d_mat); + _OutputArray(const ogl::Buffer& buf); + _OutputArray(const cuda::HostMem& cuda_mem); + template _OutputArray(const cudev::GpuMat_<_Tp>& m); + template _OutputArray(const std::vector<_Tp>& vec); + template _OutputArray(const std::vector >& vec); + template _OutputArray(const std::vector >& vec); + template _OutputArray(const Mat_<_Tp>& m); + template _OutputArray(const _Tp* vec, int n); + template _OutputArray(const Matx<_Tp, m, n>& matx); + _OutputArray(const UMat& m); + _OutputArray(const std::vector& vec); + +#ifdef CV_CXX_STD_ARRAY + template _OutputArray(std::array<_Tp, _Nm>& arr); + template _OutputArray(const std::array<_Tp, _Nm>& arr); + template _OutputArray(std::array& arr); + template _OutputArray(const std::array& arr); +#endif + + template static _OutputArray rawOut(std::vector<_Tp>& vec); +#ifdef CV_CXX_STD_ARRAY + template static _OutputArray rawOut(std::array<_Tp, _Nm>& arr); +#endif + + bool fixedSize() const; + bool fixedType() const; + bool needed() const; + Mat& getMatRef(int i=-1) const; + UMat& getUMatRef(int i=-1) const; + cuda::GpuMat& getGpuMatRef() const; + std::vector& getGpuMatVecRef() const; + ogl::Buffer& getOGlBufferRef() const; + cuda::HostMem& getHostMemRef() const; + void create(Size sz, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const; + void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const; + void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, int fixedDepthMask=0) const; + void createSameSize(const _InputArray& arr, int mtype) const; + void release() const; + void clear() const; + void setTo(const _InputArray& value, const _InputArray & mask = _InputArray()) const; + + void assign(const UMat& u) const; + void assign(const Mat& m) const; + + void assign(const std::vector& v) const; + void assign(const std::vector& v) const; +}; + + +class CV_EXPORTS _InputOutputArray : public _OutputArray +{ +public: + _InputOutputArray(); + _InputOutputArray(int _flags, void* _obj); + _InputOutputArray(Mat& m); + _InputOutputArray(std::vector& vec); + _InputOutputArray(cuda::GpuMat& d_mat); + _InputOutputArray(ogl::Buffer& buf); + _InputOutputArray(cuda::HostMem& cuda_mem); + template _InputOutputArray(cudev::GpuMat_<_Tp>& m); + template _InputOutputArray(std::vector<_Tp>& vec); + _InputOutputArray(std::vector& vec); + template _InputOutputArray(std::vector >& vec); + template _InputOutputArray(std::vector >& vec); + template _InputOutputArray(Mat_<_Tp>& m); + template _InputOutputArray(_Tp* vec, int n); + template _InputOutputArray(Matx<_Tp, m, n>& matx); + _InputOutputArray(UMat& m); + _InputOutputArray(std::vector& vec); + + _InputOutputArray(const Mat& m); + _InputOutputArray(const std::vector& vec); + _InputOutputArray(const cuda::GpuMat& d_mat); + _InputOutputArray(const std::vector& d_mat); + _InputOutputArray(const ogl::Buffer& buf); + _InputOutputArray(const cuda::HostMem& cuda_mem); + template _InputOutputArray(const cudev::GpuMat_<_Tp>& m); + template _InputOutputArray(const std::vector<_Tp>& vec); + template _InputOutputArray(const std::vector >& vec); + template _InputOutputArray(const std::vector >& vec); + template _InputOutputArray(const Mat_<_Tp>& m); + template _InputOutputArray(const _Tp* vec, int n); + template _InputOutputArray(const Matx<_Tp, m, n>& matx); + _InputOutputArray(const UMat& m); + _InputOutputArray(const std::vector& vec); + +#ifdef CV_CXX_STD_ARRAY + template _InputOutputArray(std::array<_Tp, _Nm>& arr); + template _InputOutputArray(const std::array<_Tp, _Nm>& arr); + template _InputOutputArray(std::array& arr); + template _InputOutputArray(const std::array& arr); +#endif + + template static _InputOutputArray rawInOut(std::vector<_Tp>& vec); +#ifdef CV_CXX_STD_ARRAY + template _InputOutputArray rawInOut(std::array<_Tp, _Nm>& arr); +#endif + +}; + +/** Helper to wrap custom types. @see InputArray */ +template static inline _InputArray rawIn(_Tp& v); +/** Helper to wrap custom types. @see InputArray */ +template static inline _OutputArray rawOut(_Tp& v); +/** Helper to wrap custom types. @see InputArray */ +template static inline _InputOutputArray rawInOut(_Tp& v); + +CV__DEBUG_NS_END + +typedef const _InputArray& InputArray; +typedef InputArray InputArrayOfArrays; +typedef const _OutputArray& OutputArray; +typedef OutputArray OutputArrayOfArrays; +typedef const _InputOutputArray& InputOutputArray; +typedef InputOutputArray InputOutputArrayOfArrays; + +CV_EXPORTS InputOutputArray noArray(); + +/////////////////////////////////// MatAllocator ////////////////////////////////////// + +//! Usage flags for allocator +enum UMatUsageFlags +{ + USAGE_DEFAULT = 0, + + // buffer allocation policy is platform and usage specific + USAGE_ALLOCATE_HOST_MEMORY = 1 << 0, + USAGE_ALLOCATE_DEVICE_MEMORY = 1 << 1, + USAGE_ALLOCATE_SHARED_MEMORY = 1 << 2, // It is not equal to: USAGE_ALLOCATE_HOST_MEMORY | USAGE_ALLOCATE_DEVICE_MEMORY + + __UMAT_USAGE_FLAGS_32BIT = 0x7fffffff // Binary compatibility hint +}; + +struct CV_EXPORTS UMatData; + +/** @brief Custom array allocator +*/ +class CV_EXPORTS MatAllocator +{ +public: + MatAllocator() {} + virtual ~MatAllocator() {} + + // let's comment it off for now to detect and fix all the uses of allocator + //virtual void allocate(int dims, const int* sizes, int type, int*& refcount, + // uchar*& datastart, uchar*& data, size_t* step) = 0; + //virtual void deallocate(int* refcount, uchar* datastart, uchar* data) = 0; + virtual UMatData* allocate(int dims, const int* sizes, int type, + void* data, size_t* step, int flags, UMatUsageFlags usageFlags) const = 0; + virtual bool allocate(UMatData* data, int accessflags, UMatUsageFlags usageFlags) const = 0; + virtual void deallocate(UMatData* data) const = 0; + virtual void map(UMatData* data, int accessflags) const; + virtual void unmap(UMatData* data) const; + virtual void download(UMatData* data, void* dst, int dims, const size_t sz[], + const size_t srcofs[], const size_t srcstep[], + const size_t dststep[]) const; + virtual void upload(UMatData* data, const void* src, int dims, const size_t sz[], + const size_t dstofs[], const size_t dststep[], + const size_t srcstep[]) const; + virtual void copy(UMatData* srcdata, UMatData* dstdata, int dims, const size_t sz[], + const size_t srcofs[], const size_t srcstep[], + const size_t dstofs[], const size_t dststep[], bool sync) const; + + // default implementation returns DummyBufferPoolController + virtual BufferPoolController* getBufferPoolController(const char* id = NULL) const; +}; + + +//////////////////////////////// MatCommaInitializer ////////////////////////////////// + +/** @brief Comma-separated Matrix Initializer + + The class instances are usually not created explicitly. + Instead, they are created on "matrix << firstValue" operator. + + The sample below initializes 2x2 rotation matrix: + + \code + double angle = 30, a = cos(angle*CV_PI/180), b = sin(angle*CV_PI/180); + Mat R = (Mat_(2,2) << a, -b, b, a); + \endcode +*/ +template class MatCommaInitializer_ +{ +public: + //! the constructor, created by "matrix << firstValue" operator, where matrix is cv::Mat + MatCommaInitializer_(Mat_<_Tp>* _m); + //! the operator that takes the next value and put it to the matrix + template MatCommaInitializer_<_Tp>& operator , (T2 v); + //! another form of conversion operator + operator Mat_<_Tp>() const; +protected: + MatIterator_<_Tp> it; +}; + + +/////////////////////////////////////// Mat /////////////////////////////////////////// + +// note that umatdata might be allocated together +// with the matrix data, not as a separate object. +// therefore, it does not have constructor or destructor; +// it should be explicitly initialized using init(). +struct CV_EXPORTS UMatData +{ + enum { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2, + DEVICE_COPY_OBSOLETE=4, TEMP_UMAT=8, TEMP_COPIED_UMAT=24, + USER_ALLOCATED=32, DEVICE_MEM_MAPPED=64, + ASYNC_CLEANUP=128 + }; + UMatData(const MatAllocator* allocator); + ~UMatData(); + + // provide atomic access to the structure + void lock(); + void unlock(); + + bool hostCopyObsolete() const; + bool deviceCopyObsolete() const; + bool deviceMemMapped() const; + bool copyOnMap() const; + bool tempUMat() const; + bool tempCopiedUMat() const; + void markHostCopyObsolete(bool flag); + void markDeviceCopyObsolete(bool flag); + void markDeviceMemMapped(bool flag); + + const MatAllocator* prevAllocator; + const MatAllocator* currAllocator; + int urefcount; + int refcount; + uchar* data; + uchar* origdata; + size_t size; + + int flags; + void* handle; + void* userdata; + int allocatorFlags_; + int mapcount; + UMatData* originalUMatData; +}; + + +struct CV_EXPORTS MatSize +{ + explicit MatSize(int* _p); + int dims() const; + Size operator()() const; + const int& operator[](int i) const; + int& operator[](int i); + operator const int*() const; // TODO OpenCV 4.0: drop this + bool operator == (const MatSize& sz) const; + bool operator != (const MatSize& sz) const; + + int* p; +}; + +struct CV_EXPORTS MatStep +{ + MatStep(); + explicit MatStep(size_t s); + const size_t& operator[](int i) const; + size_t& operator[](int i); + operator size_t() const; + MatStep& operator = (size_t s); + + size_t* p; + size_t buf[2]; +protected: + MatStep& operator = (const MatStep&); +}; + +/** @example samples/cpp/cout_mat.cpp +An example demonstrating the serial out capabilities of cv::Mat +*/ + + /** @brief n-dimensional dense array class \anchor CVMat_Details + +The class Mat represents an n-dimensional dense numerical single-channel or multi-channel array. It +can be used to store real or complex-valued vectors and matrices, grayscale or color images, voxel +volumes, vector fields, point clouds, tensors, histograms (though, very high-dimensional histograms +may be better stored in a SparseMat ). The data layout of the array `M` is defined by the array +`M.step[]`, so that the address of element \f$(i_0,...,i_{M.dims-1})\f$, where \f$0\leq i_k= M.step[i+1]` (in fact, `M.step[i] >= M.step[i+1]*M.size[i+1]` ). This means +that 2-dimensional matrices are stored row-by-row, 3-dimensional matrices are stored plane-by-plane, +and so on. M.step[M.dims-1] is minimal and always equal to the element size M.elemSize() . + +So, the data layout in Mat is fully compatible with CvMat, IplImage, and CvMatND types from OpenCV +1.x. It is also compatible with the majority of dense array types from the standard toolkits and +SDKs, such as Numpy (ndarray), Win32 (independent device bitmaps), and others, that is, with any +array that uses *steps* (or *strides*) to compute the position of a pixel. Due to this +compatibility, it is possible to make a Mat header for user-allocated data and process it in-place +using OpenCV functions. + +There are many different ways to create a Mat object. The most popular options are listed below: + +- Use the create(nrows, ncols, type) method or the similar Mat(nrows, ncols, type[, fillValue]) +constructor. A new array of the specified size and type is allocated. type has the same meaning as +in the cvCreateMat method. For example, CV_8UC1 means a 8-bit single-channel array, CV_32FC2 +means a 2-channel (complex) floating-point array, and so on. +@code + // make a 7x7 complex matrix filled with 1+3j. + Mat M(7,7,CV_32FC2,Scalar(1,3)); + // and now turn M to a 100x60 15-channel 8-bit matrix. + // The old content will be deallocated + M.create(100,60,CV_8UC(15)); +@endcode +As noted in the introduction to this chapter, create() allocates only a new array when the shape +or type of the current array are different from the specified ones. + +- Create a multi-dimensional array: +@code + // create a 100x100x100 8-bit array + int sz[] = {100, 100, 100}; + Mat bigCube(3, sz, CV_8U, Scalar::all(0)); +@endcode +It passes the number of dimensions =1 to the Mat constructor but the created array will be +2-dimensional with the number of columns set to 1. So, Mat::dims is always \>= 2 (can also be 0 +when the array is empty). + +- Use a copy constructor or assignment operator where there can be an array or expression on the +right side (see below). As noted in the introduction, the array assignment is an O(1) operation +because it only copies the header and increases the reference counter. The Mat::clone() method can +be used to get a full (deep) copy of the array when you need it. + +- Construct a header for a part of another array. It can be a single row, single column, several +rows, several columns, rectangular region in the array (called a *minor* in algebra) or a +diagonal. Such operations are also O(1) because the new header references the same data. You can +actually modify a part of the array using this feature, for example: +@code + // add the 5-th row, multiplied by 3 to the 3rd row + M.row(3) = M.row(3) + M.row(5)*3; + // now copy the 7-th column to the 1-st column + // M.col(1) = M.col(7); // this will not work + Mat M1 = M.col(1); + M.col(7).copyTo(M1); + // create a new 320x240 image + Mat img(Size(320,240),CV_8UC3); + // select a ROI + Mat roi(img, Rect(10,10,100,100)); + // fill the ROI with (0,255,0) (which is green in RGB space); + // the original 320x240 image will be modified + roi = Scalar(0,255,0); +@endcode +Due to the additional datastart and dataend members, it is possible to compute a relative +sub-array position in the main *container* array using locateROI(): +@code + Mat A = Mat::eye(10, 10, CV_32S); + // extracts A columns, 1 (inclusive) to 3 (exclusive). + Mat B = A(Range::all(), Range(1, 3)); + // extracts B rows, 5 (inclusive) to 9 (exclusive). + // that is, C \~ A(Range(5, 9), Range(1, 3)) + Mat C = B(Range(5, 9), Range::all()); + Size size; Point ofs; + C.locateROI(size, ofs); + // size will be (width=10,height=10) and the ofs will be (x=1, y=5) +@endcode +As in case of whole matrices, if you need a deep copy, use the `clone()` method of the extracted +sub-matrices. + +- Make a header for user-allocated data. It can be useful to do the following: + -# Process "foreign" data using OpenCV (for example, when you implement a DirectShow\* filter or + a processing module for gstreamer, and so on). For example: + @code + void process_video_frame(const unsigned char* pixels, + int width, int height, int step) + { + Mat img(height, width, CV_8UC3, pixels, step); + GaussianBlur(img, img, Size(7,7), 1.5, 1.5); + } + @endcode + -# Quickly initialize small matrices and/or get a super-fast element access. + @code + double m[3][3] = {{a, b, c}, {d, e, f}, {g, h, i}}; + Mat M = Mat(3, 3, CV_64F, m).inv(); + @endcode + . + Partial yet very common cases of this *user-allocated data* case are conversions from CvMat and + IplImage to Mat. For this purpose, there is function cv::cvarrToMat taking pointers to CvMat or + IplImage and the optional flag indicating whether to copy the data or not. + @snippet samples/cpp/image.cpp iplimage + +- Use MATLAB-style array initializers, zeros(), ones(), eye(), for example: +@code + // create a double-precision identity matrix and add it to M. + M += Mat::eye(M.rows, M.cols, CV_64F); +@endcode + +- Use a comma-separated initializer: +@code + // create a 3x3 double-precision identity matrix + Mat M = (Mat_(3,3) << 1, 0, 0, 0, 1, 0, 0, 0, 1); +@endcode +With this approach, you first call a constructor of the Mat class with the proper parameters, and +then you just put `<< operator` followed by comma-separated values that can be constants, +variables, expressions, and so on. Also, note the extra parentheses required to avoid compilation +errors. + +Once the array is created, it is automatically managed via a reference-counting mechanism. If the +array header is built on top of user-allocated data, you should handle the data by yourself. The +array data is deallocated when no one points to it. If you want to release the data pointed by a +array header before the array destructor is called, use Mat::release(). + +The next important thing to learn about the array class is element access. This manual already +described how to compute an address of each array element. Normally, you are not required to use the +formula directly in the code. If you know the array element type (which can be retrieved using the +method Mat::type() ), you can access the element \f$M_{ij}\f$ of a 2-dimensional array as: +@code + M.at(i,j) += 1.f; +@endcode +assuming that `M` is a double-precision floating-point array. There are several variants of the method +at for a different number of dimensions. + +If you need to process a whole row of a 2D array, the most efficient way is to get the pointer to +the row first, and then just use the plain C operator [] : +@code + // compute sum of positive matrix elements + // (assuming that M is a double-precision matrix) + double sum=0; + for(int i = 0; i < M.rows; i++) + { + const double* Mi = M.ptr(i); + for(int j = 0; j < M.cols; j++) + sum += std::max(Mi[j], 0.); + } +@endcode +Some operations, like the one above, do not actually depend on the array shape. They just process +elements of an array one by one (or elements from multiple arrays that have the same coordinates, +for example, array addition). Such operations are called *element-wise*. It makes sense to check +whether all the input/output arrays are continuous, namely, have no gaps at the end of each row. If +yes, process them as a long single row: +@code + // compute the sum of positive matrix elements, optimized variant + double sum=0; + int cols = M.cols, rows = M.rows; + if(M.isContinuous()) + { + cols *= rows; + rows = 1; + } + for(int i = 0; i < rows; i++) + { + const double* Mi = M.ptr(i); + for(int j = 0; j < cols; j++) + sum += std::max(Mi[j], 0.); + } +@endcode +In case of the continuous matrix, the outer loop body is executed just once. So, the overhead is +smaller, which is especially noticeable in case of small matrices. + +Finally, there are STL-style iterators that are smart enough to skip gaps between successive rows: +@code + // compute sum of positive matrix elements, iterator-based variant + double sum=0; + MatConstIterator_ it = M.begin(), it_end = M.end(); + for(; it != it_end; ++it) + sum += std::max(*it, 0.); +@endcode +The matrix iterators are random-access iterators, so they can be passed to any STL algorithm, +including std::sort(). + +@note Matrix Expressions and arithmetic see MatExpr +*/ +class CV_EXPORTS Mat +{ +public: + /** + These are various constructors that form a matrix. As noted in the AutomaticAllocation, often + the default constructor is enough, and the proper matrix will be allocated by an OpenCV function. + The constructed matrix can further be assigned to another matrix or matrix expression or can be + allocated with Mat::create . In the former case, the old content is de-referenced. + */ + Mat(); + + /** @overload + @param rows Number of rows in a 2D array. + @param cols Number of columns in a 2D array. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + */ + Mat(int rows, int cols, int type); + + /** @overload + @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the + number of columns go in the reverse order. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + */ + Mat(Size size, int type); + + /** @overload + @param rows Number of rows in a 2D array. + @param cols Number of columns in a 2D array. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param s An optional value to initialize each matrix element with. To set all the matrix elements to + the particular value after the construction, use the assignment operator + Mat::operator=(const Scalar& value) . + */ + Mat(int rows, int cols, int type, const Scalar& s); + + /** @overload + @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the + number of columns go in the reverse order. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param s An optional value to initialize each matrix element with. To set all the matrix elements to + the particular value after the construction, use the assignment operator + Mat::operator=(const Scalar& value) . + */ + Mat(Size size, int type, const Scalar& s); + + /** @overload + @param ndims Array dimensionality. + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + */ + Mat(int ndims, const int* sizes, int type); + + /** @overload + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + */ + Mat(const std::vector& sizes, int type); + + /** @overload + @param ndims Array dimensionality. + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param s An optional value to initialize each matrix element with. To set all the matrix elements to + the particular value after the construction, use the assignment operator + Mat::operator=(const Scalar& value) . + */ + Mat(int ndims, const int* sizes, int type, const Scalar& s); + + /** @overload + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param s An optional value to initialize each matrix element with. To set all the matrix elements to + the particular value after the construction, use the assignment operator + Mat::operator=(const Scalar& value) . + */ + Mat(const std::vector& sizes, int type, const Scalar& s); + + + /** @overload + @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied + by these constructors. Instead, the header pointing to m data or its sub-array is constructed and + associated with it. The reference counter, if any, is incremented. So, when you modify the matrix + formed using such a constructor, you also modify the corresponding elements of m . If you want to + have an independent copy of the sub-array, use Mat::clone() . + */ + Mat(const Mat& m); + + /** @overload + @param rows Number of rows in a 2D array. + @param cols Number of columns in a 2D array. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param data Pointer to the user data. Matrix constructors that take data and step parameters do not + allocate matrix data. Instead, they just initialize the matrix header that points to the specified + data, which means that no data is copied. This operation is very efficient and can be used to + process external data using OpenCV functions. The external data is not automatically deallocated, so + you should take care of it. + @param step Number of bytes each matrix row occupies. The value should include the padding bytes at + the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed + and the actual step is calculated as cols*elemSize(). See Mat::elemSize. + */ + Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP); + + /** @overload + @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the + number of columns go in the reverse order. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param data Pointer to the user data. Matrix constructors that take data and step parameters do not + allocate matrix data. Instead, they just initialize the matrix header that points to the specified + data, which means that no data is copied. This operation is very efficient and can be used to + process external data using OpenCV functions. The external data is not automatically deallocated, so + you should take care of it. + @param step Number of bytes each matrix row occupies. The value should include the padding bytes at + the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed + and the actual step is calculated as cols*elemSize(). See Mat::elemSize. + */ + Mat(Size size, int type, void* data, size_t step=AUTO_STEP); + + /** @overload + @param ndims Array dimensionality. + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param data Pointer to the user data. Matrix constructors that take data and step parameters do not + allocate matrix data. Instead, they just initialize the matrix header that points to the specified + data, which means that no data is copied. This operation is very efficient and can be used to + process external data using OpenCV functions. The external data is not automatically deallocated, so + you should take care of it. + @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always + set to the element size). If not specified, the matrix is assumed to be continuous. + */ + Mat(int ndims, const int* sizes, int type, void* data, const size_t* steps=0); + + /** @overload + @param sizes Array of integers specifying an n-dimensional array shape. + @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or + CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + @param data Pointer to the user data. Matrix constructors that take data and step parameters do not + allocate matrix data. Instead, they just initialize the matrix header that points to the specified + data, which means that no data is copied. This operation is very efficient and can be used to + process external data using OpenCV functions. The external data is not automatically deallocated, so + you should take care of it. + @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always + set to the element size). If not specified, the matrix is assumed to be continuous. + */ + Mat(const std::vector& sizes, int type, void* data, const size_t* steps=0); + + /** @overload + @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied + by these constructors. Instead, the header pointing to m data or its sub-array is constructed and + associated with it. The reference counter, if any, is incremented. So, when you modify the matrix + formed using such a constructor, you also modify the corresponding elements of m . If you want to + have an independent copy of the sub-array, use Mat::clone() . + @param rowRange Range of the m rows to take. As usual, the range start is inclusive and the range + end is exclusive. Use Range::all() to take all the rows. + @param colRange Range of the m columns to take. Use Range::all() to take all the columns. + */ + Mat(const Mat& m, const Range& rowRange, const Range& colRange=Range::all()); + + /** @overload + @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied + by these constructors. Instead, the header pointing to m data or its sub-array is constructed and + associated with it. The reference counter, if any, is incremented. So, when you modify the matrix + formed using such a constructor, you also modify the corresponding elements of m . If you want to + have an independent copy of the sub-array, use Mat::clone() . + @param roi Region of interest. + */ + Mat(const Mat& m, const Rect& roi); + + /** @overload + @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied + by these constructors. Instead, the header pointing to m data or its sub-array is constructed and + associated with it. The reference counter, if any, is incremented. So, when you modify the matrix + formed using such a constructor, you also modify the corresponding elements of m . If you want to + have an independent copy of the sub-array, use Mat::clone() . + @param ranges Array of selected ranges of m along each dimensionality. + */ + Mat(const Mat& m, const Range* ranges); + + /** @overload + @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied + by these constructors. Instead, the header pointing to m data or its sub-array is constructed and + associated with it. The reference counter, if any, is incremented. So, when you modify the matrix + formed using such a constructor, you also modify the corresponding elements of m . If you want to + have an independent copy of the sub-array, use Mat::clone() . + @param ranges Array of selected ranges of m along each dimensionality. + */ + Mat(const Mat& m, const std::vector& ranges); + + /** @overload + @param vec STL vector whose elements form the matrix. The matrix has a single column and the number + of rows equal to the number of vector elements. Type of the matrix matches the type of vector + elements. The constructor can handle arbitrary types, for which there is a properly declared + DataType . This means that the vector elements must be primitive numbers or uni-type numerical + tuples of numbers. Mixed-type structures are not supported. The corresponding constructor is + explicit. Since STL vectors are not automatically converted to Mat instances, you should write + Mat(vec) explicitly. Unless you copy the data into the matrix ( copyData=true ), no new elements + will be added to the vector because it can potentially yield vector data reallocation, and, thus, + the matrix data pointer will be invalid. + @param copyData Flag to specify whether the underlying data of the STL vector should be copied + to (true) or shared with (false) the newly constructed matrix. When the data is copied, the + allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not + destructed. + */ + template explicit Mat(const std::vector<_Tp>& vec, bool copyData=false); + +#ifdef CV_CXX11 + /** @overload + */ + template::value>::type> + explicit Mat(const std::initializer_list<_Tp> list); + + /** @overload + */ + template explicit Mat(const std::initializer_list sizes, const std::initializer_list<_Tp> list); +#endif + +#ifdef CV_CXX_STD_ARRAY + /** @overload + */ + template explicit Mat(const std::array<_Tp, _Nm>& arr, bool copyData=false); +#endif + + /** @overload + */ + template explicit Mat(const Vec<_Tp, n>& vec, bool copyData=true); + + /** @overload + */ + template explicit Mat(const Matx<_Tp, m, n>& mtx, bool copyData=true); + + /** @overload + */ + template explicit Mat(const Point_<_Tp>& pt, bool copyData=true); + + /** @overload + */ + template explicit Mat(const Point3_<_Tp>& pt, bool copyData=true); + + /** @overload + */ + template explicit Mat(const MatCommaInitializer_<_Tp>& commaInitializer); + + //! download data from GpuMat + explicit Mat(const cuda::GpuMat& m); + + //! destructor - calls release() + ~Mat(); + + /** @brief assignment operators + + These are available assignment operators. Since they all are very different, make sure to read the + operator parameters description. + @param m Assigned, right-hand-side matrix. Matrix assignment is an O(1) operation. This means that + no data is copied but the data is shared and the reference counter, if any, is incremented. Before + assigning new data, the old data is de-referenced via Mat::release . + */ + Mat& operator = (const Mat& m); + + /** @overload + @param expr Assigned matrix expression object. As opposite to the first form of the assignment + operation, the second form can reuse already allocated matrix if it has the right size and type to + fit the matrix expression result. It is automatically handled by the real function that the matrix + expressions is expanded to. For example, C=A+B is expanded to add(A, B, C), and add takes care of + automatic C reallocation. + */ + Mat& operator = (const MatExpr& expr); + + //! retrieve UMat from Mat + UMat getUMat(int accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT) const; + + /** @brief Creates a matrix header for the specified matrix row. + + The method makes a new header for the specified matrix row and returns it. This is an O(1) + operation, regardless of the matrix size. The underlying data of the new matrix is shared with the + original matrix. Here is the example of one of the classical basic matrix processing operations, + axpy, used by LU and many other algorithms: + @code + inline void matrix_axpy(Mat& A, int i, int j, double alpha) + { + A.row(i) += A.row(j)*alpha; + } + @endcode + @note In the current implementation, the following code does not work as expected: + @code + Mat A; + ... + A.row(i) = A.row(j); // will not work + @endcode + This happens because A.row(i) forms a temporary header that is further assigned to another header. + Remember that each of these operations is O(1), that is, no data is copied. Thus, the above + assignment is not true if you may have expected the j-th row to be copied to the i-th row. To + achieve that, you should either turn this simple assignment into an expression or use the + Mat::copyTo method: + @code + Mat A; + ... + // works, but looks a bit obscure. + A.row(i) = A.row(j) + 0; + // this is a bit longer, but the recommended method. + A.row(j).copyTo(A.row(i)); + @endcode + @param y A 0-based row index. + */ + Mat row(int y) const; + + /** @brief Creates a matrix header for the specified matrix column. + + The method makes a new header for the specified matrix column and returns it. This is an O(1) + operation, regardless of the matrix size. The underlying data of the new matrix is shared with the + original matrix. See also the Mat::row description. + @param x A 0-based column index. + */ + Mat col(int x) const; + + /** @brief Creates a matrix header for the specified row span. + + The method makes a new header for the specified row span of the matrix. Similarly to Mat::row and + Mat::col , this is an O(1) operation. + @param startrow An inclusive 0-based start index of the row span. + @param endrow An exclusive 0-based ending index of the row span. + */ + Mat rowRange(int startrow, int endrow) const; + + /** @overload + @param r Range structure containing both the start and the end indices. + */ + Mat rowRange(const Range& r) const; + + /** @brief Creates a matrix header for the specified column span. + + The method makes a new header for the specified column span of the matrix. Similarly to Mat::row and + Mat::col , this is an O(1) operation. + @param startcol An inclusive 0-based start index of the column span. + @param endcol An exclusive 0-based ending index of the column span. + */ + Mat colRange(int startcol, int endcol) const; + + /** @overload + @param r Range structure containing both the start and the end indices. + */ + Mat colRange(const Range& r) const; + + /** @brief Extracts a diagonal from a matrix + + The method makes a new header for the specified matrix diagonal. The new matrix is represented as a + single-column matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation. + @param d index of the diagonal, with the following values: + - `d=0` is the main diagonal. + - `d<0` is a diagonal from the lower half. For example, d=-1 means the diagonal is set + immediately below the main one. + - `d>0` is a diagonal from the upper half. For example, d=1 means the diagonal is set + immediately above the main one. + For example: + @code + Mat m = (Mat_(3,3) << + 1,2,3, + 4,5,6, + 7,8,9); + Mat d0 = m.diag(0); + Mat d1 = m.diag(1); + Mat d_1 = m.diag(-1); + @endcode + The resulting matrices are + @code + d0 = + [1; + 5; + 9] + d1 = + [2; + 6] + d_1 = + [4; + 8] + @endcode + */ + Mat diag(int d=0) const; + + /** @brief creates a diagonal matrix + + The method creates a square diagonal matrix from specified main diagonal. + @param d One-dimensional matrix that represents the main diagonal. + */ + static Mat diag(const Mat& d); + + /** @brief Creates a full copy of the array and the underlying data. + + The method creates a full copy of the array. The original step[] is not taken into account. So, the + array copy is a continuous array occupying total()*elemSize() bytes. + */ + Mat clone() const CV_NODISCARD; + + /** @brief Copies the matrix to another one. + + The method copies the matrix data to another matrix. Before copying the data, the method invokes : + @code + m.create(this->size(), this->type()); + @endcode + so that the destination matrix is reallocated if needed. While m.copyTo(m); works flawlessly, the + function does not handle the case of a partial overlap between the source and the destination + matrices. + + When the operation mask is specified, if the Mat::create call shown above reallocates the matrix, + the newly allocated matrix is initialized with all zeros before copying the data. + @param m Destination matrix. If it does not have a proper size or type before the operation, it is + reallocated. + */ + void copyTo( OutputArray m ) const; + + /** @overload + @param m Destination matrix. If it does not have a proper size or type before the operation, it is + reallocated. + @param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix + elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels. + */ + void copyTo( OutputArray m, InputArray mask ) const; + + /** @brief Converts an array to another data type with optional scaling. + + The method converts source pixel values to the target data type. saturate_cast\<\> is applied at + the end to avoid possible overflows: + + \f[m(x,y) = saturate \_ cast( \alpha (*this)(x,y) + \beta )\f] + @param m output matrix; if it does not have a proper size or type before the operation, it is + reallocated. + @param rtype desired output matrix type or, rather, the depth since the number of channels are the + same as the input has; if rtype is negative, the output matrix will have the same type as the input. + @param alpha optional scale factor. + @param beta optional delta added to the scaled values. + */ + void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const; + + /** @brief Provides a functional form of convertTo. + + This is an internally used method called by the @ref MatrixExpressions engine. + @param m Destination array. + @param type Desired destination array depth (or -1 if it should be the same as the source type). + */ + void assignTo( Mat& m, int type=-1 ) const; + + /** @brief Sets all or some of the array elements to the specified value. + @param s Assigned scalar converted to the actual array type. + */ + Mat& operator = (const Scalar& s); + + /** @brief Sets all or some of the array elements to the specified value. + + This is an advanced variant of the Mat::operator=(const Scalar& s) operator. + @param value Assigned scalar converted to the actual array type. + @param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix + elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels + */ + Mat& setTo(InputArray value, InputArray mask=noArray()); + + /** @brief Changes the shape and/or the number of channels of a 2D matrix without copying the data. + + The method makes a new matrix header for \*this elements. The new matrix may have a different size + and/or different number of channels. Any combination is possible if: + - No extra elements are included into the new matrix and no elements are excluded. Consequently, + the product rows\*cols\*channels() must stay the same after the transformation. + - No data is copied. That is, this is an O(1) operation. Consequently, if you change the number of + rows, or the operation changes the indices of elements row in some other way, the matrix must be + continuous. See Mat::isContinuous . + + For example, if there is a set of 3D points stored as an STL vector, and you want to represent the + points as a 3xN matrix, do the following: + @code + std::vector vec; + ... + Mat pointMat = Mat(vec). // convert vector to Mat, O(1) operation + reshape(1). // make Nx3 1-channel matrix out of Nx1 3-channel. + // Also, an O(1) operation + t(); // finally, transpose the Nx3 matrix. + // This involves copying all the elements + @endcode + @param cn New number of channels. If the parameter is 0, the number of channels remains the same. + @param rows New number of rows. If the parameter is 0, the number of rows remains the same. + */ + Mat reshape(int cn, int rows=0) const; + + /** @overload */ + Mat reshape(int cn, int newndims, const int* newsz) const; + + /** @overload */ + Mat reshape(int cn, const std::vector& newshape) const; + + /** @brief Transposes a matrix. + + The method performs matrix transposition by means of matrix expressions. It does not perform the + actual transposition but returns a temporary matrix transposition object that can be further used as + a part of more complex matrix expressions or can be assigned to a matrix: + @code + Mat A1 = A + Mat::eye(A.size(), A.type())*lambda; + Mat C = A1.t()*A1; // compute (A + lambda*I)^t * (A + lamda*I) + @endcode + */ + MatExpr t() const; + + /** @brief Inverses a matrix. + + The method performs a matrix inversion by means of matrix expressions. This means that a temporary + matrix inversion object is returned by the method and can be used further as a part of more complex + matrix expressions or can be assigned to a matrix. + @param method Matrix inversion method. One of cv::DecompTypes + */ + MatExpr inv(int method=DECOMP_LU) const; + + /** @brief Performs an element-wise multiplication or division of the two matrices. + + The method returns a temporary object encoding per-element array multiplication, with optional + scale. Note that this is not a matrix multiplication that corresponds to a simpler "\*" operator. + + Example: + @code + Mat C = A.mul(5/B); // equivalent to divide(A, B, C, 5) + @endcode + @param m Another array of the same type and the same size as \*this, or a matrix expression. + @param scale Optional scale factor. + */ + MatExpr mul(InputArray m, double scale=1) const; + + /** @brief Computes a cross-product of two 3-element vectors. + + The method computes a cross-product of two 3-element vectors. The vectors must be 3-element + floating-point vectors of the same shape and size. The result is another 3-element vector of the + same shape and type as operands. + @param m Another cross-product operand. + */ + Mat cross(InputArray m) const; + + /** @brief Computes a dot-product of two vectors. + + The method computes a dot-product of two matrices. If the matrices are not single-column or + single-row vectors, the top-to-bottom left-to-right scan ordering is used to treat them as 1D + vectors. The vectors must have the same size and type. If the matrices have more than one channel, + the dot products from all the channels are summed together. + @param m another dot-product operand. + */ + double dot(InputArray m) const; + + /** @brief Returns a zero array of the specified size and type. + + The method returns a Matlab-style zero array initializer. It can be used to quickly form a constant + array as a function parameter, part of a matrix expression, or as a matrix initializer: + @code + Mat A; + A = Mat::zeros(3, 3, CV_32F); + @endcode + In the example above, a new matrix is allocated only if A is not a 3x3 floating-point matrix. + Otherwise, the existing matrix A is filled with zeros. + @param rows Number of rows. + @param cols Number of columns. + @param type Created matrix type. + */ + static MatExpr zeros(int rows, int cols, int type); + + /** @overload + @param size Alternative to the matrix size specification Size(cols, rows) . + @param type Created matrix type. + */ + static MatExpr zeros(Size size, int type); + + /** @overload + @param ndims Array dimensionality. + @param sz Array of integers specifying the array shape. + @param type Created matrix type. + */ + static MatExpr zeros(int ndims, const int* sz, int type); + + /** @brief Returns an array of all 1's of the specified size and type. + + The method returns a Matlab-style 1's array initializer, similarly to Mat::zeros. Note that using + this method you can initialize an array with an arbitrary value, using the following Matlab idiom: + @code + Mat A = Mat::ones(100, 100, CV_8U)*3; // make 100x100 matrix filled with 3. + @endcode + The above operation does not form a 100x100 matrix of 1's and then multiply it by 3. Instead, it + just remembers the scale factor (3 in this case) and use it when actually invoking the matrix + initializer. + @note In case of multi-channels type, only the first channel will be initialized with 1's, the + others will be set to 0's. + @param rows Number of rows. + @param cols Number of columns. + @param type Created matrix type. + */ + static MatExpr ones(int rows, int cols, int type); + + /** @overload + @param size Alternative to the matrix size specification Size(cols, rows) . + @param type Created matrix type. + */ + static MatExpr ones(Size size, int type); + + /** @overload + @param ndims Array dimensionality. + @param sz Array of integers specifying the array shape. + @param type Created matrix type. + */ + static MatExpr ones(int ndims, const int* sz, int type); + + /** @brief Returns an identity matrix of the specified size and type. + + The method returns a Matlab-style identity matrix initializer, similarly to Mat::zeros. Similarly to + Mat::ones, you can use a scale operation to create a scaled identity matrix efficiently: + @code + // make a 4x4 diagonal matrix with 0.1's on the diagonal. + Mat A = Mat::eye(4, 4, CV_32F)*0.1; + @endcode + @note In case of multi-channels type, identity matrix will be initialized only for the first channel, + the others will be set to 0's + @param rows Number of rows. + @param cols Number of columns. + @param type Created matrix type. + */ + static MatExpr eye(int rows, int cols, int type); + + /** @overload + @param size Alternative matrix size specification as Size(cols, rows) . + @param type Created matrix type. + */ + static MatExpr eye(Size size, int type); + + /** @brief Allocates new array data if needed. + + This is one of the key Mat methods. Most new-style OpenCV functions and methods that produce arrays + call this method for each output array. The method uses the following algorithm: + + -# If the current array shape and the type match the new ones, return immediately. Otherwise, + de-reference the previous data by calling Mat::release. + -# Initialize the new header. + -# Allocate the new data of total()\*elemSize() bytes. + -# Allocate the new, associated with the data, reference counter and set it to 1. + + Such a scheme makes the memory management robust and efficient at the same time and helps avoid + extra typing for you. This means that usually there is no need to explicitly allocate output arrays. + That is, instead of writing: + @code + Mat color; + ... + Mat gray(color.rows, color.cols, color.depth()); + cvtColor(color, gray, COLOR_BGR2GRAY); + @endcode + you can simply write: + @code + Mat color; + ... + Mat gray; + cvtColor(color, gray, COLOR_BGR2GRAY); + @endcode + because cvtColor, as well as the most of OpenCV functions, calls Mat::create() for the output array + internally. + @param rows New number of rows. + @param cols New number of columns. + @param type New matrix type. + */ + void create(int rows, int cols, int type); + + /** @overload + @param size Alternative new matrix size specification: Size(cols, rows) + @param type New matrix type. + */ + void create(Size size, int type); + + /** @overload + @param ndims New array dimensionality. + @param sizes Array of integers specifying a new array shape. + @param type New matrix type. + */ + void create(int ndims, const int* sizes, int type); + + /** @overload + @param sizes Array of integers specifying a new array shape. + @param type New matrix type. + */ + void create(const std::vector& sizes, int type); + + /** @brief Increments the reference counter. + + The method increments the reference counter associated with the matrix data. If the matrix header + points to an external data set (see Mat::Mat ), the reference counter is NULL, and the method has no + effect in this case. Normally, to avoid memory leaks, the method should not be called explicitly. It + is called implicitly by the matrix assignment operator. The reference counter increment is an atomic + operation on the platforms that support it. Thus, it is safe to operate on the same matrices + asynchronously in different threads. + */ + void addref(); + + /** @brief Decrements the reference counter and deallocates the matrix if needed. + + The method decrements the reference counter associated with the matrix data. When the reference + counter reaches 0, the matrix data is deallocated and the data and the reference counter pointers + are set to NULL's. If the matrix header points to an external data set (see Mat::Mat ), the + reference counter is NULL, and the method has no effect in this case. + + This method can be called manually to force the matrix data deallocation. But since this method is + automatically called in the destructor, or by any other method that changes the data pointer, it is + usually not needed. The reference counter decrement and check for 0 is an atomic operation on the + platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in + different threads. + */ + void release(); + + //! internal use function, consider to use 'release' method instead; deallocates the matrix data + void deallocate(); + //! internal use function; properly re-allocates _size, _step arrays + void copySize(const Mat& m); + + /** @brief Reserves space for the certain number of rows. + + The method reserves space for sz rows. If the matrix already has enough space to store sz rows, + nothing happens. If the matrix is reallocated, the first Mat::rows rows are preserved. The method + emulates the corresponding method of the STL vector class. + @param sz Number of rows. + */ + void reserve(size_t sz); + + /** @brief Reserves space for the certain number of bytes. + + The method reserves space for sz bytes. If the matrix already has enough space to store sz bytes, + nothing happens. If matrix has to be reallocated its previous content could be lost. + @param sz Number of bytes. + */ + void reserveBuffer(size_t sz); + + /** @brief Changes the number of matrix rows. + + The methods change the number of matrix rows. If the matrix is reallocated, the first + min(Mat::rows, sz) rows are preserved. The methods emulate the corresponding methods of the STL + vector class. + @param sz New number of rows. + */ + void resize(size_t sz); + + /** @overload + @param sz New number of rows. + @param s Value assigned to the newly added elements. + */ + void resize(size_t sz, const Scalar& s); + + //! internal function + void push_back_(const void* elem); + + /** @brief Adds elements to the bottom of the matrix. + + The methods add one or more elements to the bottom of the matrix. They emulate the corresponding + method of the STL vector class. When elem is Mat , its type and the number of columns must be the + same as in the container matrix. + @param elem Added element(s). + */ + template void push_back(const _Tp& elem); + + /** @overload + @param elem Added element(s). + */ + template void push_back(const Mat_<_Tp>& elem); + + /** @overload + @param elem Added element(s). + */ + template void push_back(const std::vector<_Tp>& elem); + + /** @overload + @param m Added line(s). + */ + void push_back(const Mat& m); + + /** @brief Removes elements from the bottom of the matrix. + + The method removes one or more rows from the bottom of the matrix. + @param nelems Number of removed rows. If it is greater than the total number of rows, an exception + is thrown. + */ + void pop_back(size_t nelems=1); + + /** @brief Locates the matrix header within a parent matrix. + + After you extracted a submatrix from a matrix using Mat::row, Mat::col, Mat::rowRange, + Mat::colRange, and others, the resultant submatrix points just to the part of the original big + matrix. However, each submatrix contains information (represented by datastart and dataend + fields) that helps reconstruct the original matrix size and the position of the extracted + submatrix within the original matrix. The method locateROI does exactly that. + @param wholeSize Output parameter that contains the size of the whole matrix containing *this* + as a part. + @param ofs Output parameter that contains an offset of *this* inside the whole matrix. + */ + void locateROI( Size& wholeSize, Point& ofs ) const; + + /** @brief Adjusts a submatrix size and position within the parent matrix. + + The method is complimentary to Mat::locateROI . The typical use of these functions is to determine + the submatrix position within the parent matrix and then shift the position somehow. Typically, it + can be required for filtering operations when pixels outside of the ROI should be taken into + account. When all the method parameters are positive, the ROI needs to grow in all directions by the + specified amount, for example: + @code + A.adjustROI(2, 2, 2, 2); + @endcode + In this example, the matrix size is increased by 4 elements in each direction. The matrix is shifted + by 2 elements to the left and 2 elements up, which brings in all the necessary pixels for the + filtering with the 5x5 kernel. + + adjustROI forces the adjusted ROI to be inside of the parent matrix that is boundaries of the + adjusted ROI are constrained by boundaries of the parent matrix. For example, if the submatrix A is + located in the first row of a parent matrix and you called A.adjustROI(2, 2, 2, 2) then A will not + be increased in the upward direction. + + The function is used internally by the OpenCV filtering functions, like filter2D , morphological + operations, and so on. + @param dtop Shift of the top submatrix boundary upwards. + @param dbottom Shift of the bottom submatrix boundary downwards. + @param dleft Shift of the left submatrix boundary to the left. + @param dright Shift of the right submatrix boundary to the right. + @sa copyMakeBorder + */ + Mat& adjustROI( int dtop, int dbottom, int dleft, int dright ); + + /** @brief Extracts a rectangular submatrix. + + The operators make a new header for the specified sub-array of \*this . They are the most + generalized forms of Mat::row, Mat::col, Mat::rowRange, and Mat::colRange . For example, + `A(Range(0, 10), Range::all())` is equivalent to `A.rowRange(0, 10)`. Similarly to all of the above, + the operators are O(1) operations, that is, no matrix data is copied. + @param rowRange Start and end row of the extracted submatrix. The upper boundary is not included. To + select all the rows, use Range::all(). + @param colRange Start and end column of the extracted submatrix. The upper boundary is not included. + To select all the columns, use Range::all(). + */ + Mat operator()( Range rowRange, Range colRange ) const; + + /** @overload + @param roi Extracted submatrix specified as a rectangle. + */ + Mat operator()( const Rect& roi ) const; + + /** @overload + @param ranges Array of selected ranges along each array dimension. + */ + Mat operator()( const Range* ranges ) const; + + /** @overload + @param ranges Array of selected ranges along each array dimension. + */ + Mat operator()(const std::vector& ranges) const; + + // //! converts header to CvMat; no data is copied + // operator CvMat() const; + // //! converts header to CvMatND; no data is copied + // operator CvMatND() const; + // //! converts header to IplImage; no data is copied + // operator IplImage() const; + + template operator std::vector<_Tp>() const; + template operator Vec<_Tp, n>() const; + template operator Matx<_Tp, m, n>() const; + +#ifdef CV_CXX_STD_ARRAY + template operator std::array<_Tp, _Nm>() const; +#endif + + /** @brief Reports whether the matrix is continuous or not. + + The method returns true if the matrix elements are stored continuously without gaps at the end of + each row. Otherwise, it returns false. Obviously, 1x1 or 1xN matrices are always continuous. + Matrices created with Mat::create are always continuous. But if you extract a part of the matrix + using Mat::col, Mat::diag, and so on, or constructed a matrix header for externally allocated data, + such matrices may no longer have this property. + + The continuity flag is stored as a bit in the Mat::flags field and is computed automatically when + you construct a matrix header. Thus, the continuity check is a very fast operation, though + theoretically it could be done as follows: + @code + // alternative implementation of Mat::isContinuous() + bool myCheckMatContinuity(const Mat& m) + { + //return (m.flags & Mat::CONTINUOUS_FLAG) != 0; + return m.rows == 1 || m.step == m.cols*m.elemSize(); + } + @endcode + The method is used in quite a few of OpenCV functions. The point is that element-wise operations + (such as arithmetic and logical operations, math functions, alpha blending, color space + transformations, and others) do not depend on the image geometry. Thus, if all the input and output + arrays are continuous, the functions can process them as very long single-row vectors. The example + below illustrates how an alpha-blending function can be implemented: + @code + template + void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst) + { + const float alpha_scale = (float)std::numeric_limits::max(), + inv_scale = 1.f/alpha_scale; + + CV_Assert( src1.type() == src2.type() && + src1.type() == CV_MAKETYPE(traits::Depth::value, 4) && + src1.size() == src2.size()); + Size size = src1.size(); + dst.create(size, src1.type()); + + // here is the idiom: check the arrays for continuity and, + // if this is the case, + // treat the arrays as 1D vectors + if( src1.isContinuous() && src2.isContinuous() && dst.isContinuous() ) + { + size.width *= size.height; + size.height = 1; + } + size.width *= 4; + + for( int i = 0; i < size.height; i++ ) + { + // when the arrays are continuous, + // the outer loop is executed only once + const T* ptr1 = src1.ptr(i); + const T* ptr2 = src2.ptr(i); + T* dptr = dst.ptr(i); + + for( int j = 0; j < size.width; j += 4 ) + { + float alpha = ptr1[j+3]*inv_scale, beta = ptr2[j+3]*inv_scale; + dptr[j] = saturate_cast(ptr1[j]*alpha + ptr2[j]*beta); + dptr[j+1] = saturate_cast(ptr1[j+1]*alpha + ptr2[j+1]*beta); + dptr[j+2] = saturate_cast(ptr1[j+2]*alpha + ptr2[j+2]*beta); + dptr[j+3] = saturate_cast((1 - (1-alpha)*(1-beta))*alpha_scale); + } + } + } + @endcode + This approach, while being very simple, can boost the performance of a simple element-operation by + 10-20 percents, especially if the image is rather small and the operation is quite simple. + + Another OpenCV idiom in this function, a call of Mat::create for the destination array, that + allocates the destination array unless it already has the proper size and type. And while the newly + allocated arrays are always continuous, you still need to check the destination array because + Mat::create does not always allocate a new matrix. + */ + bool isContinuous() const; + + //! returns true if the matrix is a submatrix of another matrix + bool isSubmatrix() const; + + /** @brief Returns the matrix element size in bytes. + + The method returns the matrix element size in bytes. For example, if the matrix type is CV_16SC3 , + the method returns 3\*sizeof(short) or 6. + */ + size_t elemSize() const; + + /** @brief Returns the size of each matrix element channel in bytes. + + The method returns the matrix element channel size in bytes, that is, it ignores the number of + channels. For example, if the matrix type is CV_16SC3 , the method returns sizeof(short) or 2. + */ + size_t elemSize1() const; + + /** @brief Returns the type of a matrix element. + + The method returns a matrix element type. This is an identifier compatible with the CvMat type + system, like CV_16SC3 or 16-bit signed 3-channel array, and so on. + */ + int type() const; + + /** @brief Returns the depth of a matrix element. + + The method returns the identifier of the matrix element depth (the type of each individual channel). + For example, for a 16-bit signed element array, the method returns CV_16S . A complete list of + matrix types contains the following values: + - CV_8U - 8-bit unsigned integers ( 0..255 ) + - CV_8S - 8-bit signed integers ( -128..127 ) + - CV_16U - 16-bit unsigned integers ( 0..65535 ) + - CV_16S - 16-bit signed integers ( -32768..32767 ) + - CV_32S - 32-bit signed integers ( -2147483648..2147483647 ) + - CV_32F - 32-bit floating-point numbers ( -FLT_MAX..FLT_MAX, INF, NAN ) + - CV_64F - 64-bit floating-point numbers ( -DBL_MAX..DBL_MAX, INF, NAN ) + */ + int depth() const; + + /** @brief Returns the number of matrix channels. + + The method returns the number of matrix channels. + */ + int channels() const; + + /** @brief Returns a normalized step. + + The method returns a matrix step divided by Mat::elemSize1() . It can be useful to quickly access an + arbitrary matrix element. + */ + size_t step1(int i=0) const; + + /** @brief Returns true if the array has no elements. + + The method returns true if Mat::total() is 0 or if Mat::data is NULL. Because of pop_back() and + resize() methods `M.total() == 0` does not imply that `M.data == NULL`. + */ + bool empty() const; + + /** @brief Returns the total number of array elements. + + The method returns the number of array elements (a number of pixels if the array represents an + image). + */ + size_t total() const; + + /** @brief Returns the total number of array elements. + + The method returns the number of elements within a certain sub-array slice with startDim <= dim < endDim + */ + size_t total(int startDim, int endDim=INT_MAX) const; + + /** + * @param elemChannels Number of channels or number of columns the matrix should have. + * For a 2-D matrix, when the matrix has only 1 column, then it should have + * elemChannels channels; When the matrix has only 1 channel, + * then it should have elemChannels columns. + * For a 3-D matrix, it should have only one channel. Furthermore, + * if the number of planes is not one, then the number of rows + * within every plane has to be 1; if the number of rows within + * every plane is not 1, then the number of planes has to be 1. + * @param depth The depth the matrix should have. Set it to -1 when any depth is fine. + * @param requireContinuous Set it to true to require the matrix to be continuous + * @return -1 if the requirement is not satisfied. + * Otherwise, it returns the number of elements in the matrix. Note + * that an element may have multiple channels. + * + * The following code demonstrates its usage for a 2-d matrix: + * @snippet snippets/core_mat_checkVector.cpp example-2d + * + * The following code demonstrates its usage for a 3-d matrix: + * @snippet snippets/core_mat_checkVector.cpp example-3d + */ + int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const; + + /** @brief Returns a pointer to the specified matrix row. + + The methods return `uchar*` or typed pointer to the specified matrix row. See the sample in + Mat::isContinuous to know how to use these methods. + @param i0 A 0-based row index. + */ + uchar* ptr(int i0=0); + /** @overload */ + const uchar* ptr(int i0=0) const; + + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + uchar* ptr(int row, int col); + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + const uchar* ptr(int row, int col) const; + + /** @overload */ + uchar* ptr(int i0, int i1, int i2); + /** @overload */ + const uchar* ptr(int i0, int i1, int i2) const; + + /** @overload */ + uchar* ptr(const int* idx); + /** @overload */ + const uchar* ptr(const int* idx) const; + /** @overload */ + template uchar* ptr(const Vec& idx); + /** @overload */ + template const uchar* ptr(const Vec& idx) const; + + /** @overload */ + template _Tp* ptr(int i0=0); + /** @overload */ + template const _Tp* ptr(int i0=0) const; + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + template _Tp* ptr(int row, int col); + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + template const _Tp* ptr(int row, int col) const; + /** @overload */ + template _Tp* ptr(int i0, int i1, int i2); + /** @overload */ + template const _Tp* ptr(int i0, int i1, int i2) const; + /** @overload */ + template _Tp* ptr(const int* idx); + /** @overload */ + template const _Tp* ptr(const int* idx) const; + /** @overload */ + template _Tp* ptr(const Vec& idx); + /** @overload */ + template const _Tp* ptr(const Vec& idx) const; + + /** @brief Returns a reference to the specified array element. + + The template methods return a reference to the specified array element. For the sake of higher + performance, the index range checks are only performed in the Debug configuration. + + Note that the variants with a single index (i) can be used to access elements of single-row or + single-column 2-dimensional arrays. That is, if, for example, A is a 1 x N floating-point matrix and + B is an M x 1 integer matrix, you can simply write `A.at(k+4)` and `B.at(2*i+1)` + instead of `A.at(0,k+4)` and `B.at(2*i+1,0)`, respectively. + + The example below initializes a Hilbert matrix: + @code + Mat H(100, 100, CV_64F); + for(int i = 0; i < H.rows; i++) + for(int j = 0; j < H.cols; j++) + H.at(i,j)=1./(i+j+1); + @endcode + + Keep in mind that the size identifier used in the at operator cannot be chosen at random. It depends + on the image from which you are trying to retrieve the data. The table below gives a better insight in this: + - If matrix is of type `CV_8U` then use `Mat.at(y,x)`. + - If matrix is of type `CV_8S` then use `Mat.at(y,x)`. + - If matrix is of type `CV_16U` then use `Mat.at(y,x)`. + - If matrix is of type `CV_16S` then use `Mat.at(y,x)`. + - If matrix is of type `CV_32S` then use `Mat.at(y,x)`. + - If matrix is of type `CV_32F` then use `Mat.at(y,x)`. + - If matrix is of type `CV_64F` then use `Mat.at(y,x)`. + + @param i0 Index along the dimension 0 + */ + template _Tp& at(int i0=0); + /** @overload + @param i0 Index along the dimension 0 + */ + template const _Tp& at(int i0=0) const; + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + template _Tp& at(int row, int col); + /** @overload + @param row Index along the dimension 0 + @param col Index along the dimension 1 + */ + template const _Tp& at(int row, int col) const; + + /** @overload + @param i0 Index along the dimension 0 + @param i1 Index along the dimension 1 + @param i2 Index along the dimension 2 + */ + template _Tp& at(int i0, int i1, int i2); + /** @overload + @param i0 Index along the dimension 0 + @param i1 Index along the dimension 1 + @param i2 Index along the dimension 2 + */ + template const _Tp& at(int i0, int i1, int i2) const; + + /** @overload + @param idx Array of Mat::dims indices. + */ + template _Tp& at(const int* idx); + /** @overload + @param idx Array of Mat::dims indices. + */ + template const _Tp& at(const int* idx) const; + + /** @overload */ + template _Tp& at(const Vec& idx); + /** @overload */ + template const _Tp& at(const Vec& idx) const; + + /** @overload + special versions for 2D arrays (especially convenient for referencing image pixels) + @param pt Element position specified as Point(j,i) . + */ + template _Tp& at(Point pt); + /** @overload + special versions for 2D arrays (especially convenient for referencing image pixels) + @param pt Element position specified as Point(j,i) . + */ + template const _Tp& at(Point pt) const; + + /** @brief Returns the matrix iterator and sets it to the first matrix element. + + The methods return the matrix read-only or read-write iterators. The use of matrix iterators is very + similar to the use of bi-directional STL iterators. In the example below, the alpha blending + function is rewritten using the matrix iterators: + @code + template + void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst) + { + typedef Vec VT; + + const float alpha_scale = (float)std::numeric_limits::max(), + inv_scale = 1.f/alpha_scale; + + CV_Assert( src1.type() == src2.type() && + src1.type() == traits::Type::value && + src1.size() == src2.size()); + Size size = src1.size(); + dst.create(size, src1.type()); + + MatConstIterator_ it1 = src1.begin(), it1_end = src1.end(); + MatConstIterator_ it2 = src2.begin(); + MatIterator_ dst_it = dst.begin(); + + for( ; it1 != it1_end; ++it1, ++it2, ++dst_it ) + { + VT pix1 = *it1, pix2 = *it2; + float alpha = pix1[3]*inv_scale, beta = pix2[3]*inv_scale; + *dst_it = VT(saturate_cast(pix1[0]*alpha + pix2[0]*beta), + saturate_cast(pix1[1]*alpha + pix2[1]*beta), + saturate_cast(pix1[2]*alpha + pix2[2]*beta), + saturate_cast((1 - (1-alpha)*(1-beta))*alpha_scale)); + } + } + @endcode + */ + template MatIterator_<_Tp> begin(); + template MatConstIterator_<_Tp> begin() const; + + /** @brief Returns the matrix iterator and sets it to the after-last matrix element. + + The methods return the matrix read-only or read-write iterators, set to the point following the last + matrix element. + */ + template MatIterator_<_Tp> end(); + template MatConstIterator_<_Tp> end() const; + + /** @brief Runs the given functor over all matrix elements in parallel. + + The operation passed as argument has to be a function pointer, a function object or a lambda(C++11). + + Example 1. All of the operations below put 0xFF the first channel of all matrix elements: + @code + Mat image(1920, 1080, CV_8UC3); + typedef cv::Point3_ Pixel; + + // first. raw pointer access. + for (int r = 0; r < image.rows; ++r) { + Pixel* ptr = image.ptr(r, 0); + const Pixel* ptr_end = ptr + image.cols; + for (; ptr != ptr_end; ++ptr) { + ptr->x = 255; + } + } + + // Using MatIterator. (Simple but there are a Iterator's overhead) + for (Pixel &p : cv::Mat_(image)) { + p.x = 255; + } + + // Parallel execution with function object. + struct Operator { + void operator ()(Pixel &pixel, const int * position) { + pixel.x = 255; + } + }; + image.forEach(Operator()); + + // Parallel execution using C++11 lambda. + image.forEach([](Pixel &p, const int * position) -> void { + p.x = 255; + }); + @endcode + Example 2. Using the pixel's position: + @code + // Creating 3D matrix (255 x 255 x 255) typed uint8_t + // and initialize all elements by the value which equals elements position. + // i.e. pixels (x,y,z) = (1,2,3) is (b,g,r) = (1,2,3). + + int sizes[] = { 255, 255, 255 }; + typedef cv::Point3_ Pixel; + + Mat_ image = Mat::zeros(3, sizes, CV_8UC3); + + image.forEach([&](Pixel& pixel, const int position[]) -> void { + pixel.x = position[0]; + pixel.y = position[1]; + pixel.z = position[2]; + }); + @endcode + */ + template void forEach(const Functor& operation); + /** @overload */ + template void forEach(const Functor& operation) const; + +#ifdef CV_CXX_MOVE_SEMANTICS + Mat(Mat&& m); + Mat& operator = (Mat&& m); +#endif + + enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG }; + enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 }; + + /*! includes several bit-fields: + - the magic signature + - continuity flag + - depth + - number of channels + */ + int flags; + //! the matrix dimensionality, >= 2 + int dims; + //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions + int rows, cols; + //! pointer to the data + uchar* data; + + //! helper fields used in locateROI and adjustROI + const uchar* datastart; + const uchar* dataend; + const uchar* datalimit; + + //! custom allocator + MatAllocator* allocator; + //! and the standard allocator + static MatAllocator* getStdAllocator(); + static MatAllocator* getDefaultAllocator(); + static void setDefaultAllocator(MatAllocator* allocator); + + //! internal use method: updates the continuity flag + void updateContinuityFlag(); + + //! interaction with UMat + UMatData* u; + + MatSize size; + MatStep step; + +protected: + template void forEach_impl(const Functor& operation); +}; + + +///////////////////////////////// Mat_<_Tp> //////////////////////////////////// + +/** @brief Template matrix class derived from Mat + +@code{.cpp} + template class Mat_ : public Mat + { + public: + // ... some specific methods + // and + // no new extra fields + }; +@endcode +The class `Mat_<_Tp>` is a *thin* template wrapper on top of the Mat class. It does not have any +extra data fields. Nor this class nor Mat has any virtual methods. Thus, references or pointers to +these two classes can be freely but carefully converted one to another. For example: +@code{.cpp} + // create a 100x100 8-bit matrix + Mat M(100,100,CV_8U); + // this will be compiled fine. no any data conversion will be done. + Mat_& M1 = (Mat_&)M; + // the program is likely to crash at the statement below + M1(99,99) = 1.f; +@endcode +While Mat is sufficient in most cases, Mat_ can be more convenient if you use a lot of element +access operations and if you know matrix type at the compilation time. Note that +`Mat::at(int y,int x)` and `Mat_::operator()(int y,int x)` do absolutely the same +and run at the same speed, but the latter is certainly shorter: +@code{.cpp} + Mat_ M(20,20); + for(int i = 0; i < M.rows; i++) + for(int j = 0; j < M.cols; j++) + M(i,j) = 1./(i+j+1); + Mat E, V; + eigen(M,E,V); + cout << E.at(0,0)/E.at(M.rows-1,0); +@endcode +To use Mat_ for multi-channel images/matrices, pass Vec as a Mat_ parameter: +@code{.cpp} + // allocate a 320x240 color image and fill it with green (in RGB space) + Mat_ img(240, 320, Vec3b(0,255,0)); + // now draw a diagonal white line + for(int i = 0; i < 100; i++) + img(i,i)=Vec3b(255,255,255); + // and now scramble the 2nd (red) channel of each pixel + for(int i = 0; i < img.rows; i++) + for(int j = 0; j < img.cols; j++) + img(i,j)[2] ^= (uchar)(i ^ j); +@endcode +Mat_ is fully compatible with C++11 range-based for loop. For example such loop +can be used to safely apply look-up table: +@code{.cpp} +void applyTable(Mat_& I, const uchar* const table) +{ + for(auto& pixel : I) + { + pixel = table[pixel]; + } +} +@endcode + */ +template class Mat_ : public Mat +{ +public: + typedef _Tp value_type; + typedef typename DataType<_Tp>::channel_type channel_type; + typedef MatIterator_<_Tp> iterator; + typedef MatConstIterator_<_Tp> const_iterator; + + //! default constructor + Mat_(); + //! equivalent to Mat(_rows, _cols, DataType<_Tp>::type) + Mat_(int _rows, int _cols); + //! constructor that sets each matrix element to specified value + Mat_(int _rows, int _cols, const _Tp& value); + //! equivalent to Mat(_size, DataType<_Tp>::type) + explicit Mat_(Size _size); + //! constructor that sets each matrix element to specified value + Mat_(Size _size, const _Tp& value); + //! n-dim array constructor + Mat_(int _ndims, const int* _sizes); + //! n-dim array constructor that sets each matrix element to specified value + Mat_(int _ndims, const int* _sizes, const _Tp& value); + //! copy/conversion constructor. If m is of different type, it's converted + Mat_(const Mat& m); + //! copy constructor + Mat_(const Mat_& m); + //! constructs a matrix on top of user-allocated data. step is in bytes(!!!), regardless of the type + Mat_(int _rows, int _cols, _Tp* _data, size_t _step=AUTO_STEP); + //! constructs n-dim matrix on top of user-allocated data. steps are in bytes(!!!), regardless of the type + Mat_(int _ndims, const int* _sizes, _Tp* _data, const size_t* _steps=0); + //! selects a submatrix + Mat_(const Mat_& m, const Range& rowRange, const Range& colRange=Range::all()); + //! selects a submatrix + Mat_(const Mat_& m, const Rect& roi); + //! selects a submatrix, n-dim version + Mat_(const Mat_& m, const Range* ranges); + //! selects a submatrix, n-dim version + Mat_(const Mat_& m, const std::vector& ranges); + //! from a matrix expression + explicit Mat_(const MatExpr& e); + //! makes a matrix out of Vec, std::vector, Point_ or Point3_. The matrix will have a single column + explicit Mat_(const std::vector<_Tp>& vec, bool copyData=false); + template explicit Mat_(const Vec::channel_type, n>& vec, bool copyData=true); + template explicit Mat_(const Matx::channel_type, m, n>& mtx, bool copyData=true); + explicit Mat_(const Point_::channel_type>& pt, bool copyData=true); + explicit Mat_(const Point3_::channel_type>& pt, bool copyData=true); + explicit Mat_(const MatCommaInitializer_<_Tp>& commaInitializer); + +#ifdef CV_CXX11 + Mat_(std::initializer_list<_Tp> values); + explicit Mat_(const std::initializer_list sizes, const std::initializer_list<_Tp> values); +#endif + +#ifdef CV_CXX_STD_ARRAY + template explicit Mat_(const std::array<_Tp, _Nm>& arr, bool copyData=false); +#endif + + Mat_& operator = (const Mat& m); + Mat_& operator = (const Mat_& m); + //! set all the elements to s. + Mat_& operator = (const _Tp& s); + //! assign a matrix expression + Mat_& operator = (const MatExpr& e); + + //! iterators; they are smart enough to skip gaps in the end of rows + iterator begin(); + iterator end(); + const_iterator begin() const; + const_iterator end() const; + + //! template methods for for operation over all matrix elements. + // the operations take care of skipping gaps in the end of rows (if any) + template void forEach(const Functor& operation); + template void forEach(const Functor& operation) const; + + //! equivalent to Mat::create(_rows, _cols, DataType<_Tp>::type) + void create(int _rows, int _cols); + //! equivalent to Mat::create(_size, DataType<_Tp>::type) + void create(Size _size); + //! equivalent to Mat::create(_ndims, _sizes, DatType<_Tp>::type) + void create(int _ndims, const int* _sizes); + //! equivalent to Mat::release() + void release(); + //! cross-product + Mat_ cross(const Mat_& m) const; + //! data type conversion + template operator Mat_() const; + //! overridden forms of Mat::row() etc. + Mat_ row(int y) const; + Mat_ col(int x) const; + Mat_ diag(int d=0) const; + Mat_ clone() const CV_NODISCARD; + + //! overridden forms of Mat::elemSize() etc. + size_t elemSize() const; + size_t elemSize1() const; + int type() const; + int depth() const; + int channels() const; + size_t step1(int i=0) const; + //! returns step()/sizeof(_Tp) + size_t stepT(int i=0) const; + + //! overridden forms of Mat::zeros() etc. Data type is omitted, of course + static MatExpr zeros(int rows, int cols); + static MatExpr zeros(Size size); + static MatExpr zeros(int _ndims, const int* _sizes); + static MatExpr ones(int rows, int cols); + static MatExpr ones(Size size); + static MatExpr ones(int _ndims, const int* _sizes); + static MatExpr eye(int rows, int cols); + static MatExpr eye(Size size); + + //! some more overridden methods + Mat_& adjustROI( int dtop, int dbottom, int dleft, int dright ); + Mat_ operator()( const Range& rowRange, const Range& colRange ) const; + Mat_ operator()( const Rect& roi ) const; + Mat_ operator()( const Range* ranges ) const; + Mat_ operator()(const std::vector& ranges) const; + + //! more convenient forms of row and element access operators + _Tp* operator [](int y); + const _Tp* operator [](int y) const; + + //! returns reference to the specified element + _Tp& operator ()(const int* idx); + //! returns read-only reference to the specified element + const _Tp& operator ()(const int* idx) const; + + //! returns reference to the specified element + template _Tp& operator ()(const Vec& idx); + //! returns read-only reference to the specified element + template const _Tp& operator ()(const Vec& idx) const; + + //! returns reference to the specified element (1D case) + _Tp& operator ()(int idx0); + //! returns read-only reference to the specified element (1D case) + const _Tp& operator ()(int idx0) const; + //! returns reference to the specified element (2D case) + _Tp& operator ()(int row, int col); + //! returns read-only reference to the specified element (2D case) + const _Tp& operator ()(int row, int col) const; + //! returns reference to the specified element (3D case) + _Tp& operator ()(int idx0, int idx1, int idx2); + //! returns read-only reference to the specified element (3D case) + const _Tp& operator ()(int idx0, int idx1, int idx2) const; + + _Tp& operator ()(Point pt); + const _Tp& operator ()(Point pt) const; + + //! conversion to vector. + operator std::vector<_Tp>() const; + +#ifdef CV_CXX_STD_ARRAY + //! conversion to array. + template operator std::array<_Tp, _Nm>() const; +#endif + + //! conversion to Vec + template operator Vec::channel_type, n>() const; + //! conversion to Matx + template operator Matx::channel_type, m, n>() const; + +#ifdef CV_CXX_MOVE_SEMANTICS + Mat_(Mat_&& m); + Mat_& operator = (Mat_&& m); + + Mat_(Mat&& m); + Mat_& operator = (Mat&& m); + + Mat_(MatExpr&& e); +#endif +}; + +typedef Mat_ Mat1b; +typedef Mat_ Mat2b; +typedef Mat_ Mat3b; +typedef Mat_ Mat4b; + +typedef Mat_ Mat1s; +typedef Mat_ Mat2s; +typedef Mat_ Mat3s; +typedef Mat_ Mat4s; + +typedef Mat_ Mat1w; +typedef Mat_ Mat2w; +typedef Mat_ Mat3w; +typedef Mat_ Mat4w; + +typedef Mat_ Mat1i; +typedef Mat_ Mat2i; +typedef Mat_ Mat3i; +typedef Mat_ Mat4i; + +typedef Mat_ Mat1f; +typedef Mat_ Mat2f; +typedef Mat_ Mat3f; +typedef Mat_ Mat4f; + +typedef Mat_ Mat1d; +typedef Mat_ Mat2d; +typedef Mat_ Mat3d; +typedef Mat_ Mat4d; + +/** @todo document */ +class CV_EXPORTS UMat +{ +public: + //! default constructor + UMat(UMatUsageFlags usageFlags = USAGE_DEFAULT); + //! constructs 2D matrix of the specified size and type + // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.) + UMat(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + UMat(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + //! constucts 2D matrix and fills it with the specified value _s. + UMat(int rows, int cols, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT); + UMat(Size size, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT); + + //! constructs n-dimensional matrix + UMat(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + UMat(int ndims, const int* sizes, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT); + + //! copy constructor + UMat(const UMat& m); + + //! creates a matrix header for a part of the bigger matrix + UMat(const UMat& m, const Range& rowRange, const Range& colRange=Range::all()); + UMat(const UMat& m, const Rect& roi); + UMat(const UMat& m, const Range* ranges); + UMat(const UMat& m, const std::vector& ranges); + //! builds matrix from std::vector with or without copying the data + template explicit UMat(const std::vector<_Tp>& vec, bool copyData=false); + + //! builds matrix from cv::Vec; the data is copied by default + template explicit UMat(const Vec<_Tp, n>& vec, bool copyData=true); + //! builds matrix from cv::Matx; the data is copied by default + template explicit UMat(const Matx<_Tp, m, n>& mtx, bool copyData=true); + //! builds matrix from a 2D point + template explicit UMat(const Point_<_Tp>& pt, bool copyData=true); + //! builds matrix from a 3D point + template explicit UMat(const Point3_<_Tp>& pt, bool copyData=true); + //! builds matrix from comma initializer + template explicit UMat(const MatCommaInitializer_<_Tp>& commaInitializer); + + //! destructor - calls release() + ~UMat(); + //! assignment operators + UMat& operator = (const UMat& m); + + Mat getMat(int flags) const; + + //! returns a new matrix header for the specified row + UMat row(int y) const; + //! returns a new matrix header for the specified column + UMat col(int x) const; + //! ... for the specified row span + UMat rowRange(int startrow, int endrow) const; + UMat rowRange(const Range& r) const; + //! ... for the specified column span + UMat colRange(int startcol, int endcol) const; + UMat colRange(const Range& r) const; + //! ... for the specified diagonal + //! (d=0 - the main diagonal, + //! >0 - a diagonal from the upper half, + //! <0 - a diagonal from the lower half) + UMat diag(int d=0) const; + //! constructs a square diagonal matrix which main diagonal is vector "d" + static UMat diag(const UMat& d); + + //! returns deep copy of the matrix, i.e. the data is copied + UMat clone() const CV_NODISCARD; + //! copies the matrix content to "m". + // It calls m.create(this->size(), this->type()). + void copyTo( OutputArray m ) const; + //! copies those matrix elements to "m" that are marked with non-zero mask elements. + void copyTo( OutputArray m, InputArray mask ) const; + //! converts matrix to another datatype with optional scaling. See cvConvertScale. + void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const; + + void assignTo( UMat& m, int type=-1 ) const; + + //! sets every matrix element to s + UMat& operator = (const Scalar& s); + //! sets some of the matrix elements to s, according to the mask + UMat& setTo(InputArray value, InputArray mask=noArray()); + //! creates alternative matrix header for the same data, with different + // number of channels and/or different number of rows. see cvReshape. + UMat reshape(int cn, int rows=0) const; + UMat reshape(int cn, int newndims, const int* newsz) const; + + //! matrix transposition by means of matrix expressions + UMat t() const; + //! matrix inversion by means of matrix expressions + UMat inv(int method=DECOMP_LU) const; + //! per-element matrix multiplication by means of matrix expressions + UMat mul(InputArray m, double scale=1) const; + + //! computes dot-product + double dot(InputArray m) const; + + //! Matlab-style matrix initialization + static UMat zeros(int rows, int cols, int type); + static UMat zeros(Size size, int type); + static UMat zeros(int ndims, const int* sz, int type); + static UMat ones(int rows, int cols, int type); + static UMat ones(Size size, int type); + static UMat ones(int ndims, const int* sz, int type); + static UMat eye(int rows, int cols, int type); + static UMat eye(Size size, int type); + + //! allocates new matrix data unless the matrix already has specified size and type. + // previous data is unreferenced if needed. + void create(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + void create(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + void create(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + void create(const std::vector& sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT); + + //! increases the reference counter; use with care to avoid memleaks + void addref(); + //! decreases reference counter; + // deallocates the data when reference counter reaches 0. + void release(); + + //! deallocates the matrix data + void deallocate(); + //! internal use function; properly re-allocates _size, _step arrays + void copySize(const UMat& m); + + //! locates matrix header within a parent matrix. See below + void locateROI( Size& wholeSize, Point& ofs ) const; + //! moves/resizes the current matrix ROI inside the parent matrix. + UMat& adjustROI( int dtop, int dbottom, int dleft, int dright ); + //! extracts a rectangular sub-matrix + // (this is a generalized form of row, rowRange etc.) + UMat operator()( Range rowRange, Range colRange ) const; + UMat operator()( const Rect& roi ) const; + UMat operator()( const Range* ranges ) const; + UMat operator()(const std::vector& ranges) const; + + //! returns true iff the matrix data is continuous + // (i.e. when there are no gaps between successive rows). + // similar to CV_IS_MAT_CONT(cvmat->type) + bool isContinuous() const; + + //! returns true if the matrix is a submatrix of another matrix + bool isSubmatrix() const; + + //! returns element size in bytes, + // similar to CV_ELEM_SIZE(cvmat->type) + size_t elemSize() const; + //! returns the size of element channel in bytes. + size_t elemSize1() const; + //! returns element type, similar to CV_MAT_TYPE(cvmat->type) + int type() const; + //! returns element type, similar to CV_MAT_DEPTH(cvmat->type) + int depth() const; + //! returns element type, similar to CV_MAT_CN(cvmat->type) + int channels() const; + //! returns step/elemSize1() + size_t step1(int i=0) const; + //! returns true if matrix data is NULL + bool empty() const; + //! returns the total number of matrix elements + size_t total() const; + + //! returns N if the matrix is 1-channel (N x ptdim) or ptdim-channel (1 x N) or (N x 1); negative number otherwise + int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const; + +#ifdef CV_CXX_MOVE_SEMANTICS + UMat(UMat&& m); + UMat& operator = (UMat&& m); +#endif + + /*! Returns the OpenCL buffer handle on which UMat operates on. + The UMat instance should be kept alive during the use of the handle to prevent the buffer to be + returned to the OpenCV buffer pool. + */ + void* handle(int accessFlags) const; + void ndoffset(size_t* ofs) const; + + enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG }; + enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 }; + + /*! includes several bit-fields: + - the magic signature + - continuity flag + - depth + - number of channels + */ + int flags; + //! the matrix dimensionality, >= 2 + int dims; + //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions + int rows, cols; + + //! custom allocator + MatAllocator* allocator; + UMatUsageFlags usageFlags; // usage flags for allocator + //! and the standard allocator + static MatAllocator* getStdAllocator(); + + //! internal use method: updates the continuity flag + void updateContinuityFlag(); + + // black-box container of UMat data + UMatData* u; + + // offset of the submatrix (or 0) + size_t offset; + + MatSize size; + MatStep step; + +protected: +}; + + +/////////////////////////// multi-dimensional sparse matrix ////////////////////////// + +/** @brief The class SparseMat represents multi-dimensional sparse numerical arrays. + +Such a sparse array can store elements of any type that Mat can store. *Sparse* means that only +non-zero elements are stored (though, as a result of operations on a sparse matrix, some of its +stored elements can actually become 0. It is up to you to detect such elements and delete them +using SparseMat::erase ). The non-zero elements are stored in a hash table that grows when it is +filled so that the search time is O(1) in average (regardless of whether element is there or not). +Elements can be accessed using the following methods: +- Query operations (SparseMat::ptr and the higher-level SparseMat::ref, SparseMat::value and + SparseMat::find), for example: + @code + const int dims = 5; + int size[5] = {10, 10, 10, 10, 10}; + SparseMat sparse_mat(dims, size, CV_32F); + for(int i = 0; i < 1000; i++) + { + int idx[dims]; + for(int k = 0; k < dims; k++) + idx[k] = rand() % size[k]; + sparse_mat.ref(idx) += 1.f; + } + cout << "nnz = " << sparse_mat.nzcount() << endl; + @endcode +- Sparse matrix iterators. They are similar to MatIterator but different from NAryMatIterator. + That is, the iteration loop is familiar to STL users: + @code + // prints elements of a sparse floating-point matrix + // and the sum of elements. + SparseMatConstIterator_ + it = sparse_mat.begin(), + it_end = sparse_mat.end(); + double s = 0; + int dims = sparse_mat.dims(); + for(; it != it_end; ++it) + { + // print element indices and the element value + const SparseMat::Node* n = it.node(); + printf("("); + for(int i = 0; i < dims; i++) + printf("%d%s", n->idx[i], i < dims-1 ? ", " : ")"); + printf(": %g\n", it.value()); + s += *it; + } + printf("Element sum is %g\n", s); + @endcode + If you run this loop, you will notice that elements are not enumerated in a logical order + (lexicographical, and so on). They come in the same order as they are stored in the hash table + (semi-randomly). You may collect pointers to the nodes and sort them to get the proper ordering. + Note, however, that pointers to the nodes may become invalid when you add more elements to the + matrix. This may happen due to possible buffer reallocation. +- Combination of the above 2 methods when you need to process 2 or more sparse matrices + simultaneously. For example, this is how you can compute unnormalized cross-correlation of the 2 + floating-point sparse matrices: + @code + double cross_corr(const SparseMat& a, const SparseMat& b) + { + const SparseMat *_a = &a, *_b = &b; + // if b contains less elements than a, + // it is faster to iterate through b + if(_a->nzcount() > _b->nzcount()) + std::swap(_a, _b); + SparseMatConstIterator_ it = _a->begin(), + it_end = _a->end(); + double ccorr = 0; + for(; it != it_end; ++it) + { + // take the next element from the first matrix + float avalue = *it; + const Node* anode = it.node(); + // and try to find an element with the same index in the second matrix. + // since the hash value depends only on the element index, + // reuse the hash value stored in the node + float bvalue = _b->value(anode->idx,&anode->hashval); + ccorr += avalue*bvalue; + } + return ccorr; + } + @endcode + */ +class CV_EXPORTS SparseMat +{ +public: + typedef SparseMatIterator iterator; + typedef SparseMatConstIterator const_iterator; + + enum { MAGIC_VAL=0x42FD0000, MAX_DIM=32, HASH_SCALE=0x5bd1e995, HASH_BIT=0x80000000 }; + + //! the sparse matrix header + struct CV_EXPORTS Hdr + { + Hdr(int _dims, const int* _sizes, int _type); + void clear(); + int refcount; + int dims; + int valueOffset; + size_t nodeSize; + size_t nodeCount; + size_t freeList; + std::vector pool; + std::vector hashtab; + int size[MAX_DIM]; + }; + + //! sparse matrix node - element of a hash table + struct CV_EXPORTS Node + { + //! hash value + size_t hashval; + //! index of the next node in the same hash table entry + size_t next; + //! index of the matrix element + int idx[MAX_DIM]; + }; + + /** @brief Various SparseMat constructors. + */ + SparseMat(); + + /** @overload + @param dims Array dimensionality. + @param _sizes Sparce matrix size on all dementions. + @param _type Sparse matrix data type. + */ + SparseMat(int dims, const int* _sizes, int _type); + + /** @overload + @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted + to sparse representation. + */ + SparseMat(const SparseMat& m); + + /** @overload + @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted + to sparse representation. + */ + explicit SparseMat(const Mat& m); + + //! the destructor + ~SparseMat(); + + //! assignment operator. This is O(1) operation, i.e. no data is copied + SparseMat& operator = (const SparseMat& m); + //! equivalent to the corresponding constructor + SparseMat& operator = (const Mat& m); + + //! creates full copy of the matrix + SparseMat clone() const CV_NODISCARD; + + //! copies all the data to the destination matrix. All the previous content of m is erased + void copyTo( SparseMat& m ) const; + //! converts sparse matrix to dense matrix. + void copyTo( Mat& m ) const; + //! multiplies all the matrix elements by the specified scale factor alpha and converts the results to the specified data type + void convertTo( SparseMat& m, int rtype, double alpha=1 ) const; + //! converts sparse matrix to dense n-dim matrix with optional type conversion and scaling. + /*! + @param [out] m - output matrix; if it does not have a proper size or type before the operation, + it is reallocated + @param [in] rtype - desired output matrix type or, rather, the depth since the number of channels + are the same as the input has; if rtype is negative, the output matrix will have the + same type as the input. + @param [in] alpha - optional scale factor + @param [in] beta - optional delta added to the scaled values + */ + void convertTo( Mat& m, int rtype, double alpha=1, double beta=0 ) const; + + // not used now + void assignTo( SparseMat& m, int type=-1 ) const; + + //! reallocates sparse matrix. + /*! + If the matrix already had the proper size and type, + it is simply cleared with clear(), otherwise, + the old matrix is released (using release()) and the new one is allocated. + */ + void create(int dims, const int* _sizes, int _type); + //! sets all the sparse matrix elements to 0, which means clearing the hash table. + void clear(); + //! manually increments the reference counter to the header. + void addref(); + // decrements the header reference counter. When the counter reaches 0, the header and all the underlying data are deallocated. + void release(); + + //! converts sparse matrix to the old-style representation; all the elements are copied. + //operator CvSparseMat*() const; + //! returns the size of each element in bytes (not including the overhead - the space occupied by SparseMat::Node elements) + size_t elemSize() const; + //! returns elemSize()/channels() + size_t elemSize1() const; + + //! returns type of sparse matrix elements + int type() const; + //! returns the depth of sparse matrix elements + int depth() const; + //! returns the number of channels + int channels() const; + + //! returns the array of sizes, or NULL if the matrix is not allocated + const int* size() const; + //! returns the size of i-th matrix dimension (or 0) + int size(int i) const; + //! returns the matrix dimensionality + int dims() const; + //! returns the number of non-zero elements (=the number of hash table nodes) + size_t nzcount() const; + + //! computes the element hash value (1D case) + size_t hash(int i0) const; + //! computes the element hash value (2D case) + size_t hash(int i0, int i1) const; + //! computes the element hash value (3D case) + size_t hash(int i0, int i1, int i2) const; + //! computes the element hash value (nD case) + size_t hash(const int* idx) const; + + //!@{ + /*! + specialized variants for 1D, 2D, 3D cases and the generic_type one for n-D case. + return pointer to the matrix element. + - if the element is there (it's non-zero), the pointer to it is returned + - if it's not there and createMissing=false, NULL pointer is returned + - if it's not there and createMissing=true, then the new element + is created and initialized with 0. Pointer to it is returned + - if the optional hashval pointer is not NULL, the element hash value is + not computed, but *hashval is taken instead. + */ + //! returns pointer to the specified element (1D case) + uchar* ptr(int i0, bool createMissing, size_t* hashval=0); + //! returns pointer to the specified element (2D case) + uchar* ptr(int i0, int i1, bool createMissing, size_t* hashval=0); + //! returns pointer to the specified element (3D case) + uchar* ptr(int i0, int i1, int i2, bool createMissing, size_t* hashval=0); + //! returns pointer to the specified element (nD case) + uchar* ptr(const int* idx, bool createMissing, size_t* hashval=0); + //!@} + + //!@{ + /*! + return read-write reference to the specified sparse matrix element. + + `ref<_Tp>(i0,...[,hashval])` is equivalent to `*(_Tp*)ptr(i0,...,true[,hashval])`. + The methods always return a valid reference. + If the element did not exist, it is created and initialiazed with 0. + */ + //! returns reference to the specified element (1D case) + template _Tp& ref(int i0, size_t* hashval=0); + //! returns reference to the specified element (2D case) + template _Tp& ref(int i0, int i1, size_t* hashval=0); + //! returns reference to the specified element (3D case) + template _Tp& ref(int i0, int i1, int i2, size_t* hashval=0); + //! returns reference to the specified element (nD case) + template _Tp& ref(const int* idx, size_t* hashval=0); + //!@} + + //!@{ + /*! + return value of the specified sparse matrix element. + + `value<_Tp>(i0,...[,hashval])` is equivalent to + @code + { const _Tp* p = find<_Tp>(i0,...[,hashval]); return p ? *p : _Tp(); } + @endcode + + That is, if the element did not exist, the methods return 0. + */ + //! returns value of the specified element (1D case) + template _Tp value(int i0, size_t* hashval=0) const; + //! returns value of the specified element (2D case) + template _Tp value(int i0, int i1, size_t* hashval=0) const; + //! returns value of the specified element (3D case) + template _Tp value(int i0, int i1, int i2, size_t* hashval=0) const; + //! returns value of the specified element (nD case) + template _Tp value(const int* idx, size_t* hashval=0) const; + //!@} + + //!@{ + /*! + Return pointer to the specified sparse matrix element if it exists + + `find<_Tp>(i0,...[,hashval])` is equivalent to `(_const Tp*)ptr(i0,...false[,hashval])`. + + If the specified element does not exist, the methods return NULL. + */ + //! returns pointer to the specified element (1D case) + template const _Tp* find(int i0, size_t* hashval=0) const; + //! returns pointer to the specified element (2D case) + template const _Tp* find(int i0, int i1, size_t* hashval=0) const; + //! returns pointer to the specified element (3D case) + template const _Tp* find(int i0, int i1, int i2, size_t* hashval=0) const; + //! returns pointer to the specified element (nD case) + template const _Tp* find(const int* idx, size_t* hashval=0) const; + //!@} + + //! erases the specified element (2D case) + void erase(int i0, int i1, size_t* hashval=0); + //! erases the specified element (3D case) + void erase(int i0, int i1, int i2, size_t* hashval=0); + //! erases the specified element (nD case) + void erase(const int* idx, size_t* hashval=0); + + //!@{ + /*! + return the sparse matrix iterator pointing to the first sparse matrix element + */ + //! returns the sparse matrix iterator at the matrix beginning + SparseMatIterator begin(); + //! returns the sparse matrix iterator at the matrix beginning + template SparseMatIterator_<_Tp> begin(); + //! returns the read-only sparse matrix iterator at the matrix beginning + SparseMatConstIterator begin() const; + //! returns the read-only sparse matrix iterator at the matrix beginning + template SparseMatConstIterator_<_Tp> begin() const; + //!@} + /*! + return the sparse matrix iterator pointing to the element following the last sparse matrix element + */ + //! returns the sparse matrix iterator at the matrix end + SparseMatIterator end(); + //! returns the read-only sparse matrix iterator at the matrix end + SparseMatConstIterator end() const; + //! returns the typed sparse matrix iterator at the matrix end + template SparseMatIterator_<_Tp> end(); + //! returns the typed read-only sparse matrix iterator at the matrix end + template SparseMatConstIterator_<_Tp> end() const; + + //! returns the value stored in the sparse martix node + template _Tp& value(Node* n); + //! returns the value stored in the sparse martix node + template const _Tp& value(const Node* n) const; + + ////////////// some internal-use methods /////////////// + Node* node(size_t nidx); + const Node* node(size_t nidx) const; + + uchar* newNode(const int* idx, size_t hashval); + void removeNode(size_t hidx, size_t nidx, size_t previdx); + void resizeHashTab(size_t newsize); + + int flags; + Hdr* hdr; +}; + + + +///////////////////////////////// SparseMat_<_Tp> //////////////////////////////////// + +/** @brief Template sparse n-dimensional array class derived from SparseMat + +SparseMat_ is a thin wrapper on top of SparseMat created in the same way as Mat_ . It simplifies +notation of some operations: +@code + int sz[] = {10, 20, 30}; + SparseMat_ M(3, sz); + ... + M.ref(1, 2, 3) = M(4, 5, 6) + M(7, 8, 9); +@endcode + */ +template class SparseMat_ : public SparseMat +{ +public: + typedef SparseMatIterator_<_Tp> iterator; + typedef SparseMatConstIterator_<_Tp> const_iterator; + + //! the default constructor + SparseMat_(); + //! the full constructor equivalent to SparseMat(dims, _sizes, DataType<_Tp>::type) + SparseMat_(int dims, const int* _sizes); + //! the copy constructor. If DataType<_Tp>.type != m.type(), the m elements are converted + SparseMat_(const SparseMat& m); + //! the copy constructor. This is O(1) operation - no data is copied + SparseMat_(const SparseMat_& m); + //! converts dense matrix to the sparse form + SparseMat_(const Mat& m); + //! converts the old-style sparse matrix to the C++ class. All the elements are copied + //SparseMat_(const CvSparseMat* m); + //! the assignment operator. If DataType<_Tp>.type != m.type(), the m elements are converted + SparseMat_& operator = (const SparseMat& m); + //! the assignment operator. This is O(1) operation - no data is copied + SparseMat_& operator = (const SparseMat_& m); + //! converts dense matrix to the sparse form + SparseMat_& operator = (const Mat& m); + + //! makes full copy of the matrix. All the elements are duplicated + SparseMat_ clone() const CV_NODISCARD; + //! equivalent to cv::SparseMat::create(dims, _sizes, DataType<_Tp>::type) + void create(int dims, const int* _sizes); + //! converts sparse matrix to the old-style CvSparseMat. All the elements are copied + //operator CvSparseMat*() const; + + //! returns type of the matrix elements + int type() const; + //! returns depth of the matrix elements + int depth() const; + //! returns the number of channels in each matrix element + int channels() const; + + //! equivalent to SparseMat::ref<_Tp>(i0, hashval) + _Tp& ref(int i0, size_t* hashval=0); + //! equivalent to SparseMat::ref<_Tp>(i0, i1, hashval) + _Tp& ref(int i0, int i1, size_t* hashval=0); + //! equivalent to SparseMat::ref<_Tp>(i0, i1, i2, hashval) + _Tp& ref(int i0, int i1, int i2, size_t* hashval=0); + //! equivalent to SparseMat::ref<_Tp>(idx, hashval) + _Tp& ref(const int* idx, size_t* hashval=0); + + //! equivalent to SparseMat::value<_Tp>(i0, hashval) + _Tp operator()(int i0, size_t* hashval=0) const; + //! equivalent to SparseMat::value<_Tp>(i0, i1, hashval) + _Tp operator()(int i0, int i1, size_t* hashval=0) const; + //! equivalent to SparseMat::value<_Tp>(i0, i1, i2, hashval) + _Tp operator()(int i0, int i1, int i2, size_t* hashval=0) const; + //! equivalent to SparseMat::value<_Tp>(idx, hashval) + _Tp operator()(const int* idx, size_t* hashval=0) const; + + //! returns sparse matrix iterator pointing to the first sparse matrix element + SparseMatIterator_<_Tp> begin(); + //! returns read-only sparse matrix iterator pointing to the first sparse matrix element + SparseMatConstIterator_<_Tp> begin() const; + //! returns sparse matrix iterator pointing to the element following the last sparse matrix element + SparseMatIterator_<_Tp> end(); + //! returns read-only sparse matrix iterator pointing to the element following the last sparse matrix element + SparseMatConstIterator_<_Tp> end() const; +}; + + + +////////////////////////////////// MatConstIterator ////////////////////////////////// + +class CV_EXPORTS MatConstIterator +{ +public: + typedef uchar* value_type; + typedef ptrdiff_t difference_type; + typedef const uchar** pointer; + typedef uchar* reference; + + typedef std::random_access_iterator_tag iterator_category; + + //! default constructor + MatConstIterator(); + //! constructor that sets the iterator to the beginning of the matrix + MatConstIterator(const Mat* _m); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator(const Mat* _m, int _row, int _col=0); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator(const Mat* _m, Point _pt); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator(const Mat* _m, const int* _idx); + //! copy constructor + MatConstIterator(const MatConstIterator& it); + + //! copy operator + MatConstIterator& operator = (const MatConstIterator& it); + //! returns the current matrix element + const uchar* operator *() const; + //! returns the i-th matrix element, relative to the current + const uchar* operator [](ptrdiff_t i) const; + + //! shifts the iterator forward by the specified number of elements + MatConstIterator& operator += (ptrdiff_t ofs); + //! shifts the iterator backward by the specified number of elements + MatConstIterator& operator -= (ptrdiff_t ofs); + //! decrements the iterator + MatConstIterator& operator --(); + //! decrements the iterator + MatConstIterator operator --(int); + //! increments the iterator + MatConstIterator& operator ++(); + //! increments the iterator + MatConstIterator operator ++(int); + //! returns the current iterator position + Point pos() const; + //! returns the current iterator position + void pos(int* _idx) const; + + ptrdiff_t lpos() const; + void seek(ptrdiff_t ofs, bool relative = false); + void seek(const int* _idx, bool relative = false); + + const Mat* m; + size_t elemSize; + const uchar* ptr; + const uchar* sliceStart; + const uchar* sliceEnd; +}; + + + +////////////////////////////////// MatConstIterator_ ///////////////////////////////// + +/** @brief Matrix read-only iterator + */ +template +class MatConstIterator_ : public MatConstIterator +{ +public: + typedef _Tp value_type; + typedef ptrdiff_t difference_type; + typedef const _Tp* pointer; + typedef const _Tp& reference; + + typedef std::random_access_iterator_tag iterator_category; + + //! default constructor + MatConstIterator_(); + //! constructor that sets the iterator to the beginning of the matrix + MatConstIterator_(const Mat_<_Tp>* _m); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator_(const Mat_<_Tp>* _m, int _row, int _col=0); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator_(const Mat_<_Tp>* _m, Point _pt); + //! constructor that sets the iterator to the specified element of the matrix + MatConstIterator_(const Mat_<_Tp>* _m, const int* _idx); + //! copy constructor + MatConstIterator_(const MatConstIterator_& it); + + //! copy operator + MatConstIterator_& operator = (const MatConstIterator_& it); + //! returns the current matrix element + const _Tp& operator *() const; + //! returns the i-th matrix element, relative to the current + const _Tp& operator [](ptrdiff_t i) const; + + //! shifts the iterator forward by the specified number of elements + MatConstIterator_& operator += (ptrdiff_t ofs); + //! shifts the iterator backward by the specified number of elements + MatConstIterator_& operator -= (ptrdiff_t ofs); + //! decrements the iterator + MatConstIterator_& operator --(); + //! decrements the iterator + MatConstIterator_ operator --(int); + //! increments the iterator + MatConstIterator_& operator ++(); + //! increments the iterator + MatConstIterator_ operator ++(int); + //! returns the current iterator position + Point pos() const; +}; + + + +//////////////////////////////////// MatIterator_ //////////////////////////////////// + +/** @brief Matrix read-write iterator +*/ +template +class MatIterator_ : public MatConstIterator_<_Tp> +{ +public: + typedef _Tp* pointer; + typedef _Tp& reference; + + typedef std::random_access_iterator_tag iterator_category; + + //! the default constructor + MatIterator_(); + //! constructor that sets the iterator to the beginning of the matrix + MatIterator_(Mat_<_Tp>* _m); + //! constructor that sets the iterator to the specified element of the matrix + MatIterator_(Mat_<_Tp>* _m, int _row, int _col=0); + //! constructor that sets the iterator to the specified element of the matrix + MatIterator_(Mat_<_Tp>* _m, Point _pt); + //! constructor that sets the iterator to the specified element of the matrix + MatIterator_(Mat_<_Tp>* _m, const int* _idx); + //! copy constructor + MatIterator_(const MatIterator_& it); + //! copy operator + MatIterator_& operator = (const MatIterator_<_Tp>& it ); + + //! returns the current matrix element + _Tp& operator *() const; + //! returns the i-th matrix element, relative to the current + _Tp& operator [](ptrdiff_t i) const; + + //! shifts the iterator forward by the specified number of elements + MatIterator_& operator += (ptrdiff_t ofs); + //! shifts the iterator backward by the specified number of elements + MatIterator_& operator -= (ptrdiff_t ofs); + //! decrements the iterator + MatIterator_& operator --(); + //! decrements the iterator + MatIterator_ operator --(int); + //! increments the iterator + MatIterator_& operator ++(); + //! increments the iterator + MatIterator_ operator ++(int); +}; + + + +/////////////////////////////// SparseMatConstIterator /////////////////////////////// + +/** @brief Read-Only Sparse Matrix Iterator. + + Here is how to use the iterator to compute the sum of floating-point sparse matrix elements: + + \code + SparseMatConstIterator it = m.begin(), it_end = m.end(); + double s = 0; + CV_Assert( m.type() == CV_32F ); + for( ; it != it_end; ++it ) + s += it.value(); + \endcode +*/ +class CV_EXPORTS SparseMatConstIterator +{ +public: + //! the default constructor + SparseMatConstIterator(); + //! the full constructor setting the iterator to the first sparse matrix element + SparseMatConstIterator(const SparseMat* _m); + //! the copy constructor + SparseMatConstIterator(const SparseMatConstIterator& it); + + //! the assignment operator + SparseMatConstIterator& operator = (const SparseMatConstIterator& it); + + //! template method returning the current matrix element + template const _Tp& value() const; + //! returns the current node of the sparse matrix. it.node->idx is the current element index + const SparseMat::Node* node() const; + + //! moves iterator to the previous element + SparseMatConstIterator& operator --(); + //! moves iterator to the previous element + SparseMatConstIterator operator --(int); + //! moves iterator to the next element + SparseMatConstIterator& operator ++(); + //! moves iterator to the next element + SparseMatConstIterator operator ++(int); + + //! moves iterator to the element after the last element + void seekEnd(); + + const SparseMat* m; + size_t hashidx; + uchar* ptr; +}; + + + +////////////////////////////////// SparseMatIterator ///////////////////////////////// + +/** @brief Read-write Sparse Matrix Iterator + + The class is similar to cv::SparseMatConstIterator, + but can be used for in-place modification of the matrix elements. +*/ +class CV_EXPORTS SparseMatIterator : public SparseMatConstIterator +{ +public: + //! the default constructor + SparseMatIterator(); + //! the full constructor setting the iterator to the first sparse matrix element + SparseMatIterator(SparseMat* _m); + //! the full constructor setting the iterator to the specified sparse matrix element + SparseMatIterator(SparseMat* _m, const int* idx); + //! the copy constructor + SparseMatIterator(const SparseMatIterator& it); + + //! the assignment operator + SparseMatIterator& operator = (const SparseMatIterator& it); + //! returns read-write reference to the current sparse matrix element + template _Tp& value() const; + //! returns pointer to the current sparse matrix node. it.node->idx is the index of the current element (do not modify it!) + SparseMat::Node* node() const; + + //! moves iterator to the next element + SparseMatIterator& operator ++(); + //! moves iterator to the next element + SparseMatIterator operator ++(int); +}; + + + +/////////////////////////////// SparseMatConstIterator_ ////////////////////////////// + +/** @brief Template Read-Only Sparse Matrix Iterator Class. + + This is the derived from SparseMatConstIterator class that + introduces more convenient operator *() for accessing the current element. +*/ +template class SparseMatConstIterator_ : public SparseMatConstIterator +{ +public: + + typedef std::forward_iterator_tag iterator_category; + + //! the default constructor + SparseMatConstIterator_(); + //! the full constructor setting the iterator to the first sparse matrix element + SparseMatConstIterator_(const SparseMat_<_Tp>* _m); + SparseMatConstIterator_(const SparseMat* _m); + //! the copy constructor + SparseMatConstIterator_(const SparseMatConstIterator_& it); + + //! the assignment operator + SparseMatConstIterator_& operator = (const SparseMatConstIterator_& it); + //! the element access operator + const _Tp& operator *() const; + + //! moves iterator to the next element + SparseMatConstIterator_& operator ++(); + //! moves iterator to the next element + SparseMatConstIterator_ operator ++(int); +}; + + + +///////////////////////////////// SparseMatIterator_ ///////////////////////////////// + +/** @brief Template Read-Write Sparse Matrix Iterator Class. + + This is the derived from cv::SparseMatConstIterator_ class that + introduces more convenient operator *() for accessing the current element. +*/ +template class SparseMatIterator_ : public SparseMatConstIterator_<_Tp> +{ +public: + + typedef std::forward_iterator_tag iterator_category; + + //! the default constructor + SparseMatIterator_(); + //! the full constructor setting the iterator to the first sparse matrix element + SparseMatIterator_(SparseMat_<_Tp>* _m); + SparseMatIterator_(SparseMat* _m); + //! the copy constructor + SparseMatIterator_(const SparseMatIterator_& it); + + //! the assignment operator + SparseMatIterator_& operator = (const SparseMatIterator_& it); + //! returns the reference to the current element + _Tp& operator *() const; + + //! moves the iterator to the next element + SparseMatIterator_& operator ++(); + //! moves the iterator to the next element + SparseMatIterator_ operator ++(int); +}; + + + +/////////////////////////////////// NAryMatIterator ////////////////////////////////// + +/** @brief n-ary multi-dimensional array iterator. + +Use the class to implement unary, binary, and, generally, n-ary element-wise operations on +multi-dimensional arrays. Some of the arguments of an n-ary function may be continuous arrays, some +may be not. It is possible to use conventional MatIterator 's for each array but incrementing all of +the iterators after each small operations may be a big overhead. In this case consider using +NAryMatIterator to iterate through several matrices simultaneously as long as they have the same +geometry (dimensionality and all the dimension sizes are the same). On each iteration `it.planes[0]`, +`it.planes[1]`,... will be the slices of the corresponding matrices. + +The example below illustrates how you can compute a normalized and threshold 3D color histogram: +@code + void computeNormalizedColorHist(const Mat& image, Mat& hist, int N, double minProb) + { + const int histSize[] = {N, N, N}; + + // make sure that the histogram has a proper size and type + hist.create(3, histSize, CV_32F); + + // and clear it + hist = Scalar(0); + + // the loop below assumes that the image + // is a 8-bit 3-channel. check it. + CV_Assert(image.type() == CV_8UC3); + MatConstIterator_ it = image.begin(), + it_end = image.end(); + for( ; it != it_end; ++it ) + { + const Vec3b& pix = *it; + hist.at(pix[0]*N/256, pix[1]*N/256, pix[2]*N/256) += 1.f; + } + + minProb *= image.rows*image.cols; + + // initialize iterator (the style is different from STL). + // after initialization the iterator will contain + // the number of slices or planes the iterator will go through. + // it simultaneously increments iterators for several matrices + // supplied as a null terminated list of pointers + const Mat* arrays[] = {&hist, 0}; + Mat planes[1]; + NAryMatIterator itNAry(arrays, planes, 1); + double s = 0; + // iterate through the matrix. on each iteration + // itNAry.planes[i] (of type Mat) will be set to the current plane + // of the i-th n-dim matrix passed to the iterator constructor. + for(int p = 0; p < itNAry.nplanes; p++, ++itNAry) + { + threshold(itNAry.planes[0], itNAry.planes[0], minProb, 0, THRESH_TOZERO); + s += sum(itNAry.planes[0])[0]; + } + + s = 1./s; + itNAry = NAryMatIterator(arrays, planes, 1); + for(int p = 0; p < itNAry.nplanes; p++, ++itNAry) + itNAry.planes[0] *= s; + } +@endcode + */ +class CV_EXPORTS NAryMatIterator +{ +public: + //! the default constructor + NAryMatIterator(); + //! the full constructor taking arbitrary number of n-dim matrices + NAryMatIterator(const Mat** arrays, uchar** ptrs, int narrays=-1); + //! the full constructor taking arbitrary number of n-dim matrices + NAryMatIterator(const Mat** arrays, Mat* planes, int narrays=-1); + //! the separate iterator initialization method + void init(const Mat** arrays, Mat* planes, uchar** ptrs, int narrays=-1); + + //! proceeds to the next plane of every iterated matrix + NAryMatIterator& operator ++(); + //! proceeds to the next plane of every iterated matrix (postfix increment operator) + NAryMatIterator operator ++(int); + + //! the iterated arrays + const Mat** arrays; + //! the current planes + Mat* planes; + //! data pointers + uchar** ptrs; + //! the number of arrays + int narrays; + //! the number of hyper-planes that the iterator steps through + size_t nplanes; + //! the size of each segment (in elements) + size_t size; +protected: + int iterdepth; + size_t idx; +}; + + + +///////////////////////////////// Matrix Expressions ///////////////////////////////// + +class CV_EXPORTS MatOp +{ +public: + MatOp(); + virtual ~MatOp(); + + virtual bool elementWise(const MatExpr& expr) const; + virtual void assign(const MatExpr& expr, Mat& m, int type=-1) const = 0; + virtual void roi(const MatExpr& expr, const Range& rowRange, + const Range& colRange, MatExpr& res) const; + virtual void diag(const MatExpr& expr, int d, MatExpr& res) const; + virtual void augAssignAdd(const MatExpr& expr, Mat& m) const; + virtual void augAssignSubtract(const MatExpr& expr, Mat& m) const; + virtual void augAssignMultiply(const MatExpr& expr, Mat& m) const; + virtual void augAssignDivide(const MatExpr& expr, Mat& m) const; + virtual void augAssignAnd(const MatExpr& expr, Mat& m) const; + virtual void augAssignOr(const MatExpr& expr, Mat& m) const; + virtual void augAssignXor(const MatExpr& expr, Mat& m) const; + + virtual void add(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const; + virtual void add(const MatExpr& expr1, const Scalar& s, MatExpr& res) const; + + virtual void subtract(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const; + virtual void subtract(const Scalar& s, const MatExpr& expr, MatExpr& res) const; + + virtual void multiply(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const; + virtual void multiply(const MatExpr& expr1, double s, MatExpr& res) const; + + virtual void divide(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const; + virtual void divide(double s, const MatExpr& expr, MatExpr& res) const; + + virtual void abs(const MatExpr& expr, MatExpr& res) const; + + virtual void transpose(const MatExpr& expr, MatExpr& res) const; + virtual void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const; + virtual void invert(const MatExpr& expr, int method, MatExpr& res) const; + + virtual Size size(const MatExpr& expr) const; + virtual int type(const MatExpr& expr) const; +}; + +/** @brief Matrix expression representation +@anchor MatrixExpressions +This is a list of implemented matrix operations that can be combined in arbitrary complex +expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a +real-valued scalar ( double )): +- Addition, subtraction, negation: `A+B`, `A-B`, `A+s`, `A-s`, `s+A`, `s-A`, `-A` +- Scaling: `A*alpha` +- Per-element multiplication and division: `A.mul(B)`, `A/B`, `alpha/A` +- Matrix multiplication: `A*B` +- Transposition: `A.t()` (means AT) +- Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems: + `A.inv([method]) (~ A-1)`, `A.inv([method])*B (~ X: AX=B)` +- Comparison: `A cmpop B`, `A cmpop alpha`, `alpha cmpop A`, where *cmpop* is one of + `>`, `>=`, `==`, `!=`, `<=`, `<`. The result of comparison is an 8-bit single channel mask whose + elements are set to 255 (if the particular element or pair of elements satisfy the condition) or + 0. +- Bitwise logical operations: `A logicop B`, `A logicop s`, `s logicop A`, `~A`, where *logicop* is one of + `&`, `|`, `^`. +- Element-wise minimum and maximum: `min(A, B)`, `min(A, alpha)`, `max(A, B)`, `max(A, alpha)` +- Element-wise absolute value: `abs(A)` +- Cross-product, dot-product: `A.cross(B)`, `A.dot(B)` +- Any function of matrix or matrices and scalars that returns a matrix or a scalar, such as norm, + mean, sum, countNonZero, trace, determinant, repeat, and others. +- Matrix initializers ( Mat::eye(), Mat::zeros(), Mat::ones() ), matrix comma-separated + initializers, matrix constructors and operators that extract sub-matrices (see Mat description). +- Mat_() constructors to cast the result to the proper type. +@note Comma-separated initializers and probably some other operations may require additional +explicit Mat() or Mat_() constructor calls to resolve a possible ambiguity. + +Here are examples of matrix expressions: +@code + // compute pseudo-inverse of A, equivalent to A.inv(DECOMP_SVD) + SVD svd(A); + Mat pinvA = svd.vt.t()*Mat::diag(1./svd.w)*svd.u.t(); + + // compute the new vector of parameters in the Levenberg-Marquardt algorithm + x -= (A.t()*A + lambda*Mat::eye(A.cols,A.cols,A.type())).inv(DECOMP_CHOLESKY)*(A.t()*err); + + // sharpen image using "unsharp mask" algorithm + Mat blurred; double sigma = 1, threshold = 5, amount = 1; + GaussianBlur(img, blurred, Size(), sigma, sigma); + Mat lowContrastMask = abs(img - blurred) < threshold; + Mat sharpened = img*(1+amount) + blurred*(-amount); + img.copyTo(sharpened, lowContrastMask); +@endcode +*/ +class CV_EXPORTS MatExpr +{ +public: + MatExpr(); + explicit MatExpr(const Mat& m); + + MatExpr(const MatOp* _op, int _flags, const Mat& _a = Mat(), const Mat& _b = Mat(), + const Mat& _c = Mat(), double _alpha = 1, double _beta = 1, const Scalar& _s = Scalar()); + + operator Mat() const; + template operator Mat_<_Tp>() const; + + Size size() const; + int type() const; + + MatExpr row(int y) const; + MatExpr col(int x) const; + MatExpr diag(int d = 0) const; + MatExpr operator()( const Range& rowRange, const Range& colRange ) const; + MatExpr operator()( const Rect& roi ) const; + + MatExpr t() const; + MatExpr inv(int method = DECOMP_LU) const; + MatExpr mul(const MatExpr& e, double scale=1) const; + MatExpr mul(const Mat& m, double scale=1) const; + + Mat cross(const Mat& m) const; + double dot(const Mat& m) const; + + const MatOp* op; + int flags; + + Mat a, b, c; + double alpha, beta; + Scalar s; +}; + +//! @} core_basic + +//! @relates cv::MatExpr +//! @{ +CV_EXPORTS MatExpr operator + (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator + (const Mat& a, const Scalar& s); +CV_EXPORTS MatExpr operator + (const Scalar& s, const Mat& a); +CV_EXPORTS MatExpr operator + (const MatExpr& e, const Mat& m); +CV_EXPORTS MatExpr operator + (const Mat& m, const MatExpr& e); +CV_EXPORTS MatExpr operator + (const MatExpr& e, const Scalar& s); +CV_EXPORTS MatExpr operator + (const Scalar& s, const MatExpr& e); +CV_EXPORTS MatExpr operator + (const MatExpr& e1, const MatExpr& e2); +template static inline +MatExpr operator + (const Mat& a, const Matx<_Tp, m, n>& b) { return a + Mat(b); } +template static inline +MatExpr operator + (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) + b; } + +CV_EXPORTS MatExpr operator - (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator - (const Mat& a, const Scalar& s); +CV_EXPORTS MatExpr operator - (const Scalar& s, const Mat& a); +CV_EXPORTS MatExpr operator - (const MatExpr& e, const Mat& m); +CV_EXPORTS MatExpr operator - (const Mat& m, const MatExpr& e); +CV_EXPORTS MatExpr operator - (const MatExpr& e, const Scalar& s); +CV_EXPORTS MatExpr operator - (const Scalar& s, const MatExpr& e); +CV_EXPORTS MatExpr operator - (const MatExpr& e1, const MatExpr& e2); +template static inline +MatExpr operator - (const Mat& a, const Matx<_Tp, m, n>& b) { return a - Mat(b); } +template static inline +MatExpr operator - (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) - b; } + +CV_EXPORTS MatExpr operator - (const Mat& m); +CV_EXPORTS MatExpr operator - (const MatExpr& e); + +CV_EXPORTS MatExpr operator * (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator * (const Mat& a, double s); +CV_EXPORTS MatExpr operator * (double s, const Mat& a); +CV_EXPORTS MatExpr operator * (const MatExpr& e, const Mat& m); +CV_EXPORTS MatExpr operator * (const Mat& m, const MatExpr& e); +CV_EXPORTS MatExpr operator * (const MatExpr& e, double s); +CV_EXPORTS MatExpr operator * (double s, const MatExpr& e); +CV_EXPORTS MatExpr operator * (const MatExpr& e1, const MatExpr& e2); +template static inline +MatExpr operator * (const Mat& a, const Matx<_Tp, m, n>& b) { return a * Mat(b); } +template static inline +MatExpr operator * (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) * b; } + +CV_EXPORTS MatExpr operator / (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator / (const Mat& a, double s); +CV_EXPORTS MatExpr operator / (double s, const Mat& a); +CV_EXPORTS MatExpr operator / (const MatExpr& e, const Mat& m); +CV_EXPORTS MatExpr operator / (const Mat& m, const MatExpr& e); +CV_EXPORTS MatExpr operator / (const MatExpr& e, double s); +CV_EXPORTS MatExpr operator / (double s, const MatExpr& e); +CV_EXPORTS MatExpr operator / (const MatExpr& e1, const MatExpr& e2); +template static inline +MatExpr operator / (const Mat& a, const Matx<_Tp, m, n>& b) { return a / Mat(b); } +template static inline +MatExpr operator / (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) / b; } + +CV_EXPORTS MatExpr operator < (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator < (const Mat& a, double s); +CV_EXPORTS MatExpr operator < (double s, const Mat& a); +template static inline +MatExpr operator < (const Mat& a, const Matx<_Tp, m, n>& b) { return a < Mat(b); } +template static inline +MatExpr operator < (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) < b; } + +CV_EXPORTS MatExpr operator <= (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator <= (const Mat& a, double s); +CV_EXPORTS MatExpr operator <= (double s, const Mat& a); +template static inline +MatExpr operator <= (const Mat& a, const Matx<_Tp, m, n>& b) { return a <= Mat(b); } +template static inline +MatExpr operator <= (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) <= b; } + +CV_EXPORTS MatExpr operator == (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator == (const Mat& a, double s); +CV_EXPORTS MatExpr operator == (double s, const Mat& a); +template static inline +MatExpr operator == (const Mat& a, const Matx<_Tp, m, n>& b) { return a == Mat(b); } +template static inline +MatExpr operator == (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) == b; } + +CV_EXPORTS MatExpr operator != (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator != (const Mat& a, double s); +CV_EXPORTS MatExpr operator != (double s, const Mat& a); +template static inline +MatExpr operator != (const Mat& a, const Matx<_Tp, m, n>& b) { return a != Mat(b); } +template static inline +MatExpr operator != (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) != b; } + +CV_EXPORTS MatExpr operator >= (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator >= (const Mat& a, double s); +CV_EXPORTS MatExpr operator >= (double s, const Mat& a); +template static inline +MatExpr operator >= (const Mat& a, const Matx<_Tp, m, n>& b) { return a >= Mat(b); } +template static inline +MatExpr operator >= (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) >= b; } + +CV_EXPORTS MatExpr operator > (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator > (const Mat& a, double s); +CV_EXPORTS MatExpr operator > (double s, const Mat& a); +template static inline +MatExpr operator > (const Mat& a, const Matx<_Tp, m, n>& b) { return a > Mat(b); } +template static inline +MatExpr operator > (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) > b; } + +CV_EXPORTS MatExpr operator & (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator & (const Mat& a, const Scalar& s); +CV_EXPORTS MatExpr operator & (const Scalar& s, const Mat& a); +template static inline +MatExpr operator & (const Mat& a, const Matx<_Tp, m, n>& b) { return a & Mat(b); } +template static inline +MatExpr operator & (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) & b; } + +CV_EXPORTS MatExpr operator | (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator | (const Mat& a, const Scalar& s); +CV_EXPORTS MatExpr operator | (const Scalar& s, const Mat& a); +template static inline +MatExpr operator | (const Mat& a, const Matx<_Tp, m, n>& b) { return a | Mat(b); } +template static inline +MatExpr operator | (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) | b; } + +CV_EXPORTS MatExpr operator ^ (const Mat& a, const Mat& b); +CV_EXPORTS MatExpr operator ^ (const Mat& a, const Scalar& s); +CV_EXPORTS MatExpr operator ^ (const Scalar& s, const Mat& a); +template static inline +MatExpr operator ^ (const Mat& a, const Matx<_Tp, m, n>& b) { return a ^ Mat(b); } +template static inline +MatExpr operator ^ (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) ^ b; } + +CV_EXPORTS MatExpr operator ~(const Mat& m); + +CV_EXPORTS MatExpr min(const Mat& a, const Mat& b); +CV_EXPORTS MatExpr min(const Mat& a, double s); +CV_EXPORTS MatExpr min(double s, const Mat& a); +template static inline +MatExpr min (const Mat& a, const Matx<_Tp, m, n>& b) { return min(a, Mat(b)); } +template static inline +MatExpr min (const Matx<_Tp, m, n>& a, const Mat& b) { return min(Mat(a), b); } + +CV_EXPORTS MatExpr max(const Mat& a, const Mat& b); +CV_EXPORTS MatExpr max(const Mat& a, double s); +CV_EXPORTS MatExpr max(double s, const Mat& a); +template static inline +MatExpr max (const Mat& a, const Matx<_Tp, m, n>& b) { return max(a, Mat(b)); } +template static inline +MatExpr max (const Matx<_Tp, m, n>& a, const Mat& b) { return max(Mat(a), b); } + +/** @brief Calculates an absolute value of each matrix element. + +abs is a meta-function that is expanded to one of absdiff or convertScaleAbs forms: +- C = abs(A-B) is equivalent to `absdiff(A, B, C)` +- C = abs(A) is equivalent to `absdiff(A, Scalar::all(0), C)` +- C = `Mat_ >(abs(A*alpha + beta))` is equivalent to `convertScaleAbs(A, C, alpha, +beta)` + +The output matrix has the same size and the same type as the input one except for the last case, +where C is depth=CV_8U . +@param m matrix. +@sa @ref MatrixExpressions, absdiff, convertScaleAbs + */ +CV_EXPORTS MatExpr abs(const Mat& m); +/** @overload +@param e matrix expression. +*/ +CV_EXPORTS MatExpr abs(const MatExpr& e); +//! @} relates cv::MatExpr + +} // cv + +#include "opencv2/core/mat.inl.hpp" + +#endif // OPENCV_CORE_MAT_HPP diff --git a/3rdparty/opencv/include/opencv2/core/mat.inl.hpp b/3rdparty/opencv/include/opencv2/core/mat.inl.hpp new file mode 100644 index 00000000..a2e7923b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/mat.inl.hpp @@ -0,0 +1,4027 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_MATRIX_OPERATIONS_HPP +#define OPENCV_CORE_MATRIX_OPERATIONS_HPP + +#ifndef __cplusplus +# error mat.inl.hpp header must be compiled as C++ +#endif + +#ifdef _MSC_VER +#pragma warning( push ) +#pragma warning( disable: 4127 ) +#endif + +namespace cv +{ +CV__DEBUG_NS_BEGIN + + +//! @cond IGNORED + +////////////////////////// Custom (raw) type wrapper ////////////////////////// + +template static inline +int rawType() +{ + CV_StaticAssert(sizeof(_Tp) <= CV_CN_MAX, "sizeof(_Tp) is too large"); + const int elemSize = sizeof(_Tp); + return (int)CV_MAKETYPE(CV_8U, elemSize); +} + +//////////////////////// Input/Output Arrays //////////////////////// + +inline void _InputArray::init(int _flags, const void* _obj) +{ flags = _flags; obj = (void*)_obj; } + +inline void _InputArray::init(int _flags, const void* _obj, Size _sz) +{ flags = _flags; obj = (void*)_obj; sz = _sz; } + +inline void* _InputArray::getObj() const { return obj; } +inline int _InputArray::getFlags() const { return flags; } +inline Size _InputArray::getSz() const { return sz; } + +inline _InputArray::_InputArray() { init(NONE, 0); } +inline _InputArray::_InputArray(int _flags, void* _obj) { init(_flags, _obj); } +inline _InputArray::_InputArray(const Mat& m) { init(MAT+ACCESS_READ, &m); } +inline _InputArray::_InputArray(const std::vector& vec) { init(STD_VECTOR_MAT+ACCESS_READ, &vec); } +inline _InputArray::_InputArray(const UMat& m) { init(UMAT+ACCESS_READ, &m); } +inline _InputArray::_InputArray(const std::vector& vec) { init(STD_VECTOR_UMAT+ACCESS_READ, &vec); } + +template inline +_InputArray::_InputArray(const std::vector<_Tp>& vec) +{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_READ, &vec); } + +#ifdef CV_CXX_STD_ARRAY +template inline +_InputArray::_InputArray(const std::array<_Tp, _Nm>& arr) +{ init(FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_READ, arr.data(), Size(1, _Nm)); } + +template inline +_InputArray::_InputArray(const std::array& arr) +{ init(STD_ARRAY_MAT + ACCESS_READ, arr.data(), Size(1, _Nm)); } +#endif + +inline +_InputArray::_InputArray(const std::vector& vec) +{ init(FIXED_TYPE + STD_BOOL_VECTOR + traits::Type::value + ACCESS_READ, &vec); } + +template inline +_InputArray::_InputArray(const std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_READ, &vec); } + +inline +_InputArray::_InputArray(const std::vector >&) +{ CV_Error(Error::StsUnsupportedFormat, "std::vector > is not supported!\n"); } + +template inline +_InputArray::_InputArray(const std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_READ, &vec); } + +template inline +_InputArray::_InputArray(const Matx<_Tp, m, n>& mtx) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ, &mtx, Size(n, m)); } + +template inline +_InputArray::_InputArray(const _Tp* vec, int n) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ, vec, Size(n, 1)); } + +template inline +_InputArray::_InputArray(const Mat_<_Tp>& m) +{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_READ, &m); } + +inline _InputArray::_InputArray(const double& val) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + CV_64F + ACCESS_READ, &val, Size(1,1)); } + +inline _InputArray::_InputArray(const MatExpr& expr) +{ init(FIXED_TYPE + FIXED_SIZE + EXPR + ACCESS_READ, &expr); } + +inline _InputArray::_InputArray(const cuda::GpuMat& d_mat) +{ init(CUDA_GPU_MAT + ACCESS_READ, &d_mat); } + +inline _InputArray::_InputArray(const std::vector& d_mat) +{ init(STD_VECTOR_CUDA_GPU_MAT + ACCESS_READ, &d_mat);} + +inline _InputArray::_InputArray(const ogl::Buffer& buf) +{ init(OPENGL_BUFFER + ACCESS_READ, &buf); } + +inline _InputArray::_InputArray(const cuda::HostMem& cuda_mem) +{ init(CUDA_HOST_MEM + ACCESS_READ, &cuda_mem); } + +template inline +_InputArray _InputArray::rawIn(const std::vector<_Tp>& vec) +{ + _InputArray v; + v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_READ; + v.obj = (void*)&vec; + return v; +} + +#ifdef CV_CXX_STD_ARRAY +template inline +_InputArray _InputArray::rawIn(const std::array<_Tp, _Nm>& arr) +{ + _InputArray v; + v.flags = FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_READ; + v.obj = (void*)arr.data(); + v.sz = Size(1, _Nm); + return v; +} +#endif + +inline _InputArray::~_InputArray() {} + +inline Mat _InputArray::getMat(int i) const +{ + if( kind() == MAT && i < 0 ) + return *(const Mat*)obj; + return getMat_(i); +} + +inline bool _InputArray::isMat() const { return kind() == _InputArray::MAT; } +inline bool _InputArray::isUMat() const { return kind() == _InputArray::UMAT; } +inline bool _InputArray::isMatVector() const { return kind() == _InputArray::STD_VECTOR_MAT; } +inline bool _InputArray::isUMatVector() const { return kind() == _InputArray::STD_VECTOR_UMAT; } +inline bool _InputArray::isMatx() const { return kind() == _InputArray::MATX; } +inline bool _InputArray::isVector() const { return kind() == _InputArray::STD_VECTOR || + kind() == _InputArray::STD_BOOL_VECTOR || + kind() == _InputArray::STD_ARRAY; } +inline bool _InputArray::isGpuMat() const { return kind() == _InputArray::CUDA_GPU_MAT; } +inline bool _InputArray::isGpuMatVector() const { return kind() == _InputArray::STD_VECTOR_CUDA_GPU_MAT; } + +//////////////////////////////////////////////////////////////////////////////////////// + +inline _OutputArray::_OutputArray() { init(ACCESS_WRITE, 0); } +inline _OutputArray::_OutputArray(int _flags, void* _obj) { init(_flags|ACCESS_WRITE, _obj); } +inline _OutputArray::_OutputArray(Mat& m) { init(MAT+ACCESS_WRITE, &m); } +inline _OutputArray::_OutputArray(std::vector& vec) { init(STD_VECTOR_MAT+ACCESS_WRITE, &vec); } +inline _OutputArray::_OutputArray(UMat& m) { init(UMAT+ACCESS_WRITE, &m); } +inline _OutputArray::_OutputArray(std::vector& vec) { init(STD_VECTOR_UMAT+ACCESS_WRITE, &vec); } + +template inline +_OutputArray::_OutputArray(std::vector<_Tp>& vec) +{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +#ifdef CV_CXX_STD_ARRAY +template inline +_OutputArray::_OutputArray(std::array<_Tp, _Nm>& arr) +{ init(FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_WRITE, arr.data(), Size(1, _Nm)); } + +template inline +_OutputArray::_OutputArray(std::array& arr) +{ init(STD_ARRAY_MAT + ACCESS_WRITE, arr.data(), Size(1, _Nm)); } +#endif + +inline +_OutputArray::_OutputArray(std::vector&) +{ CV_Error(Error::StsUnsupportedFormat, "std::vector cannot be an output array\n"); } + +template inline +_OutputArray::_OutputArray(std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +inline +_OutputArray::_OutputArray(std::vector >&) +{ CV_Error(Error::StsUnsupportedFormat, "std::vector > cannot be an output array\n"); } + +template inline +_OutputArray::_OutputArray(std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +template inline +_OutputArray::_OutputArray(Mat_<_Tp>& m) +{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &m); } + +template inline +_OutputArray::_OutputArray(Matx<_Tp, m, n>& mtx) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, &mtx, Size(n, m)); } + +template inline +_OutputArray::_OutputArray(_Tp* vec, int n) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, vec, Size(n, 1)); } + +template inline +_OutputArray::_OutputArray(const std::vector<_Tp>& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +#ifdef CV_CXX_STD_ARRAY +template inline +_OutputArray::_OutputArray(const std::array<_Tp, _Nm>& arr) +{ init(FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_WRITE, arr.data(), Size(1, _Nm)); } + +template inline +_OutputArray::_OutputArray(const std::array& arr) +{ init(FIXED_SIZE + STD_ARRAY_MAT + ACCESS_WRITE, arr.data(), Size(1, _Nm)); } +#endif + +template inline +_OutputArray::_OutputArray(const std::vector >& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +template inline +_OutputArray::_OutputArray(const std::vector >& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); } + +template inline +_OutputArray::_OutputArray(const Mat_<_Tp>& m) +{ init(FIXED_TYPE + FIXED_SIZE + MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &m); } + +template inline +_OutputArray::_OutputArray(const Matx<_Tp, m, n>& mtx) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, &mtx, Size(n, m)); } + +template inline +_OutputArray::_OutputArray(const _Tp* vec, int n) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, vec, Size(n, 1)); } + +inline _OutputArray::_OutputArray(cuda::GpuMat& d_mat) +{ init(CUDA_GPU_MAT + ACCESS_WRITE, &d_mat); } + +inline _OutputArray::_OutputArray(std::vector& d_mat) +{ init(STD_VECTOR_CUDA_GPU_MAT + ACCESS_WRITE, &d_mat);} + +inline _OutputArray::_OutputArray(ogl::Buffer& buf) +{ init(OPENGL_BUFFER + ACCESS_WRITE, &buf); } + +inline _OutputArray::_OutputArray(cuda::HostMem& cuda_mem) +{ init(CUDA_HOST_MEM + ACCESS_WRITE, &cuda_mem); } + +inline _OutputArray::_OutputArray(const Mat& m) +{ init(FIXED_TYPE + FIXED_SIZE + MAT + ACCESS_WRITE, &m); } + +inline _OutputArray::_OutputArray(const std::vector& vec) +{ init(FIXED_SIZE + STD_VECTOR_MAT + ACCESS_WRITE, &vec); } + +inline _OutputArray::_OutputArray(const UMat& m) +{ init(FIXED_TYPE + FIXED_SIZE + UMAT + ACCESS_WRITE, &m); } + +inline _OutputArray::_OutputArray(const std::vector& vec) +{ init(FIXED_SIZE + STD_VECTOR_UMAT + ACCESS_WRITE, &vec); } + +inline _OutputArray::_OutputArray(const cuda::GpuMat& d_mat) +{ init(FIXED_TYPE + FIXED_SIZE + CUDA_GPU_MAT + ACCESS_WRITE, &d_mat); } + + +inline _OutputArray::_OutputArray(const ogl::Buffer& buf) +{ init(FIXED_TYPE + FIXED_SIZE + OPENGL_BUFFER + ACCESS_WRITE, &buf); } + +inline _OutputArray::_OutputArray(const cuda::HostMem& cuda_mem) +{ init(FIXED_TYPE + FIXED_SIZE + CUDA_HOST_MEM + ACCESS_WRITE, &cuda_mem); } + +template inline +_OutputArray _OutputArray::rawOut(std::vector<_Tp>& vec) +{ + _OutputArray v; + v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_WRITE; + v.obj = (void*)&vec; + return v; +} + +#ifdef CV_CXX_STD_ARRAY +template inline +_OutputArray _OutputArray::rawOut(std::array<_Tp, _Nm>& arr) +{ + _OutputArray v; + v.flags = FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_WRITE; + v.obj = (void*)arr.data(); + v.sz = Size(1, _Nm); + return v; +} +#endif + +/////////////////////////////////////////////////////////////////////////////////////////// + +inline _InputOutputArray::_InputOutputArray() { init(ACCESS_RW, 0); } +inline _InputOutputArray::_InputOutputArray(int _flags, void* _obj) { init(_flags|ACCESS_RW, _obj); } +inline _InputOutputArray::_InputOutputArray(Mat& m) { init(MAT+ACCESS_RW, &m); } +inline _InputOutputArray::_InputOutputArray(std::vector& vec) { init(STD_VECTOR_MAT+ACCESS_RW, &vec); } +inline _InputOutputArray::_InputOutputArray(UMat& m) { init(UMAT+ACCESS_RW, &m); } +inline _InputOutputArray::_InputOutputArray(std::vector& vec) { init(STD_VECTOR_UMAT+ACCESS_RW, &vec); } + +template inline +_InputOutputArray::_InputOutputArray(std::vector<_Tp>& vec) +{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +#ifdef CV_CXX_STD_ARRAY +template inline +_InputOutputArray::_InputOutputArray(std::array<_Tp, _Nm>& arr) +{ init(FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_RW, arr.data(), Size(1, _Nm)); } + +template inline +_InputOutputArray::_InputOutputArray(std::array& arr) +{ init(STD_ARRAY_MAT + ACCESS_RW, arr.data(), Size(1, _Nm)); } +#endif + +inline _InputOutputArray::_InputOutputArray(std::vector&) +{ CV_Error(Error::StsUnsupportedFormat, "std::vector cannot be an input/output array\n"); } + +template inline +_InputOutputArray::_InputOutputArray(std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +template inline +_InputOutputArray::_InputOutputArray(std::vector >& vec) +{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +template inline +_InputOutputArray::_InputOutputArray(Mat_<_Tp>& m) +{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_RW, &m); } + +template inline +_InputOutputArray::_InputOutputArray(Matx<_Tp, m, n>& mtx) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, &mtx, Size(n, m)); } + +template inline +_InputOutputArray::_InputOutputArray(_Tp* vec, int n) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, vec, Size(n, 1)); } + +template inline +_InputOutputArray::_InputOutputArray(const std::vector<_Tp>& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +#ifdef CV_CXX_STD_ARRAY +template inline +_InputOutputArray::_InputOutputArray(const std::array<_Tp, _Nm>& arr) +{ init(FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_RW, arr.data(), Size(1, _Nm)); } + +template inline +_InputOutputArray::_InputOutputArray(const std::array& arr) +{ init(FIXED_SIZE + STD_ARRAY_MAT + ACCESS_RW, arr.data(), Size(1, _Nm)); } +#endif + +template inline +_InputOutputArray::_InputOutputArray(const std::vector >& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +template inline +_InputOutputArray::_InputOutputArray(const std::vector >& vec) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_RW, &vec); } + +template inline +_InputOutputArray::_InputOutputArray(const Mat_<_Tp>& m) +{ init(FIXED_TYPE + FIXED_SIZE + MAT + traits::Type<_Tp>::value + ACCESS_RW, &m); } + +template inline +_InputOutputArray::_InputOutputArray(const Matx<_Tp, m, n>& mtx) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, &mtx, Size(n, m)); } + +template inline +_InputOutputArray::_InputOutputArray(const _Tp* vec, int n) +{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, vec, Size(n, 1)); } + +inline _InputOutputArray::_InputOutputArray(cuda::GpuMat& d_mat) +{ init(CUDA_GPU_MAT + ACCESS_RW, &d_mat); } + +inline _InputOutputArray::_InputOutputArray(ogl::Buffer& buf) +{ init(OPENGL_BUFFER + ACCESS_RW, &buf); } + +inline _InputOutputArray::_InputOutputArray(cuda::HostMem& cuda_mem) +{ init(CUDA_HOST_MEM + ACCESS_RW, &cuda_mem); } + +inline _InputOutputArray::_InputOutputArray(const Mat& m) +{ init(FIXED_TYPE + FIXED_SIZE + MAT + ACCESS_RW, &m); } + +inline _InputOutputArray::_InputOutputArray(const std::vector& vec) +{ init(FIXED_SIZE + STD_VECTOR_MAT + ACCESS_RW, &vec); } + +inline _InputOutputArray::_InputOutputArray(const UMat& m) +{ init(FIXED_TYPE + FIXED_SIZE + UMAT + ACCESS_RW, &m); } + +inline _InputOutputArray::_InputOutputArray(const std::vector& vec) +{ init(FIXED_SIZE + STD_VECTOR_UMAT + ACCESS_RW, &vec); } + +inline _InputOutputArray::_InputOutputArray(const cuda::GpuMat& d_mat) +{ init(FIXED_TYPE + FIXED_SIZE + CUDA_GPU_MAT + ACCESS_RW, &d_mat); } + +inline _InputOutputArray::_InputOutputArray(const std::vector& d_mat) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_CUDA_GPU_MAT + ACCESS_RW, &d_mat);} + +template<> inline _InputOutputArray::_InputOutputArray(std::vector& d_mat) +{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_CUDA_GPU_MAT + ACCESS_RW, &d_mat);} + +inline _InputOutputArray::_InputOutputArray(const ogl::Buffer& buf) +{ init(FIXED_TYPE + FIXED_SIZE + OPENGL_BUFFER + ACCESS_RW, &buf); } + +inline _InputOutputArray::_InputOutputArray(const cuda::HostMem& cuda_mem) +{ init(FIXED_TYPE + FIXED_SIZE + CUDA_HOST_MEM + ACCESS_RW, &cuda_mem); } + +template inline +_InputOutputArray _InputOutputArray::rawInOut(std::vector<_Tp>& vec) +{ + _InputOutputArray v; + v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_RW; + v.obj = (void*)&vec; + return v; +} + +#ifdef CV_CXX_STD_ARRAY +template inline +_InputOutputArray _InputOutputArray::rawInOut(std::array<_Tp, _Nm>& arr) +{ + _InputOutputArray v; + v.flags = FIXED_TYPE + FIXED_SIZE + STD_ARRAY + traits::Type<_Tp>::value + ACCESS_RW; + v.obj = (void*)arr.data(); + v.sz = Size(1, _Nm); + return v; +} +#endif + + +template static inline _InputArray rawIn(_Tp& v) { return _InputArray::rawIn(v); } +template static inline _OutputArray rawOut(_Tp& v) { return _OutputArray::rawOut(v); } +template static inline _InputOutputArray rawInOut(_Tp& v) { return _InputOutputArray::rawInOut(v); } + +CV__DEBUG_NS_END + +//////////////////////////////////////////// Mat ////////////////////////////////////////// + +inline +Mat::Mat() + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{} + +inline +Mat::Mat(int _rows, int _cols, int _type) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_rows, _cols, _type); +} + +inline +Mat::Mat(int _rows, int _cols, int _type, const Scalar& _s) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_rows, _cols, _type); + *this = _s; +} + +inline +Mat::Mat(Size _sz, int _type) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create( _sz.height, _sz.width, _type ); +} + +inline +Mat::Mat(Size _sz, int _type, const Scalar& _s) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_sz.height, _sz.width, _type); + *this = _s; +} + +inline +Mat::Mat(int _dims, const int* _sz, int _type) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_dims, _sz, _type); +} + +inline +Mat::Mat(int _dims, const int* _sz, int _type, const Scalar& _s) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_dims, _sz, _type); + *this = _s; +} + +inline +Mat::Mat(const std::vector& _sz, int _type) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_sz, _type); +} + +inline +Mat::Mat(const std::vector& _sz, int _type, const Scalar& _s) + : flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), + datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + create(_sz, _type); + *this = _s; +} + +inline +Mat::Mat(const Mat& m) + : flags(m.flags), dims(m.dims), rows(m.rows), cols(m.cols), data(m.data), + datastart(m.datastart), dataend(m.dataend), datalimit(m.datalimit), allocator(m.allocator), + u(m.u), size(&rows), step(0) +{ + if( u ) + CV_XADD(&u->refcount, 1); + if( m.dims <= 2 ) + { + step[0] = m.step[0]; step[1] = m.step[1]; + } + else + { + dims = 0; + copySize(m); + } +} + +inline +Mat::Mat(int _rows, int _cols, int _type, void* _data, size_t _step) + : flags(MAGIC_VAL + (_type & TYPE_MASK)), dims(2), rows(_rows), cols(_cols), + data((uchar*)_data), datastart((uchar*)_data), dataend(0), datalimit(0), + allocator(0), u(0), size(&rows) +{ + CV_Assert(total() == 0 || data != NULL); + + size_t esz = CV_ELEM_SIZE(_type), esz1 = CV_ELEM_SIZE1(_type); + size_t minstep = cols * esz; + if( _step == AUTO_STEP ) + { + _step = minstep; + } + else + { + CV_DbgAssert( _step >= minstep ); + if (_step % esz1 != 0) + { + CV_Error(Error::BadStep, "Step must be a multiple of esz1"); + } + } + step[0] = _step; + step[1] = esz; + datalimit = datastart + _step * rows; + dataend = datalimit - _step + minstep; + updateContinuityFlag(); +} + +inline +Mat::Mat(Size _sz, int _type, void* _data, size_t _step) + : flags(MAGIC_VAL + (_type & TYPE_MASK)), dims(2), rows(_sz.height), cols(_sz.width), + data((uchar*)_data), datastart((uchar*)_data), dataend(0), datalimit(0), + allocator(0), u(0), size(&rows) +{ + CV_Assert(total() == 0 || data != NULL); + + size_t esz = CV_ELEM_SIZE(_type), esz1 = CV_ELEM_SIZE1(_type); + size_t minstep = cols*esz; + if( _step == AUTO_STEP ) + { + _step = minstep; + } + else + { + CV_DbgAssert( _step >= minstep ); + + if (_step % esz1 != 0) + { + CV_Error(Error::BadStep, "Step must be a multiple of esz1"); + } + } + step[0] = _step; + step[1] = esz; + datalimit = datastart + _step*rows; + dataend = datalimit - _step + minstep; + updateContinuityFlag(); +} + +template inline +Mat::Mat(const std::vector<_Tp>& vec, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()), + cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if(vec.empty()) + return; + if( !copyData ) + { + step[0] = step[1] = sizeof(_Tp); + datastart = data = (uchar*)&vec[0]; + datalimit = dataend = datastart + rows * step[0]; + } + else + Mat((int)vec.size(), 1, traits::Type<_Tp>::value, (uchar*)&vec[0]).copyTo(*this); +} + +#ifdef CV_CXX11 +template inline +Mat::Mat(const std::initializer_list<_Tp> list) + : Mat() +{ + CV_Assert(list.size() != 0); + Mat((int)list.size(), 1, traits::Type<_Tp>::value, (uchar*)list.begin()).copyTo(*this); +} + +template inline +Mat::Mat(const std::initializer_list sizes, const std::initializer_list<_Tp> list) + : Mat() +{ + size_t size_total = 1; + for(auto s : sizes) + size_total *= s; + CV_Assert(list.size() != 0); + CV_Assert(size_total == list.size()); + Mat((int)sizes.size(), (int*)sizes.begin(), traits::Type<_Tp>::value, (uchar*)list.begin()).copyTo(*this); +} +#endif + +#ifdef CV_CXX_STD_ARRAY +template inline +Mat::Mat(const std::array<_Tp, _Nm>& arr, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)arr.size()), + cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if(arr.empty()) + return; + if( !copyData ) + { + step[0] = step[1] = sizeof(_Tp); + datastart = data = (uchar*)arr.data(); + datalimit = dataend = datastart + rows * step[0]; + } + else + Mat((int)arr.size(), 1, traits::Type<_Tp>::value, (uchar*)arr.data()).copyTo(*this); +} +#endif + +template inline +Mat::Mat(const Vec<_Tp, n>& vec, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(n), cols(1), data(0), + datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if( !copyData ) + { + step[0] = step[1] = sizeof(_Tp); + datastart = data = (uchar*)vec.val; + datalimit = dataend = datastart + rows * step[0]; + } + else + Mat(n, 1, traits::Type<_Tp>::value, (void*)vec.val).copyTo(*this); +} + + +template inline +Mat::Mat(const Matx<_Tp,m,n>& M, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(m), cols(n), data(0), + datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if( !copyData ) + { + step[0] = cols * sizeof(_Tp); + step[1] = sizeof(_Tp); + datastart = data = (uchar*)M.val; + datalimit = dataend = datastart + rows * step[0]; + } + else + Mat(m, n, traits::Type<_Tp>::value, (uchar*)M.val).copyTo(*this); +} + +template inline +Mat::Mat(const Point_<_Tp>& pt, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(2), cols(1), data(0), + datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if( !copyData ) + { + step[0] = step[1] = sizeof(_Tp); + datastart = data = (uchar*)&pt.x; + datalimit = dataend = datastart + rows * step[0]; + } + else + { + create(2, 1, traits::Type<_Tp>::value); + ((_Tp*)data)[0] = pt.x; + ((_Tp*)data)[1] = pt.y; + } +} + +template inline +Mat::Mat(const Point3_<_Tp>& pt, bool copyData) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows(3), cols(1), data(0), + datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0) +{ + if( !copyData ) + { + step[0] = step[1] = sizeof(_Tp); + datastart = data = (uchar*)&pt.x; + datalimit = dataend = datastart + rows * step[0]; + } + else + { + create(3, 1, traits::Type<_Tp>::value); + ((_Tp*)data)[0] = pt.x; + ((_Tp*)data)[1] = pt.y; + ((_Tp*)data)[2] = pt.z; + } +} + +template inline +Mat::Mat(const MatCommaInitializer_<_Tp>& commaInitializer) + : flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(0), rows(0), cols(0), data(0), + datastart(0), dataend(0), allocator(0), u(0), size(&rows) +{ + *this = commaInitializer.operator Mat_<_Tp>(); +} + +inline +Mat::~Mat() +{ + release(); + if( step.p != step.buf ) + fastFree(step.p); +} + +inline +Mat& Mat::operator = (const Mat& m) +{ + if( this != &m ) + { + if( m.u ) + CV_XADD(&m.u->refcount, 1); + release(); + flags = m.flags; + if( dims <= 2 && m.dims <= 2 ) + { + dims = m.dims; + rows = m.rows; + cols = m.cols; + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + copySize(m); + data = m.data; + datastart = m.datastart; + dataend = m.dataend; + datalimit = m.datalimit; + allocator = m.allocator; + u = m.u; + } + return *this; +} + +inline +Mat Mat::row(int y) const +{ + return Mat(*this, Range(y, y + 1), Range::all()); +} + +inline +Mat Mat::col(int x) const +{ + return Mat(*this, Range::all(), Range(x, x + 1)); +} + +inline +Mat Mat::rowRange(int startrow, int endrow) const +{ + return Mat(*this, Range(startrow, endrow), Range::all()); +} + +inline +Mat Mat::rowRange(const Range& r) const +{ + return Mat(*this, r, Range::all()); +} + +inline +Mat Mat::colRange(int startcol, int endcol) const +{ + return Mat(*this, Range::all(), Range(startcol, endcol)); +} + +inline +Mat Mat::colRange(const Range& r) const +{ + return Mat(*this, Range::all(), r); +} + +inline +Mat Mat::clone() const +{ + Mat m; + copyTo(m); + return m; +} + +inline +void Mat::assignTo( Mat& m, int _type ) const +{ + if( _type < 0 ) + m = *this; + else + convertTo(m, _type); +} + +inline +void Mat::create(int _rows, int _cols, int _type) +{ + _type &= TYPE_MASK; + if( dims <= 2 && rows == _rows && cols == _cols && type() == _type && data ) + return; + int sz[] = {_rows, _cols}; + create(2, sz, _type); +} + +inline +void Mat::create(Size _sz, int _type) +{ + create(_sz.height, _sz.width, _type); +} + +inline +void Mat::addref() +{ + if( u ) + CV_XADD(&u->refcount, 1); +} + +inline +void Mat::release() +{ + if( u && CV_XADD(&u->refcount, -1) == 1 ) + deallocate(); + u = NULL; + datastart = dataend = datalimit = data = 0; + for(int i = 0; i < dims; i++) + size.p[i] = 0; +#ifdef _DEBUG + flags = MAGIC_VAL; + dims = rows = cols = 0; + if(step.p != step.buf) + { + fastFree(step.p); + step.p = step.buf; + size.p = &rows; + } +#endif +} + +inline +Mat Mat::operator()( Range _rowRange, Range _colRange ) const +{ + return Mat(*this, _rowRange, _colRange); +} + +inline +Mat Mat::operator()( const Rect& roi ) const +{ + return Mat(*this, roi); +} + +inline +Mat Mat::operator()(const Range* ranges) const +{ + return Mat(*this, ranges); +} + +inline +Mat Mat::operator()(const std::vector& ranges) const +{ + return Mat(*this, ranges); +} + +inline +bool Mat::isContinuous() const +{ + return (flags & CONTINUOUS_FLAG) != 0; +} + +inline +bool Mat::isSubmatrix() const +{ + return (flags & SUBMATRIX_FLAG) != 0; +} + +inline +size_t Mat::elemSize() const +{ + size_t res = dims > 0 ? step.p[dims - 1] : 0; + CV_DbgAssert(res != 0); + return res; +} + +inline +size_t Mat::elemSize1() const +{ + return CV_ELEM_SIZE1(flags); +} + +inline +int Mat::type() const +{ + return CV_MAT_TYPE(flags); +} + +inline +int Mat::depth() const +{ + return CV_MAT_DEPTH(flags); +} + +inline +int Mat::channels() const +{ + return CV_MAT_CN(flags); +} + +inline +size_t Mat::step1(int i) const +{ + return step.p[i] / elemSize1(); +} + +inline +bool Mat::empty() const +{ + return data == 0 || total() == 0 || dims == 0; +} + +inline +size_t Mat::total() const +{ + if( dims <= 2 ) + return (size_t)rows * cols; + size_t p = 1; + for( int i = 0; i < dims; i++ ) + p *= size[i]; + return p; +} + +inline +size_t Mat::total(int startDim, int endDim) const +{ + CV_Assert( 0 <= startDim && startDim <= endDim); + size_t p = 1; + int endDim_ = endDim <= dims ? endDim : dims; + for( int i = startDim; i < endDim_; i++ ) + p *= size[i]; + return p; +} + +inline +uchar* Mat::ptr(int y) +{ + CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) ); + return data + step.p[0] * y; +} + +inline +const uchar* Mat::ptr(int y) const +{ + CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) ); + return data + step.p[0] * y; +} + +template inline +_Tp* Mat::ptr(int y) +{ + CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) ); + return (_Tp*)(data + step.p[0] * y); +} + +template inline +const _Tp* Mat::ptr(int y) const +{ + CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) ); + return (const _Tp*)(data + step.p[0] * y); +} + +inline +uchar* Mat::ptr(int i0, int i1) +{ + CV_DbgAssert(dims >= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + return data + i0 * step.p[0] + i1 * step.p[1]; +} + +inline +const uchar* Mat::ptr(int i0, int i1) const +{ + CV_DbgAssert(dims >= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + return data + i0 * step.p[0] + i1 * step.p[1]; +} + +template inline +_Tp* Mat::ptr(int i0, int i1) +{ + CV_DbgAssert(dims >= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + return (_Tp*)(data + i0 * step.p[0] + i1 * step.p[1]); +} + +template inline +const _Tp* Mat::ptr(int i0, int i1) const +{ + CV_DbgAssert(dims >= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + return (const _Tp*)(data + i0 * step.p[0] + i1 * step.p[1]); +} + +inline +uchar* Mat::ptr(int i0, int i1, int i2) +{ + CV_DbgAssert(dims >= 3); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]); + return data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]; +} + +inline +const uchar* Mat::ptr(int i0, int i1, int i2) const +{ + CV_DbgAssert(dims >= 3); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]); + return data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]; +} + +template inline +_Tp* Mat::ptr(int i0, int i1, int i2) +{ + CV_DbgAssert(dims >= 3); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]); + return (_Tp*)(data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]); +} + +template inline +const _Tp* Mat::ptr(int i0, int i1, int i2) const +{ + CV_DbgAssert(dims >= 3); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]); + return (const _Tp*)(data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]); +} + +inline +uchar* Mat::ptr(const int* idx) +{ + int i, d = dims; + uchar* p = data; + CV_DbgAssert( d >= 1 && p ); + for( i = 0; i < d; i++ ) + { + CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] ); + p += idx[i] * step.p[i]; + } + return p; +} + +inline +const uchar* Mat::ptr(const int* idx) const +{ + int i, d = dims; + uchar* p = data; + CV_DbgAssert( d >= 1 && p ); + for( i = 0; i < d; i++ ) + { + CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] ); + p += idx[i] * step.p[i]; + } + return p; +} + +template inline +_Tp* Mat::ptr(const int* idx) +{ + int i, d = dims; + uchar* p = data; + CV_DbgAssert( d >= 1 && p ); + for( i = 0; i < d; i++ ) + { + CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] ); + p += idx[i] * step.p[i]; + } + return (_Tp*)p; +} + +template inline +const _Tp* Mat::ptr(const int* idx) const +{ + int i, d = dims; + uchar* p = data; + CV_DbgAssert( d >= 1 && p ); + for( i = 0; i < d; i++ ) + { + CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] ); + p += idx[i] * step.p[i]; + } + return (const _Tp*)p; +} + +template inline +_Tp& Mat::at(int i0, int i1) +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)(i1 * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels())); + CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1()); + return ((_Tp*)(data + step.p[0] * i0))[i1]; +} + +template inline +const _Tp& Mat::at(int i0, int i1) const +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)(i1 * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels())); + CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1()); + return ((const _Tp*)(data + step.p[0] * i0))[i1]; +} + +template inline +_Tp& Mat::at(Point pt) +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)(pt.x * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels())); + CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1()); + return ((_Tp*)(data + step.p[0] * pt.y))[pt.x]; +} + +template inline +const _Tp& Mat::at(Point pt) const +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)(pt.x * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels())); + CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1()); + return ((const _Tp*)(data + step.p[0] * pt.y))[pt.x]; +} + +template inline +_Tp& Mat::at(int i0) +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)(size.p[0] * size.p[1])); + CV_DbgAssert(elemSize() == sizeof(_Tp)); + if( isContinuous() || size.p[0] == 1 ) + return ((_Tp*)data)[i0]; + if( size.p[1] == 1 ) + return *(_Tp*)(data + step.p[0] * i0); + int i = i0 / cols, j = i0 - i * cols; + return ((_Tp*)(data + step.p[0] * i))[j]; +} + +template inline +const _Tp& Mat::at(int i0) const +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)(size.p[0] * size.p[1])); + CV_DbgAssert(elemSize() == sizeof(_Tp)); + if( isContinuous() || size.p[0] == 1 ) + return ((const _Tp*)data)[i0]; + if( size.p[1] == 1 ) + return *(const _Tp*)(data + step.p[0] * i0); + int i = i0 / cols, j = i0 - i * cols; + return ((const _Tp*)(data + step.p[0] * i))[j]; +} + +template inline +_Tp& Mat::at(int i0, int i1, int i2) +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(_Tp*)ptr(i0, i1, i2); +} + +template inline +const _Tp& Mat::at(int i0, int i1, int i2) const +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(const _Tp*)ptr(i0, i1, i2); +} + +template inline +_Tp& Mat::at(const int* idx) +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(_Tp*)ptr(idx); +} + +template inline +const _Tp& Mat::at(const int* idx) const +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(const _Tp*)ptr(idx); +} + +template inline +_Tp& Mat::at(const Vec& idx) +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(_Tp*)ptr(idx.val); +} + +template inline +const _Tp& Mat::at(const Vec& idx) const +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return *(const _Tp*)ptr(idx.val); +} + +template inline +MatConstIterator_<_Tp> Mat::begin() const +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return MatConstIterator_<_Tp>((const Mat_<_Tp>*)this); +} + +template inline +MatConstIterator_<_Tp> Mat::end() const +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + MatConstIterator_<_Tp> it((const Mat_<_Tp>*)this); + it += total(); + return it; +} + +template inline +MatIterator_<_Tp> Mat::begin() +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + return MatIterator_<_Tp>((Mat_<_Tp>*)this); +} + +template inline +MatIterator_<_Tp> Mat::end() +{ + CV_DbgAssert( elemSize() == sizeof(_Tp) ); + MatIterator_<_Tp> it((Mat_<_Tp>*)this); + it += total(); + return it; +} + +template inline +void Mat::forEach(const Functor& operation) { + this->forEach_impl<_Tp>(operation); +} + +template inline +void Mat::forEach(const Functor& operation) const { + // call as not const + (const_cast(this))->forEach<_Tp>(operation); +} + +template inline +Mat::operator std::vector<_Tp>() const +{ + std::vector<_Tp> v; + copyTo(v); + return v; +} + +#ifdef CV_CXX_STD_ARRAY +template inline +Mat::operator std::array<_Tp, _Nm>() const +{ + std::array<_Tp, _Nm> v; + copyTo(v); + return v; +} +#endif + +template inline +Mat::operator Vec<_Tp, n>() const +{ + CV_Assert( data && dims <= 2 && (rows == 1 || cols == 1) && + rows + cols - 1 == n && channels() == 1 ); + + if( isContinuous() && type() == traits::Type<_Tp>::value ) + return Vec<_Tp, n>((_Tp*)data); + Vec<_Tp, n> v; + Mat tmp(rows, cols, traits::Type<_Tp>::value, v.val); + convertTo(tmp, tmp.type()); + return v; +} + +template inline +Mat::operator Matx<_Tp, m, n>() const +{ + CV_Assert( data && dims <= 2 && rows == m && cols == n && channels() == 1 ); + + if( isContinuous() && type() == traits::Type<_Tp>::value ) + return Matx<_Tp, m, n>((_Tp*)data); + Matx<_Tp, m, n> mtx; + Mat tmp(rows, cols, traits::Type<_Tp>::value, mtx.val); + convertTo(tmp, tmp.type()); + return mtx; +} + +template inline +void Mat::push_back(const _Tp& elem) +{ + if( !data ) + { + *this = Mat(1, 1, traits::Type<_Tp>::value, (void*)&elem).clone(); + return; + } + CV_Assert(traits::Type<_Tp>::value == type() && cols == 1 + /* && dims == 2 (cols == 1 implies dims == 2) */); + const uchar* tmp = dataend + step[0]; + if( !isSubmatrix() && isContinuous() && tmp <= datalimit ) + { + *(_Tp*)(data + (size.p[0]++) * step.p[0]) = elem; + dataend = tmp; + } + else + push_back_(&elem); +} + +template inline +void Mat::push_back(const Mat_<_Tp>& m) +{ + push_back((const Mat&)m); +} + +template<> inline +void Mat::push_back(const MatExpr& expr) +{ + push_back(static_cast(expr)); +} + + +template inline +void Mat::push_back(const std::vector<_Tp>& v) +{ + push_back(Mat(v)); +} + +#ifdef CV_CXX_MOVE_SEMANTICS + +inline +Mat::Mat(Mat&& m) + : flags(m.flags), dims(m.dims), rows(m.rows), cols(m.cols), data(m.data), + datastart(m.datastart), dataend(m.dataend), datalimit(m.datalimit), allocator(m.allocator), + u(m.u), size(&rows) +{ + if (m.dims <= 2) // move new step/size info + { + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + { + CV_DbgAssert(m.step.p != m.step.buf); + step.p = m.step.p; + size.p = m.size.p; + m.step.p = m.step.buf; + m.size.p = &m.rows; + } + m.flags = MAGIC_VAL; m.dims = m.rows = m.cols = 0; + m.data = NULL; m.datastart = NULL; m.dataend = NULL; m.datalimit = NULL; + m.allocator = NULL; + m.u = NULL; +} + +inline +Mat& Mat::operator = (Mat&& m) +{ + if (this == &m) + return *this; + + release(); + flags = m.flags; dims = m.dims; rows = m.rows; cols = m.cols; data = m.data; + datastart = m.datastart; dataend = m.dataend; datalimit = m.datalimit; allocator = m.allocator; + u = m.u; + if (step.p != step.buf) // release self step/size + { + fastFree(step.p); + step.p = step.buf; + size.p = &rows; + } + if (m.dims <= 2) // move new step/size info + { + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + { + CV_DbgAssert(m.step.p != m.step.buf); + step.p = m.step.p; + size.p = m.size.p; + m.step.p = m.step.buf; + m.size.p = &m.rows; + } + m.flags = MAGIC_VAL; m.dims = m.rows = m.cols = 0; + m.data = NULL; m.datastart = NULL; m.dataend = NULL; m.datalimit = NULL; + m.allocator = NULL; + m.u = NULL; + return *this; +} + +#endif + + +///////////////////////////// MatSize //////////////////////////// + +inline +MatSize::MatSize(int* _p) + : p(_p) {} + +inline +int MatSize::dims() const +{ + return (p - 1)[0]; +} + +inline +Size MatSize::operator()() const +{ + CV_DbgAssert(dims() <= 2); + return Size(p[1], p[0]); +} + +inline +const int& MatSize::operator[](int i) const +{ + CV_DbgAssert(i < dims()); +#ifdef __OPENCV_BUILD + CV_DbgAssert(i >= 0); +#endif + return p[i]; +} + +inline +int& MatSize::operator[](int i) +{ + CV_DbgAssert(i < dims()); +#ifdef __OPENCV_BUILD + CV_DbgAssert(i >= 0); +#endif + return p[i]; +} + +inline +MatSize::operator const int*() const +{ + return p; +} + +inline +bool MatSize::operator == (const MatSize& sz) const +{ + int d = dims(); + int dsz = sz.dims(); + if( d != dsz ) + return false; + if( d == 2 ) + return p[0] == sz.p[0] && p[1] == sz.p[1]; + + for( int i = 0; i < d; i++ ) + if( p[i] != sz.p[i] ) + return false; + return true; +} + +inline +bool MatSize::operator != (const MatSize& sz) const +{ + return !(*this == sz); +} + + + +///////////////////////////// MatStep //////////////////////////// + +inline +MatStep::MatStep() +{ + p = buf; p[0] = p[1] = 0; +} + +inline +MatStep::MatStep(size_t s) +{ + p = buf; p[0] = s; p[1] = 0; +} + +inline +const size_t& MatStep::operator[](int i) const +{ + return p[i]; +} + +inline +size_t& MatStep::operator[](int i) +{ + return p[i]; +} + +inline MatStep::operator size_t() const +{ + CV_DbgAssert( p == buf ); + return buf[0]; +} + +inline MatStep& MatStep::operator = (size_t s) +{ + CV_DbgAssert( p == buf ); + buf[0] = s; + return *this; +} + + + +////////////////////////////// Mat_<_Tp> //////////////////////////// + +template inline +Mat_<_Tp>::Mat_() + : Mat() +{ + flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value; +} + +template inline +Mat_<_Tp>::Mat_(int _rows, int _cols) + : Mat(_rows, _cols, traits::Type<_Tp>::value) +{ +} + +template inline +Mat_<_Tp>::Mat_(int _rows, int _cols, const _Tp& value) + : Mat(_rows, _cols, traits::Type<_Tp>::value) +{ + *this = value; +} + +template inline +Mat_<_Tp>::Mat_(Size _sz) + : Mat(_sz.height, _sz.width, traits::Type<_Tp>::value) +{} + +template inline +Mat_<_Tp>::Mat_(Size _sz, const _Tp& value) + : Mat(_sz.height, _sz.width, traits::Type<_Tp>::value) +{ + *this = value; +} + +template inline +Mat_<_Tp>::Mat_(int _dims, const int* _sz) + : Mat(_dims, _sz, traits::Type<_Tp>::value) +{} + +template inline +Mat_<_Tp>::Mat_(int _dims, const int* _sz, const _Tp& _s) + : Mat(_dims, _sz, traits::Type<_Tp>::value, Scalar(_s)) +{} + +template inline +Mat_<_Tp>::Mat_(int _dims, const int* _sz, _Tp* _data, const size_t* _steps) + : Mat(_dims, _sz, traits::Type<_Tp>::value, _data, _steps) +{} + +template inline +Mat_<_Tp>::Mat_(const Mat_<_Tp>& m, const Range* ranges) + : Mat(m, ranges) +{} + +template inline +Mat_<_Tp>::Mat_(const Mat_<_Tp>& m, const std::vector& ranges) + : Mat(m, ranges) +{} + +template inline +Mat_<_Tp>::Mat_(const Mat& m) + : Mat() +{ + flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value; + *this = m; +} + +template inline +Mat_<_Tp>::Mat_(const Mat_& m) + : Mat(m) +{} + +template inline +Mat_<_Tp>::Mat_(int _rows, int _cols, _Tp* _data, size_t steps) + : Mat(_rows, _cols, traits::Type<_Tp>::value, _data, steps) +{} + +template inline +Mat_<_Tp>::Mat_(const Mat_& m, const Range& _rowRange, const Range& _colRange) + : Mat(m, _rowRange, _colRange) +{} + +template inline +Mat_<_Tp>::Mat_(const Mat_& m, const Rect& roi) + : Mat(m, roi) +{} + +template template inline +Mat_<_Tp>::Mat_(const Vec::channel_type, n>& vec, bool copyData) + : Mat(n / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&vec) +{ + CV_Assert(n%DataType<_Tp>::channels == 0); + if( copyData ) + *this = clone(); +} + +template template inline +Mat_<_Tp>::Mat_(const Matx::channel_type, m, n>& M, bool copyData) + : Mat(m, n / DataType<_Tp>::channels, traits::Type<_Tp>::value, (void*)&M) +{ + CV_Assert(n % DataType<_Tp>::channels == 0); + if( copyData ) + *this = clone(); +} + +template inline +Mat_<_Tp>::Mat_(const Point_::channel_type>& pt, bool copyData) + : Mat(2 / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&pt) +{ + CV_Assert(2 % DataType<_Tp>::channels == 0); + if( copyData ) + *this = clone(); +} + +template inline +Mat_<_Tp>::Mat_(const Point3_::channel_type>& pt, bool copyData) + : Mat(3 / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&pt) +{ + CV_Assert(3 % DataType<_Tp>::channels == 0); + if( copyData ) + *this = clone(); +} + +template inline +Mat_<_Tp>::Mat_(const MatCommaInitializer_<_Tp>& commaInitializer) + : Mat(commaInitializer) +{} + +template inline +Mat_<_Tp>::Mat_(const std::vector<_Tp>& vec, bool copyData) + : Mat(vec, copyData) +{} + +#ifdef CV_CXX11 +template inline +Mat_<_Tp>::Mat_(std::initializer_list<_Tp> list) + : Mat(list) +{} + +template inline +Mat_<_Tp>::Mat_(const std::initializer_list sizes, std::initializer_list<_Tp> list) + : Mat(sizes, list) +{} +#endif + +#ifdef CV_CXX_STD_ARRAY +template template inline +Mat_<_Tp>::Mat_(const std::array<_Tp, _Nm>& arr, bool copyData) + : Mat(arr, copyData) +{} +#endif + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (const Mat& m) +{ + if( traits::Type<_Tp>::value == m.type() ) + { + Mat::operator = (m); + return *this; + } + if( traits::Depth<_Tp>::value == m.depth() ) + { + return (*this = m.reshape(DataType<_Tp>::channels, m.dims, 0)); + } + CV_Assert(DataType<_Tp>::channels == m.channels() || m.empty()); + m.convertTo(*this, type()); + return *this; +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (const Mat_& m) +{ + Mat::operator=(m); + return *this; +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (const _Tp& s) +{ + typedef typename DataType<_Tp>::vec_type VT; + Mat::operator=(Scalar((const VT&)s)); + return *this; +} + +template inline +void Mat_<_Tp>::create(int _rows, int _cols) +{ + Mat::create(_rows, _cols, traits::Type<_Tp>::value); +} + +template inline +void Mat_<_Tp>::create(Size _sz) +{ + Mat::create(_sz, traits::Type<_Tp>::value); +} + +template inline +void Mat_<_Tp>::create(int _dims, const int* _sz) +{ + Mat::create(_dims, _sz, traits::Type<_Tp>::value); +} + +template inline +void Mat_<_Tp>::release() +{ + Mat::release(); +#ifdef _DEBUG + flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value; +#endif +} + +template inline +Mat_<_Tp> Mat_<_Tp>::cross(const Mat_& m) const +{ + return Mat_<_Tp>(Mat::cross(m)); +} + +template template inline +Mat_<_Tp>::operator Mat_() const +{ + return Mat_(*this); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::row(int y) const +{ + return Mat_(*this, Range(y, y+1), Range::all()); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::col(int x) const +{ + return Mat_(*this, Range::all(), Range(x, x+1)); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::diag(int d) const +{ + return Mat_(Mat::diag(d)); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::clone() const +{ + return Mat_(Mat::clone()); +} + +template inline +size_t Mat_<_Tp>::elemSize() const +{ + CV_DbgAssert( Mat::elemSize() == sizeof(_Tp) ); + return sizeof(_Tp); +} + +template inline +size_t Mat_<_Tp>::elemSize1() const +{ + CV_DbgAssert( Mat::elemSize1() == sizeof(_Tp) / DataType<_Tp>::channels ); + return sizeof(_Tp) / DataType<_Tp>::channels; +} + +template inline +int Mat_<_Tp>::type() const +{ + CV_DbgAssert( Mat::type() == traits::Type<_Tp>::value ); + return traits::Type<_Tp>::value; +} + +template inline +int Mat_<_Tp>::depth() const +{ + CV_DbgAssert( Mat::depth() == traits::Depth<_Tp>::value ); + return traits::Depth<_Tp>::value; +} + +template inline +int Mat_<_Tp>::channels() const +{ + CV_DbgAssert( Mat::channels() == DataType<_Tp>::channels ); + return DataType<_Tp>::channels; +} + +template inline +size_t Mat_<_Tp>::stepT(int i) const +{ + return step.p[i] / elemSize(); +} + +template inline +size_t Mat_<_Tp>::step1(int i) const +{ + return step.p[i] / elemSize1(); +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::adjustROI( int dtop, int dbottom, int dleft, int dright ) +{ + return (Mat_<_Tp>&)(Mat::adjustROI(dtop, dbottom, dleft, dright)); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::operator()( const Range& _rowRange, const Range& _colRange ) const +{ + return Mat_<_Tp>(*this, _rowRange, _colRange); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::operator()( const Rect& roi ) const +{ + return Mat_<_Tp>(*this, roi); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::operator()( const Range* ranges ) const +{ + return Mat_<_Tp>(*this, ranges); +} + +template inline +Mat_<_Tp> Mat_<_Tp>::operator()(const std::vector& ranges) const +{ + return Mat_<_Tp>(*this, ranges); +} + +template inline +_Tp* Mat_<_Tp>::operator [](int y) +{ + CV_DbgAssert( 0 <= y && y < size.p[0] ); + return (_Tp*)(data + y*step.p[0]); +} + +template inline +const _Tp* Mat_<_Tp>::operator [](int y) const +{ + CV_DbgAssert( 0 <= y && y < size.p[0] ); + return (const _Tp*)(data + y*step.p[0]); +} + +template inline +_Tp& Mat_<_Tp>::operator ()(int i0, int i1) +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert(type() == traits::Type<_Tp>::value); + return ((_Tp*)(data + step.p[0] * i0))[i1]; +} + +template inline +const _Tp& Mat_<_Tp>::operator ()(int i0, int i1) const +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]); + CV_DbgAssert(type() == traits::Type<_Tp>::value); + return ((const _Tp*)(data + step.p[0] * i0))[i1]; +} + +template inline +_Tp& Mat_<_Tp>::operator ()(Point pt) +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)pt.x < (unsigned)size.p[1]); + CV_DbgAssert(type() == traits::Type<_Tp>::value); + return ((_Tp*)(data + step.p[0] * pt.y))[pt.x]; +} + +template inline +const _Tp& Mat_<_Tp>::operator ()(Point pt) const +{ + CV_DbgAssert(dims <= 2); + CV_DbgAssert(data); + CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]); + CV_DbgAssert((unsigned)pt.x < (unsigned)size.p[1]); + CV_DbgAssert(type() == traits::Type<_Tp>::value); + return ((const _Tp*)(data + step.p[0] * pt.y))[pt.x]; +} + +template inline +_Tp& Mat_<_Tp>::operator ()(const int* idx) +{ + return Mat::at<_Tp>(idx); +} + +template inline +const _Tp& Mat_<_Tp>::operator ()(const int* idx) const +{ + return Mat::at<_Tp>(idx); +} + +template template inline +_Tp& Mat_<_Tp>::operator ()(const Vec& idx) +{ + return Mat::at<_Tp>(idx); +} + +template template inline +const _Tp& Mat_<_Tp>::operator ()(const Vec& idx) const +{ + return Mat::at<_Tp>(idx); +} + +template inline +_Tp& Mat_<_Tp>::operator ()(int i0) +{ + return this->at<_Tp>(i0); +} + +template inline +const _Tp& Mat_<_Tp>::operator ()(int i0) const +{ + return this->at<_Tp>(i0); +} + +template inline +_Tp& Mat_<_Tp>::operator ()(int i0, int i1, int i2) +{ + return this->at<_Tp>(i0, i1, i2); +} + +template inline +const _Tp& Mat_<_Tp>::operator ()(int i0, int i1, int i2) const +{ + return this->at<_Tp>(i0, i1, i2); +} + +template inline +Mat_<_Tp>::operator std::vector<_Tp>() const +{ + std::vector<_Tp> v; + copyTo(v); + return v; +} + +#ifdef CV_CXX_STD_ARRAY +template template inline +Mat_<_Tp>::operator std::array<_Tp, _Nm>() const +{ + std::array<_Tp, _Nm> a; + copyTo(a); + return a; +} +#endif + +template template inline +Mat_<_Tp>::operator Vec::channel_type, n>() const +{ + CV_Assert(n % DataType<_Tp>::channels == 0); + +#if defined _MSC_VER + const Mat* pMat = (const Mat*)this; // workaround for MSVS <= 2012 compiler bugs (but GCC 4.6 dislikes this workaround) + return pMat->operator Vec::channel_type, n>(); +#else + return this->Mat::operator Vec::channel_type, n>(); +#endif +} + +template template inline +Mat_<_Tp>::operator Matx::channel_type, m, n>() const +{ + CV_Assert(n % DataType<_Tp>::channels == 0); + +#if defined _MSC_VER + const Mat* pMat = (const Mat*)this; // workaround for MSVS <= 2012 compiler bugs (but GCC 4.6 dislikes this workaround) + Matx::channel_type, m, n> res = pMat->operator Matx::channel_type, m, n>(); + return res; +#else + Matx::channel_type, m, n> res = this->Mat::operator Matx::channel_type, m, n>(); + return res; +#endif +} + +template inline +MatConstIterator_<_Tp> Mat_<_Tp>::begin() const +{ + return Mat::begin<_Tp>(); +} + +template inline +MatConstIterator_<_Tp> Mat_<_Tp>::end() const +{ + return Mat::end<_Tp>(); +} + +template inline +MatIterator_<_Tp> Mat_<_Tp>::begin() +{ + return Mat::begin<_Tp>(); +} + +template inline +MatIterator_<_Tp> Mat_<_Tp>::end() +{ + return Mat::end<_Tp>(); +} + +template template inline +void Mat_<_Tp>::forEach(const Functor& operation) { + Mat::forEach<_Tp, Functor>(operation); +} + +template template inline +void Mat_<_Tp>::forEach(const Functor& operation) const { + Mat::forEach<_Tp, Functor>(operation); +} + +#ifdef CV_CXX_MOVE_SEMANTICS + +template inline +Mat_<_Tp>::Mat_(Mat_&& m) + : Mat(m) +{ +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (Mat_&& m) +{ + Mat::operator = (std::move(m)); + return *this; +} + +template inline +Mat_<_Tp>::Mat_(Mat&& m) + : Mat() +{ + flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value; + *this = m; +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (Mat&& m) +{ + if( traits::Type<_Tp>::value == m.type() ) + { + Mat::operator = ((Mat&&)m); + return *this; + } + if( traits::Depth<_Tp>::value == m.depth() ) + { + Mat::operator = ((Mat&&)m.reshape(DataType<_Tp>::channels, m.dims, 0)); + return *this; + } + CV_DbgAssert(DataType<_Tp>::channels == m.channels()); + m.convertTo(*this, type()); + return *this; +} + +template inline +Mat_<_Tp>::Mat_(MatExpr&& e) + : Mat() +{ + flags = (flags & ~CV_MAT_TYPE_MASK) | traits::Type<_Tp>::value; + *this = Mat(e); +} + +#endif + +///////////////////////////// SparseMat ///////////////////////////// + +inline +SparseMat::SparseMat() + : flags(MAGIC_VAL), hdr(0) +{} + +inline +SparseMat::SparseMat(int _dims, const int* _sizes, int _type) + : flags(MAGIC_VAL), hdr(0) +{ + create(_dims, _sizes, _type); +} + +inline +SparseMat::SparseMat(const SparseMat& m) + : flags(m.flags), hdr(m.hdr) +{ + addref(); +} + +inline +SparseMat::~SparseMat() +{ + release(); +} + +inline +SparseMat& SparseMat::operator = (const SparseMat& m) +{ + if( this != &m ) + { + if( m.hdr ) + CV_XADD(&m.hdr->refcount, 1); + release(); + flags = m.flags; + hdr = m.hdr; + } + return *this; +} + +inline +SparseMat& SparseMat::operator = (const Mat& m) +{ + return (*this = SparseMat(m)); +} + +inline +SparseMat SparseMat::clone() const +{ + SparseMat temp; + this->copyTo(temp); + return temp; +} + +inline +void SparseMat::assignTo( SparseMat& m, int _type ) const +{ + if( _type < 0 ) + m = *this; + else + convertTo(m, _type); +} + +inline +void SparseMat::addref() +{ + if( hdr ) + CV_XADD(&hdr->refcount, 1); +} + +inline +void SparseMat::release() +{ + if( hdr && CV_XADD(&hdr->refcount, -1) == 1 ) + delete hdr; + hdr = 0; +} + +inline +size_t SparseMat::elemSize() const +{ + return CV_ELEM_SIZE(flags); +} + +inline +size_t SparseMat::elemSize1() const +{ + return CV_ELEM_SIZE1(flags); +} + +inline +int SparseMat::type() const +{ + return CV_MAT_TYPE(flags); +} + +inline +int SparseMat::depth() const +{ + return CV_MAT_DEPTH(flags); +} + +inline +int SparseMat::channels() const +{ + return CV_MAT_CN(flags); +} + +inline +const int* SparseMat::size() const +{ + return hdr ? hdr->size : 0; +} + +inline +int SparseMat::size(int i) const +{ + if( hdr ) + { + CV_DbgAssert((unsigned)i < (unsigned)hdr->dims); + return hdr->size[i]; + } + return 0; +} + +inline +int SparseMat::dims() const +{ + return hdr ? hdr->dims : 0; +} + +inline +size_t SparseMat::nzcount() const +{ + return hdr ? hdr->nodeCount : 0; +} + +inline +size_t SparseMat::hash(int i0) const +{ + return (size_t)i0; +} + +inline +size_t SparseMat::hash(int i0, int i1) const +{ + return (size_t)(unsigned)i0 * HASH_SCALE + (unsigned)i1; +} + +inline +size_t SparseMat::hash(int i0, int i1, int i2) const +{ + return ((size_t)(unsigned)i0 * HASH_SCALE + (unsigned)i1) * HASH_SCALE + (unsigned)i2; +} + +inline +size_t SparseMat::hash(const int* idx) const +{ + size_t h = (unsigned)idx[0]; + if( !hdr ) + return 0; + int d = hdr->dims; + for(int i = 1; i < d; i++ ) + h = h * HASH_SCALE + (unsigned)idx[i]; + return h; +} + +template inline +_Tp& SparseMat::ref(int i0, size_t* hashval) +{ + return *(_Tp*)((SparseMat*)this)->ptr(i0, true, hashval); +} + +template inline +_Tp& SparseMat::ref(int i0, int i1, size_t* hashval) +{ + return *(_Tp*)((SparseMat*)this)->ptr(i0, i1, true, hashval); +} + +template inline +_Tp& SparseMat::ref(int i0, int i1, int i2, size_t* hashval) +{ + return *(_Tp*)((SparseMat*)this)->ptr(i0, i1, i2, true, hashval); +} + +template inline +_Tp& SparseMat::ref(const int* idx, size_t* hashval) +{ + return *(_Tp*)((SparseMat*)this)->ptr(idx, true, hashval); +} + +template inline +_Tp SparseMat::value(int i0, size_t* hashval) const +{ + const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, false, hashval); + return p ? *p : _Tp(); +} + +template inline +_Tp SparseMat::value(int i0, int i1, size_t* hashval) const +{ + const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, i1, false, hashval); + return p ? *p : _Tp(); +} + +template inline +_Tp SparseMat::value(int i0, int i1, int i2, size_t* hashval) const +{ + const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, i1, i2, false, hashval); + return p ? *p : _Tp(); +} + +template inline +_Tp SparseMat::value(const int* idx, size_t* hashval) const +{ + const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(idx, false, hashval); + return p ? *p : _Tp(); +} + +template inline +const _Tp* SparseMat::find(int i0, size_t* hashval) const +{ + return (const _Tp*)((SparseMat*)this)->ptr(i0, false, hashval); +} + +template inline +const _Tp* SparseMat::find(int i0, int i1, size_t* hashval) const +{ + return (const _Tp*)((SparseMat*)this)->ptr(i0, i1, false, hashval); +} + +template inline +const _Tp* SparseMat::find(int i0, int i1, int i2, size_t* hashval) const +{ + return (const _Tp*)((SparseMat*)this)->ptr(i0, i1, i2, false, hashval); +} + +template inline +const _Tp* SparseMat::find(const int* idx, size_t* hashval) const +{ + return (const _Tp*)((SparseMat*)this)->ptr(idx, false, hashval); +} + +template inline +_Tp& SparseMat::value(Node* n) +{ + return *(_Tp*)((uchar*)n + hdr->valueOffset); +} + +template inline +const _Tp& SparseMat::value(const Node* n) const +{ + return *(const _Tp*)((const uchar*)n + hdr->valueOffset); +} + +inline +SparseMat::Node* SparseMat::node(size_t nidx) +{ + return (Node*)(void*)&hdr->pool[nidx]; +} + +inline +const SparseMat::Node* SparseMat::node(size_t nidx) const +{ + return (const Node*)(const void*)&hdr->pool[nidx]; +} + +inline +SparseMatIterator SparseMat::begin() +{ + return SparseMatIterator(this); +} + +inline +SparseMatConstIterator SparseMat::begin() const +{ + return SparseMatConstIterator(this); +} + +inline +SparseMatIterator SparseMat::end() +{ + SparseMatIterator it(this); + it.seekEnd(); + return it; +} + +inline +SparseMatConstIterator SparseMat::end() const +{ + SparseMatConstIterator it(this); + it.seekEnd(); + return it; +} + +template inline +SparseMatIterator_<_Tp> SparseMat::begin() +{ + return SparseMatIterator_<_Tp>(this); +} + +template inline +SparseMatConstIterator_<_Tp> SparseMat::begin() const +{ + return SparseMatConstIterator_<_Tp>(this); +} + +template inline +SparseMatIterator_<_Tp> SparseMat::end() +{ + SparseMatIterator_<_Tp> it(this); + it.seekEnd(); + return it; +} + +template inline +SparseMatConstIterator_<_Tp> SparseMat::end() const +{ + SparseMatConstIterator_<_Tp> it(this); + it.seekEnd(); + return it; +} + + + +///////////////////////////// SparseMat_ //////////////////////////// + +template inline +SparseMat_<_Tp>::SparseMat_() +{ + flags = MAGIC_VAL | traits::Type<_Tp>::value; +} + +template inline +SparseMat_<_Tp>::SparseMat_(int _dims, const int* _sizes) + : SparseMat(_dims, _sizes, traits::Type<_Tp>::value) +{} + +template inline +SparseMat_<_Tp>::SparseMat_(const SparseMat& m) +{ + if( m.type() == traits::Type<_Tp>::value ) + *this = (const SparseMat_<_Tp>&)m; + else + m.convertTo(*this, traits::Type<_Tp>::value); +} + +template inline +SparseMat_<_Tp>::SparseMat_(const SparseMat_<_Tp>& m) +{ + this->flags = m.flags; + this->hdr = m.hdr; + if( this->hdr ) + CV_XADD(&this->hdr->refcount, 1); +} + +template inline +SparseMat_<_Tp>::SparseMat_(const Mat& m) +{ + SparseMat sm(m); + *this = sm; +} + +template inline +SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const SparseMat_<_Tp>& m) +{ + if( this != &m ) + { + if( m.hdr ) CV_XADD(&m.hdr->refcount, 1); + release(); + flags = m.flags; + hdr = m.hdr; + } + return *this; +} + +template inline +SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const SparseMat& m) +{ + if( m.type() == traits::Type<_Tp>::value ) + return (*this = (const SparseMat_<_Tp>&)m); + m.convertTo(*this, traits::Type<_Tp>::value); + return *this; +} + +template inline +SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const Mat& m) +{ + return (*this = SparseMat(m)); +} + +template inline +SparseMat_<_Tp> SparseMat_<_Tp>::clone() const +{ + SparseMat_<_Tp> m; + this->copyTo(m); + return m; +} + +template inline +void SparseMat_<_Tp>::create(int _dims, const int* _sizes) +{ + SparseMat::create(_dims, _sizes, traits::Type<_Tp>::value); +} + +template inline +int SparseMat_<_Tp>::type() const +{ + return traits::Type<_Tp>::value; +} + +template inline +int SparseMat_<_Tp>::depth() const +{ + return traits::Depth<_Tp>::value; +} + +template inline +int SparseMat_<_Tp>::channels() const +{ + return DataType<_Tp>::channels; +} + +template inline +_Tp& SparseMat_<_Tp>::ref(int i0, size_t* hashval) +{ + return SparseMat::ref<_Tp>(i0, hashval); +} + +template inline +_Tp SparseMat_<_Tp>::operator()(int i0, size_t* hashval) const +{ + return SparseMat::value<_Tp>(i0, hashval); +} + +template inline +_Tp& SparseMat_<_Tp>::ref(int i0, int i1, size_t* hashval) +{ + return SparseMat::ref<_Tp>(i0, i1, hashval); +} + +template inline +_Tp SparseMat_<_Tp>::operator()(int i0, int i1, size_t* hashval) const +{ + return SparseMat::value<_Tp>(i0, i1, hashval); +} + +template inline +_Tp& SparseMat_<_Tp>::ref(int i0, int i1, int i2, size_t* hashval) +{ + return SparseMat::ref<_Tp>(i0, i1, i2, hashval); +} + +template inline +_Tp SparseMat_<_Tp>::operator()(int i0, int i1, int i2, size_t* hashval) const +{ + return SparseMat::value<_Tp>(i0, i1, i2, hashval); +} + +template inline +_Tp& SparseMat_<_Tp>::ref(const int* idx, size_t* hashval) +{ + return SparseMat::ref<_Tp>(idx, hashval); +} + +template inline +_Tp SparseMat_<_Tp>::operator()(const int* idx, size_t* hashval) const +{ + return SparseMat::value<_Tp>(idx, hashval); +} + +template inline +SparseMatIterator_<_Tp> SparseMat_<_Tp>::begin() +{ + return SparseMatIterator_<_Tp>(this); +} + +template inline +SparseMatConstIterator_<_Tp> SparseMat_<_Tp>::begin() const +{ + return SparseMatConstIterator_<_Tp>(this); +} + +template inline +SparseMatIterator_<_Tp> SparseMat_<_Tp>::end() +{ + SparseMatIterator_<_Tp> it(this); + it.seekEnd(); + return it; +} + +template inline +SparseMatConstIterator_<_Tp> SparseMat_<_Tp>::end() const +{ + SparseMatConstIterator_<_Tp> it(this); + it.seekEnd(); + return it; +} + + + +////////////////////////// MatConstIterator ///////////////////////// + +inline +MatConstIterator::MatConstIterator() + : m(0), elemSize(0), ptr(0), sliceStart(0), sliceEnd(0) +{} + +inline +MatConstIterator::MatConstIterator(const Mat* _m) + : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0) +{ + if( m && m->isContinuous() ) + { + sliceStart = m->ptr(); + sliceEnd = sliceStart + m->total()*elemSize; + } + seek((const int*)0); +} + +inline +MatConstIterator::MatConstIterator(const Mat* _m, int _row, int _col) + : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0) +{ + CV_Assert(m && m->dims <= 2); + if( m->isContinuous() ) + { + sliceStart = m->ptr(); + sliceEnd = sliceStart + m->total()*elemSize; + } + int idx[] = {_row, _col}; + seek(idx); +} + +inline +MatConstIterator::MatConstIterator(const Mat* _m, Point _pt) + : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0) +{ + CV_Assert(m && m->dims <= 2); + if( m->isContinuous() ) + { + sliceStart = m->ptr(); + sliceEnd = sliceStart + m->total()*elemSize; + } + int idx[] = {_pt.y, _pt.x}; + seek(idx); +} + +inline +MatConstIterator::MatConstIterator(const MatConstIterator& it) + : m(it.m), elemSize(it.elemSize), ptr(it.ptr), sliceStart(it.sliceStart), sliceEnd(it.sliceEnd) +{} + +inline +MatConstIterator& MatConstIterator::operator = (const MatConstIterator& it ) +{ + m = it.m; elemSize = it.elemSize; ptr = it.ptr; + sliceStart = it.sliceStart; sliceEnd = it.sliceEnd; + return *this; +} + +inline +const uchar* MatConstIterator::operator *() const +{ + return ptr; +} + +inline MatConstIterator& MatConstIterator::operator += (ptrdiff_t ofs) +{ + if( !m || ofs == 0 ) + return *this; + ptrdiff_t ofsb = ofs*elemSize; + ptr += ofsb; + if( ptr < sliceStart || sliceEnd <= ptr ) + { + ptr -= ofsb; + seek(ofs, true); + } + return *this; +} + +inline +MatConstIterator& MatConstIterator::operator -= (ptrdiff_t ofs) +{ + return (*this += -ofs); +} + +inline +MatConstIterator& MatConstIterator::operator --() +{ + if( m && (ptr -= elemSize) < sliceStart ) + { + ptr += elemSize; + seek(-1, true); + } + return *this; +} + +inline +MatConstIterator MatConstIterator::operator --(int) +{ + MatConstIterator b = *this; + *this += -1; + return b; +} + +inline +MatConstIterator& MatConstIterator::operator ++() +{ + if( m && (ptr += elemSize) >= sliceEnd ) + { + ptr -= elemSize; + seek(1, true); + } + return *this; +} + +inline MatConstIterator MatConstIterator::operator ++(int) +{ + MatConstIterator b = *this; + *this += 1; + return b; +} + + +static inline +bool operator == (const MatConstIterator& a, const MatConstIterator& b) +{ + return a.m == b.m && a.ptr == b.ptr; +} + +static inline +bool operator != (const MatConstIterator& a, const MatConstIterator& b) +{ + return !(a == b); +} + +static inline +bool operator < (const MatConstIterator& a, const MatConstIterator& b) +{ + return a.ptr < b.ptr; +} + +static inline +bool operator > (const MatConstIterator& a, const MatConstIterator& b) +{ + return a.ptr > b.ptr; +} + +static inline +bool operator <= (const MatConstIterator& a, const MatConstIterator& b) +{ + return a.ptr <= b.ptr; +} + +static inline +bool operator >= (const MatConstIterator& a, const MatConstIterator& b) +{ + return a.ptr >= b.ptr; +} + +static inline +ptrdiff_t operator - (const MatConstIterator& b, const MatConstIterator& a) +{ + if( a.m != b.m ) + return ((size_t)(-1) >> 1); + if( a.sliceEnd == b.sliceEnd ) + return (b.ptr - a.ptr)/static_cast(b.elemSize); + + return b.lpos() - a.lpos(); +} + +static inline +MatConstIterator operator + (const MatConstIterator& a, ptrdiff_t ofs) +{ + MatConstIterator b = a; + return b += ofs; +} + +static inline +MatConstIterator operator + (ptrdiff_t ofs, const MatConstIterator& a) +{ + MatConstIterator b = a; + return b += ofs; +} + +static inline +MatConstIterator operator - (const MatConstIterator& a, ptrdiff_t ofs) +{ + MatConstIterator b = a; + return b += -ofs; +} + + +inline +const uchar* MatConstIterator::operator [](ptrdiff_t i) const +{ + return *(*this + i); +} + + + +///////////////////////// MatConstIterator_ ///////////////////////// + +template inline +MatConstIterator_<_Tp>::MatConstIterator_() +{} + +template inline +MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m) + : MatConstIterator(_m) +{} + +template inline +MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m, int _row, int _col) + : MatConstIterator(_m, _row, _col) +{} + +template inline +MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m, Point _pt) + : MatConstIterator(_m, _pt) +{} + +template inline +MatConstIterator_<_Tp>::MatConstIterator_(const MatConstIterator_& it) + : MatConstIterator(it) +{} + +template inline +MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator = (const MatConstIterator_& it ) +{ + MatConstIterator::operator = (it); + return *this; +} + +template inline +const _Tp& MatConstIterator_<_Tp>::operator *() const +{ + return *(_Tp*)(this->ptr); +} + +template inline +MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator += (ptrdiff_t ofs) +{ + MatConstIterator::operator += (ofs); + return *this; +} + +template inline +MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator -= (ptrdiff_t ofs) +{ + return (*this += -ofs); +} + +template inline +MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator --() +{ + MatConstIterator::operator --(); + return *this; +} + +template inline +MatConstIterator_<_Tp> MatConstIterator_<_Tp>::operator --(int) +{ + MatConstIterator_ b = *this; + MatConstIterator::operator --(); + return b; +} + +template inline +MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator ++() +{ + MatConstIterator::operator ++(); + return *this; +} + +template inline +MatConstIterator_<_Tp> MatConstIterator_<_Tp>::operator ++(int) +{ + MatConstIterator_ b = *this; + MatConstIterator::operator ++(); + return b; +} + + +template inline +Point MatConstIterator_<_Tp>::pos() const +{ + if( !m ) + return Point(); + CV_DbgAssert( m->dims <= 2 ); + if( m->isContinuous() ) + { + ptrdiff_t ofs = (const _Tp*)ptr - (const _Tp*)m->data; + int y = (int)(ofs / m->cols); + int x = (int)(ofs - (ptrdiff_t)y * m->cols); + return Point(x, y); + } + else + { + ptrdiff_t ofs = (uchar*)ptr - m->data; + int y = (int)(ofs / m->step); + int x = (int)((ofs - y * m->step)/sizeof(_Tp)); + return Point(x, y); + } +} + + +template static inline +bool operator == (const MatConstIterator_<_Tp>& a, const MatConstIterator_<_Tp>& b) +{ + return a.m == b.m && a.ptr == b.ptr; +} + +template static inline +bool operator != (const MatConstIterator_<_Tp>& a, const MatConstIterator_<_Tp>& b) +{ + return a.m != b.m || a.ptr != b.ptr; +} + +template static inline +MatConstIterator_<_Tp> operator + (const MatConstIterator_<_Tp>& a, ptrdiff_t ofs) +{ + MatConstIterator t = (const MatConstIterator&)a + ofs; + return (MatConstIterator_<_Tp>&)t; +} + +template static inline +MatConstIterator_<_Tp> operator + (ptrdiff_t ofs, const MatConstIterator_<_Tp>& a) +{ + MatConstIterator t = (const MatConstIterator&)a + ofs; + return (MatConstIterator_<_Tp>&)t; +} + +template static inline +MatConstIterator_<_Tp> operator - (const MatConstIterator_<_Tp>& a, ptrdiff_t ofs) +{ + MatConstIterator t = (const MatConstIterator&)a - ofs; + return (MatConstIterator_<_Tp>&)t; +} + +template inline +const _Tp& MatConstIterator_<_Tp>::operator [](ptrdiff_t i) const +{ + return *(_Tp*)MatConstIterator::operator [](i); +} + + + +//////////////////////////// MatIterator_ /////////////////////////// + +template inline +MatIterator_<_Tp>::MatIterator_() + : MatConstIterator_<_Tp>() +{} + +template inline +MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m) + : MatConstIterator_<_Tp>(_m) +{} + +template inline +MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, int _row, int _col) + : MatConstIterator_<_Tp>(_m, _row, _col) +{} + +template inline +MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, Point _pt) + : MatConstIterator_<_Tp>(_m, _pt) +{} + +template inline +MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, const int* _idx) + : MatConstIterator_<_Tp>(_m, _idx) +{} + +template inline +MatIterator_<_Tp>::MatIterator_(const MatIterator_& it) + : MatConstIterator_<_Tp>(it) +{} + +template inline +MatIterator_<_Tp>& MatIterator_<_Tp>::operator = (const MatIterator_<_Tp>& it ) +{ + MatConstIterator::operator = (it); + return *this; +} + +template inline +_Tp& MatIterator_<_Tp>::operator *() const +{ + return *(_Tp*)(this->ptr); +} + +template inline +MatIterator_<_Tp>& MatIterator_<_Tp>::operator += (ptrdiff_t ofs) +{ + MatConstIterator::operator += (ofs); + return *this; +} + +template inline +MatIterator_<_Tp>& MatIterator_<_Tp>::operator -= (ptrdiff_t ofs) +{ + MatConstIterator::operator += (-ofs); + return *this; +} + +template inline +MatIterator_<_Tp>& MatIterator_<_Tp>::operator --() +{ + MatConstIterator::operator --(); + return *this; +} + +template inline +MatIterator_<_Tp> MatIterator_<_Tp>::operator --(int) +{ + MatIterator_ b = *this; + MatConstIterator::operator --(); + return b; +} + +template inline +MatIterator_<_Tp>& MatIterator_<_Tp>::operator ++() +{ + MatConstIterator::operator ++(); + return *this; +} + +template inline +MatIterator_<_Tp> MatIterator_<_Tp>::operator ++(int) +{ + MatIterator_ b = *this; + MatConstIterator::operator ++(); + return b; +} + +template inline +_Tp& MatIterator_<_Tp>::operator [](ptrdiff_t i) const +{ + return *(*this + i); +} + + +template static inline +bool operator == (const MatIterator_<_Tp>& a, const MatIterator_<_Tp>& b) +{ + return a.m == b.m && a.ptr == b.ptr; +} + +template static inline +bool operator != (const MatIterator_<_Tp>& a, const MatIterator_<_Tp>& b) +{ + return a.m != b.m || a.ptr != b.ptr; +} + +template static inline +MatIterator_<_Tp> operator + (const MatIterator_<_Tp>& a, ptrdiff_t ofs) +{ + MatConstIterator t = (const MatConstIterator&)a + ofs; + return (MatIterator_<_Tp>&)t; +} + +template static inline +MatIterator_<_Tp> operator + (ptrdiff_t ofs, const MatIterator_<_Tp>& a) +{ + MatConstIterator t = (const MatConstIterator&)a + ofs; + return (MatIterator_<_Tp>&)t; +} + +template static inline +MatIterator_<_Tp> operator - (const MatIterator_<_Tp>& a, ptrdiff_t ofs) +{ + MatConstIterator t = (const MatConstIterator&)a - ofs; + return (MatIterator_<_Tp>&)t; +} + + + +/////////////////////// SparseMatConstIterator ////////////////////// + +inline +SparseMatConstIterator::SparseMatConstIterator() + : m(0), hashidx(0), ptr(0) +{} + +inline +SparseMatConstIterator::SparseMatConstIterator(const SparseMatConstIterator& it) + : m(it.m), hashidx(it.hashidx), ptr(it.ptr) +{} + +inline SparseMatConstIterator& SparseMatConstIterator::operator = (const SparseMatConstIterator& it) +{ + if( this != &it ) + { + m = it.m; + hashidx = it.hashidx; + ptr = it.ptr; + } + return *this; +} + +template inline +const _Tp& SparseMatConstIterator::value() const +{ + return *(const _Tp*)ptr; +} + +inline +const SparseMat::Node* SparseMatConstIterator::node() const +{ + return (ptr && m && m->hdr) ? (const SparseMat::Node*)(const void*)(ptr - m->hdr->valueOffset) : 0; +} + +inline +SparseMatConstIterator SparseMatConstIterator::operator ++(int) +{ + SparseMatConstIterator it = *this; + ++*this; + return it; +} + +inline +void SparseMatConstIterator::seekEnd() +{ + if( m && m->hdr ) + { + hashidx = m->hdr->hashtab.size(); + ptr = 0; + } +} + + +static inline +bool operator == (const SparseMatConstIterator& it1, const SparseMatConstIterator& it2) +{ + return it1.m == it2.m && it1.ptr == it2.ptr; +} + +static inline +bool operator != (const SparseMatConstIterator& it1, const SparseMatConstIterator& it2) +{ + return !(it1 == it2); +} + + + +///////////////////////// SparseMatIterator ///////////////////////// + +inline +SparseMatIterator::SparseMatIterator() +{} + +inline +SparseMatIterator::SparseMatIterator(SparseMat* _m) + : SparseMatConstIterator(_m) +{} + +inline +SparseMatIterator::SparseMatIterator(const SparseMatIterator& it) + : SparseMatConstIterator(it) +{} + +inline +SparseMatIterator& SparseMatIterator::operator = (const SparseMatIterator& it) +{ + (SparseMatConstIterator&)*this = it; + return *this; +} + +template inline +_Tp& SparseMatIterator::value() const +{ + return *(_Tp*)ptr; +} + +inline +SparseMat::Node* SparseMatIterator::node() const +{ + return (SparseMat::Node*)SparseMatConstIterator::node(); +} + +inline +SparseMatIterator& SparseMatIterator::operator ++() +{ + SparseMatConstIterator::operator ++(); + return *this; +} + +inline +SparseMatIterator SparseMatIterator::operator ++(int) +{ + SparseMatIterator it = *this; + ++*this; + return it; +} + + + +////////////////////// SparseMatConstIterator_ ////////////////////// + +template inline +SparseMatConstIterator_<_Tp>::SparseMatConstIterator_() +{} + +template inline +SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMat_<_Tp>* _m) + : SparseMatConstIterator(_m) +{} + +template inline +SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMat* _m) + : SparseMatConstIterator(_m) +{ + CV_Assert( _m->type() == traits::Type<_Tp>::value ); +} + +template inline +SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMatConstIterator_<_Tp>& it) + : SparseMatConstIterator(it) +{} + +template inline +SparseMatConstIterator_<_Tp>& SparseMatConstIterator_<_Tp>::operator = (const SparseMatConstIterator_<_Tp>& it) +{ + return reinterpret_cast&> + (*reinterpret_cast(this) = + reinterpret_cast(it)); +} + +template inline +const _Tp& SparseMatConstIterator_<_Tp>::operator *() const +{ + return *(const _Tp*)this->ptr; +} + +template inline +SparseMatConstIterator_<_Tp>& SparseMatConstIterator_<_Tp>::operator ++() +{ + SparseMatConstIterator::operator ++(); + return *this; +} + +template inline +SparseMatConstIterator_<_Tp> SparseMatConstIterator_<_Tp>::operator ++(int) +{ + SparseMatConstIterator_<_Tp> it = *this; + SparseMatConstIterator::operator ++(); + return it; +} + + + +///////////////////////// SparseMatIterator_ //////////////////////// + +template inline +SparseMatIterator_<_Tp>::SparseMatIterator_() +{} + +template inline +SparseMatIterator_<_Tp>::SparseMatIterator_(SparseMat_<_Tp>* _m) + : SparseMatConstIterator_<_Tp>(_m) +{} + +template inline +SparseMatIterator_<_Tp>::SparseMatIterator_(SparseMat* _m) + : SparseMatConstIterator_<_Tp>(_m) +{} + +template inline +SparseMatIterator_<_Tp>::SparseMatIterator_(const SparseMatIterator_<_Tp>& it) + : SparseMatConstIterator_<_Tp>(it) +{} + +template inline +SparseMatIterator_<_Tp>& SparseMatIterator_<_Tp>::operator = (const SparseMatIterator_<_Tp>& it) +{ + return reinterpret_cast&> + (*reinterpret_cast(this) = + reinterpret_cast(it)); +} + +template inline +_Tp& SparseMatIterator_<_Tp>::operator *() const +{ + return *(_Tp*)this->ptr; +} + +template inline +SparseMatIterator_<_Tp>& SparseMatIterator_<_Tp>::operator ++() +{ + SparseMatConstIterator::operator ++(); + return *this; +} + +template inline +SparseMatIterator_<_Tp> SparseMatIterator_<_Tp>::operator ++(int) +{ + SparseMatIterator_<_Tp> it = *this; + SparseMatConstIterator::operator ++(); + return it; +} + + + +//////////////////////// MatCommaInitializer_ /////////////////////// + +template inline +MatCommaInitializer_<_Tp>::MatCommaInitializer_(Mat_<_Tp>* _m) + : it(_m) +{} + +template template inline +MatCommaInitializer_<_Tp>& MatCommaInitializer_<_Tp>::operator , (T2 v) +{ + CV_DbgAssert( this->it < ((const Mat_<_Tp>*)this->it.m)->end() ); + *this->it = _Tp(v); + ++this->it; + return *this; +} + +template inline +MatCommaInitializer_<_Tp>::operator Mat_<_Tp>() const +{ + CV_DbgAssert( this->it == ((const Mat_<_Tp>*)this->it.m)->end() ); + return Mat_<_Tp>(*this->it.m); +} + + +template static inline +MatCommaInitializer_<_Tp> operator << (const Mat_<_Tp>& m, T2 val) +{ + MatCommaInitializer_<_Tp> commaInitializer((Mat_<_Tp>*)&m); + return (commaInitializer, val); +} + + + +///////////////////////// Matrix Expressions //////////////////////// + +inline +Mat& Mat::operator = (const MatExpr& e) +{ + e.op->assign(e, *this); + return *this; +} + +template inline +Mat_<_Tp>::Mat_(const MatExpr& e) +{ + e.op->assign(e, *this, traits::Type<_Tp>::value); +} + +template inline +Mat_<_Tp>& Mat_<_Tp>::operator = (const MatExpr& e) +{ + e.op->assign(e, *this, traits::Type<_Tp>::value); + return *this; +} + +template inline +MatExpr Mat_<_Tp>::zeros(int rows, int cols) +{ + return Mat::zeros(rows, cols, traits::Type<_Tp>::value); +} + +template inline +MatExpr Mat_<_Tp>::zeros(Size sz) +{ + return Mat::zeros(sz, traits::Type<_Tp>::value); +} + +template inline +MatExpr Mat_<_Tp>::ones(int rows, int cols) +{ + return Mat::ones(rows, cols, traits::Type<_Tp>::value); +} + +template inline +MatExpr Mat_<_Tp>::ones(Size sz) +{ + return Mat::ones(sz, traits::Type<_Tp>::value); +} + +template inline +MatExpr Mat_<_Tp>::eye(int rows, int cols) +{ + return Mat::eye(rows, cols, traits::Type<_Tp>::value); +} + +template inline +MatExpr Mat_<_Tp>::eye(Size sz) +{ + return Mat::eye(sz, traits::Type<_Tp>::value); +} + +inline +MatExpr::MatExpr() + : op(0), flags(0), a(Mat()), b(Mat()), c(Mat()), alpha(0), beta(0), s() +{} + +inline +MatExpr::MatExpr(const MatOp* _op, int _flags, const Mat& _a, const Mat& _b, + const Mat& _c, double _alpha, double _beta, const Scalar& _s) + : op(_op), flags(_flags), a(_a), b(_b), c(_c), alpha(_alpha), beta(_beta), s(_s) +{} + +inline +MatExpr::operator Mat() const +{ + Mat m; + op->assign(*this, m); + return m; +} + +template inline +MatExpr::operator Mat_<_Tp>() const +{ + Mat_<_Tp> m; + op->assign(*this, m, traits::Type<_Tp>::value); + return m; +} + + +template static inline +MatExpr min(const Mat_<_Tp>& a, const Mat_<_Tp>& b) +{ + return cv::min((const Mat&)a, (const Mat&)b); +} + +template static inline +MatExpr min(const Mat_<_Tp>& a, double s) +{ + return cv::min((const Mat&)a, s); +} + +template static inline +MatExpr min(double s, const Mat_<_Tp>& a) +{ + return cv::min((const Mat&)a, s); +} + +template static inline +MatExpr max(const Mat_<_Tp>& a, const Mat_<_Tp>& b) +{ + return cv::max((const Mat&)a, (const Mat&)b); +} + +template static inline +MatExpr max(const Mat_<_Tp>& a, double s) +{ + return cv::max((const Mat&)a, s); +} + +template static inline +MatExpr max(double s, const Mat_<_Tp>& a) +{ + return cv::max((const Mat&)a, s); +} + +template static inline +MatExpr abs(const Mat_<_Tp>& m) +{ + return cv::abs((const Mat&)m); +} + + +static inline +Mat& operator += (Mat& a, const MatExpr& b) +{ + b.op->augAssignAdd(b, a); + return a; +} + +static inline +const Mat& operator += (const Mat& a, const MatExpr& b) +{ + b.op->augAssignAdd(b, (Mat&)a); + return a; +} + +template static inline +Mat_<_Tp>& operator += (Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignAdd(b, a); + return a; +} + +template static inline +const Mat_<_Tp>& operator += (const Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignAdd(b, (Mat&)a); + return a; +} + +static inline +Mat& operator -= (Mat& a, const MatExpr& b) +{ + b.op->augAssignSubtract(b, a); + return a; +} + +static inline +const Mat& operator -= (const Mat& a, const MatExpr& b) +{ + b.op->augAssignSubtract(b, (Mat&)a); + return a; +} + +template static inline +Mat_<_Tp>& operator -= (Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignSubtract(b, a); + return a; +} + +template static inline +const Mat_<_Tp>& operator -= (const Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignSubtract(b, (Mat&)a); + return a; +} + +static inline +Mat& operator *= (Mat& a, const MatExpr& b) +{ + b.op->augAssignMultiply(b, a); + return a; +} + +static inline +const Mat& operator *= (const Mat& a, const MatExpr& b) +{ + b.op->augAssignMultiply(b, (Mat&)a); + return a; +} + +template static inline +Mat_<_Tp>& operator *= (Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignMultiply(b, a); + return a; +} + +template static inline +const Mat_<_Tp>& operator *= (const Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignMultiply(b, (Mat&)a); + return a; +} + +static inline +Mat& operator /= (Mat& a, const MatExpr& b) +{ + b.op->augAssignDivide(b, a); + return a; +} + +static inline +const Mat& operator /= (const Mat& a, const MatExpr& b) +{ + b.op->augAssignDivide(b, (Mat&)a); + return a; +} + +template static inline +Mat_<_Tp>& operator /= (Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignDivide(b, a); + return a; +} + +template static inline +const Mat_<_Tp>& operator /= (const Mat_<_Tp>& a, const MatExpr& b) +{ + b.op->augAssignDivide(b, (Mat&)a); + return a; +} + + +//////////////////////////////// UMat //////////////////////////////// + +inline +UMat::UMat(UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{} + +inline +UMat::UMat(int _rows, int _cols, int _type, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create(_rows, _cols, _type); +} + +inline +UMat::UMat(int _rows, int _cols, int _type, const Scalar& _s, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create(_rows, _cols, _type); + *this = _s; +} + +inline +UMat::UMat(Size _sz, int _type, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create( _sz.height, _sz.width, _type ); +} + +inline +UMat::UMat(Size _sz, int _type, const Scalar& _s, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create(_sz.height, _sz.width, _type); + *this = _s; +} + +inline +UMat::UMat(int _dims, const int* _sz, int _type, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create(_dims, _sz, _type); +} + +inline +UMat::UMat(int _dims, const int* _sz, int _type, const Scalar& _s, UMatUsageFlags _usageFlags) +: flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), usageFlags(_usageFlags), u(0), offset(0), size(&rows) +{ + create(_dims, _sz, _type); + *this = _s; +} + +inline +UMat::UMat(const UMat& m) +: flags(m.flags), dims(m.dims), rows(m.rows), cols(m.cols), allocator(m.allocator), + usageFlags(m.usageFlags), u(m.u), offset(m.offset), size(&rows) +{ + addref(); + if( m.dims <= 2 ) + { + step[0] = m.step[0]; step[1] = m.step[1]; + } + else + { + dims = 0; + copySize(m); + } +} + + +template inline +UMat::UMat(const std::vector<_Tp>& vec, bool copyData) +: flags(MAGIC_VAL | traits::Type<_Tp>::value | CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()), +cols(1), allocator(0), usageFlags(USAGE_DEFAULT), u(0), offset(0), size(&rows) +{ + if(vec.empty()) + return; + if( !copyData ) + { + // !!!TODO!!! + CV_Error(Error::StsNotImplemented, ""); + } + else + Mat((int)vec.size(), 1, traits::Type<_Tp>::value, (uchar*)&vec[0]).copyTo(*this); +} + +inline +UMat& UMat::operator = (const UMat& m) +{ + if( this != &m ) + { + const_cast(m).addref(); + release(); + flags = m.flags; + if( dims <= 2 && m.dims <= 2 ) + { + dims = m.dims; + rows = m.rows; + cols = m.cols; + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + copySize(m); + allocator = m.allocator; + if (usageFlags == USAGE_DEFAULT) + usageFlags = m.usageFlags; + u = m.u; + offset = m.offset; + } + return *this; +} + +inline +UMat UMat::row(int y) const +{ + return UMat(*this, Range(y, y + 1), Range::all()); +} + +inline +UMat UMat::col(int x) const +{ + return UMat(*this, Range::all(), Range(x, x + 1)); +} + +inline +UMat UMat::rowRange(int startrow, int endrow) const +{ + return UMat(*this, Range(startrow, endrow), Range::all()); +} + +inline +UMat UMat::rowRange(const Range& r) const +{ + return UMat(*this, r, Range::all()); +} + +inline +UMat UMat::colRange(int startcol, int endcol) const +{ + return UMat(*this, Range::all(), Range(startcol, endcol)); +} + +inline +UMat UMat::colRange(const Range& r) const +{ + return UMat(*this, Range::all(), r); +} + +inline +UMat UMat::clone() const +{ + UMat m; + copyTo(m); + return m; +} + +inline +void UMat::assignTo( UMat& m, int _type ) const +{ + if( _type < 0 ) + m = *this; + else + convertTo(m, _type); +} + +inline +void UMat::create(int _rows, int _cols, int _type, UMatUsageFlags _usageFlags) +{ + _type &= TYPE_MASK; + if( dims <= 2 && rows == _rows && cols == _cols && type() == _type && u ) + return; + int sz[] = {_rows, _cols}; + create(2, sz, _type, _usageFlags); +} + +inline +void UMat::create(Size _sz, int _type, UMatUsageFlags _usageFlags) +{ + create(_sz.height, _sz.width, _type, _usageFlags); +} + +inline +void UMat::addref() +{ + if( u ) + CV_XADD(&(u->urefcount), 1); +} + +inline void UMat::release() +{ + if( u && CV_XADD(&(u->urefcount), -1) == 1 ) + deallocate(); + for(int i = 0; i < dims; i++) + size.p[i] = 0; + u = 0; +} + +inline +UMat UMat::operator()( Range _rowRange, Range _colRange ) const +{ + return UMat(*this, _rowRange, _colRange); +} + +inline +UMat UMat::operator()( const Rect& roi ) const +{ + return UMat(*this, roi); +} + +inline +UMat UMat::operator()(const Range* ranges) const +{ + return UMat(*this, ranges); +} + +inline +UMat UMat::operator()(const std::vector& ranges) const +{ + return UMat(*this, ranges); +} + +inline +bool UMat::isContinuous() const +{ + return (flags & CONTINUOUS_FLAG) != 0; +} + +inline +bool UMat::isSubmatrix() const +{ + return (flags & SUBMATRIX_FLAG) != 0; +} + +inline +size_t UMat::elemSize() const +{ + size_t res = dims > 0 ? step.p[dims - 1] : 0; + CV_DbgAssert(res != 0); + return res; +} + +inline +size_t UMat::elemSize1() const +{ + return CV_ELEM_SIZE1(flags); +} + +inline +int UMat::type() const +{ + return CV_MAT_TYPE(flags); +} + +inline +int UMat::depth() const +{ + return CV_MAT_DEPTH(flags); +} + +inline +int UMat::channels() const +{ + return CV_MAT_CN(flags); +} + +inline +size_t UMat::step1(int i) const +{ + return step.p[i] / elemSize1(); +} + +inline +bool UMat::empty() const +{ + return u == 0 || total() == 0 || dims == 0; +} + +inline +size_t UMat::total() const +{ + if( dims <= 2 ) + return (size_t)rows * cols; + size_t p = 1; + for( int i = 0; i < dims; i++ ) + p *= size[i]; + return p; +} + +#ifdef CV_CXX_MOVE_SEMANTICS + +inline +UMat::UMat(UMat&& m) +: flags(m.flags), dims(m.dims), rows(m.rows), cols(m.cols), allocator(m.allocator), + usageFlags(m.usageFlags), u(m.u), offset(m.offset), size(&rows) +{ + if (m.dims <= 2) // move new step/size info + { + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + { + CV_DbgAssert(m.step.p != m.step.buf); + step.p = m.step.p; + size.p = m.size.p; + m.step.p = m.step.buf; + m.size.p = &m.rows; + } + m.flags = MAGIC_VAL; m.dims = m.rows = m.cols = 0; + m.allocator = NULL; + m.u = NULL; + m.offset = 0; +} + +inline +UMat& UMat::operator = (UMat&& m) +{ + if (this == &m) + return *this; + release(); + flags = m.flags; dims = m.dims; rows = m.rows; cols = m.cols; + allocator = m.allocator; usageFlags = m.usageFlags; + u = m.u; + offset = m.offset; + if (step.p != step.buf) // release self step/size + { + fastFree(step.p); + step.p = step.buf; + size.p = &rows; + } + if (m.dims <= 2) // move new step/size info + { + step[0] = m.step[0]; + step[1] = m.step[1]; + } + else + { + CV_DbgAssert(m.step.p != m.step.buf); + step.p = m.step.p; + size.p = m.size.p; + m.step.p = m.step.buf; + m.size.p = &m.rows; + } + m.flags = MAGIC_VAL; m.dims = m.rows = m.cols = 0; + m.allocator = NULL; + m.u = NULL; + m.offset = 0; + return *this; +} + +#endif + + +inline bool UMatData::hostCopyObsolete() const { return (flags & HOST_COPY_OBSOLETE) != 0; } +inline bool UMatData::deviceCopyObsolete() const { return (flags & DEVICE_COPY_OBSOLETE) != 0; } +inline bool UMatData::deviceMemMapped() const { return (flags & DEVICE_MEM_MAPPED) != 0; } +inline bool UMatData::copyOnMap() const { return (flags & COPY_ON_MAP) != 0; } +inline bool UMatData::tempUMat() const { return (flags & TEMP_UMAT) != 0; } +inline bool UMatData::tempCopiedUMat() const { return (flags & TEMP_COPIED_UMAT) == TEMP_COPIED_UMAT; } + +inline void UMatData::markDeviceMemMapped(bool flag) +{ + if(flag) + flags |= DEVICE_MEM_MAPPED; + else + flags &= ~DEVICE_MEM_MAPPED; +} + +inline void UMatData::markHostCopyObsolete(bool flag) +{ + if(flag) + flags |= HOST_COPY_OBSOLETE; + else + flags &= ~HOST_COPY_OBSOLETE; +} +inline void UMatData::markDeviceCopyObsolete(bool flag) +{ + if(flag) + flags |= DEVICE_COPY_OBSOLETE; + else + flags &= ~DEVICE_COPY_OBSOLETE; +} + +//! @endcond + +} //cv + +#ifdef _MSC_VER +#pragma warning( pop ) +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/matx.hpp b/3rdparty/opencv/include/opencv2/core/matx.hpp new file mode 100644 index 00000000..d8e17e70 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/matx.hpp @@ -0,0 +1,1477 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_MATX_HPP +#define OPENCV_CORE_MATX_HPP + +#ifndef __cplusplus +# error matx.hpp header must be compiled as C++ +#endif + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/base.hpp" +#include "opencv2/core/traits.hpp" +#include "opencv2/core/saturate.hpp" + +#ifdef CV_CXX11 +#include +#endif + +namespace cv +{ + +//! @addtogroup core_basic +//! @{ + +////////////////////////////// Small Matrix /////////////////////////// + +//! @cond IGNORED +// FIXIT Remove this (especially CV_EXPORTS modifier) +struct CV_EXPORTS Matx_AddOp { Matx_AddOp() {} Matx_AddOp(const Matx_AddOp&) {} }; +struct CV_EXPORTS Matx_SubOp { Matx_SubOp() {} Matx_SubOp(const Matx_SubOp&) {} }; +struct CV_EXPORTS Matx_ScaleOp { Matx_ScaleOp() {} Matx_ScaleOp(const Matx_ScaleOp&) {} }; +struct CV_EXPORTS Matx_MulOp { Matx_MulOp() {} Matx_MulOp(const Matx_MulOp&) {} }; +struct CV_EXPORTS Matx_DivOp { Matx_DivOp() {} Matx_DivOp(const Matx_DivOp&) {} }; +struct CV_EXPORTS Matx_MatMulOp { Matx_MatMulOp() {} Matx_MatMulOp(const Matx_MatMulOp&) {} }; +struct CV_EXPORTS Matx_TOp { Matx_TOp() {} Matx_TOp(const Matx_TOp&) {} }; +//! @endcond + +/** @brief Template class for small matrices whose type and size are known at compilation time + +If you need a more flexible type, use Mat . The elements of the matrix M are accessible using the +M(i,j) notation. Most of the common matrix operations (see also @ref MatrixExpressions ) are +available. To do an operation on Matx that is not implemented, you can easily convert the matrix to +Mat and backwards: +@code{.cpp} + Matx33f m(1, 2, 3, + 4, 5, 6, + 7, 8, 9); + cout << sum(Mat(m*m.t())) << endl; +@endcode +Except of the plain constructor which takes a list of elements, Matx can be initialized from a C-array: +@code{.cpp} + float values[] = { 1, 2, 3}; + Matx31f m(values); +@endcode +In case if C++11 features are available, std::initializer_list can be also used to initialize Matx: +@code{.cpp} + Matx31f m = { 1, 2, 3}; +@endcode + */ +template class Matx +{ +public: + enum { + rows = m, + cols = n, + channels = rows*cols, +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + depth = traits::Type<_Tp>::value, + type = CV_MAKETYPE(depth, channels), +#endif + shortdim = (m < n ? m : n) + }; + + typedef _Tp value_type; + typedef Matx<_Tp, m, n> mat_type; + typedef Matx<_Tp, shortdim, 1> diag_type; + + //! default constructor + Matx(); + + explicit Matx(_Tp v0); //!< 1x1 matrix + Matx(_Tp v0, _Tp v1); //!< 1x2 or 2x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2); //!< 1x3 or 3x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3); //!< 1x4, 2x2 or 4x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4); //!< 1x5 or 5x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5); //!< 1x6, 2x3, 3x2 or 6x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6); //!< 1x7 or 7x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7); //!< 1x8, 2x4, 4x2 or 8x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8); //!< 1x9, 3x3 or 9x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9); //!< 1x10, 2x5 or 5x2 or 10x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, + _Tp v4, _Tp v5, _Tp v6, _Tp v7, + _Tp v8, _Tp v9, _Tp v10, _Tp v11); //!< 1x12, 2x6, 3x4, 4x3, 6x2 or 12x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, + _Tp v4, _Tp v5, _Tp v6, _Tp v7, + _Tp v8, _Tp v9, _Tp v10, _Tp v11, + _Tp v12, _Tp v13); //!< 1x14, 2x7, 7x2 or 14x1 matrix + Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, + _Tp v4, _Tp v5, _Tp v6, _Tp v7, + _Tp v8, _Tp v9, _Tp v10, _Tp v11, + _Tp v12, _Tp v13, _Tp v14, _Tp v15); //!< 1x16, 4x4 or 16x1 matrix + explicit Matx(const _Tp* vals); //!< initialize from a plain array + +#ifdef CV_CXX11 + Matx(std::initializer_list<_Tp>); //!< initialize from an initializer list +#endif + + static Matx all(_Tp alpha); + static Matx zeros(); + static Matx ones(); + static Matx eye(); + static Matx diag(const diag_type& d); + static Matx randu(_Tp a, _Tp b); + static Matx randn(_Tp a, _Tp b); + + //! dot product computed with the default precision + _Tp dot(const Matx<_Tp, m, n>& v) const; + + //! dot product computed in double-precision arithmetics + double ddot(const Matx<_Tp, m, n>& v) const; + + //! conversion to another data type + template operator Matx() const; + + //! change the matrix shape + template Matx<_Tp, m1, n1> reshape() const; + + //! extract part of the matrix + template Matx<_Tp, m1, n1> get_minor(int base_row, int base_col) const; + + //! extract the matrix row + Matx<_Tp, 1, n> row(int i) const; + + //! extract the matrix column + Matx<_Tp, m, 1> col(int i) const; + + //! extract the matrix diagonal + diag_type diag() const; + + //! transpose the matrix + Matx<_Tp, n, m> t() const; + + //! invert the matrix + Matx<_Tp, n, m> inv(int method=DECOMP_LU, bool *p_is_ok = NULL) const; + + //! solve linear system + template Matx<_Tp, n, l> solve(const Matx<_Tp, m, l>& rhs, int flags=DECOMP_LU) const; + Vec<_Tp, n> solve(const Vec<_Tp, m>& rhs, int method) const; + + //! multiply two matrices element-wise + Matx<_Tp, m, n> mul(const Matx<_Tp, m, n>& a) const; + + //! divide two matrices element-wise + Matx<_Tp, m, n> div(const Matx<_Tp, m, n>& a) const; + + //! element access + const _Tp& operator ()(int row, int col) const; + _Tp& operator ()(int row, int col); + + //! 1D element access + const _Tp& operator ()(int i) const; + _Tp& operator ()(int i); + + Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_AddOp); + Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_SubOp); + template Matx(const Matx<_Tp, m, n>& a, _T2 alpha, Matx_ScaleOp); + Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_MulOp); + Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_DivOp); + template Matx(const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b, Matx_MatMulOp); + Matx(const Matx<_Tp, n, m>& a, Matx_TOp); + + _Tp val[m*n]; //< matrix elements +}; + +typedef Matx Matx12f; +typedef Matx Matx12d; +typedef Matx Matx13f; +typedef Matx Matx13d; +typedef Matx Matx14f; +typedef Matx Matx14d; +typedef Matx Matx16f; +typedef Matx Matx16d; + +typedef Matx Matx21f; +typedef Matx Matx21d; +typedef Matx Matx31f; +typedef Matx Matx31d; +typedef Matx Matx41f; +typedef Matx Matx41d; +typedef Matx Matx61f; +typedef Matx Matx61d; + +typedef Matx Matx22f; +typedef Matx Matx22d; +typedef Matx Matx23f; +typedef Matx Matx23d; +typedef Matx Matx32f; +typedef Matx Matx32d; + +typedef Matx Matx33f; +typedef Matx Matx33d; + +typedef Matx Matx34f; +typedef Matx Matx34d; +typedef Matx Matx43f; +typedef Matx Matx43d; + +typedef Matx Matx44f; +typedef Matx Matx44d; +typedef Matx Matx66f; +typedef Matx Matx66d; + +/*! + traits +*/ +template class DataType< Matx<_Tp, m, n> > +{ +public: + typedef Matx<_Tp, m, n> value_type; + typedef Matx::work_type, m, n> work_type; + typedef _Tp channel_type; + typedef value_type vec_type; + + enum { generic_type = 0, + channels = m * n, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; +}; + +namespace traits { +template +struct Depth< Matx<_Tp, m, n> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Matx<_Tp, m, n> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, n*m) }; }; +} // namespace + + +/** @brief Comma-separated Matrix Initializer +*/ +template class MatxCommaInitializer +{ +public: + MatxCommaInitializer(Matx<_Tp, m, n>* _mtx); + template MatxCommaInitializer<_Tp, m, n>& operator , (T2 val); + Matx<_Tp, m, n> operator *() const; + + Matx<_Tp, m, n>* dst; + int idx; +}; + +/* + Utility methods +*/ +template static double determinant(const Matx<_Tp, m, m>& a); +template static double trace(const Matx<_Tp, m, n>& a); +template static double norm(const Matx<_Tp, m, n>& M); +template static double norm(const Matx<_Tp, m, n>& M, int normType); + + + +/////////////////////// Vec (used as element of multi-channel images ///////////////////// + +/** @brief Template class for short numerical vectors, a partial case of Matx + +This template class represents short numerical vectors (of 1, 2, 3, 4 ... elements) on which you +can perform basic arithmetical operations, access individual elements using [] operator etc. The +vectors are allocated on stack, as opposite to std::valarray, std::vector, cv::Mat etc., which +elements are dynamically allocated in the heap. + +The template takes 2 parameters: +@tparam _Tp element type +@tparam cn the number of elements + +In addition to the universal notation like Vec, you can use shorter aliases +for the most popular specialized variants of Vec, e.g. Vec3f ~ Vec. + +It is possible to convert Vec\ to/from Point_, Vec\ to/from Point3_ , and Vec\ +to CvScalar or Scalar_. Use operator[] to access the elements of Vec. + +All the expected vector operations are also implemented: +- v1 = v2 + v3 +- v1 = v2 - v3 +- v1 = v2 \* scale +- v1 = scale \* v2 +- v1 = -v2 +- v1 += v2 and other augmenting operations +- v1 == v2, v1 != v2 +- norm(v1) (euclidean norm) +The Vec class is commonly used to describe pixel types of multi-channel arrays. See Mat for details. +*/ +template class Vec : public Matx<_Tp, cn, 1> +{ +public: + typedef _Tp value_type; + enum { + channels = cn, +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + depth = Matx<_Tp, cn, 1>::depth, + type = CV_MAKETYPE(depth, channels), +#endif + _dummy_enum_finalizer = 0 + }; + + //! default constructor + Vec(); + + Vec(_Tp v0); //!< 1-element vector constructor + Vec(_Tp v0, _Tp v1); //!< 2-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2); //!< 3-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3); //!< 4-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4); //!< 5-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5); //!< 6-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6); //!< 7-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7); //!< 8-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8); //!< 9-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9); //!< 10-element vector constructor + Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13); //!< 14-element vector constructor + explicit Vec(const _Tp* values); + +#ifdef CV_CXX11 + Vec(std::initializer_list<_Tp>); +#endif + + Vec(const Vec<_Tp, cn>& v); + + static Vec all(_Tp alpha); + + //! per-element multiplication + Vec mul(const Vec<_Tp, cn>& v) const; + + //! conjugation (makes sense for complex numbers and quaternions) + Vec conj() const; + + /*! + cross product of the two 3D vectors. + + For other dimensionalities the exception is raised + */ + Vec cross(const Vec& v) const; + //! conversion to another data type + template operator Vec() const; + + /*! element access */ + const _Tp& operator [](int i) const; + _Tp& operator[](int i); + const _Tp& operator ()(int i) const; + _Tp& operator ()(int i); + + Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_AddOp); + Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_SubOp); + template Vec(const Matx<_Tp, cn, 1>& a, _T2 alpha, Matx_ScaleOp); +}; + +/** @name Shorter aliases for the most popular specializations of Vec + @{ +*/ +typedef Vec Vec2b; +typedef Vec Vec3b; +typedef Vec Vec4b; + +typedef Vec Vec2s; +typedef Vec Vec3s; +typedef Vec Vec4s; + +typedef Vec Vec2w; +typedef Vec Vec3w; +typedef Vec Vec4w; + +typedef Vec Vec2i; +typedef Vec Vec3i; +typedef Vec Vec4i; +typedef Vec Vec6i; +typedef Vec Vec8i; + +typedef Vec Vec2f; +typedef Vec Vec3f; +typedef Vec Vec4f; +typedef Vec Vec6f; + +typedef Vec Vec2d; +typedef Vec Vec3d; +typedef Vec Vec4d; +typedef Vec Vec6d; +/** @} */ + +/*! + traits +*/ +template class DataType< Vec<_Tp, cn> > +{ +public: + typedef Vec<_Tp, cn> value_type; + typedef Vec::work_type, cn> work_type; + typedef _Tp channel_type; + typedef value_type vec_type; + + enum { generic_type = 0, + channels = cn, + fmt = DataType::fmt + ((channels - 1) << 8), +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + depth = DataType::depth, + type = CV_MAKETYPE(depth, channels), +#endif + _dummy_enum_finalizer = 0 + }; +}; + +namespace traits { +template +struct Depth< Vec<_Tp, cn> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Vec<_Tp, cn> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, cn) }; }; +} // namespace + + +/** @brief Comma-separated Vec Initializer +*/ +template class VecCommaInitializer : public MatxCommaInitializer<_Tp, m, 1> +{ +public: + VecCommaInitializer(Vec<_Tp, m>* _vec); + template VecCommaInitializer<_Tp, m>& operator , (T2 val); + Vec<_Tp, m> operator *() const; +}; + +template static Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v); + +//! @} core_basic + +//! @cond IGNORED + +///////////////////////////////////// helper classes ///////////////////////////////////// +namespace internal +{ + +template struct Matx_DetOp +{ + double operator ()(const Matx<_Tp, m, m>& a) const + { + Matx<_Tp, m, m> temp = a; + double p = LU(temp.val, m*sizeof(_Tp), m, 0, 0, 0); + if( p == 0 ) + return p; + for( int i = 0; i < m; i++ ) + p *= temp(i, i); + return p; + } +}; + +template struct Matx_DetOp<_Tp, 1> +{ + double operator ()(const Matx<_Tp, 1, 1>& a) const + { + return a(0,0); + } +}; + +template struct Matx_DetOp<_Tp, 2> +{ + double operator ()(const Matx<_Tp, 2, 2>& a) const + { + return a(0,0)*a(1,1) - a(0,1)*a(1,0); + } +}; + +template struct Matx_DetOp<_Tp, 3> +{ + double operator ()(const Matx<_Tp, 3, 3>& a) const + { + return a(0,0)*(a(1,1)*a(2,2) - a(2,1)*a(1,2)) - + a(0,1)*(a(1,0)*a(2,2) - a(2,0)*a(1,2)) + + a(0,2)*(a(1,0)*a(2,1) - a(2,0)*a(1,1)); + } +}; + +template Vec<_Tp, 2> inline conjugate(const Vec<_Tp, 2>& v) +{ + return Vec<_Tp, 2>(v[0], -v[1]); +} + +template Vec<_Tp, 4> inline conjugate(const Vec<_Tp, 4>& v) +{ + return Vec<_Tp, 4>(v[0], -v[1], -v[2], -v[3]); +} + +} // internal + + + +////////////////////////////////// Matx Implementation /////////////////////////////////// + +template inline +Matx<_Tp, m, n>::Matx() +{ + for(int i = 0; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0) +{ + val[0] = v0; + for(int i = 1; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1) +{ + CV_StaticAssert(channels >= 2, "Matx should have at least 2 elements."); + val[0] = v0; val[1] = v1; + for(int i = 2; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2) +{ + CV_StaticAssert(channels >= 3, "Matx should have at least 3 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; + for(int i = 3; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3) +{ + CV_StaticAssert(channels >= 4, "Matx should have at least 4 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + for(int i = 4; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4) +{ + CV_StaticAssert(channels >= 5, "Matx should have at least 5 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; val[4] = v4; + for(int i = 5; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5) +{ + CV_StaticAssert(channels >= 6, "Matx should have at least 6 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; + for(int i = 6; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6) +{ + CV_StaticAssert(channels >= 7, "Matx should have at least 7 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; + for(int i = 7; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7) +{ + CV_StaticAssert(channels >= 8, "Matx should have at least 8 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + for(int i = 8; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8) +{ + CV_StaticAssert(channels >= 9, "Matx should have at least 9 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + val[8] = v8; + for(int i = 9; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9) +{ + CV_StaticAssert(channels >= 10, "Matx should have at least 10 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + val[8] = v8; val[9] = v9; + for(int i = 10; i < channels; i++) val[i] = _Tp(0); +} + + +template inline +Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11) +{ + CV_StaticAssert(channels >= 12, "Matx should have at least 12 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11; + for(int i = 12; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13) +{ + CV_StaticAssert(channels >= 14, "Matx should have at least 14 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11; + val[12] = v12; val[13] = v13; + for (int i = 14; i < channels; i++) val[i] = _Tp(0); +} + + +template inline +Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13, _Tp v14, _Tp v15) +{ + CV_StaticAssert(channels >= 16, "Matx should have at least 16 elements."); + val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; + val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7; + val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11; + val[12] = v12; val[13] = v13; val[14] = v14; val[15] = v15; + for(int i = 16; i < channels; i++) val[i] = _Tp(0); +} + +template inline +Matx<_Tp, m, n>::Matx(const _Tp* values) +{ + for( int i = 0; i < channels; i++ ) val[i] = values[i]; +} + +#ifdef CV_CXX11 +template inline +Matx<_Tp, m, n>::Matx(std::initializer_list<_Tp> list) +{ + CV_DbgAssert(list.size() == channels); + int i = 0; + for(const auto& elem : list) + { + val[i++] = elem; + } +} +#endif + +template inline +Matx<_Tp, m, n> Matx<_Tp, m, n>::all(_Tp alpha) +{ + Matx<_Tp, m, n> M; + for( int i = 0; i < m*n; i++ ) M.val[i] = alpha; + return M; +} + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::zeros() +{ + return all(0); +} + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::ones() +{ + return all(1); +} + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::eye() +{ + Matx<_Tp,m,n> M; + for(int i = 0; i < shortdim; i++) + M(i,i) = 1; + return M; +} + +template inline +_Tp Matx<_Tp, m, n>::dot(const Matx<_Tp, m, n>& M) const +{ + _Tp s = 0; + for( int i = 0; i < channels; i++ ) s += val[i]*M.val[i]; + return s; +} + +template inline +double Matx<_Tp, m, n>::ddot(const Matx<_Tp, m, n>& M) const +{ + double s = 0; + for( int i = 0; i < channels; i++ ) s += (double)val[i]*M.val[i]; + return s; +} + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::diag(const typename Matx<_Tp,m,n>::diag_type& d) +{ + Matx<_Tp,m,n> M; + for(int i = 0; i < shortdim; i++) + M(i,i) = d(i, 0); + return M; +} + +template template +inline Matx<_Tp, m, n>::operator Matx() const +{ + Matx M; + for( int i = 0; i < m*n; i++ ) M.val[i] = saturate_cast(val[i]); + return M; +} + +template template inline +Matx<_Tp, m1, n1> Matx<_Tp, m, n>::reshape() const +{ + CV_StaticAssert(m1*n1 == m*n, "Input and destnarion matrices must have the same number of elements"); + return (const Matx<_Tp, m1, n1>&)*this; +} + +template +template inline +Matx<_Tp, m1, n1> Matx<_Tp, m, n>::get_minor(int base_row, int base_col) const +{ + CV_DbgAssert(0 <= base_row && base_row+m1 <= m && 0 <= base_col && base_col+n1 <= n); + Matx<_Tp, m1, n1> s; + for( int di = 0; di < m1; di++ ) + for( int dj = 0; dj < n1; dj++ ) + s(di, dj) = (*this)(base_row+di, base_col+dj); + return s; +} + +template inline +Matx<_Tp, 1, n> Matx<_Tp, m, n>::row(int i) const +{ + CV_DbgAssert((unsigned)i < (unsigned)m); + return Matx<_Tp, 1, n>(&val[i*n]); +} + +template inline +Matx<_Tp, m, 1> Matx<_Tp, m, n>::col(int j) const +{ + CV_DbgAssert((unsigned)j < (unsigned)n); + Matx<_Tp, m, 1> v; + for( int i = 0; i < m; i++ ) + v.val[i] = val[i*n + j]; + return v; +} + +template inline +typename Matx<_Tp, m, n>::diag_type Matx<_Tp, m, n>::diag() const +{ + diag_type d; + for( int i = 0; i < shortdim; i++ ) + d.val[i] = val[i*n + i]; + return d; +} + +template inline +const _Tp& Matx<_Tp, m, n>::operator()(int row_idx, int col_idx) const +{ + CV_DbgAssert( (unsigned)row_idx < (unsigned)m && (unsigned)col_idx < (unsigned)n ); + return this->val[row_idx*n + col_idx]; +} + +template inline +_Tp& Matx<_Tp, m, n>::operator ()(int row_idx, int col_idx) +{ + CV_DbgAssert( (unsigned)row_idx < (unsigned)m && (unsigned)col_idx < (unsigned)n ); + return val[row_idx*n + col_idx]; +} + +template inline +const _Tp& Matx<_Tp, m, n>::operator ()(int i) const +{ + CV_StaticAssert(m == 1 || n == 1, "Single index indexation requires matrix to be a column or a row"); + CV_DbgAssert( (unsigned)i < (unsigned)(m+n-1) ); + return val[i]; +} + +template inline +_Tp& Matx<_Tp, m, n>::operator ()(int i) +{ + CV_StaticAssert(m == 1 || n == 1, "Single index indexation requires matrix to be a column or a row"); + CV_DbgAssert( (unsigned)i < (unsigned)(m+n-1) ); + return val[i]; +} + +template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_AddOp) +{ + for( int i = 0; i < channels; i++ ) + val[i] = saturate_cast<_Tp>(a.val[i] + b.val[i]); +} + +template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_SubOp) +{ + for( int i = 0; i < channels; i++ ) + val[i] = saturate_cast<_Tp>(a.val[i] - b.val[i]); +} + +template template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, _T2 alpha, Matx_ScaleOp) +{ + for( int i = 0; i < channels; i++ ) + val[i] = saturate_cast<_Tp>(a.val[i] * alpha); +} + +template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_MulOp) +{ + for( int i = 0; i < channels; i++ ) + val[i] = saturate_cast<_Tp>(a.val[i] * b.val[i]); +} + +template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_DivOp) +{ + for( int i = 0; i < channels; i++ ) + val[i] = saturate_cast<_Tp>(a.val[i] / b.val[i]); +} + +template template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b, Matx_MatMulOp) +{ + for( int i = 0; i < m; i++ ) + for( int j = 0; j < n; j++ ) + { + _Tp s = 0; + for( int k = 0; k < l; k++ ) + s += a(i, k) * b(k, j); + val[i*n + j] = s; + } +} + +template inline +Matx<_Tp,m,n>::Matx(const Matx<_Tp, n, m>& a, Matx_TOp) +{ + for( int i = 0; i < m; i++ ) + for( int j = 0; j < n; j++ ) + val[i*n + j] = a(j, i); +} + +template inline +Matx<_Tp, m, n> Matx<_Tp, m, n>::mul(const Matx<_Tp, m, n>& a) const +{ + return Matx<_Tp, m, n>(*this, a, Matx_MulOp()); +} + +template inline +Matx<_Tp, m, n> Matx<_Tp, m, n>::div(const Matx<_Tp, m, n>& a) const +{ + return Matx<_Tp, m, n>(*this, a, Matx_DivOp()); +} + +template inline +Matx<_Tp, n, m> Matx<_Tp, m, n>::t() const +{ + return Matx<_Tp, n, m>(*this, Matx_TOp()); +} + +template inline +Vec<_Tp, n> Matx<_Tp, m, n>::solve(const Vec<_Tp, m>& rhs, int method) const +{ + Matx<_Tp, n, 1> x = solve((const Matx<_Tp, m, 1>&)(rhs), method); + return (Vec<_Tp, n>&)(x); +} + +template static inline +double determinant(const Matx<_Tp, m, m>& a) +{ + return cv::internal::Matx_DetOp<_Tp, m>()(a); +} + +template static inline +double trace(const Matx<_Tp, m, n>& a) +{ + _Tp s = 0; + for( int i = 0; i < std::min(m, n); i++ ) + s += a(i,i); + return s; +} + +template static inline +double norm(const Matx<_Tp, m, n>& M) +{ + return std::sqrt(normL2Sqr<_Tp, double>(M.val, m*n)); +} + +template static inline +double norm(const Matx<_Tp, m, n>& M, int normType) +{ + switch(normType) { + case NORM_INF: + return (double)normInf<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n); + case NORM_L1: + return (double)normL1<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n); + case NORM_L2SQR: + return (double)normL2Sqr<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n); + default: + case NORM_L2: + return std::sqrt((double)normL2Sqr<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n)); + } +} + + + +//////////////////////////////// matx comma initializer ////////////////////////////////// + +template static inline +MatxCommaInitializer<_Tp, m, n> operator << (const Matx<_Tp, m, n>& mtx, _T2 val) +{ + MatxCommaInitializer<_Tp, m, n> commaInitializer((Matx<_Tp, m, n>*)&mtx); + return (commaInitializer, val); +} + +template inline +MatxCommaInitializer<_Tp, m, n>::MatxCommaInitializer(Matx<_Tp, m, n>* _mtx) + : dst(_mtx), idx(0) +{} + +template template inline +MatxCommaInitializer<_Tp, m, n>& MatxCommaInitializer<_Tp, m, n>::operator , (_T2 value) +{ + CV_DbgAssert( idx < m*n ); + dst->val[idx++] = saturate_cast<_Tp>(value); + return *this; +} + +template inline +Matx<_Tp, m, n> MatxCommaInitializer<_Tp, m, n>::operator *() const +{ + CV_DbgAssert( idx == n*m ); + return *dst; +} + + + +/////////////////////////////////// Vec Implementation /////////////////////////////////// + +template inline +Vec<_Tp, cn>::Vec() {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0) + : Matx<_Tp, cn, 1>(v0) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1) + : Matx<_Tp, cn, 1>(v0, v1) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2) + : Matx<_Tp, cn, 1>(v0, v1, v2) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9) {} + +template inline +Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13) + : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13) {} + +template inline +Vec<_Tp, cn>::Vec(const _Tp* values) + : Matx<_Tp, cn, 1>(values) {} + +#ifdef CV_CXX11 +template inline +Vec<_Tp, cn>::Vec(std::initializer_list<_Tp> list) + : Matx<_Tp, cn, 1>(list) {} +#endif + +template inline +Vec<_Tp, cn>::Vec(const Vec<_Tp, cn>& m) + : Matx<_Tp, cn, 1>(m.val) {} + +template inline +Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_AddOp op) + : Matx<_Tp, cn, 1>(a, b, op) {} + +template inline +Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_SubOp op) + : Matx<_Tp, cn, 1>(a, b, op) {} + +template template inline +Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, _T2 alpha, Matx_ScaleOp op) + : Matx<_Tp, cn, 1>(a, alpha, op) {} + +template inline +Vec<_Tp, cn> Vec<_Tp, cn>::all(_Tp alpha) +{ + Vec v; + for( int i = 0; i < cn; i++ ) v.val[i] = alpha; + return v; +} + +template inline +Vec<_Tp, cn> Vec<_Tp, cn>::mul(const Vec<_Tp, cn>& v) const +{ + Vec<_Tp, cn> w; + for( int i = 0; i < cn; i++ ) w.val[i] = saturate_cast<_Tp>(this->val[i]*v.val[i]); + return w; +} + +template<> inline +Vec Vec::conj() const +{ + return cv::internal::conjugate(*this); +} + +template<> inline +Vec Vec::conj() const +{ + return cv::internal::conjugate(*this); +} + +template<> inline +Vec Vec::conj() const +{ + return cv::internal::conjugate(*this); +} + +template<> inline +Vec Vec::conj() const +{ + return cv::internal::conjugate(*this); +} + +template inline +Vec<_Tp, cn> Vec<_Tp, cn>::cross(const Vec<_Tp, cn>&) const +{ + CV_StaticAssert(cn == 3, "for arbitrary-size vector there is no cross-product defined"); + return Vec<_Tp, cn>(); +} + +template<> inline +Vec Vec::cross(const Vec& v) const +{ + return Vec(this->val[1]*v.val[2] - this->val[2]*v.val[1], + this->val[2]*v.val[0] - this->val[0]*v.val[2], + this->val[0]*v.val[1] - this->val[1]*v.val[0]); +} + +template<> inline +Vec Vec::cross(const Vec& v) const +{ + return Vec(this->val[1]*v.val[2] - this->val[2]*v.val[1], + this->val[2]*v.val[0] - this->val[0]*v.val[2], + this->val[0]*v.val[1] - this->val[1]*v.val[0]); +} + +template template inline +Vec<_Tp, cn>::operator Vec() const +{ + Vec v; + for( int i = 0; i < cn; i++ ) v.val[i] = saturate_cast(this->val[i]); + return v; +} + +template inline +const _Tp& Vec<_Tp, cn>::operator [](int i) const +{ + CV_DbgAssert( (unsigned)i < (unsigned)cn ); + return this->val[i]; +} + +template inline +_Tp& Vec<_Tp, cn>::operator [](int i) +{ + CV_DbgAssert( (unsigned)i < (unsigned)cn ); + return this->val[i]; +} + +template inline +const _Tp& Vec<_Tp, cn>::operator ()(int i) const +{ + CV_DbgAssert( (unsigned)i < (unsigned)cn ); + return this->val[i]; +} + +template inline +_Tp& Vec<_Tp, cn>::operator ()(int i) +{ + CV_DbgAssert( (unsigned)i < (unsigned)cn ); + return this->val[i]; +} + +template inline +Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v) +{ + double nv = norm(v); + return v * (nv ? 1./nv : 0.); +} + + + +//////////////////////////////// vec comma initializer ////////////////////////////////// + + +template static inline +VecCommaInitializer<_Tp, cn> operator << (const Vec<_Tp, cn>& vec, _T2 val) +{ + VecCommaInitializer<_Tp, cn> commaInitializer((Vec<_Tp, cn>*)&vec); + return (commaInitializer, val); +} + +template inline +VecCommaInitializer<_Tp, cn>::VecCommaInitializer(Vec<_Tp, cn>* _vec) + : MatxCommaInitializer<_Tp, cn, 1>(_vec) +{} + +template template inline +VecCommaInitializer<_Tp, cn>& VecCommaInitializer<_Tp, cn>::operator , (_T2 value) +{ + CV_DbgAssert( this->idx < cn ); + this->dst->val[this->idx++] = saturate_cast<_Tp>(value); + return *this; +} + +template inline +Vec<_Tp, cn> VecCommaInitializer<_Tp, cn>::operator *() const +{ + CV_DbgAssert( this->idx == cn ); + return *this->dst; +} + +//! @endcond + +///////////////////////////// Matx out-of-class operators //////////////////////////////// + +//! @relates cv::Matx +//! @{ + +template static inline +Matx<_Tp1, m, n>& operator += (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b) +{ + for( int i = 0; i < m*n; i++ ) + a.val[i] = saturate_cast<_Tp1>(a.val[i] + b.val[i]); + return a; +} + +template static inline +Matx<_Tp1, m, n>& operator -= (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b) +{ + for( int i = 0; i < m*n; i++ ) + a.val[i] = saturate_cast<_Tp1>(a.val[i] - b.val[i]); + return a; +} + +template static inline +Matx<_Tp, m, n> operator + (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b) +{ + return Matx<_Tp, m, n>(a, b, Matx_AddOp()); +} + +template static inline +Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b) +{ + return Matx<_Tp, m, n>(a, b, Matx_SubOp()); +} + +template static inline +Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, int alpha) +{ + for( int i = 0; i < m*n; i++ ) + a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha); + return a; +} + +template static inline +Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, float alpha) +{ + for( int i = 0; i < m*n; i++ ) + a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha); + return a; +} + +template static inline +Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, double alpha) +{ + for( int i = 0; i < m*n; i++ ) + a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha); + return a; +} + +template static inline +Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, int alpha) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, float alpha) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, double alpha) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (int alpha, const Matx<_Tp, m, n>& a) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (float alpha, const Matx<_Tp, m, n>& a) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (double alpha, const Matx<_Tp, m, n>& a) +{ + return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a) +{ + return Matx<_Tp, m, n>(a, -1, Matx_ScaleOp()); +} + +template static inline +Matx<_Tp, m, n> operator * (const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b) +{ + return Matx<_Tp, m, n>(a, b, Matx_MatMulOp()); +} + +template static inline +Vec<_Tp, m> operator * (const Matx<_Tp, m, n>& a, const Vec<_Tp, n>& b) +{ + Matx<_Tp, m, 1> c(a, b, Matx_MatMulOp()); + return (const Vec<_Tp, m>&)(c); +} + +template static inline +bool operator == (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b) +{ + for( int i = 0; i < m*n; i++ ) + if( a.val[i] != b.val[i] ) return false; + return true; +} + +template static inline +bool operator != (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b) +{ + return !(a == b); +} + +//! @} + +////////////////////////////// Vec out-of-class operators //////////////////////////////// + +//! @relates cv::Vec +//! @{ + +template static inline +Vec<_Tp1, cn>& operator += (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b) +{ + for( int i = 0; i < cn; i++ ) + a.val[i] = saturate_cast<_Tp1>(a.val[i] + b.val[i]); + return a; +} + +template static inline +Vec<_Tp1, cn>& operator -= (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b) +{ + for( int i = 0; i < cn; i++ ) + a.val[i] = saturate_cast<_Tp1>(a.val[i] - b.val[i]); + return a; +} + +template static inline +Vec<_Tp, cn> operator + (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b) +{ + return Vec<_Tp, cn>(a, b, Matx_AddOp()); +} + +template static inline +Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b) +{ + return Vec<_Tp, cn>(a, b, Matx_SubOp()); +} + +template static inline +Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, int alpha) +{ + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*alpha); + return a; +} + +template static inline +Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, float alpha) +{ + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*alpha); + return a; +} + +template static inline +Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, double alpha) +{ + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*alpha); + return a; +} + +template static inline +Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, int alpha) +{ + double ialpha = 1./alpha; + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*ialpha); + return a; +} + +template static inline +Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, float alpha) +{ + float ialpha = 1.f/alpha; + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*ialpha); + return a; +} + +template static inline +Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, double alpha) +{ + double ialpha = 1./alpha; + for( int i = 0; i < cn; i++ ) + a[i] = saturate_cast<_Tp>(a[i]*ialpha); + return a; +} + +template static inline +Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, int alpha) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator * (int alpha, const Vec<_Tp, cn>& a) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, float alpha) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator * (float alpha, const Vec<_Tp, cn>& a) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, double alpha) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator * (double alpha, const Vec<_Tp, cn>& a) +{ + return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, int alpha) +{ + return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, float alpha) +{ + return Vec<_Tp, cn>(a, 1.f/alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, double alpha) +{ + return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp()); +} + +template static inline +Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a) +{ + Vec<_Tp,cn> t; + for( int i = 0; i < cn; i++ ) t.val[i] = saturate_cast<_Tp>(-a.val[i]); + return t; +} + +template inline Vec<_Tp, 4> operator * (const Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2) +{ + return Vec<_Tp, 4>(saturate_cast<_Tp>(v1[0]*v2[0] - v1[1]*v2[1] - v1[2]*v2[2] - v1[3]*v2[3]), + saturate_cast<_Tp>(v1[0]*v2[1] + v1[1]*v2[0] + v1[2]*v2[3] - v1[3]*v2[2]), + saturate_cast<_Tp>(v1[0]*v2[2] - v1[1]*v2[3] + v1[2]*v2[0] + v1[3]*v2[1]), + saturate_cast<_Tp>(v1[0]*v2[3] + v1[1]*v2[2] - v1[2]*v2[1] + v1[3]*v2[0])); +} + +template inline Vec<_Tp, 4>& operator *= (Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2) +{ + v1 = v1 * v2; + return v1; +} + +//! @} + +} // cv + +#endif // OPENCV_CORE_MATX_HPP diff --git a/3rdparty/opencv/include/opencv2/core/neon_utils.hpp b/3rdparty/opencv/include/opencv2/core/neon_utils.hpp new file mode 100644 index 00000000..573ba99e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/neon_utils.hpp @@ -0,0 +1,128 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HAL_NEON_UTILS_HPP +#define OPENCV_HAL_NEON_UTILS_HPP + +#include "opencv2/core/cvdef.h" + +//! @addtogroup core_utils_neon +//! @{ + +#if CV_NEON + +inline int32x2_t cv_vrnd_s32_f32(float32x2_t v) +{ + static int32x2_t v_sign = vdup_n_s32(1 << 31), + v_05 = vreinterpret_s32_f32(vdup_n_f32(0.5f)); + + int32x2_t v_addition = vorr_s32(v_05, vand_s32(v_sign, vreinterpret_s32_f32(v))); + return vcvt_s32_f32(vadd_f32(v, vreinterpret_f32_s32(v_addition))); +} + +inline int32x4_t cv_vrndq_s32_f32(float32x4_t v) +{ + static int32x4_t v_sign = vdupq_n_s32(1 << 31), + v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f)); + + int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(v))); + return vcvtq_s32_f32(vaddq_f32(v, vreinterpretq_f32_s32(v_addition))); +} + +inline uint32x2_t cv_vrnd_u32_f32(float32x2_t v) +{ + static float32x2_t v_05 = vdup_n_f32(0.5f); + return vcvt_u32_f32(vadd_f32(v, v_05)); +} + +inline uint32x4_t cv_vrndq_u32_f32(float32x4_t v) +{ + static float32x4_t v_05 = vdupq_n_f32(0.5f); + return vcvtq_u32_f32(vaddq_f32(v, v_05)); +} + +inline float32x4_t cv_vrecpq_f32(float32x4_t val) +{ + float32x4_t reciprocal = vrecpeq_f32(val); + reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal); + reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal); + return reciprocal; +} + +inline float32x2_t cv_vrecp_f32(float32x2_t val) +{ + float32x2_t reciprocal = vrecpe_f32(val); + reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal); + reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal); + return reciprocal; +} + +inline float32x4_t cv_vrsqrtq_f32(float32x4_t val) +{ + float32x4_t e = vrsqrteq_f32(val); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e); + e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e); + return e; +} + +inline float32x2_t cv_vrsqrt_f32(float32x2_t val) +{ + float32x2_t e = vrsqrte_f32(val); + e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e); + e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e); + return e; +} + +inline float32x4_t cv_vsqrtq_f32(float32x4_t val) +{ + return cv_vrecpq_f32(cv_vrsqrtq_f32(val)); +} + +inline float32x2_t cv_vsqrt_f32(float32x2_t val) +{ + return cv_vrecp_f32(cv_vrsqrt_f32(val)); +} + +#endif + +//! @} + +#endif // OPENCV_HAL_NEON_UTILS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/ocl.hpp b/3rdparty/opencv/include/opencv2/core/ocl.hpp new file mode 100644 index 00000000..95f0fcdd --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/ocl.hpp @@ -0,0 +1,843 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OPENCL_HPP +#define OPENCV_OPENCL_HPP + +#include "opencv2/core.hpp" + +namespace cv { namespace ocl { + +//! @addtogroup core_opencl +//! @{ + +CV_EXPORTS_W bool haveOpenCL(); +CV_EXPORTS_W bool useOpenCL(); +CV_EXPORTS_W bool haveAmdBlas(); +CV_EXPORTS_W bool haveAmdFft(); +CV_EXPORTS_W void setUseOpenCL(bool flag); +CV_EXPORTS_W void finish(); + +CV_EXPORTS bool haveSVM(); + +class CV_EXPORTS Context; +class CV_EXPORTS_W_SIMPLE Device; +class CV_EXPORTS Kernel; +class CV_EXPORTS Program; +class CV_EXPORTS ProgramSource; +class CV_EXPORTS Queue; +class CV_EXPORTS PlatformInfo; +class CV_EXPORTS Image2D; + +class CV_EXPORTS_W_SIMPLE Device +{ +public: + CV_WRAP Device(); + explicit Device(void* d); + Device(const Device& d); + Device& operator = (const Device& d); + CV_WRAP ~Device(); + + void set(void* d); + + enum + { + TYPE_DEFAULT = (1 << 0), + TYPE_CPU = (1 << 1), + TYPE_GPU = (1 << 2), + TYPE_ACCELERATOR = (1 << 3), + TYPE_DGPU = TYPE_GPU + (1 << 16), + TYPE_IGPU = TYPE_GPU + (1 << 17), + TYPE_ALL = 0xFFFFFFFF + }; + + CV_WRAP String name() const; + CV_WRAP String extensions() const; + CV_WRAP bool isExtensionSupported(const String& extensionName) const; + CV_WRAP String version() const; + CV_WRAP String vendorName() const; + CV_WRAP String OpenCL_C_Version() const; + CV_WRAP String OpenCLVersion() const; + CV_WRAP int deviceVersionMajor() const; + CV_WRAP int deviceVersionMinor() const; + CV_WRAP String driverVersion() const; + void* ptr() const; + + CV_WRAP int type() const; + + CV_WRAP int addressBits() const; + CV_WRAP bool available() const; + CV_WRAP bool compilerAvailable() const; + CV_WRAP bool linkerAvailable() const; + + enum + { + FP_DENORM=(1 << 0), + FP_INF_NAN=(1 << 1), + FP_ROUND_TO_NEAREST=(1 << 2), + FP_ROUND_TO_ZERO=(1 << 3), + FP_ROUND_TO_INF=(1 << 4), + FP_FMA=(1 << 5), + FP_SOFT_FLOAT=(1 << 6), + FP_CORRECTLY_ROUNDED_DIVIDE_SQRT=(1 << 7) + }; + CV_WRAP int doubleFPConfig() const; + CV_WRAP int singleFPConfig() const; + CV_WRAP int halfFPConfig() const; + + CV_WRAP bool endianLittle() const; + CV_WRAP bool errorCorrectionSupport() const; + + enum + { + EXEC_KERNEL=(1 << 0), + EXEC_NATIVE_KERNEL=(1 << 1) + }; + CV_WRAP int executionCapabilities() const; + + CV_WRAP size_t globalMemCacheSize() const; + + enum + { + NO_CACHE=0, + READ_ONLY_CACHE=1, + READ_WRITE_CACHE=2 + }; + CV_WRAP int globalMemCacheType() const; + CV_WRAP int globalMemCacheLineSize() const; + CV_WRAP size_t globalMemSize() const; + + CV_WRAP size_t localMemSize() const; + enum + { + NO_LOCAL_MEM=0, + LOCAL_IS_LOCAL=1, + LOCAL_IS_GLOBAL=2 + }; + CV_WRAP int localMemType() const; + CV_WRAP bool hostUnifiedMemory() const; + + CV_WRAP bool imageSupport() const; + + CV_WRAP bool imageFromBufferSupport() const; + uint imagePitchAlignment() const; + uint imageBaseAddressAlignment() const; + + /// deprecated, use isExtensionSupported() method (probably with "cl_khr_subgroups" value) + CV_WRAP bool intelSubgroupsSupport() const; + + CV_WRAP size_t image2DMaxWidth() const; + CV_WRAP size_t image2DMaxHeight() const; + + CV_WRAP size_t image3DMaxWidth() const; + CV_WRAP size_t image3DMaxHeight() const; + CV_WRAP size_t image3DMaxDepth() const; + + CV_WRAP size_t imageMaxBufferSize() const; + CV_WRAP size_t imageMaxArraySize() const; + + enum + { + UNKNOWN_VENDOR=0, + VENDOR_AMD=1, + VENDOR_INTEL=2, + VENDOR_NVIDIA=3 + }; + CV_WRAP int vendorID() const; + // FIXIT + // dev.isAMD() doesn't work for OpenCL CPU devices from AMD OpenCL platform. + // This method should use platform name instead of vendor name. + // After fix restore code in arithm.cpp: ocl_compare() + CV_WRAP inline bool isAMD() const { return vendorID() == VENDOR_AMD; } + CV_WRAP inline bool isIntel() const { return vendorID() == VENDOR_INTEL; } + CV_WRAP inline bool isNVidia() const { return vendorID() == VENDOR_NVIDIA; } + + CV_WRAP int maxClockFrequency() const; + CV_WRAP int maxComputeUnits() const; + CV_WRAP int maxConstantArgs() const; + CV_WRAP size_t maxConstantBufferSize() const; + + CV_WRAP size_t maxMemAllocSize() const; + CV_WRAP size_t maxParameterSize() const; + + CV_WRAP int maxReadImageArgs() const; + CV_WRAP int maxWriteImageArgs() const; + CV_WRAP int maxSamplers() const; + + CV_WRAP size_t maxWorkGroupSize() const; + CV_WRAP int maxWorkItemDims() const; + void maxWorkItemSizes(size_t*) const; + + CV_WRAP int memBaseAddrAlign() const; + + CV_WRAP int nativeVectorWidthChar() const; + CV_WRAP int nativeVectorWidthShort() const; + CV_WRAP int nativeVectorWidthInt() const; + CV_WRAP int nativeVectorWidthLong() const; + CV_WRAP int nativeVectorWidthFloat() const; + CV_WRAP int nativeVectorWidthDouble() const; + CV_WRAP int nativeVectorWidthHalf() const; + + CV_WRAP int preferredVectorWidthChar() const; + CV_WRAP int preferredVectorWidthShort() const; + CV_WRAP int preferredVectorWidthInt() const; + CV_WRAP int preferredVectorWidthLong() const; + CV_WRAP int preferredVectorWidthFloat() const; + CV_WRAP int preferredVectorWidthDouble() const; + CV_WRAP int preferredVectorWidthHalf() const; + + CV_WRAP size_t printfBufferSize() const; + CV_WRAP size_t profilingTimerResolution() const; + + CV_WRAP static const Device& getDefault(); + +protected: + struct Impl; + Impl* p; +}; + + +class CV_EXPORTS Context +{ +public: + Context(); + explicit Context(int dtype); + ~Context(); + Context(const Context& c); + Context& operator = (const Context& c); + + bool create(); + bool create(int dtype); + size_t ndevices() const; + const Device& device(size_t idx) const; + Program getProg(const ProgramSource& prog, + const String& buildopt, String& errmsg); + void unloadProg(Program& prog); + + static Context& getDefault(bool initialize = true); + void* ptr() const; + + friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device); + + bool useSVM() const; + void setUseSVM(bool enabled); + + struct Impl; + inline Impl* getImpl() const { return (Impl*)p; } +//protected: + Impl* p; +}; + +class CV_EXPORTS Platform +{ +public: + Platform(); + ~Platform(); + Platform(const Platform& p); + Platform& operator = (const Platform& p); + + void* ptr() const; + static Platform& getDefault(); + + friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device); +protected: + struct Impl; + Impl* p; +}; + +/** @brief Attaches OpenCL context to OpenCV +@note + OpenCV will check if available OpenCL platform has platformName name, then assign context to + OpenCV and call `clRetainContext` function. The deviceID device will be used as target device and + new command queue will be created. +@param platformName name of OpenCL platform to attach, this string is used to check if platform is available to OpenCV at runtime +@param platformID ID of platform attached context was created for +@param context OpenCL context to be attached to OpenCV +@param deviceID ID of device, must be created from attached context +*/ +CV_EXPORTS void attachContext(const String& platformName, void* platformID, void* context, void* deviceID); + +/** @brief Convert OpenCL buffer to UMat +@note + OpenCL buffer (cl_mem_buffer) should contain 2D image data, compatible with OpenCV. Memory + content is not copied from `clBuffer` to UMat. Instead, buffer handle assigned to UMat and + `clRetainMemObject` is called. +@param cl_mem_buffer source clBuffer handle +@param step num of bytes in single row +@param rows number of rows +@param cols number of cols +@param type OpenCV type of image +@param dst destination UMat +*/ +CV_EXPORTS void convertFromBuffer(void* cl_mem_buffer, size_t step, int rows, int cols, int type, UMat& dst); + +/** @brief Convert OpenCL image2d_t to UMat +@note + OpenCL `image2d_t` (cl_mem_image), should be compatible with OpenCV UMat formats. Memory content + is copied from image to UMat with `clEnqueueCopyImageToBuffer` function. +@param cl_mem_image source image2d_t handle +@param dst destination UMat +*/ +CV_EXPORTS void convertFromImage(void* cl_mem_image, UMat& dst); + +// TODO Move to internal header +void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device); + +class CV_EXPORTS Queue +{ +public: + Queue(); + explicit Queue(const Context& c, const Device& d=Device()); + ~Queue(); + Queue(const Queue& q); + Queue& operator = (const Queue& q); + + bool create(const Context& c=Context(), const Device& d=Device()); + void finish(); + void* ptr() const; + static Queue& getDefault(); + + /// @brief Returns OpenCL command queue with enable profiling mode support + const Queue& getProfilingQueue() const; + + struct Impl; friend struct Impl; + inline Impl* getImpl() const { return p; } +protected: + Impl* p; +}; + + +class CV_EXPORTS KernelArg +{ +public: + enum { LOCAL=1, READ_ONLY=2, WRITE_ONLY=4, READ_WRITE=6, CONSTANT=8, PTR_ONLY = 16, NO_SIZE=256 }; + KernelArg(int _flags, UMat* _m, int wscale=1, int iwscale=1, const void* _obj=0, size_t _sz=0); + KernelArg(); + + static KernelArg Local(size_t localMemSize) + { return KernelArg(LOCAL, 0, 1, 1, 0, localMemSize); } + static KernelArg PtrWriteOnly(const UMat& m) + { return KernelArg(PTR_ONLY+WRITE_ONLY, (UMat*)&m); } + static KernelArg PtrReadOnly(const UMat& m) + { return KernelArg(PTR_ONLY+READ_ONLY, (UMat*)&m); } + static KernelArg PtrReadWrite(const UMat& m) + { return KernelArg(PTR_ONLY+READ_WRITE, (UMat*)&m); } + static KernelArg ReadWrite(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(READ_WRITE, (UMat*)&m, wscale, iwscale); } + static KernelArg ReadWriteNoSize(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(READ_WRITE+NO_SIZE, (UMat*)&m, wscale, iwscale); } + static KernelArg ReadOnly(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(READ_ONLY, (UMat*)&m, wscale, iwscale); } + static KernelArg WriteOnly(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(WRITE_ONLY, (UMat*)&m, wscale, iwscale); } + static KernelArg ReadOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(READ_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); } + static KernelArg WriteOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1) + { return KernelArg(WRITE_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); } + static KernelArg Constant(const Mat& m); + template static KernelArg Constant(const _Tp* arr, size_t n) + { return KernelArg(CONSTANT, 0, 1, 1, (void*)arr, n); } + + int flags; + UMat* m; + const void* obj; + size_t sz; + int wscale, iwscale; +}; + + +class CV_EXPORTS Kernel +{ +public: + Kernel(); + Kernel(const char* kname, const Program& prog); + Kernel(const char* kname, const ProgramSource& prog, + const String& buildopts = String(), String* errmsg=0); + ~Kernel(); + Kernel(const Kernel& k); + Kernel& operator = (const Kernel& k); + + bool empty() const; + bool create(const char* kname, const Program& prog); + bool create(const char* kname, const ProgramSource& prog, + const String& buildopts, String* errmsg=0); + + int set(int i, const void* value, size_t sz); + int set(int i, const Image2D& image2D); + int set(int i, const UMat& m); + int set(int i, const KernelArg& arg); + template int set(int i, const _Tp& value) + { return set(i, &value, sizeof(value)); } + + template + Kernel& args(const _Tp0& a0) + { + set(0, a0); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1) + { + int i = set(0, a0); set(i, a1); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2) + { + int i = set(0, a0); i = set(i, a1); set(i, a2); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, + const _Tp3& a3, const _Tp4& a4) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); + i = set(i, a3); set(i, a4); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, + const _Tp3& a3, const _Tp4& a4, const _Tp5& a5) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); + i = set(i, a3); i = set(i, a4); set(i, a5); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); + i = set(i, a4); i = set(i, a5); set(i, a6); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); + i = set(i, a4); i = set(i, a5); i = set(i, a6); set(i, a7); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); + i = set(i, a5); i = set(i, a6); i = set(i, a7); set(i, a8); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); set(i, a9); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); set(i, a10); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); set(i, a11); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11, + const _Tp12& a12) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11); + set(i, a12); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11, + const _Tp12& a12, const _Tp13& a13) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11); + i = set(i, a12); set(i, a13); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11, + const _Tp12& a12, const _Tp13& a13, const _Tp14& a14) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11); + i = set(i, a12); i = set(i, a13); set(i, a14); return *this; + } + + template + Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3, + const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7, + const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11, + const _Tp12& a12, const _Tp13& a13, const _Tp14& a14, const _Tp15& a15) + { + int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5); + i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11); + i = set(i, a12); i = set(i, a13); i = set(i, a14); set(i, a15); return *this; + } + /** @brief Run the OpenCL kernel. + @param dims the work problem dimensions. It is the length of globalsize and localsize. It can be either 1, 2 or 3. + @param globalsize work items for each dimension. It is not the final globalsize passed to + OpenCL. Each dimension will be adjusted to the nearest integer divisible by the corresponding + value in localsize. If localsize is NULL, it will still be adjusted depending on dims. The + adjusted values are greater than or equal to the original values. + @param localsize work-group size for each dimension. + @param sync specify whether to wait for OpenCL computation to finish before return. + @param q command queue + */ + bool run(int dims, size_t globalsize[], + size_t localsize[], bool sync, const Queue& q=Queue()); + bool runTask(bool sync, const Queue& q=Queue()); + + /** @brief Similar to synchronized run() call with returning of kernel execution time + * Separate OpenCL command queue may be used (with CL_QUEUE_PROFILING_ENABLE) + * @return Execution time in nanoseconds or negative number on error + */ + int64 runProfiling(int dims, size_t globalsize[], size_t localsize[], const Queue& q=Queue()); + + size_t workGroupSize() const; + size_t preferedWorkGroupSizeMultiple() const; + bool compileWorkGroupSize(size_t wsz[]) const; + size_t localMemSize() const; + + void* ptr() const; + struct Impl; + +protected: + Impl* p; +}; + +class CV_EXPORTS Program +{ +public: + Program(); + Program(const ProgramSource& src, + const String& buildflags, String& errmsg); + Program(const Program& prog); + + Program& operator = (const Program& prog); + ~Program(); + + bool create(const ProgramSource& src, + const String& buildflags, String& errmsg); + + void* ptr() const; + + /** + * @brief Query device-specific program binary. + * + * Returns RAW OpenCL executable binary without additional attachments. + * + * @sa ProgramSource::fromBinary + * + * @param[out] binary output buffer + */ + void getBinary(std::vector& binary) const; + + struct Impl; friend struct Impl; + inline Impl* getImpl() const { return (Impl*)p; } +protected: + Impl* p; +public: +#ifndef OPENCV_REMOVE_DEPRECATED_API + // TODO Remove this + CV_DEPRECATED bool read(const String& buf, const String& buildflags); // removed, use ProgramSource instead + CV_DEPRECATED bool write(String& buf) const; // removed, use getBinary() method instead (RAW OpenCL binary) + CV_DEPRECATED const ProgramSource& source() const; // implementation removed + CV_DEPRECATED String getPrefix() const; // deprecated, implementation replaced + CV_DEPRECATED static String getPrefix(const String& buildflags); // deprecated, implementation replaced +#endif +}; + + +class CV_EXPORTS ProgramSource +{ +public: + typedef uint64 hash_t; // deprecated + + ProgramSource(); + explicit ProgramSource(const String& module, const String& name, const String& codeStr, const String& codeHash); + explicit ProgramSource(const String& prog); // deprecated + explicit ProgramSource(const char* prog); // deprecated + ~ProgramSource(); + ProgramSource(const ProgramSource& prog); + ProgramSource& operator = (const ProgramSource& prog); + + const String& source() const; // deprecated + hash_t hash() const; // deprecated + + + /** @brief Describe OpenCL program binary. + * Do not call clCreateProgramWithBinary() and/or clBuildProgram(). + * + * Caller should guarantee binary buffer lifetime greater than ProgramSource object (and any of its copies). + * + * This kind of binary is not portable between platforms in general - it is specific to OpenCL vendor / device / driver version. + * + * @param module name of program owner module + * @param name unique name of program (module+name is used as key for OpenCL program caching) + * @param binary buffer address. See buffer lifetime requirement in description. + * @param size buffer size + * @param buildOptions additional program-related build options passed to clBuildProgram() + * @return created ProgramSource object + */ + static ProgramSource fromBinary(const String& module, const String& name, + const unsigned char* binary, const size_t size, + const cv::String& buildOptions = cv::String()); + + /** @brief Describe OpenCL program in SPIR format. + * Do not call clCreateProgramWithBinary() and/or clBuildProgram(). + * + * Supports SPIR 1.2 by default (pass '-spir-std=X.Y' in buildOptions to override this behavior) + * + * Caller should guarantee binary buffer lifetime greater than ProgramSource object (and any of its copies). + * + * Programs in this format are portable between OpenCL implementations with 'khr_spir' extension: + * https://www.khronos.org/registry/OpenCL/sdk/2.0/docs/man/xhtml/cl_khr_spir.html + * (but they are not portable between different platforms: 32-bit / 64-bit) + * + * Note: these programs can't support vendor specific extensions, like 'cl_intel_subgroups'. + * + * @param module name of program owner module + * @param name unique name of program (module+name is used as key for OpenCL program caching) + * @param binary buffer address. See buffer lifetime requirement in description. + * @param size buffer size + * @param buildOptions additional program-related build options passed to clBuildProgram() + * (these options are added automatically: '-x spir' and '-spir-std=1.2') + * @return created ProgramSource object. + */ + static ProgramSource fromSPIR(const String& module, const String& name, + const unsigned char* binary, const size_t size, + const cv::String& buildOptions = cv::String()); + + //OpenCL 2.1+ only + //static Program fromSPIRV(const String& module, const String& name, + // const unsigned char* binary, const size_t size, + // const cv::String& buildOptions = cv::String()); + + struct Impl; friend struct Impl; + inline Impl* getImpl() const { return (Impl*)p; } +protected: + Impl* p; +}; + +class CV_EXPORTS PlatformInfo +{ +public: + PlatformInfo(); + explicit PlatformInfo(void* id); + ~PlatformInfo(); + + PlatformInfo(const PlatformInfo& i); + PlatformInfo& operator =(const PlatformInfo& i); + + String name() const; + String vendor() const; + String version() const; + int deviceNumber() const; + void getDevice(Device& device, int d) const; + +protected: + struct Impl; + Impl* p; +}; + +CV_EXPORTS const char* convertTypeStr(int sdepth, int ddepth, int cn, char* buf); +CV_EXPORTS const char* typeToStr(int t); +CV_EXPORTS const char* memopTypeToStr(int t); +CV_EXPORTS const char* vecopTypeToStr(int t); +CV_EXPORTS const char* getOpenCLErrorString(int errorCode); +CV_EXPORTS String kernelToStr(InputArray _kernel, int ddepth = -1, const char * name = NULL); +CV_EXPORTS void getPlatfomsInfo(std::vector& platform_info); + + +enum OclVectorStrategy +{ + // all matrices have its own vector width + OCL_VECTOR_OWN = 0, + // all matrices have maximal vector width among all matrices + // (useful for cases when matrices have different data types) + OCL_VECTOR_MAX = 1, + + // default strategy + OCL_VECTOR_DEFAULT = OCL_VECTOR_OWN +}; + +CV_EXPORTS int predictOptimalVectorWidth(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(), + InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(), + InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(), + OclVectorStrategy strat = OCL_VECTOR_DEFAULT); + +CV_EXPORTS int checkOptimalVectorWidth(const int *vectorWidths, + InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(), + InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(), + InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(), + OclVectorStrategy strat = OCL_VECTOR_DEFAULT); + +// with OCL_VECTOR_MAX strategy +CV_EXPORTS int predictOptimalVectorWidthMax(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(), + InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(), + InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray()); + +CV_EXPORTS void buildOptionsAddMatrixDescription(String& buildOptions, const String& name, InputArray _m); + +class CV_EXPORTS Image2D +{ +public: + Image2D(); + + /** + @param src UMat object from which to get image properties and data + @param norm flag to enable the use of normalized channel data types + @param alias flag indicating that the image should alias the src UMat. If true, changes to the + image or src will be reflected in both objects. + */ + explicit Image2D(const UMat &src, bool norm = false, bool alias = false); + Image2D(const Image2D & i); + ~Image2D(); + + Image2D & operator = (const Image2D & i); + + /** Indicates if creating an aliased image should succeed. + Depends on the underlying platform and the dimensions of the UMat. + */ + static bool canCreateAlias(const UMat &u); + + /** Indicates if the image format is supported. + */ + static bool isFormatSupported(int depth, int cn, bool norm); + + void* ptr() const; +protected: + struct Impl; + Impl* p; +}; + +class CV_EXPORTS Timer +{ +public: + Timer(const Queue& q); + ~Timer(); + void start(); + void stop(); + + uint64 durationNS() const; //< duration in nanoseconds + +protected: + struct Impl; + Impl* const p; + +private: + Timer(const Timer&); // disabled + Timer& operator=(const Timer&); // disabled +}; + +CV_EXPORTS MatAllocator* getOpenCLAllocator(); + + +#ifdef __OPENCV_BUILD +namespace internal { + +CV_EXPORTS bool isOpenCLForced(); +#define OCL_FORCE_CHECK(condition) (cv::ocl::internal::isOpenCLForced() || (condition)) + +CV_EXPORTS bool isPerformanceCheckBypassed(); +#define OCL_PERFORMANCE_CHECK(condition) (cv::ocl::internal::isPerformanceCheckBypassed() || (condition)) + +CV_EXPORTS bool isCLBuffer(UMat& u); + +} // namespace internal +#endif + +//! @} + +}} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/ocl_genbase.hpp b/3rdparty/opencv/include/opencv2/core/ocl_genbase.hpp new file mode 100644 index 00000000..5334cf1f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/ocl_genbase.hpp @@ -0,0 +1,69 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OPENCL_GENBASE_HPP +#define OPENCV_OPENCL_GENBASE_HPP + +//! @cond IGNORED + +namespace cv { +namespace ocl { + +class ProgramSource; + +namespace internal { + +struct CV_EXPORTS ProgramEntry +{ + const char* module; + const char* name; + const char* programCode; + const char* programHash; + ProgramSource* pProgramSource; + + operator ProgramSource& () const; +}; + +} } } // namespace + +//! @endcond + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/opencl/ocl_defs.hpp b/3rdparty/opencv/include/opencv2/core/opencl/ocl_defs.hpp new file mode 100644 index 00000000..605a65f8 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/ocl_defs.hpp @@ -0,0 +1,75 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. + +#ifndef OPENCV_CORE_OPENCL_DEFS_HPP +#define OPENCV_CORE_OPENCL_DEFS_HPP + +#include "opencv2/core/utility.hpp" +#include "cvconfig.h" + +namespace cv { namespace ocl { +#ifdef HAVE_OPENCL +/// Call is similar to useOpenCL() but doesn't try to load OpenCL runtime or create OpenCL context +CV_EXPORTS bool isOpenCLActivated(); +#else +static inline bool isOpenCLActivated() { return false; } +#endif +}} // namespace + + +//#define CV_OPENCL_RUN_ASSERT + +#ifdef HAVE_OPENCL + +#ifdef CV_OPENCL_RUN_VERBOSE +#define CV_OCL_RUN_(condition, func, ...) \ + { \ + if (cv::ocl::isOpenCLActivated() && (condition) && func) \ + { \ + printf("%s: OpenCL implementation is running\n", CV_Func); \ + fflush(stdout); \ + CV_IMPL_ADD(CV_IMPL_OCL); \ + return __VA_ARGS__; \ + } \ + else \ + { \ + printf("%s: Plain implementation is running\n", CV_Func); \ + fflush(stdout); \ + } \ + } +#elif defined CV_OPENCL_RUN_ASSERT +#define CV_OCL_RUN_(condition, func, ...) \ + { \ + if (cv::ocl::isOpenCLActivated() && (condition)) \ + { \ + if(func) \ + { \ + CV_IMPL_ADD(CV_IMPL_OCL); \ + } \ + else \ + { \ + CV_Error(cv::Error::StsAssert, #func); \ + } \ + return __VA_ARGS__; \ + } \ + } +#else +#define CV_OCL_RUN_(condition, func, ...) \ + if (cv::ocl::isOpenCLActivated() && (condition) && func) \ + { \ + CV_IMPL_ADD(CV_IMPL_OCL); \ + return __VA_ARGS__; \ + } +#endif + +#else +#define CV_OCL_RUN_(condition, func, ...) +#endif + +#define CV_OCL_RUN(condition, func) CV_OCL_RUN_(condition, func) + +#endif // OPENCV_CORE_OPENCL_DEFS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/opencl_info.hpp b/3rdparty/opencv/include/opencv2/core/opencl/opencl_info.hpp new file mode 100644 index 00000000..b5d37394 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/opencl_info.hpp @@ -0,0 +1,198 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#include + +#include +#include + +#ifndef DUMP_CONFIG_PROPERTY +#define DUMP_CONFIG_PROPERTY(...) +#endif + +#ifndef DUMP_MESSAGE_STDOUT +#define DUMP_MESSAGE_STDOUT(...) do { std::cout << __VA_ARGS__ << std::endl; } while (false) +#endif + +namespace cv { + +namespace { +static std::string bytesToStringRepr(size_t value) +{ + size_t b = value % 1024; + value /= 1024; + + size_t kb = value % 1024; + value /= 1024; + + size_t mb = value % 1024; + value /= 1024; + + size_t gb = value; + + std::ostringstream stream; + + if (gb > 0) + stream << gb << " GB "; + if (mb > 0) + stream << mb << " MB "; + if (kb > 0) + stream << kb << " KB "; + if (b > 0) + stream << b << " B"; + + std::string s = stream.str(); + if (s[s.size() - 1] == ' ') + s = s.substr(0, s.size() - 1); + return s; +} +} // namespace + +static void dumpOpenCLInformation() +{ + using namespace cv::ocl; + + try + { + if (!haveOpenCL() || !useOpenCL()) + { + DUMP_MESSAGE_STDOUT("OpenCL is disabled"); + DUMP_CONFIG_PROPERTY("cv_ocl", "disabled"); + return; + } + + std::vector platforms; + cv::ocl::getPlatfomsInfo(platforms); + if (platforms.size() > 0) + { + DUMP_MESSAGE_STDOUT("OpenCL Platforms: "); + for (size_t i = 0; i < platforms.size(); i++) + { + const PlatformInfo* platform = &platforms[i]; + DUMP_MESSAGE_STDOUT(" " << platform->name().c_str()); + Device current_device; + for (int j = 0; j < platform->deviceNumber(); j++) + { + platform->getDevice(current_device, j); + const char* deviceTypeStr = current_device.type() == Device::TYPE_CPU + ? ("CPU") : (current_device.type() == Device::TYPE_GPU ? current_device.hostUnifiedMemory() ? "iGPU" : "dGPU" : "unknown"); + DUMP_MESSAGE_STDOUT( " " << deviceTypeStr << ": " << current_device.name().c_str() << " (" << current_device.version().c_str() << ")"); + DUMP_CONFIG_PROPERTY( cv::format("cv_ocl_platform_%d_device_%d", (int)i, (int)j ), + cv::format("(Platform=%s)(Type=%s)(Name=%s)(Version=%s)", + platform->name().c_str(), deviceTypeStr, current_device.name().c_str(), current_device.version().c_str()) ); + } + } + } + else + { + DUMP_MESSAGE_STDOUT("OpenCL is not available"); + DUMP_CONFIG_PROPERTY("cv_ocl", "not available"); + return; + } + + const Device& device = Device::getDefault(); + if (!device.available()) + CV_Error(Error::OpenCLInitError, "OpenCL device is not available"); + + DUMP_MESSAGE_STDOUT("Current OpenCL device: "); + +#if 0 + DUMP_MESSAGE_STDOUT(" Platform = " << device.getPlatform().name()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_platformName", device.getPlatform().name()); +#endif + + const char* deviceTypeStr = device.type() == Device::TYPE_CPU + ? ("CPU") : (device.type() == Device::TYPE_GPU ? device.hostUnifiedMemory() ? "iGPU" : "dGPU" : "unknown"); + DUMP_MESSAGE_STDOUT(" Type = " << deviceTypeStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceType", deviceTypeStr); + + DUMP_MESSAGE_STDOUT(" Name = " << device.name()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceName", device.name()); + + DUMP_MESSAGE_STDOUT(" Version = " << device.version()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceVersion", device.version()); + + DUMP_MESSAGE_STDOUT(" Driver version = " << device.driverVersion()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_driverVersion", device.driverVersion()); + + DUMP_MESSAGE_STDOUT(" Address bits = " << device.addressBits()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_addressBits", device.addressBits()); + + DUMP_MESSAGE_STDOUT(" Compute units = " << device.maxComputeUnits()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_maxComputeUnits", device.maxComputeUnits()); + + DUMP_MESSAGE_STDOUT(" Max work group size = " << device.maxWorkGroupSize()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_maxWorkGroupSize", device.maxWorkGroupSize()); + + std::string localMemorySizeStr = bytesToStringRepr(device.localMemSize()); + DUMP_MESSAGE_STDOUT(" Local memory size = " << localMemorySizeStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_localMemSize", device.localMemSize()); + + std::string maxMemAllocSizeStr = bytesToStringRepr(device.maxMemAllocSize()); + DUMP_MESSAGE_STDOUT(" Max memory allocation size = " << maxMemAllocSizeStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_maxMemAllocSize", device.maxMemAllocSize()); + + const char* doubleSupportStr = device.doubleFPConfig() > 0 ? "Yes" : "No"; + DUMP_MESSAGE_STDOUT(" Double support = " << doubleSupportStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_haveDoubleSupport", device.doubleFPConfig() > 0); + + const char* isUnifiedMemoryStr = device.hostUnifiedMemory() ? "Yes" : "No"; + DUMP_MESSAGE_STDOUT(" Host unified memory = " << isUnifiedMemoryStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_hostUnifiedMemory", device.hostUnifiedMemory()); + + DUMP_MESSAGE_STDOUT(" Device extensions:"); + String extensionsStr = device.extensions(); + size_t pos = 0; + while (pos < extensionsStr.size()) + { + size_t pos2 = extensionsStr.find(' ', pos); + if (pos2 == String::npos) + pos2 = extensionsStr.size(); + if (pos2 > pos) + { + String extensionName = extensionsStr.substr(pos, pos2 - pos); + DUMP_MESSAGE_STDOUT(" " << extensionName); + } + pos = pos2 + 1; + } + DUMP_CONFIG_PROPERTY("cv_ocl_current_extensions", extensionsStr.c_str()); + + const char* haveAmdBlasStr = haveAmdBlas() ? "Yes" : "No"; + DUMP_MESSAGE_STDOUT(" Has AMD Blas = " << haveAmdBlasStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_AmdBlas", haveAmdBlas()); + + const char* haveAmdFftStr = haveAmdFft() ? "Yes" : "No"; + DUMP_MESSAGE_STDOUT(" Has AMD Fft = " << haveAmdFftStr); + DUMP_CONFIG_PROPERTY("cv_ocl_current_AmdFft", haveAmdFft()); + + + DUMP_MESSAGE_STDOUT(" Preferred vector width char = " << device.preferredVectorWidthChar()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthChar", device.preferredVectorWidthChar()); + + DUMP_MESSAGE_STDOUT(" Preferred vector width short = " << device.preferredVectorWidthShort()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthShort", device.preferredVectorWidthShort()); + + DUMP_MESSAGE_STDOUT(" Preferred vector width int = " << device.preferredVectorWidthInt()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthInt", device.preferredVectorWidthInt()); + + DUMP_MESSAGE_STDOUT(" Preferred vector width long = " << device.preferredVectorWidthLong()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthLong", device.preferredVectorWidthLong()); + + DUMP_MESSAGE_STDOUT(" Preferred vector width float = " << device.preferredVectorWidthFloat()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthFloat", device.preferredVectorWidthFloat()); + + DUMP_MESSAGE_STDOUT(" Preferred vector width double = " << device.preferredVectorWidthDouble()); + DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthDouble", device.preferredVectorWidthDouble()); + } + catch (...) + { + DUMP_MESSAGE_STDOUT("Exception. Can't dump OpenCL info"); + DUMP_MESSAGE_STDOUT("OpenCL device not available"); + DUMP_CONFIG_PROPERTY("cv_ocl", "not available"); + } +} +#undef DUMP_MESSAGE_STDOUT +#undef DUMP_CONFIG_PROPERTY + +} // namespace diff --git a/3rdparty/opencv/include/opencv2/core/opencl/opencl_svm.hpp b/3rdparty/opencv/include/opencv2/core/opencl/opencl_svm.hpp new file mode 100644 index 00000000..7453082a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/opencl_svm.hpp @@ -0,0 +1,81 @@ +/* See LICENSE file in the root OpenCV directory */ + +#ifndef OPENCV_CORE_OPENCL_SVM_HPP +#define OPENCV_CORE_OPENCL_SVM_HPP + +// +// Internal usage only (binary compatibility is not guaranteed) +// +#ifndef __OPENCV_BUILD +#error Internal header file +#endif + +#if defined(HAVE_OPENCL) && defined(HAVE_OPENCL_SVM) +#include "runtime/opencl_core.hpp" +#include "runtime/opencl_svm_20.hpp" +#include "runtime/opencl_svm_hsa_extension.hpp" + +namespace cv { namespace ocl { namespace svm { + +struct SVMCapabilities +{ + enum Value + { + SVM_COARSE_GRAIN_BUFFER = (1 << 0), + SVM_FINE_GRAIN_BUFFER = (1 << 1), + SVM_FINE_GRAIN_SYSTEM = (1 << 2), + SVM_ATOMICS = (1 << 3), + }; + int value_; + + SVMCapabilities(int capabilities = 0) : value_(capabilities) { } + operator int() const { return value_; } + + inline bool isNoSVMSupport() const { return value_ == 0; } + inline bool isSupportCoarseGrainBuffer() const { return (value_ & SVM_COARSE_GRAIN_BUFFER) != 0; } + inline bool isSupportFineGrainBuffer() const { return (value_ & SVM_FINE_GRAIN_BUFFER) != 0; } + inline bool isSupportFineGrainSystem() const { return (value_ & SVM_FINE_GRAIN_SYSTEM) != 0; } + inline bool isSupportAtomics() const { return (value_ & SVM_ATOMICS) != 0; } +}; + +CV_EXPORTS const SVMCapabilities getSVMCapabilitites(const ocl::Context& context); + +struct SVMFunctions +{ + clSVMAllocAMD_fn fn_clSVMAlloc; + clSVMFreeAMD_fn fn_clSVMFree; + clSetKernelArgSVMPointerAMD_fn fn_clSetKernelArgSVMPointer; + //clSetKernelExecInfoAMD_fn fn_clSetKernelExecInfo; + //clEnqueueSVMFreeAMD_fn fn_clEnqueueSVMFree; + clEnqueueSVMMemcpyAMD_fn fn_clEnqueueSVMMemcpy; + clEnqueueSVMMemFillAMD_fn fn_clEnqueueSVMMemFill; + clEnqueueSVMMapAMD_fn fn_clEnqueueSVMMap; + clEnqueueSVMUnmapAMD_fn fn_clEnqueueSVMUnmap; + + inline SVMFunctions() + : fn_clSVMAlloc(NULL), fn_clSVMFree(NULL), + fn_clSetKernelArgSVMPointer(NULL), /*fn_clSetKernelExecInfo(NULL),*/ + /*fn_clEnqueueSVMFree(NULL),*/ fn_clEnqueueSVMMemcpy(NULL), fn_clEnqueueSVMMemFill(NULL), + fn_clEnqueueSVMMap(NULL), fn_clEnqueueSVMUnmap(NULL) + { + // nothing + } + + inline bool isValid() const + { + return fn_clSVMAlloc != NULL && fn_clSVMFree && fn_clSetKernelArgSVMPointer && + /*fn_clSetKernelExecInfo && fn_clEnqueueSVMFree &&*/ fn_clEnqueueSVMMemcpy && + fn_clEnqueueSVMMemFill && fn_clEnqueueSVMMap && fn_clEnqueueSVMUnmap; + } +}; + +// We should guarantee that SVMFunctions lifetime is not less than context's lifetime +CV_EXPORTS const SVMFunctions* getSVMFunctions(const ocl::Context& context); + +CV_EXPORTS bool useSVM(UMatUsageFlags usageFlags); + +}}} //namespace cv::ocl::svm +#endif + +#endif // OPENCV_CORE_OPENCL_SVM_HPP +/* End of file. */ diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdblas.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdblas.hpp new file mode 100644 index 00000000..65c84935 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdblas.hpp @@ -0,0 +1,714 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP +#error "Invalid usage" +#endif + +// generated by parser_clamdblas.py +#define clAmdBlasAddScratchImage clAmdBlasAddScratchImage_ +#define clAmdBlasCaxpy clAmdBlasCaxpy_ +#define clAmdBlasCcopy clAmdBlasCcopy_ +#define clAmdBlasCdotc clAmdBlasCdotc_ +#define clAmdBlasCdotu clAmdBlasCdotu_ +#define clAmdBlasCgbmv clAmdBlasCgbmv_ +#define clAmdBlasCgemm clAmdBlasCgemm_ +#define clAmdBlasCgemmEx clAmdBlasCgemmEx_ +#define clAmdBlasCgemv clAmdBlasCgemv_ +#define clAmdBlasCgemvEx clAmdBlasCgemvEx_ +#define clAmdBlasCgerc clAmdBlasCgerc_ +#define clAmdBlasCgeru clAmdBlasCgeru_ +#define clAmdBlasChbmv clAmdBlasChbmv_ +#define clAmdBlasChemm clAmdBlasChemm_ +#define clAmdBlasChemv clAmdBlasChemv_ +#define clAmdBlasCher clAmdBlasCher_ +#define clAmdBlasCher2 clAmdBlasCher2_ +#define clAmdBlasCher2k clAmdBlasCher2k_ +#define clAmdBlasCherk clAmdBlasCherk_ +#define clAmdBlasChpmv clAmdBlasChpmv_ +#define clAmdBlasChpr clAmdBlasChpr_ +#define clAmdBlasChpr2 clAmdBlasChpr2_ +#define clAmdBlasCrotg clAmdBlasCrotg_ +#define clAmdBlasCscal clAmdBlasCscal_ +#define clAmdBlasCsrot clAmdBlasCsrot_ +#define clAmdBlasCsscal clAmdBlasCsscal_ +#define clAmdBlasCswap clAmdBlasCswap_ +#define clAmdBlasCsymm clAmdBlasCsymm_ +#define clAmdBlasCsyr2k clAmdBlasCsyr2k_ +#define clAmdBlasCsyr2kEx clAmdBlasCsyr2kEx_ +#define clAmdBlasCsyrk clAmdBlasCsyrk_ +#define clAmdBlasCsyrkEx clAmdBlasCsyrkEx_ +#define clAmdBlasCtbmv clAmdBlasCtbmv_ +#define clAmdBlasCtbsv clAmdBlasCtbsv_ +#define clAmdBlasCtpmv clAmdBlasCtpmv_ +#define clAmdBlasCtpsv clAmdBlasCtpsv_ +#define clAmdBlasCtrmm clAmdBlasCtrmm_ +#define clAmdBlasCtrmmEx clAmdBlasCtrmmEx_ +#define clAmdBlasCtrmv clAmdBlasCtrmv_ +#define clAmdBlasCtrsm clAmdBlasCtrsm_ +#define clAmdBlasCtrsmEx clAmdBlasCtrsmEx_ +#define clAmdBlasCtrsv clAmdBlasCtrsv_ +#define clAmdBlasDasum clAmdBlasDasum_ +#define clAmdBlasDaxpy clAmdBlasDaxpy_ +#define clAmdBlasDcopy clAmdBlasDcopy_ +#define clAmdBlasDdot clAmdBlasDdot_ +#define clAmdBlasDgbmv clAmdBlasDgbmv_ +#define clAmdBlasDgemm clAmdBlasDgemm_ +#define clAmdBlasDgemmEx clAmdBlasDgemmEx_ +#define clAmdBlasDgemv clAmdBlasDgemv_ +#define clAmdBlasDgemvEx clAmdBlasDgemvEx_ +#define clAmdBlasDger clAmdBlasDger_ +#define clAmdBlasDnrm2 clAmdBlasDnrm2_ +#define clAmdBlasDrot clAmdBlasDrot_ +#define clAmdBlasDrotg clAmdBlasDrotg_ +#define clAmdBlasDrotm clAmdBlasDrotm_ +#define clAmdBlasDrotmg clAmdBlasDrotmg_ +#define clAmdBlasDsbmv clAmdBlasDsbmv_ +#define clAmdBlasDscal clAmdBlasDscal_ +#define clAmdBlasDspmv clAmdBlasDspmv_ +#define clAmdBlasDspr clAmdBlasDspr_ +#define clAmdBlasDspr2 clAmdBlasDspr2_ +#define clAmdBlasDswap clAmdBlasDswap_ +#define clAmdBlasDsymm clAmdBlasDsymm_ +#define clAmdBlasDsymv clAmdBlasDsymv_ +#define clAmdBlasDsymvEx clAmdBlasDsymvEx_ +#define clAmdBlasDsyr clAmdBlasDsyr_ +#define clAmdBlasDsyr2 clAmdBlasDsyr2_ +#define clAmdBlasDsyr2k clAmdBlasDsyr2k_ +#define clAmdBlasDsyr2kEx clAmdBlasDsyr2kEx_ +#define clAmdBlasDsyrk clAmdBlasDsyrk_ +#define clAmdBlasDsyrkEx clAmdBlasDsyrkEx_ +#define clAmdBlasDtbmv clAmdBlasDtbmv_ +#define clAmdBlasDtbsv clAmdBlasDtbsv_ +#define clAmdBlasDtpmv clAmdBlasDtpmv_ +#define clAmdBlasDtpsv clAmdBlasDtpsv_ +#define clAmdBlasDtrmm clAmdBlasDtrmm_ +#define clAmdBlasDtrmmEx clAmdBlasDtrmmEx_ +#define clAmdBlasDtrmv clAmdBlasDtrmv_ +#define clAmdBlasDtrsm clAmdBlasDtrsm_ +#define clAmdBlasDtrsmEx clAmdBlasDtrsmEx_ +#define clAmdBlasDtrsv clAmdBlasDtrsv_ +#define clAmdBlasDzasum clAmdBlasDzasum_ +#define clAmdBlasDznrm2 clAmdBlasDznrm2_ +#define clAmdBlasGetVersion clAmdBlasGetVersion_ +#define clAmdBlasRemoveScratchImage clAmdBlasRemoveScratchImage_ +#define clAmdBlasSasum clAmdBlasSasum_ +#define clAmdBlasSaxpy clAmdBlasSaxpy_ +#define clAmdBlasScasum clAmdBlasScasum_ +#define clAmdBlasScnrm2 clAmdBlasScnrm2_ +#define clAmdBlasScopy clAmdBlasScopy_ +#define clAmdBlasSdot clAmdBlasSdot_ +#define clAmdBlasSetup clAmdBlasSetup_ +#define clAmdBlasSgbmv clAmdBlasSgbmv_ +#define clAmdBlasSgemm clAmdBlasSgemm_ +#define clAmdBlasSgemmEx clAmdBlasSgemmEx_ +#define clAmdBlasSgemv clAmdBlasSgemv_ +#define clAmdBlasSgemvEx clAmdBlasSgemvEx_ +#define clAmdBlasSger clAmdBlasSger_ +#define clAmdBlasSnrm2 clAmdBlasSnrm2_ +#define clAmdBlasSrot clAmdBlasSrot_ +#define clAmdBlasSrotg clAmdBlasSrotg_ +#define clAmdBlasSrotm clAmdBlasSrotm_ +#define clAmdBlasSrotmg clAmdBlasSrotmg_ +#define clAmdBlasSsbmv clAmdBlasSsbmv_ +#define clAmdBlasSscal clAmdBlasSscal_ +#define clAmdBlasSspmv clAmdBlasSspmv_ +#define clAmdBlasSspr clAmdBlasSspr_ +#define clAmdBlasSspr2 clAmdBlasSspr2_ +#define clAmdBlasSswap clAmdBlasSswap_ +#define clAmdBlasSsymm clAmdBlasSsymm_ +#define clAmdBlasSsymv clAmdBlasSsymv_ +#define clAmdBlasSsymvEx clAmdBlasSsymvEx_ +#define clAmdBlasSsyr clAmdBlasSsyr_ +#define clAmdBlasSsyr2 clAmdBlasSsyr2_ +#define clAmdBlasSsyr2k clAmdBlasSsyr2k_ +#define clAmdBlasSsyr2kEx clAmdBlasSsyr2kEx_ +#define clAmdBlasSsyrk clAmdBlasSsyrk_ +#define clAmdBlasSsyrkEx clAmdBlasSsyrkEx_ +#define clAmdBlasStbmv clAmdBlasStbmv_ +#define clAmdBlasStbsv clAmdBlasStbsv_ +#define clAmdBlasStpmv clAmdBlasStpmv_ +#define clAmdBlasStpsv clAmdBlasStpsv_ +#define clAmdBlasStrmm clAmdBlasStrmm_ +#define clAmdBlasStrmmEx clAmdBlasStrmmEx_ +#define clAmdBlasStrmv clAmdBlasStrmv_ +#define clAmdBlasStrsm clAmdBlasStrsm_ +#define clAmdBlasStrsmEx clAmdBlasStrsmEx_ +#define clAmdBlasStrsv clAmdBlasStrsv_ +#define clAmdBlasTeardown clAmdBlasTeardown_ +#define clAmdBlasZaxpy clAmdBlasZaxpy_ +#define clAmdBlasZcopy clAmdBlasZcopy_ +#define clAmdBlasZdotc clAmdBlasZdotc_ +#define clAmdBlasZdotu clAmdBlasZdotu_ +#define clAmdBlasZdrot clAmdBlasZdrot_ +#define clAmdBlasZdscal clAmdBlasZdscal_ +#define clAmdBlasZgbmv clAmdBlasZgbmv_ +#define clAmdBlasZgemm clAmdBlasZgemm_ +#define clAmdBlasZgemmEx clAmdBlasZgemmEx_ +#define clAmdBlasZgemv clAmdBlasZgemv_ +#define clAmdBlasZgemvEx clAmdBlasZgemvEx_ +#define clAmdBlasZgerc clAmdBlasZgerc_ +#define clAmdBlasZgeru clAmdBlasZgeru_ +#define clAmdBlasZhbmv clAmdBlasZhbmv_ +#define clAmdBlasZhemm clAmdBlasZhemm_ +#define clAmdBlasZhemv clAmdBlasZhemv_ +#define clAmdBlasZher clAmdBlasZher_ +#define clAmdBlasZher2 clAmdBlasZher2_ +#define clAmdBlasZher2k clAmdBlasZher2k_ +#define clAmdBlasZherk clAmdBlasZherk_ +#define clAmdBlasZhpmv clAmdBlasZhpmv_ +#define clAmdBlasZhpr clAmdBlasZhpr_ +#define clAmdBlasZhpr2 clAmdBlasZhpr2_ +#define clAmdBlasZrotg clAmdBlasZrotg_ +#define clAmdBlasZscal clAmdBlasZscal_ +#define clAmdBlasZswap clAmdBlasZswap_ +#define clAmdBlasZsymm clAmdBlasZsymm_ +#define clAmdBlasZsyr2k clAmdBlasZsyr2k_ +#define clAmdBlasZsyr2kEx clAmdBlasZsyr2kEx_ +#define clAmdBlasZsyrk clAmdBlasZsyrk_ +#define clAmdBlasZsyrkEx clAmdBlasZsyrkEx_ +#define clAmdBlasZtbmv clAmdBlasZtbmv_ +#define clAmdBlasZtbsv clAmdBlasZtbsv_ +#define clAmdBlasZtpmv clAmdBlasZtpmv_ +#define clAmdBlasZtpsv clAmdBlasZtpsv_ +#define clAmdBlasZtrmm clAmdBlasZtrmm_ +#define clAmdBlasZtrmmEx clAmdBlasZtrmmEx_ +#define clAmdBlasZtrmv clAmdBlasZtrmv_ +#define clAmdBlasZtrsm clAmdBlasZtrsm_ +#define clAmdBlasZtrsmEx clAmdBlasZtrsmEx_ +#define clAmdBlasZtrsv clAmdBlasZtrsv_ +#define clAmdBlasiCamax clAmdBlasiCamax_ +#define clAmdBlasiDamax clAmdBlasiDamax_ +#define clAmdBlasiSamax clAmdBlasiSamax_ +#define clAmdBlasiZamax clAmdBlasiZamax_ + +#include + +// generated by parser_clamdblas.py +#undef clAmdBlasAddScratchImage +//#define clAmdBlasAddScratchImage clAmdBlasAddScratchImage_pfn +#undef clAmdBlasCaxpy +//#define clAmdBlasCaxpy clAmdBlasCaxpy_pfn +#undef clAmdBlasCcopy +//#define clAmdBlasCcopy clAmdBlasCcopy_pfn +#undef clAmdBlasCdotc +//#define clAmdBlasCdotc clAmdBlasCdotc_pfn +#undef clAmdBlasCdotu +//#define clAmdBlasCdotu clAmdBlasCdotu_pfn +#undef clAmdBlasCgbmv +//#define clAmdBlasCgbmv clAmdBlasCgbmv_pfn +#undef clAmdBlasCgemm +//#define clAmdBlasCgemm clAmdBlasCgemm_pfn +#undef clAmdBlasCgemmEx +#define clAmdBlasCgemmEx clAmdBlasCgemmEx_pfn +#undef clAmdBlasCgemv +//#define clAmdBlasCgemv clAmdBlasCgemv_pfn +#undef clAmdBlasCgemvEx +//#define clAmdBlasCgemvEx clAmdBlasCgemvEx_pfn +#undef clAmdBlasCgerc +//#define clAmdBlasCgerc clAmdBlasCgerc_pfn +#undef clAmdBlasCgeru +//#define clAmdBlasCgeru clAmdBlasCgeru_pfn +#undef clAmdBlasChbmv +//#define clAmdBlasChbmv clAmdBlasChbmv_pfn +#undef clAmdBlasChemm +//#define clAmdBlasChemm clAmdBlasChemm_pfn +#undef clAmdBlasChemv +//#define clAmdBlasChemv clAmdBlasChemv_pfn +#undef clAmdBlasCher +//#define clAmdBlasCher clAmdBlasCher_pfn +#undef clAmdBlasCher2 +//#define clAmdBlasCher2 clAmdBlasCher2_pfn +#undef clAmdBlasCher2k +//#define clAmdBlasCher2k clAmdBlasCher2k_pfn +#undef clAmdBlasCherk +//#define clAmdBlasCherk clAmdBlasCherk_pfn +#undef clAmdBlasChpmv +//#define clAmdBlasChpmv clAmdBlasChpmv_pfn +#undef clAmdBlasChpr +//#define clAmdBlasChpr clAmdBlasChpr_pfn +#undef clAmdBlasChpr2 +//#define clAmdBlasChpr2 clAmdBlasChpr2_pfn +#undef clAmdBlasCrotg +//#define clAmdBlasCrotg clAmdBlasCrotg_pfn +#undef clAmdBlasCscal +//#define clAmdBlasCscal clAmdBlasCscal_pfn +#undef clAmdBlasCsrot +//#define clAmdBlasCsrot clAmdBlasCsrot_pfn +#undef clAmdBlasCsscal +//#define clAmdBlasCsscal clAmdBlasCsscal_pfn +#undef clAmdBlasCswap +//#define clAmdBlasCswap clAmdBlasCswap_pfn +#undef clAmdBlasCsymm +//#define clAmdBlasCsymm clAmdBlasCsymm_pfn +#undef clAmdBlasCsyr2k +//#define clAmdBlasCsyr2k clAmdBlasCsyr2k_pfn +#undef clAmdBlasCsyr2kEx +//#define clAmdBlasCsyr2kEx clAmdBlasCsyr2kEx_pfn +#undef clAmdBlasCsyrk +//#define clAmdBlasCsyrk clAmdBlasCsyrk_pfn +#undef clAmdBlasCsyrkEx +//#define clAmdBlasCsyrkEx clAmdBlasCsyrkEx_pfn +#undef clAmdBlasCtbmv +//#define clAmdBlasCtbmv clAmdBlasCtbmv_pfn +#undef clAmdBlasCtbsv +//#define clAmdBlasCtbsv clAmdBlasCtbsv_pfn +#undef clAmdBlasCtpmv +//#define clAmdBlasCtpmv clAmdBlasCtpmv_pfn +#undef clAmdBlasCtpsv +//#define clAmdBlasCtpsv clAmdBlasCtpsv_pfn +#undef clAmdBlasCtrmm +//#define clAmdBlasCtrmm clAmdBlasCtrmm_pfn +#undef clAmdBlasCtrmmEx +//#define clAmdBlasCtrmmEx clAmdBlasCtrmmEx_pfn +#undef clAmdBlasCtrmv +//#define clAmdBlasCtrmv clAmdBlasCtrmv_pfn +#undef clAmdBlasCtrsm +//#define clAmdBlasCtrsm clAmdBlasCtrsm_pfn +#undef clAmdBlasCtrsmEx +//#define clAmdBlasCtrsmEx clAmdBlasCtrsmEx_pfn +#undef clAmdBlasCtrsv +//#define clAmdBlasCtrsv clAmdBlasCtrsv_pfn +#undef clAmdBlasDasum +//#define clAmdBlasDasum clAmdBlasDasum_pfn +#undef clAmdBlasDaxpy +//#define clAmdBlasDaxpy clAmdBlasDaxpy_pfn +#undef clAmdBlasDcopy +//#define clAmdBlasDcopy clAmdBlasDcopy_pfn +#undef clAmdBlasDdot +//#define clAmdBlasDdot clAmdBlasDdot_pfn +#undef clAmdBlasDgbmv +//#define clAmdBlasDgbmv clAmdBlasDgbmv_pfn +#undef clAmdBlasDgemm +//#define clAmdBlasDgemm clAmdBlasDgemm_pfn +#undef clAmdBlasDgemmEx +#define clAmdBlasDgemmEx clAmdBlasDgemmEx_pfn +#undef clAmdBlasDgemv +//#define clAmdBlasDgemv clAmdBlasDgemv_pfn +#undef clAmdBlasDgemvEx +//#define clAmdBlasDgemvEx clAmdBlasDgemvEx_pfn +#undef clAmdBlasDger +//#define clAmdBlasDger clAmdBlasDger_pfn +#undef clAmdBlasDnrm2 +//#define clAmdBlasDnrm2 clAmdBlasDnrm2_pfn +#undef clAmdBlasDrot +//#define clAmdBlasDrot clAmdBlasDrot_pfn +#undef clAmdBlasDrotg +//#define clAmdBlasDrotg clAmdBlasDrotg_pfn +#undef clAmdBlasDrotm +//#define clAmdBlasDrotm clAmdBlasDrotm_pfn +#undef clAmdBlasDrotmg +//#define clAmdBlasDrotmg clAmdBlasDrotmg_pfn +#undef clAmdBlasDsbmv +//#define clAmdBlasDsbmv clAmdBlasDsbmv_pfn +#undef clAmdBlasDscal +//#define clAmdBlasDscal clAmdBlasDscal_pfn +#undef clAmdBlasDspmv +//#define clAmdBlasDspmv clAmdBlasDspmv_pfn +#undef clAmdBlasDspr +//#define clAmdBlasDspr clAmdBlasDspr_pfn +#undef clAmdBlasDspr2 +//#define clAmdBlasDspr2 clAmdBlasDspr2_pfn +#undef clAmdBlasDswap +//#define clAmdBlasDswap clAmdBlasDswap_pfn +#undef clAmdBlasDsymm +//#define clAmdBlasDsymm clAmdBlasDsymm_pfn +#undef clAmdBlasDsymv +//#define clAmdBlasDsymv clAmdBlasDsymv_pfn +#undef clAmdBlasDsymvEx +//#define clAmdBlasDsymvEx clAmdBlasDsymvEx_pfn +#undef clAmdBlasDsyr +//#define clAmdBlasDsyr clAmdBlasDsyr_pfn +#undef clAmdBlasDsyr2 +//#define clAmdBlasDsyr2 clAmdBlasDsyr2_pfn +#undef clAmdBlasDsyr2k +//#define clAmdBlasDsyr2k clAmdBlasDsyr2k_pfn +#undef clAmdBlasDsyr2kEx +//#define clAmdBlasDsyr2kEx clAmdBlasDsyr2kEx_pfn +#undef clAmdBlasDsyrk +//#define clAmdBlasDsyrk clAmdBlasDsyrk_pfn +#undef clAmdBlasDsyrkEx +//#define clAmdBlasDsyrkEx clAmdBlasDsyrkEx_pfn +#undef clAmdBlasDtbmv +//#define clAmdBlasDtbmv clAmdBlasDtbmv_pfn +#undef clAmdBlasDtbsv +//#define clAmdBlasDtbsv clAmdBlasDtbsv_pfn +#undef clAmdBlasDtpmv +//#define clAmdBlasDtpmv clAmdBlasDtpmv_pfn +#undef clAmdBlasDtpsv +//#define clAmdBlasDtpsv clAmdBlasDtpsv_pfn +#undef clAmdBlasDtrmm +//#define clAmdBlasDtrmm clAmdBlasDtrmm_pfn +#undef clAmdBlasDtrmmEx +//#define clAmdBlasDtrmmEx clAmdBlasDtrmmEx_pfn +#undef clAmdBlasDtrmv +//#define clAmdBlasDtrmv clAmdBlasDtrmv_pfn +#undef clAmdBlasDtrsm +//#define clAmdBlasDtrsm clAmdBlasDtrsm_pfn +#undef clAmdBlasDtrsmEx +//#define clAmdBlasDtrsmEx clAmdBlasDtrsmEx_pfn +#undef clAmdBlasDtrsv +//#define clAmdBlasDtrsv clAmdBlasDtrsv_pfn +#undef clAmdBlasDzasum +//#define clAmdBlasDzasum clAmdBlasDzasum_pfn +#undef clAmdBlasDznrm2 +//#define clAmdBlasDznrm2 clAmdBlasDznrm2_pfn +#undef clAmdBlasGetVersion +//#define clAmdBlasGetVersion clAmdBlasGetVersion_pfn +#undef clAmdBlasRemoveScratchImage +//#define clAmdBlasRemoveScratchImage clAmdBlasRemoveScratchImage_pfn +#undef clAmdBlasSasum +//#define clAmdBlasSasum clAmdBlasSasum_pfn +#undef clAmdBlasSaxpy +//#define clAmdBlasSaxpy clAmdBlasSaxpy_pfn +#undef clAmdBlasScasum +//#define clAmdBlasScasum clAmdBlasScasum_pfn +#undef clAmdBlasScnrm2 +//#define clAmdBlasScnrm2 clAmdBlasScnrm2_pfn +#undef clAmdBlasScopy +//#define clAmdBlasScopy clAmdBlasScopy_pfn +#undef clAmdBlasSdot +//#define clAmdBlasSdot clAmdBlasSdot_pfn +#undef clAmdBlasSetup +#define clAmdBlasSetup clAmdBlasSetup_pfn +#undef clAmdBlasSgbmv +//#define clAmdBlasSgbmv clAmdBlasSgbmv_pfn +#undef clAmdBlasSgemm +//#define clAmdBlasSgemm clAmdBlasSgemm_pfn +#undef clAmdBlasSgemmEx +#define clAmdBlasSgemmEx clAmdBlasSgemmEx_pfn +#undef clAmdBlasSgemv +//#define clAmdBlasSgemv clAmdBlasSgemv_pfn +#undef clAmdBlasSgemvEx +//#define clAmdBlasSgemvEx clAmdBlasSgemvEx_pfn +#undef clAmdBlasSger +//#define clAmdBlasSger clAmdBlasSger_pfn +#undef clAmdBlasSnrm2 +//#define clAmdBlasSnrm2 clAmdBlasSnrm2_pfn +#undef clAmdBlasSrot +//#define clAmdBlasSrot clAmdBlasSrot_pfn +#undef clAmdBlasSrotg +//#define clAmdBlasSrotg clAmdBlasSrotg_pfn +#undef clAmdBlasSrotm +//#define clAmdBlasSrotm clAmdBlasSrotm_pfn +#undef clAmdBlasSrotmg +//#define clAmdBlasSrotmg clAmdBlasSrotmg_pfn +#undef clAmdBlasSsbmv +//#define clAmdBlasSsbmv clAmdBlasSsbmv_pfn +#undef clAmdBlasSscal +//#define clAmdBlasSscal clAmdBlasSscal_pfn +#undef clAmdBlasSspmv +//#define clAmdBlasSspmv clAmdBlasSspmv_pfn +#undef clAmdBlasSspr +//#define clAmdBlasSspr clAmdBlasSspr_pfn +#undef clAmdBlasSspr2 +//#define clAmdBlasSspr2 clAmdBlasSspr2_pfn +#undef clAmdBlasSswap +//#define clAmdBlasSswap clAmdBlasSswap_pfn +#undef clAmdBlasSsymm +//#define clAmdBlasSsymm clAmdBlasSsymm_pfn +#undef clAmdBlasSsymv +//#define clAmdBlasSsymv clAmdBlasSsymv_pfn +#undef clAmdBlasSsymvEx +//#define clAmdBlasSsymvEx clAmdBlasSsymvEx_pfn +#undef clAmdBlasSsyr +//#define clAmdBlasSsyr clAmdBlasSsyr_pfn +#undef clAmdBlasSsyr2 +//#define clAmdBlasSsyr2 clAmdBlasSsyr2_pfn +#undef clAmdBlasSsyr2k +//#define clAmdBlasSsyr2k clAmdBlasSsyr2k_pfn +#undef clAmdBlasSsyr2kEx +//#define clAmdBlasSsyr2kEx clAmdBlasSsyr2kEx_pfn +#undef clAmdBlasSsyrk +//#define clAmdBlasSsyrk clAmdBlasSsyrk_pfn +#undef clAmdBlasSsyrkEx +//#define clAmdBlasSsyrkEx clAmdBlasSsyrkEx_pfn +#undef clAmdBlasStbmv +//#define clAmdBlasStbmv clAmdBlasStbmv_pfn +#undef clAmdBlasStbsv +//#define clAmdBlasStbsv clAmdBlasStbsv_pfn +#undef clAmdBlasStpmv +//#define clAmdBlasStpmv clAmdBlasStpmv_pfn +#undef clAmdBlasStpsv +//#define clAmdBlasStpsv clAmdBlasStpsv_pfn +#undef clAmdBlasStrmm +//#define clAmdBlasStrmm clAmdBlasStrmm_pfn +#undef clAmdBlasStrmmEx +//#define clAmdBlasStrmmEx clAmdBlasStrmmEx_pfn +#undef clAmdBlasStrmv +//#define clAmdBlasStrmv clAmdBlasStrmv_pfn +#undef clAmdBlasStrsm +//#define clAmdBlasStrsm clAmdBlasStrsm_pfn +#undef clAmdBlasStrsmEx +//#define clAmdBlasStrsmEx clAmdBlasStrsmEx_pfn +#undef clAmdBlasStrsv +//#define clAmdBlasStrsv clAmdBlasStrsv_pfn +#undef clAmdBlasTeardown +#define clAmdBlasTeardown clAmdBlasTeardown_pfn +#undef clAmdBlasZaxpy +//#define clAmdBlasZaxpy clAmdBlasZaxpy_pfn +#undef clAmdBlasZcopy +//#define clAmdBlasZcopy clAmdBlasZcopy_pfn +#undef clAmdBlasZdotc +//#define clAmdBlasZdotc clAmdBlasZdotc_pfn +#undef clAmdBlasZdotu +//#define clAmdBlasZdotu clAmdBlasZdotu_pfn +#undef clAmdBlasZdrot +//#define clAmdBlasZdrot clAmdBlasZdrot_pfn +#undef clAmdBlasZdscal +//#define clAmdBlasZdscal clAmdBlasZdscal_pfn +#undef clAmdBlasZgbmv +//#define clAmdBlasZgbmv clAmdBlasZgbmv_pfn +#undef clAmdBlasZgemm +//#define clAmdBlasZgemm clAmdBlasZgemm_pfn +#undef clAmdBlasZgemmEx +#define clAmdBlasZgemmEx clAmdBlasZgemmEx_pfn +#undef clAmdBlasZgemv +//#define clAmdBlasZgemv clAmdBlasZgemv_pfn +#undef clAmdBlasZgemvEx +//#define clAmdBlasZgemvEx clAmdBlasZgemvEx_pfn +#undef clAmdBlasZgerc +//#define clAmdBlasZgerc clAmdBlasZgerc_pfn +#undef clAmdBlasZgeru +//#define clAmdBlasZgeru clAmdBlasZgeru_pfn +#undef clAmdBlasZhbmv +//#define clAmdBlasZhbmv clAmdBlasZhbmv_pfn +#undef clAmdBlasZhemm +//#define clAmdBlasZhemm clAmdBlasZhemm_pfn +#undef clAmdBlasZhemv +//#define clAmdBlasZhemv clAmdBlasZhemv_pfn +#undef clAmdBlasZher +//#define clAmdBlasZher clAmdBlasZher_pfn +#undef clAmdBlasZher2 +//#define clAmdBlasZher2 clAmdBlasZher2_pfn +#undef clAmdBlasZher2k +//#define clAmdBlasZher2k clAmdBlasZher2k_pfn +#undef clAmdBlasZherk +//#define clAmdBlasZherk clAmdBlasZherk_pfn +#undef clAmdBlasZhpmv +//#define clAmdBlasZhpmv clAmdBlasZhpmv_pfn +#undef clAmdBlasZhpr +//#define clAmdBlasZhpr clAmdBlasZhpr_pfn +#undef clAmdBlasZhpr2 +//#define clAmdBlasZhpr2 clAmdBlasZhpr2_pfn +#undef clAmdBlasZrotg +//#define clAmdBlasZrotg clAmdBlasZrotg_pfn +#undef clAmdBlasZscal +//#define clAmdBlasZscal clAmdBlasZscal_pfn +#undef clAmdBlasZswap +//#define clAmdBlasZswap clAmdBlasZswap_pfn +#undef clAmdBlasZsymm +//#define clAmdBlasZsymm clAmdBlasZsymm_pfn +#undef clAmdBlasZsyr2k +//#define clAmdBlasZsyr2k clAmdBlasZsyr2k_pfn +#undef clAmdBlasZsyr2kEx +//#define clAmdBlasZsyr2kEx clAmdBlasZsyr2kEx_pfn +#undef clAmdBlasZsyrk +//#define clAmdBlasZsyrk clAmdBlasZsyrk_pfn +#undef clAmdBlasZsyrkEx +//#define clAmdBlasZsyrkEx clAmdBlasZsyrkEx_pfn +#undef clAmdBlasZtbmv +//#define clAmdBlasZtbmv clAmdBlasZtbmv_pfn +#undef clAmdBlasZtbsv +//#define clAmdBlasZtbsv clAmdBlasZtbsv_pfn +#undef clAmdBlasZtpmv +//#define clAmdBlasZtpmv clAmdBlasZtpmv_pfn +#undef clAmdBlasZtpsv +//#define clAmdBlasZtpsv clAmdBlasZtpsv_pfn +#undef clAmdBlasZtrmm +//#define clAmdBlasZtrmm clAmdBlasZtrmm_pfn +#undef clAmdBlasZtrmmEx +//#define clAmdBlasZtrmmEx clAmdBlasZtrmmEx_pfn +#undef clAmdBlasZtrmv +//#define clAmdBlasZtrmv clAmdBlasZtrmv_pfn +#undef clAmdBlasZtrsm +//#define clAmdBlasZtrsm clAmdBlasZtrsm_pfn +#undef clAmdBlasZtrsmEx +//#define clAmdBlasZtrsmEx clAmdBlasZtrsmEx_pfn +#undef clAmdBlasZtrsv +//#define clAmdBlasZtrsv clAmdBlasZtrsv_pfn +#undef clAmdBlasiCamax +//#define clAmdBlasiCamax clAmdBlasiCamax_pfn +#undef clAmdBlasiDamax +//#define clAmdBlasiDamax clAmdBlasiDamax_pfn +#undef clAmdBlasiSamax +//#define clAmdBlasiSamax clAmdBlasiSamax_pfn +#undef clAmdBlasiZamax +//#define clAmdBlasiZamax clAmdBlasiZamax_pfn + +// generated by parser_clamdblas.py +//extern CL_RUNTIME_EXPORT cl_ulong (*clAmdBlasAddScratchImage)(cl_context context, size_t width, size_t height, clAmdBlasStatus* status); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCaxpy)(size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCdotc)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCdotu)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgbmv)(clAmdBlasOrder order, clAmdBlasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgemm)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, FloatComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgemmEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgemv)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, FloatComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgemvEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, FloatComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgerc)(clAmdBlasOrder order, size_t M, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCgeru)(clAmdBlasOrder order, size_t M, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, size_t K, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChemm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChemv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, FloatComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, FloatComplex beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCher)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCher2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCher2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCherk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, float alpha, const cl_mem A, size_t offa, size_t lda, float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float2 alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChpr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasChpr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCrotg)(cl_mem CA, size_t offCA, cl_mem CB, size_t offCB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCscal)(size_t N, cl_float2 alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_float C, cl_float S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsscal)(size_t N, cl_float alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsymm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsyr2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, FloatComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsyr2kEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsyrk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t lda, FloatComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCsyrkEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtbsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtpsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrmm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrmmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrsm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrsmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasCtrsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDaxpy)(size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDdot)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDgbmv)(clAmdBlasOrder order, clAmdBlasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDgemm)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, cl_double beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDgemmEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDgemv)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDgemvEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDger)(clAmdBlasOrder order, size_t M, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_double C, cl_double S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDrotg)(cl_mem DA, size_t offDA, cl_mem DB, size_t offDB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDrotm)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, const cl_mem DPARAM, size_t offDparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDrotmg)(cl_mem DD1, size_t offDD1, cl_mem DD2, size_t offDD2, cl_mem DX1, size_t offDX1, const cl_mem DY1, size_t offDY1, cl_mem DPARAM, size_t offDparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDscal)(size_t N, cl_double alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDspmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDspr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDspr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsymm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsymv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsymvEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyr2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, cl_double beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyr2kEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyrk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t lda, cl_double beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDsyrkEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtbsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtpsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrmm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrmmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrsm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrsmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDtrsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDzasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasDznrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasGetVersion)(cl_uint* major, cl_uint* minor, cl_uint* patch); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasRemoveScratchImage)(cl_ulong imageID); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSaxpy)(size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasScasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasScnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasScopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSdot)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSetup)(); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSgbmv)(clAmdBlasOrder order, clAmdBlasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSgemm)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, cl_float beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSgemmEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSgemv)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSgemvEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSger)(clAmdBlasOrder order, size_t M, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_float C, cl_float S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSrotg)(cl_mem SA, size_t offSA, cl_mem SB, size_t offSB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSrotm)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, const cl_mem SPARAM, size_t offSparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSrotmg)(cl_mem SD1, size_t offSD1, cl_mem SD2, size_t offSD2, cl_mem SX1, size_t offSX1, const cl_mem SY1, size_t offSY1, cl_mem SPARAM, size_t offSparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSscal)(size_t N, cl_float alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSspmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSspr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSspr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsymm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsymv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsymvEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyr2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, cl_float beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyr2kEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyrk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t lda, cl_float beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasSsyrkEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStbsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStpsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrmm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrmmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrsm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrsmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasStrsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT void (*clAmdBlasTeardown)(); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZaxpy)(size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZdotc)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZdotu)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZdrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_double C, cl_double S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZdscal)(size_t N, cl_double alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgbmv)(clAmdBlasOrder order, clAmdBlasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgemm)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, DoubleComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgemmEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, clAmdBlasTranspose transB, size_t M, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgemv)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t lda, const cl_mem x, size_t offx, int incx, DoubleComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgemvEx)(clAmdBlasOrder order, clAmdBlasTranspose transA, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, DoubleComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgerc)(clAmdBlasOrder order, size_t M, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZgeru)(clAmdBlasOrder order, size_t M, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, size_t K, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhemm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhemv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, DoubleComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, DoubleComplex beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZher)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZher2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZher2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZherk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, double alpha, const cl_mem A, size_t offa, size_t lda, double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double2 alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhpr)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZhpr2)(clAmdBlasOrder order, clAmdBlasUplo uplo, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZrotg)(cl_mem CA, size_t offCA, cl_mem CB, size_t offCB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZscal)(size_t N, cl_double2 alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZsymm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, size_t M, size_t N, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZsyr2k)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t lda, const cl_mem B, size_t ldb, DoubleComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZsyr2kEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transAB, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZsyrk)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t lda, DoubleComplex beta, cl_mem C, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZsyrkEx)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose transA, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtbmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtbsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtpmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtpsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrmm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrmmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrmv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrsm)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t lda, cl_mem B, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrsmEx)(clAmdBlasOrder order, clAmdBlasSide side, clAmdBlasUplo uplo, clAmdBlasTranspose transA, clAmdBlasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasZtrsv)(clAmdBlasOrder order, clAmdBlasUplo uplo, clAmdBlasTranspose trans, clAmdBlasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasiCamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasiDamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasiSamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); +//extern CL_RUNTIME_EXPORT clAmdBlasStatus (*clAmdBlasiZamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events); diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdfft.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdfft.hpp new file mode 100644 index 00000000..1457d7eb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_clamdfft.hpp @@ -0,0 +1,142 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP +#error "Invalid usage" +#endif + +// generated by parser_clamdfft.py +#define clAmdFftBakePlan clAmdFftBakePlan_ +#define clAmdFftCopyPlan clAmdFftCopyPlan_ +#define clAmdFftCreateDefaultPlan clAmdFftCreateDefaultPlan_ +#define clAmdFftDestroyPlan clAmdFftDestroyPlan_ +#define clAmdFftEnqueueTransform clAmdFftEnqueueTransform_ +#define clAmdFftGetLayout clAmdFftGetLayout_ +#define clAmdFftGetPlanBatchSize clAmdFftGetPlanBatchSize_ +#define clAmdFftGetPlanContext clAmdFftGetPlanContext_ +#define clAmdFftGetPlanDim clAmdFftGetPlanDim_ +#define clAmdFftGetPlanDistance clAmdFftGetPlanDistance_ +#define clAmdFftGetPlanInStride clAmdFftGetPlanInStride_ +#define clAmdFftGetPlanLength clAmdFftGetPlanLength_ +#define clAmdFftGetPlanOutStride clAmdFftGetPlanOutStride_ +#define clAmdFftGetPlanPrecision clAmdFftGetPlanPrecision_ +#define clAmdFftGetPlanScale clAmdFftGetPlanScale_ +#define clAmdFftGetPlanTransposeResult clAmdFftGetPlanTransposeResult_ +#define clAmdFftGetResultLocation clAmdFftGetResultLocation_ +#define clAmdFftGetTmpBufSize clAmdFftGetTmpBufSize_ +#define clAmdFftGetVersion clAmdFftGetVersion_ +#define clAmdFftSetLayout clAmdFftSetLayout_ +#define clAmdFftSetPlanBatchSize clAmdFftSetPlanBatchSize_ +#define clAmdFftSetPlanDim clAmdFftSetPlanDim_ +#define clAmdFftSetPlanDistance clAmdFftSetPlanDistance_ +#define clAmdFftSetPlanInStride clAmdFftSetPlanInStride_ +#define clAmdFftSetPlanLength clAmdFftSetPlanLength_ +#define clAmdFftSetPlanOutStride clAmdFftSetPlanOutStride_ +#define clAmdFftSetPlanPrecision clAmdFftSetPlanPrecision_ +#define clAmdFftSetPlanScale clAmdFftSetPlanScale_ +#define clAmdFftSetPlanTransposeResult clAmdFftSetPlanTransposeResult_ +#define clAmdFftSetResultLocation clAmdFftSetResultLocation_ +#define clAmdFftSetup clAmdFftSetup_ +#define clAmdFftTeardown clAmdFftTeardown_ + +#include + +// generated by parser_clamdfft.py +#undef clAmdFftBakePlan +#define clAmdFftBakePlan clAmdFftBakePlan_pfn +#undef clAmdFftCopyPlan +//#define clAmdFftCopyPlan clAmdFftCopyPlan_pfn +#undef clAmdFftCreateDefaultPlan +#define clAmdFftCreateDefaultPlan clAmdFftCreateDefaultPlan_pfn +#undef clAmdFftDestroyPlan +#define clAmdFftDestroyPlan clAmdFftDestroyPlan_pfn +#undef clAmdFftEnqueueTransform +#define clAmdFftEnqueueTransform clAmdFftEnqueueTransform_pfn +#undef clAmdFftGetLayout +//#define clAmdFftGetLayout clAmdFftGetLayout_pfn +#undef clAmdFftGetPlanBatchSize +//#define clAmdFftGetPlanBatchSize clAmdFftGetPlanBatchSize_pfn +#undef clAmdFftGetPlanContext +//#define clAmdFftGetPlanContext clAmdFftGetPlanContext_pfn +#undef clAmdFftGetPlanDim +//#define clAmdFftGetPlanDim clAmdFftGetPlanDim_pfn +#undef clAmdFftGetPlanDistance +//#define clAmdFftGetPlanDistance clAmdFftGetPlanDistance_pfn +#undef clAmdFftGetPlanInStride +//#define clAmdFftGetPlanInStride clAmdFftGetPlanInStride_pfn +#undef clAmdFftGetPlanLength +//#define clAmdFftGetPlanLength clAmdFftGetPlanLength_pfn +#undef clAmdFftGetPlanOutStride +//#define clAmdFftGetPlanOutStride clAmdFftGetPlanOutStride_pfn +#undef clAmdFftGetPlanPrecision +//#define clAmdFftGetPlanPrecision clAmdFftGetPlanPrecision_pfn +#undef clAmdFftGetPlanScale +//#define clAmdFftGetPlanScale clAmdFftGetPlanScale_pfn +#undef clAmdFftGetPlanTransposeResult +//#define clAmdFftGetPlanTransposeResult clAmdFftGetPlanTransposeResult_pfn +#undef clAmdFftGetResultLocation +//#define clAmdFftGetResultLocation clAmdFftGetResultLocation_pfn +#undef clAmdFftGetTmpBufSize +#define clAmdFftGetTmpBufSize clAmdFftGetTmpBufSize_pfn +#undef clAmdFftGetVersion +#define clAmdFftGetVersion clAmdFftGetVersion_pfn +#undef clAmdFftSetLayout +#define clAmdFftSetLayout clAmdFftSetLayout_pfn +#undef clAmdFftSetPlanBatchSize +#define clAmdFftSetPlanBatchSize clAmdFftSetPlanBatchSize_pfn +#undef clAmdFftSetPlanDim +//#define clAmdFftSetPlanDim clAmdFftSetPlanDim_pfn +#undef clAmdFftSetPlanDistance +#define clAmdFftSetPlanDistance clAmdFftSetPlanDistance_pfn +#undef clAmdFftSetPlanInStride +#define clAmdFftSetPlanInStride clAmdFftSetPlanInStride_pfn +#undef clAmdFftSetPlanLength +//#define clAmdFftSetPlanLength clAmdFftSetPlanLength_pfn +#undef clAmdFftSetPlanOutStride +#define clAmdFftSetPlanOutStride clAmdFftSetPlanOutStride_pfn +#undef clAmdFftSetPlanPrecision +#define clAmdFftSetPlanPrecision clAmdFftSetPlanPrecision_pfn +#undef clAmdFftSetPlanScale +#define clAmdFftSetPlanScale clAmdFftSetPlanScale_pfn +#undef clAmdFftSetPlanTransposeResult +//#define clAmdFftSetPlanTransposeResult clAmdFftSetPlanTransposeResult_pfn +#undef clAmdFftSetResultLocation +#define clAmdFftSetResultLocation clAmdFftSetResultLocation_pfn +#undef clAmdFftSetup +#define clAmdFftSetup clAmdFftSetup_pfn +#undef clAmdFftTeardown +#define clAmdFftTeardown clAmdFftTeardown_pfn + +// generated by parser_clamdfft.py +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftBakePlan)(clAmdFftPlanHandle plHandle, cl_uint numQueues, cl_command_queue* commQueueFFT, void (CL_CALLBACK* pfn_notify) (clAmdFftPlanHandle plHandle, void* user_data), void* user_data); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftCopyPlan)(clAmdFftPlanHandle* out_plHandle, cl_context new_context, clAmdFftPlanHandle in_plHandle); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftCreateDefaultPlan)(clAmdFftPlanHandle* plHandle, cl_context context, const clAmdFftDim dim, const size_t* clLengths); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftDestroyPlan)(clAmdFftPlanHandle* plHandle); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftEnqueueTransform)(clAmdFftPlanHandle plHandle, clAmdFftDirection dir, cl_uint numQueuesAndEvents, cl_command_queue* commQueues, cl_uint numWaitEvents, const cl_event* waitEvents, cl_event* outEvents, cl_mem* inputBuffers, cl_mem* outputBuffers, cl_mem tmpBuffer); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetLayout)(const clAmdFftPlanHandle plHandle, clAmdFftLayout* iLayout, clAmdFftLayout* oLayout); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanBatchSize)(const clAmdFftPlanHandle plHandle, size_t* batchSize); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanContext)(const clAmdFftPlanHandle plHandle, cl_context* context); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanDim)(const clAmdFftPlanHandle plHandle, clAmdFftDim* dim, cl_uint* size); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanDistance)(const clAmdFftPlanHandle plHandle, size_t* iDist, size_t* oDist); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanInStride)(const clAmdFftPlanHandle plHandle, const clAmdFftDim dim, size_t* clStrides); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanLength)(const clAmdFftPlanHandle plHandle, const clAmdFftDim dim, size_t* clLengths); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanOutStride)(const clAmdFftPlanHandle plHandle, const clAmdFftDim dim, size_t* clStrides); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanPrecision)(const clAmdFftPlanHandle plHandle, clAmdFftPrecision* precision); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanScale)(const clAmdFftPlanHandle plHandle, clAmdFftDirection dir, cl_float* scale); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetPlanTransposeResult)(const clAmdFftPlanHandle plHandle, clAmdFftResultTransposed* transposed); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetResultLocation)(const clAmdFftPlanHandle plHandle, clAmdFftResultLocation* placeness); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetTmpBufSize)(const clAmdFftPlanHandle plHandle, size_t* buffersize); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftGetVersion)(cl_uint* major, cl_uint* minor, cl_uint* patch); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetLayout)(clAmdFftPlanHandle plHandle, clAmdFftLayout iLayout, clAmdFftLayout oLayout); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanBatchSize)(clAmdFftPlanHandle plHandle, size_t batchSize); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanDim)(clAmdFftPlanHandle plHandle, const clAmdFftDim dim); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanDistance)(clAmdFftPlanHandle plHandle, size_t iDist, size_t oDist); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanInStride)(clAmdFftPlanHandle plHandle, const clAmdFftDim dim, size_t* clStrides); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanLength)(clAmdFftPlanHandle plHandle, const clAmdFftDim dim, const size_t* clLengths); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanOutStride)(clAmdFftPlanHandle plHandle, const clAmdFftDim dim, size_t* clStrides); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanPrecision)(clAmdFftPlanHandle plHandle, clAmdFftPrecision precision); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanScale)(clAmdFftPlanHandle plHandle, clAmdFftDirection dir, cl_float scale); +//extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetPlanTransposeResult)(clAmdFftPlanHandle plHandle, clAmdFftResultTransposed transposed); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetResultLocation)(clAmdFftPlanHandle plHandle, clAmdFftResultLocation placeness); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftSetup)(const clAmdFftSetupData* setupData); +extern CL_RUNTIME_EXPORT clAmdFftStatus (*clAmdFftTeardown)(); diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core.hpp new file mode 100644 index 00000000..28618a1f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core.hpp @@ -0,0 +1,371 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP +#error "Invalid usage" +#endif + +// generated by parser_cl.py +#define clBuildProgram clBuildProgram_ +#define clCompileProgram clCompileProgram_ +#define clCreateBuffer clCreateBuffer_ +#define clCreateCommandQueue clCreateCommandQueue_ +#define clCreateContext clCreateContext_ +#define clCreateContextFromType clCreateContextFromType_ +#define clCreateImage clCreateImage_ +#define clCreateImage2D clCreateImage2D_ +#define clCreateImage3D clCreateImage3D_ +#define clCreateKernel clCreateKernel_ +#define clCreateKernelsInProgram clCreateKernelsInProgram_ +#define clCreateProgramWithBinary clCreateProgramWithBinary_ +#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_ +#define clCreateProgramWithSource clCreateProgramWithSource_ +#define clCreateSampler clCreateSampler_ +#define clCreateSubBuffer clCreateSubBuffer_ +#define clCreateSubDevices clCreateSubDevices_ +#define clCreateUserEvent clCreateUserEvent_ +#define clEnqueueBarrier clEnqueueBarrier_ +#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_ +#define clEnqueueCopyBuffer clEnqueueCopyBuffer_ +#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_ +#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_ +#define clEnqueueCopyImage clEnqueueCopyImage_ +#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_ +#define clEnqueueFillBuffer clEnqueueFillBuffer_ +#define clEnqueueFillImage clEnqueueFillImage_ +#define clEnqueueMapBuffer clEnqueueMapBuffer_ +#define clEnqueueMapImage clEnqueueMapImage_ +#define clEnqueueMarker clEnqueueMarker_ +#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_ +#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_ +#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_ +#define clEnqueueNativeKernel clEnqueueNativeKernel_ +#define clEnqueueReadBuffer clEnqueueReadBuffer_ +#define clEnqueueReadBufferRect clEnqueueReadBufferRect_ +#define clEnqueueReadImage clEnqueueReadImage_ +#define clEnqueueTask clEnqueueTask_ +#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_ +#define clEnqueueWaitForEvents clEnqueueWaitForEvents_ +#define clEnqueueWriteBuffer clEnqueueWriteBuffer_ +#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_ +#define clEnqueueWriteImage clEnqueueWriteImage_ +#define clFinish clFinish_ +#define clFlush clFlush_ +#define clGetCommandQueueInfo clGetCommandQueueInfo_ +#define clGetContextInfo clGetContextInfo_ +#define clGetDeviceIDs clGetDeviceIDs_ +#define clGetDeviceInfo clGetDeviceInfo_ +#define clGetEventInfo clGetEventInfo_ +#define clGetEventProfilingInfo clGetEventProfilingInfo_ +#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_ +#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_ +#define clGetImageInfo clGetImageInfo_ +#define clGetKernelArgInfo clGetKernelArgInfo_ +#define clGetKernelInfo clGetKernelInfo_ +#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_ +#define clGetMemObjectInfo clGetMemObjectInfo_ +#define clGetPlatformIDs clGetPlatformIDs_ +#define clGetPlatformInfo clGetPlatformInfo_ +#define clGetProgramBuildInfo clGetProgramBuildInfo_ +#define clGetProgramInfo clGetProgramInfo_ +#define clGetSamplerInfo clGetSamplerInfo_ +#define clGetSupportedImageFormats clGetSupportedImageFormats_ +#define clLinkProgram clLinkProgram_ +#define clReleaseCommandQueue clReleaseCommandQueue_ +#define clReleaseContext clReleaseContext_ +#define clReleaseDevice clReleaseDevice_ +#define clReleaseEvent clReleaseEvent_ +#define clReleaseKernel clReleaseKernel_ +#define clReleaseMemObject clReleaseMemObject_ +#define clReleaseProgram clReleaseProgram_ +#define clReleaseSampler clReleaseSampler_ +#define clRetainCommandQueue clRetainCommandQueue_ +#define clRetainContext clRetainContext_ +#define clRetainDevice clRetainDevice_ +#define clRetainEvent clRetainEvent_ +#define clRetainKernel clRetainKernel_ +#define clRetainMemObject clRetainMemObject_ +#define clRetainProgram clRetainProgram_ +#define clRetainSampler clRetainSampler_ +#define clSetEventCallback clSetEventCallback_ +#define clSetKernelArg clSetKernelArg_ +#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_ +#define clSetUserEventStatus clSetUserEventStatus_ +#define clUnloadCompiler clUnloadCompiler_ +#define clUnloadPlatformCompiler clUnloadPlatformCompiler_ +#define clWaitForEvents clWaitForEvents_ + +#if defined __APPLE__ +#define CL_SILENCE_DEPRECATION +#include +#else +#include +#endif + +// generated by parser_cl.py +#undef clBuildProgram +#define clBuildProgram clBuildProgram_pfn +#undef clCompileProgram +#define clCompileProgram clCompileProgram_pfn +#undef clCreateBuffer +#define clCreateBuffer clCreateBuffer_pfn +#undef clCreateCommandQueue +#define clCreateCommandQueue clCreateCommandQueue_pfn +#undef clCreateContext +#define clCreateContext clCreateContext_pfn +#undef clCreateContextFromType +#define clCreateContextFromType clCreateContextFromType_pfn +#undef clCreateImage +#define clCreateImage clCreateImage_pfn +#undef clCreateImage2D +#define clCreateImage2D clCreateImage2D_pfn +#undef clCreateImage3D +#define clCreateImage3D clCreateImage3D_pfn +#undef clCreateKernel +#define clCreateKernel clCreateKernel_pfn +#undef clCreateKernelsInProgram +#define clCreateKernelsInProgram clCreateKernelsInProgram_pfn +#undef clCreateProgramWithBinary +#define clCreateProgramWithBinary clCreateProgramWithBinary_pfn +#undef clCreateProgramWithBuiltInKernels +#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_pfn +#undef clCreateProgramWithSource +#define clCreateProgramWithSource clCreateProgramWithSource_pfn +#undef clCreateSampler +#define clCreateSampler clCreateSampler_pfn +#undef clCreateSubBuffer +#define clCreateSubBuffer clCreateSubBuffer_pfn +#undef clCreateSubDevices +#define clCreateSubDevices clCreateSubDevices_pfn +#undef clCreateUserEvent +#define clCreateUserEvent clCreateUserEvent_pfn +#undef clEnqueueBarrier +#define clEnqueueBarrier clEnqueueBarrier_pfn +#undef clEnqueueBarrierWithWaitList +#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_pfn +#undef clEnqueueCopyBuffer +#define clEnqueueCopyBuffer clEnqueueCopyBuffer_pfn +#undef clEnqueueCopyBufferRect +#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_pfn +#undef clEnqueueCopyBufferToImage +#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_pfn +#undef clEnqueueCopyImage +#define clEnqueueCopyImage clEnqueueCopyImage_pfn +#undef clEnqueueCopyImageToBuffer +#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_pfn +#undef clEnqueueFillBuffer +#define clEnqueueFillBuffer clEnqueueFillBuffer_pfn +#undef clEnqueueFillImage +#define clEnqueueFillImage clEnqueueFillImage_pfn +#undef clEnqueueMapBuffer +#define clEnqueueMapBuffer clEnqueueMapBuffer_pfn +#undef clEnqueueMapImage +#define clEnqueueMapImage clEnqueueMapImage_pfn +#undef clEnqueueMarker +#define clEnqueueMarker clEnqueueMarker_pfn +#undef clEnqueueMarkerWithWaitList +#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_pfn +#undef clEnqueueMigrateMemObjects +#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_pfn +#undef clEnqueueNDRangeKernel +#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_pfn +#undef clEnqueueNativeKernel +#define clEnqueueNativeKernel clEnqueueNativeKernel_pfn +#undef clEnqueueReadBuffer +#define clEnqueueReadBuffer clEnqueueReadBuffer_pfn +#undef clEnqueueReadBufferRect +#define clEnqueueReadBufferRect clEnqueueReadBufferRect_pfn +#undef clEnqueueReadImage +#define clEnqueueReadImage clEnqueueReadImage_pfn +#undef clEnqueueTask +#define clEnqueueTask clEnqueueTask_pfn +#undef clEnqueueUnmapMemObject +#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_pfn +#undef clEnqueueWaitForEvents +#define clEnqueueWaitForEvents clEnqueueWaitForEvents_pfn +#undef clEnqueueWriteBuffer +#define clEnqueueWriteBuffer clEnqueueWriteBuffer_pfn +#undef clEnqueueWriteBufferRect +#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_pfn +#undef clEnqueueWriteImage +#define clEnqueueWriteImage clEnqueueWriteImage_pfn +#undef clFinish +#define clFinish clFinish_pfn +#undef clFlush +#define clFlush clFlush_pfn +#undef clGetCommandQueueInfo +#define clGetCommandQueueInfo clGetCommandQueueInfo_pfn +#undef clGetContextInfo +#define clGetContextInfo clGetContextInfo_pfn +#undef clGetDeviceIDs +#define clGetDeviceIDs clGetDeviceIDs_pfn +#undef clGetDeviceInfo +#define clGetDeviceInfo clGetDeviceInfo_pfn +#undef clGetEventInfo +#define clGetEventInfo clGetEventInfo_pfn +#undef clGetEventProfilingInfo +#define clGetEventProfilingInfo clGetEventProfilingInfo_pfn +#undef clGetExtensionFunctionAddress +#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_pfn +#undef clGetExtensionFunctionAddressForPlatform +#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_pfn +#undef clGetImageInfo +#define clGetImageInfo clGetImageInfo_pfn +#undef clGetKernelArgInfo +#define clGetKernelArgInfo clGetKernelArgInfo_pfn +#undef clGetKernelInfo +#define clGetKernelInfo clGetKernelInfo_pfn +#undef clGetKernelWorkGroupInfo +#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_pfn +#undef clGetMemObjectInfo +#define clGetMemObjectInfo clGetMemObjectInfo_pfn +#undef clGetPlatformIDs +#define clGetPlatformIDs clGetPlatformIDs_pfn +#undef clGetPlatformInfo +#define clGetPlatformInfo clGetPlatformInfo_pfn +#undef clGetProgramBuildInfo +#define clGetProgramBuildInfo clGetProgramBuildInfo_pfn +#undef clGetProgramInfo +#define clGetProgramInfo clGetProgramInfo_pfn +#undef clGetSamplerInfo +#define clGetSamplerInfo clGetSamplerInfo_pfn +#undef clGetSupportedImageFormats +#define clGetSupportedImageFormats clGetSupportedImageFormats_pfn +#undef clLinkProgram +#define clLinkProgram clLinkProgram_pfn +#undef clReleaseCommandQueue +#define clReleaseCommandQueue clReleaseCommandQueue_pfn +#undef clReleaseContext +#define clReleaseContext clReleaseContext_pfn +#undef clReleaseDevice +#define clReleaseDevice clReleaseDevice_pfn +#undef clReleaseEvent +#define clReleaseEvent clReleaseEvent_pfn +#undef clReleaseKernel +#define clReleaseKernel clReleaseKernel_pfn +#undef clReleaseMemObject +#define clReleaseMemObject clReleaseMemObject_pfn +#undef clReleaseProgram +#define clReleaseProgram clReleaseProgram_pfn +#undef clReleaseSampler +#define clReleaseSampler clReleaseSampler_pfn +#undef clRetainCommandQueue +#define clRetainCommandQueue clRetainCommandQueue_pfn +#undef clRetainContext +#define clRetainContext clRetainContext_pfn +#undef clRetainDevice +#define clRetainDevice clRetainDevice_pfn +#undef clRetainEvent +#define clRetainEvent clRetainEvent_pfn +#undef clRetainKernel +#define clRetainKernel clRetainKernel_pfn +#undef clRetainMemObject +#define clRetainMemObject clRetainMemObject_pfn +#undef clRetainProgram +#define clRetainProgram clRetainProgram_pfn +#undef clRetainSampler +#define clRetainSampler clRetainSampler_pfn +#undef clSetEventCallback +#define clSetEventCallback clSetEventCallback_pfn +#undef clSetKernelArg +#define clSetKernelArg clSetKernelArg_pfn +#undef clSetMemObjectDestructorCallback +#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_pfn +#undef clSetUserEventStatus +#define clSetUserEventStatus clSetUserEventStatus_pfn +#undef clUnloadCompiler +#define clUnloadCompiler clUnloadCompiler_pfn +#undef clUnloadPlatformCompiler +#define clUnloadPlatformCompiler clUnloadPlatformCompiler_pfn +#undef clWaitForEvents +#define clWaitForEvents clWaitForEvents_pfn + +// generated by parser_cl.py +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clBuildProgram)(cl_program, cl_uint, const cl_device_id*, const char*, void (CL_CALLBACK*) (cl_program, void*), void*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCompileProgram)(cl_program, cl_uint, const cl_device_id*, const char*, cl_uint, const cl_program*, const char**, void (CL_CALLBACK*) (cl_program, void*), void*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateBuffer)(cl_context, cl_mem_flags, size_t, void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_command_queue (CL_API_CALL*clCreateCommandQueue)(cl_context, cl_device_id, cl_command_queue_properties, cl_int*); +extern CL_RUNTIME_EXPORT cl_context (CL_API_CALL*clCreateContext)(const cl_context_properties*, cl_uint, const cl_device_id*, void (CL_CALLBACK*) (const char*, const void*, size_t, void*), void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_context (CL_API_CALL*clCreateContextFromType)(const cl_context_properties*, cl_device_type, void (CL_CALLBACK*) (const char*, const void*, size_t, void*), void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage)(cl_context, cl_mem_flags, const cl_image_format*, const cl_image_desc*, void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage2D)(cl_context, cl_mem_flags, const cl_image_format*, size_t, size_t, size_t, void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage3D)(cl_context, cl_mem_flags, const cl_image_format*, size_t, size_t, size_t, size_t, size_t, void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_kernel (CL_API_CALL*clCreateKernel)(cl_program, const char*, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCreateKernelsInProgram)(cl_program, cl_uint, cl_kernel*, cl_uint*); +extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithBinary)(cl_context, cl_uint, const cl_device_id*, const size_t*, const unsigned char**, cl_int*, cl_int*); +extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithBuiltInKernels)(cl_context, cl_uint, const cl_device_id*, const char*, cl_int*); +extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithSource)(cl_context, cl_uint, const char**, const size_t*, cl_int*); +extern CL_RUNTIME_EXPORT cl_sampler (CL_API_CALL*clCreateSampler)(cl_context, cl_bool, cl_addressing_mode, cl_filter_mode, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateSubBuffer)(cl_mem, cl_mem_flags, cl_buffer_create_type, const void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCreateSubDevices)(cl_device_id, const cl_device_partition_property*, cl_uint, cl_device_id*, cl_uint*); +extern CL_RUNTIME_EXPORT cl_event (CL_API_CALL*clCreateUserEvent)(cl_context, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueBarrier)(cl_command_queue); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueBarrierWithWaitList)(cl_command_queue, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBuffer)(cl_command_queue, cl_mem, cl_mem, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBufferRect)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBufferToImage)(cl_command_queue, cl_mem, cl_mem, size_t, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyImage)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyImageToBuffer)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, size_t, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueFillBuffer)(cl_command_queue, cl_mem, const void*, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueFillImage)(cl_command_queue, cl_mem, const void*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clEnqueueMapBuffer)(cl_command_queue, cl_mem, cl_bool, cl_map_flags, size_t, size_t, cl_uint, const cl_event*, cl_event*, cl_int*); +extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clEnqueueMapImage)(cl_command_queue, cl_mem, cl_bool, cl_map_flags, const size_t*, const size_t*, size_t*, size_t*, cl_uint, const cl_event*, cl_event*, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMarker)(cl_command_queue, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMarkerWithWaitList)(cl_command_queue, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMigrateMemObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_mem_migration_flags, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueNDRangeKernel)(cl_command_queue, cl_kernel, cl_uint, const size_t*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueNativeKernel)(cl_command_queue, void (CL_CALLBACK*) (void*), void*, size_t, cl_uint, const cl_mem*, const void**, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadBuffer)(cl_command_queue, cl_mem, cl_bool, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadBufferRect)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadImage)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueTask)(cl_command_queue, cl_kernel, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueUnmapMemObject)(cl_command_queue, cl_mem, void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWaitForEvents)(cl_command_queue, cl_uint, const cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteBuffer)(cl_command_queue, cl_mem, cl_bool, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteBufferRect)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteImage)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clFinish)(cl_command_queue); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clFlush)(cl_command_queue); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetCommandQueueInfo)(cl_command_queue, cl_command_queue_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetContextInfo)(cl_context, cl_context_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetDeviceIDs)(cl_platform_id, cl_device_type, cl_uint, cl_device_id*, cl_uint*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetDeviceInfo)(cl_device_id, cl_device_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetEventInfo)(cl_event, cl_event_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetEventProfilingInfo)(cl_event, cl_profiling_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clGetExtensionFunctionAddress)(const char*); +extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clGetExtensionFunctionAddressForPlatform)(cl_platform_id, const char*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetImageInfo)(cl_mem, cl_image_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelArgInfo)(cl_kernel, cl_uint, cl_kernel_arg_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelInfo)(cl_kernel, cl_kernel_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelWorkGroupInfo)(cl_kernel, cl_device_id, cl_kernel_work_group_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetMemObjectInfo)(cl_mem, cl_mem_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetPlatformIDs)(cl_uint, cl_platform_id*, cl_uint*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetPlatformInfo)(cl_platform_id, cl_platform_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetProgramBuildInfo)(cl_program, cl_device_id, cl_program_build_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetProgramInfo)(cl_program, cl_program_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetSamplerInfo)(cl_sampler, cl_sampler_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetSupportedImageFormats)(cl_context, cl_mem_flags, cl_mem_object_type, cl_uint, cl_image_format*, cl_uint*); +extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clLinkProgram)(cl_context, cl_uint, const cl_device_id*, const char*, cl_uint, const cl_program*, void (CL_CALLBACK*) (cl_program, void*), void*, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseCommandQueue)(cl_command_queue); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseContext)(cl_context); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseDevice)(cl_device_id); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseEvent)(cl_event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseKernel)(cl_kernel); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseMemObject)(cl_mem); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseProgram)(cl_program); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseSampler)(cl_sampler); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainCommandQueue)(cl_command_queue); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainContext)(cl_context); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainDevice)(cl_device_id); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainEvent)(cl_event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainKernel)(cl_kernel); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainMemObject)(cl_mem); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainProgram)(cl_program); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainSampler)(cl_sampler); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetEventCallback)(cl_event, cl_int, void (CL_CALLBACK*) (cl_event, cl_int, void*), void*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetKernelArg)(cl_kernel, cl_uint, size_t, const void*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetMemObjectDestructorCallback)(cl_mem, void (CL_CALLBACK*) (cl_mem, void*), void*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetUserEventStatus)(cl_event, cl_int); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clUnloadCompiler)(); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clUnloadPlatformCompiler)(cl_platform_id); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clWaitForEvents)(cl_uint, const cl_event*); diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core_wrappers.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core_wrappers.hpp new file mode 100644 index 00000000..216b22b8 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_core_wrappers.hpp @@ -0,0 +1,272 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_WRAPPERS_HPP +#error "Invalid usage" +#endif + +// generated by parser_cl.py +#undef clBuildProgram +#define clBuildProgram clBuildProgram_fn +inline cl_int clBuildProgram(cl_program p0, cl_uint p1, const cl_device_id* p2, const char* p3, void (CL_CALLBACK*p4) (cl_program, void*), void* p5) { return clBuildProgram_pfn(p0, p1, p2, p3, p4, p5); } +#undef clCompileProgram +#define clCompileProgram clCompileProgram_fn +inline cl_int clCompileProgram(cl_program p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_uint p4, const cl_program* p5, const char** p6, void (CL_CALLBACK*p7) (cl_program, void*), void* p8) { return clCompileProgram_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clCreateBuffer +#define clCreateBuffer clCreateBuffer_fn +inline cl_mem clCreateBuffer(cl_context p0, cl_mem_flags p1, size_t p2, void* p3, cl_int* p4) { return clCreateBuffer_pfn(p0, p1, p2, p3, p4); } +#undef clCreateCommandQueue +#define clCreateCommandQueue clCreateCommandQueue_fn +inline cl_command_queue clCreateCommandQueue(cl_context p0, cl_device_id p1, cl_command_queue_properties p2, cl_int* p3) { return clCreateCommandQueue_pfn(p0, p1, p2, p3); } +#undef clCreateContext +#define clCreateContext clCreateContext_fn +inline cl_context clCreateContext(const cl_context_properties* p0, cl_uint p1, const cl_device_id* p2, void (CL_CALLBACK*p3) (const char*, const void*, size_t, void*), void* p4, cl_int* p5) { return clCreateContext_pfn(p0, p1, p2, p3, p4, p5); } +#undef clCreateContextFromType +#define clCreateContextFromType clCreateContextFromType_fn +inline cl_context clCreateContextFromType(const cl_context_properties* p0, cl_device_type p1, void (CL_CALLBACK*p2) (const char*, const void*, size_t, void*), void* p3, cl_int* p4) { return clCreateContextFromType_pfn(p0, p1, p2, p3, p4); } +#undef clCreateImage +#define clCreateImage clCreateImage_fn +inline cl_mem clCreateImage(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, const cl_image_desc* p3, void* p4, cl_int* p5) { return clCreateImage_pfn(p0, p1, p2, p3, p4, p5); } +#undef clCreateImage2D +#define clCreateImage2D clCreateImage2D_fn +inline cl_mem clCreateImage2D(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, size_t p3, size_t p4, size_t p5, void* p6, cl_int* p7) { return clCreateImage2D_pfn(p0, p1, p2, p3, p4, p5, p6, p7); } +#undef clCreateImage3D +#define clCreateImage3D clCreateImage3D_fn +inline cl_mem clCreateImage3D(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, size_t p3, size_t p4, size_t p5, size_t p6, size_t p7, void* p8, cl_int* p9) { return clCreateImage3D_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); } +#undef clCreateKernel +#define clCreateKernel clCreateKernel_fn +inline cl_kernel clCreateKernel(cl_program p0, const char* p1, cl_int* p2) { return clCreateKernel_pfn(p0, p1, p2); } +#undef clCreateKernelsInProgram +#define clCreateKernelsInProgram clCreateKernelsInProgram_fn +inline cl_int clCreateKernelsInProgram(cl_program p0, cl_uint p1, cl_kernel* p2, cl_uint* p3) { return clCreateKernelsInProgram_pfn(p0, p1, p2, p3); } +#undef clCreateProgramWithBinary +#define clCreateProgramWithBinary clCreateProgramWithBinary_fn +inline cl_program clCreateProgramWithBinary(cl_context p0, cl_uint p1, const cl_device_id* p2, const size_t* p3, const unsigned char** p4, cl_int* p5, cl_int* p6) { return clCreateProgramWithBinary_pfn(p0, p1, p2, p3, p4, p5, p6); } +#undef clCreateProgramWithBuiltInKernels +#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_fn +inline cl_program clCreateProgramWithBuiltInKernels(cl_context p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_int* p4) { return clCreateProgramWithBuiltInKernels_pfn(p0, p1, p2, p3, p4); } +#undef clCreateProgramWithSource +#define clCreateProgramWithSource clCreateProgramWithSource_fn +inline cl_program clCreateProgramWithSource(cl_context p0, cl_uint p1, const char** p2, const size_t* p3, cl_int* p4) { return clCreateProgramWithSource_pfn(p0, p1, p2, p3, p4); } +#undef clCreateSampler +#define clCreateSampler clCreateSampler_fn +inline cl_sampler clCreateSampler(cl_context p0, cl_bool p1, cl_addressing_mode p2, cl_filter_mode p3, cl_int* p4) { return clCreateSampler_pfn(p0, p1, p2, p3, p4); } +#undef clCreateSubBuffer +#define clCreateSubBuffer clCreateSubBuffer_fn +inline cl_mem clCreateSubBuffer(cl_mem p0, cl_mem_flags p1, cl_buffer_create_type p2, const void* p3, cl_int* p4) { return clCreateSubBuffer_pfn(p0, p1, p2, p3, p4); } +#undef clCreateSubDevices +#define clCreateSubDevices clCreateSubDevices_fn +inline cl_int clCreateSubDevices(cl_device_id p0, const cl_device_partition_property* p1, cl_uint p2, cl_device_id* p3, cl_uint* p4) { return clCreateSubDevices_pfn(p0, p1, p2, p3, p4); } +#undef clCreateUserEvent +#define clCreateUserEvent clCreateUserEvent_fn +inline cl_event clCreateUserEvent(cl_context p0, cl_int* p1) { return clCreateUserEvent_pfn(p0, p1); } +#undef clEnqueueBarrier +#define clEnqueueBarrier clEnqueueBarrier_fn +inline cl_int clEnqueueBarrier(cl_command_queue p0) { return clEnqueueBarrier_pfn(p0); } +#undef clEnqueueBarrierWithWaitList +#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_fn +inline cl_int clEnqueueBarrierWithWaitList(cl_command_queue p0, cl_uint p1, const cl_event* p2, cl_event* p3) { return clEnqueueBarrierWithWaitList_pfn(p0, p1, p2, p3); } +#undef clEnqueueCopyBuffer +#define clEnqueueCopyBuffer clEnqueueCopyBuffer_fn +inline cl_int clEnqueueCopyBuffer(cl_command_queue p0, cl_mem p1, cl_mem p2, size_t p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueCopyBufferRect +#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_fn +inline cl_int clEnqueueCopyBufferRect(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, cl_uint p10, const cl_event* p11, cl_event* p12) { return clEnqueueCopyBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12); } +#undef clEnqueueCopyBufferToImage +#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_fn +inline cl_int clEnqueueCopyBufferToImage(cl_command_queue p0, cl_mem p1, cl_mem p2, size_t p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyBufferToImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueCopyImage +#define clEnqueueCopyImage clEnqueueCopyImage_fn +inline cl_int clEnqueueCopyImage(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueCopyImageToBuffer +#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_fn +inline cl_int clEnqueueCopyImageToBuffer(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyImageToBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueFillBuffer +#define clEnqueueFillBuffer clEnqueueFillBuffer_fn +inline cl_int clEnqueueFillBuffer(cl_command_queue p0, cl_mem p1, const void* p2, size_t p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueFillBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueFillImage +#define clEnqueueFillImage clEnqueueFillImage_fn +inline cl_int clEnqueueFillImage(cl_command_queue p0, cl_mem p1, const void* p2, const size_t* p3, const size_t* p4, cl_uint p5, const cl_event* p6, cl_event* p7) { return clEnqueueFillImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7); } +#undef clEnqueueMapBuffer +#define clEnqueueMapBuffer clEnqueueMapBuffer_fn +inline void* clEnqueueMapBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, cl_map_flags p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8, cl_int* p9) { return clEnqueueMapBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); } +#undef clEnqueueMapImage +#define clEnqueueMapImage clEnqueueMapImage_fn +inline void* clEnqueueMapImage(cl_command_queue p0, cl_mem p1, cl_bool p2, cl_map_flags p3, const size_t* p4, const size_t* p5, size_t* p6, size_t* p7, cl_uint p8, const cl_event* p9, cl_event* p10, cl_int* p11) { return clEnqueueMapImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11); } +#undef clEnqueueMarker +#define clEnqueueMarker clEnqueueMarker_fn +inline cl_int clEnqueueMarker(cl_command_queue p0, cl_event* p1) { return clEnqueueMarker_pfn(p0, p1); } +#undef clEnqueueMarkerWithWaitList +#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_fn +inline cl_int clEnqueueMarkerWithWaitList(cl_command_queue p0, cl_uint p1, const cl_event* p2, cl_event* p3) { return clEnqueueMarkerWithWaitList_pfn(p0, p1, p2, p3); } +#undef clEnqueueMigrateMemObjects +#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_fn +inline cl_int clEnqueueMigrateMemObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_mem_migration_flags p3, cl_uint p4, const cl_event* p5, cl_event* p6) { return clEnqueueMigrateMemObjects_pfn(p0, p1, p2, p3, p4, p5, p6); } +#undef clEnqueueNDRangeKernel +#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_fn +inline cl_int clEnqueueNDRangeKernel(cl_command_queue p0, cl_kernel p1, cl_uint p2, const size_t* p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueNDRangeKernel_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueNativeKernel +#define clEnqueueNativeKernel clEnqueueNativeKernel_fn +inline cl_int clEnqueueNativeKernel(cl_command_queue p0, void (CL_CALLBACK*p1) (void*), void* p2, size_t p3, cl_uint p4, const cl_mem* p5, const void** p6, cl_uint p7, const cl_event* p8, cl_event* p9) { return clEnqueueNativeKernel_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); } +#undef clEnqueueReadBuffer +#define clEnqueueReadBuffer clEnqueueReadBuffer_fn +inline cl_int clEnqueueReadBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, size_t p3, size_t p4, void* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueReadBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueReadBufferRect +#define clEnqueueReadBufferRect clEnqueueReadBufferRect_fn +inline cl_int clEnqueueReadBufferRect(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, void* p10, cl_uint p11, const cl_event* p12, cl_event* p13) { return clEnqueueReadBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13); } +#undef clEnqueueReadImage +#define clEnqueueReadImage clEnqueueReadImage_fn +inline cl_int clEnqueueReadImage(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, size_t p5, size_t p6, void* p7, cl_uint p8, const cl_event* p9, cl_event* p10) { return clEnqueueReadImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10); } +#undef clEnqueueTask +#define clEnqueueTask clEnqueueTask_fn +inline cl_int clEnqueueTask(cl_command_queue p0, cl_kernel p1, cl_uint p2, const cl_event* p3, cl_event* p4) { return clEnqueueTask_pfn(p0, p1, p2, p3, p4); } +#undef clEnqueueUnmapMemObject +#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_fn +inline cl_int clEnqueueUnmapMemObject(cl_command_queue p0, cl_mem p1, void* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueUnmapMemObject_pfn(p0, p1, p2, p3, p4, p5); } +#undef clEnqueueWaitForEvents +#define clEnqueueWaitForEvents clEnqueueWaitForEvents_fn +inline cl_int clEnqueueWaitForEvents(cl_command_queue p0, cl_uint p1, const cl_event* p2) { return clEnqueueWaitForEvents_pfn(p0, p1, p2); } +#undef clEnqueueWriteBuffer +#define clEnqueueWriteBuffer clEnqueueWriteBuffer_fn +inline cl_int clEnqueueWriteBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, size_t p3, size_t p4, const void* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueWriteBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clEnqueueWriteBufferRect +#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_fn +inline cl_int clEnqueueWriteBufferRect(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, const void* p10, cl_uint p11, const cl_event* p12, cl_event* p13) { return clEnqueueWriteBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13); } +#undef clEnqueueWriteImage +#define clEnqueueWriteImage clEnqueueWriteImage_fn +inline cl_int clEnqueueWriteImage(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, size_t p5, size_t p6, const void* p7, cl_uint p8, const cl_event* p9, cl_event* p10) { return clEnqueueWriteImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10); } +#undef clFinish +#define clFinish clFinish_fn +inline cl_int clFinish(cl_command_queue p0) { return clFinish_pfn(p0); } +#undef clFlush +#define clFlush clFlush_fn +inline cl_int clFlush(cl_command_queue p0) { return clFlush_pfn(p0); } +#undef clGetCommandQueueInfo +#define clGetCommandQueueInfo clGetCommandQueueInfo_fn +inline cl_int clGetCommandQueueInfo(cl_command_queue p0, cl_command_queue_info p1, size_t p2, void* p3, size_t* p4) { return clGetCommandQueueInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetContextInfo +#define clGetContextInfo clGetContextInfo_fn +inline cl_int clGetContextInfo(cl_context p0, cl_context_info p1, size_t p2, void* p3, size_t* p4) { return clGetContextInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetDeviceIDs +#define clGetDeviceIDs clGetDeviceIDs_fn +inline cl_int clGetDeviceIDs(cl_platform_id p0, cl_device_type p1, cl_uint p2, cl_device_id* p3, cl_uint* p4) { return clGetDeviceIDs_pfn(p0, p1, p2, p3, p4); } +#undef clGetDeviceInfo +#define clGetDeviceInfo clGetDeviceInfo_fn +inline cl_int clGetDeviceInfo(cl_device_id p0, cl_device_info p1, size_t p2, void* p3, size_t* p4) { return clGetDeviceInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetEventInfo +#define clGetEventInfo clGetEventInfo_fn +inline cl_int clGetEventInfo(cl_event p0, cl_event_info p1, size_t p2, void* p3, size_t* p4) { return clGetEventInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetEventProfilingInfo +#define clGetEventProfilingInfo clGetEventProfilingInfo_fn +inline cl_int clGetEventProfilingInfo(cl_event p0, cl_profiling_info p1, size_t p2, void* p3, size_t* p4) { return clGetEventProfilingInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetExtensionFunctionAddress +#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_fn +inline void* clGetExtensionFunctionAddress(const char* p0) { return clGetExtensionFunctionAddress_pfn(p0); } +#undef clGetExtensionFunctionAddressForPlatform +#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_fn +inline void* clGetExtensionFunctionAddressForPlatform(cl_platform_id p0, const char* p1) { return clGetExtensionFunctionAddressForPlatform_pfn(p0, p1); } +#undef clGetImageInfo +#define clGetImageInfo clGetImageInfo_fn +inline cl_int clGetImageInfo(cl_mem p0, cl_image_info p1, size_t p2, void* p3, size_t* p4) { return clGetImageInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetKernelArgInfo +#define clGetKernelArgInfo clGetKernelArgInfo_fn +inline cl_int clGetKernelArgInfo(cl_kernel p0, cl_uint p1, cl_kernel_arg_info p2, size_t p3, void* p4, size_t* p5) { return clGetKernelArgInfo_pfn(p0, p1, p2, p3, p4, p5); } +#undef clGetKernelInfo +#define clGetKernelInfo clGetKernelInfo_fn +inline cl_int clGetKernelInfo(cl_kernel p0, cl_kernel_info p1, size_t p2, void* p3, size_t* p4) { return clGetKernelInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetKernelWorkGroupInfo +#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_fn +inline cl_int clGetKernelWorkGroupInfo(cl_kernel p0, cl_device_id p1, cl_kernel_work_group_info p2, size_t p3, void* p4, size_t* p5) { return clGetKernelWorkGroupInfo_pfn(p0, p1, p2, p3, p4, p5); } +#undef clGetMemObjectInfo +#define clGetMemObjectInfo clGetMemObjectInfo_fn +inline cl_int clGetMemObjectInfo(cl_mem p0, cl_mem_info p1, size_t p2, void* p3, size_t* p4) { return clGetMemObjectInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetPlatformIDs +#define clGetPlatformIDs clGetPlatformIDs_fn +inline cl_int clGetPlatformIDs(cl_uint p0, cl_platform_id* p1, cl_uint* p2) { return clGetPlatformIDs_pfn(p0, p1, p2); } +#undef clGetPlatformInfo +#define clGetPlatformInfo clGetPlatformInfo_fn +inline cl_int clGetPlatformInfo(cl_platform_id p0, cl_platform_info p1, size_t p2, void* p3, size_t* p4) { return clGetPlatformInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetProgramBuildInfo +#define clGetProgramBuildInfo clGetProgramBuildInfo_fn +inline cl_int clGetProgramBuildInfo(cl_program p0, cl_device_id p1, cl_program_build_info p2, size_t p3, void* p4, size_t* p5) { return clGetProgramBuildInfo_pfn(p0, p1, p2, p3, p4, p5); } +#undef clGetProgramInfo +#define clGetProgramInfo clGetProgramInfo_fn +inline cl_int clGetProgramInfo(cl_program p0, cl_program_info p1, size_t p2, void* p3, size_t* p4) { return clGetProgramInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetSamplerInfo +#define clGetSamplerInfo clGetSamplerInfo_fn +inline cl_int clGetSamplerInfo(cl_sampler p0, cl_sampler_info p1, size_t p2, void* p3, size_t* p4) { return clGetSamplerInfo_pfn(p0, p1, p2, p3, p4); } +#undef clGetSupportedImageFormats +#define clGetSupportedImageFormats clGetSupportedImageFormats_fn +inline cl_int clGetSupportedImageFormats(cl_context p0, cl_mem_flags p1, cl_mem_object_type p2, cl_uint p3, cl_image_format* p4, cl_uint* p5) { return clGetSupportedImageFormats_pfn(p0, p1, p2, p3, p4, p5); } +#undef clLinkProgram +#define clLinkProgram clLinkProgram_fn +inline cl_program clLinkProgram(cl_context p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_uint p4, const cl_program* p5, void (CL_CALLBACK*p6) (cl_program, void*), void* p7, cl_int* p8) { return clLinkProgram_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); } +#undef clReleaseCommandQueue +#define clReleaseCommandQueue clReleaseCommandQueue_fn +inline cl_int clReleaseCommandQueue(cl_command_queue p0) { return clReleaseCommandQueue_pfn(p0); } +#undef clReleaseContext +#define clReleaseContext clReleaseContext_fn +inline cl_int clReleaseContext(cl_context p0) { return clReleaseContext_pfn(p0); } +#undef clReleaseDevice +#define clReleaseDevice clReleaseDevice_fn +inline cl_int clReleaseDevice(cl_device_id p0) { return clReleaseDevice_pfn(p0); } +#undef clReleaseEvent +#define clReleaseEvent clReleaseEvent_fn +inline cl_int clReleaseEvent(cl_event p0) { return clReleaseEvent_pfn(p0); } +#undef clReleaseKernel +#define clReleaseKernel clReleaseKernel_fn +inline cl_int clReleaseKernel(cl_kernel p0) { return clReleaseKernel_pfn(p0); } +#undef clReleaseMemObject +#define clReleaseMemObject clReleaseMemObject_fn +inline cl_int clReleaseMemObject(cl_mem p0) { return clReleaseMemObject_pfn(p0); } +#undef clReleaseProgram +#define clReleaseProgram clReleaseProgram_fn +inline cl_int clReleaseProgram(cl_program p0) { return clReleaseProgram_pfn(p0); } +#undef clReleaseSampler +#define clReleaseSampler clReleaseSampler_fn +inline cl_int clReleaseSampler(cl_sampler p0) { return clReleaseSampler_pfn(p0); } +#undef clRetainCommandQueue +#define clRetainCommandQueue clRetainCommandQueue_fn +inline cl_int clRetainCommandQueue(cl_command_queue p0) { return clRetainCommandQueue_pfn(p0); } +#undef clRetainContext +#define clRetainContext clRetainContext_fn +inline cl_int clRetainContext(cl_context p0) { return clRetainContext_pfn(p0); } +#undef clRetainDevice +#define clRetainDevice clRetainDevice_fn +inline cl_int clRetainDevice(cl_device_id p0) { return clRetainDevice_pfn(p0); } +#undef clRetainEvent +#define clRetainEvent clRetainEvent_fn +inline cl_int clRetainEvent(cl_event p0) { return clRetainEvent_pfn(p0); } +#undef clRetainKernel +#define clRetainKernel clRetainKernel_fn +inline cl_int clRetainKernel(cl_kernel p0) { return clRetainKernel_pfn(p0); } +#undef clRetainMemObject +#define clRetainMemObject clRetainMemObject_fn +inline cl_int clRetainMemObject(cl_mem p0) { return clRetainMemObject_pfn(p0); } +#undef clRetainProgram +#define clRetainProgram clRetainProgram_fn +inline cl_int clRetainProgram(cl_program p0) { return clRetainProgram_pfn(p0); } +#undef clRetainSampler +#define clRetainSampler clRetainSampler_fn +inline cl_int clRetainSampler(cl_sampler p0) { return clRetainSampler_pfn(p0); } +#undef clSetEventCallback +#define clSetEventCallback clSetEventCallback_fn +inline cl_int clSetEventCallback(cl_event p0, cl_int p1, void (CL_CALLBACK*p2) (cl_event, cl_int, void*), void* p3) { return clSetEventCallback_pfn(p0, p1, p2, p3); } +#undef clSetKernelArg +#define clSetKernelArg clSetKernelArg_fn +inline cl_int clSetKernelArg(cl_kernel p0, cl_uint p1, size_t p2, const void* p3) { return clSetKernelArg_pfn(p0, p1, p2, p3); } +#undef clSetMemObjectDestructorCallback +#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_fn +inline cl_int clSetMemObjectDestructorCallback(cl_mem p0, void (CL_CALLBACK*p1) (cl_mem, void*), void* p2) { return clSetMemObjectDestructorCallback_pfn(p0, p1, p2); } +#undef clSetUserEventStatus +#define clSetUserEventStatus clSetUserEventStatus_fn +inline cl_int clSetUserEventStatus(cl_event p0, cl_int p1) { return clSetUserEventStatus_pfn(p0, p1); } +#undef clUnloadCompiler +#define clUnloadCompiler clUnloadCompiler_fn +inline cl_int clUnloadCompiler() { return clUnloadCompiler_pfn(); } +#undef clUnloadPlatformCompiler +#define clUnloadPlatformCompiler clUnloadPlatformCompiler_fn +inline cl_int clUnloadPlatformCompiler(cl_platform_id p0) { return clUnloadPlatformCompiler_pfn(p0); } +#undef clWaitForEvents +#define clWaitForEvents clWaitForEvents_fn +inline cl_int clWaitForEvents(cl_uint p0, const cl_event* p1) { return clWaitForEvents_pfn(p0, p1); } diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl.hpp new file mode 100644 index 00000000..0b12aed6 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl.hpp @@ -0,0 +1,62 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_HPP +#error "Invalid usage" +#endif + +// generated by parser_cl.py +#define clCreateFromGLBuffer clCreateFromGLBuffer_ +#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_ +#define clCreateFromGLTexture clCreateFromGLTexture_ +#define clCreateFromGLTexture2D clCreateFromGLTexture2D_ +#define clCreateFromGLTexture3D clCreateFromGLTexture3D_ +#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_ +#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_ +#define clGetGLContextInfoKHR clGetGLContextInfoKHR_ +#define clGetGLObjectInfo clGetGLObjectInfo_ +#define clGetGLTextureInfo clGetGLTextureInfo_ + +#if defined __APPLE__ +#include +#else +#include +#endif + +// generated by parser_cl.py +#undef clCreateFromGLBuffer +#define clCreateFromGLBuffer clCreateFromGLBuffer_pfn +#undef clCreateFromGLRenderbuffer +#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_pfn +#undef clCreateFromGLTexture +#define clCreateFromGLTexture clCreateFromGLTexture_pfn +#undef clCreateFromGLTexture2D +#define clCreateFromGLTexture2D clCreateFromGLTexture2D_pfn +#undef clCreateFromGLTexture3D +#define clCreateFromGLTexture3D clCreateFromGLTexture3D_pfn +#undef clEnqueueAcquireGLObjects +#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_pfn +#undef clEnqueueReleaseGLObjects +#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_pfn +#undef clGetGLContextInfoKHR +#define clGetGLContextInfoKHR clGetGLContextInfoKHR_pfn +#undef clGetGLObjectInfo +#define clGetGLObjectInfo clGetGLObjectInfo_pfn +#undef clGetGLTextureInfo +#define clGetGLTextureInfo clGetGLTextureInfo_pfn + +#ifdef cl_khr_gl_sharing + +// generated by parser_cl.py +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLBuffer)(cl_context, cl_mem_flags, cl_GLuint, int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLRenderbuffer)(cl_context, cl_mem_flags, cl_GLuint, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture2D)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*); +extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture3D)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueAcquireGLObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReleaseGLObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_uint, const cl_event*, cl_event*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLContextInfoKHR)(const cl_context_properties*, cl_gl_context_info, size_t, void*, size_t*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLObjectInfo)(cl_mem, cl_gl_object_type*, cl_GLuint*); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLTextureInfo)(cl_mem, cl_gl_texture_info, size_t, void*, size_t*); + +#endif // cl_khr_gl_sharing diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl_wrappers.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl_wrappers.hpp new file mode 100644 index 00000000..12f342b2 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/autogenerated/opencl_gl_wrappers.hpp @@ -0,0 +1,42 @@ +// +// AUTOGENERATED, DO NOT EDIT +// +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_WRAPPERS_HPP +#error "Invalid usage" +#endif + +#ifdef cl_khr_gl_sharing + +// generated by parser_cl.py +#undef clCreateFromGLBuffer +#define clCreateFromGLBuffer clCreateFromGLBuffer_fn +inline cl_mem clCreateFromGLBuffer(cl_context p0, cl_mem_flags p1, cl_GLuint p2, int* p3) { return clCreateFromGLBuffer_pfn(p0, p1, p2, p3); } +#undef clCreateFromGLRenderbuffer +#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_fn +inline cl_mem clCreateFromGLRenderbuffer(cl_context p0, cl_mem_flags p1, cl_GLuint p2, cl_int* p3) { return clCreateFromGLRenderbuffer_pfn(p0, p1, p2, p3); } +#undef clCreateFromGLTexture +#define clCreateFromGLTexture clCreateFromGLTexture_fn +inline cl_mem clCreateFromGLTexture(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture_pfn(p0, p1, p2, p3, p4, p5); } +#undef clCreateFromGLTexture2D +#define clCreateFromGLTexture2D clCreateFromGLTexture2D_fn +inline cl_mem clCreateFromGLTexture2D(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture2D_pfn(p0, p1, p2, p3, p4, p5); } +#undef clCreateFromGLTexture3D +#define clCreateFromGLTexture3D clCreateFromGLTexture3D_fn +inline cl_mem clCreateFromGLTexture3D(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture3D_pfn(p0, p1, p2, p3, p4, p5); } +#undef clEnqueueAcquireGLObjects +#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_fn +inline cl_int clEnqueueAcquireGLObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueAcquireGLObjects_pfn(p0, p1, p2, p3, p4, p5); } +#undef clEnqueueReleaseGLObjects +#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_fn +inline cl_int clEnqueueReleaseGLObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueReleaseGLObjects_pfn(p0, p1, p2, p3, p4, p5); } +#undef clGetGLContextInfoKHR +#define clGetGLContextInfoKHR clGetGLContextInfoKHR_fn +inline cl_int clGetGLContextInfoKHR(const cl_context_properties* p0, cl_gl_context_info p1, size_t p2, void* p3, size_t* p4) { return clGetGLContextInfoKHR_pfn(p0, p1, p2, p3, p4); } +#undef clGetGLObjectInfo +#define clGetGLObjectInfo clGetGLObjectInfo_fn +inline cl_int clGetGLObjectInfo(cl_mem p0, cl_gl_object_type* p1, cl_GLuint* p2) { return clGetGLObjectInfo_pfn(p0, p1, p2); } +#undef clGetGLTextureInfo +#define clGetGLTextureInfo clGetGLTextureInfo_fn +inline cl_int clGetGLTextureInfo(cl_mem p0, cl_gl_texture_info p1, size_t p2, void* p3, size_t* p4) { return clGetGLTextureInfo_pfn(p0, p1, p2, p3, p4); } + +#endif // cl_khr_gl_sharing diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdblas.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdblas.hpp new file mode 100644 index 00000000..2ad8ac0b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdblas.hpp @@ -0,0 +1,53 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP +#define OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP + +#ifdef HAVE_CLAMDBLAS + +#include "opencl_core.hpp" + +#include "autogenerated/opencl_clamdblas.hpp" + +#endif // HAVE_CLAMDBLAS + +#endif // OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdfft.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdfft.hpp new file mode 100644 index 00000000..a328f722 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_clamdfft.hpp @@ -0,0 +1,53 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP +#define OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP + +#ifdef HAVE_CLAMDFFT + +#include "opencl_core.hpp" + +#include "autogenerated/opencl_clamdfft.hpp" + +#endif // HAVE_CLAMDFFT + +#endif // OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core.hpp new file mode 100644 index 00000000..0404b317 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core.hpp @@ -0,0 +1,84 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP + +#ifdef HAVE_OPENCL + +#ifndef CL_RUNTIME_EXPORT +#if (defined(BUILD_SHARED_LIBS) || defined(OPENCV_CORE_SHARED)) && (defined _WIN32 || defined WINCE) && \ + !(defined(__OPENCV_BUILD) && defined(OPENCV_MODULE_IS_PART_OF_WORLD)) +#define CL_RUNTIME_EXPORT __declspec(dllimport) +#else +#define CL_RUNTIME_EXPORT +#endif +#endif + +#ifdef HAVE_OPENCL_SVM +#define clSVMAlloc clSVMAlloc_ +#define clSVMFree clSVMFree_ +#define clSetKernelArgSVMPointer clSetKernelArgSVMPointer_ +#define clSetKernelExecInfo clSetKernelExecInfo_ +#define clEnqueueSVMFree clEnqueueSVMFree_ +#define clEnqueueSVMMemcpy clEnqueueSVMMemcpy_ +#define clEnqueueSVMMemFill clEnqueueSVMMemFill_ +#define clEnqueueSVMMap clEnqueueSVMMap_ +#define clEnqueueSVMUnmap clEnqueueSVMUnmap_ +#endif + +#include "autogenerated/opencl_core.hpp" + +#ifndef CL_DEVICE_DOUBLE_FP_CONFIG +#define CL_DEVICE_DOUBLE_FP_CONFIG 0x1032 +#endif + +#ifndef CL_DEVICE_HALF_FP_CONFIG +#define CL_DEVICE_HALF_FP_CONFIG 0x1033 +#endif + +#ifndef CL_VERSION_1_2 +#define CV_REQUIRE_OPENCL_1_2_ERROR CV_Error(cv::Error::OpenCLApiCallError, "OpenCV compiled without OpenCL v1.2 support, so we can't use functionality from OpenCL v1.2") +#endif + +#endif // HAVE_OPENCL + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core_wrappers.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core_wrappers.hpp new file mode 100644 index 00000000..38fcae99 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_core_wrappers.hpp @@ -0,0 +1,47 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_WRAPPERS_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_WRAPPERS_HPP + +#include "autogenerated/opencl_core_wrappers.hpp" + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_WRAPPERS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl.hpp new file mode 100644 index 00000000..659c7d80 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl.hpp @@ -0,0 +1,53 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_HPP + +#if defined HAVE_OPENCL && defined HAVE_OPENGL + +#include "opencl_core.hpp" + +#include "autogenerated/opencl_gl.hpp" + +#endif // defined HAVE_OPENCL && defined HAVE_OPENGL + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl_wrappers.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl_wrappers.hpp new file mode 100644 index 00000000..9700004c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_gl_wrappers.hpp @@ -0,0 +1,47 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_WRAPPERS_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_WRAPPERS_HPP + +#include "autogenerated/opencl_gl_wrappers.hpp" + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_WRAPPERS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_20.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_20.hpp new file mode 100644 index 00000000..9636b19b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_20.hpp @@ -0,0 +1,48 @@ +/* See LICENSE file in the root OpenCV directory */ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_2_0_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_2_0_HPP + +#if defined(HAVE_OPENCL_SVM) +#include "opencl_core.hpp" + +#include "opencl_svm_definitions.hpp" + +#undef clSVMAlloc +#define clSVMAlloc clSVMAlloc_pfn +#undef clSVMFree +#define clSVMFree clSVMFree_pfn +#undef clSetKernelArgSVMPointer +#define clSetKernelArgSVMPointer clSetKernelArgSVMPointer_pfn +#undef clSetKernelExecInfo +//#define clSetKernelExecInfo clSetKernelExecInfo_pfn +#undef clEnqueueSVMFree +//#define clEnqueueSVMFree clEnqueueSVMFree_pfn +#undef clEnqueueSVMMemcpy +#define clEnqueueSVMMemcpy clEnqueueSVMMemcpy_pfn +#undef clEnqueueSVMMemFill +#define clEnqueueSVMMemFill clEnqueueSVMMemFill_pfn +#undef clEnqueueSVMMap +#define clEnqueueSVMMap clEnqueueSVMMap_pfn +#undef clEnqueueSVMUnmap +#define clEnqueueSVMUnmap clEnqueueSVMUnmap_pfn + +extern CL_RUNTIME_EXPORT void* (CL_API_CALL *clSVMAlloc)(cl_context context, cl_svm_mem_flags flags, size_t size, unsigned int alignment); +extern CL_RUNTIME_EXPORT void (CL_API_CALL *clSVMFree)(cl_context context, void* svm_pointer); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clSetKernelArgSVMPointer)(cl_kernel kernel, cl_uint arg_index, const void* arg_value); +//extern CL_RUNTIME_EXPORT void* (CL_API_CALL *clSetKernelExecInfo)(cl_kernel kernel, cl_kernel_exec_info param_name, size_t param_value_size, const void* param_value); +//extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clEnqueueSVMFree)(cl_command_queue command_queue, cl_uint num_svm_pointers, void* svm_pointers[], +// void (CL_CALLBACK *pfn_free_func)(cl_command_queue queue, cl_uint num_svm_pointers, void* svm_pointers[], void* user_data), void* user_data, +// cl_uint num_events_in_wait_list, const cl_event* event_wait_list, cl_event* event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clEnqueueSVMMemcpy)(cl_command_queue command_queue, cl_bool blocking_copy, void* dst_ptr, const void* src_ptr, size_t size, + cl_uint num_events_in_wait_list, const cl_event* event_wait_list, cl_event* event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clEnqueueSVMMemFill)(cl_command_queue command_queue, void* svm_ptr, const void* pattern, size_t pattern_size, size_t size, + cl_uint num_events_in_wait_list, const cl_event* event_wait_list, cl_event* event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clEnqueueSVMMap)(cl_command_queue command_queue, cl_bool blocking_map, cl_map_flags map_flags, void* svm_ptr, size_t size, + cl_uint num_events_in_wait_list, const cl_event* event_wait_list, cl_event* event); +extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL *clEnqueueSVMUnmap)(cl_command_queue command_queue, void* svm_ptr, + cl_uint num_events_in_wait_list, const cl_event* event_wait_list, cl_event* event); + +#endif // HAVE_OPENCL_SVM + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_2_0_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_definitions.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_definitions.hpp new file mode 100644 index 00000000..97c927b4 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_definitions.hpp @@ -0,0 +1,42 @@ +/* See LICENSE file in the root OpenCV directory */ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_DEFINITIONS_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_DEFINITIONS_HPP + +#if defined(HAVE_OPENCL_SVM) +#if defined(CL_VERSION_2_0) + +// OpenCL 2.0 contains SVM definitions + +#else + +typedef cl_bitfield cl_device_svm_capabilities; +typedef cl_bitfield cl_svm_mem_flags; +typedef cl_uint cl_kernel_exec_info; + +// +// TODO Add real values after OpenCL 2.0 release +// + +#ifndef CL_DEVICE_SVM_CAPABILITIES +#define CL_DEVICE_SVM_CAPABILITIES 0x1053 + +#define CL_DEVICE_SVM_COARSE_GRAIN_BUFFER (1 << 0) +#define CL_DEVICE_SVM_FINE_GRAIN_BUFFER (1 << 1) +#define CL_DEVICE_SVM_FINE_GRAIN_SYSTEM (1 << 2) +#define CL_DEVICE_SVM_ATOMICS (1 << 3) +#endif + +#ifndef CL_MEM_SVM_FINE_GRAIN_BUFFER +#define CL_MEM_SVM_FINE_GRAIN_BUFFER (1 << 10) +#endif + +#ifndef CL_MEM_SVM_ATOMICS +#define CL_MEM_SVM_ATOMICS (1 << 11) +#endif + + +#endif // CL_VERSION_2_0 +#endif // HAVE_OPENCL_SVM + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_DEFINITIONS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_hsa_extension.hpp b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_hsa_extension.hpp new file mode 100644 index 00000000..497bc3de --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opencl/runtime/opencl_svm_hsa_extension.hpp @@ -0,0 +1,166 @@ +/* See LICENSE file in the root OpenCV directory */ + +#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_HSA_EXTENSION_HPP +#define OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_HSA_EXTENSION_HPP + +#if defined(HAVE_OPENCL_SVM) +#include "opencl_core.hpp" + +#ifndef CL_DEVICE_SVM_CAPABILITIES_AMD +// +// Part of the file is an extract from the cl_ext.h file from AMD APP SDK package. +// Below is the original copyright. +// +/******************************************************************************* + * Copyright (c) 2008-2013 The Khronos Group Inc. + * + * Permission is hereby granted, free of charge, to any person obtaining a + * copy of this software and/or associated documentation files (the + * "Materials"), to deal in the Materials without restriction, including + * without limitation the rights to use, copy, modify, merge, publish, + * distribute, sublicense, and/or sell copies of the Materials, and to + * permit persons to whom the Materials are furnished to do so, subject to + * the following conditions: + * + * The above copyright notice and this permission notice shall be included + * in all copies or substantial portions of the Materials. + * + * THE MATERIALS ARE PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, + * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * MATERIALS OR THE USE OR OTHER DEALINGS IN THE MATERIALS. + ******************************************************************************/ + +/******************************************* + * Shared Virtual Memory (SVM) extension + *******************************************/ +typedef cl_bitfield cl_device_svm_capabilities_amd; +typedef cl_bitfield cl_svm_mem_flags_amd; +typedef cl_uint cl_kernel_exec_info_amd; + +/* cl_device_info */ +#define CL_DEVICE_SVM_CAPABILITIES_AMD 0x1053 +#define CL_DEVICE_PREFERRED_PLATFORM_ATOMIC_ALIGNMENT_AMD 0x1054 + +/* cl_device_svm_capabilities_amd */ +#define CL_DEVICE_SVM_COARSE_GRAIN_BUFFER_AMD (1 << 0) +#define CL_DEVICE_SVM_FINE_GRAIN_BUFFER_AMD (1 << 1) +#define CL_DEVICE_SVM_FINE_GRAIN_SYSTEM_AMD (1 << 2) +#define CL_DEVICE_SVM_ATOMICS_AMD (1 << 3) + +/* cl_svm_mem_flags_amd */ +#define CL_MEM_SVM_FINE_GRAIN_BUFFER_AMD (1 << 10) +#define CL_MEM_SVM_ATOMICS_AMD (1 << 11) + +/* cl_mem_info */ +#define CL_MEM_USES_SVM_POINTER_AMD 0x1109 + +/* cl_kernel_exec_info_amd */ +#define CL_KERNEL_EXEC_INFO_SVM_PTRS_AMD 0x11B6 +#define CL_KERNEL_EXEC_INFO_SVM_FINE_GRAIN_SYSTEM_AMD 0x11B7 + +/* cl_command_type */ +#define CL_COMMAND_SVM_FREE_AMD 0x1209 +#define CL_COMMAND_SVM_MEMCPY_AMD 0x120A +#define CL_COMMAND_SVM_MEMFILL_AMD 0x120B +#define CL_COMMAND_SVM_MAP_AMD 0x120C +#define CL_COMMAND_SVM_UNMAP_AMD 0x120D + +typedef CL_API_ENTRY void* +(CL_API_CALL * clSVMAllocAMD_fn)( + cl_context /* context */, + cl_svm_mem_flags_amd /* flags */, + size_t /* size */, + unsigned int /* alignment */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY void +(CL_API_CALL * clSVMFreeAMD_fn)( + cl_context /* context */, + void* /* svm_pointer */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clEnqueueSVMFreeAMD_fn)( + cl_command_queue /* command_queue */, + cl_uint /* num_svm_pointers */, + void** /* svm_pointers */, + void (CL_CALLBACK *)( /*pfn_free_func*/ + cl_command_queue /* queue */, + cl_uint /* num_svm_pointers */, + void** /* svm_pointers */, + void* /* user_data */), + void* /* user_data */, + cl_uint /* num_events_in_wait_list */, + const cl_event* /* event_wait_list */, + cl_event* /* event */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clEnqueueSVMMemcpyAMD_fn)( + cl_command_queue /* command_queue */, + cl_bool /* blocking_copy */, + void* /* dst_ptr */, + const void* /* src_ptr */, + size_t /* size */, + cl_uint /* num_events_in_wait_list */, + const cl_event* /* event_wait_list */, + cl_event* /* event */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clEnqueueSVMMemFillAMD_fn)( + cl_command_queue /* command_queue */, + void* /* svm_ptr */, + const void* /* pattern */, + size_t /* pattern_size */, + size_t /* size */, + cl_uint /* num_events_in_wait_list */, + const cl_event* /* event_wait_list */, + cl_event* /* event */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clEnqueueSVMMapAMD_fn)( + cl_command_queue /* command_queue */, + cl_bool /* blocking_map */, + cl_map_flags /* map_flags */, + void* /* svm_ptr */, + size_t /* size */, + cl_uint /* num_events_in_wait_list */, + const cl_event* /* event_wait_list */, + cl_event* /* event */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clEnqueueSVMUnmapAMD_fn)( + cl_command_queue /* command_queue */, + void* /* svm_ptr */, + cl_uint /* num_events_in_wait_list */, + const cl_event* /* event_wait_list */, + cl_event* /* event */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clSetKernelArgSVMPointerAMD_fn)( + cl_kernel /* kernel */, + cl_uint /* arg_index */, + const void * /* arg_value */ +) CL_EXT_SUFFIX__VERSION_1_2; + +typedef CL_API_ENTRY cl_int +(CL_API_CALL * clSetKernelExecInfoAMD_fn)( + cl_kernel /* kernel */, + cl_kernel_exec_info_amd /* param_name */, + size_t /* param_value_size */, + const void * /* param_value */ +) CL_EXT_SUFFIX__VERSION_1_2; + +#endif + +#endif // HAVE_OPENCL_SVM + +#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_SVM_HSA_EXTENSION_HPP diff --git a/3rdparty/opencv/include/opencv2/core/opengl.hpp b/3rdparty/opencv/include/opencv2/core/opengl.hpp new file mode 100644 index 00000000..a6288beb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/opengl.hpp @@ -0,0 +1,725 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OPENGL_HPP +#define OPENCV_CORE_OPENGL_HPP + +#ifndef __cplusplus +# error opengl.hpp header must be compiled as C++ +#endif + +#include "opencv2/core.hpp" +#include "ocl.hpp" + +namespace cv { namespace ogl { + +/** @addtogroup core_opengl +This section describes OpenGL interoperability. + +To enable OpenGL support, configure OpenCV using CMake with WITH_OPENGL=ON . Currently OpenGL is +supported only with WIN32, GTK and Qt backends on Windows and Linux (MacOS and Android are not +supported). For GTK backend gtkglext-1.0 library is required. + +To use OpenGL functionality you should first create OpenGL context (window or frame buffer). You can +do this with namedWindow function or with other OpenGL toolkit (GLUT, for example). +*/ +//! @{ + +/////////////////// OpenGL Objects /////////////////// + +/** @brief Smart pointer for OpenGL buffer object with reference counting. + +Buffer Objects are OpenGL objects that store an array of unformatted memory allocated by the OpenGL +context. These can be used to store vertex data, pixel data retrieved from images or the +framebuffer, and a variety of other things. + +ogl::Buffer has interface similar with Mat interface and represents 2D array memory. + +ogl::Buffer supports memory transfers between host and device and also can be mapped to CUDA memory. + */ +class CV_EXPORTS Buffer +{ +public: + /** @brief The target defines how you intend to use the buffer object. + */ + enum Target + { + ARRAY_BUFFER = 0x8892, //!< The buffer will be used as a source for vertex data + ELEMENT_ARRAY_BUFFER = 0x8893, //!< The buffer will be used for indices (in glDrawElements, for example) + PIXEL_PACK_BUFFER = 0x88EB, //!< The buffer will be used for reading from OpenGL textures + PIXEL_UNPACK_BUFFER = 0x88EC //!< The buffer will be used for writing to OpenGL textures + }; + + enum Access + { + READ_ONLY = 0x88B8, + WRITE_ONLY = 0x88B9, + READ_WRITE = 0x88BA + }; + + /** @brief The constructors. + + Creates empty ogl::Buffer object, creates ogl::Buffer object from existed buffer ( abufId + parameter), allocates memory for ogl::Buffer object or copies from host/device memory. + */ + Buffer(); + + /** @overload + @param arows Number of rows in a 2D array. + @param acols Number of columns in a 2D array. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param abufId Buffer object name. + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Buffer(int arows, int acols, int atype, unsigned int abufId, bool autoRelease = false); + + /** @overload + @param asize 2D array size. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param abufId Buffer object name. + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Buffer(Size asize, int atype, unsigned int abufId, bool autoRelease = false); + + /** @overload + @param arows Number of rows in a 2D array. + @param acols Number of columns in a 2D array. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Buffer(int arows, int acols, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @overload + @param asize 2D array size. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Buffer(Size asize, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @overload + @param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or std::vector ). + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + explicit Buffer(InputArray arr, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @brief Allocates memory for ogl::Buffer object. + + @param arows Number of rows in a 2D array. + @param acols Number of columns in a 2D array. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void create(int arows, int acols, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @overload + @param asize 2D array size. + @param atype Array type ( CV_8UC1, ..., CV_64FC4 ). See Mat for details. + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void create(Size asize, int atype, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @brief Decrements the reference counter and destroys the buffer object if needed. + + The function will call setAutoRelease(true) . + */ + void release(); + + /** @brief Sets auto release mode. + + The lifetime of the OpenGL object is tied to the lifetime of the context. If OpenGL context was + bound to a window it could be released at any time (user can close a window). If object's destructor + is called after destruction of the context it will cause an error. Thus ogl::Buffer doesn't destroy + OpenGL object in destructor by default (all OpenGL resources will be released with OpenGL context). + This function can force ogl::Buffer destructor to destroy OpenGL object. + @param flag Auto release mode (if true, release will be called in object's destructor). + */ + void setAutoRelease(bool flag); + + /** @brief Copies from host/device memory to OpenGL buffer. + @param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or std::vector ). + @param target Buffer usage. See cv::ogl::Buffer::Target . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void copyFrom(InputArray arr, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @overload */ + void copyFrom(InputArray arr, cuda::Stream& stream, Target target = ARRAY_BUFFER, bool autoRelease = false); + + /** @brief Copies from OpenGL buffer to host/device memory or another OpenGL buffer object. + + @param arr Destination array (host or device memory, can be Mat , cuda::GpuMat , std::vector or + ogl::Buffer ). + */ + void copyTo(OutputArray arr) const; + + /** @overload */ + void copyTo(OutputArray arr, cuda::Stream& stream) const; + + /** @brief Creates a full copy of the buffer object and the underlying data. + + @param target Buffer usage for destination buffer. + @param autoRelease Auto release mode for destination buffer. + */ + Buffer clone(Target target = ARRAY_BUFFER, bool autoRelease = false) const; + + /** @brief Binds OpenGL buffer to the specified buffer binding point. + + @param target Binding point. See cv::ogl::Buffer::Target . + */ + void bind(Target target) const; + + /** @brief Unbind any buffers from the specified binding point. + + @param target Binding point. See cv::ogl::Buffer::Target . + */ + static void unbind(Target target); + + /** @brief Maps OpenGL buffer to host memory. + + mapHost maps to the client's address space the entire data store of the buffer object. The data can + then be directly read and/or written relative to the returned pointer, depending on the specified + access policy. + + A mapped data store must be unmapped with ogl::Buffer::unmapHost before its buffer object is used. + + This operation can lead to memory transfers between host and device. + + Only one buffer object can be mapped at a time. + @param access Access policy, indicating whether it will be possible to read from, write to, or both + read from and write to the buffer object's mapped data store. The symbolic constant must be + ogl::Buffer::READ_ONLY , ogl::Buffer::WRITE_ONLY or ogl::Buffer::READ_WRITE . + */ + Mat mapHost(Access access); + + /** @brief Unmaps OpenGL buffer. + */ + void unmapHost(); + + //! map to device memory (blocking) + cuda::GpuMat mapDevice(); + void unmapDevice(); + + /** @brief Maps OpenGL buffer to CUDA device memory. + + This operation doesn't copy data. Several buffer objects can be mapped to CUDA memory at a time. + + A mapped data store must be unmapped with ogl::Buffer::unmapDevice before its buffer object is used. + */ + cuda::GpuMat mapDevice(cuda::Stream& stream); + + /** @brief Unmaps OpenGL buffer. + */ + void unmapDevice(cuda::Stream& stream); + + int rows() const; + int cols() const; + Size size() const; + bool empty() const; + + int type() const; + int depth() const; + int channels() const; + int elemSize() const; + int elemSize1() const; + + //! get OpenGL opject id + unsigned int bufId() const; + + class Impl; + +private: + Ptr impl_; + int rows_; + int cols_; + int type_; +}; + +/** @brief Smart pointer for OpenGL 2D texture memory with reference counting. + */ +class CV_EXPORTS Texture2D +{ +public: + /** @brief An Image Format describes the way that the images in Textures store their data. + */ + enum Format + { + NONE = 0, + DEPTH_COMPONENT = 0x1902, //!< Depth + RGB = 0x1907, //!< Red, Green, Blue + RGBA = 0x1908 //!< Red, Green, Blue, Alpha + }; + + /** @brief The constructors. + + Creates empty ogl::Texture2D object, allocates memory for ogl::Texture2D object or copies from + host/device memory. + */ + Texture2D(); + + /** @overload */ + Texture2D(int arows, int acols, Format aformat, unsigned int atexId, bool autoRelease = false); + + /** @overload */ + Texture2D(Size asize, Format aformat, unsigned int atexId, bool autoRelease = false); + + /** @overload + @param arows Number of rows. + @param acols Number of columns. + @param aformat Image format. See cv::ogl::Texture2D::Format . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Texture2D(int arows, int acols, Format aformat, bool autoRelease = false); + + /** @overload + @param asize 2D array size. + @param aformat Image format. See cv::ogl::Texture2D::Format . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + Texture2D(Size asize, Format aformat, bool autoRelease = false); + + /** @overload + @param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or ogl::Buffer ). + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + explicit Texture2D(InputArray arr, bool autoRelease = false); + + /** @brief Allocates memory for ogl::Texture2D object. + + @param arows Number of rows. + @param acols Number of columns. + @param aformat Image format. See cv::ogl::Texture2D::Format . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void create(int arows, int acols, Format aformat, bool autoRelease = false); + /** @overload + @param asize 2D array size. + @param aformat Image format. See cv::ogl::Texture2D::Format . + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void create(Size asize, Format aformat, bool autoRelease = false); + + /** @brief Decrements the reference counter and destroys the texture object if needed. + + The function will call setAutoRelease(true) . + */ + void release(); + + /** @brief Sets auto release mode. + + @param flag Auto release mode (if true, release will be called in object's destructor). + + The lifetime of the OpenGL object is tied to the lifetime of the context. If OpenGL context was + bound to a window it could be released at any time (user can close a window). If object's destructor + is called after destruction of the context it will cause an error. Thus ogl::Texture2D doesn't + destroy OpenGL object in destructor by default (all OpenGL resources will be released with OpenGL + context). This function can force ogl::Texture2D destructor to destroy OpenGL object. + */ + void setAutoRelease(bool flag); + + /** @brief Copies from host/device memory to OpenGL texture. + + @param arr Input array (host or device memory, it can be Mat , cuda::GpuMat or ogl::Buffer ). + @param autoRelease Auto release mode (if true, release will be called in object's destructor). + */ + void copyFrom(InputArray arr, bool autoRelease = false); + + /** @brief Copies from OpenGL texture to host/device memory or another OpenGL texture object. + + @param arr Destination array (host or device memory, can be Mat , cuda::GpuMat , ogl::Buffer or + ogl::Texture2D ). + @param ddepth Destination depth. + @param autoRelease Auto release mode for destination buffer (if arr is OpenGL buffer or texture). + */ + void copyTo(OutputArray arr, int ddepth = CV_32F, bool autoRelease = false) const; + + /** @brief Binds texture to current active texture unit for GL_TEXTURE_2D target. + */ + void bind() const; + + int rows() const; + int cols() const; + Size size() const; + bool empty() const; + + Format format() const; + + //! get OpenGL opject id + unsigned int texId() const; + + class Impl; + +private: + Ptr impl_; + int rows_; + int cols_; + Format format_; +}; + +/** @brief Wrapper for OpenGL Client-Side Vertex arrays. + +ogl::Arrays stores vertex data in ogl::Buffer objects. + */ +class CV_EXPORTS Arrays +{ +public: + /** @brief Default constructor + */ + Arrays(); + + /** @brief Sets an array of vertex coordinates. + @param vertex array with vertex coordinates, can be both host and device memory. + */ + void setVertexArray(InputArray vertex); + + /** @brief Resets vertex coordinates. + */ + void resetVertexArray(); + + /** @brief Sets an array of vertex colors. + @param color array with vertex colors, can be both host and device memory. + */ + void setColorArray(InputArray color); + + /** @brief Resets vertex colors. + */ + void resetColorArray(); + + /** @brief Sets an array of vertex normals. + @param normal array with vertex normals, can be both host and device memory. + */ + void setNormalArray(InputArray normal); + + /** @brief Resets vertex normals. + */ + void resetNormalArray(); + + /** @brief Sets an array of vertex texture coordinates. + @param texCoord array with vertex texture coordinates, can be both host and device memory. + */ + void setTexCoordArray(InputArray texCoord); + + /** @brief Resets vertex texture coordinates. + */ + void resetTexCoordArray(); + + /** @brief Releases all inner buffers. + */ + void release(); + + /** @brief Sets auto release mode all inner buffers. + @param flag Auto release mode. + */ + void setAutoRelease(bool flag); + + /** @brief Binds all vertex arrays. + */ + void bind() const; + + /** @brief Returns the vertex count. + */ + int size() const; + bool empty() const; + +private: + int size_; + Buffer vertex_; + Buffer color_; + Buffer normal_; + Buffer texCoord_; +}; + +/////////////////// Render Functions /////////////////// + +//! render mode +enum RenderModes { + POINTS = 0x0000, + LINES = 0x0001, + LINE_LOOP = 0x0002, + LINE_STRIP = 0x0003, + TRIANGLES = 0x0004, + TRIANGLE_STRIP = 0x0005, + TRIANGLE_FAN = 0x0006, + QUADS = 0x0007, + QUAD_STRIP = 0x0008, + POLYGON = 0x0009 +}; + +/** @brief Render OpenGL texture or primitives. +@param tex Texture to draw. +@param wndRect Region of window, where to draw a texture (normalized coordinates). +@param texRect Region of texture to draw (normalized coordinates). + */ +CV_EXPORTS void render(const Texture2D& tex, + Rect_ wndRect = Rect_(0.0, 0.0, 1.0, 1.0), + Rect_ texRect = Rect_(0.0, 0.0, 1.0, 1.0)); + +/** @overload +@param arr Array of privitives vertices. +@param mode Render mode. One of cv::ogl::RenderModes +@param color Color for all vertices. Will be used if arr doesn't contain color array. +*/ +CV_EXPORTS void render(const Arrays& arr, int mode = POINTS, Scalar color = Scalar::all(255)); + +/** @overload +@param arr Array of privitives vertices. +@param indices Array of vertices indices (host or device memory). +@param mode Render mode. One of cv::ogl::RenderModes +@param color Color for all vertices. Will be used if arr doesn't contain color array. +*/ +CV_EXPORTS void render(const Arrays& arr, InputArray indices, int mode = POINTS, Scalar color = Scalar::all(255)); + +/////////////////// CL-GL Interoperability Functions /////////////////// + +namespace ocl { +using namespace cv::ocl; + +// TODO static functions in the Context class +/** @brief Creates OpenCL context from GL. +@return Returns reference to OpenCL Context + */ +CV_EXPORTS Context& initializeContextFromGL(); + +} // namespace cv::ogl::ocl + +/** @brief Converts InputArray to Texture2D object. +@param src - source InputArray. +@param texture - destination Texture2D object. + */ +CV_EXPORTS void convertToGLTexture2D(InputArray src, Texture2D& texture); + +/** @brief Converts Texture2D object to OutputArray. +@param texture - source Texture2D object. +@param dst - destination OutputArray. + */ +CV_EXPORTS void convertFromGLTexture2D(const Texture2D& texture, OutputArray dst); + +/** @brief Maps Buffer object to process on CL side (convert to UMat). + +Function creates CL buffer from GL one, and then constructs UMat that can be used +to process buffer data with OpenCV functions. Note that in current implementation +UMat constructed this way doesn't own corresponding GL buffer object, so it is +the user responsibility to close down CL/GL buffers relationships by explicitly +calling unmapGLBuffer() function. +@param buffer - source Buffer object. +@param accessFlags - data access flags (ACCESS_READ|ACCESS_WRITE). +@return Returns UMat object + */ +CV_EXPORTS UMat mapGLBuffer(const Buffer& buffer, int accessFlags = ACCESS_READ|ACCESS_WRITE); + +/** @brief Unmaps Buffer object (releases UMat, previously mapped from Buffer). + +Function must be called explicitly by the user for each UMat previously constructed +by the call to mapGLBuffer() function. +@param u - source UMat, created by mapGLBuffer(). + */ +CV_EXPORTS void unmapGLBuffer(UMat& u); + +//! @} +}} // namespace cv::ogl + +namespace cv { namespace cuda { + +/** @brief Sets a CUDA device and initializes it for the current thread with OpenGL interoperability. + +This function should be explicitly called after OpenGL context creation and before any CUDA calls. +@param device System index of a CUDA device starting with 0. +@ingroup core_opengl + */ +CV_EXPORTS void setGlDevice(int device = 0); + +}} + +//! @cond IGNORED + +//////////////////////////////////////////////////////////////////////// +//////////////////////////////////////////////////////////////////////// +//////////////////////////////////////////////////////////////////////// + +inline +cv::ogl::Buffer::Buffer(int arows, int acols, int atype, Target target, bool autoRelease) : rows_(0), cols_(0), type_(0) +{ + create(arows, acols, atype, target, autoRelease); +} + +inline +cv::ogl::Buffer::Buffer(Size asize, int atype, Target target, bool autoRelease) : rows_(0), cols_(0), type_(0) +{ + create(asize, atype, target, autoRelease); +} + +inline +void cv::ogl::Buffer::create(Size asize, int atype, Target target, bool autoRelease) +{ + create(asize.height, asize.width, atype, target, autoRelease); +} + +inline +int cv::ogl::Buffer::rows() const +{ + return rows_; +} + +inline +int cv::ogl::Buffer::cols() const +{ + return cols_; +} + +inline +cv::Size cv::ogl::Buffer::size() const +{ + return Size(cols_, rows_); +} + +inline +bool cv::ogl::Buffer::empty() const +{ + return rows_ == 0 || cols_ == 0; +} + +inline +int cv::ogl::Buffer::type() const +{ + return type_; +} + +inline +int cv::ogl::Buffer::depth() const +{ + return CV_MAT_DEPTH(type_); +} + +inline +int cv::ogl::Buffer::channels() const +{ + return CV_MAT_CN(type_); +} + +inline +int cv::ogl::Buffer::elemSize() const +{ + return CV_ELEM_SIZE(type_); +} + +inline +int cv::ogl::Buffer::elemSize1() const +{ + return CV_ELEM_SIZE1(type_); +} + +/////// + +inline +cv::ogl::Texture2D::Texture2D(int arows, int acols, Format aformat, bool autoRelease) : rows_(0), cols_(0), format_(NONE) +{ + create(arows, acols, aformat, autoRelease); +} + +inline +cv::ogl::Texture2D::Texture2D(Size asize, Format aformat, bool autoRelease) : rows_(0), cols_(0), format_(NONE) +{ + create(asize, aformat, autoRelease); +} + +inline +void cv::ogl::Texture2D::create(Size asize, Format aformat, bool autoRelease) +{ + create(asize.height, asize.width, aformat, autoRelease); +} + +inline +int cv::ogl::Texture2D::rows() const +{ + return rows_; +} + +inline +int cv::ogl::Texture2D::cols() const +{ + return cols_; +} + +inline +cv::Size cv::ogl::Texture2D::size() const +{ + return Size(cols_, rows_); +} + +inline +bool cv::ogl::Texture2D::empty() const +{ + return rows_ == 0 || cols_ == 0; +} + +inline +cv::ogl::Texture2D::Format cv::ogl::Texture2D::format() const +{ + return format_; +} + +/////// + +inline +cv::ogl::Arrays::Arrays() : size_(0) +{ +} + +inline +int cv::ogl::Arrays::size() const +{ + return size_; +} + +inline +bool cv::ogl::Arrays::empty() const +{ + return size_ == 0; +} + +//! @endcond + +#endif /* OPENCV_CORE_OPENGL_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/operations.hpp b/3rdparty/opencv/include/opencv2/core/operations.hpp new file mode 100644 index 00000000..082fef44 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/operations.hpp @@ -0,0 +1,573 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_OPERATIONS_HPP +#define OPENCV_CORE_OPERATIONS_HPP + +#ifndef __cplusplus +# error operations.hpp header must be compiled as C++ +#endif + +#include + +//! @cond IGNORED + +namespace cv +{ + +////////////////////////////// Matx methods depending on core API ///////////////////////////// + +namespace internal +{ + +template struct Matx_FastInvOp +{ + bool operator()(const Matx<_Tp, m, n>& a, Matx<_Tp, n, m>& b, int method) const + { + return invert(a, b, method) != 0; + } +}; + +template struct Matx_FastInvOp<_Tp, m, m> +{ + bool operator()(const Matx<_Tp, m, m>& a, Matx<_Tp, m, m>& b, int method) const + { + if (method == DECOMP_LU || method == DECOMP_CHOLESKY) + { + Matx<_Tp, m, m> temp = a; + + // assume that b is all 0's on input => make it a unity matrix + for (int i = 0; i < m; i++) + b(i, i) = (_Tp)1; + + if (method == DECOMP_CHOLESKY) + return Cholesky(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m); + + return LU(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m) != 0; + } + else + { + return invert(a, b, method) != 0; + } + } +}; + +template struct Matx_FastInvOp<_Tp, 2, 2> +{ + bool operator()(const Matx<_Tp, 2, 2>& a, Matx<_Tp, 2, 2>& b, int /*method*/) const + { + _Tp d = (_Tp)determinant(a); + if (d == 0) + return false; + d = 1/d; + b(1,1) = a(0,0)*d; + b(0,0) = a(1,1)*d; + b(0,1) = -a(0,1)*d; + b(1,0) = -a(1,0)*d; + return true; + } +}; + +template struct Matx_FastInvOp<_Tp, 3, 3> +{ + bool operator()(const Matx<_Tp, 3, 3>& a, Matx<_Tp, 3, 3>& b, int /*method*/) const + { + _Tp d = (_Tp)determinant(a); + if (d == 0) + return false; + d = 1/d; + b(0,0) = (a(1,1) * a(2,2) - a(1,2) * a(2,1)) * d; + b(0,1) = (a(0,2) * a(2,1) - a(0,1) * a(2,2)) * d; + b(0,2) = (a(0,1) * a(1,2) - a(0,2) * a(1,1)) * d; + + b(1,0) = (a(1,2) * a(2,0) - a(1,0) * a(2,2)) * d; + b(1,1) = (a(0,0) * a(2,2) - a(0,2) * a(2,0)) * d; + b(1,2) = (a(0,2) * a(1,0) - a(0,0) * a(1,2)) * d; + + b(2,0) = (a(1,0) * a(2,1) - a(1,1) * a(2,0)) * d; + b(2,1) = (a(0,1) * a(2,0) - a(0,0) * a(2,1)) * d; + b(2,2) = (a(0,0) * a(1,1) - a(0,1) * a(1,0)) * d; + return true; + } +}; + + +template struct Matx_FastSolveOp +{ + bool operator()(const Matx<_Tp, m, l>& a, const Matx<_Tp, m, n>& b, + Matx<_Tp, l, n>& x, int method) const + { + return cv::solve(a, b, x, method); + } +}; + +template struct Matx_FastSolveOp<_Tp, m, m, n> +{ + bool operator()(const Matx<_Tp, m, m>& a, const Matx<_Tp, m, n>& b, + Matx<_Tp, m, n>& x, int method) const + { + if (method == DECOMP_LU || method == DECOMP_CHOLESKY) + { + Matx<_Tp, m, m> temp = a; + x = b; + if( method == DECOMP_CHOLESKY ) + return Cholesky(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n); + + return LU(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n) != 0; + } + else + { + return cv::solve(a, b, x, method); + } + } +}; + +template struct Matx_FastSolveOp<_Tp, 2, 2, 1> +{ + bool operator()(const Matx<_Tp, 2, 2>& a, const Matx<_Tp, 2, 1>& b, + Matx<_Tp, 2, 1>& x, int) const + { + _Tp d = (_Tp)determinant(a); + if (d == 0) + return false; + d = 1/d; + x(0) = (b(0)*a(1,1) - b(1)*a(0,1))*d; + x(1) = (b(1)*a(0,0) - b(0)*a(1,0))*d; + return true; + } +}; + +template struct Matx_FastSolveOp<_Tp, 3, 3, 1> +{ + bool operator()(const Matx<_Tp, 3, 3>& a, const Matx<_Tp, 3, 1>& b, + Matx<_Tp, 3, 1>& x, int) const + { + _Tp d = (_Tp)determinant(a); + if (d == 0) + return false; + d = 1/d; + x(0) = d*(b(0)*(a(1,1)*a(2,2) - a(1,2)*a(2,1)) - + a(0,1)*(b(1)*a(2,2) - a(1,2)*b(2)) + + a(0,2)*(b(1)*a(2,1) - a(1,1)*b(2))); + + x(1) = d*(a(0,0)*(b(1)*a(2,2) - a(1,2)*b(2)) - + b(0)*(a(1,0)*a(2,2) - a(1,2)*a(2,0)) + + a(0,2)*(a(1,0)*b(2) - b(1)*a(2,0))); + + x(2) = d*(a(0,0)*(a(1,1)*b(2) - b(1)*a(2,1)) - + a(0,1)*(a(1,0)*b(2) - b(1)*a(2,0)) + + b(0)*(a(1,0)*a(2,1) - a(1,1)*a(2,0))); + return true; + } +}; + +} // internal + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::randu(_Tp a, _Tp b) +{ + Matx<_Tp,m,n> M; + cv::randu(M, Scalar(a), Scalar(b)); + return M; +} + +template inline +Matx<_Tp,m,n> Matx<_Tp,m,n>::randn(_Tp a, _Tp b) +{ + Matx<_Tp,m,n> M; + cv::randn(M, Scalar(a), Scalar(b)); + return M; +} + +template inline +Matx<_Tp, n, m> Matx<_Tp, m, n>::inv(int method, bool *p_is_ok /*= NULL*/) const +{ + Matx<_Tp, n, m> b; + bool ok = cv::internal::Matx_FastInvOp<_Tp, m, n>()(*this, b, method); + if (p_is_ok) *p_is_ok = ok; + return ok ? b : Matx<_Tp, n, m>::zeros(); +} + +template template inline +Matx<_Tp, n, l> Matx<_Tp, m, n>::solve(const Matx<_Tp, m, l>& rhs, int method) const +{ + Matx<_Tp, n, l> x; + bool ok = cv::internal::Matx_FastSolveOp<_Tp, m, n, l>()(*this, rhs, x, method); + return ok ? x : Matx<_Tp, n, l>::zeros(); +} + + + +////////////////////////// Augmenting algebraic & logical operations ////////////////////////// + +#define CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \ + static inline A& operator op (A& a, const B& b) { cvop; return a; } + +#define CV_MAT_AUG_OPERATOR(op, cvop, A, B) \ + CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \ + CV_MAT_AUG_OPERATOR1(op, cvop, const A, B) + +#define CV_MAT_AUG_OPERATOR_T(op, cvop, A, B) \ + template CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \ + template CV_MAT_AUG_OPERATOR1(op, cvop, const A, B) + +#define CV_MAT_AUG_OPERATOR_TN(op, cvop, A) \ + template static inline A& operator op (A& a, const Matx<_Tp,m,n>& b) { cvop; return a; } \ + template static inline const A& operator op (const A& a, const Matx<_Tp,m,n>& b) { cvop; return a; } + +CV_MAT_AUG_OPERATOR (+=, cv::add(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR (+=, cv::add(a,b,a), Mat, Scalar) +CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Scalar) +CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR_TN(+=, cv::add(a,Mat(b),a), Mat) +CV_MAT_AUG_OPERATOR_TN(+=, cv::add(a,Mat(b),a), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (-=, cv::subtract(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR (-=, cv::subtract(a,b,a), Mat, Scalar) +CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Scalar) +CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR_TN(-=, cv::subtract(a,Mat(b),a), Mat) +CV_MAT_AUG_OPERATOR_TN(-=, cv::subtract(a,Mat(b),a), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat, Mat) +CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR (*=, a.convertTo(a, -1, b), Mat, double) +CV_MAT_AUG_OPERATOR_T(*=, a.convertTo(a, -1, b), Mat_<_Tp>, double) +CV_MAT_AUG_OPERATOR_TN(*=, cv::gemm(a, Mat(b), 1, Mat(), 0, a, 0), Mat) +CV_MAT_AUG_OPERATOR_TN(*=, cv::gemm(a, Mat(b), 1, Mat(), 0, a, 0), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (/=, cv::divide(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR (/=, a.convertTo((Mat&)a, -1, 1./b), Mat, double) +CV_MAT_AUG_OPERATOR_T(/=, a.convertTo((Mat&)a, -1, 1./b), Mat_<_Tp>, double) +CV_MAT_AUG_OPERATOR_TN(/=, cv::divide(a, Mat(b), a), Mat) +CV_MAT_AUG_OPERATOR_TN(/=, cv::divide(a, Mat(b), a), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (&=, cv::bitwise_and(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR (&=, cv::bitwise_and(a,b,a), Mat, Scalar) +CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Scalar) +CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR_TN(&=, cv::bitwise_and(a, Mat(b), a), Mat) +CV_MAT_AUG_OPERATOR_TN(&=, cv::bitwise_and(a, Mat(b), a), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (|=, cv::bitwise_or(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR (|=, cv::bitwise_or(a,b,a), Mat, Scalar) +CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Scalar) +CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR_TN(|=, cv::bitwise_or(a, Mat(b), a), Mat) +CV_MAT_AUG_OPERATOR_TN(|=, cv::bitwise_or(a, Mat(b), a), Mat_<_Tp>) + +CV_MAT_AUG_OPERATOR (^=, cv::bitwise_xor(a,b,a), Mat, Mat) +CV_MAT_AUG_OPERATOR (^=, cv::bitwise_xor(a,b,a), Mat, Scalar) +CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat) +CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Scalar) +CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat_<_Tp>) +CV_MAT_AUG_OPERATOR_TN(^=, cv::bitwise_xor(a, Mat(b), a), Mat) +CV_MAT_AUG_OPERATOR_TN(^=, cv::bitwise_xor(a, Mat(b), a), Mat_<_Tp>) + +#undef CV_MAT_AUG_OPERATOR_TN +#undef CV_MAT_AUG_OPERATOR_T +#undef CV_MAT_AUG_OPERATOR +#undef CV_MAT_AUG_OPERATOR1 + + + +///////////////////////////////////////////// SVD ///////////////////////////////////////////// + +inline SVD::SVD() {} +inline SVD::SVD( InputArray m, int flags ) { operator ()(m, flags); } +inline void SVD::solveZ( InputArray m, OutputArray _dst ) +{ + Mat mtx = m.getMat(); + SVD svd(mtx, (mtx.rows >= mtx.cols ? 0 : SVD::FULL_UV)); + _dst.create(svd.vt.cols, 1, svd.vt.type()); + Mat dst = _dst.getMat(); + svd.vt.row(svd.vt.rows-1).reshape(1,svd.vt.cols).copyTo(dst); +} + +template inline void + SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt ) +{ + CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector."); + Mat _a(a, false), _u(u, false), _w(w, false), _vt(vt, false); + SVD::compute(_a, _w, _u, _vt); + CV_Assert(_w.data == (uchar*)&w.val[0] && _u.data == (uchar*)&u.val[0] && _vt.data == (uchar*)&vt.val[0]); +} + +template inline void +SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w ) +{ + CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector."); + Mat _a(a, false), _w(w, false); + SVD::compute(_a, _w); + CV_Assert(_w.data == (uchar*)&w.val[0]); +} + +template inline void +SVD::backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u, + const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, + Matx<_Tp, n, nb>& dst ) +{ + CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector."); + Mat _u(u, false), _w(w, false), _vt(vt, false), _rhs(rhs, false), _dst(dst, false); + SVD::backSubst(_w, _u, _vt, _rhs, _dst); + CV_Assert(_dst.data == (uchar*)&dst.val[0]); +} + + + +/////////////////////////////////// Multiply-with-Carry RNG /////////////////////////////////// + +inline RNG::RNG() { state = 0xffffffff; } +inline RNG::RNG(uint64 _state) { state = _state ? _state : 0xffffffff; } + +inline RNG::operator uchar() { return (uchar)next(); } +inline RNG::operator schar() { return (schar)next(); } +inline RNG::operator ushort() { return (ushort)next(); } +inline RNG::operator short() { return (short)next(); } +inline RNG::operator int() { return (int)next(); } +inline RNG::operator unsigned() { return next(); } +inline RNG::operator float() { return next()*2.3283064365386962890625e-10f; } +inline RNG::operator double() { unsigned t = next(); return (((uint64)t << 32) | next()) * 5.4210108624275221700372640043497e-20; } + +inline unsigned RNG::operator ()(unsigned N) { return (unsigned)uniform(0,N); } +inline unsigned RNG::operator ()() { return next(); } + +inline int RNG::uniform(int a, int b) { return a == b ? a : (int)(next() % (b - a) + a); } +inline float RNG::uniform(float a, float b) { return ((float)*this)*(b - a) + a; } +inline double RNG::uniform(double a, double b) { return ((double)*this)*(b - a) + a; } + +inline bool RNG::operator ==(const RNG& other) const { return state == other.state; } + +inline unsigned RNG::next() +{ + state = (uint64)(unsigned)state* /*CV_RNG_COEFF*/ 4164903690U + (unsigned)(state >> 32); + return (unsigned)state; +} + +//! returns the next unifomly-distributed random number of the specified type +template static inline _Tp randu() +{ + return (_Tp)theRNG(); +} + +///////////////////////////////// Formatted string generation ///////////////////////////////// + +/** @brief Returns a text string formatted using the printf-like expression. + +The function acts like sprintf but forms and returns an STL string. It can be used to form an error +message in the Exception constructor. +@param fmt printf-compatible formatting specifiers. + */ +CV_EXPORTS String format( const char* fmt, ... ); + +///////////////////////////////// Formatted output of cv::Mat ///////////////////////////////// + +static inline +Ptr format(InputArray mtx, int fmt) +{ + return Formatter::get(fmt)->format(mtx.getMat()); +} + +static inline +int print(Ptr fmtd, FILE* stream = stdout) +{ + int written = 0; + fmtd->reset(); + for(const char* str = fmtd->next(); str; str = fmtd->next()) + written += fputs(str, stream); + + return written; +} + +static inline +int print(const Mat& mtx, FILE* stream = stdout) +{ + return print(Formatter::get()->format(mtx), stream); +} + +static inline +int print(const UMat& mtx, FILE* stream = stdout) +{ + return print(Formatter::get()->format(mtx.getMat(ACCESS_READ)), stream); +} + +template static inline +int print(const std::vector >& vec, FILE* stream = stdout) +{ + return print(Formatter::get()->format(Mat(vec)), stream); +} + +template static inline +int print(const std::vector >& vec, FILE* stream = stdout) +{ + return print(Formatter::get()->format(Mat(vec)), stream); +} + +template static inline +int print(const Matx<_Tp, m, n>& matx, FILE* stream = stdout) +{ + return print(Formatter::get()->format(cv::Mat(matx)), stream); +} + +//! @endcond + +/****************************************************************************************\ +* Auxiliary algorithms * +\****************************************************************************************/ + +/** @brief Splits an element set into equivalency classes. + +The generic function partition implements an \f$O(N^2)\f$ algorithm for splitting a set of \f$N\f$ elements +into one or more equivalency classes, as described in + . The function returns the number of +equivalency classes. +@param _vec Set of elements stored as a vector. +@param labels Output vector of labels. It contains as many elements as vec. Each label labels[i] is +a 0-based cluster index of `vec[i]`. +@param predicate Equivalence predicate (pointer to a boolean function of two arguments or an +instance of the class that has the method bool operator()(const _Tp& a, const _Tp& b) ). The +predicate returns true when the elements are certainly in the same class, and returns false if they +may or may not be in the same class. +@ingroup core_cluster +*/ +template int +partition( const std::vector<_Tp>& _vec, std::vector& labels, + _EqPredicate predicate=_EqPredicate()) +{ + int i, j, N = (int)_vec.size(); + const _Tp* vec = &_vec[0]; + + const int PARENT=0; + const int RANK=1; + + std::vector _nodes(N*2); + int (*nodes)[2] = (int(*)[2])&_nodes[0]; + + // The first O(N) pass: create N single-vertex trees + for(i = 0; i < N; i++) + { + nodes[i][PARENT]=-1; + nodes[i][RANK] = 0; + } + + // The main O(N^2) pass: merge connected components + for( i = 0; i < N; i++ ) + { + int root = i; + + // find root + while( nodes[root][PARENT] >= 0 ) + root = nodes[root][PARENT]; + + for( j = 0; j < N; j++ ) + { + if( i == j || !predicate(vec[i], vec[j])) + continue; + int root2 = j; + + while( nodes[root2][PARENT] >= 0 ) + root2 = nodes[root2][PARENT]; + + if( root2 != root ) + { + // unite both trees + int rank = nodes[root][RANK], rank2 = nodes[root2][RANK]; + if( rank > rank2 ) + nodes[root2][PARENT] = root; + else + { + nodes[root][PARENT] = root2; + nodes[root2][RANK] += rank == rank2; + root = root2; + } + CV_Assert( nodes[root][PARENT] < 0 ); + + int k = j, parent; + + // compress the path from node2 to root + while( (parent = nodes[k][PARENT]) >= 0 ) + { + nodes[k][PARENT] = root; + k = parent; + } + + // compress the path from node to root + k = i; + while( (parent = nodes[k][PARENT]) >= 0 ) + { + nodes[k][PARENT] = root; + k = parent; + } + } + } + } + + // Final O(N) pass: enumerate classes + labels.resize(N); + int nclasses = 0; + + for( i = 0; i < N; i++ ) + { + int root = i; + while( nodes[root][PARENT] >= 0 ) + root = nodes[root][PARENT]; + // re-use the rank as the class label + if( nodes[root][RANK] >= 0 ) + nodes[root][RANK] = ~nclasses++; + labels[i] = ~nodes[root][RANK]; + } + + return nclasses; +} + +} // cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/optim.hpp b/3rdparty/opencv/include/opencv2/core/optim.hpp new file mode 100644 index 00000000..c4729a9c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/optim.hpp @@ -0,0 +1,302 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the OpenCV Foundation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OPTIM_HPP +#define OPENCV_OPTIM_HPP + +#include "opencv2/core.hpp" + +namespace cv +{ + +/** @addtogroup core_optim +The algorithms in this section minimize or maximize function value within specified constraints or +without any constraints. +@{ +*/ + +/** @brief Basic interface for all solvers + */ +class CV_EXPORTS MinProblemSolver : public Algorithm +{ +public: + /** @brief Represents function being optimized + */ + class CV_EXPORTS Function + { + public: + virtual ~Function() {} + virtual int getDims() const = 0; + virtual double getGradientEps() const; + virtual double calc(const double* x) const = 0; + virtual void getGradient(const double* x,double* grad); + }; + + /** @brief Getter for the optimized function. + + The optimized function is represented by Function interface, which requires derivatives to + implement the calc(double*) and getDim() methods to evaluate the function. + + @return Smart-pointer to an object that implements Function interface - it represents the + function that is being optimized. It can be empty, if no function was given so far. + */ + virtual Ptr getFunction() const = 0; + + /** @brief Setter for the optimized function. + + *It should be called at least once before the call to* minimize(), as default value is not usable. + + @param f The new function to optimize. + */ + virtual void setFunction(const Ptr& f) = 0; + + /** @brief Getter for the previously set terminal criteria for this algorithm. + + @return Deep copy of the terminal criteria used at the moment. + */ + virtual TermCriteria getTermCriteria() const = 0; + + /** @brief Set terminal criteria for solver. + + This method *is not necessary* to be called before the first call to minimize(), as the default + value is sensible. + + Algorithm stops when the number of function evaluations done exceeds termcrit.maxCount, when + the function values at the vertices of simplex are within termcrit.epsilon range or simplex + becomes so small that it can enclosed in a box with termcrit.epsilon sides, whatever comes + first. + @param termcrit Terminal criteria to be used, represented as cv::TermCriteria structure. + */ + virtual void setTermCriteria(const TermCriteria& termcrit) = 0; + + /** @brief actually runs the algorithm and performs the minimization. + + The sole input parameter determines the centroid of the starting simplex (roughly, it tells + where to start), all the others (terminal criteria, initial step, function to be minimized) are + supposed to be set via the setters before the call to this method or the default values (not + always sensible) will be used. + + @param x The initial point, that will become a centroid of an initial simplex. After the algorithm + will terminate, it will be set to the point where the algorithm stops, the point of possible + minimum. + @return The value of a function at the point found. + */ + virtual double minimize(InputOutputArray x) = 0; +}; + +/** @brief This class is used to perform the non-linear non-constrained minimization of a function, + +defined on an `n`-dimensional Euclidean space, using the **Nelder-Mead method**, also known as +**downhill simplex method**. The basic idea about the method can be obtained from +. + +It should be noted, that this method, although deterministic, is rather a heuristic and therefore +may converge to a local minima, not necessary a global one. It is iterative optimization technique, +which at each step uses an information about the values of a function evaluated only at `n+1` +points, arranged as a *simplex* in `n`-dimensional space (hence the second name of the method). At +each step new point is chosen to evaluate function at, obtained value is compared with previous +ones and based on this information simplex changes it's shape , slowly moving to the local minimum. +Thus this method is using *only* function values to make decision, on contrary to, say, Nonlinear +Conjugate Gradient method (which is also implemented in optim). + +Algorithm stops when the number of function evaluations done exceeds termcrit.maxCount, when the +function values at the vertices of simplex are within termcrit.epsilon range or simplex becomes so +small that it can enclosed in a box with termcrit.epsilon sides, whatever comes first, for some +defined by user positive integer termcrit.maxCount and positive non-integer termcrit.epsilon. + +@note DownhillSolver is a derivative of the abstract interface +cv::MinProblemSolver, which in turn is derived from the Algorithm interface and is used to +encapsulate the functionality, common to all non-linear optimization algorithms in the optim +module. + +@note term criteria should meet following condition: +@code + termcrit.type == (TermCriteria::MAX_ITER + TermCriteria::EPS) && termcrit.epsilon > 0 && termcrit.maxCount > 0 +@endcode + */ +class CV_EXPORTS DownhillSolver : public MinProblemSolver +{ +public: + /** @brief Returns the initial step that will be used in downhill simplex algorithm. + + @param step Initial step that will be used in algorithm. Note, that although corresponding setter + accepts column-vectors as well as row-vectors, this method will return a row-vector. + @see DownhillSolver::setInitStep + */ + virtual void getInitStep(OutputArray step) const=0; + + /** @brief Sets the initial step that will be used in downhill simplex algorithm. + + Step, together with initial point (givin in DownhillSolver::minimize) are two `n`-dimensional + vectors that are used to determine the shape of initial simplex. Roughly said, initial point + determines the position of a simplex (it will become simplex's centroid), while step determines the + spread (size in each dimension) of a simplex. To be more precise, if \f$s,x_0\in\mathbb{R}^n\f$ are + the initial step and initial point respectively, the vertices of a simplex will be: + \f$v_0:=x_0-\frac{1}{2} s\f$ and \f$v_i:=x_0+s_i\f$ for \f$i=1,2,\dots,n\f$ where \f$s_i\f$ denotes + projections of the initial step of *n*-th coordinate (the result of projection is treated to be + vector given by \f$s_i:=e_i\cdot\left\f$, where \f$e_i\f$ form canonical basis) + + @param step Initial step that will be used in algorithm. Roughly said, it determines the spread + (size in each dimension) of an initial simplex. + */ + virtual void setInitStep(InputArray step)=0; + + /** @brief This function returns the reference to the ready-to-use DownhillSolver object. + + All the parameters are optional, so this procedure can be called even without parameters at + all. In this case, the default values will be used. As default value for terminal criteria are + the only sensible ones, MinProblemSolver::setFunction() and DownhillSolver::setInitStep() + should be called upon the obtained object, if the respective parameters were not given to + create(). Otherwise, the two ways (give parameters to createDownhillSolver() or miss them out + and call the MinProblemSolver::setFunction() and DownhillSolver::setInitStep()) are absolutely + equivalent (and will drop the same errors in the same way, should invalid input be detected). + @param f Pointer to the function that will be minimized, similarly to the one you submit via + MinProblemSolver::setFunction. + @param initStep Initial step, that will be used to construct the initial simplex, similarly to the one + you submit via MinProblemSolver::setInitStep. + @param termcrit Terminal criteria to the algorithm, similarly to the one you submit via + MinProblemSolver::setTermCriteria. + */ + static Ptr create(const Ptr& f=Ptr(), + InputArray initStep=Mat_(1,1,0.0), + TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5000,0.000001)); +}; + +/** @brief This class is used to perform the non-linear non-constrained minimization of a function +with known gradient, + +defined on an *n*-dimensional Euclidean space, using the **Nonlinear Conjugate Gradient method**. +The implementation was done based on the beautifully clear explanatory article [An Introduction to +the Conjugate Gradient Method Without the Agonizing +Pain](http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf) by Jonathan Richard +Shewchuk. The method can be seen as an adaptation of a standard Conjugate Gradient method (see, for +example ) for numerically solving the +systems of linear equations. + +It should be noted, that this method, although deterministic, is rather a heuristic method and +therefore may converge to a local minima, not necessary a global one. What is even more disastrous, +most of its behaviour is ruled by gradient, therefore it essentially cannot distinguish between +local minima and maxima. Therefore, if it starts sufficiently near to the local maximum, it may +converge to it. Another obvious restriction is that it should be possible to compute the gradient of +a function at any point, thus it is preferable to have analytic expression for gradient and +computational burden should be born by the user. + +The latter responsibility is accompilished via the getGradient method of a +MinProblemSolver::Function interface (which represents function being optimized). This method takes +point a point in *n*-dimensional space (first argument represents the array of coordinates of that +point) and comput its gradient (it should be stored in the second argument as an array). + +@note class ConjGradSolver thus does not add any new methods to the basic MinProblemSolver interface. + +@note term criteria should meet following condition: +@code + termcrit.type == (TermCriteria::MAX_ITER + TermCriteria::EPS) && termcrit.epsilon > 0 && termcrit.maxCount > 0 + // or + termcrit.type == TermCriteria::MAX_ITER) && termcrit.maxCount > 0 +@endcode + */ +class CV_EXPORTS ConjGradSolver : public MinProblemSolver +{ +public: + /** @brief This function returns the reference to the ready-to-use ConjGradSolver object. + + All the parameters are optional, so this procedure can be called even without parameters at + all. In this case, the default values will be used. As default value for terminal criteria are + the only sensible ones, MinProblemSolver::setFunction() should be called upon the obtained + object, if the function was not given to create(). Otherwise, the two ways (submit it to + create() or miss it out and call the MinProblemSolver::setFunction()) are absolutely equivalent + (and will drop the same errors in the same way, should invalid input be detected). + @param f Pointer to the function that will be minimized, similarly to the one you submit via + MinProblemSolver::setFunction. + @param termcrit Terminal criteria to the algorithm, similarly to the one you submit via + MinProblemSolver::setTermCriteria. + */ + static Ptr create(const Ptr& f=Ptr(), + TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5000,0.000001)); +}; + +//! return codes for cv::solveLP() function +enum SolveLPResult +{ + SOLVELP_UNBOUNDED = -2, //!< problem is unbounded (target function can achieve arbitrary high values) + SOLVELP_UNFEASIBLE = -1, //!< problem is unfeasible (there are no points that satisfy all the constraints imposed) + SOLVELP_SINGLE = 0, //!< there is only one maximum for target function + SOLVELP_MULTI = 1 //!< there are multiple maxima for target function - the arbitrary one is returned +}; + +/** @brief Solve given (non-integer) linear programming problem using the Simplex Algorithm (Simplex Method). + +What we mean here by "linear programming problem" (or LP problem, for short) can be formulated as: + +\f[\mbox{Maximize } c\cdot x\\ + \mbox{Subject to:}\\ + Ax\leq b\\ + x\geq 0\f] + +Where \f$c\f$ is fixed `1`-by-`n` row-vector, \f$A\f$ is fixed `m`-by-`n` matrix, \f$b\f$ is fixed `m`-by-`1` +column vector and \f$x\f$ is an arbitrary `n`-by-`1` column vector, which satisfies the constraints. + +Simplex algorithm is one of many algorithms that are designed to handle this sort of problems +efficiently. Although it is not optimal in theoretical sense (there exist algorithms that can solve +any problem written as above in polynomial time, while simplex method degenerates to exponential +time for some special cases), it is well-studied, easy to implement and is shown to work well for +real-life purposes. + +The particular implementation is taken almost verbatim from **Introduction to Algorithms, third +edition** by T. H. Cormen, C. E. Leiserson, R. L. Rivest and Clifford Stein. In particular, the +Bland's rule is used to prevent cycling. + +@param Func This row-vector corresponds to \f$c\f$ in the LP problem formulation (see above). It should +contain 32- or 64-bit floating point numbers. As a convenience, column-vector may be also submitted, +in the latter case it is understood to correspond to \f$c^T\f$. +@param Constr `m`-by-`n+1` matrix, whose rightmost column corresponds to \f$b\f$ in formulation above +and the remaining to \f$A\f$. It should contain 32- or 64-bit floating point numbers. +@param z The solution will be returned here as a column-vector - it corresponds to \f$c\f$ in the +formulation above. It will contain 64-bit floating point numbers. +@return One of cv::SolveLPResult + */ +CV_EXPORTS_W int solveLP(const Mat& Func, const Mat& Constr, Mat& z); + +//! @} + +}// cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/ovx.hpp b/3rdparty/opencv/include/opencv2/core/ovx.hpp new file mode 100644 index 00000000..8bb7d549 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/ovx.hpp @@ -0,0 +1,28 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +// Copyright (C) 2016, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. + +// OpenVX related definitions and declarations + +#pragma once +#ifndef OPENCV_OVX_HPP +#define OPENCV_OVX_HPP + +#include "cvdef.h" + +namespace cv +{ +/// Check if use of OpenVX is possible +CV_EXPORTS_W bool haveOpenVX(); + +/// Check if use of OpenVX is enabled +CV_EXPORTS_W bool useOpenVX(); + +/// Enable/disable use of OpenVX +CV_EXPORTS_W void setUseOpenVX(bool flag); +} // namespace cv + +#endif // OPENCV_OVX_HPP diff --git a/3rdparty/opencv/include/opencv2/core/persistence.hpp b/3rdparty/opencv/include/opencv2/core/persistence.hpp new file mode 100644 index 00000000..126393fa --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/persistence.hpp @@ -0,0 +1,1366 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_PERSISTENCE_HPP +#define OPENCV_CORE_PERSISTENCE_HPP + +#ifndef CV_DOXYGEN +/// Define to support persistence legacy formats +#define CV__LEGACY_PERSISTENCE +#endif + +#ifndef __cplusplus +# error persistence.hpp header must be compiled as C++ +#endif + +//! @addtogroup core_c +//! @{ + +/** @brief "black box" representation of the file storage associated with a file on disk. + +Several functions that are described below take CvFileStorage\* as inputs and allow the user to +save or to load hierarchical collections that consist of scalar values, standard CXCore objects +(such as matrices, sequences, graphs), and user-defined objects. + +OpenCV can read and write data in XML (), YAML () or +JSON () formats. Below is an example of 3x3 floating-point identity matrix A, +stored in XML and YAML files +using CXCore functions: +XML: +@code{.xml} + + + + 3 + 3 +
f
+ 1. 0. 0. 0. 1. 0. 0. 0. 1. + + +@endcode +YAML: +@code{.yaml} + %YAML:1.0 + A: !!opencv-matrix + rows: 3 + cols: 3 + dt: f + data: [ 1., 0., 0., 0., 1., 0., 0., 0., 1.] +@endcode +As it can be seen from the examples, XML uses nested tags to represent hierarchy, while YAML uses +indentation for that purpose (similar to the Python programming language). + +The same functions can read and write data in both formats; the particular format is determined by +the extension of the opened file, ".xml" for XML files, ".yml" or ".yaml" for YAML and ".json" for +JSON. + */ +typedef struct CvFileStorage CvFileStorage; +typedef struct CvFileNode CvFileNode; +typedef struct CvMat CvMat; +typedef struct CvMatND CvMatND; + +//! @} core_c + +#include "opencv2/core/types.hpp" +#include "opencv2/core/mat.hpp" + +namespace cv { + +/** @addtogroup core_xml + +XML/YAML/JSON file storages. {#xml_storage} +======================= +Writing to a file storage. +-------------------------- +You can store and then restore various OpenCV data structures to/from XML (), +YAML () or JSON () formats. Also, it is possible to store +and load arbitrarily complex data structures, which include OpenCV data structures, as well as +primitive data types (integer and floating-point numbers and text strings) as their elements. + +Use the following procedure to write something to XML, YAML or JSON: +-# Create new FileStorage and open it for writing. It can be done with a single call to +FileStorage::FileStorage constructor that takes a filename, or you can use the default constructor +and then call FileStorage::open. Format of the file (XML, YAML or JSON) is determined from the filename +extension (".xml", ".yml"/".yaml" and ".json", respectively) +-# Write all the data you want using the streaming operator `<<`, just like in the case of STL +streams. +-# Close the file using FileStorage::release. FileStorage destructor also closes the file. + +Here is an example: +@code + #include "opencv2/opencv.hpp" + #include + + using namespace cv; + + int main(int, char** argv) + { + FileStorage fs("test.yml", FileStorage::WRITE); + + fs << "frameCount" << 5; + time_t rawtime; time(&rawtime); + fs << "calibrationDate" << asctime(localtime(&rawtime)); + Mat cameraMatrix = (Mat_(3,3) << 1000, 0, 320, 0, 1000, 240, 0, 0, 1); + Mat distCoeffs = (Mat_(5,1) << 0.1, 0.01, -0.001, 0, 0); + fs << "cameraMatrix" << cameraMatrix << "distCoeffs" << distCoeffs; + fs << "features" << "["; + for( int i = 0; i < 3; i++ ) + { + int x = rand() % 640; + int y = rand() % 480; + uchar lbp = rand() % 256; + + fs << "{:" << "x" << x << "y" << y << "lbp" << "[:"; + for( int j = 0; j < 8; j++ ) + fs << ((lbp >> j) & 1); + fs << "]" << "}"; + } + fs << "]"; + fs.release(); + return 0; + } +@endcode +The sample above stores to YML an integer, a text string (calibration date), 2 matrices, and a custom +structure "feature", which includes feature coordinates and LBP (local binary pattern) value. Here +is output of the sample: +@code{.yaml} +%YAML:1.0 +frameCount: 5 +calibrationDate: "Fri Jun 17 14:09:29 2011\n" +cameraMatrix: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [ 1000., 0., 320., 0., 1000., 240., 0., 0., 1. ] +distCoeffs: !!opencv-matrix + rows: 5 + cols: 1 + dt: d + data: [ 1.0000000000000001e-01, 1.0000000000000000e-02, + -1.0000000000000000e-03, 0., 0. ] +features: + - { x:167, y:49, lbp:[ 1, 0, 0, 1, 1, 0, 1, 1 ] } + - { x:298, y:130, lbp:[ 0, 0, 0, 1, 0, 0, 1, 1 ] } + - { x:344, y:158, lbp:[ 1, 1, 0, 0, 0, 0, 1, 0 ] } +@endcode + +As an exercise, you can replace ".yml" with ".xml" or ".json" in the sample above and see, how the +corresponding XML file will look like. + +Several things can be noted by looking at the sample code and the output: + +- The produced YAML (and XML/JSON) consists of heterogeneous collections that can be nested. There are + 2 types of collections: named collections (mappings) and unnamed collections (sequences). In mappings + each element has a name and is accessed by name. This is similar to structures and std::map in + C/C++ and dictionaries in Python. In sequences elements do not have names, they are accessed by + indices. This is similar to arrays and std::vector in C/C++ and lists, tuples in Python. + "Heterogeneous" means that elements of each single collection can have different types. + + Top-level collection in YAML/XML/JSON is a mapping. Each matrix is stored as a mapping, and the matrix + elements are stored as a sequence. Then, there is a sequence of features, where each feature is + represented a mapping, and lbp value in a nested sequence. + +- When you write to a mapping (a structure), you write element name followed by its value. When you + write to a sequence, you simply write the elements one by one. OpenCV data structures (such as + cv::Mat) are written in absolutely the same way as simple C data structures - using `<<` + operator. + +- To write a mapping, you first write the special string `{` to the storage, then write the + elements as pairs (`fs << << `) and then write the closing + `}`. + +- To write a sequence, you first write the special string `[`, then write the elements, then + write the closing `]`. + +- In YAML/JSON (but not XML), mappings and sequences can be written in a compact Python-like inline + form. In the sample above matrix elements, as well as each feature, including its lbp value, is + stored in such inline form. To store a mapping/sequence in a compact form, put `:` after the + opening character, e.g. use `{:` instead of `{` and `[:` instead of `[`. When the + data is written to XML, those extra `:` are ignored. + +Reading data from a file storage. +--------------------------------- +To read the previously written XML, YAML or JSON file, do the following: +-# Open the file storage using FileStorage::FileStorage constructor or FileStorage::open method. + In the current implementation the whole file is parsed and the whole representation of file + storage is built in memory as a hierarchy of file nodes (see FileNode) + +-# Read the data you are interested in. Use FileStorage::operator [], FileNode::operator [] + and/or FileNodeIterator. + +-# Close the storage using FileStorage::release. + +Here is how to read the file created by the code sample above: +@code + FileStorage fs2("test.yml", FileStorage::READ); + + // first method: use (type) operator on FileNode. + int frameCount = (int)fs2["frameCount"]; + + String date; + // second method: use FileNode::operator >> + fs2["calibrationDate"] >> date; + + Mat cameraMatrix2, distCoeffs2; + fs2["cameraMatrix"] >> cameraMatrix2; + fs2["distCoeffs"] >> distCoeffs2; + + cout << "frameCount: " << frameCount << endl + << "calibration date: " << date << endl + << "camera matrix: " << cameraMatrix2 << endl + << "distortion coeffs: " << distCoeffs2 << endl; + + FileNode features = fs2["features"]; + FileNodeIterator it = features.begin(), it_end = features.end(); + int idx = 0; + std::vector lbpval; + + // iterate through a sequence using FileNodeIterator + for( ; it != it_end; ++it, idx++ ) + { + cout << "feature #" << idx << ": "; + cout << "x=" << (int)(*it)["x"] << ", y=" << (int)(*it)["y"] << ", lbp: ("; + // you can also easily read numerical arrays using FileNode >> std::vector operator. + (*it)["lbp"] >> lbpval; + for( int i = 0; i < (int)lbpval.size(); i++ ) + cout << " " << (int)lbpval[i]; + cout << ")" << endl; + } + fs2.release(); +@endcode + +Format specification {#format_spec} +-------------------- +`([count]{u|c|w|s|i|f|d})`... where the characters correspond to fundamental C++ types: +- `u` 8-bit unsigned number +- `c` 8-bit signed number +- `w` 16-bit unsigned number +- `s` 16-bit signed number +- `i` 32-bit signed number +- `f` single precision floating-point number +- `d` double precision floating-point number +- `r` pointer, 32 lower bits of which are written as a signed integer. The type can be used to + store structures with links between the elements. + +`count` is the optional counter of values of a given type. For example, `2if` means that each array +element is a structure of 2 integers, followed by a single-precision floating-point number. The +equivalent notations of the above specification are `iif`, `2i1f` and so forth. Other examples: `u` +means that the array consists of bytes, and `2d` means the array consists of pairs of doubles. + +@see @ref samples/cpp/filestorage.cpp +*/ + +//! @{ + +/** @example samples/cpp/filestorage.cpp +A complete example using the FileStorage interface +*/ + +////////////////////////// XML & YAML I/O ////////////////////////// + +class CV_EXPORTS FileNode; +class CV_EXPORTS FileNodeIterator; + +/** @brief XML/YAML/JSON file storage class that encapsulates all the information necessary for writing or +reading data to/from a file. + */ +class CV_EXPORTS_W FileStorage +{ +public: + //! file storage mode + enum Mode + { + READ = 0, //!< value, open the file for reading + WRITE = 1, //!< value, open the file for writing + APPEND = 2, //!< value, open the file for appending + MEMORY = 4, //!< flag, read data from source or write data to the internal buffer (which is + //!< returned by FileStorage::release) + FORMAT_MASK = (7<<3), //!< mask for format flags + FORMAT_AUTO = 0, //!< flag, auto format + FORMAT_XML = (1<<3), //!< flag, XML format + FORMAT_YAML = (2<<3), //!< flag, YAML format + FORMAT_JSON = (3<<3), //!< flag, JSON format + + BASE64 = 64, //!< flag, write rawdata in Base64 by default. (consider using WRITE_BASE64) + WRITE_BASE64 = BASE64 | WRITE, //!< flag, enable both WRITE and BASE64 + }; + enum + { + UNDEFINED = 0, + VALUE_EXPECTED = 1, + NAME_EXPECTED = 2, + INSIDE_MAP = 4 + }; + + /** @brief The constructors. + + The full constructor opens the file. Alternatively you can use the default constructor and then + call FileStorage::open. + */ + CV_WRAP FileStorage(); + + /** @overload + @copydoc open() + */ + CV_WRAP FileStorage(const String& filename, int flags, const String& encoding=String()); + + /** @overload */ + FileStorage(CvFileStorage* fs, bool owning=true); + + //! the destructor. calls release() + virtual ~FileStorage(); + + /** @brief Opens a file. + + See description of parameters in FileStorage::FileStorage. The method calls FileStorage::release + before opening the file. + @param filename Name of the file to open or the text string to read the data from. + Extension of the file (.xml, .yml/.yaml or .json) determines its format (XML, YAML or JSON + respectively). Also you can append .gz to work with compressed files, for example myHugeMatrix.xml.gz. If both + FileStorage::WRITE and FileStorage::MEMORY flags are specified, source is used just to specify + the output file format (e.g. mydata.xml, .yml etc.). A file name can also contain parameters. + You can use this format, "*?base64" (e.g. "file.json?base64" (case sensitive)), as an alternative to + FileStorage::BASE64 flag. + @param flags Mode of operation. One of FileStorage::Mode + @param encoding Encoding of the file. Note that UTF-16 XML encoding is not supported currently and + you should use 8-bit encoding instead of it. + */ + CV_WRAP virtual bool open(const String& filename, int flags, const String& encoding=String()); + + /** @brief Checks whether the file is opened. + + @returns true if the object is associated with the current file and false otherwise. It is a + good practice to call this method after you tried to open a file. + */ + CV_WRAP virtual bool isOpened() const; + + /** @brief Closes the file and releases all the memory buffers. + + Call this method after all I/O operations with the storage are finished. + */ + CV_WRAP virtual void release(); + + /** @brief Closes the file and releases all the memory buffers. + + Call this method after all I/O operations with the storage are finished. If the storage was + opened for writing data and FileStorage::WRITE was specified + */ + CV_WRAP virtual String releaseAndGetString(); + + /** @brief Returns the first element of the top-level mapping. + @returns The first element of the top-level mapping. + */ + CV_WRAP FileNode getFirstTopLevelNode() const; + + /** @brief Returns the top-level mapping + @param streamidx Zero-based index of the stream. In most cases there is only one stream in the file. + However, YAML supports multiple streams and so there can be several. + @returns The top-level mapping. + */ + CV_WRAP FileNode root(int streamidx=0) const; + + /** @brief Returns the specified element of the top-level mapping. + @param nodename Name of the file node. + @returns Node with the given name. + */ + FileNode operator[](const String& nodename) const; + + /** @overload */ + CV_WRAP_AS(getNode) FileNode operator[](const char* nodename) const; + + /** @brief Returns the obsolete C FileStorage structure. + @returns Pointer to the underlying C FileStorage structure + */ + CvFileStorage* operator *() { return fs.get(); } + + /** @overload */ + const CvFileStorage* operator *() const { return fs.get(); } + + /** @brief Writes multiple numbers. + + Writes one or more numbers of the specified format to the currently written structure. Usually it is + more convenient to use operator `<<` instead of this method. + @param fmt Specification of each array element, see @ref format_spec "format specification" + @param vec Pointer to the written array. + @param len Number of the uchar elements to write. + */ + void writeRaw( const String& fmt, const uchar* vec, size_t len ); + + /** @brief Writes the registered C structure (CvMat, CvMatND, CvSeq). + @param name Name of the written object. + @param obj Pointer to the object. + @see ocvWrite for details. + */ + void writeObj( const String& name, const void* obj ); + + /** + * @brief Simplified writing API to use with bindings. + * @param name Name of the written object + * @param val Value of the written object + */ + CV_WRAP void write(const String& name, int val); + /// @overload + CV_WRAP void write(const String& name, double val); + /// @overload + CV_WRAP void write(const String& name, const String& val); + /// @overload + CV_WRAP void write(const String& name, InputArray val); + + /** @brief Writes a comment. + + The function writes a comment into file storage. The comments are skipped when the storage is read. + @param comment The written comment, single-line or multi-line + @param append If true, the function tries to put the comment at the end of current line. + Else if the comment is multi-line, or if it does not fit at the end of the current + line, the comment starts a new line. + */ + CV_WRAP void writeComment(const String& comment, bool append = false); + + /** @brief Returns the normalized object name for the specified name of a file. + @param filename Name of a file + @returns The normalized object name. + */ + static String getDefaultObjectName(const String& filename); + + /** @brief Returns the current format. + * @returns The current format, see FileStorage::Mode + */ + CV_WRAP int getFormat() const; + + Ptr fs; //!< the underlying C FileStorage structure + String elname; //!< the currently written element + std::vector structs; //!< the stack of written structures + int state; //!< the writer state +}; + +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvFileStorage* obj) const; + +/** @brief File Storage Node class. + +The node is used to store each and every element of the file storage opened for reading. When +XML/YAML file is read, it is first parsed and stored in the memory as a hierarchical collection of +nodes. Each node can be a "leaf" that is contain a single number or a string, or be a collection of +other nodes. There can be named collections (mappings) where each element has a name and it is +accessed by a name, and ordered collections (sequences) where elements do not have names but rather +accessed by index. Type of the file node can be determined using FileNode::type method. + +Note that file nodes are only used for navigating file storages opened for reading. When a file +storage is opened for writing, no data is stored in memory after it is written. + */ +class CV_EXPORTS_W_SIMPLE FileNode +{ +public: + //! type of the file storage node + enum Type + { + NONE = 0, //!< empty node + INT = 1, //!< an integer + REAL = 2, //!< floating-point number + FLOAT = REAL, //!< synonym or REAL + STR = 3, //!< text string in UTF-8 encoding + STRING = STR, //!< synonym for STR + REF = 4, //!< integer of size size_t. Typically used for storing complex dynamic structures where some elements reference the others + SEQ = 5, //!< sequence + MAP = 6, //!< mapping + TYPE_MASK = 7, + FLOW = 8, //!< compact representation of a sequence or mapping. Used only by YAML writer + USER = 16, //!< a registered object (e.g. a matrix) + EMPTY = 32, //!< empty structure (sequence or mapping) + NAMED = 64 //!< the node has a name (i.e. it is element of a mapping) + }; + /** @brief The constructors. + + These constructors are used to create a default file node, construct it from obsolete structures or + from the another file node. + */ + CV_WRAP FileNode(); + + /** @overload + @param fs Pointer to the obsolete file storage structure. + @param node File node to be used as initialization for the created file node. + */ + FileNode(const CvFileStorage* fs, const CvFileNode* node); + + /** @overload + @param node File node to be used as initialization for the created file node. + */ + FileNode(const FileNode& node); + + /** @brief Returns element of a mapping node or a sequence node. + @param nodename Name of an element in the mapping node. + @returns Returns the element with the given identifier. + */ + FileNode operator[](const String& nodename) const; + + /** @overload + @param nodename Name of an element in the mapping node. + */ + CV_WRAP_AS(getNode) FileNode operator[](const char* nodename) const; + + /** @overload + @param i Index of an element in the sequence node. + */ + CV_WRAP_AS(at) FileNode operator[](int i) const; + + /** @brief Returns keys of a mapping node. + @returns Keys of a mapping node. + */ + CV_WRAP std::vector keys() const; + + /** @brief Returns type of the node. + @returns Type of the node. See FileNode::Type + */ + CV_WRAP int type() const; + + //! returns true if the node is empty + CV_WRAP bool empty() const; + //! returns true if the node is a "none" object + CV_WRAP bool isNone() const; + //! returns true if the node is a sequence + CV_WRAP bool isSeq() const; + //! returns true if the node is a mapping + CV_WRAP bool isMap() const; + //! returns true if the node is an integer + CV_WRAP bool isInt() const; + //! returns true if the node is a floating-point number + CV_WRAP bool isReal() const; + //! returns true if the node is a text string + CV_WRAP bool isString() const; + //! returns true if the node has a name + CV_WRAP bool isNamed() const; + //! returns the node name or an empty string if the node is nameless + CV_WRAP String name() const; + //! returns the number of elements in the node, if it is a sequence or mapping, or 1 otherwise. + CV_WRAP size_t size() const; + //! returns the node content as an integer. If the node stores floating-point number, it is rounded. + operator int() const; + //! returns the node content as float + operator float() const; + //! returns the node content as double + operator double() const; + //! returns the node content as text string + operator String() const; + operator std::string() const; + + //! returns pointer to the underlying file node + CvFileNode* operator *(); + //! returns pointer to the underlying file node + const CvFileNode* operator* () const; + + //! returns iterator pointing to the first node element + FileNodeIterator begin() const; + //! returns iterator pointing to the element following the last node element + FileNodeIterator end() const; + + /** @brief Reads node elements to the buffer with the specified format. + + Usually it is more convenient to use operator `>>` instead of this method. + @param fmt Specification of each array element. See @ref format_spec "format specification" + @param vec Pointer to the destination array. + @param len Number of elements to read. If it is greater than number of remaining elements then all + of them will be read. + */ + void readRaw( const String& fmt, uchar* vec, size_t len ) const; + + //! reads the registered object and returns pointer to it + void* readObj() const; + + //! Simplified reading API to use with bindings. + CV_WRAP double real() const; + //! Simplified reading API to use with bindings. + CV_WRAP String string() const; + //! Simplified reading API to use with bindings. + CV_WRAP Mat mat() const; + + // do not use wrapper pointer classes for better efficiency + const CvFileStorage* fs; + const CvFileNode* node; +}; + + +/** @brief used to iterate through sequences and mappings. + +A standard STL notation, with node.begin(), node.end() denoting the beginning and the end of a +sequence, stored in node. See the data reading sample in the beginning of the section. + */ +class CV_EXPORTS FileNodeIterator +{ +public: + /** @brief The constructors. + + These constructors are used to create a default iterator, set it to specific element in a file node + or construct it from another iterator. + */ + FileNodeIterator(); + + /** @overload + @param fs File storage for the iterator. + @param node File node for the iterator. + @param ofs Index of the element in the node. The created iterator will point to this element. + */ + FileNodeIterator(const CvFileStorage* fs, const CvFileNode* node, size_t ofs=0); + + /** @overload + @param it Iterator to be used as initialization for the created iterator. + */ + FileNodeIterator(const FileNodeIterator& it); + + //! returns the currently observed element + FileNode operator *() const; + //! accesses the currently observed element methods + FileNode operator ->() const; + + //! moves iterator to the next node + FileNodeIterator& operator ++ (); + //! moves iterator to the next node + FileNodeIterator operator ++ (int); + //! moves iterator to the previous node + FileNodeIterator& operator -- (); + //! moves iterator to the previous node + FileNodeIterator operator -- (int); + //! moves iterator forward by the specified offset (possibly negative) + FileNodeIterator& operator += (int ofs); + //! moves iterator backward by the specified offset (possibly negative) + FileNodeIterator& operator -= (int ofs); + + /** @brief Reads node elements to the buffer with the specified format. + + Usually it is more convenient to use operator `>>` instead of this method. + @param fmt Specification of each array element. See @ref format_spec "format specification" + @param vec Pointer to the destination array. + @param maxCount Number of elements to read. If it is greater than number of remaining elements then + all of them will be read. + */ + FileNodeIterator& readRaw( const String& fmt, uchar* vec, + size_t maxCount=(size_t)INT_MAX ); + + struct SeqReader + { + int header_size; + void* seq; /* sequence, beign read; CvSeq */ + void* block; /* current block; CvSeqBlock */ + schar* ptr; /* pointer to element be read next */ + schar* block_min; /* pointer to the beginning of block */ + schar* block_max; /* pointer to the end of block */ + int delta_index;/* = seq->first->start_index */ + schar* prev_elem; /* pointer to previous element */ + }; + + const CvFileStorage* fs; + const CvFileNode* container; + SeqReader reader; + size_t remaining; +}; + +//! @} core_xml + +/////////////////// XML & YAML I/O implementation ////////////////// + +//! @relates cv::FileStorage +//! @{ + +CV_EXPORTS void write( FileStorage& fs, const String& name, int value ); +CV_EXPORTS void write( FileStorage& fs, const String& name, float value ); +CV_EXPORTS void write( FileStorage& fs, const String& name, double value ); +CV_EXPORTS void write( FileStorage& fs, const String& name, const String& value ); +CV_EXPORTS void write( FileStorage& fs, const String& name, const Mat& value ); +CV_EXPORTS void write( FileStorage& fs, const String& name, const SparseMat& value ); +#ifdef CV__LEGACY_PERSISTENCE +CV_EXPORTS void write( FileStorage& fs, const String& name, const std::vector& value); +CV_EXPORTS void write( FileStorage& fs, const String& name, const std::vector& value); +#endif + +CV_EXPORTS void writeScalar( FileStorage& fs, int value ); +CV_EXPORTS void writeScalar( FileStorage& fs, float value ); +CV_EXPORTS void writeScalar( FileStorage& fs, double value ); +CV_EXPORTS void writeScalar( FileStorage& fs, const String& value ); + +//! @} + +//! @relates cv::FileNode +//! @{ + +CV_EXPORTS void read(const FileNode& node, int& value, int default_value); +CV_EXPORTS void read(const FileNode& node, float& value, float default_value); +CV_EXPORTS void read(const FileNode& node, double& value, double default_value); +CV_EXPORTS void read(const FileNode& node, String& value, const String& default_value); +CV_EXPORTS void read(const FileNode& node, std::string& value, const std::string& default_value); +CV_EXPORTS void read(const FileNode& node, Mat& mat, const Mat& default_mat = Mat() ); +CV_EXPORTS void read(const FileNode& node, SparseMat& mat, const SparseMat& default_mat = SparseMat() ); +#ifdef CV__LEGACY_PERSISTENCE +CV_EXPORTS void read(const FileNode& node, std::vector& keypoints); +CV_EXPORTS void read(const FileNode& node, std::vector& matches); +#endif +CV_EXPORTS void read(const FileNode& node, KeyPoint& value, const KeyPoint& default_value); +CV_EXPORTS void read(const FileNode& node, DMatch& value, const DMatch& default_value); + +template static inline void read(const FileNode& node, Point_<_Tp>& value, const Point_<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 2 ? default_value : Point_<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1])); +} + +template static inline void read(const FileNode& node, Point3_<_Tp>& value, const Point3_<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 3 ? default_value : Point3_<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1]), + saturate_cast<_Tp>(temp[2])); +} + +template static inline void read(const FileNode& node, Size_<_Tp>& value, const Size_<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 2 ? default_value : Size_<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1])); +} + +template static inline void read(const FileNode& node, Complex<_Tp>& value, const Complex<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 2 ? default_value : Complex<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1])); +} + +template static inline void read(const FileNode& node, Rect_<_Tp>& value, const Rect_<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 4 ? default_value : Rect_<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1]), + saturate_cast<_Tp>(temp[2]), saturate_cast<_Tp>(temp[3])); +} + +template static inline void read(const FileNode& node, Vec<_Tp, cn>& value, const Vec<_Tp, cn>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != cn ? default_value : Vec<_Tp, cn>(&temp[0]); +} + +template static inline void read(const FileNode& node, Scalar_<_Tp>& value, const Scalar_<_Tp>& default_value) +{ + std::vector<_Tp> temp; FileNodeIterator it = node.begin(); it >> temp; + value = temp.size() != 4 ? default_value : Scalar_<_Tp>(saturate_cast<_Tp>(temp[0]), saturate_cast<_Tp>(temp[1]), + saturate_cast<_Tp>(temp[2]), saturate_cast<_Tp>(temp[3])); +} + +static inline void read(const FileNode& node, Range& value, const Range& default_value) +{ + Point2i temp(value.start, value.end); const Point2i default_temp = Point2i(default_value.start, default_value.end); + read(node, temp, default_temp); + value.start = temp.x; value.end = temp.y; +} + +//! @} + +/** @brief Writes string to a file storage. +@relates cv::FileStorage + */ +CV_EXPORTS FileStorage& operator << (FileStorage& fs, const String& str); + +//! @cond IGNORED + +namespace internal +{ + class CV_EXPORTS WriteStructContext + { + public: + WriteStructContext(FileStorage& _fs, const String& name, int flags, const String& typeName = String()); + ~WriteStructContext(); + private: + FileStorage* fs; + }; + + template class VecWriterProxy + { + public: + VecWriterProxy( FileStorage* _fs ) : fs(_fs) {} + void operator()(const std::vector<_Tp>& vec) const + { + size_t count = vec.size(); + for (size_t i = 0; i < count; i++) + write(*fs, vec[i]); + } + private: + FileStorage* fs; + }; + + template class VecWriterProxy<_Tp, 1> + { + public: + VecWriterProxy( FileStorage* _fs ) : fs(_fs) {} + void operator()(const std::vector<_Tp>& vec) const + { + int _fmt = traits::SafeFmt<_Tp>::fmt; + char fmt[] = { (char)((_fmt >> 8) + '1'), (char)_fmt, '\0' }; + fs->writeRaw(fmt, !vec.empty() ? (uchar*)&vec[0] : 0, vec.size() * sizeof(_Tp)); + } + private: + FileStorage* fs; + }; + + template class VecReaderProxy + { + public: + VecReaderProxy( FileNodeIterator* _it ) : it(_it) {} + void operator()(std::vector<_Tp>& vec, size_t count) const + { + count = std::min(count, it->remaining); + vec.resize(count); + for (size_t i = 0; i < count; i++, ++(*it)) + read(**it, vec[i], _Tp()); + } + private: + FileNodeIterator* it; + }; + + template class VecReaderProxy<_Tp, 1> + { + public: + VecReaderProxy( FileNodeIterator* _it ) : it(_it) {} + void operator()(std::vector<_Tp>& vec, size_t count) const + { + size_t remaining = it->remaining; + size_t cn = DataType<_Tp>::channels; + int _fmt = traits::SafeFmt<_Tp>::fmt; + CV_Assert((_fmt >> 8) < 9); + char fmt[] = { (char)((_fmt >> 8)+'1'), (char)_fmt, '\0' }; + CV_Assert((remaining % cn) == 0); + size_t remaining1 = remaining / cn; + count = count < remaining1 ? count : remaining1; + vec.resize(count); + it->readRaw(fmt, !vec.empty() ? (uchar*)&vec[0] : 0, count*sizeof(_Tp)); + } + private: + FileNodeIterator* it; + }; + +} // internal + +//! @endcond + +//! @relates cv::FileStorage +//! @{ + +template static inline +void write(FileStorage& fs, const _Tp& value) +{ + write(fs, String(), value); +} + +template<> inline +void write( FileStorage& fs, const int& value ) +{ + writeScalar(fs, value); +} + +template<> inline +void write( FileStorage& fs, const float& value ) +{ + writeScalar(fs, value); +} + +template<> inline +void write( FileStorage& fs, const double& value ) +{ + writeScalar(fs, value); +} + +template<> inline +void write( FileStorage& fs, const String& value ) +{ + writeScalar(fs, value); +} + +template static inline +void write(FileStorage& fs, const Point_<_Tp>& pt ) +{ + write(fs, pt.x); + write(fs, pt.y); +} + +template static inline +void write(FileStorage& fs, const Point3_<_Tp>& pt ) +{ + write(fs, pt.x); + write(fs, pt.y); + write(fs, pt.z); +} + +template static inline +void write(FileStorage& fs, const Size_<_Tp>& sz ) +{ + write(fs, sz.width); + write(fs, sz.height); +} + +template static inline +void write(FileStorage& fs, const Complex<_Tp>& c ) +{ + write(fs, c.re); + write(fs, c.im); +} + +template static inline +void write(FileStorage& fs, const Rect_<_Tp>& r ) +{ + write(fs, r.x); + write(fs, r.y); + write(fs, r.width); + write(fs, r.height); +} + +template static inline +void write(FileStorage& fs, const Vec<_Tp, cn>& v ) +{ + for(int i = 0; i < cn; i++) + write(fs, v.val[i]); +} + +template static inline +void write(FileStorage& fs, const Scalar_<_Tp>& s ) +{ + write(fs, s.val[0]); + write(fs, s.val[1]); + write(fs, s.val[2]); + write(fs, s.val[3]); +} + +static inline +void write(FileStorage& fs, const Range& r ) +{ + write(fs, r.start); + write(fs, r.end); +} + +template static inline +void write( FileStorage& fs, const std::vector<_Tp>& vec ) +{ + cv::internal::VecWriterProxy<_Tp, traits::SafeFmt<_Tp>::fmt != 0> w(&fs); + w(vec); +} + +template static inline +void write(FileStorage& fs, const String& name, const Point_<_Tp>& pt ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, pt); +} + +template static inline +void write(FileStorage& fs, const String& name, const Point3_<_Tp>& pt ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, pt); +} + +template static inline +void write(FileStorage& fs, const String& name, const Size_<_Tp>& sz ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, sz); +} + +template static inline +void write(FileStorage& fs, const String& name, const Complex<_Tp>& c ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, c); +} + +template static inline +void write(FileStorage& fs, const String& name, const Rect_<_Tp>& r ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, r); +} + +template static inline +void write(FileStorage& fs, const String& name, const Vec<_Tp, cn>& v ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, v); +} + +template static inline +void write(FileStorage& fs, const String& name, const Scalar_<_Tp>& s ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, s); +} + +static inline +void write(FileStorage& fs, const String& name, const Range& r ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, r); +} + +static inline +void write(FileStorage& fs, const String& name, const KeyPoint& kpt) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, kpt.pt.x); + write(fs, kpt.pt.y); + write(fs, kpt.size); + write(fs, kpt.angle); + write(fs, kpt.response); + write(fs, kpt.octave); + write(fs, kpt.class_id); +} + +static inline +void write(FileStorage& fs, const String& name, const DMatch& m) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+FileNode::FLOW); + write(fs, m.queryIdx); + write(fs, m.trainIdx); + write(fs, m.imgIdx); + write(fs, m.distance); +} + +template static inline +void write( FileStorage& fs, const String& name, const std::vector<_Tp>& vec ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ+(traits::SafeFmt<_Tp>::fmt != 0 ? FileNode::FLOW : 0)); + write(fs, vec); +} + +template static inline +void write( FileStorage& fs, const String& name, const std::vector< std::vector<_Tp> >& vec ) +{ + cv::internal::WriteStructContext ws(fs, name, FileNode::SEQ); + for(size_t i = 0; i < vec.size(); i++) + { + cv::internal::WriteStructContext ws_(fs, name, FileNode::SEQ+(traits::SafeFmt<_Tp>::fmt != 0 ? FileNode::FLOW : 0)); + write(fs, vec[i]); + } +} + +#ifdef CV__LEGACY_PERSISTENCE +// This code is not needed anymore, but it is preserved here to keep source compatibility +// Implementation is similar to templates instantiations +static inline void write(FileStorage& fs, const KeyPoint& kpt) { write(fs, String(), kpt); } +static inline void write(FileStorage& fs, const DMatch& m) { write(fs, String(), m); } +static inline void write(FileStorage& fs, const std::vector& vec) +{ + cv::internal::VecWriterProxy w(&fs); + w(vec); +} +static inline void write(FileStorage& fs, const std::vector& vec) +{ + cv::internal::VecWriterProxy w(&fs); + w(vec); + +} +#endif + +//! @} FileStorage + +//! @relates cv::FileNode +//! @{ + +static inline +void read(const FileNode& node, bool& value, bool default_value) +{ + int temp; + read(node, temp, (int)default_value); + value = temp != 0; +} + +static inline +void read(const FileNode& node, uchar& value, uchar default_value) +{ + int temp; + read(node, temp, (int)default_value); + value = saturate_cast(temp); +} + +static inline +void read(const FileNode& node, schar& value, schar default_value) +{ + int temp; + read(node, temp, (int)default_value); + value = saturate_cast(temp); +} + +static inline +void read(const FileNode& node, ushort& value, ushort default_value) +{ + int temp; + read(node, temp, (int)default_value); + value = saturate_cast(temp); +} + +static inline +void read(const FileNode& node, short& value, short default_value) +{ + int temp; + read(node, temp, (int)default_value); + value = saturate_cast(temp); +} + +template static inline +void read( FileNodeIterator& it, std::vector<_Tp>& vec, size_t maxCount = (size_t)INT_MAX ) +{ + cv::internal::VecReaderProxy<_Tp, traits::SafeFmt<_Tp>::fmt != 0> r(&it); + r(vec, maxCount); +} + +template static inline +void read( const FileNode& node, std::vector<_Tp>& vec, const std::vector<_Tp>& default_value = std::vector<_Tp>() ) +{ + if(!node.node) + vec = default_value; + else + { + FileNodeIterator it = node.begin(); + read( it, vec ); + } +} + +static inline +void read( const FileNode& node, std::vector& vec, const std::vector& default_value ) +{ + if(!node.node) + vec = default_value; + else + read(node, vec); +} + +static inline +void read( const FileNode& node, std::vector& vec, const std::vector& default_value ) +{ + if(!node.node) + vec = default_value; + else + read(node, vec); +} + +//! @} FileNode + +//! @relates cv::FileStorage +//! @{ + +/** @brief Writes data to a file storage. + */ +template static inline +FileStorage& operator << (FileStorage& fs, const _Tp& value) +{ + if( !fs.isOpened() ) + return fs; + if( fs.state == FileStorage::NAME_EXPECTED + FileStorage::INSIDE_MAP ) + CV_Error( Error::StsError, "No element name has been given" ); + write( fs, fs.elname, value ); + if( fs.state & FileStorage::INSIDE_MAP ) + fs.state = FileStorage::NAME_EXPECTED + FileStorage::INSIDE_MAP; + return fs; +} + +/** @brief Writes data to a file storage. + */ +static inline +FileStorage& operator << (FileStorage& fs, const char* str) +{ + return (fs << String(str)); +} + +/** @brief Writes data to a file storage. + */ +static inline +FileStorage& operator << (FileStorage& fs, char* value) +{ + return (fs << String(value)); +} + +//! @} FileStorage + +//! @relates cv::FileNodeIterator +//! @{ + +/** @brief Reads data from a file storage. + */ +template static inline +FileNodeIterator& operator >> (FileNodeIterator& it, _Tp& value) +{ + read( *it, value, _Tp()); + return ++it; +} + +/** @brief Reads data from a file storage. + */ +template static inline +FileNodeIterator& operator >> (FileNodeIterator& it, std::vector<_Tp>& vec) +{ + cv::internal::VecReaderProxy<_Tp, traits::SafeFmt<_Tp>::fmt != 0> r(&it); + r(vec, (size_t)INT_MAX); + return it; +} + +//! @} FileNodeIterator + +//! @relates cv::FileNode +//! @{ + +/** @brief Reads data from a file storage. + */ +template static inline +void operator >> (const FileNode& n, _Tp& value) +{ + read( n, value, _Tp()); +} + +/** @brief Reads data from a file storage. + */ +template static inline +void operator >> (const FileNode& n, std::vector<_Tp>& vec) +{ + FileNodeIterator it = n.begin(); + it >> vec; +} + +/** @brief Reads KeyPoint from a file storage. +*/ +//It needs special handling because it contains two types of fields, int & float. +static inline +void operator >> (const FileNode& n, KeyPoint& kpt) +{ + FileNodeIterator it = n.begin(); + it >> kpt.pt.x >> kpt.pt.y >> kpt.size >> kpt.angle >> kpt.response >> kpt.octave >> kpt.class_id; +} + +#ifdef CV__LEGACY_PERSISTENCE +static inline +void operator >> (const FileNode& n, std::vector& vec) +{ + read(n, vec); +} +static inline +void operator >> (const FileNode& n, std::vector& vec) +{ + read(n, vec); +} +#endif + +/** @brief Reads DMatch from a file storage. +*/ +//It needs special handling because it contains two types of fields, int & float. +static inline +void operator >> (const FileNode& n, DMatch& m) +{ + FileNodeIterator it = n.begin(); + it >> m.queryIdx >> m.trainIdx >> m.imgIdx >> m.distance; +} + +//! @} FileNode + +//! @relates cv::FileNodeIterator +//! @{ + +static inline +bool operator == (const FileNodeIterator& it1, const FileNodeIterator& it2) +{ + return it1.fs == it2.fs && it1.container == it2.container && + it1.reader.ptr == it2.reader.ptr && it1.remaining == it2.remaining; +} + +static inline +bool operator != (const FileNodeIterator& it1, const FileNodeIterator& it2) +{ + return !(it1 == it2); +} + +static inline +ptrdiff_t operator - (const FileNodeIterator& it1, const FileNodeIterator& it2) +{ + return it2.remaining - it1.remaining; +} + +static inline +bool operator < (const FileNodeIterator& it1, const FileNodeIterator& it2) +{ + return it1.remaining > it2.remaining; +} + +//! @} FileNodeIterator + +//! @cond IGNORED + +inline FileNode FileStorage::getFirstTopLevelNode() const { FileNode r = root(); FileNodeIterator it = r.begin(); return it != r.end() ? *it : FileNode(); } +inline FileNode::FileNode() : fs(0), node(0) {} +inline FileNode::FileNode(const CvFileStorage* _fs, const CvFileNode* _node) : fs(_fs), node(_node) {} +inline FileNode::FileNode(const FileNode& _node) : fs(_node.fs), node(_node.node) {} +inline bool FileNode::empty() const { return node == 0; } +inline bool FileNode::isNone() const { return type() == NONE; } +inline bool FileNode::isSeq() const { return type() == SEQ; } +inline bool FileNode::isMap() const { return type() == MAP; } +inline bool FileNode::isInt() const { return type() == INT; } +inline bool FileNode::isReal() const { return type() == REAL; } +inline bool FileNode::isString() const { return type() == STR; } +inline CvFileNode* FileNode::operator *() { return (CvFileNode*)node; } +inline const CvFileNode* FileNode::operator* () const { return node; } +inline FileNode::operator int() const { int value; read(*this, value, 0); return value; } +inline FileNode::operator float() const { float value; read(*this, value, 0.f); return value; } +inline FileNode::operator double() const { double value; read(*this, value, 0.); return value; } +inline FileNode::operator String() const { String value; read(*this, value, value); return value; } +inline double FileNode::real() const { return double(*this); } +inline String FileNode::string() const { return String(*this); } +inline Mat FileNode::mat() const { Mat value; read(*this, value, value); return value; } +inline FileNodeIterator FileNode::begin() const { return FileNodeIterator(fs, node); } +inline FileNodeIterator FileNode::end() const { return FileNodeIterator(fs, node, size()); } +inline void FileNode::readRaw( const String& fmt, uchar* vec, size_t len ) const { begin().readRaw( fmt, vec, len ); } +inline FileNode FileNodeIterator::operator *() const { return FileNode(fs, (const CvFileNode*)(const void*)reader.ptr); } +inline FileNode FileNodeIterator::operator ->() const { return FileNode(fs, (const CvFileNode*)(const void*)reader.ptr); } +inline String::String(const FileNode& fn): cstr_(0), len_(0) { read(fn, *this, *this); } + +//! @endcond + + +CV_EXPORTS void cvStartWriteRawData_Base64(::CvFileStorage * fs, const char* name, int len, const char* dt); + +CV_EXPORTS void cvWriteRawData_Base64(::CvFileStorage * fs, const void* _data, int len); + +CV_EXPORTS void cvEndWriteRawData_Base64(::CvFileStorage * fs); + +CV_EXPORTS void cvWriteMat_Base64(::CvFileStorage* fs, const char* name, const ::CvMat* mat); + +CV_EXPORTS void cvWriteMatND_Base64(::CvFileStorage* fs, const char* name, const ::CvMatND* mat); + +} // cv + +#endif // OPENCV_CORE_PERSISTENCE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/ptr.inl.hpp b/3rdparty/opencv/include/opencv2/core/ptr.inl.hpp new file mode 100644 index 00000000..466f6342 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/ptr.inl.hpp @@ -0,0 +1,379 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, NVIDIA Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the copyright holders or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_PTR_INL_HPP +#define OPENCV_CORE_PTR_INL_HPP + +#include + +//! @cond IGNORED + +namespace cv { + +template +void DefaultDeleter::operator () (Y* p) const +{ + delete p; +} + +namespace detail +{ + +struct PtrOwner +{ + PtrOwner() : refCount(1) + {} + + void incRef() + { + CV_XADD(&refCount, 1); + } + + void decRef() + { + if (CV_XADD(&refCount, -1) == 1) deleteSelf(); + } + +protected: + /* This doesn't really need to be virtual, since PtrOwner is never deleted + directly, but it doesn't hurt and it helps avoid warnings. */ + virtual ~PtrOwner() + {} + + virtual void deleteSelf() = 0; + +private: + unsigned int refCount; + + // noncopyable + PtrOwner(const PtrOwner&); + PtrOwner& operator = (const PtrOwner&); +}; + +template +struct PtrOwnerImpl CV_FINAL : PtrOwner +{ + PtrOwnerImpl(Y* p, D d) : owned(p), deleter(d) + {} + + void deleteSelf() CV_OVERRIDE + { + deleter(owned); + delete this; + } + +private: + Y* owned; + D deleter; +}; + + +} + +template +Ptr::Ptr() : owner(NULL), stored(NULL) +{} + +template +template +Ptr::Ptr(Y* p) + : owner(p + ? new detail::PtrOwnerImpl >(p, DefaultDeleter()) + : NULL), + stored(p) +{} + +template +template +Ptr::Ptr(Y* p, D d) + : owner(p + ? new detail::PtrOwnerImpl(p, d) + : NULL), + stored(p) +{} + +template +Ptr::Ptr(const Ptr& o) : owner(o.owner), stored(o.stored) +{ + if (owner) owner->incRef(); +} + +template +template +Ptr::Ptr(const Ptr& o) : owner(o.owner), stored(o.stored) +{ + if (owner) owner->incRef(); +} + +template +template +Ptr::Ptr(const Ptr& o, T* p) : owner(o.owner), stored(p) +{ + if (owner) owner->incRef(); +} + +template +Ptr::~Ptr() +{ + release(); +} + +template +Ptr& Ptr::operator = (const Ptr& o) +{ + Ptr(o).swap(*this); + return *this; +} + +template +template +Ptr& Ptr::operator = (const Ptr& o) +{ + Ptr(o).swap(*this); + return *this; +} + +template +void Ptr::release() +{ + if (owner) owner->decRef(); + owner = NULL; + stored = NULL; +} + +template +template +void Ptr::reset(Y* p) +{ + Ptr(p).swap(*this); +} + +template +template +void Ptr::reset(Y* p, D d) +{ + Ptr(p, d).swap(*this); +} + +template +void Ptr::swap(Ptr& o) +{ + std::swap(owner, o.owner); + std::swap(stored, o.stored); +} + +template +T* Ptr::get() const +{ + return stored; +} + +template +typename detail::RefOrVoid::type Ptr::operator * () const +{ + return *stored; +} + +template +T* Ptr::operator -> () const +{ + return stored; +} + +template +Ptr::operator T* () const +{ + return stored; +} + + +template +bool Ptr::empty() const +{ + return !stored; +} + +template +template +Ptr Ptr::staticCast() const +{ + return Ptr(*this, static_cast(stored)); +} + +template +template +Ptr Ptr::constCast() const +{ + return Ptr(*this, const_cast(stored)); +} + +template +template +Ptr Ptr::dynamicCast() const +{ + return Ptr(*this, dynamic_cast(stored)); +} + +#ifdef CV_CXX_MOVE_SEMANTICS + +template +Ptr::Ptr(Ptr&& o) : owner(o.owner), stored(o.stored) +{ + o.owner = NULL; + o.stored = NULL; +} + +template +Ptr& Ptr::operator = (Ptr&& o) +{ + if (this == &o) + return *this; + + release(); + owner = o.owner; + stored = o.stored; + o.owner = NULL; + o.stored = NULL; + return *this; +} + +#endif + + +template +void swap(Ptr& ptr1, Ptr& ptr2){ + ptr1.swap(ptr2); +} + +template +bool operator == (const Ptr& ptr1, const Ptr& ptr2) +{ + return ptr1.get() == ptr2.get(); +} + +template +bool operator != (const Ptr& ptr1, const Ptr& ptr2) +{ + return ptr1.get() != ptr2.get(); +} + +template +Ptr makePtr() +{ + return Ptr(new T()); +} + +template +Ptr makePtr(const A1& a1) +{ + return Ptr(new T(a1)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2) +{ + return Ptr(new T(a1, a2)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3) +{ + return Ptr(new T(a1, a2, a3)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4) +{ + return Ptr(new T(a1, a2, a3, a4)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5) +{ + return Ptr(new T(a1, a2, a3, a4, a5)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7, a8)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7, a8, a9)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9, const A10& a10) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7, a8, a9, a10)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9, const A10& a10, const A11& a11) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11)); +} + +template +Ptr makePtr(const A1& a1, const A2& a2, const A3& a3, const A4& a4, const A5& a5, const A6& a6, const A7& a7, const A8& a8, const A9& a9, const A10& a10, const A11& a11, const A12& a12) +{ + return Ptr(new T(a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11, a12)); +} +} // namespace cv + +//! @endcond + +#endif // OPENCV_CORE_PTR_INL_HPP diff --git a/3rdparty/opencv/include/opencv2/core/saturate.hpp b/3rdparty/opencv/include/opencv2/core/saturate.hpp new file mode 100644 index 00000000..118599f8 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/saturate.hpp @@ -0,0 +1,165 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2014, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_SATURATE_HPP +#define OPENCV_CORE_SATURATE_HPP + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/fast_math.hpp" + +namespace cv +{ + +//! @addtogroup core_utils +//! @{ + +/////////////// saturate_cast (used in image & signal processing) /////////////////// + +/** @brief Template function for accurate conversion from one primitive type to another. + + The function saturate_cast resembles the standard C++ cast operations, such as static_cast\() + and others. It perform an efficient and accurate conversion from one primitive type to another + (see the introduction chapter). saturate in the name means that when the input value v is out of the + range of the target type, the result is not formed just by taking low bits of the input, but instead + the value is clipped. For example: + @code + uchar a = saturate_cast(-100); // a = 0 (UCHAR_MIN) + short b = saturate_cast(33333.33333); // b = 32767 (SHRT_MAX) + @endcode + Such clipping is done when the target type is unsigned char , signed char , unsigned short or + signed short . For 32-bit integers, no clipping is done. + + When the parameter is a floating-point value and the target type is an integer (8-, 16- or 32-bit), + the floating-point value is first rounded to the nearest integer and then clipped if needed (when + the target type is 8- or 16-bit). + + This operation is used in the simplest or most complex image processing functions in OpenCV. + + @param v Function parameter. + @sa add, subtract, multiply, divide, Mat::convertTo + */ +template static inline _Tp saturate_cast(uchar v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(schar v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(ushort v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(short v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(unsigned v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(int v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(float v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(double v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(int64 v) { return _Tp(v); } +/** @overload */ +template static inline _Tp saturate_cast(uint64 v) { return _Tp(v); } + +template<> inline uchar saturate_cast(schar v) { return (uchar)std::max((int)v, 0); } +template<> inline uchar saturate_cast(ushort v) { return (uchar)std::min((unsigned)v, (unsigned)UCHAR_MAX); } +template<> inline uchar saturate_cast(int v) { return (uchar)((unsigned)v <= UCHAR_MAX ? v : v > 0 ? UCHAR_MAX : 0); } +template<> inline uchar saturate_cast(short v) { return saturate_cast((int)v); } +template<> inline uchar saturate_cast(unsigned v) { return (uchar)std::min(v, (unsigned)UCHAR_MAX); } +template<> inline uchar saturate_cast(float v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline uchar saturate_cast(double v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline uchar saturate_cast(int64 v) { return (uchar)((uint64)v <= (uint64)UCHAR_MAX ? v : v > 0 ? UCHAR_MAX : 0); } +template<> inline uchar saturate_cast(uint64 v) { return (uchar)std::min(v, (uint64)UCHAR_MAX); } + +template<> inline schar saturate_cast(uchar v) { return (schar)std::min((int)v, SCHAR_MAX); } +template<> inline schar saturate_cast(ushort v) { return (schar)std::min((unsigned)v, (unsigned)SCHAR_MAX); } +template<> inline schar saturate_cast(int v) { return (schar)((unsigned)(v-SCHAR_MIN) <= (unsigned)UCHAR_MAX ? v : v > 0 ? SCHAR_MAX : SCHAR_MIN); } +template<> inline schar saturate_cast(short v) { return saturate_cast((int)v); } +template<> inline schar saturate_cast(unsigned v) { return (schar)std::min(v, (unsigned)SCHAR_MAX); } +template<> inline schar saturate_cast(float v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline schar saturate_cast(double v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline schar saturate_cast(int64 v) { return (schar)((uint64)((int64)v-SCHAR_MIN) <= (uint64)UCHAR_MAX ? v : v > 0 ? SCHAR_MAX : SCHAR_MIN); } +template<> inline schar saturate_cast(uint64 v) { return (schar)std::min(v, (uint64)SCHAR_MAX); } + +template<> inline ushort saturate_cast(schar v) { return (ushort)std::max((int)v, 0); } +template<> inline ushort saturate_cast(short v) { return (ushort)std::max((int)v, 0); } +template<> inline ushort saturate_cast(int v) { return (ushort)((unsigned)v <= (unsigned)USHRT_MAX ? v : v > 0 ? USHRT_MAX : 0); } +template<> inline ushort saturate_cast(unsigned v) { return (ushort)std::min(v, (unsigned)USHRT_MAX); } +template<> inline ushort saturate_cast(float v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline ushort saturate_cast(double v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline ushort saturate_cast(int64 v) { return (ushort)((uint64)v <= (uint64)USHRT_MAX ? v : v > 0 ? USHRT_MAX : 0); } +template<> inline ushort saturate_cast(uint64 v) { return (ushort)std::min(v, (uint64)USHRT_MAX); } + +template<> inline short saturate_cast(ushort v) { return (short)std::min((int)v, SHRT_MAX); } +template<> inline short saturate_cast(int v) { return (short)((unsigned)(v - SHRT_MIN) <= (unsigned)USHRT_MAX ? v : v > 0 ? SHRT_MAX : SHRT_MIN); } +template<> inline short saturate_cast(unsigned v) { return (short)std::min(v, (unsigned)SHRT_MAX); } +template<> inline short saturate_cast(float v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline short saturate_cast(double v) { int iv = cvRound(v); return saturate_cast(iv); } +template<> inline short saturate_cast(int64 v) { return (short)((uint64)((int64)v - SHRT_MIN) <= (uint64)USHRT_MAX ? v : v > 0 ? SHRT_MAX : SHRT_MIN); } +template<> inline short saturate_cast(uint64 v) { return (short)std::min(v, (uint64)SHRT_MAX); } + +template<> inline int saturate_cast(unsigned v) { return (int)std::min(v, (unsigned)INT_MAX); } +template<> inline int saturate_cast(int64 v) { return (int)((uint64)(v - INT_MIN) <= (uint64)UINT_MAX ? v : v > 0 ? INT_MAX : INT_MIN); } +template<> inline int saturate_cast(uint64 v) { return (int)std::min(v, (uint64)INT_MAX); } +template<> inline int saturate_cast(float v) { return cvRound(v); } +template<> inline int saturate_cast(double v) { return cvRound(v); } + +template<> inline unsigned saturate_cast(schar v) { return (unsigned)std::max(v, (schar)0); } +template<> inline unsigned saturate_cast(short v) { return (unsigned)std::max(v, (short)0); } +template<> inline unsigned saturate_cast(int v) { return (unsigned)std::max(v, (int)0); } +template<> inline unsigned saturate_cast(int64 v) { return (unsigned)((uint64)v <= (uint64)UINT_MAX ? v : v > 0 ? UINT_MAX : 0); } +template<> inline unsigned saturate_cast(uint64 v) { return (unsigned)std::min(v, (uint64)UINT_MAX); } +// we intentionally do not clip negative numbers, to make -1 become 0xffffffff etc. +template<> inline unsigned saturate_cast(float v) { return static_cast(cvRound(v)); } +template<> inline unsigned saturate_cast(double v) { return static_cast(cvRound(v)); } + +template<> inline uint64 saturate_cast(schar v) { return (uint64)std::max(v, (schar)0); } +template<> inline uint64 saturate_cast(short v) { return (uint64)std::max(v, (short)0); } +template<> inline uint64 saturate_cast(int v) { return (uint64)std::max(v, (int)0); } +template<> inline uint64 saturate_cast(int64 v) { return (uint64)std::max(v, (int64)0); } + +template<> inline int64 saturate_cast(uint64 v) { return (int64)std::min(v, (uint64)LLONG_MAX); } + +//! @} + +} // cv + +#endif // OPENCV_CORE_SATURATE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/softfloat.hpp b/3rdparty/opencv/include/opencv2/core/softfloat.hpp new file mode 100644 index 00000000..54709803 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/softfloat.hpp @@ -0,0 +1,514 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +// This file is based on files from package issued with the following license: + +/*============================================================================ + +This C header file is part of the SoftFloat IEEE Floating-Point Arithmetic +Package, Release 3c, by John R. Hauser. + +Copyright 2011, 2012, 2013, 2014, 2015, 2016, 2017 The Regents of the +University of California. All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + + 1. Redistributions of source code must retain the above copyright notice, + this list of conditions, and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions, and the following disclaimer in the documentation + and/or other materials provided with the distribution. + + 3. Neither the name of the University nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS "AS IS", AND ANY +EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, ARE +DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY +DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +=============================================================================*/ + +#pragma once +#ifndef softfloat_h +#define softfloat_h 1 + +#include "cvdef.h" + +namespace cv +{ + +/** @addtogroup core_utils_softfloat + + [SoftFloat](http://www.jhauser.us/arithmetic/SoftFloat.html) is a software implementation + of floating-point calculations according to IEEE 754 standard. + All calculations are done in integers, that's why they are machine-independent and bit-exact. + This library can be useful in accuracy-critical parts like look-up tables generation, tests, etc. + OpenCV contains a subset of SoftFloat partially rewritten to C++. + + ### Types + + There are two basic types: @ref softfloat and @ref softdouble. + These types are binary compatible with float and double types respectively + and support conversions to/from them. + Other types from original SoftFloat library like fp16 or fp128 were thrown away + as well as quiet/signaling NaN support, on-the-fly rounding mode switch + and exception flags (though exceptions can be implemented in the future). + + ### Operations + + Both types support the following: + - Construction from signed and unsigned 32-bit and 64 integers, + float/double or raw binary representation + - Conversions between each other, to float or double and to int + using @ref cvRound, @ref cvTrunc, @ref cvFloor, @ref cvCeil or a bunch of + saturate_cast functions + - Add, subtract, multiply, divide, remainder, square root, FMA with absolute precision + - Comparison operations + - Explicit sign, exponent and significand manipulation through get/set methods, + number state indicators (isInf, isNan, isSubnormal) + - Type-specific constants like eps, minimum/maximum value, best pi approximation, etc. + - min(), max(), abs(), exp(), log() and pow() functions + +*/ +//! @{ + +struct softfloat; +struct softdouble; + +struct CV_EXPORTS softfloat +{ +public: + /** @brief Default constructor */ + softfloat() { v = 0; } + /** @brief Copy constructor */ + softfloat( const softfloat& c) { v = c.v; } + /** @brief Assign constructor */ + softfloat& operator=( const softfloat& c ) + { + if(&c != this) v = c.v; + return *this; + } + /** @brief Construct from raw + + Builds new value from raw binary representation + */ + static const softfloat fromRaw( const uint32_t a ) { softfloat x; x.v = a; return x; } + + /** @brief Construct from integer */ + explicit softfloat( const uint32_t ); + explicit softfloat( const uint64_t ); + explicit softfloat( const int32_t ); + explicit softfloat( const int64_t ); + +#ifdef CV_INT32_T_IS_LONG_INT + // for platforms with int32_t = long int + explicit softfloat( const int a ) { *this = softfloat(static_cast(a)); } +#endif + + /** @brief Construct from float */ + explicit softfloat( const float a ) { Cv32suf s; s.f = a; v = s.u; } + + /** @brief Type casts */ + operator softdouble() const; + operator float() const { Cv32suf s; s.u = v; return s.f; } + + /** @brief Basic arithmetics */ + softfloat operator + (const softfloat&) const; + softfloat operator - (const softfloat&) const; + softfloat operator * (const softfloat&) const; + softfloat operator / (const softfloat&) const; + softfloat operator - () const { softfloat x; x.v = v ^ (1U << 31); return x; } + + /** @brief Remainder operator + + A quote from original SoftFloat manual: + + > The IEEE Standard remainder operation computes the value + > a - n * b, where n is the integer closest to a / b. + > If a / b is exactly halfway between two integers, n is the even integer + > closest to a / b. The IEEE Standard’s remainder operation is always exact and so requires no rounding. + > Depending on the relative magnitudes of the operands, the remainder functions + > can take considerably longer to execute than the other SoftFloat functions. + > This is an inherent characteristic of the remainder operation itself and is not a flaw + > in the SoftFloat implementation. + */ + softfloat operator % (const softfloat&) const; + + softfloat& operator += (const softfloat& a) { *this = *this + a; return *this; } + softfloat& operator -= (const softfloat& a) { *this = *this - a; return *this; } + softfloat& operator *= (const softfloat& a) { *this = *this * a; return *this; } + softfloat& operator /= (const softfloat& a) { *this = *this / a; return *this; } + softfloat& operator %= (const softfloat& a) { *this = *this % a; return *this; } + + /** @brief Comparison operations + + - Any operation with NaN produces false + + The only exception is when x is NaN: x != y for any y. + - Positive and negative zeros are equal + */ + bool operator == ( const softfloat& ) const; + bool operator != ( const softfloat& ) const; + bool operator > ( const softfloat& ) const; + bool operator >= ( const softfloat& ) const; + bool operator < ( const softfloat& ) const; + bool operator <= ( const softfloat& ) const; + + /** @brief NaN state indicator */ + inline bool isNaN() const { return (v & 0x7fffffff) > 0x7f800000; } + /** @brief Inf state indicator */ + inline bool isInf() const { return (v & 0x7fffffff) == 0x7f800000; } + /** @brief Subnormal number indicator */ + inline bool isSubnormal() const { return ((v >> 23) & 0xFF) == 0; } + + /** @brief Get sign bit */ + inline bool getSign() const { return (v >> 31) != 0; } + /** @brief Construct a copy with new sign bit */ + inline softfloat setSign(bool sign) const { softfloat x; x.v = (v & ((1U << 31) - 1)) | ((uint32_t)sign << 31); return x; } + /** @brief Get 0-based exponent */ + inline int getExp() const { return ((v >> 23) & 0xFF) - 127; } + /** @brief Construct a copy with new 0-based exponent */ + inline softfloat setExp(int e) const { softfloat x; x.v = (v & 0x807fffff) | (((e + 127) & 0xFF) << 23 ); return x; } + + /** @brief Get a fraction part + + Returns a number 1 <= x < 2 with the same significand + */ + inline softfloat getFrac() const + { + uint_fast32_t vv = (v & 0x007fffff) | (127 << 23); + return softfloat::fromRaw(vv); + } + /** @brief Construct a copy with provided significand + + Constructs a copy of a number with significand taken from parameter + */ + inline softfloat setFrac(const softfloat& s) const + { + softfloat x; + x.v = (v & 0xff800000) | (s.v & 0x007fffff); + return x; + } + + /** @brief Zero constant */ + static softfloat zero() { return softfloat::fromRaw( 0 ); } + /** @brief Positive infinity constant */ + static softfloat inf() { return softfloat::fromRaw( 0xFF << 23 ); } + /** @brief Default NaN constant */ + static softfloat nan() { return softfloat::fromRaw( 0x7fffffff ); } + /** @brief One constant */ + static softfloat one() { return softfloat::fromRaw( 127 << 23 ); } + /** @brief Smallest normalized value */ + static softfloat min() { return softfloat::fromRaw( 0x01 << 23 ); } + /** @brief Difference between 1 and next representable value */ + static softfloat eps() { return softfloat::fromRaw( (127 - 23) << 23 ); } + /** @brief Biggest finite value */ + static softfloat max() { return softfloat::fromRaw( (0xFF << 23) - 1 ); } + /** @brief Correct pi approximation */ + static softfloat pi() { return softfloat::fromRaw( 0x40490fdb ); } + + uint32_t v; +}; + +/*---------------------------------------------------------------------------- +*----------------------------------------------------------------------------*/ + +struct CV_EXPORTS softdouble +{ +public: + /** @brief Default constructor */ + softdouble() : v(0) { } + /** @brief Copy constructor */ + softdouble( const softdouble& c) { v = c.v; } + /** @brief Assign constructor */ + softdouble& operator=( const softdouble& c ) + { + if(&c != this) v = c.v; + return *this; + } + /** @brief Construct from raw + + Builds new value from raw binary representation + */ + static softdouble fromRaw( const uint64_t a ) { softdouble x; x.v = a; return x; } + + /** @brief Construct from integer */ + explicit softdouble( const uint32_t ); + explicit softdouble( const uint64_t ); + explicit softdouble( const int32_t ); + explicit softdouble( const int64_t ); + +#ifdef CV_INT32_T_IS_LONG_INT + // for platforms with int32_t = long int + explicit softdouble( const int a ) { *this = softdouble(static_cast(a)); } +#endif + + /** @brief Construct from double */ + explicit softdouble( const double a ) { Cv64suf s; s.f = a; v = s.u; } + + /** @brief Type casts */ + operator softfloat() const; + operator double() const { Cv64suf s; s.u = v; return s.f; } + + /** @brief Basic arithmetics */ + softdouble operator + (const softdouble&) const; + softdouble operator - (const softdouble&) const; + softdouble operator * (const softdouble&) const; + softdouble operator / (const softdouble&) const; + softdouble operator - () const { softdouble x; x.v = v ^ (1ULL << 63); return x; } + + /** @brief Remainder operator + + A quote from original SoftFloat manual: + + > The IEEE Standard remainder operation computes the value + > a - n * b, where n is the integer closest to a / b. + > If a / b is exactly halfway between two integers, n is the even integer + > closest to a / b. The IEEE Standard’s remainder operation is always exact and so requires no rounding. + > Depending on the relative magnitudes of the operands, the remainder functions + > can take considerably longer to execute than the other SoftFloat functions. + > This is an inherent characteristic of the remainder operation itself and is not a flaw + > in the SoftFloat implementation. + */ + softdouble operator % (const softdouble&) const; + + softdouble& operator += (const softdouble& a) { *this = *this + a; return *this; } + softdouble& operator -= (const softdouble& a) { *this = *this - a; return *this; } + softdouble& operator *= (const softdouble& a) { *this = *this * a; return *this; } + softdouble& operator /= (const softdouble& a) { *this = *this / a; return *this; } + softdouble& operator %= (const softdouble& a) { *this = *this % a; return *this; } + + /** @brief Comparison operations + + - Any operation with NaN produces false + + The only exception is when x is NaN: x != y for any y. + - Positive and negative zeros are equal + */ + bool operator == ( const softdouble& ) const; + bool operator != ( const softdouble& ) const; + bool operator > ( const softdouble& ) const; + bool operator >= ( const softdouble& ) const; + bool operator < ( const softdouble& ) const; + bool operator <= ( const softdouble& ) const; + + /** @brief NaN state indicator */ + inline bool isNaN() const { return (v & 0x7fffffffffffffff) > 0x7ff0000000000000; } + /** @brief Inf state indicator */ + inline bool isInf() const { return (v & 0x7fffffffffffffff) == 0x7ff0000000000000; } + /** @brief Subnormal number indicator */ + inline bool isSubnormal() const { return ((v >> 52) & 0x7FF) == 0; } + + /** @brief Get sign bit */ + inline bool getSign() const { return (v >> 63) != 0; } + /** @brief Construct a copy with new sign bit */ + softdouble setSign(bool sign) const { softdouble x; x.v = (v & ((1ULL << 63) - 1)) | ((uint_fast64_t)(sign) << 63); return x; } + /** @brief Get 0-based exponent */ + inline int getExp() const { return ((v >> 52) & 0x7FF) - 1023; } + /** @brief Construct a copy with new 0-based exponent */ + inline softdouble setExp(int e) const + { + softdouble x; + x.v = (v & 0x800FFFFFFFFFFFFF) | ((uint_fast64_t)((e + 1023) & 0x7FF) << 52); + return x; + } + + /** @brief Get a fraction part + + Returns a number 1 <= x < 2 with the same significand + */ + inline softdouble getFrac() const + { + uint_fast64_t vv = (v & 0x000FFFFFFFFFFFFF) | ((uint_fast64_t)(1023) << 52); + return softdouble::fromRaw(vv); + } + /** @brief Construct a copy with provided significand + + Constructs a copy of a number with significand taken from parameter + */ + inline softdouble setFrac(const softdouble& s) const + { + softdouble x; + x.v = (v & 0xFFF0000000000000) | (s.v & 0x000FFFFFFFFFFFFF); + return x; + } + + /** @brief Zero constant */ + static softdouble zero() { return softdouble::fromRaw( 0 ); } + /** @brief Positive infinity constant */ + static softdouble inf() { return softdouble::fromRaw( (uint_fast64_t)(0x7FF) << 52 ); } + /** @brief Default NaN constant */ + static softdouble nan() { return softdouble::fromRaw( CV_BIG_INT(0x7FFFFFFFFFFFFFFF) ); } + /** @brief One constant */ + static softdouble one() { return softdouble::fromRaw( (uint_fast64_t)( 1023) << 52 ); } + /** @brief Smallest normalized value */ + static softdouble min() { return softdouble::fromRaw( (uint_fast64_t)( 0x01) << 52 ); } + /** @brief Difference between 1 and next representable value */ + static softdouble eps() { return softdouble::fromRaw( (uint_fast64_t)( 1023 - 52 ) << 52 ); } + /** @brief Biggest finite value */ + static softdouble max() { return softdouble::fromRaw( ((uint_fast64_t)(0x7FF) << 52) - 1 ); } + /** @brief Correct pi approximation */ + static softdouble pi() { return softdouble::fromRaw( CV_BIG_INT(0x400921FB54442D18) ); } + + uint64_t v; +}; + +/*---------------------------------------------------------------------------- +*----------------------------------------------------------------------------*/ + +/** @brief Fused Multiplication and Addition + +Computes (a*b)+c with single rounding +*/ +CV_EXPORTS softfloat mulAdd( const softfloat& a, const softfloat& b, const softfloat & c); +CV_EXPORTS softdouble mulAdd( const softdouble& a, const softdouble& b, const softdouble& c); + +/** @brief Square root */ +CV_EXPORTS softfloat sqrt( const softfloat& a ); +CV_EXPORTS softdouble sqrt( const softdouble& a ); +} + +/*---------------------------------------------------------------------------- +| Ported from OpenCV and added for usability +*----------------------------------------------------------------------------*/ + +/** @brief Truncates number to integer with minimum magnitude */ +CV_EXPORTS int cvTrunc(const cv::softfloat& a); +CV_EXPORTS int cvTrunc(const cv::softdouble& a); + +/** @brief Rounds a number to nearest even integer */ +CV_EXPORTS int cvRound(const cv::softfloat& a); +CV_EXPORTS int cvRound(const cv::softdouble& a); + +/** @brief Rounds a number to nearest even long long integer */ +CV_EXPORTS int64_t cvRound64(const cv::softdouble& a); + +/** @brief Rounds a number down to integer */ +CV_EXPORTS int cvFloor(const cv::softfloat& a); +CV_EXPORTS int cvFloor(const cv::softdouble& a); + +/** @brief Rounds number up to integer */ +CV_EXPORTS int cvCeil(const cv::softfloat& a); +CV_EXPORTS int cvCeil(const cv::softdouble& a); + +namespace cv +{ +/** @brief Saturate casts */ +template static inline _Tp saturate_cast(softfloat a) { return _Tp(a); } +template static inline _Tp saturate_cast(softdouble a) { return _Tp(a); } + +template<> inline uchar saturate_cast(softfloat a) { return (uchar)std::max(std::min(cvRound(a), (int)UCHAR_MAX), 0); } +template<> inline uchar saturate_cast(softdouble a) { return (uchar)std::max(std::min(cvRound(a), (int)UCHAR_MAX), 0); } + +template<> inline schar saturate_cast(softfloat a) { return (schar)std::min(std::max(cvRound(a), (int)SCHAR_MIN), (int)SCHAR_MAX); } +template<> inline schar saturate_cast(softdouble a) { return (schar)std::min(std::max(cvRound(a), (int)SCHAR_MIN), (int)SCHAR_MAX); } + +template<> inline ushort saturate_cast(softfloat a) { return (ushort)std::max(std::min(cvRound(a), (int)USHRT_MAX), 0); } +template<> inline ushort saturate_cast(softdouble a) { return (ushort)std::max(std::min(cvRound(a), (int)USHRT_MAX), 0); } + +template<> inline short saturate_cast(softfloat a) { return (short)std::min(std::max(cvRound(a), (int)SHRT_MIN), (int)SHRT_MAX); } +template<> inline short saturate_cast(softdouble a) { return (short)std::min(std::max(cvRound(a), (int)SHRT_MIN), (int)SHRT_MAX); } + +template<> inline int saturate_cast(softfloat a) { return cvRound(a); } +template<> inline int saturate_cast(softdouble a) { return cvRound(a); } + +template<> inline int64_t saturate_cast(softfloat a) { return cvRound(a); } +template<> inline int64_t saturate_cast(softdouble a) { return cvRound64(a); } + +/** @brief Saturate cast to unsigned integer and unsigned long long integer +We intentionally do not clip negative numbers, to make -1 become 0xffffffff etc. +*/ +template<> inline unsigned saturate_cast(softfloat a) { return cvRound(a); } +template<> inline unsigned saturate_cast(softdouble a) { return cvRound(a); } + +template<> inline uint64_t saturate_cast(softfloat a) { return cvRound(a); } +template<> inline uint64_t saturate_cast(softdouble a) { return cvRound64(a); } + +/** @brief Min and Max functions */ +inline softfloat min(const softfloat& a, const softfloat& b) { return (a > b) ? b : a; } +inline softdouble min(const softdouble& a, const softdouble& b) { return (a > b) ? b : a; } + +inline softfloat max(const softfloat& a, const softfloat& b) { return (a > b) ? a : b; } +inline softdouble max(const softdouble& a, const softdouble& b) { return (a > b) ? a : b; } + +/** @brief Absolute value */ +inline softfloat abs( softfloat a) { softfloat x; x.v = a.v & ((1U << 31) - 1); return x; } +inline softdouble abs( softdouble a) { softdouble x; x.v = a.v & ((1ULL << 63) - 1); return x; } + +/** @brief Exponent + +Special cases: +- exp(NaN) is NaN +- exp(-Inf) == 0 +- exp(+Inf) == +Inf +*/ +CV_EXPORTS softfloat exp( const softfloat& a); +CV_EXPORTS softdouble exp( const softdouble& a); + +/** @brief Natural logarithm + +Special cases: +- log(NaN), log(x < 0) are NaN +- log(0) == -Inf +*/ +CV_EXPORTS softfloat log( const softfloat& a ); +CV_EXPORTS softdouble log( const softdouble& a ); + +/** @brief Raising to the power + +Special cases: +- x**NaN is NaN for any x +- ( |x| == 1 )**Inf is NaN +- ( |x| > 1 )**+Inf or ( |x| < 1 )**-Inf is +Inf +- ( |x| > 1 )**-Inf or ( |x| < 1 )**+Inf is 0 +- x ** 0 == 1 for any x +- x ** 1 == 1 for any x +- NaN ** y is NaN for any other y +- Inf**(y < 0) == 0 +- Inf ** y is +Inf for any other y +- (x < 0)**y is NaN for any other y if x can't be correctly rounded to integer +- 0 ** 0 == 1 +- 0 ** (y < 0) is +Inf +- 0 ** (y > 0) is 0 +*/ +CV_EXPORTS softfloat pow( const softfloat& a, const softfloat& b); +CV_EXPORTS softdouble pow( const softdouble& a, const softdouble& b); + +/** @brief Cube root + +Special cases: +- cbrt(NaN) is NaN +- cbrt(+/-Inf) is +/-Inf +*/ +CV_EXPORTS softfloat cbrt( const softfloat& a ); + +/** @brief Sine + +Special cases: +- sin(Inf) or sin(NaN) is NaN +- sin(x) == x when sin(x) is close to zero +*/ +CV_EXPORTS softdouble sin( const softdouble& a ); + +/** @brief Cosine + * +Special cases: +- cos(Inf) or cos(NaN) is NaN +- cos(x) == +/- 1 when cos(x) is close to +/- 1 +*/ +CV_EXPORTS softdouble cos( const softdouble& a ); + +} + +//! @} + +#endif diff --git a/3rdparty/opencv/include/opencv2/core/sse_utils.hpp b/3rdparty/opencv/include/opencv2/core/sse_utils.hpp new file mode 100644 index 00000000..0906583e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/sse_utils.hpp @@ -0,0 +1,652 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_SSE_UTILS_HPP +#define OPENCV_CORE_SSE_UTILS_HPP + +#ifndef __cplusplus +# error sse_utils.hpp header must be compiled as C++ +#endif + +#include "opencv2/core/cvdef.h" + +//! @addtogroup core_utils_sse +//! @{ + +#if CV_SSE2 + +inline void _mm_deinterleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi8(v_r0, v_g0); + __m128i layer1_chunk1 = _mm_unpackhi_epi8(v_r0, v_g0); + __m128i layer1_chunk2 = _mm_unpacklo_epi8(v_r1, v_g1); + __m128i layer1_chunk3 = _mm_unpackhi_epi8(v_r1, v_g1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi8(layer1_chunk0, layer1_chunk2); + __m128i layer2_chunk1 = _mm_unpackhi_epi8(layer1_chunk0, layer1_chunk2); + __m128i layer2_chunk2 = _mm_unpacklo_epi8(layer1_chunk1, layer1_chunk3); + __m128i layer2_chunk3 = _mm_unpackhi_epi8(layer1_chunk1, layer1_chunk3); + + __m128i layer3_chunk0 = _mm_unpacklo_epi8(layer2_chunk0, layer2_chunk2); + __m128i layer3_chunk1 = _mm_unpackhi_epi8(layer2_chunk0, layer2_chunk2); + __m128i layer3_chunk2 = _mm_unpacklo_epi8(layer2_chunk1, layer2_chunk3); + __m128i layer3_chunk3 = _mm_unpackhi_epi8(layer2_chunk1, layer2_chunk3); + + __m128i layer4_chunk0 = _mm_unpacklo_epi8(layer3_chunk0, layer3_chunk2); + __m128i layer4_chunk1 = _mm_unpackhi_epi8(layer3_chunk0, layer3_chunk2); + __m128i layer4_chunk2 = _mm_unpacklo_epi8(layer3_chunk1, layer3_chunk3); + __m128i layer4_chunk3 = _mm_unpackhi_epi8(layer3_chunk1, layer3_chunk3); + + v_r0 = _mm_unpacklo_epi8(layer4_chunk0, layer4_chunk2); + v_r1 = _mm_unpackhi_epi8(layer4_chunk0, layer4_chunk2); + v_g0 = _mm_unpacklo_epi8(layer4_chunk1, layer4_chunk3); + v_g1 = _mm_unpackhi_epi8(layer4_chunk1, layer4_chunk3); +} + +inline void _mm_deinterleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, + __m128i & v_g1, __m128i & v_b0, __m128i & v_b1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi8(v_r0, v_g1); + __m128i layer1_chunk1 = _mm_unpackhi_epi8(v_r0, v_g1); + __m128i layer1_chunk2 = _mm_unpacklo_epi8(v_r1, v_b0); + __m128i layer1_chunk3 = _mm_unpackhi_epi8(v_r1, v_b0); + __m128i layer1_chunk4 = _mm_unpacklo_epi8(v_g0, v_b1); + __m128i layer1_chunk5 = _mm_unpackhi_epi8(v_g0, v_b1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi8(layer1_chunk0, layer1_chunk3); + __m128i layer2_chunk1 = _mm_unpackhi_epi8(layer1_chunk0, layer1_chunk3); + __m128i layer2_chunk2 = _mm_unpacklo_epi8(layer1_chunk1, layer1_chunk4); + __m128i layer2_chunk3 = _mm_unpackhi_epi8(layer1_chunk1, layer1_chunk4); + __m128i layer2_chunk4 = _mm_unpacklo_epi8(layer1_chunk2, layer1_chunk5); + __m128i layer2_chunk5 = _mm_unpackhi_epi8(layer1_chunk2, layer1_chunk5); + + __m128i layer3_chunk0 = _mm_unpacklo_epi8(layer2_chunk0, layer2_chunk3); + __m128i layer3_chunk1 = _mm_unpackhi_epi8(layer2_chunk0, layer2_chunk3); + __m128i layer3_chunk2 = _mm_unpacklo_epi8(layer2_chunk1, layer2_chunk4); + __m128i layer3_chunk3 = _mm_unpackhi_epi8(layer2_chunk1, layer2_chunk4); + __m128i layer3_chunk4 = _mm_unpacklo_epi8(layer2_chunk2, layer2_chunk5); + __m128i layer3_chunk5 = _mm_unpackhi_epi8(layer2_chunk2, layer2_chunk5); + + __m128i layer4_chunk0 = _mm_unpacklo_epi8(layer3_chunk0, layer3_chunk3); + __m128i layer4_chunk1 = _mm_unpackhi_epi8(layer3_chunk0, layer3_chunk3); + __m128i layer4_chunk2 = _mm_unpacklo_epi8(layer3_chunk1, layer3_chunk4); + __m128i layer4_chunk3 = _mm_unpackhi_epi8(layer3_chunk1, layer3_chunk4); + __m128i layer4_chunk4 = _mm_unpacklo_epi8(layer3_chunk2, layer3_chunk5); + __m128i layer4_chunk5 = _mm_unpackhi_epi8(layer3_chunk2, layer3_chunk5); + + v_r0 = _mm_unpacklo_epi8(layer4_chunk0, layer4_chunk3); + v_r1 = _mm_unpackhi_epi8(layer4_chunk0, layer4_chunk3); + v_g0 = _mm_unpacklo_epi8(layer4_chunk1, layer4_chunk4); + v_g1 = _mm_unpackhi_epi8(layer4_chunk1, layer4_chunk4); + v_b0 = _mm_unpacklo_epi8(layer4_chunk2, layer4_chunk5); + v_b1 = _mm_unpackhi_epi8(layer4_chunk2, layer4_chunk5); +} + +inline void _mm_deinterleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1, + __m128i & v_b0, __m128i & v_b1, __m128i & v_a0, __m128i & v_a1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi8(v_r0, v_b0); + __m128i layer1_chunk1 = _mm_unpackhi_epi8(v_r0, v_b0); + __m128i layer1_chunk2 = _mm_unpacklo_epi8(v_r1, v_b1); + __m128i layer1_chunk3 = _mm_unpackhi_epi8(v_r1, v_b1); + __m128i layer1_chunk4 = _mm_unpacklo_epi8(v_g0, v_a0); + __m128i layer1_chunk5 = _mm_unpackhi_epi8(v_g0, v_a0); + __m128i layer1_chunk6 = _mm_unpacklo_epi8(v_g1, v_a1); + __m128i layer1_chunk7 = _mm_unpackhi_epi8(v_g1, v_a1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi8(layer1_chunk0, layer1_chunk4); + __m128i layer2_chunk1 = _mm_unpackhi_epi8(layer1_chunk0, layer1_chunk4); + __m128i layer2_chunk2 = _mm_unpacklo_epi8(layer1_chunk1, layer1_chunk5); + __m128i layer2_chunk3 = _mm_unpackhi_epi8(layer1_chunk1, layer1_chunk5); + __m128i layer2_chunk4 = _mm_unpacklo_epi8(layer1_chunk2, layer1_chunk6); + __m128i layer2_chunk5 = _mm_unpackhi_epi8(layer1_chunk2, layer1_chunk6); + __m128i layer2_chunk6 = _mm_unpacklo_epi8(layer1_chunk3, layer1_chunk7); + __m128i layer2_chunk7 = _mm_unpackhi_epi8(layer1_chunk3, layer1_chunk7); + + __m128i layer3_chunk0 = _mm_unpacklo_epi8(layer2_chunk0, layer2_chunk4); + __m128i layer3_chunk1 = _mm_unpackhi_epi8(layer2_chunk0, layer2_chunk4); + __m128i layer3_chunk2 = _mm_unpacklo_epi8(layer2_chunk1, layer2_chunk5); + __m128i layer3_chunk3 = _mm_unpackhi_epi8(layer2_chunk1, layer2_chunk5); + __m128i layer3_chunk4 = _mm_unpacklo_epi8(layer2_chunk2, layer2_chunk6); + __m128i layer3_chunk5 = _mm_unpackhi_epi8(layer2_chunk2, layer2_chunk6); + __m128i layer3_chunk6 = _mm_unpacklo_epi8(layer2_chunk3, layer2_chunk7); + __m128i layer3_chunk7 = _mm_unpackhi_epi8(layer2_chunk3, layer2_chunk7); + + __m128i layer4_chunk0 = _mm_unpacklo_epi8(layer3_chunk0, layer3_chunk4); + __m128i layer4_chunk1 = _mm_unpackhi_epi8(layer3_chunk0, layer3_chunk4); + __m128i layer4_chunk2 = _mm_unpacklo_epi8(layer3_chunk1, layer3_chunk5); + __m128i layer4_chunk3 = _mm_unpackhi_epi8(layer3_chunk1, layer3_chunk5); + __m128i layer4_chunk4 = _mm_unpacklo_epi8(layer3_chunk2, layer3_chunk6); + __m128i layer4_chunk5 = _mm_unpackhi_epi8(layer3_chunk2, layer3_chunk6); + __m128i layer4_chunk6 = _mm_unpacklo_epi8(layer3_chunk3, layer3_chunk7); + __m128i layer4_chunk7 = _mm_unpackhi_epi8(layer3_chunk3, layer3_chunk7); + + v_r0 = _mm_unpacklo_epi8(layer4_chunk0, layer4_chunk4); + v_r1 = _mm_unpackhi_epi8(layer4_chunk0, layer4_chunk4); + v_g0 = _mm_unpacklo_epi8(layer4_chunk1, layer4_chunk5); + v_g1 = _mm_unpackhi_epi8(layer4_chunk1, layer4_chunk5); + v_b0 = _mm_unpacklo_epi8(layer4_chunk2, layer4_chunk6); + v_b1 = _mm_unpackhi_epi8(layer4_chunk2, layer4_chunk6); + v_a0 = _mm_unpacklo_epi8(layer4_chunk3, layer4_chunk7); + v_a1 = _mm_unpackhi_epi8(layer4_chunk3, layer4_chunk7); +} + +inline void _mm_interleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1) +{ + __m128i v_mask = _mm_set1_epi16(0x00ff); + + __m128i layer4_chunk0 = _mm_packus_epi16(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer4_chunk2 = _mm_packus_epi16(_mm_srli_epi16(v_r0, 8), _mm_srli_epi16(v_r1, 8)); + __m128i layer4_chunk1 = _mm_packus_epi16(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer4_chunk3 = _mm_packus_epi16(_mm_srli_epi16(v_g0, 8), _mm_srli_epi16(v_g1, 8)); + + __m128i layer3_chunk0 = _mm_packus_epi16(_mm_and_si128(layer4_chunk0, v_mask), _mm_and_si128(layer4_chunk1, v_mask)); + __m128i layer3_chunk2 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk0, 8), _mm_srli_epi16(layer4_chunk1, 8)); + __m128i layer3_chunk1 = _mm_packus_epi16(_mm_and_si128(layer4_chunk2, v_mask), _mm_and_si128(layer4_chunk3, v_mask)); + __m128i layer3_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk2, 8), _mm_srli_epi16(layer4_chunk3, 8)); + + __m128i layer2_chunk0 = _mm_packus_epi16(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk2 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk0, 8), _mm_srli_epi16(layer3_chunk1, 8)); + __m128i layer2_chunk1 = _mm_packus_epi16(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk2, 8), _mm_srli_epi16(layer3_chunk3, 8)); + + __m128i layer1_chunk0 = _mm_packus_epi16(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk2 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk0, 8), _mm_srli_epi16(layer2_chunk1, 8)); + __m128i layer1_chunk1 = _mm_packus_epi16(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk2, 8), _mm_srli_epi16(layer2_chunk3, 8)); + + v_r0 = _mm_packus_epi16(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_g0 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk0, 8), _mm_srli_epi16(layer1_chunk1, 8)); + v_r1 = _mm_packus_epi16(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_g1 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk2, 8), _mm_srli_epi16(layer1_chunk3, 8)); +} + +inline void _mm_interleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, + __m128i & v_g1, __m128i & v_b0, __m128i & v_b1) +{ + __m128i v_mask = _mm_set1_epi16(0x00ff); + + __m128i layer4_chunk0 = _mm_packus_epi16(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer4_chunk3 = _mm_packus_epi16(_mm_srli_epi16(v_r0, 8), _mm_srli_epi16(v_r1, 8)); + __m128i layer4_chunk1 = _mm_packus_epi16(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer4_chunk4 = _mm_packus_epi16(_mm_srli_epi16(v_g0, 8), _mm_srli_epi16(v_g1, 8)); + __m128i layer4_chunk2 = _mm_packus_epi16(_mm_and_si128(v_b0, v_mask), _mm_and_si128(v_b1, v_mask)); + __m128i layer4_chunk5 = _mm_packus_epi16(_mm_srli_epi16(v_b0, 8), _mm_srli_epi16(v_b1, 8)); + + __m128i layer3_chunk0 = _mm_packus_epi16(_mm_and_si128(layer4_chunk0, v_mask), _mm_and_si128(layer4_chunk1, v_mask)); + __m128i layer3_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk0, 8), _mm_srli_epi16(layer4_chunk1, 8)); + __m128i layer3_chunk1 = _mm_packus_epi16(_mm_and_si128(layer4_chunk2, v_mask), _mm_and_si128(layer4_chunk3, v_mask)); + __m128i layer3_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk2, 8), _mm_srli_epi16(layer4_chunk3, 8)); + __m128i layer3_chunk2 = _mm_packus_epi16(_mm_and_si128(layer4_chunk4, v_mask), _mm_and_si128(layer4_chunk5, v_mask)); + __m128i layer3_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk4, 8), _mm_srli_epi16(layer4_chunk5, 8)); + + __m128i layer2_chunk0 = _mm_packus_epi16(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk0, 8), _mm_srli_epi16(layer3_chunk1, 8)); + __m128i layer2_chunk1 = _mm_packus_epi16(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk2, 8), _mm_srli_epi16(layer3_chunk3, 8)); + __m128i layer2_chunk2 = _mm_packus_epi16(_mm_and_si128(layer3_chunk4, v_mask), _mm_and_si128(layer3_chunk5, v_mask)); + __m128i layer2_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk4, 8), _mm_srli_epi16(layer3_chunk5, 8)); + + __m128i layer1_chunk0 = _mm_packus_epi16(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk3 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk0, 8), _mm_srli_epi16(layer2_chunk1, 8)); + __m128i layer1_chunk1 = _mm_packus_epi16(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk2, 8), _mm_srli_epi16(layer2_chunk3, 8)); + __m128i layer1_chunk2 = _mm_packus_epi16(_mm_and_si128(layer2_chunk4, v_mask), _mm_and_si128(layer2_chunk5, v_mask)); + __m128i layer1_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk4, 8), _mm_srli_epi16(layer2_chunk5, 8)); + + v_r0 = _mm_packus_epi16(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_g1 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk0, 8), _mm_srli_epi16(layer1_chunk1, 8)); + v_r1 = _mm_packus_epi16(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_b0 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk2, 8), _mm_srli_epi16(layer1_chunk3, 8)); + v_g0 = _mm_packus_epi16(_mm_and_si128(layer1_chunk4, v_mask), _mm_and_si128(layer1_chunk5, v_mask)); + v_b1 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk4, 8), _mm_srli_epi16(layer1_chunk5, 8)); +} + +inline void _mm_interleave_epi8(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1, + __m128i & v_b0, __m128i & v_b1, __m128i & v_a0, __m128i & v_a1) +{ + __m128i v_mask = _mm_set1_epi16(0x00ff); + + __m128i layer4_chunk0 = _mm_packus_epi16(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer4_chunk4 = _mm_packus_epi16(_mm_srli_epi16(v_r0, 8), _mm_srli_epi16(v_r1, 8)); + __m128i layer4_chunk1 = _mm_packus_epi16(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer4_chunk5 = _mm_packus_epi16(_mm_srli_epi16(v_g0, 8), _mm_srli_epi16(v_g1, 8)); + __m128i layer4_chunk2 = _mm_packus_epi16(_mm_and_si128(v_b0, v_mask), _mm_and_si128(v_b1, v_mask)); + __m128i layer4_chunk6 = _mm_packus_epi16(_mm_srli_epi16(v_b0, 8), _mm_srli_epi16(v_b1, 8)); + __m128i layer4_chunk3 = _mm_packus_epi16(_mm_and_si128(v_a0, v_mask), _mm_and_si128(v_a1, v_mask)); + __m128i layer4_chunk7 = _mm_packus_epi16(_mm_srli_epi16(v_a0, 8), _mm_srli_epi16(v_a1, 8)); + + __m128i layer3_chunk0 = _mm_packus_epi16(_mm_and_si128(layer4_chunk0, v_mask), _mm_and_si128(layer4_chunk1, v_mask)); + __m128i layer3_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk0, 8), _mm_srli_epi16(layer4_chunk1, 8)); + __m128i layer3_chunk1 = _mm_packus_epi16(_mm_and_si128(layer4_chunk2, v_mask), _mm_and_si128(layer4_chunk3, v_mask)); + __m128i layer3_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk2, 8), _mm_srli_epi16(layer4_chunk3, 8)); + __m128i layer3_chunk2 = _mm_packus_epi16(_mm_and_si128(layer4_chunk4, v_mask), _mm_and_si128(layer4_chunk5, v_mask)); + __m128i layer3_chunk6 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk4, 8), _mm_srli_epi16(layer4_chunk5, 8)); + __m128i layer3_chunk3 = _mm_packus_epi16(_mm_and_si128(layer4_chunk6, v_mask), _mm_and_si128(layer4_chunk7, v_mask)); + __m128i layer3_chunk7 = _mm_packus_epi16(_mm_srli_epi16(layer4_chunk6, 8), _mm_srli_epi16(layer4_chunk7, 8)); + + __m128i layer2_chunk0 = _mm_packus_epi16(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk0, 8), _mm_srli_epi16(layer3_chunk1, 8)); + __m128i layer2_chunk1 = _mm_packus_epi16(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk2, 8), _mm_srli_epi16(layer3_chunk3, 8)); + __m128i layer2_chunk2 = _mm_packus_epi16(_mm_and_si128(layer3_chunk4, v_mask), _mm_and_si128(layer3_chunk5, v_mask)); + __m128i layer2_chunk6 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk4, 8), _mm_srli_epi16(layer3_chunk5, 8)); + __m128i layer2_chunk3 = _mm_packus_epi16(_mm_and_si128(layer3_chunk6, v_mask), _mm_and_si128(layer3_chunk7, v_mask)); + __m128i layer2_chunk7 = _mm_packus_epi16(_mm_srli_epi16(layer3_chunk6, 8), _mm_srli_epi16(layer3_chunk7, 8)); + + __m128i layer1_chunk0 = _mm_packus_epi16(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk4 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk0, 8), _mm_srli_epi16(layer2_chunk1, 8)); + __m128i layer1_chunk1 = _mm_packus_epi16(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk5 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk2, 8), _mm_srli_epi16(layer2_chunk3, 8)); + __m128i layer1_chunk2 = _mm_packus_epi16(_mm_and_si128(layer2_chunk4, v_mask), _mm_and_si128(layer2_chunk5, v_mask)); + __m128i layer1_chunk6 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk4, 8), _mm_srli_epi16(layer2_chunk5, 8)); + __m128i layer1_chunk3 = _mm_packus_epi16(_mm_and_si128(layer2_chunk6, v_mask), _mm_and_si128(layer2_chunk7, v_mask)); + __m128i layer1_chunk7 = _mm_packus_epi16(_mm_srli_epi16(layer2_chunk6, 8), _mm_srli_epi16(layer2_chunk7, 8)); + + v_r0 = _mm_packus_epi16(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_b0 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk0, 8), _mm_srli_epi16(layer1_chunk1, 8)); + v_r1 = _mm_packus_epi16(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_b1 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk2, 8), _mm_srli_epi16(layer1_chunk3, 8)); + v_g0 = _mm_packus_epi16(_mm_and_si128(layer1_chunk4, v_mask), _mm_and_si128(layer1_chunk5, v_mask)); + v_a0 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk4, 8), _mm_srli_epi16(layer1_chunk5, 8)); + v_g1 = _mm_packus_epi16(_mm_and_si128(layer1_chunk6, v_mask), _mm_and_si128(layer1_chunk7, v_mask)); + v_a1 = _mm_packus_epi16(_mm_srli_epi16(layer1_chunk6, 8), _mm_srli_epi16(layer1_chunk7, 8)); +} + +inline void _mm_deinterleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi16(v_r0, v_g0); + __m128i layer1_chunk1 = _mm_unpackhi_epi16(v_r0, v_g0); + __m128i layer1_chunk2 = _mm_unpacklo_epi16(v_r1, v_g1); + __m128i layer1_chunk3 = _mm_unpackhi_epi16(v_r1, v_g1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi16(layer1_chunk0, layer1_chunk2); + __m128i layer2_chunk1 = _mm_unpackhi_epi16(layer1_chunk0, layer1_chunk2); + __m128i layer2_chunk2 = _mm_unpacklo_epi16(layer1_chunk1, layer1_chunk3); + __m128i layer2_chunk3 = _mm_unpackhi_epi16(layer1_chunk1, layer1_chunk3); + + __m128i layer3_chunk0 = _mm_unpacklo_epi16(layer2_chunk0, layer2_chunk2); + __m128i layer3_chunk1 = _mm_unpackhi_epi16(layer2_chunk0, layer2_chunk2); + __m128i layer3_chunk2 = _mm_unpacklo_epi16(layer2_chunk1, layer2_chunk3); + __m128i layer3_chunk3 = _mm_unpackhi_epi16(layer2_chunk1, layer2_chunk3); + + v_r0 = _mm_unpacklo_epi16(layer3_chunk0, layer3_chunk2); + v_r1 = _mm_unpackhi_epi16(layer3_chunk0, layer3_chunk2); + v_g0 = _mm_unpacklo_epi16(layer3_chunk1, layer3_chunk3); + v_g1 = _mm_unpackhi_epi16(layer3_chunk1, layer3_chunk3); +} + +inline void _mm_deinterleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, + __m128i & v_g1, __m128i & v_b0, __m128i & v_b1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi16(v_r0, v_g1); + __m128i layer1_chunk1 = _mm_unpackhi_epi16(v_r0, v_g1); + __m128i layer1_chunk2 = _mm_unpacklo_epi16(v_r1, v_b0); + __m128i layer1_chunk3 = _mm_unpackhi_epi16(v_r1, v_b0); + __m128i layer1_chunk4 = _mm_unpacklo_epi16(v_g0, v_b1); + __m128i layer1_chunk5 = _mm_unpackhi_epi16(v_g0, v_b1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi16(layer1_chunk0, layer1_chunk3); + __m128i layer2_chunk1 = _mm_unpackhi_epi16(layer1_chunk0, layer1_chunk3); + __m128i layer2_chunk2 = _mm_unpacklo_epi16(layer1_chunk1, layer1_chunk4); + __m128i layer2_chunk3 = _mm_unpackhi_epi16(layer1_chunk1, layer1_chunk4); + __m128i layer2_chunk4 = _mm_unpacklo_epi16(layer1_chunk2, layer1_chunk5); + __m128i layer2_chunk5 = _mm_unpackhi_epi16(layer1_chunk2, layer1_chunk5); + + __m128i layer3_chunk0 = _mm_unpacklo_epi16(layer2_chunk0, layer2_chunk3); + __m128i layer3_chunk1 = _mm_unpackhi_epi16(layer2_chunk0, layer2_chunk3); + __m128i layer3_chunk2 = _mm_unpacklo_epi16(layer2_chunk1, layer2_chunk4); + __m128i layer3_chunk3 = _mm_unpackhi_epi16(layer2_chunk1, layer2_chunk4); + __m128i layer3_chunk4 = _mm_unpacklo_epi16(layer2_chunk2, layer2_chunk5); + __m128i layer3_chunk5 = _mm_unpackhi_epi16(layer2_chunk2, layer2_chunk5); + + v_r0 = _mm_unpacklo_epi16(layer3_chunk0, layer3_chunk3); + v_r1 = _mm_unpackhi_epi16(layer3_chunk0, layer3_chunk3); + v_g0 = _mm_unpacklo_epi16(layer3_chunk1, layer3_chunk4); + v_g1 = _mm_unpackhi_epi16(layer3_chunk1, layer3_chunk4); + v_b0 = _mm_unpacklo_epi16(layer3_chunk2, layer3_chunk5); + v_b1 = _mm_unpackhi_epi16(layer3_chunk2, layer3_chunk5); +} + +inline void _mm_deinterleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1, + __m128i & v_b0, __m128i & v_b1, __m128i & v_a0, __m128i & v_a1) +{ + __m128i layer1_chunk0 = _mm_unpacklo_epi16(v_r0, v_b0); + __m128i layer1_chunk1 = _mm_unpackhi_epi16(v_r0, v_b0); + __m128i layer1_chunk2 = _mm_unpacklo_epi16(v_r1, v_b1); + __m128i layer1_chunk3 = _mm_unpackhi_epi16(v_r1, v_b1); + __m128i layer1_chunk4 = _mm_unpacklo_epi16(v_g0, v_a0); + __m128i layer1_chunk5 = _mm_unpackhi_epi16(v_g0, v_a0); + __m128i layer1_chunk6 = _mm_unpacklo_epi16(v_g1, v_a1); + __m128i layer1_chunk7 = _mm_unpackhi_epi16(v_g1, v_a1); + + __m128i layer2_chunk0 = _mm_unpacklo_epi16(layer1_chunk0, layer1_chunk4); + __m128i layer2_chunk1 = _mm_unpackhi_epi16(layer1_chunk0, layer1_chunk4); + __m128i layer2_chunk2 = _mm_unpacklo_epi16(layer1_chunk1, layer1_chunk5); + __m128i layer2_chunk3 = _mm_unpackhi_epi16(layer1_chunk1, layer1_chunk5); + __m128i layer2_chunk4 = _mm_unpacklo_epi16(layer1_chunk2, layer1_chunk6); + __m128i layer2_chunk5 = _mm_unpackhi_epi16(layer1_chunk2, layer1_chunk6); + __m128i layer2_chunk6 = _mm_unpacklo_epi16(layer1_chunk3, layer1_chunk7); + __m128i layer2_chunk7 = _mm_unpackhi_epi16(layer1_chunk3, layer1_chunk7); + + __m128i layer3_chunk0 = _mm_unpacklo_epi16(layer2_chunk0, layer2_chunk4); + __m128i layer3_chunk1 = _mm_unpackhi_epi16(layer2_chunk0, layer2_chunk4); + __m128i layer3_chunk2 = _mm_unpacklo_epi16(layer2_chunk1, layer2_chunk5); + __m128i layer3_chunk3 = _mm_unpackhi_epi16(layer2_chunk1, layer2_chunk5); + __m128i layer3_chunk4 = _mm_unpacklo_epi16(layer2_chunk2, layer2_chunk6); + __m128i layer3_chunk5 = _mm_unpackhi_epi16(layer2_chunk2, layer2_chunk6); + __m128i layer3_chunk6 = _mm_unpacklo_epi16(layer2_chunk3, layer2_chunk7); + __m128i layer3_chunk7 = _mm_unpackhi_epi16(layer2_chunk3, layer2_chunk7); + + v_r0 = _mm_unpacklo_epi16(layer3_chunk0, layer3_chunk4); + v_r1 = _mm_unpackhi_epi16(layer3_chunk0, layer3_chunk4); + v_g0 = _mm_unpacklo_epi16(layer3_chunk1, layer3_chunk5); + v_g1 = _mm_unpackhi_epi16(layer3_chunk1, layer3_chunk5); + v_b0 = _mm_unpacklo_epi16(layer3_chunk2, layer3_chunk6); + v_b1 = _mm_unpackhi_epi16(layer3_chunk2, layer3_chunk6); + v_a0 = _mm_unpacklo_epi16(layer3_chunk3, layer3_chunk7); + v_a1 = _mm_unpackhi_epi16(layer3_chunk3, layer3_chunk7); +} + +#if CV_SSE4_1 + +inline void _mm_interleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1) +{ + __m128i v_mask = _mm_set1_epi32(0x0000ffff); + + __m128i layer3_chunk0 = _mm_packus_epi32(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer3_chunk2 = _mm_packus_epi32(_mm_srli_epi32(v_r0, 16), _mm_srli_epi32(v_r1, 16)); + __m128i layer3_chunk1 = _mm_packus_epi32(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer3_chunk3 = _mm_packus_epi32(_mm_srli_epi32(v_g0, 16), _mm_srli_epi32(v_g1, 16)); + + __m128i layer2_chunk0 = _mm_packus_epi32(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk2 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk0, 16), _mm_srli_epi32(layer3_chunk1, 16)); + __m128i layer2_chunk1 = _mm_packus_epi32(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk3 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk2, 16), _mm_srli_epi32(layer3_chunk3, 16)); + + __m128i layer1_chunk0 = _mm_packus_epi32(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk2 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk0, 16), _mm_srli_epi32(layer2_chunk1, 16)); + __m128i layer1_chunk1 = _mm_packus_epi32(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk3 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk2, 16), _mm_srli_epi32(layer2_chunk3, 16)); + + v_r0 = _mm_packus_epi32(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_g0 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk0, 16), _mm_srli_epi32(layer1_chunk1, 16)); + v_r1 = _mm_packus_epi32(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_g1 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk2, 16), _mm_srli_epi32(layer1_chunk3, 16)); +} + +inline void _mm_interleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, + __m128i & v_g1, __m128i & v_b0, __m128i & v_b1) +{ + __m128i v_mask = _mm_set1_epi32(0x0000ffff); + + __m128i layer3_chunk0 = _mm_packus_epi32(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer3_chunk3 = _mm_packus_epi32(_mm_srli_epi32(v_r0, 16), _mm_srli_epi32(v_r1, 16)); + __m128i layer3_chunk1 = _mm_packus_epi32(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer3_chunk4 = _mm_packus_epi32(_mm_srli_epi32(v_g0, 16), _mm_srli_epi32(v_g1, 16)); + __m128i layer3_chunk2 = _mm_packus_epi32(_mm_and_si128(v_b0, v_mask), _mm_and_si128(v_b1, v_mask)); + __m128i layer3_chunk5 = _mm_packus_epi32(_mm_srli_epi32(v_b0, 16), _mm_srli_epi32(v_b1, 16)); + + __m128i layer2_chunk0 = _mm_packus_epi32(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk3 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk0, 16), _mm_srli_epi32(layer3_chunk1, 16)); + __m128i layer2_chunk1 = _mm_packus_epi32(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk4 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk2, 16), _mm_srli_epi32(layer3_chunk3, 16)); + __m128i layer2_chunk2 = _mm_packus_epi32(_mm_and_si128(layer3_chunk4, v_mask), _mm_and_si128(layer3_chunk5, v_mask)); + __m128i layer2_chunk5 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk4, 16), _mm_srli_epi32(layer3_chunk5, 16)); + + __m128i layer1_chunk0 = _mm_packus_epi32(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk3 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk0, 16), _mm_srli_epi32(layer2_chunk1, 16)); + __m128i layer1_chunk1 = _mm_packus_epi32(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk4 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk2, 16), _mm_srli_epi32(layer2_chunk3, 16)); + __m128i layer1_chunk2 = _mm_packus_epi32(_mm_and_si128(layer2_chunk4, v_mask), _mm_and_si128(layer2_chunk5, v_mask)); + __m128i layer1_chunk5 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk4, 16), _mm_srli_epi32(layer2_chunk5, 16)); + + v_r0 = _mm_packus_epi32(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_g1 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk0, 16), _mm_srli_epi32(layer1_chunk1, 16)); + v_r1 = _mm_packus_epi32(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_b0 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk2, 16), _mm_srli_epi32(layer1_chunk3, 16)); + v_g0 = _mm_packus_epi32(_mm_and_si128(layer1_chunk4, v_mask), _mm_and_si128(layer1_chunk5, v_mask)); + v_b1 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk4, 16), _mm_srli_epi32(layer1_chunk5, 16)); +} + +inline void _mm_interleave_epi16(__m128i & v_r0, __m128i & v_r1, __m128i & v_g0, __m128i & v_g1, + __m128i & v_b0, __m128i & v_b1, __m128i & v_a0, __m128i & v_a1) +{ + __m128i v_mask = _mm_set1_epi32(0x0000ffff); + + __m128i layer3_chunk0 = _mm_packus_epi32(_mm_and_si128(v_r0, v_mask), _mm_and_si128(v_r1, v_mask)); + __m128i layer3_chunk4 = _mm_packus_epi32(_mm_srli_epi32(v_r0, 16), _mm_srli_epi32(v_r1, 16)); + __m128i layer3_chunk1 = _mm_packus_epi32(_mm_and_si128(v_g0, v_mask), _mm_and_si128(v_g1, v_mask)); + __m128i layer3_chunk5 = _mm_packus_epi32(_mm_srli_epi32(v_g0, 16), _mm_srli_epi32(v_g1, 16)); + __m128i layer3_chunk2 = _mm_packus_epi32(_mm_and_si128(v_b0, v_mask), _mm_and_si128(v_b1, v_mask)); + __m128i layer3_chunk6 = _mm_packus_epi32(_mm_srli_epi32(v_b0, 16), _mm_srli_epi32(v_b1, 16)); + __m128i layer3_chunk3 = _mm_packus_epi32(_mm_and_si128(v_a0, v_mask), _mm_and_si128(v_a1, v_mask)); + __m128i layer3_chunk7 = _mm_packus_epi32(_mm_srli_epi32(v_a0, 16), _mm_srli_epi32(v_a1, 16)); + + __m128i layer2_chunk0 = _mm_packus_epi32(_mm_and_si128(layer3_chunk0, v_mask), _mm_and_si128(layer3_chunk1, v_mask)); + __m128i layer2_chunk4 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk0, 16), _mm_srli_epi32(layer3_chunk1, 16)); + __m128i layer2_chunk1 = _mm_packus_epi32(_mm_and_si128(layer3_chunk2, v_mask), _mm_and_si128(layer3_chunk3, v_mask)); + __m128i layer2_chunk5 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk2, 16), _mm_srli_epi32(layer3_chunk3, 16)); + __m128i layer2_chunk2 = _mm_packus_epi32(_mm_and_si128(layer3_chunk4, v_mask), _mm_and_si128(layer3_chunk5, v_mask)); + __m128i layer2_chunk6 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk4, 16), _mm_srli_epi32(layer3_chunk5, 16)); + __m128i layer2_chunk3 = _mm_packus_epi32(_mm_and_si128(layer3_chunk6, v_mask), _mm_and_si128(layer3_chunk7, v_mask)); + __m128i layer2_chunk7 = _mm_packus_epi32(_mm_srli_epi32(layer3_chunk6, 16), _mm_srli_epi32(layer3_chunk7, 16)); + + __m128i layer1_chunk0 = _mm_packus_epi32(_mm_and_si128(layer2_chunk0, v_mask), _mm_and_si128(layer2_chunk1, v_mask)); + __m128i layer1_chunk4 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk0, 16), _mm_srli_epi32(layer2_chunk1, 16)); + __m128i layer1_chunk1 = _mm_packus_epi32(_mm_and_si128(layer2_chunk2, v_mask), _mm_and_si128(layer2_chunk3, v_mask)); + __m128i layer1_chunk5 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk2, 16), _mm_srli_epi32(layer2_chunk3, 16)); + __m128i layer1_chunk2 = _mm_packus_epi32(_mm_and_si128(layer2_chunk4, v_mask), _mm_and_si128(layer2_chunk5, v_mask)); + __m128i layer1_chunk6 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk4, 16), _mm_srli_epi32(layer2_chunk5, 16)); + __m128i layer1_chunk3 = _mm_packus_epi32(_mm_and_si128(layer2_chunk6, v_mask), _mm_and_si128(layer2_chunk7, v_mask)); + __m128i layer1_chunk7 = _mm_packus_epi32(_mm_srli_epi32(layer2_chunk6, 16), _mm_srli_epi32(layer2_chunk7, 16)); + + v_r0 = _mm_packus_epi32(_mm_and_si128(layer1_chunk0, v_mask), _mm_and_si128(layer1_chunk1, v_mask)); + v_b0 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk0, 16), _mm_srli_epi32(layer1_chunk1, 16)); + v_r1 = _mm_packus_epi32(_mm_and_si128(layer1_chunk2, v_mask), _mm_and_si128(layer1_chunk3, v_mask)); + v_b1 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk2, 16), _mm_srli_epi32(layer1_chunk3, 16)); + v_g0 = _mm_packus_epi32(_mm_and_si128(layer1_chunk4, v_mask), _mm_and_si128(layer1_chunk5, v_mask)); + v_a0 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk4, 16), _mm_srli_epi32(layer1_chunk5, 16)); + v_g1 = _mm_packus_epi32(_mm_and_si128(layer1_chunk6, v_mask), _mm_and_si128(layer1_chunk7, v_mask)); + v_a1 = _mm_packus_epi32(_mm_srli_epi32(layer1_chunk6, 16), _mm_srli_epi32(layer1_chunk7, 16)); +} + +#endif // CV_SSE4_1 + +inline void _mm_deinterleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, __m128 & v_g1) +{ + __m128 layer1_chunk0 = _mm_unpacklo_ps(v_r0, v_g0); + __m128 layer1_chunk1 = _mm_unpackhi_ps(v_r0, v_g0); + __m128 layer1_chunk2 = _mm_unpacklo_ps(v_r1, v_g1); + __m128 layer1_chunk3 = _mm_unpackhi_ps(v_r1, v_g1); + + __m128 layer2_chunk0 = _mm_unpacklo_ps(layer1_chunk0, layer1_chunk2); + __m128 layer2_chunk1 = _mm_unpackhi_ps(layer1_chunk0, layer1_chunk2); + __m128 layer2_chunk2 = _mm_unpacklo_ps(layer1_chunk1, layer1_chunk3); + __m128 layer2_chunk3 = _mm_unpackhi_ps(layer1_chunk1, layer1_chunk3); + + v_r0 = _mm_unpacklo_ps(layer2_chunk0, layer2_chunk2); + v_r1 = _mm_unpackhi_ps(layer2_chunk0, layer2_chunk2); + v_g0 = _mm_unpacklo_ps(layer2_chunk1, layer2_chunk3); + v_g1 = _mm_unpackhi_ps(layer2_chunk1, layer2_chunk3); +} + +inline void _mm_deinterleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, + __m128 & v_g1, __m128 & v_b0, __m128 & v_b1) +{ + __m128 layer1_chunk0 = _mm_unpacklo_ps(v_r0, v_g1); + __m128 layer1_chunk1 = _mm_unpackhi_ps(v_r0, v_g1); + __m128 layer1_chunk2 = _mm_unpacklo_ps(v_r1, v_b0); + __m128 layer1_chunk3 = _mm_unpackhi_ps(v_r1, v_b0); + __m128 layer1_chunk4 = _mm_unpacklo_ps(v_g0, v_b1); + __m128 layer1_chunk5 = _mm_unpackhi_ps(v_g0, v_b1); + + __m128 layer2_chunk0 = _mm_unpacklo_ps(layer1_chunk0, layer1_chunk3); + __m128 layer2_chunk1 = _mm_unpackhi_ps(layer1_chunk0, layer1_chunk3); + __m128 layer2_chunk2 = _mm_unpacklo_ps(layer1_chunk1, layer1_chunk4); + __m128 layer2_chunk3 = _mm_unpackhi_ps(layer1_chunk1, layer1_chunk4); + __m128 layer2_chunk4 = _mm_unpacklo_ps(layer1_chunk2, layer1_chunk5); + __m128 layer2_chunk5 = _mm_unpackhi_ps(layer1_chunk2, layer1_chunk5); + + v_r0 = _mm_unpacklo_ps(layer2_chunk0, layer2_chunk3); + v_r1 = _mm_unpackhi_ps(layer2_chunk0, layer2_chunk3); + v_g0 = _mm_unpacklo_ps(layer2_chunk1, layer2_chunk4); + v_g1 = _mm_unpackhi_ps(layer2_chunk1, layer2_chunk4); + v_b0 = _mm_unpacklo_ps(layer2_chunk2, layer2_chunk5); + v_b1 = _mm_unpackhi_ps(layer2_chunk2, layer2_chunk5); +} + +inline void _mm_deinterleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, __m128 & v_g1, + __m128 & v_b0, __m128 & v_b1, __m128 & v_a0, __m128 & v_a1) +{ + __m128 layer1_chunk0 = _mm_unpacklo_ps(v_r0, v_b0); + __m128 layer1_chunk1 = _mm_unpackhi_ps(v_r0, v_b0); + __m128 layer1_chunk2 = _mm_unpacklo_ps(v_r1, v_b1); + __m128 layer1_chunk3 = _mm_unpackhi_ps(v_r1, v_b1); + __m128 layer1_chunk4 = _mm_unpacklo_ps(v_g0, v_a0); + __m128 layer1_chunk5 = _mm_unpackhi_ps(v_g0, v_a0); + __m128 layer1_chunk6 = _mm_unpacklo_ps(v_g1, v_a1); + __m128 layer1_chunk7 = _mm_unpackhi_ps(v_g1, v_a1); + + __m128 layer2_chunk0 = _mm_unpacklo_ps(layer1_chunk0, layer1_chunk4); + __m128 layer2_chunk1 = _mm_unpackhi_ps(layer1_chunk0, layer1_chunk4); + __m128 layer2_chunk2 = _mm_unpacklo_ps(layer1_chunk1, layer1_chunk5); + __m128 layer2_chunk3 = _mm_unpackhi_ps(layer1_chunk1, layer1_chunk5); + __m128 layer2_chunk4 = _mm_unpacklo_ps(layer1_chunk2, layer1_chunk6); + __m128 layer2_chunk5 = _mm_unpackhi_ps(layer1_chunk2, layer1_chunk6); + __m128 layer2_chunk6 = _mm_unpacklo_ps(layer1_chunk3, layer1_chunk7); + __m128 layer2_chunk7 = _mm_unpackhi_ps(layer1_chunk3, layer1_chunk7); + + v_r0 = _mm_unpacklo_ps(layer2_chunk0, layer2_chunk4); + v_r1 = _mm_unpackhi_ps(layer2_chunk0, layer2_chunk4); + v_g0 = _mm_unpacklo_ps(layer2_chunk1, layer2_chunk5); + v_g1 = _mm_unpackhi_ps(layer2_chunk1, layer2_chunk5); + v_b0 = _mm_unpacklo_ps(layer2_chunk2, layer2_chunk6); + v_b1 = _mm_unpackhi_ps(layer2_chunk2, layer2_chunk6); + v_a0 = _mm_unpacklo_ps(layer2_chunk3, layer2_chunk7); + v_a1 = _mm_unpackhi_ps(layer2_chunk3, layer2_chunk7); +} + +inline void _mm_interleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, __m128 & v_g1) +{ + enum { mask_lo = _MM_SHUFFLE(2, 0, 2, 0), mask_hi = _MM_SHUFFLE(3, 1, 3, 1) }; + + __m128 layer2_chunk0 = _mm_shuffle_ps(v_r0, v_r1, mask_lo); + __m128 layer2_chunk2 = _mm_shuffle_ps(v_r0, v_r1, mask_hi); + __m128 layer2_chunk1 = _mm_shuffle_ps(v_g0, v_g1, mask_lo); + __m128 layer2_chunk3 = _mm_shuffle_ps(v_g0, v_g1, mask_hi); + + __m128 layer1_chunk0 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_lo); + __m128 layer1_chunk2 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_hi); + __m128 layer1_chunk1 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_lo); + __m128 layer1_chunk3 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_hi); + + v_r0 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_lo); + v_g0 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_hi); + v_r1 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_lo); + v_g1 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_hi); +} + +inline void _mm_interleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, + __m128 & v_g1, __m128 & v_b0, __m128 & v_b1) +{ + enum { mask_lo = _MM_SHUFFLE(2, 0, 2, 0), mask_hi = _MM_SHUFFLE(3, 1, 3, 1) }; + + __m128 layer2_chunk0 = _mm_shuffle_ps(v_r0, v_r1, mask_lo); + __m128 layer2_chunk3 = _mm_shuffle_ps(v_r0, v_r1, mask_hi); + __m128 layer2_chunk1 = _mm_shuffle_ps(v_g0, v_g1, mask_lo); + __m128 layer2_chunk4 = _mm_shuffle_ps(v_g0, v_g1, mask_hi); + __m128 layer2_chunk2 = _mm_shuffle_ps(v_b0, v_b1, mask_lo); + __m128 layer2_chunk5 = _mm_shuffle_ps(v_b0, v_b1, mask_hi); + + __m128 layer1_chunk0 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_lo); + __m128 layer1_chunk3 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_hi); + __m128 layer1_chunk1 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_lo); + __m128 layer1_chunk4 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_hi); + __m128 layer1_chunk2 = _mm_shuffle_ps(layer2_chunk4, layer2_chunk5, mask_lo); + __m128 layer1_chunk5 = _mm_shuffle_ps(layer2_chunk4, layer2_chunk5, mask_hi); + + v_r0 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_lo); + v_g1 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_hi); + v_r1 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_lo); + v_b0 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_hi); + v_g0 = _mm_shuffle_ps(layer1_chunk4, layer1_chunk5, mask_lo); + v_b1 = _mm_shuffle_ps(layer1_chunk4, layer1_chunk5, mask_hi); +} + +inline void _mm_interleave_ps(__m128 & v_r0, __m128 & v_r1, __m128 & v_g0, __m128 & v_g1, + __m128 & v_b0, __m128 & v_b1, __m128 & v_a0, __m128 & v_a1) +{ + enum { mask_lo = _MM_SHUFFLE(2, 0, 2, 0), mask_hi = _MM_SHUFFLE(3, 1, 3, 1) }; + + __m128 layer2_chunk0 = _mm_shuffle_ps(v_r0, v_r1, mask_lo); + __m128 layer2_chunk4 = _mm_shuffle_ps(v_r0, v_r1, mask_hi); + __m128 layer2_chunk1 = _mm_shuffle_ps(v_g0, v_g1, mask_lo); + __m128 layer2_chunk5 = _mm_shuffle_ps(v_g0, v_g1, mask_hi); + __m128 layer2_chunk2 = _mm_shuffle_ps(v_b0, v_b1, mask_lo); + __m128 layer2_chunk6 = _mm_shuffle_ps(v_b0, v_b1, mask_hi); + __m128 layer2_chunk3 = _mm_shuffle_ps(v_a0, v_a1, mask_lo); + __m128 layer2_chunk7 = _mm_shuffle_ps(v_a0, v_a1, mask_hi); + + __m128 layer1_chunk0 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_lo); + __m128 layer1_chunk4 = _mm_shuffle_ps(layer2_chunk0, layer2_chunk1, mask_hi); + __m128 layer1_chunk1 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_lo); + __m128 layer1_chunk5 = _mm_shuffle_ps(layer2_chunk2, layer2_chunk3, mask_hi); + __m128 layer1_chunk2 = _mm_shuffle_ps(layer2_chunk4, layer2_chunk5, mask_lo); + __m128 layer1_chunk6 = _mm_shuffle_ps(layer2_chunk4, layer2_chunk5, mask_hi); + __m128 layer1_chunk3 = _mm_shuffle_ps(layer2_chunk6, layer2_chunk7, mask_lo); + __m128 layer1_chunk7 = _mm_shuffle_ps(layer2_chunk6, layer2_chunk7, mask_hi); + + v_r0 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_lo); + v_b0 = _mm_shuffle_ps(layer1_chunk0, layer1_chunk1, mask_hi); + v_r1 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_lo); + v_b1 = _mm_shuffle_ps(layer1_chunk2, layer1_chunk3, mask_hi); + v_g0 = _mm_shuffle_ps(layer1_chunk4, layer1_chunk5, mask_lo); + v_a0 = _mm_shuffle_ps(layer1_chunk4, layer1_chunk5, mask_hi); + v_g1 = _mm_shuffle_ps(layer1_chunk6, layer1_chunk7, mask_lo); + v_a1 = _mm_shuffle_ps(layer1_chunk6, layer1_chunk7, mask_hi); +} + +#endif // CV_SSE2 + +//! @} + +#endif //OPENCV_CORE_SSE_UTILS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/traits.hpp b/3rdparty/opencv/include/opencv2/core/traits.hpp new file mode 100644 index 00000000..6cb10f44 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/traits.hpp @@ -0,0 +1,397 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_TRAITS_HPP +#define OPENCV_CORE_TRAITS_HPP + +#include "opencv2/core/cvdef.h" + +namespace cv +{ + +//#define OPENCV_TRAITS_ENABLE_DEPRECATED + +//! @addtogroup core_basic +//! @{ + +/** @brief Template "trait" class for OpenCV primitive data types. + +@note Deprecated. This is replaced by "single purpose" traits: traits::Type and traits::Depth + +A primitive OpenCV data type is one of unsigned char, bool, signed char, unsigned short, signed +short, int, float, double, or a tuple of values of one of these types, where all the values in the +tuple have the same type. Any primitive type from the list can be defined by an identifier in the +form CV_\{U|S|F}C(\), for example: uchar \~ CV_8UC1, 3-element +floating-point tuple \~ CV_32FC3, and so on. A universal OpenCV structure that is able to store a +single instance of such a primitive data type is Vec. Multiple instances of such a type can be +stored in a std::vector, Mat, Mat_, SparseMat, SparseMat_, or any other container that is able to +store Vec instances. + +The DataType class is basically used to provide a description of such primitive data types without +adding any fields or methods to the corresponding classes (and it is actually impossible to add +anything to primitive C/C++ data types). This technique is known in C++ as class traits. It is not +DataType itself that is used but its specialized versions, such as: +@code + template<> class DataType + { + typedef uchar value_type; + typedef int work_type; + typedef uchar channel_type; + enum { channel_type = CV_8U, channels = 1, fmt='u', type = CV_8U }; + }; + ... + template DataType > + { + typedef std::complex<_Tp> value_type; + typedef std::complex<_Tp> work_type; + typedef _Tp channel_type; + // DataDepth is another helper trait class + enum { depth = DataDepth<_Tp>::value, channels=2, + fmt=(channels-1)*256+DataDepth<_Tp>::fmt, + type=CV_MAKETYPE(depth, channels) }; + }; + ... +@endcode +The main purpose of this class is to convert compilation-time type information to an +OpenCV-compatible data type identifier, for example: +@code + // allocates a 30x40 floating-point matrix + Mat A(30, 40, DataType::type); + + Mat B = Mat_ >(3, 3); + // the statement below will print 6, 2 , that is depth == CV_64F, channels == 2 + cout << B.depth() << ", " << B.channels() << endl; +@endcode +So, such traits are used to tell OpenCV which data type you are working with, even if such a type is +not native to OpenCV. For example, the matrix B initialization above is compiled because OpenCV +defines the proper specialized template class DataType\ \> . This mechanism is also +useful (and used in OpenCV this way) for generic algorithms implementations. + +@note Default values were dropped to stop confusing developers about using of unsupported types (see #7599) +*/ +template class DataType +{ +public: +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + typedef _Tp value_type; + typedef value_type work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 1, + depth = -1, + channels = 1, + fmt = 0, + type = CV_MAKETYPE(depth, channels) + }; +#endif +}; + +template<> class DataType +{ +public: + typedef bool value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_8U, + channels = 1, + fmt = (int)'u', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef uchar value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_8U, + channels = 1, + fmt = (int)'u', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef schar value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_8S, + channels = 1, + fmt = (int)'c', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef schar value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_8S, + channels = 1, + fmt = (int)'c', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef ushort value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_16U, + channels = 1, + fmt = (int)'w', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef short value_type; + typedef int work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_16S, + channels = 1, + fmt = (int)'s', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef int value_type; + typedef value_type work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_32S, + channels = 1, + fmt = (int)'i', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef float value_type; + typedef value_type work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_32F, + channels = 1, + fmt = (int)'f', + type = CV_MAKETYPE(depth, channels) + }; +}; + +template<> class DataType +{ +public: + typedef double value_type; + typedef value_type work_type; + typedef value_type channel_type; + typedef value_type vec_type; + enum { generic_type = 0, + depth = CV_64F, + channels = 1, + fmt = (int)'d', + type = CV_MAKETYPE(depth, channels) + }; +}; + + +/** @brief A helper class for cv::DataType + +The class is specialized for each fundamental numerical data type supported by OpenCV. It provides +DataDepth::value constant. +*/ +template class DataDepth +{ +public: + enum + { + value = DataType<_Tp>::depth, + fmt = DataType<_Tp>::fmt + }; +}; + + +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + +template class TypeDepth +{ +#ifdef OPENCV_TRAITS_ENABLE_LEGACY_DEFAULTS + enum { depth = CV_USRTYPE1 }; + typedef void value_type; +#endif +}; + +template<> class TypeDepth +{ + enum { depth = CV_8U }; + typedef uchar value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_8S }; + typedef schar value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_16U }; + typedef ushort value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_16S }; + typedef short value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_32S }; + typedef int value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_32F }; + typedef float value_type; +}; + +template<> class TypeDepth +{ + enum { depth = CV_64F }; + typedef double value_type; +}; + +#endif + +//! @} + +namespace traits { + +namespace internal { +#define CV_CREATE_MEMBER_CHECK(X) \ +template class CheckMember_##X { \ + struct Fallback { int X; }; \ + struct Derived : T, Fallback { }; \ + template struct Check; \ + typedef char CV_NO[1]; \ + typedef char CV_YES[2]; \ + template static CV_NO & func(Check *); \ + template static CV_YES & func(...); \ +public: \ + typedef CheckMember_##X type; \ + enum { value = sizeof(func(0)) == sizeof(CV_YES) }; \ +}; + +CV_CREATE_MEMBER_CHECK(fmt) +CV_CREATE_MEMBER_CHECK(type) + +} // namespace internal + + +template +struct Depth +{ enum { value = DataType::depth }; }; + +template +struct Type +{ enum { value = DataType::type }; }; + +/** Similar to traits::Type but has value = -1 in case of unknown type (instead of compiler error) */ +template >::value > +struct SafeType {}; + +template +struct SafeType +{ enum { value = -1 }; }; + +template +struct SafeType +{ enum { value = Type::value }; }; + + +template >::value > +struct SafeFmt {}; + +template +struct SafeFmt +{ enum { fmt = 0 }; }; + +template +struct SafeFmt +{ enum { fmt = DataType::fmt }; }; + + +} // namespace + +} // cv + +#endif // OPENCV_CORE_TRAITS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/types.hpp b/3rdparty/opencv/include/opencv2/core/types.hpp new file mode 100644 index 00000000..ef9ab593 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/types.hpp @@ -0,0 +1,2391 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_TYPES_HPP +#define OPENCV_CORE_TYPES_HPP + +#ifndef __cplusplus +# error types.hpp header must be compiled as C++ +#endif + +#include +#include +#include +#include + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/cvstd.hpp" +#include "opencv2/core/matx.hpp" + +namespace cv +{ + +//! @addtogroup core_basic +//! @{ + +//////////////////////////////// Complex ////////////////////////////// + +/** @brief A complex number class. + + The template class is similar and compatible with std::complex, however it provides slightly + more convenient access to the real and imaginary parts using through the simple field access, as opposite + to std::complex::real() and std::complex::imag(). +*/ +template class Complex +{ +public: + + //! default constructor + Complex(); + Complex( _Tp _re, _Tp _im = 0 ); + + //! conversion to another data type + template operator Complex() const; + //! conjugation + Complex conj() const; + + _Tp re, im; //< the real and the imaginary parts +}; + +typedef Complex Complexf; +typedef Complex Complexd; + +template class DataType< Complex<_Tp> > +{ +public: + typedef Complex<_Tp> value_type; + typedef value_type work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 2, + fmt = DataType::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Complex<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Complex<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 2) }; }; +} // namespace + + +//////////////////////////////// Point_ //////////////////////////////// + +/** @brief Template class for 2D points specified by its coordinates `x` and `y`. + +An instance of the class is interchangeable with C structures, CvPoint and CvPoint2D32f . There is +also a cast operator to convert point coordinates to the specified type. The conversion from +floating-point coordinates to integer coordinates is done by rounding. Commonly, the conversion +uses this operation for each of the coordinates. Besides the class members listed in the +declaration above, the following operations on points are implemented: +@code + pt1 = pt2 + pt3; + pt1 = pt2 - pt3; + pt1 = pt2 * a; + pt1 = a * pt2; + pt1 = pt2 / a; + pt1 += pt2; + pt1 -= pt2; + pt1 *= a; + pt1 /= a; + double value = norm(pt); // L2 norm + pt1 == pt2; + pt1 != pt2; +@endcode +For your convenience, the following type aliases are defined: +@code + typedef Point_ Point2i; + typedef Point2i Point; + typedef Point_ Point2f; + typedef Point_ Point2d; +@endcode +Example: +@code + Point2f a(0.3f, 0.f), b(0.f, 0.4f); + Point pt = (a + b)*10.f; + cout << pt.x << ", " << pt.y << endl; +@endcode +*/ +template class Point_ +{ +public: + typedef _Tp value_type; + + //! default constructor + Point_(); + Point_(_Tp _x, _Tp _y); + Point_(const Point_& pt); + Point_(const Size_<_Tp>& sz); + Point_(const Vec<_Tp, 2>& v); + + Point_& operator = (const Point_& pt); + //! conversion to another data type + template operator Point_<_Tp2>() const; + + //! conversion to the old-style C structures + operator Vec<_Tp, 2>() const; + + //! dot product + _Tp dot(const Point_& pt) const; + //! dot product computed in double-precision arithmetics + double ddot(const Point_& pt) const; + //! cross-product + double cross(const Point_& pt) const; + //! checks whether the point is inside the specified rectangle + bool inside(const Rect_<_Tp>& r) const; + _Tp x; //!< x coordinate of the point + _Tp y; //!< y coordinate of the point +}; + +typedef Point_ Point2i; +typedef Point_ Point2l; +typedef Point_ Point2f; +typedef Point_ Point2d; +typedef Point2i Point; + +template class DataType< Point_<_Tp> > +{ +public: + typedef Point_<_Tp> value_type; + typedef Point_::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 2, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Point_<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Point_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 2) }; }; +} // namespace + + +//////////////////////////////// Point3_ //////////////////////////////// + +/** @brief Template class for 3D points specified by its coordinates `x`, `y` and `z`. + +An instance of the class is interchangeable with the C structure CvPoint2D32f . Similarly to +Point_ , the coordinates of 3D points can be converted to another type. The vector arithmetic and +comparison operations are also supported. + +The following Point3_\<\> aliases are available: +@code + typedef Point3_ Point3i; + typedef Point3_ Point3f; + typedef Point3_ Point3d; +@endcode +@see cv::Point3i, cv::Point3f and cv::Point3d +*/ +template class Point3_ +{ +public: + typedef _Tp value_type; + + //! default constructor + Point3_(); + Point3_(_Tp _x, _Tp _y, _Tp _z); + Point3_(const Point3_& pt); + explicit Point3_(const Point_<_Tp>& pt); + Point3_(const Vec<_Tp, 3>& v); + + Point3_& operator = (const Point3_& pt); + //! conversion to another data type + template operator Point3_<_Tp2>() const; + //! conversion to cv::Vec<> +#if OPENCV_ABI_COMPATIBILITY > 300 + template operator Vec<_Tp2, 3>() const; +#else + operator Vec<_Tp, 3>() const; +#endif + + //! dot product + _Tp dot(const Point3_& pt) const; + //! dot product computed in double-precision arithmetics + double ddot(const Point3_& pt) const; + //! cross product of the 2 3D points + Point3_ cross(const Point3_& pt) const; + _Tp x; //!< x coordinate of the 3D point + _Tp y; //!< y coordinate of the 3D point + _Tp z; //!< z coordinate of the 3D point +}; + +typedef Point3_ Point3i; +typedef Point3_ Point3f; +typedef Point3_ Point3d; + +template class DataType< Point3_<_Tp> > +{ +public: + typedef Point3_<_Tp> value_type; + typedef Point3_::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 3, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Point3_<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Point3_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 3) }; }; +} // namespace + +//////////////////////////////// Size_ //////////////////////////////// + +/** @brief Template class for specifying the size of an image or rectangle. + +The class includes two members called width and height. The structure can be converted to and from +the old OpenCV structures CvSize and CvSize2D32f . The same set of arithmetic and comparison +operations as for Point_ is available. + +OpenCV defines the following Size_\<\> aliases: +@code + typedef Size_ Size2i; + typedef Size2i Size; + typedef Size_ Size2f; +@endcode +*/ +template class Size_ +{ +public: + typedef _Tp value_type; + + //! default constructor + Size_(); + Size_(_Tp _width, _Tp _height); + Size_(const Size_& sz); + Size_(const Point_<_Tp>& pt); + + Size_& operator = (const Size_& sz); + //! the area (width*height) + _Tp area() const; + //! true if empty + bool empty() const; + + //! conversion of another data type. + template operator Size_<_Tp2>() const; + + _Tp width; //!< the width + _Tp height; //!< the height +}; + +typedef Size_ Size2i; +typedef Size_ Size2l; +typedef Size_ Size2f; +typedef Size_ Size2d; +typedef Size2i Size; + +template class DataType< Size_<_Tp> > +{ +public: + typedef Size_<_Tp> value_type; + typedef Size_::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 2, + fmt = DataType::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Size_<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Size_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 2) }; }; +} // namespace + +//////////////////////////////// Rect_ //////////////////////////////// + +/** @brief Template class for 2D rectangles + +described by the following parameters: +- Coordinates of the top-left corner. This is a default interpretation of Rect_::x and Rect_::y + in OpenCV. Though, in your algorithms you may count x and y from the bottom-left corner. +- Rectangle width and height. + +OpenCV typically assumes that the top and left boundary of the rectangle are inclusive, while the +right and bottom boundaries are not. For example, the method Rect_::contains returns true if + +\f[x \leq pt.x < x+width, + y \leq pt.y < y+height\f] + +Virtually every loop over an image ROI in OpenCV (where ROI is specified by Rect_\ ) is +implemented as: +@code + for(int y = roi.y; y < roi.y + roi.height; y++) + for(int x = roi.x; x < roi.x + roi.width; x++) + { + // ... + } +@endcode +In addition to the class members, the following operations on rectangles are implemented: +- \f$\texttt{rect} = \texttt{rect} \pm \texttt{point}\f$ (shifting a rectangle by a certain offset) +- \f$\texttt{rect} = \texttt{rect} \pm \texttt{size}\f$ (expanding or shrinking a rectangle by a + certain amount) +- rect += point, rect -= point, rect += size, rect -= size (augmenting operations) +- rect = rect1 & rect2 (rectangle intersection) +- rect = rect1 | rect2 (minimum area rectangle containing rect1 and rect2 ) +- rect &= rect1, rect |= rect1 (and the corresponding augmenting operations) +- rect == rect1, rect != rect1 (rectangle comparison) + +This is an example how the partial ordering on rectangles can be established (rect1 \f$\subseteq\f$ +rect2): +@code + template inline bool + operator <= (const Rect_<_Tp>& r1, const Rect_<_Tp>& r2) + { + return (r1 & r2) == r1; + } +@endcode +For your convenience, the Rect_\<\> alias is available: cv::Rect +*/ +template class Rect_ +{ +public: + typedef _Tp value_type; + + //! default constructor + Rect_(); + Rect_(_Tp _x, _Tp _y, _Tp _width, _Tp _height); + Rect_(const Rect_& r); + Rect_(const Point_<_Tp>& org, const Size_<_Tp>& sz); + Rect_(const Point_<_Tp>& pt1, const Point_<_Tp>& pt2); + + Rect_& operator = ( const Rect_& r ); + //! the top-left corner + Point_<_Tp> tl() const; + //! the bottom-right corner + Point_<_Tp> br() const; + + //! size (width, height) of the rectangle + Size_<_Tp> size() const; + //! area (width*height) of the rectangle + _Tp area() const; + //! true if empty + bool empty() const; + + //! conversion to another data type + template operator Rect_<_Tp2>() const; + + //! checks whether the rectangle contains the point + bool contains(const Point_<_Tp>& pt) const; + + _Tp x; //!< x coordinate of the top-left corner + _Tp y; //!< y coordinate of the top-left corner + _Tp width; //!< width of the rectangle + _Tp height; //!< height of the rectangle +}; + +typedef Rect_ Rect2i; +typedef Rect_ Rect2f; +typedef Rect_ Rect2d; +typedef Rect2i Rect; + +template class DataType< Rect_<_Tp> > +{ +public: + typedef Rect_<_Tp> value_type; + typedef Rect_::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 4, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Rect_<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Rect_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 4) }; }; +} // namespace + +///////////////////////////// RotatedRect ///////////////////////////// + +/** @brief The class represents rotated (i.e. not up-right) rectangles on a plane. + +Each rectangle is specified by the center point (mass center), length of each side (represented by +#Size2f structure) and the rotation angle in degrees. + +The sample below demonstrates how to use RotatedRect: +@snippet snippets/core_various.cpp RotatedRect_demo +![image](pics/rotatedrect.png) + +@sa CamShift, fitEllipse, minAreaRect, CvBox2D +*/ +class CV_EXPORTS RotatedRect +{ +public: + //! default constructor + RotatedRect(); + /** full constructor + @param center The rectangle mass center. + @param size Width and height of the rectangle. + @param angle The rotation angle in a clockwise direction. When the angle is 0, 90, 180, 270 etc., + the rectangle becomes an up-right rectangle. + */ + RotatedRect(const Point2f& center, const Size2f& size, float angle); + /** + Any 3 end points of the RotatedRect. They must be given in order (either clockwise or + anticlockwise). + */ + RotatedRect(const Point2f& point1, const Point2f& point2, const Point2f& point3); + + /** returns 4 vertices of the rectangle + @param pts The points array for storing rectangle vertices. The order is bottomLeft, topLeft, topRight, bottomRight. + */ + void points(Point2f pts[]) const; + //! returns the minimal up-right integer rectangle containing the rotated rectangle + Rect boundingRect() const; + //! returns the minimal (exact) floating point rectangle containing the rotated rectangle, not intended for use with images + Rect_ boundingRect2f() const; + //! returns the rectangle mass center + Point2f center; + //! returns width and height of the rectangle + Size2f size; + //! returns the rotation angle. When the angle is 0, 90, 180, 270 etc., the rectangle becomes an up-right rectangle. + float angle; +}; + +template<> class DataType< RotatedRect > +{ +public: + typedef RotatedRect value_type; + typedef value_type work_type; + typedef float channel_type; + + enum { generic_type = 0, + channels = (int)sizeof(value_type)/sizeof(channel_type), // 5 + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template<> +struct Depth< RotatedRect > { enum { value = Depth::value }; }; +template<> +struct Type< RotatedRect > { enum { value = CV_MAKETYPE(Depth::value, (int)sizeof(RotatedRect)/sizeof(float)) }; }; +} // namespace + + +//////////////////////////////// Range ///////////////////////////////// + +/** @brief Template class specifying a continuous subsequence (slice) of a sequence. + +The class is used to specify a row or a column span in a matrix ( Mat ) and for many other purposes. +Range(a,b) is basically the same as a:b in Matlab or a..b in Python. As in Python, start is an +inclusive left boundary of the range and end is an exclusive right boundary of the range. Such a +half-opened interval is usually denoted as \f$[start,end)\f$ . + +The static method Range::all() returns a special variable that means "the whole sequence" or "the +whole range", just like " : " in Matlab or " ... " in Python. All the methods and functions in +OpenCV that take Range support this special Range::all() value. But, of course, in case of your own +custom processing, you will probably have to check and handle it explicitly: +@code + void my_function(..., const Range& r, ....) + { + if(r == Range::all()) { + // process all the data + } + else { + // process [r.start, r.end) + } + } +@endcode +*/ +class CV_EXPORTS Range +{ +public: + Range(); + Range(int _start, int _end); + int size() const; + bool empty() const; + static Range all(); + + int start, end; +}; + +template<> class DataType +{ +public: + typedef Range value_type; + typedef value_type work_type; + typedef int channel_type; + + enum { generic_type = 0, + channels = 2, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template<> +struct Depth< Range > { enum { value = Depth::value }; }; +template<> +struct Type< Range > { enum { value = CV_MAKETYPE(Depth::value, 2) }; }; +} // namespace + + +//////////////////////////////// Scalar_ /////////////////////////////// + +/** @brief Template class for a 4-element vector derived from Vec. + +Being derived from Vec\<_Tp, 4\> , Scalar\_ and Scalar can be used just as typical 4-element +vectors. In addition, they can be converted to/from CvScalar . The type Scalar is widely used in +OpenCV to pass pixel values. +*/ +template class Scalar_ : public Vec<_Tp, 4> +{ +public: + //! default constructor + Scalar_(); + Scalar_(_Tp v0, _Tp v1, _Tp v2=0, _Tp v3=0); + Scalar_(_Tp v0); + + template + Scalar_(const Vec<_Tp2, cn>& v); + + //! returns a scalar with all elements set to v0 + static Scalar_<_Tp> all(_Tp v0); + + //! conversion to another data type + template operator Scalar_() const; + + //! per-element product + Scalar_<_Tp> mul(const Scalar_<_Tp>& a, double scale=1 ) const; + + //! returns (v0, -v1, -v2, -v3) + Scalar_<_Tp> conj() const; + + //! returns true iff v1 == v2 == v3 == 0 + bool isReal() const; +}; + +typedef Scalar_ Scalar; + +template class DataType< Scalar_<_Tp> > +{ +public: + typedef Scalar_<_Tp> value_type; + typedef Scalar_::work_type> work_type; + typedef _Tp channel_type; + + enum { generic_type = 0, + channels = 4, + fmt = traits::SafeFmt::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template +struct Depth< Scalar_<_Tp> > { enum { value = Depth<_Tp>::value }; }; +template +struct Type< Scalar_<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 4) }; }; +} // namespace + + +/////////////////////////////// KeyPoint //////////////////////////////// + +/** @brief Data structure for salient point detectors. + +The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint +detectors, such as Harris corner detector, #FAST, %StarDetector, %SURF, %SIFT etc. + +The keypoint is characterized by the 2D position, scale (proportional to the diameter of the +neighborhood that needs to be taken into account), orientation and some other parameters. The +keypoint neighborhood is then analyzed by another algorithm that builds a descriptor (usually +represented as a feature vector). The keypoints representing the same object in different images +can then be matched using %KDTree or another method. +*/ +class CV_EXPORTS_W_SIMPLE KeyPoint +{ +public: + //! the default constructor + CV_WRAP KeyPoint(); + /** + @param _pt x & y coordinates of the keypoint + @param _size keypoint diameter + @param _angle keypoint orientation + @param _response keypoint detector response on the keypoint (that is, strength of the keypoint) + @param _octave pyramid octave in which the keypoint has been detected + @param _class_id object id + */ + KeyPoint(Point2f _pt, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1); + /** + @param x x-coordinate of the keypoint + @param y y-coordinate of the keypoint + @param _size keypoint diameter + @param _angle keypoint orientation + @param _response keypoint detector response on the keypoint (that is, strength of the keypoint) + @param _octave pyramid octave in which the keypoint has been detected + @param _class_id object id + */ + CV_WRAP KeyPoint(float x, float y, float _size, float _angle=-1, float _response=0, int _octave=0, int _class_id=-1); + + size_t hash() const; + + /** + This method converts vector of keypoints to vector of points or the reverse, where each keypoint is + assigned the same size and the same orientation. + + @param keypoints Keypoints obtained from any feature detection algorithm like SIFT/SURF/ORB + @param points2f Array of (x,y) coordinates of each keypoint + @param keypointIndexes Array of indexes of keypoints to be converted to points. (Acts like a mask to + convert only specified keypoints) + */ + CV_WRAP static void convert(const std::vector& keypoints, + CV_OUT std::vector& points2f, + const std::vector& keypointIndexes=std::vector()); + /** @overload + @param points2f Array of (x,y) coordinates of each keypoint + @param keypoints Keypoints obtained from any feature detection algorithm like SIFT/SURF/ORB + @param size keypoint diameter + @param response keypoint detector response on the keypoint (that is, strength of the keypoint) + @param octave pyramid octave in which the keypoint has been detected + @param class_id object id + */ + CV_WRAP static void convert(const std::vector& points2f, + CV_OUT std::vector& keypoints, + float size=1, float response=1, int octave=0, int class_id=-1); + + /** + This method computes overlap for pair of keypoints. Overlap is the ratio between area of keypoint + regions' intersection and area of keypoint regions' union (considering keypoint region as circle). + If they don't overlap, we get zero. If they coincide at same location with same size, we get 1. + @param kp1 First keypoint + @param kp2 Second keypoint + */ + CV_WRAP static float overlap(const KeyPoint& kp1, const KeyPoint& kp2); + + CV_PROP_RW Point2f pt; //!< coordinates of the keypoints + CV_PROP_RW float size; //!< diameter of the meaningful keypoint neighborhood + CV_PROP_RW float angle; //!< computed orientation of the keypoint (-1 if not applicable); + //!< it's in [0,360) degrees and measured relative to + //!< image coordinate system, ie in clockwise. + CV_PROP_RW float response; //!< the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling + CV_PROP_RW int octave; //!< octave (pyramid layer) from which the keypoint has been extracted + CV_PROP_RW int class_id; //!< object class (if the keypoints need to be clustered by an object they belong to) +}; + +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED +template<> class DataType +{ +public: + typedef KeyPoint value_type; + typedef float work_type; + typedef float channel_type; + + enum { generic_type = 0, + depth = DataType::depth, + channels = (int)(sizeof(value_type)/sizeof(channel_type)), // 7 + fmt = DataType::fmt + ((channels - 1) << 8), + type = CV_MAKETYPE(depth, channels) + }; + + typedef Vec vec_type; +}; +#endif + + +//////////////////////////////// DMatch ///////////////////////////////// + +/** @brief Class for matching keypoint descriptors + +query descriptor index, train descriptor index, train image index, and distance between +descriptors. +*/ +class CV_EXPORTS_W_SIMPLE DMatch +{ +public: + CV_WRAP DMatch(); + CV_WRAP DMatch(int _queryIdx, int _trainIdx, float _distance); + CV_WRAP DMatch(int _queryIdx, int _trainIdx, int _imgIdx, float _distance); + + CV_PROP_RW int queryIdx; //!< query descriptor index + CV_PROP_RW int trainIdx; //!< train descriptor index + CV_PROP_RW int imgIdx; //!< train image index + + CV_PROP_RW float distance; + + // less is better + bool operator<(const DMatch &m) const; +}; + +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED +template<> class DataType +{ +public: + typedef DMatch value_type; + typedef int work_type; + typedef int channel_type; + + enum { generic_type = 0, + depth = DataType::depth, + channels = (int)(sizeof(value_type)/sizeof(channel_type)), // 4 + fmt = DataType::fmt + ((channels - 1) << 8), + type = CV_MAKETYPE(depth, channels) + }; + + typedef Vec vec_type; +}; +#endif + + +///////////////////////////// TermCriteria ////////////////////////////// + +/** @brief The class defining termination criteria for iterative algorithms. + +You can initialize it by default constructor and then override any parameters, or the structure may +be fully initialized using the advanced variant of the constructor. +*/ +class CV_EXPORTS TermCriteria +{ +public: + /** + Criteria type, can be one of: COUNT, EPS or COUNT + EPS + */ + enum Type + { + COUNT=1, //!< the maximum number of iterations or elements to compute + MAX_ITER=COUNT, //!< ditto + EPS=2 //!< the desired accuracy or change in parameters at which the iterative algorithm stops + }; + + //! default constructor + TermCriteria(); + /** + @param type The type of termination criteria, one of TermCriteria::Type + @param maxCount The maximum number of iterations or elements to compute. + @param epsilon The desired accuracy or change in parameters at which the iterative algorithm stops. + */ + TermCriteria(int type, int maxCount, double epsilon); + + inline bool isValid() const + { + const bool isCount = (type & COUNT) && maxCount > 0; + const bool isEps = (type & EPS) && !cvIsNaN(epsilon); + return isCount || isEps; + } + + int type; //!< the type of termination criteria: COUNT, EPS or COUNT + EPS + int maxCount; //!< the maximum number of iterations/elements + double epsilon; //!< the desired accuracy +}; + + +//! @} core_basic + +///////////////////////// raster image moments ////////////////////////// + +//! @addtogroup imgproc_shape +//! @{ + +/** @brief struct returned by cv::moments + +The spatial moments \f$\texttt{Moments::m}_{ji}\f$ are computed as: + +\f[\texttt{m} _{ji}= \sum _{x,y} \left ( \texttt{array} (x,y) \cdot x^j \cdot y^i \right )\f] + +The central moments \f$\texttt{Moments::mu}_{ji}\f$ are computed as: + +\f[\texttt{mu} _{ji}= \sum _{x,y} \left ( \texttt{array} (x,y) \cdot (x - \bar{x} )^j \cdot (y - \bar{y} )^i \right )\f] + +where \f$(\bar{x}, \bar{y})\f$ is the mass center: + +\f[\bar{x} = \frac{\texttt{m}_{10}}{\texttt{m}_{00}} , \; \bar{y} = \frac{\texttt{m}_{01}}{\texttt{m}_{00}}\f] + +The normalized central moments \f$\texttt{Moments::nu}_{ij}\f$ are computed as: + +\f[\texttt{nu} _{ji}= \frac{\texttt{mu}_{ji}}{\texttt{m}_{00}^{(i+j)/2+1}} .\f] + +@note +\f$\texttt{mu}_{00}=\texttt{m}_{00}\f$, \f$\texttt{nu}_{00}=1\f$ +\f$\texttt{nu}_{10}=\texttt{mu}_{10}=\texttt{mu}_{01}=\texttt{mu}_{10}=0\f$ , hence the values are not +stored. + +The moments of a contour are defined in the same way but computed using the Green's formula (see +). So, due to a limited raster resolution, the moments +computed for a contour are slightly different from the moments computed for the same rasterized +contour. + +@note +Since the contour moments are computed using Green formula, you may get seemingly odd results for +contours with self-intersections, e.g. a zero area (m00) for butterfly-shaped contours. + */ +class CV_EXPORTS_W_MAP Moments +{ +public: + //! the default constructor + Moments(); + //! the full constructor + Moments(double m00, double m10, double m01, double m20, double m11, + double m02, double m30, double m21, double m12, double m03 ); + ////! the conversion from CvMoments + //Moments( const CvMoments& moments ); + ////! the conversion to CvMoments + //operator CvMoments() const; + + //! @name spatial moments + //! @{ + CV_PROP_RW double m00, m10, m01, m20, m11, m02, m30, m21, m12, m03; + //! @} + + //! @name central moments + //! @{ + CV_PROP_RW double mu20, mu11, mu02, mu30, mu21, mu12, mu03; + //! @} + + //! @name central normalized moments + //! @{ + CV_PROP_RW double nu20, nu11, nu02, nu30, nu21, nu12, nu03; + //! @} +}; + +template<> class DataType +{ +public: + typedef Moments value_type; + typedef double work_type; + typedef double channel_type; + + enum { generic_type = 0, + channels = (int)(sizeof(value_type)/sizeof(channel_type)), // 24 + fmt = DataType::fmt + ((channels - 1) << 8) +#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED + ,depth = DataType::depth + ,type = CV_MAKETYPE(depth, channels) +#endif + }; + + typedef Vec vec_type; +}; + +namespace traits { +template<> +struct Depth< Moments > { enum { value = Depth::value }; }; +template<> +struct Type< Moments > { enum { value = CV_MAKETYPE(Depth::value, (int)(sizeof(Moments)/sizeof(double))) }; }; +} // namespace + +//! @} imgproc_shape + +//! @cond IGNORED + +///////////////////////////////////////////////////////////////////////// +///////////////////////////// Implementation //////////////////////////// +///////////////////////////////////////////////////////////////////////// + +//////////////////////////////// Complex //////////////////////////////// + +template inline +Complex<_Tp>::Complex() + : re(0), im(0) {} + +template inline +Complex<_Tp>::Complex( _Tp _re, _Tp _im ) + : re(_re), im(_im) {} + +template template inline +Complex<_Tp>::operator Complex() const +{ + return Complex(saturate_cast(re), saturate_cast(im)); +} + +template inline +Complex<_Tp> Complex<_Tp>::conj() const +{ + return Complex<_Tp>(re, -im); +} + + +template static inline +bool operator == (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + return a.re == b.re && a.im == b.im; +} + +template static inline +bool operator != (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + return a.re != b.re || a.im != b.im; +} + +template static inline +Complex<_Tp> operator + (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + return Complex<_Tp>( a.re + b.re, a.im + b.im ); +} + +template static inline +Complex<_Tp>& operator += (Complex<_Tp>& a, const Complex<_Tp>& b) +{ + a.re += b.re; a.im += b.im; + return a; +} + +template static inline +Complex<_Tp> operator - (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + return Complex<_Tp>( a.re - b.re, a.im - b.im ); +} + +template static inline +Complex<_Tp>& operator -= (Complex<_Tp>& a, const Complex<_Tp>& b) +{ + a.re -= b.re; a.im -= b.im; + return a; +} + +template static inline +Complex<_Tp> operator - (const Complex<_Tp>& a) +{ + return Complex<_Tp>(-a.re, -a.im); +} + +template static inline +Complex<_Tp> operator * (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + return Complex<_Tp>( a.re*b.re - a.im*b.im, a.re*b.im + a.im*b.re ); +} + +template static inline +Complex<_Tp> operator * (const Complex<_Tp>& a, _Tp b) +{ + return Complex<_Tp>( a.re*b, a.im*b ); +} + +template static inline +Complex<_Tp> operator * (_Tp b, const Complex<_Tp>& a) +{ + return Complex<_Tp>( a.re*b, a.im*b ); +} + +template static inline +Complex<_Tp> operator + (const Complex<_Tp>& a, _Tp b) +{ + return Complex<_Tp>( a.re + b, a.im ); +} + +template static inline +Complex<_Tp> operator - (const Complex<_Tp>& a, _Tp b) +{ return Complex<_Tp>( a.re - b, a.im ); } + +template static inline +Complex<_Tp> operator + (_Tp b, const Complex<_Tp>& a) +{ + return Complex<_Tp>( a.re + b, a.im ); +} + +template static inline +Complex<_Tp> operator - (_Tp b, const Complex<_Tp>& a) +{ + return Complex<_Tp>( b - a.re, -a.im ); +} + +template static inline +Complex<_Tp>& operator += (Complex<_Tp>& a, _Tp b) +{ + a.re += b; return a; +} + +template static inline +Complex<_Tp>& operator -= (Complex<_Tp>& a, _Tp b) +{ + a.re -= b; return a; +} + +template static inline +Complex<_Tp>& operator *= (Complex<_Tp>& a, _Tp b) +{ + a.re *= b; a.im *= b; return a; +} + +template static inline +double abs(const Complex<_Tp>& a) +{ + return std::sqrt( (double)a.re*a.re + (double)a.im*a.im); +} + +template static inline +Complex<_Tp> operator / (const Complex<_Tp>& a, const Complex<_Tp>& b) +{ + double t = 1./((double)b.re*b.re + (double)b.im*b.im); + return Complex<_Tp>( (_Tp)((a.re*b.re + a.im*b.im)*t), + (_Tp)((-a.re*b.im + a.im*b.re)*t) ); +} + +template static inline +Complex<_Tp>& operator /= (Complex<_Tp>& a, const Complex<_Tp>& b) +{ + a = a / b; + return a; +} + +template static inline +Complex<_Tp> operator / (const Complex<_Tp>& a, _Tp b) +{ + _Tp t = (_Tp)1/b; + return Complex<_Tp>( a.re*t, a.im*t ); +} + +template static inline +Complex<_Tp> operator / (_Tp b, const Complex<_Tp>& a) +{ + return Complex<_Tp>(b)/a; +} + +template static inline +Complex<_Tp> operator /= (const Complex<_Tp>& a, _Tp b) +{ + _Tp t = (_Tp)1/b; + a.re *= t; a.im *= t; return a; +} + + + +//////////////////////////////// 2D Point /////////////////////////////// + +template inline +Point_<_Tp>::Point_() + : x(0), y(0) {} + +template inline +Point_<_Tp>::Point_(_Tp _x, _Tp _y) + : x(_x), y(_y) {} + +template inline +Point_<_Tp>::Point_(const Point_& pt) + : x(pt.x), y(pt.y) {} + +template inline +Point_<_Tp>::Point_(const Size_<_Tp>& sz) + : x(sz.width), y(sz.height) {} + +template inline +Point_<_Tp>::Point_(const Vec<_Tp,2>& v) + : x(v[0]), y(v[1]) {} + +template inline +Point_<_Tp>& Point_<_Tp>::operator = (const Point_& pt) +{ + x = pt.x; y = pt.y; + return *this; +} + +template template inline +Point_<_Tp>::operator Point_<_Tp2>() const +{ + return Point_<_Tp2>(saturate_cast<_Tp2>(x), saturate_cast<_Tp2>(y)); +} + +template inline +Point_<_Tp>::operator Vec<_Tp, 2>() const +{ + return Vec<_Tp, 2>(x, y); +} + +template inline +_Tp Point_<_Tp>::dot(const Point_& pt) const +{ + return saturate_cast<_Tp>(x*pt.x + y*pt.y); +} + +template inline +double Point_<_Tp>::ddot(const Point_& pt) const +{ + return (double)x*pt.x + (double)y*pt.y; +} + +template inline +double Point_<_Tp>::cross(const Point_& pt) const +{ + return (double)x*pt.y - (double)y*pt.x; +} + +template inline bool +Point_<_Tp>::inside( const Rect_<_Tp>& r ) const +{ + return r.contains(*this); +} + + +template static inline +Point_<_Tp>& operator += (Point_<_Tp>& a, const Point_<_Tp>& b) +{ + a.x += b.x; + a.y += b.y; + return a; +} + +template static inline +Point_<_Tp>& operator -= (Point_<_Tp>& a, const Point_<_Tp>& b) +{ + a.x -= b.x; + a.y -= b.y; + return a; +} + +template static inline +Point_<_Tp>& operator *= (Point_<_Tp>& a, int b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + return a; +} + +template static inline +Point_<_Tp>& operator *= (Point_<_Tp>& a, float b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + return a; +} + +template static inline +Point_<_Tp>& operator *= (Point_<_Tp>& a, double b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + return a; +} + +template static inline +Point_<_Tp>& operator /= (Point_<_Tp>& a, int b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + return a; +} + +template static inline +Point_<_Tp>& operator /= (Point_<_Tp>& a, float b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + return a; +} + +template static inline +Point_<_Tp>& operator /= (Point_<_Tp>& a, double b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + return a; +} + +template static inline +double norm(const Point_<_Tp>& pt) +{ + return std::sqrt((double)pt.x*pt.x + (double)pt.y*pt.y); +} + +template static inline +bool operator == (const Point_<_Tp>& a, const Point_<_Tp>& b) +{ + return a.x == b.x && a.y == b.y; +} + +template static inline +bool operator != (const Point_<_Tp>& a, const Point_<_Tp>& b) +{ + return a.x != b.x || a.y != b.y; +} + +template static inline +Point_<_Tp> operator + (const Point_<_Tp>& a, const Point_<_Tp>& b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(a.x + b.x), saturate_cast<_Tp>(a.y + b.y) ); +} + +template static inline +Point_<_Tp> operator - (const Point_<_Tp>& a, const Point_<_Tp>& b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(a.x - b.x), saturate_cast<_Tp>(a.y - b.y) ); +} + +template static inline +Point_<_Tp> operator - (const Point_<_Tp>& a) +{ + return Point_<_Tp>( saturate_cast<_Tp>(-a.x), saturate_cast<_Tp>(-a.y) ); +} + +template static inline +Point_<_Tp> operator * (const Point_<_Tp>& a, int b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(a.x*b), saturate_cast<_Tp>(a.y*b) ); +} + +template static inline +Point_<_Tp> operator * (int a, const Point_<_Tp>& b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(b.x*a), saturate_cast<_Tp>(b.y*a) ); +} + +template static inline +Point_<_Tp> operator * (const Point_<_Tp>& a, float b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(a.x*b), saturate_cast<_Tp>(a.y*b) ); +} + +template static inline +Point_<_Tp> operator * (float a, const Point_<_Tp>& b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(b.x*a), saturate_cast<_Tp>(b.y*a) ); +} + +template static inline +Point_<_Tp> operator * (const Point_<_Tp>& a, double b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(a.x*b), saturate_cast<_Tp>(a.y*b) ); +} + +template static inline +Point_<_Tp> operator * (double a, const Point_<_Tp>& b) +{ + return Point_<_Tp>( saturate_cast<_Tp>(b.x*a), saturate_cast<_Tp>(b.y*a) ); +} + +template static inline +Point_<_Tp> operator * (const Matx<_Tp, 2, 2>& a, const Point_<_Tp>& b) +{ + Matx<_Tp, 2, 1> tmp = a * Vec<_Tp,2>(b.x, b.y); + return Point_<_Tp>(tmp.val[0], tmp.val[1]); +} + +template static inline +Point3_<_Tp> operator * (const Matx<_Tp, 3, 3>& a, const Point_<_Tp>& b) +{ + Matx<_Tp, 3, 1> tmp = a * Vec<_Tp,3>(b.x, b.y, 1); + return Point3_<_Tp>(tmp.val[0], tmp.val[1], tmp.val[2]); +} + +template static inline +Point_<_Tp> operator / (const Point_<_Tp>& a, int b) +{ + Point_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + +template static inline +Point_<_Tp> operator / (const Point_<_Tp>& a, float b) +{ + Point_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + +template static inline +Point_<_Tp> operator / (const Point_<_Tp>& a, double b) +{ + Point_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + + +template static inline _AccTp normL2Sqr(const Point_& pt); +template static inline _AccTp normL2Sqr(const Point_& pt); +template static inline _AccTp normL2Sqr(const Point_& pt); +template static inline _AccTp normL2Sqr(const Point_& pt); + +template<> inline int normL2Sqr(const Point_& pt) { return pt.dot(pt); } +template<> inline int64 normL2Sqr(const Point_& pt) { return pt.dot(pt); } +template<> inline float normL2Sqr(const Point_& pt) { return pt.dot(pt); } +template<> inline double normL2Sqr(const Point_& pt) { return pt.dot(pt); } + +template<> inline double normL2Sqr(const Point_& pt) { return pt.ddot(pt); } +template<> inline double normL2Sqr(const Point_& pt) { return pt.ddot(pt); } + + + +//////////////////////////////// 3D Point /////////////////////////////// + +template inline +Point3_<_Tp>::Point3_() + : x(0), y(0), z(0) {} + +template inline +Point3_<_Tp>::Point3_(_Tp _x, _Tp _y, _Tp _z) + : x(_x), y(_y), z(_z) {} + +template inline +Point3_<_Tp>::Point3_(const Point3_& pt) + : x(pt.x), y(pt.y), z(pt.z) {} + +template inline +Point3_<_Tp>::Point3_(const Point_<_Tp>& pt) + : x(pt.x), y(pt.y), z(_Tp()) {} + +template inline +Point3_<_Tp>::Point3_(const Vec<_Tp, 3>& v) + : x(v[0]), y(v[1]), z(v[2]) {} + +template template inline +Point3_<_Tp>::operator Point3_<_Tp2>() const +{ + return Point3_<_Tp2>(saturate_cast<_Tp2>(x), saturate_cast<_Tp2>(y), saturate_cast<_Tp2>(z)); +} + +#if OPENCV_ABI_COMPATIBILITY > 300 +template template inline +Point3_<_Tp>::operator Vec<_Tp2, 3>() const +{ + return Vec<_Tp2, 3>(x, y, z); +} +#else +template inline +Point3_<_Tp>::operator Vec<_Tp, 3>() const +{ + return Vec<_Tp, 3>(x, y, z); +} +#endif + +template inline +Point3_<_Tp>& Point3_<_Tp>::operator = (const Point3_& pt) +{ + x = pt.x; y = pt.y; z = pt.z; + return *this; +} + +template inline +_Tp Point3_<_Tp>::dot(const Point3_& pt) const +{ + return saturate_cast<_Tp>(x*pt.x + y*pt.y + z*pt.z); +} + +template inline +double Point3_<_Tp>::ddot(const Point3_& pt) const +{ + return (double)x*pt.x + (double)y*pt.y + (double)z*pt.z; +} + +template inline +Point3_<_Tp> Point3_<_Tp>::cross(const Point3_<_Tp>& pt) const +{ + return Point3_<_Tp>(y*pt.z - z*pt.y, z*pt.x - x*pt.z, x*pt.y - y*pt.x); +} + + +template static inline +Point3_<_Tp>& operator += (Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + a.x += b.x; + a.y += b.y; + a.z += b.z; + return a; +} + +template static inline +Point3_<_Tp>& operator -= (Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + a.x -= b.x; + a.y -= b.y; + a.z -= b.z; + return a; +} + +template static inline +Point3_<_Tp>& operator *= (Point3_<_Tp>& a, int b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + a.z = saturate_cast<_Tp>(a.z * b); + return a; +} + +template static inline +Point3_<_Tp>& operator *= (Point3_<_Tp>& a, float b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + a.z = saturate_cast<_Tp>(a.z * b); + return a; +} + +template static inline +Point3_<_Tp>& operator *= (Point3_<_Tp>& a, double b) +{ + a.x = saturate_cast<_Tp>(a.x * b); + a.y = saturate_cast<_Tp>(a.y * b); + a.z = saturate_cast<_Tp>(a.z * b); + return a; +} + +template static inline +Point3_<_Tp>& operator /= (Point3_<_Tp>& a, int b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + a.z = saturate_cast<_Tp>(a.z / b); + return a; +} + +template static inline +Point3_<_Tp>& operator /= (Point3_<_Tp>& a, float b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + a.z = saturate_cast<_Tp>(a.z / b); + return a; +} + +template static inline +Point3_<_Tp>& operator /= (Point3_<_Tp>& a, double b) +{ + a.x = saturate_cast<_Tp>(a.x / b); + a.y = saturate_cast<_Tp>(a.y / b); + a.z = saturate_cast<_Tp>(a.z / b); + return a; +} + +template static inline +double norm(const Point3_<_Tp>& pt) +{ + return std::sqrt((double)pt.x*pt.x + (double)pt.y*pt.y + (double)pt.z*pt.z); +} + +template static inline +bool operator == (const Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + return a.x == b.x && a.y == b.y && a.z == b.z; +} + +template static inline +bool operator != (const Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + return a.x != b.x || a.y != b.y || a.z != b.z; +} + +template static inline +Point3_<_Tp> operator + (const Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(a.x + b.x), saturate_cast<_Tp>(a.y + b.y), saturate_cast<_Tp>(a.z + b.z)); +} + +template static inline +Point3_<_Tp> operator - (const Point3_<_Tp>& a, const Point3_<_Tp>& b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(a.x - b.x), saturate_cast<_Tp>(a.y - b.y), saturate_cast<_Tp>(a.z - b.z)); +} + +template static inline +Point3_<_Tp> operator - (const Point3_<_Tp>& a) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(-a.x), saturate_cast<_Tp>(-a.y), saturate_cast<_Tp>(-a.z) ); +} + +template static inline +Point3_<_Tp> operator * (const Point3_<_Tp>& a, int b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(a.x*b), saturate_cast<_Tp>(a.y*b), saturate_cast<_Tp>(a.z*b) ); +} + +template static inline +Point3_<_Tp> operator * (int a, const Point3_<_Tp>& b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(b.x * a), saturate_cast<_Tp>(b.y * a), saturate_cast<_Tp>(b.z * a) ); +} + +template static inline +Point3_<_Tp> operator * (const Point3_<_Tp>& a, float b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(a.x * b), saturate_cast<_Tp>(a.y * b), saturate_cast<_Tp>(a.z * b) ); +} + +template static inline +Point3_<_Tp> operator * (float a, const Point3_<_Tp>& b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(b.x * a), saturate_cast<_Tp>(b.y * a), saturate_cast<_Tp>(b.z * a) ); +} + +template static inline +Point3_<_Tp> operator * (const Point3_<_Tp>& a, double b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(a.x * b), saturate_cast<_Tp>(a.y * b), saturate_cast<_Tp>(a.z * b) ); +} + +template static inline +Point3_<_Tp> operator * (double a, const Point3_<_Tp>& b) +{ + return Point3_<_Tp>( saturate_cast<_Tp>(b.x * a), saturate_cast<_Tp>(b.y * a), saturate_cast<_Tp>(b.z * a) ); +} + +template static inline +Point3_<_Tp> operator * (const Matx<_Tp, 3, 3>& a, const Point3_<_Tp>& b) +{ + Matx<_Tp, 3, 1> tmp = a * Vec<_Tp,3>(b.x, b.y, b.z); + return Point3_<_Tp>(tmp.val[0], tmp.val[1], tmp.val[2]); +} + +template static inline +Matx<_Tp, 4, 1> operator * (const Matx<_Tp, 4, 4>& a, const Point3_<_Tp>& b) +{ + return a * Matx<_Tp, 4, 1>(b.x, b.y, b.z, 1); +} + +template static inline +Point3_<_Tp> operator / (const Point3_<_Tp>& a, int b) +{ + Point3_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + +template static inline +Point3_<_Tp> operator / (const Point3_<_Tp>& a, float b) +{ + Point3_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + +template static inline +Point3_<_Tp> operator / (const Point3_<_Tp>& a, double b) +{ + Point3_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + + + +////////////////////////////////// Size ///////////////////////////////// + +template inline +Size_<_Tp>::Size_() + : width(0), height(0) {} + +template inline +Size_<_Tp>::Size_(_Tp _width, _Tp _height) + : width(_width), height(_height) {} + +template inline +Size_<_Tp>::Size_(const Size_& sz) + : width(sz.width), height(sz.height) {} + +template inline +Size_<_Tp>::Size_(const Point_<_Tp>& pt) + : width(pt.x), height(pt.y) {} + +template template inline +Size_<_Tp>::operator Size_<_Tp2>() const +{ + return Size_<_Tp2>(saturate_cast<_Tp2>(width), saturate_cast<_Tp2>(height)); +} + +template inline +Size_<_Tp>& Size_<_Tp>::operator = (const Size_<_Tp>& sz) +{ + width = sz.width; height = sz.height; + return *this; +} + +template inline +_Tp Size_<_Tp>::area() const +{ + const _Tp result = width * height; + CV_DbgAssert(!std::numeric_limits<_Tp>::is_integer + || width == 0 || result / width == height); // make sure the result fits in the return value + return result; +} + +template inline +bool Size_<_Tp>::empty() const +{ + return width <= 0 || height <= 0; +} + + +template static inline +Size_<_Tp>& operator *= (Size_<_Tp>& a, _Tp b) +{ + a.width *= b; + a.height *= b; + return a; +} + +template static inline +Size_<_Tp> operator * (const Size_<_Tp>& a, _Tp b) +{ + Size_<_Tp> tmp(a); + tmp *= b; + return tmp; +} + +template static inline +Size_<_Tp>& operator /= (Size_<_Tp>& a, _Tp b) +{ + a.width /= b; + a.height /= b; + return a; +} + +template static inline +Size_<_Tp> operator / (const Size_<_Tp>& a, _Tp b) +{ + Size_<_Tp> tmp(a); + tmp /= b; + return tmp; +} + +template static inline +Size_<_Tp>& operator += (Size_<_Tp>& a, const Size_<_Tp>& b) +{ + a.width += b.width; + a.height += b.height; + return a; +} + +template static inline +Size_<_Tp> operator + (const Size_<_Tp>& a, const Size_<_Tp>& b) +{ + Size_<_Tp> tmp(a); + tmp += b; + return tmp; +} + +template static inline +Size_<_Tp>& operator -= (Size_<_Tp>& a, const Size_<_Tp>& b) +{ + a.width -= b.width; + a.height -= b.height; + return a; +} + +template static inline +Size_<_Tp> operator - (const Size_<_Tp>& a, const Size_<_Tp>& b) +{ + Size_<_Tp> tmp(a); + tmp -= b; + return tmp; +} + +template static inline +bool operator == (const Size_<_Tp>& a, const Size_<_Tp>& b) +{ + return a.width == b.width && a.height == b.height; +} + +template static inline +bool operator != (const Size_<_Tp>& a, const Size_<_Tp>& b) +{ + return !(a == b); +} + + + +////////////////////////////////// Rect ///////////////////////////////// + +template inline +Rect_<_Tp>::Rect_() + : x(0), y(0), width(0), height(0) {} + +template inline +Rect_<_Tp>::Rect_(_Tp _x, _Tp _y, _Tp _width, _Tp _height) + : x(_x), y(_y), width(_width), height(_height) {} + +template inline +Rect_<_Tp>::Rect_(const Rect_<_Tp>& r) + : x(r.x), y(r.y), width(r.width), height(r.height) {} + +template inline +Rect_<_Tp>::Rect_(const Point_<_Tp>& org, const Size_<_Tp>& sz) + : x(org.x), y(org.y), width(sz.width), height(sz.height) {} + +template inline +Rect_<_Tp>::Rect_(const Point_<_Tp>& pt1, const Point_<_Tp>& pt2) +{ + x = std::min(pt1.x, pt2.x); + y = std::min(pt1.y, pt2.y); + width = std::max(pt1.x, pt2.x) - x; + height = std::max(pt1.y, pt2.y) - y; +} + +template inline +Rect_<_Tp>& Rect_<_Tp>::operator = ( const Rect_<_Tp>& r ) +{ + x = r.x; + y = r.y; + width = r.width; + height = r.height; + return *this; +} + +template inline +Point_<_Tp> Rect_<_Tp>::tl() const +{ + return Point_<_Tp>(x,y); +} + +template inline +Point_<_Tp> Rect_<_Tp>::br() const +{ + return Point_<_Tp>(x + width, y + height); +} + +template inline +Size_<_Tp> Rect_<_Tp>::size() const +{ + return Size_<_Tp>(width, height); +} + +template inline +_Tp Rect_<_Tp>::area() const +{ + const _Tp result = width * height; + CV_DbgAssert(!std::numeric_limits<_Tp>::is_integer + || width == 0 || result / width == height); // make sure the result fits in the return value + return result; +} + +template inline +bool Rect_<_Tp>::empty() const +{ + return width <= 0 || height <= 0; +} + +template template inline +Rect_<_Tp>::operator Rect_<_Tp2>() const +{ + return Rect_<_Tp2>(saturate_cast<_Tp2>(x), saturate_cast<_Tp2>(y), saturate_cast<_Tp2>(width), saturate_cast<_Tp2>(height)); +} + +template inline +bool Rect_<_Tp>::contains(const Point_<_Tp>& pt) const +{ + return x <= pt.x && pt.x < x + width && y <= pt.y && pt.y < y + height; +} + + +template static inline +Rect_<_Tp>& operator += ( Rect_<_Tp>& a, const Point_<_Tp>& b ) +{ + a.x += b.x; + a.y += b.y; + return a; +} + +template static inline +Rect_<_Tp>& operator -= ( Rect_<_Tp>& a, const Point_<_Tp>& b ) +{ + a.x -= b.x; + a.y -= b.y; + return a; +} + +template static inline +Rect_<_Tp>& operator += ( Rect_<_Tp>& a, const Size_<_Tp>& b ) +{ + a.width += b.width; + a.height += b.height; + return a; +} + +template static inline +Rect_<_Tp>& operator -= ( Rect_<_Tp>& a, const Size_<_Tp>& b ) +{ + const _Tp width = a.width - b.width; + const _Tp height = a.height - b.height; + CV_DbgAssert(width >= 0 && height >= 0); + a.width = width; + a.height = height; + return a; +} + +template static inline +Rect_<_Tp>& operator &= ( Rect_<_Tp>& a, const Rect_<_Tp>& b ) +{ + _Tp x1 = std::max(a.x, b.x); + _Tp y1 = std::max(a.y, b.y); + a.width = std::min(a.x + a.width, b.x + b.width) - x1; + a.height = std::min(a.y + a.height, b.y + b.height) - y1; + a.x = x1; + a.y = y1; + if( a.width <= 0 || a.height <= 0 ) + a = Rect(); + return a; +} + +template static inline +Rect_<_Tp>& operator |= ( Rect_<_Tp>& a, const Rect_<_Tp>& b ) +{ + if (a.empty()) { + a = b; + } + else if (!b.empty()) { + _Tp x1 = std::min(a.x, b.x); + _Tp y1 = std::min(a.y, b.y); + a.width = std::max(a.x + a.width, b.x + b.width) - x1; + a.height = std::max(a.y + a.height, b.y + b.height) - y1; + a.x = x1; + a.y = y1; + } + return a; +} + +template static inline +bool operator == (const Rect_<_Tp>& a, const Rect_<_Tp>& b) +{ + return a.x == b.x && a.y == b.y && a.width == b.width && a.height == b.height; +} + +template static inline +bool operator != (const Rect_<_Tp>& a, const Rect_<_Tp>& b) +{ + return a.x != b.x || a.y != b.y || a.width != b.width || a.height != b.height; +} + +template static inline +Rect_<_Tp> operator + (const Rect_<_Tp>& a, const Point_<_Tp>& b) +{ + return Rect_<_Tp>( a.x + b.x, a.y + b.y, a.width, a.height ); +} + +template static inline +Rect_<_Tp> operator - (const Rect_<_Tp>& a, const Point_<_Tp>& b) +{ + return Rect_<_Tp>( a.x - b.x, a.y - b.y, a.width, a.height ); +} + +template static inline +Rect_<_Tp> operator + (const Rect_<_Tp>& a, const Size_<_Tp>& b) +{ + return Rect_<_Tp>( a.x, a.y, a.width + b.width, a.height + b.height ); +} + +template static inline +Rect_<_Tp> operator - (const Rect_<_Tp>& a, const Size_<_Tp>& b) +{ + const _Tp width = a.width - b.width; + const _Tp height = a.height - b.height; + CV_DbgAssert(width >= 0 && height >= 0); + return Rect_<_Tp>( a.x, a.y, width, height ); +} + +template static inline +Rect_<_Tp> operator & (const Rect_<_Tp>& a, const Rect_<_Tp>& b) +{ + Rect_<_Tp> c = a; + return c &= b; +} + +template static inline +Rect_<_Tp> operator | (const Rect_<_Tp>& a, const Rect_<_Tp>& b) +{ + Rect_<_Tp> c = a; + return c |= b; +} + +/** + * @brief measure dissimilarity between two sample sets + * + * computes the complement of the Jaccard Index as described in . + * For rectangles this reduces to computing the intersection over the union. + */ +template static inline +double jaccardDistance(const Rect_<_Tp>& a, const Rect_<_Tp>& b) { + _Tp Aa = a.area(); + _Tp Ab = b.area(); + + if ((Aa + Ab) <= std::numeric_limits<_Tp>::epsilon()) { + // jaccard_index = 1 -> distance = 0 + return 0.0; + } + + double Aab = (a & b).area(); + // distance = 1 - jaccard_index + return 1.0 - Aab / (Aa + Ab - Aab); +} + +////////////////////////////// RotatedRect ////////////////////////////// + +inline +RotatedRect::RotatedRect() + : center(), size(), angle(0) {} + +inline +RotatedRect::RotatedRect(const Point2f& _center, const Size2f& _size, float _angle) + : center(_center), size(_size), angle(_angle) {} + + + +///////////////////////////////// Range ///////////////////////////////// + +inline +Range::Range() + : start(0), end(0) {} + +inline +Range::Range(int _start, int _end) + : start(_start), end(_end) {} + +inline +int Range::size() const +{ + return end - start; +} + +inline +bool Range::empty() const +{ + return start == end; +} + +inline +Range Range::all() +{ + return Range(INT_MIN, INT_MAX); +} + + +static inline +bool operator == (const Range& r1, const Range& r2) +{ + return r1.start == r2.start && r1.end == r2.end; +} + +static inline +bool operator != (const Range& r1, const Range& r2) +{ + return !(r1 == r2); +} + +static inline +bool operator !(const Range& r) +{ + return r.start == r.end; +} + +static inline +Range operator & (const Range& r1, const Range& r2) +{ + Range r(std::max(r1.start, r2.start), std::min(r1.end, r2.end)); + r.end = std::max(r.end, r.start); + return r; +} + +static inline +Range& operator &= (Range& r1, const Range& r2) +{ + r1 = r1 & r2; + return r1; +} + +static inline +Range operator + (const Range& r1, int delta) +{ + return Range(r1.start + delta, r1.end + delta); +} + +static inline +Range operator + (int delta, const Range& r1) +{ + return Range(r1.start + delta, r1.end + delta); +} + +static inline +Range operator - (const Range& r1, int delta) +{ + return r1 + (-delta); +} + + + +///////////////////////////////// Scalar //////////////////////////////// + +template inline +Scalar_<_Tp>::Scalar_() +{ + this->val[0] = this->val[1] = this->val[2] = this->val[3] = 0; +} + +template inline +Scalar_<_Tp>::Scalar_(_Tp v0, _Tp v1, _Tp v2, _Tp v3) +{ + this->val[0] = v0; + this->val[1] = v1; + this->val[2] = v2; + this->val[3] = v3; +} + +template template inline +Scalar_<_Tp>::Scalar_(const Vec<_Tp2, cn>& v) +{ + int i; + for( i = 0; i < (cn < 4 ? cn : 4); i++ ) + this->val[i] = cv::saturate_cast<_Tp>(v.val[i]); + for( ; i < 4; i++ ) + this->val[i] = 0; +} + +template inline +Scalar_<_Tp>::Scalar_(_Tp v0) +{ + this->val[0] = v0; + this->val[1] = this->val[2] = this->val[3] = 0; +} + +template inline +Scalar_<_Tp> Scalar_<_Tp>::all(_Tp v0) +{ + return Scalar_<_Tp>(v0, v0, v0, v0); +} + + +template inline +Scalar_<_Tp> Scalar_<_Tp>::mul(const Scalar_<_Tp>& a, double scale ) const +{ + return Scalar_<_Tp>(saturate_cast<_Tp>(this->val[0] * a.val[0] * scale), + saturate_cast<_Tp>(this->val[1] * a.val[1] * scale), + saturate_cast<_Tp>(this->val[2] * a.val[2] * scale), + saturate_cast<_Tp>(this->val[3] * a.val[3] * scale)); +} + +template inline +Scalar_<_Tp> Scalar_<_Tp>::conj() const +{ + return Scalar_<_Tp>(saturate_cast<_Tp>( this->val[0]), + saturate_cast<_Tp>(-this->val[1]), + saturate_cast<_Tp>(-this->val[2]), + saturate_cast<_Tp>(-this->val[3])); +} + +template inline +bool Scalar_<_Tp>::isReal() const +{ + return this->val[1] == 0 && this->val[2] == 0 && this->val[3] == 0; +} + + +template template inline +Scalar_<_Tp>::operator Scalar_() const +{ + return Scalar_(saturate_cast(this->val[0]), + saturate_cast(this->val[1]), + saturate_cast(this->val[2]), + saturate_cast(this->val[3])); +} + + +template static inline +Scalar_<_Tp>& operator += (Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + a.val[0] += b.val[0]; + a.val[1] += b.val[1]; + a.val[2] += b.val[2]; + a.val[3] += b.val[3]; + return a; +} + +template static inline +Scalar_<_Tp>& operator -= (Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + a.val[0] -= b.val[0]; + a.val[1] -= b.val[1]; + a.val[2] -= b.val[2]; + a.val[3] -= b.val[3]; + return a; +} + +template static inline +Scalar_<_Tp>& operator *= ( Scalar_<_Tp>& a, _Tp v ) +{ + a.val[0] *= v; + a.val[1] *= v; + a.val[2] *= v; + a.val[3] *= v; + return a; +} + +template static inline +bool operator == ( const Scalar_<_Tp>& a, const Scalar_<_Tp>& b ) +{ + return a.val[0] == b.val[0] && a.val[1] == b.val[1] && + a.val[2] == b.val[2] && a.val[3] == b.val[3]; +} + +template static inline +bool operator != ( const Scalar_<_Tp>& a, const Scalar_<_Tp>& b ) +{ + return a.val[0] != b.val[0] || a.val[1] != b.val[1] || + a.val[2] != b.val[2] || a.val[3] != b.val[3]; +} + +template static inline +Scalar_<_Tp> operator + (const Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + return Scalar_<_Tp>(a.val[0] + b.val[0], + a.val[1] + b.val[1], + a.val[2] + b.val[2], + a.val[3] + b.val[3]); +} + +template static inline +Scalar_<_Tp> operator - (const Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + return Scalar_<_Tp>(saturate_cast<_Tp>(a.val[0] - b.val[0]), + saturate_cast<_Tp>(a.val[1] - b.val[1]), + saturate_cast<_Tp>(a.val[2] - b.val[2]), + saturate_cast<_Tp>(a.val[3] - b.val[3])); +} + +template static inline +Scalar_<_Tp> operator * (const Scalar_<_Tp>& a, _Tp alpha) +{ + return Scalar_<_Tp>(a.val[0] * alpha, + a.val[1] * alpha, + a.val[2] * alpha, + a.val[3] * alpha); +} + +template static inline +Scalar_<_Tp> operator * (_Tp alpha, const Scalar_<_Tp>& a) +{ + return a*alpha; +} + +template static inline +Scalar_<_Tp> operator - (const Scalar_<_Tp>& a) +{ + return Scalar_<_Tp>(saturate_cast<_Tp>(-a.val[0]), + saturate_cast<_Tp>(-a.val[1]), + saturate_cast<_Tp>(-a.val[2]), + saturate_cast<_Tp>(-a.val[3])); +} + + +template static inline +Scalar_<_Tp> operator * (const Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + return Scalar_<_Tp>(saturate_cast<_Tp>(a[0]*b[0] - a[1]*b[1] - a[2]*b[2] - a[3]*b[3]), + saturate_cast<_Tp>(a[0]*b[1] + a[1]*b[0] + a[2]*b[3] - a[3]*b[2]), + saturate_cast<_Tp>(a[0]*b[2] - a[1]*b[3] + a[2]*b[0] + a[3]*b[1]), + saturate_cast<_Tp>(a[0]*b[3] + a[1]*b[2] - a[2]*b[1] + a[3]*b[0])); +} + +template static inline +Scalar_<_Tp>& operator *= (Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + a = a * b; + return a; +} + +template static inline +Scalar_<_Tp> operator / (const Scalar_<_Tp>& a, _Tp alpha) +{ + return Scalar_<_Tp>(a.val[0] / alpha, + a.val[1] / alpha, + a.val[2] / alpha, + a.val[3] / alpha); +} + +template static inline +Scalar_ operator / (const Scalar_& a, float alpha) +{ + float s = 1 / alpha; + return Scalar_(a.val[0] * s, a.val[1] * s, a.val[2] * s, a.val[3] * s); +} + +template static inline +Scalar_ operator / (const Scalar_& a, double alpha) +{ + double s = 1 / alpha; + return Scalar_(a.val[0] * s, a.val[1] * s, a.val[2] * s, a.val[3] * s); +} + +template static inline +Scalar_<_Tp>& operator /= (Scalar_<_Tp>& a, _Tp alpha) +{ + a = a / alpha; + return a; +} + +template static inline +Scalar_<_Tp> operator / (_Tp a, const Scalar_<_Tp>& b) +{ + _Tp s = a / (b[0]*b[0] + b[1]*b[1] + b[2]*b[2] + b[3]*b[3]); + return b.conj() * s; +} + +template static inline +Scalar_<_Tp> operator / (const Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + return a * ((_Tp)1 / b); +} + +template static inline +Scalar_<_Tp>& operator /= (Scalar_<_Tp>& a, const Scalar_<_Tp>& b) +{ + a = a / b; + return a; +} + +template static inline +Scalar operator * (const Matx<_Tp, 4, 4>& a, const Scalar& b) +{ + Matx c((Matx)a, b, Matx_MatMulOp()); + return reinterpret_cast(c); +} + +template<> inline +Scalar operator * (const Matx& a, const Scalar& b) +{ + Matx c(a, b, Matx_MatMulOp()); + return reinterpret_cast(c); +} + + + +//////////////////////////////// KeyPoint /////////////////////////////// + +inline +KeyPoint::KeyPoint() + : pt(0,0), size(0), angle(-1), response(0), octave(0), class_id(-1) {} + +inline +KeyPoint::KeyPoint(Point2f _pt, float _size, float _angle, float _response, int _octave, int _class_id) + : pt(_pt), size(_size), angle(_angle), response(_response), octave(_octave), class_id(_class_id) {} + +inline +KeyPoint::KeyPoint(float x, float y, float _size, float _angle, float _response, int _octave, int _class_id) + : pt(x, y), size(_size), angle(_angle), response(_response), octave(_octave), class_id(_class_id) {} + + + +///////////////////////////////// DMatch //////////////////////////////// + +inline +DMatch::DMatch() + : queryIdx(-1), trainIdx(-1), imgIdx(-1), distance(FLT_MAX) {} + +inline +DMatch::DMatch(int _queryIdx, int _trainIdx, float _distance) + : queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(-1), distance(_distance) {} + +inline +DMatch::DMatch(int _queryIdx, int _trainIdx, int _imgIdx, float _distance) + : queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(_imgIdx), distance(_distance) {} + +inline +bool DMatch::operator < (const DMatch &m) const +{ + return distance < m.distance; +} + + + +////////////////////////////// TermCriteria ///////////////////////////// + +inline +TermCriteria::TermCriteria() + : type(0), maxCount(0), epsilon(0) {} + +inline +TermCriteria::TermCriteria(int _type, int _maxCount, double _epsilon) + : type(_type), maxCount(_maxCount), epsilon(_epsilon) {} + +//! @endcond + +} // cv + +#endif //OPENCV_CORE_TYPES_HPP diff --git a/3rdparty/opencv/include/opencv2/core/types_c.h b/3rdparty/opencv/include/opencv2/core/types_c.h new file mode 100644 index 00000000..5f63eb8f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/types_c.h @@ -0,0 +1,2139 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_TYPES_H +#define OPENCV_CORE_TYPES_H + +#if !defined(__OPENCV_BUILD) && !defined(CV__DISABLE_C_API_CTORS) +#define CV__ENABLE_C_API_CTORS // enable C API ctors (must be removed) +#endif + +//#define CV__VALIDATE_UNUNITIALIZED_VARS 1 // C++11 & GCC only + +#ifdef __cplusplus + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS +#pragma GCC diagnostic ignored "-Wmissing-field-initializers" +#define CV_STRUCT_INITIALIZER {0,} +#else +#if defined(__GNUC__) && __GNUC__ == 4 // GCC 4.x warns on "= {}" initialization, fixed in GCC 5.0 +#pragma GCC diagnostic ignored "-Wmissing-field-initializers" +#endif +#define CV_STRUCT_INITIALIZER {} +#endif + +#else +#define CV_STRUCT_INITIALIZER {0} +#endif + + +#ifdef HAVE_IPL +# ifndef __IPL_H__ +# if defined _WIN32 +# include +# else +# include +# endif +# endif +#elif defined __IPL_H__ +# define HAVE_IPL +#endif + +#include "opencv2/core/cvdef.h" + +#ifndef SKIP_INCLUDES +#include +#include +#include +#include +#endif // SKIP_INCLUDES + +#if defined _WIN32 +# define CV_CDECL __cdecl +# define CV_STDCALL __stdcall +#else +# define CV_CDECL +# define CV_STDCALL +#endif + +#ifndef CV_DEFAULT +# ifdef __cplusplus +# define CV_DEFAULT(val) = val +# else +# define CV_DEFAULT(val) +# endif +#endif + +#ifndef CV_EXTERN_C_FUNCPTR +# ifdef __cplusplus +# define CV_EXTERN_C_FUNCPTR(x) extern "C" { typedef x; } +# else +# define CV_EXTERN_C_FUNCPTR(x) typedef x +# endif +#endif + +#ifndef CVAPI +# define CVAPI(rettype) CV_EXTERN_C CV_EXPORTS rettype CV_CDECL +#endif + +#ifndef CV_IMPL +# define CV_IMPL CV_EXTERN_C +#endif + +#ifdef __cplusplus +# include "opencv2/core.hpp" +#endif + +/** @addtogroup core_c + @{ +*/ + +/** @brief This is the "metatype" used *only* as a function parameter. + +It denotes that the function accepts arrays of multiple types, such as IplImage*, CvMat* or even +CvSeq* sometimes. The particular array type is determined at runtime by analyzing the first 4 +bytes of the header. In C++ interface the role of CvArr is played by InputArray and OutputArray. + */ +typedef void CvArr; + +typedef int CVStatus; + +/** @see cv::Error::Code */ +enum { + CV_StsOk= 0, /**< everything is ok */ + CV_StsBackTrace= -1, /**< pseudo error for back trace */ + CV_StsError= -2, /**< unknown /unspecified error */ + CV_StsInternal= -3, /**< internal error (bad state) */ + CV_StsNoMem= -4, /**< insufficient memory */ + CV_StsBadArg= -5, /**< function arg/param is bad */ + CV_StsBadFunc= -6, /**< unsupported function */ + CV_StsNoConv= -7, /**< iter. didn't converge */ + CV_StsAutoTrace= -8, /**< tracing */ + CV_HeaderIsNull= -9, /**< image header is NULL */ + CV_BadImageSize= -10, /**< image size is invalid */ + CV_BadOffset= -11, /**< offset is invalid */ + CV_BadDataPtr= -12, /**/ + CV_BadStep= -13, /**< image step is wrong, this may happen for a non-continuous matrix */ + CV_BadModelOrChSeq= -14, /**/ + CV_BadNumChannels= -15, /**< bad number of channels, for example, some functions accept only single channel matrices */ + CV_BadNumChannel1U= -16, /**/ + CV_BadDepth= -17, /**< input image depth is not supported by the function */ + CV_BadAlphaChannel= -18, /**/ + CV_BadOrder= -19, /**< number of dimensions is out of range */ + CV_BadOrigin= -20, /**< incorrect input origin */ + CV_BadAlign= -21, /**< incorrect input align */ + CV_BadCallBack= -22, /**/ + CV_BadTileSize= -23, /**/ + CV_BadCOI= -24, /**< input COI is not supported */ + CV_BadROISize= -25, /**< incorrect input roi */ + CV_MaskIsTiled= -26, /**/ + CV_StsNullPtr= -27, /**< null pointer */ + CV_StsVecLengthErr= -28, /**< incorrect vector length */ + CV_StsFilterStructContentErr= -29, /**< incorrect filter structure content */ + CV_StsKernelStructContentErr= -30, /**< incorrect transform kernel content */ + CV_StsFilterOffsetErr= -31, /**< incorrect filter offset value */ + CV_StsBadSize= -201, /**< the input/output structure size is incorrect */ + CV_StsDivByZero= -202, /**< division by zero */ + CV_StsInplaceNotSupported= -203, /**< in-place operation is not supported */ + CV_StsObjectNotFound= -204, /**< request can't be completed */ + CV_StsUnmatchedFormats= -205, /**< formats of input/output arrays differ */ + CV_StsBadFlag= -206, /**< flag is wrong or not supported */ + CV_StsBadPoint= -207, /**< bad CvPoint */ + CV_StsBadMask= -208, /**< bad format of mask (neither 8uC1 nor 8sC1)*/ + CV_StsUnmatchedSizes= -209, /**< sizes of input/output structures do not match */ + CV_StsUnsupportedFormat= -210, /**< the data format/type is not supported by the function*/ + CV_StsOutOfRange= -211, /**< some of parameters are out of range */ + CV_StsParseError= -212, /**< invalid syntax/structure of the parsed file */ + CV_StsNotImplemented= -213, /**< the requested function/feature is not implemented */ + CV_StsBadMemBlock= -214, /**< an allocated block has been corrupted */ + CV_StsAssert= -215, /**< assertion failed */ + CV_GpuNotSupported= -216, /**< no CUDA support */ + CV_GpuApiCallError= -217, /**< GPU API call error */ + CV_OpenGlNotSupported= -218, /**< no OpenGL support */ + CV_OpenGlApiCallError= -219, /**< OpenGL API call error */ + CV_OpenCLApiCallError= -220, /**< OpenCL API call error */ + CV_OpenCLDoubleNotSupported= -221, + CV_OpenCLInitError= -222, /**< OpenCL initialization error */ + CV_OpenCLNoAMDBlasFft= -223 +}; + +/****************************************************************************************\ +* Common macros and inline functions * +\****************************************************************************************/ + +#define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t)) + +/** min & max without jumps */ +#define CV_IMIN(a, b) ((a) ^ (((a)^(b)) & (((a) < (b)) - 1))) + +#define CV_IMAX(a, b) ((a) ^ (((a)^(b)) & (((a) > (b)) - 1))) + +/** absolute value without jumps */ +#ifndef __cplusplus +# define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0)) +#else +# define CV_IABS(a) abs(a) +#endif +#define CV_CMP(a,b) (((a) > (b)) - ((a) < (b))) +#define CV_SIGN(a) CV_CMP((a),0) + +#define cvInvSqrt(value) ((float)(1./sqrt(value))) +#define cvSqrt(value) ((float)sqrt(value)) + + +/*************** Random number generation *******************/ + +typedef uint64 CvRNG; + +#define CV_RNG_COEFF 4164903690U + +/** @brief Initializes a random number generator state. + +The function initializes a random number generator and returns the state. The pointer to the state +can be then passed to the cvRandInt, cvRandReal and cvRandArr functions. In the current +implementation a multiply-with-carry generator is used. +@param seed 64-bit value used to initiate a random sequence +@sa the C++ class RNG replaced CvRNG. + */ +CV_INLINE CvRNG cvRNG( int64 seed CV_DEFAULT(-1)) +{ + CvRNG rng = seed ? (uint64)seed : (uint64)(int64)-1; + return rng; +} + +/** @brief Returns a 32-bit unsigned integer and updates RNG. + +The function returns a uniformly-distributed random 32-bit unsigned integer and updates the RNG +state. It is similar to the rand() function from the C runtime library, except that OpenCV functions +always generates a 32-bit random number, regardless of the platform. +@param rng CvRNG state initialized by cvRNG. + */ +CV_INLINE unsigned cvRandInt( CvRNG* rng ) +{ + uint64 temp = *rng; + temp = (uint64)(unsigned)temp*CV_RNG_COEFF + (temp >> 32); + *rng = temp; + return (unsigned)temp; +} + +/** @brief Returns a floating-point random number and updates RNG. + +The function returns a uniformly-distributed random floating-point number between 0 and 1 (1 is not +included). +@param rng RNG state initialized by cvRNG + */ +CV_INLINE double cvRandReal( CvRNG* rng ) +{ + return cvRandInt(rng)*2.3283064365386962890625e-10 /* 2^-32 */; +} + +/****************************************************************************************\ +* Image type (IplImage) * +\****************************************************************************************/ + +#ifndef HAVE_IPL + +/* + * The following definitions (until #endif) + * is an extract from IPL headers. + * Copyright (c) 1995 Intel Corporation. + */ +#define IPL_DEPTH_SIGN 0x80000000 + +#define IPL_DEPTH_1U 1 +#define IPL_DEPTH_8U 8 +#define IPL_DEPTH_16U 16 +#define IPL_DEPTH_32F 32 + +#define IPL_DEPTH_8S (IPL_DEPTH_SIGN| 8) +#define IPL_DEPTH_16S (IPL_DEPTH_SIGN|16) +#define IPL_DEPTH_32S (IPL_DEPTH_SIGN|32) + +#define IPL_DATA_ORDER_PIXEL 0 +#define IPL_DATA_ORDER_PLANE 1 + +#define IPL_ORIGIN_TL 0 +#define IPL_ORIGIN_BL 1 + +#define IPL_ALIGN_4BYTES 4 +#define IPL_ALIGN_8BYTES 8 +#define IPL_ALIGN_16BYTES 16 +#define IPL_ALIGN_32BYTES 32 + +#define IPL_ALIGN_DWORD IPL_ALIGN_4BYTES +#define IPL_ALIGN_QWORD IPL_ALIGN_8BYTES + +#define IPL_BORDER_CONSTANT 0 +#define IPL_BORDER_REPLICATE 1 +#define IPL_BORDER_REFLECT 2 +#define IPL_BORDER_WRAP 3 + +#ifdef __cplusplus +typedef struct _IplImage IplImage; +CV_EXPORTS _IplImage cvIplImage(const cv::Mat& m); +#endif + +/** The IplImage is taken from the Intel Image Processing Library, in which the format is native. OpenCV +only supports a subset of possible IplImage formats, as outlined in the parameter list above. + +In addition to the above restrictions, OpenCV handles ROIs differently. OpenCV functions require +that the image size or ROI size of all source and destination images match exactly. On the other +hand, the Intel Image Processing Library processes the area of intersection between the source and +destination images (or ROIs), allowing them to vary independently. +*/ +typedef struct +_IplImage +{ + int nSize; /**< sizeof(IplImage) */ + int ID; /**< version (=0)*/ + int nChannels; /**< Most of OpenCV functions support 1,2,3 or 4 channels */ + int alphaChannel; /**< Ignored by OpenCV */ + int depth; /**< Pixel depth in bits: IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16S, + IPL_DEPTH_32S, IPL_DEPTH_32F and IPL_DEPTH_64F are supported. */ + char colorModel[4]; /**< Ignored by OpenCV */ + char channelSeq[4]; /**< ditto */ + int dataOrder; /**< 0 - interleaved color channels, 1 - separate color channels. + cvCreateImage can only create interleaved images */ + int origin; /**< 0 - top-left origin, + 1 - bottom-left origin (Windows bitmaps style). */ + int align; /**< Alignment of image rows (4 or 8). + OpenCV ignores it and uses widthStep instead. */ + int width; /**< Image width in pixels. */ + int height; /**< Image height in pixels. */ + struct _IplROI *roi; /**< Image ROI. If NULL, the whole image is selected. */ + struct _IplImage *maskROI; /**< Must be NULL. */ + void *imageId; /**< " " */ + struct _IplTileInfo *tileInfo; /**< " " */ + int imageSize; /**< Image data size in bytes + (==image->height*image->widthStep + in case of interleaved data)*/ + char *imageData; /**< Pointer to aligned image data. */ + int widthStep; /**< Size of aligned image row in bytes. */ + int BorderMode[4]; /**< Ignored by OpenCV. */ + int BorderConst[4]; /**< Ditto. */ + char *imageDataOrigin; /**< Pointer to very origin of image data + (not necessarily aligned) - + needed for correct deallocation */ + +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + _IplImage() {} + _IplImage(const cv::Mat& m) { *this = cvIplImage(m); } +#endif +} +IplImage; + +CV_INLINE IplImage cvIplImage() +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + IplImage self = CV_STRUCT_INITIALIZER; self.nSize = sizeof(IplImage); return self; +#else + return _IplImage(); +#endif +} + +typedef struct _IplTileInfo IplTileInfo; + +typedef struct _IplROI +{ + int coi; /**< 0 - no COI (all channels are selected), 1 - 0th channel is selected ...*/ + int xOffset; + int yOffset; + int width; + int height; +} +IplROI; + +typedef struct _IplConvKernel +{ + int nCols; + int nRows; + int anchorX; + int anchorY; + int *values; + int nShiftR; +} +IplConvKernel; + +typedef struct _IplConvKernelFP +{ + int nCols; + int nRows; + int anchorX; + int anchorY; + float *values; +} +IplConvKernelFP; + +#define IPL_IMAGE_HEADER 1 +#define IPL_IMAGE_DATA 2 +#define IPL_IMAGE_ROI 4 + +#endif/*HAVE_IPL*/ + +/** extra border mode */ +#define IPL_BORDER_REFLECT_101 4 +#define IPL_BORDER_TRANSPARENT 5 + +#define IPL_IMAGE_MAGIC_VAL ((int)sizeof(IplImage)) +#define CV_TYPE_NAME_IMAGE "opencv-image" + +#define CV_IS_IMAGE_HDR(img) \ + ((img) != NULL && ((const IplImage*)(img))->nSize == sizeof(IplImage)) + +#define CV_IS_IMAGE(img) \ + (CV_IS_IMAGE_HDR(img) && ((IplImage*)img)->imageData != NULL) + +/** for storing double-precision + floating point data in IplImage's */ +#define IPL_DEPTH_64F 64 + +/** get reference to pixel at (col,row), + for multi-channel images (col) should be multiplied by number of channels */ +#define CV_IMAGE_ELEM( image, elemtype, row, col ) \ + (((elemtype*)((image)->imageData + (image)->widthStep*(row)))[(col)]) + +/****************************************************************************************\ +* Matrix type (CvMat) * +\****************************************************************************************/ + +#define CV_AUTO_STEP 0x7fffffff +#define CV_WHOLE_ARR cvSlice( 0, 0x3fffffff ) + +#define CV_MAGIC_MASK 0xFFFF0000 +#define CV_MAT_MAGIC_VAL 0x42420000 +#define CV_TYPE_NAME_MAT "opencv-matrix" + +#ifdef __cplusplus +typedef struct CvMat CvMat; +CV_INLINE CvMat cvMat(const cv::Mat& m); +#endif + +/** Matrix elements are stored row by row. Element (i, j) (i - 0-based row index, j - 0-based column +index) of a matrix can be retrieved or modified using CV_MAT_ELEM macro: + + uchar pixval = CV_MAT_ELEM(grayimg, uchar, i, j) + CV_MAT_ELEM(cameraMatrix, float, 0, 2) = image.width*0.5f; + +To access multiple-channel matrices, you can use +CV_MAT_ELEM(matrix, type, i, j\*nchannels + channel_idx). + +@deprecated CvMat is now obsolete; consider using Mat instead. + */ +typedef struct CvMat +{ + int type; + int step; + + /* for internal use only */ + int* refcount; + int hdr_refcount; + + union + { + uchar* ptr; + short* s; + int* i; + float* fl; + double* db; + } data; + +#ifdef __cplusplus + union + { + int rows; + int height; + }; + + union + { + int cols; + int width; + }; +#else + int rows; + int cols; +#endif + +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvMat() {} + CvMat(const cv::Mat& m) { *this = cvMat(m); } +#endif +} +CvMat; + + +#define CV_IS_MAT_HDR(mat) \ + ((mat) != NULL && \ + (((const CvMat*)(mat))->type & CV_MAGIC_MASK) == CV_MAT_MAGIC_VAL && \ + ((const CvMat*)(mat))->cols > 0 && ((const CvMat*)(mat))->rows > 0) + +#define CV_IS_MAT_HDR_Z(mat) \ + ((mat) != NULL && \ + (((const CvMat*)(mat))->type & CV_MAGIC_MASK) == CV_MAT_MAGIC_VAL && \ + ((const CvMat*)(mat))->cols >= 0 && ((const CvMat*)(mat))->rows >= 0) + +#define CV_IS_MAT(mat) \ + (CV_IS_MAT_HDR(mat) && ((const CvMat*)(mat))->data.ptr != NULL) + +#define CV_IS_MASK_ARR(mat) \ + (((mat)->type & (CV_MAT_TYPE_MASK & ~CV_8SC1)) == 0) + +#define CV_ARE_TYPES_EQ(mat1, mat2) \ + ((((mat1)->type ^ (mat2)->type) & CV_MAT_TYPE_MASK) == 0) + +#define CV_ARE_CNS_EQ(mat1, mat2) \ + ((((mat1)->type ^ (mat2)->type) & CV_MAT_CN_MASK) == 0) + +#define CV_ARE_DEPTHS_EQ(mat1, mat2) \ + ((((mat1)->type ^ (mat2)->type) & CV_MAT_DEPTH_MASK) == 0) + +#define CV_ARE_SIZES_EQ(mat1, mat2) \ + ((mat1)->rows == (mat2)->rows && (mat1)->cols == (mat2)->cols) + +#define CV_IS_MAT_CONST(mat) \ + (((mat)->rows|(mat)->cols) == 1) + +#define IPL2CV_DEPTH(depth) \ + ((((CV_8U)+(CV_16U<<4)+(CV_32F<<8)+(CV_64F<<16)+(CV_8S<<20)+ \ + (CV_16S<<24)+(CV_32S<<28)) >> ((((depth) & 0xF0) >> 2) + \ + (((depth) & IPL_DEPTH_SIGN) ? 20 : 0))) & 15) + +/** Inline constructor. No data is allocated internally!!! + * (Use together with cvCreateData, or use cvCreateMat instead to + * get a matrix with allocated data): + */ +CV_INLINE CvMat cvMat( int rows, int cols, int type, void* data CV_DEFAULT(NULL)) +{ + CvMat m; + + assert( (unsigned)CV_MAT_DEPTH(type) <= CV_64F ); + type = CV_MAT_TYPE(type); + m.type = CV_MAT_MAGIC_VAL | CV_MAT_CONT_FLAG | type; + m.cols = cols; + m.rows = rows; + m.step = m.cols*CV_ELEM_SIZE(type); + m.data.ptr = (uchar*)data; + m.refcount = NULL; + m.hdr_refcount = 0; + + return m; +} + +#ifdef __cplusplus + +CV_INLINE CvMat cvMat(const cv::Mat& m) +{ + CvMat self; + CV_DbgAssert(m.dims <= 2); + self = cvMat(m.rows, m.dims == 1 ? 1 : m.cols, m.type(), m.data); + self.step = (int)m.step[0]; + self.type = (self.type & ~cv::Mat::CONTINUOUS_FLAG) | (m.flags & cv::Mat::CONTINUOUS_FLAG); + return self; +} +CV_INLINE CvMat cvMat() +{ +#if !defined(CV__ENABLE_C_API_CTORS) + CvMat self = CV_STRUCT_INITIALIZER; return self; +#else + return CvMat(); +#endif +} +CV_INLINE CvMat cvMat(const CvMat& m) +{ +#if !defined(CV__ENABLE_C_API_CTORS) + CvMat self = CV_STRUCT_INITIALIZER; memcpy(&self, &m, sizeof(self)); return self; +#else + return CvMat(m); +#endif +} + +#endif // __cplusplus + + +#define CV_MAT_ELEM_PTR_FAST( mat, row, col, pix_size ) \ + (assert( (unsigned)(row) < (unsigned)(mat).rows && \ + (unsigned)(col) < (unsigned)(mat).cols ), \ + (mat).data.ptr + (size_t)(mat).step*(row) + (pix_size)*(col)) + +#define CV_MAT_ELEM_PTR( mat, row, col ) \ + CV_MAT_ELEM_PTR_FAST( mat, row, col, CV_ELEM_SIZE((mat).type) ) + +#define CV_MAT_ELEM( mat, elemtype, row, col ) \ + (*(elemtype*)CV_MAT_ELEM_PTR_FAST( mat, row, col, sizeof(elemtype))) + +/** @brief Returns the particular element of single-channel floating-point matrix. + +The function is a fast replacement for cvGetReal2D in the case of single-channel floating-point +matrices. It is faster because it is inline, it does fewer checks for array type and array element +type, and it checks for the row and column ranges only in debug mode. +@param mat Input matrix +@param row The zero-based index of row +@param col The zero-based index of column + */ +CV_INLINE double cvmGet( const CvMat* mat, int row, int col ) +{ + int type; + + type = CV_MAT_TYPE(mat->type); + assert( (unsigned)row < (unsigned)mat->rows && + (unsigned)col < (unsigned)mat->cols ); + + if( type == CV_32FC1 ) + return ((float*)(void*)(mat->data.ptr + (size_t)mat->step*row))[col]; + else + { + assert( type == CV_64FC1 ); + return ((double*)(void*)(mat->data.ptr + (size_t)mat->step*row))[col]; + } +} + +/** @brief Sets a specific element of a single-channel floating-point matrix. + +The function is a fast replacement for cvSetReal2D in the case of single-channel floating-point +matrices. It is faster because it is inline, it does fewer checks for array type and array element +type, and it checks for the row and column ranges only in debug mode. +@param mat The matrix +@param row The zero-based index of row +@param col The zero-based index of column +@param value The new value of the matrix element + */ +CV_INLINE void cvmSet( CvMat* mat, int row, int col, double value ) +{ + int type; + type = CV_MAT_TYPE(mat->type); + assert( (unsigned)row < (unsigned)mat->rows && + (unsigned)col < (unsigned)mat->cols ); + + if( type == CV_32FC1 ) + ((float*)(void*)(mat->data.ptr + (size_t)mat->step*row))[col] = (float)value; + else + { + assert( type == CV_64FC1 ); + ((double*)(void*)(mat->data.ptr + (size_t)mat->step*row))[col] = value; + } +} + + +CV_INLINE int cvIplDepth( int type ) +{ + int depth = CV_MAT_DEPTH(type); + return CV_ELEM_SIZE1(depth)*8 | (depth == CV_8S || depth == CV_16S || + depth == CV_32S ? IPL_DEPTH_SIGN : 0); +} + + +/****************************************************************************************\ +* Multi-dimensional dense array (CvMatND) * +\****************************************************************************************/ + +#define CV_MATND_MAGIC_VAL 0x42430000 +#define CV_TYPE_NAME_MATND "opencv-nd-matrix" + +#define CV_MAX_DIM 32 + +#ifdef __cplusplus +typedef struct CvMatND CvMatND; +CV_EXPORTS CvMatND cvMatND(const cv::Mat& m); +#endif + +/** + @deprecated consider using cv::Mat instead + */ +typedef struct +CvMatND +{ + int type; + int dims; + + int* refcount; + int hdr_refcount; + + union + { + uchar* ptr; + float* fl; + double* db; + int* i; + short* s; + } data; + + struct + { + int size; + int step; + } + dim[CV_MAX_DIM]; + +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvMatND() {} + CvMatND(const cv::Mat& m) { *this = cvMatND(m); } +#endif +} +CvMatND; + + +CV_INLINE CvMatND cvMatND() +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvMatND self = CV_STRUCT_INITIALIZER; return self; +#else + return CvMatND(); +#endif +} + +#define CV_IS_MATND_HDR(mat) \ + ((mat) != NULL && (((const CvMatND*)(mat))->type & CV_MAGIC_MASK) == CV_MATND_MAGIC_VAL) + +#define CV_IS_MATND(mat) \ + (CV_IS_MATND_HDR(mat) && ((const CvMatND*)(mat))->data.ptr != NULL) + + +/****************************************************************************************\ +* Multi-dimensional sparse array (CvSparseMat) * +\****************************************************************************************/ + +#define CV_SPARSE_MAT_MAGIC_VAL 0x42440000 +#define CV_TYPE_NAME_SPARSE_MAT "opencv-sparse-matrix" + +struct CvSet; + +typedef struct CvSparseMat +{ + int type; + int dims; + int* refcount; + int hdr_refcount; + + struct CvSet* heap; + void** hashtable; + int hashsize; + int valoffset; + int idxoffset; + int size[CV_MAX_DIM]; + +#ifdef __cplusplus + CV_EXPORTS void copyToSparseMat(cv::SparseMat& m) const; +#endif +} +CvSparseMat; + +#ifdef __cplusplus +CV_EXPORTS CvSparseMat* cvCreateSparseMat(const cv::SparseMat& m); +#endif + +#define CV_IS_SPARSE_MAT_HDR(mat) \ + ((mat) != NULL && \ + (((const CvSparseMat*)(mat))->type & CV_MAGIC_MASK) == CV_SPARSE_MAT_MAGIC_VAL) + +#define CV_IS_SPARSE_MAT(mat) \ + CV_IS_SPARSE_MAT_HDR(mat) + +/**************** iteration through a sparse array *****************/ + +typedef struct CvSparseNode +{ + unsigned hashval; + struct CvSparseNode* next; +} +CvSparseNode; + +typedef struct CvSparseMatIterator +{ + CvSparseMat* mat; + CvSparseNode* node; + int curidx; +} +CvSparseMatIterator; + +#define CV_NODE_VAL(mat,node) ((void*)((uchar*)(node) + (mat)->valoffset)) +#define CV_NODE_IDX(mat,node) ((int*)((uchar*)(node) + (mat)->idxoffset)) + +/****************************************************************************************\ +* Histogram * +\****************************************************************************************/ + +typedef int CvHistType; + +#define CV_HIST_MAGIC_VAL 0x42450000 +#define CV_HIST_UNIFORM_FLAG (1 << 10) + +/** indicates whether bin ranges are set already or not */ +#define CV_HIST_RANGES_FLAG (1 << 11) + +#define CV_HIST_ARRAY 0 +#define CV_HIST_SPARSE 1 +#define CV_HIST_TREE CV_HIST_SPARSE + +/** should be used as a parameter only, + it turns to CV_HIST_UNIFORM_FLAG of hist->type */ +#define CV_HIST_UNIFORM 1 + +typedef struct CvHistogram +{ + int type; + CvArr* bins; + float thresh[CV_MAX_DIM][2]; /**< For uniform histograms. */ + float** thresh2; /**< For non-uniform histograms. */ + CvMatND mat; /**< Embedded matrix header for array histograms. */ +} +CvHistogram; + +#define CV_IS_HIST( hist ) \ + ((hist) != NULL && \ + (((CvHistogram*)(hist))->type & CV_MAGIC_MASK) == CV_HIST_MAGIC_VAL && \ + (hist)->bins != NULL) + +#define CV_IS_UNIFORM_HIST( hist ) \ + (((hist)->type & CV_HIST_UNIFORM_FLAG) != 0) + +#define CV_IS_SPARSE_HIST( hist ) \ + CV_IS_SPARSE_MAT((hist)->bins) + +#define CV_HIST_HAS_RANGES( hist ) \ + (((hist)->type & CV_HIST_RANGES_FLAG) != 0) + +/****************************************************************************************\ +* Other supplementary data type definitions * +\****************************************************************************************/ + +/*************************************** CvRect *****************************************/ +/** @sa Rect_ */ +typedef struct CvRect +{ + int x; + int y; + int width; + int height; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvRect() __attribute__(( warning("Non-initialized variable") )) {}; + template CvRect(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 4); + x = y = width = height = 0; + if (list.size() == 4) + { + x = list.begin()[0]; y = list.begin()[1]; width = list.begin()[2]; height = list.begin()[3]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvRect(int _x = 0, int _y = 0, int w = 0, int h = 0): x(_x), y(_y), width(w), height(h) {} + template + CvRect(const cv::Rect_<_Tp>& r): x(cv::saturate_cast(r.x)), y(cv::saturate_cast(r.y)), width(cv::saturate_cast(r.width)), height(cv::saturate_cast(r.height)) {} +#endif +#ifdef __cplusplus + template + operator cv::Rect_<_Tp>() const { return cv::Rect_<_Tp>((_Tp)x, (_Tp)y, (_Tp)width, (_Tp)height); } +#endif +} +CvRect; + +/** constructs CvRect structure. */ +CV_INLINE CvRect cvRect( int x, int y, int width, int height ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvRect r = {x, y, width, height}; +#else + CvRect r(x, y , width, height); +#endif + return r; +} +#ifdef __cplusplus +CV_INLINE CvRect cvRect(const cv::Rect& rc) { return cvRect(rc.x, rc.y, rc.width, rc.height); } +#endif + +CV_INLINE IplROI cvRectToROI( CvRect rect, int coi ) +{ + IplROI roi; + roi.xOffset = rect.x; + roi.yOffset = rect.y; + roi.width = rect.width; + roi.height = rect.height; + roi.coi = coi; + + return roi; +} + + +CV_INLINE CvRect cvROIToRect( IplROI roi ) +{ + return cvRect( roi.xOffset, roi.yOffset, roi.width, roi.height ); +} + +/*********************************** CvTermCriteria *************************************/ + +#define CV_TERMCRIT_ITER 1 +#define CV_TERMCRIT_NUMBER CV_TERMCRIT_ITER +#define CV_TERMCRIT_EPS 2 + +/** @sa TermCriteria + */ +typedef struct CvTermCriteria +{ + int type; /**< may be combination of + CV_TERMCRIT_ITER + CV_TERMCRIT_EPS */ + int max_iter; + double epsilon; +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvTermCriteria(int _type = 0, int _iter = 0, double _eps = 0) : type(_type), max_iter(_iter), epsilon(_eps) {} + CvTermCriteria(const cv::TermCriteria& t) : type(t.type), max_iter(t.maxCount), epsilon(t.epsilon) {} +#endif +#ifdef __cplusplus + operator cv::TermCriteria() const { return cv::TermCriteria(type, max_iter, epsilon); } +#endif +} +CvTermCriteria; + +CV_INLINE CvTermCriteria cvTermCriteria( int type, int max_iter, double epsilon ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvTermCriteria t = { type, max_iter, (float)epsilon}; +#else + CvTermCriteria t(type, max_iter, epsilon); +#endif + return t; +} +#ifdef __cplusplus +CV_INLINE CvTermCriteria cvTermCriteria(const cv::TermCriteria& t) { return cvTermCriteria(t.type, t.maxCount, t.epsilon); } +#endif + + +/******************************* CvPoint and variants ***********************************/ + +typedef struct CvPoint +{ + int x; + int y; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvPoint() __attribute__(( warning("Non-initialized variable") )) {} + template CvPoint(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + x = y = 0; + if (list.size() == 2) + { + x = list.begin()[0]; y = list.begin()[1]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvPoint(int _x = 0, int _y = 0): x(_x), y(_y) {} + template + CvPoint(const cv::Point_<_Tp>& pt): x((int)pt.x), y((int)pt.y) {} +#endif +#ifdef __cplusplus + template + operator cv::Point_<_Tp>() const { return cv::Point_<_Tp>(cv::saturate_cast<_Tp>(x), cv::saturate_cast<_Tp>(y)); } +#endif +} +CvPoint; + +/** constructs CvPoint structure. */ +CV_INLINE CvPoint cvPoint( int x, int y ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint p = {x, y}; +#else + CvPoint p(x, y); +#endif + return p; +} +#ifdef __cplusplus +CV_INLINE CvPoint cvPoint(const cv::Point& pt) { return cvPoint(pt.x, pt.y); } +#endif + +typedef struct CvPoint2D32f +{ + float x; + float y; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvPoint2D32f() __attribute__(( warning("Non-initialized variable") )) {} + template CvPoint2D32f(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + x = y = 0; + if (list.size() == 2) + { + x = list.begin()[0]; y = list.begin()[1]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvPoint2D32f(float _x = 0, float _y = 0): x(_x), y(_y) {} + template + CvPoint2D32f(const cv::Point_<_Tp>& pt): x((float)pt.x), y((float)pt.y) {} +#endif +#ifdef __cplusplus + template + operator cv::Point_<_Tp>() const { return cv::Point_<_Tp>(cv::saturate_cast<_Tp>(x), cv::saturate_cast<_Tp>(y)); } +#endif +} +CvPoint2D32f; + +/** constructs CvPoint2D32f structure. */ +CV_INLINE CvPoint2D32f cvPoint2D32f( double x, double y ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint2D32f p = { (float)x, (float)y }; +#else + CvPoint2D32f p((float)x, (float)y); +#endif + return p; +} + +#ifdef __cplusplus +template +CvPoint2D32f cvPoint2D32f(const cv::Point_<_Tp>& pt) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint2D32f p = { (float)pt.x, (float)pt.y }; +#else + CvPoint2D32f p((float)pt.x, (float)pt.y); +#endif + return p; +} +#endif + +/** converts CvPoint to CvPoint2D32f. */ +CV_INLINE CvPoint2D32f cvPointTo32f( CvPoint point ) +{ + return cvPoint2D32f( (float)point.x, (float)point.y ); +} + +/** converts CvPoint2D32f to CvPoint. */ +CV_INLINE CvPoint cvPointFrom32f( CvPoint2D32f point ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint ipt = { cvRound(point.x), cvRound(point.y) }; +#else + CvPoint ipt(cvRound(point.x), cvRound(point.y)); +#endif + return ipt; +} + + +typedef struct CvPoint3D32f +{ + float x; + float y; + float z; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvPoint3D32f() __attribute__(( warning("Non-initialized variable") )) {} + template CvPoint3D32f(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 3); + x = y = z = 0; + if (list.size() == 3) + { + x = list.begin()[0]; y = list.begin()[1]; z = list.begin()[2]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvPoint3D32f(float _x = 0, float _y = 0, float _z = 0): x(_x), y(_y), z(_z) {} + template + CvPoint3D32f(const cv::Point3_<_Tp>& pt): x((float)pt.x), y((float)pt.y), z((float)pt.z) {} +#endif +#ifdef __cplusplus + template + operator cv::Point3_<_Tp>() const { return cv::Point3_<_Tp>(cv::saturate_cast<_Tp>(x), cv::saturate_cast<_Tp>(y), cv::saturate_cast<_Tp>(z)); } +#endif +} +CvPoint3D32f; + +/** constructs CvPoint3D32f structure. */ +CV_INLINE CvPoint3D32f cvPoint3D32f( double x, double y, double z ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint3D32f p = { (float)x, (float)y, (float)z }; +#else + CvPoint3D32f p((float)x, (float)y, (float)z); +#endif + return p; +} + +#ifdef __cplusplus +template +CvPoint3D32f cvPoint3D32f(const cv::Point3_<_Tp>& pt) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvPoint3D32f p = { (float)pt.x, (float)pt.y, (float)pt.z }; +#else + CvPoint3D32f p((float)pt.x, (float)pt.y, (float)pt.z); +#endif + return p; +} +#endif + + +typedef struct CvPoint2D64f +{ + double x; + double y; +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvPoint2D64f() __attribute__(( warning("Non-initialized variable") )) {} + template CvPoint2D64f(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + x = y = 0; + if (list.size() == 2) + { + x = list.begin()[0]; y = list.begin()[1]; + } + }; +#endif +} +CvPoint2D64f; + +/** constructs CvPoint2D64f structure.*/ +CV_INLINE CvPoint2D64f cvPoint2D64f( double x, double y ) +{ + CvPoint2D64f p = { x, y }; + return p; +} + + +typedef struct CvPoint3D64f +{ + double x; + double y; + double z; +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvPoint3D64f() __attribute__(( warning("Non-initialized variable") )) {} + template CvPoint3D64f(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 3); + x = y = z = 0; + if (list.size() == 3) + { + x = list.begin()[0]; y = list.begin()[1]; z = list.begin()[2]; + } + }; +#endif +} +CvPoint3D64f; + +/** constructs CvPoint3D64f structure. */ +CV_INLINE CvPoint3D64f cvPoint3D64f( double x, double y, double z ) +{ + CvPoint3D64f p = { x, y, z }; + return p; +} + + +/******************************** CvSize's & CvBox **************************************/ + +typedef struct CvSize +{ + int width; + int height; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvSize() __attribute__(( warning("Non-initialized variable") )) {} + template CvSize(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + width = 0; height = 0; + if (list.size() == 2) + { + width = list.begin()[0]; height = list.begin()[1]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvSize(int w = 0, int h = 0): width(w), height(h) {} + template + CvSize(const cv::Size_<_Tp>& sz): width(cv::saturate_cast(sz.width)), height(cv::saturate_cast(sz.height)) {} +#endif +#ifdef __cplusplus + template + operator cv::Size_<_Tp>() const { return cv::Size_<_Tp>(cv::saturate_cast<_Tp>(width), cv::saturate_cast<_Tp>(height)); } +#endif +} +CvSize; + +/** constructs CvSize structure. */ +CV_INLINE CvSize cvSize( int width, int height ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvSize s = { width, height }; +#else + CvSize s(width, height); +#endif + return s; +} + +#ifdef __cplusplus +CV_INLINE CvSize cvSize(const cv::Size& sz) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvSize s = { sz.width, sz.height }; +#else + CvSize s(sz.width, sz.height); +#endif + return s; +} +#endif + +typedef struct CvSize2D32f +{ + float width; + float height; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvSize2D32f() __attribute__(( warning("Non-initialized variable") )) {} + template CvSize2D32f(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + width = 0; height = 0; + if (list.size() == 2) + { + width = list.begin()[0]; height = list.begin()[1]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvSize2D32f(float w = 0, float h = 0): width(w), height(h) {} + template + CvSize2D32f(const cv::Size_<_Tp>& sz): width(cv::saturate_cast(sz.width)), height(cv::saturate_cast(sz.height)) {} +#endif +#ifdef __cplusplus + template + operator cv::Size_<_Tp>() const { return cv::Size_<_Tp>(cv::saturate_cast<_Tp>(width), cv::saturate_cast<_Tp>(height)); } +#endif +} +CvSize2D32f; + +/** constructs CvSize2D32f structure. */ +CV_INLINE CvSize2D32f cvSize2D32f( double width, double height ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvSize2D32f s = { (float)width, (float)height }; +#else + CvSize2D32f s((float)width, (float)height); +#endif + return s; +} +#ifdef __cplusplus +template +CvSize2D32f cvSize2D32f(const cv::Size_<_Tp>& sz) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvSize2D32f s = { (float)sz.width, (float)sz.height }; +#else + CvSize2D32f s((float)sz.width, (float)sz.height); +#endif + return s; +} +#endif + +/** @sa RotatedRect + */ +typedef struct CvBox2D +{ + CvPoint2D32f center; /**< Center of the box. */ + CvSize2D32f size; /**< Box width and length. */ + float angle; /**< Angle between the horizontal axis */ + /**< and the first side (i.e. length) in degrees */ + +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvBox2D(CvPoint2D32f c = CvPoint2D32f(), CvSize2D32f s = CvSize2D32f(), float a = 0) : center(c), size(s), angle(a) {} + CvBox2D(const cv::RotatedRect& rr) : center(rr.center), size(rr.size), angle(rr.angle) {} +#endif +#ifdef __cplusplus + operator cv::RotatedRect() const { return cv::RotatedRect(center, size, angle); } +#endif +} +CvBox2D; + + +#ifdef __cplusplus +CV_INLINE CvBox2D cvBox2D(CvPoint2D32f c = CvPoint2D32f(), CvSize2D32f s = CvSize2D32f(), float a = 0) +{ + CvBox2D self; + self.center = c; + self.size = s; + self.angle = a; + return self; +} +CV_INLINE CvBox2D cvBox2D(const cv::RotatedRect& rr) +{ + CvBox2D self; + self.center = cvPoint2D32f(rr.center); + self.size = cvSize2D32f(rr.size); + self.angle = rr.angle; + return self; +} +#endif + + +/** Line iterator state: */ +typedef struct CvLineIterator +{ + /** Pointer to the current point: */ + uchar* ptr; + + /* Bresenham algorithm state: */ + int err; + int plus_delta; + int minus_delta; + int plus_step; + int minus_step; +} +CvLineIterator; + + + +/************************************* CvSlice ******************************************/ +#define CV_WHOLE_SEQ_END_INDEX 0x3fffffff +#define CV_WHOLE_SEQ cvSlice(0, CV_WHOLE_SEQ_END_INDEX) + +typedef struct CvSlice +{ + int start_index, end_index; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvSlice() __attribute__(( warning("Non-initialized variable") )) {} + template CvSlice(const std::initializer_list<_Tp> list) + { + CV_Assert(list.size() == 0 || list.size() == 2); + start_index = end_index = 0; + if (list.size() == 2) + { + start_index = list.begin()[0]; end_index = list.begin()[1]; + } + }; +#endif +#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) && !defined(__CUDACC__) + CvSlice(int start = 0, int end = 0) : start_index(start), end_index(end) {} + CvSlice(const cv::Range& r) { *this = (r.start != INT_MIN && r.end != INT_MAX) ? CvSlice(r.start, r.end) : CvSlice(0, CV_WHOLE_SEQ_END_INDEX); } + operator cv::Range() const { return (start_index == 0 && end_index == CV_WHOLE_SEQ_END_INDEX ) ? cv::Range::all() : cv::Range(start_index, end_index); } +#endif +} +CvSlice; + +CV_INLINE CvSlice cvSlice( int start, int end ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) && !defined(__CUDACC__)) + CvSlice slice = { start, end }; +#else + CvSlice slice(start, end); +#endif + return slice; +} + +#if defined(__cplusplus) +CV_INLINE CvSlice cvSlice(const cv::Range& r) +{ + CvSlice slice = (r.start != INT_MIN && r.end != INT_MAX) ? cvSlice(r.start, r.end) : cvSlice(0, CV_WHOLE_SEQ_END_INDEX); + return slice; +} +#endif + + +/************************************* CvScalar *****************************************/ +/** @sa Scalar_ + */ +typedef struct CvScalar +{ + double val[4]; + +#ifdef CV__VALIDATE_UNUNITIALIZED_VARS + CvScalar() __attribute__(( warning("Non-initialized variable") )) {} + CvScalar(const std::initializer_list list) + { + CV_Assert(list.size() == 0 || list.size() == 4); + val[0] = val[1] = val[2] = val[3] = 0; + if (list.size() == 4) + { + val[0] = list.begin()[0]; val[1] = list.begin()[1]; val[2] = list.begin()[2]; val[3] = list.begin()[3]; + } + }; +#elif defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus) + CvScalar() {} + CvScalar(double d0, double d1 = 0, double d2 = 0, double d3 = 0) { val[0] = d0; val[1] = d1; val[2] = d2; val[3] = d3; } + template + CvScalar(const cv::Scalar_<_Tp>& s) { val[0] = s.val[0]; val[1] = s.val[1]; val[2] = s.val[2]; val[3] = s.val[3]; } + template + CvScalar(const cv::Vec<_Tp, cn>& v) + { + int i; + for( i = 0; i < (cn < 4 ? cn : 4); i++ ) val[i] = v.val[i]; + for( ; i < 4; i++ ) val[i] = 0; + } +#endif +#ifdef __cplusplus + template + operator cv::Scalar_<_Tp>() const { return cv::Scalar_<_Tp>(cv::saturate_cast<_Tp>(val[0]), cv::saturate_cast<_Tp>(val[1]), cv::saturate_cast<_Tp>(val[2]), cv::saturate_cast<_Tp>(val[3])); } +#endif +} +CvScalar; + +CV_INLINE CvScalar cvScalar( double val0, double val1 CV_DEFAULT(0), + double val2 CV_DEFAULT(0), double val3 CV_DEFAULT(0)) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvScalar scalar = CV_STRUCT_INITIALIZER; +#else + CvScalar scalar; +#endif + scalar.val[0] = val0; scalar.val[1] = val1; + scalar.val[2] = val2; scalar.val[3] = val3; + return scalar; +} + +#ifdef __cplusplus +CV_INLINE CvScalar cvScalar() +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvScalar scalar = CV_STRUCT_INITIALIZER; +#else + CvScalar scalar; +#endif + scalar.val[0] = scalar.val[1] = scalar.val[2] = scalar.val[3] = 0; + return scalar; +} +CV_INLINE CvScalar cvScalar(const cv::Scalar& s) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvScalar scalar = CV_STRUCT_INITIALIZER; +#else + CvScalar scalar; +#endif + scalar.val[0] = s.val[0]; + scalar.val[1] = s.val[1]; + scalar.val[2] = s.val[2]; + scalar.val[3] = s.val[3]; + return scalar; +} +#endif + +CV_INLINE CvScalar cvRealScalar( double val0 ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvScalar scalar = CV_STRUCT_INITIALIZER; +#else + CvScalar scalar; +#endif + scalar.val[0] = val0; + scalar.val[1] = scalar.val[2] = scalar.val[3] = 0; + return scalar; +} + +CV_INLINE CvScalar cvScalarAll( double val0123 ) +{ +#if !(defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)) + CvScalar scalar = CV_STRUCT_INITIALIZER; +#else + CvScalar scalar; +#endif + scalar.val[0] = val0123; + scalar.val[1] = val0123; + scalar.val[2] = val0123; + scalar.val[3] = val0123; + return scalar; +} + +/****************************************************************************************\ +* Dynamic Data structures * +\****************************************************************************************/ + +/******************************** Memory storage ****************************************/ + +typedef struct CvMemBlock +{ + struct CvMemBlock* prev; + struct CvMemBlock* next; +} +CvMemBlock; + +#define CV_STORAGE_MAGIC_VAL 0x42890000 + +typedef struct CvMemStorage +{ + int signature; + CvMemBlock* bottom; /**< First allocated block. */ + CvMemBlock* top; /**< Current memory block - top of the stack. */ + struct CvMemStorage* parent; /**< We get new blocks from parent as needed. */ + int block_size; /**< Block size. */ + int free_space; /**< Remaining free space in current block. */ +} +CvMemStorage; + +#define CV_IS_STORAGE(storage) \ + ((storage) != NULL && \ + (((CvMemStorage*)(storage))->signature & CV_MAGIC_MASK) == CV_STORAGE_MAGIC_VAL) + + +typedef struct CvMemStoragePos +{ + CvMemBlock* top; + int free_space; +} +CvMemStoragePos; + + +/*********************************** Sequence *******************************************/ + +typedef struct CvSeqBlock +{ + struct CvSeqBlock* prev; /**< Previous sequence block. */ + struct CvSeqBlock* next; /**< Next sequence block. */ + int start_index; /**< Index of the first element in the block + */ + /**< sequence->first->start_index. */ + int count; /**< Number of elements in the block. */ + schar* data; /**< Pointer to the first element of the block. */ +} +CvSeqBlock; + + +#define CV_TREE_NODE_FIELDS(node_type) \ + int flags; /**< Miscellaneous flags. */ \ + int header_size; /**< Size of sequence header. */ \ + struct node_type* h_prev; /**< Previous sequence. */ \ + struct node_type* h_next; /**< Next sequence. */ \ + struct node_type* v_prev; /**< 2nd previous sequence. */ \ + struct node_type* v_next /**< 2nd next sequence. */ + +/** + Read/Write sequence. + Elements can be dynamically inserted to or deleted from the sequence. +*/ +#define CV_SEQUENCE_FIELDS() \ + CV_TREE_NODE_FIELDS(CvSeq); \ + int total; /**< Total number of elements. */ \ + int elem_size; /**< Size of sequence element in bytes. */ \ + schar* block_max; /**< Maximal bound of the last block. */ \ + schar* ptr; /**< Current write pointer. */ \ + int delta_elems; /**< Grow seq this many at a time. */ \ + CvMemStorage* storage; /**< Where the seq is stored. */ \ + CvSeqBlock* free_blocks; /**< Free blocks list. */ \ + CvSeqBlock* first; /**< Pointer to the first sequence block. */ + +typedef struct CvSeq +{ + CV_SEQUENCE_FIELDS() +} +CvSeq; + +#define CV_TYPE_NAME_SEQ "opencv-sequence" +#define CV_TYPE_NAME_SEQ_TREE "opencv-sequence-tree" + +/*************************************** Set ********************************************/ +/** @brief Set + Order is not preserved. There can be gaps between sequence elements. + After the element has been inserted it stays in the same place all the time. + The MSB(most-significant or sign bit) of the first field (flags) is 0 iff the element exists. +*/ +#define CV_SET_ELEM_FIELDS(elem_type) \ + int flags; \ + struct elem_type* next_free; + +typedef struct CvSetElem +{ + CV_SET_ELEM_FIELDS(CvSetElem) +} +CvSetElem; + +#define CV_SET_FIELDS() \ + CV_SEQUENCE_FIELDS() \ + CvSetElem* free_elems; \ + int active_count; + +typedef struct CvSet +{ + CV_SET_FIELDS() +} +CvSet; + + +#define CV_SET_ELEM_IDX_MASK ((1 << 26) - 1) +#define CV_SET_ELEM_FREE_FLAG (1 << (sizeof(int)*8-1)) + +/** Checks whether the element pointed by ptr belongs to a set or not */ +#define CV_IS_SET_ELEM( ptr ) (((CvSetElem*)(ptr))->flags >= 0) + +/************************************* Graph ********************************************/ + +/** @name Graph + +We represent a graph as a set of vertices. Vertices contain their adjacency lists (more exactly, +pointers to first incoming or outcoming edge (or 0 if isolated vertex)). Edges are stored in +another set. There is a singly-linked list of incoming/outcoming edges for each vertex. + +Each edge consists of: + +- Two pointers to the starting and ending vertices (vtx[0] and vtx[1] respectively). + + A graph may be oriented or not. In the latter case, edges between vertex i to vertex j are not +distinguished during search operations. + +- Two pointers to next edges for the starting and ending vertices, where next[0] points to the +next edge in the vtx[0] adjacency list and next[1] points to the next edge in the vtx[1] +adjacency list. + +@see CvGraphEdge, CvGraphVtx, CvGraphVtx2D, CvGraph +@{ +*/ +#define CV_GRAPH_EDGE_FIELDS() \ + int flags; \ + float weight; \ + struct CvGraphEdge* next[2]; \ + struct CvGraphVtx* vtx[2]; + + +#define CV_GRAPH_VERTEX_FIELDS() \ + int flags; \ + struct CvGraphEdge* first; + + +typedef struct CvGraphEdge +{ + CV_GRAPH_EDGE_FIELDS() +} +CvGraphEdge; + +typedef struct CvGraphVtx +{ + CV_GRAPH_VERTEX_FIELDS() +} +CvGraphVtx; + +typedef struct CvGraphVtx2D +{ + CV_GRAPH_VERTEX_FIELDS() + CvPoint2D32f* ptr; +} +CvGraphVtx2D; + +/** + Graph is "derived" from the set (this is set a of vertices) + and includes another set (edges) +*/ +#define CV_GRAPH_FIELDS() \ + CV_SET_FIELDS() \ + CvSet* edges; + +typedef struct CvGraph +{ + CV_GRAPH_FIELDS() +} +CvGraph; + +#define CV_TYPE_NAME_GRAPH "opencv-graph" + +/** @} */ + +/*********************************** Chain/Contour *************************************/ + +typedef struct CvChain +{ + CV_SEQUENCE_FIELDS() + CvPoint origin; +} +CvChain; + +#define CV_CONTOUR_FIELDS() \ + CV_SEQUENCE_FIELDS() \ + CvRect rect; \ + int color; \ + int reserved[3]; + +typedef struct CvContour +{ + CV_CONTOUR_FIELDS() +} +CvContour; + +typedef CvContour CvPoint2DSeq; + +/****************************************************************************************\ +* Sequence types * +\****************************************************************************************/ + +#define CV_SEQ_MAGIC_VAL 0x42990000 + +#define CV_IS_SEQ(seq) \ + ((seq) != NULL && (((CvSeq*)(seq))->flags & CV_MAGIC_MASK) == CV_SEQ_MAGIC_VAL) + +#define CV_SET_MAGIC_VAL 0x42980000 +#define CV_IS_SET(set) \ + ((set) != NULL && (((CvSeq*)(set))->flags & CV_MAGIC_MASK) == CV_SET_MAGIC_VAL) + +#define CV_SEQ_ELTYPE_BITS 12 +#define CV_SEQ_ELTYPE_MASK ((1 << CV_SEQ_ELTYPE_BITS) - 1) + +#define CV_SEQ_ELTYPE_POINT CV_32SC2 /**< (x,y) */ +#define CV_SEQ_ELTYPE_CODE CV_8UC1 /**< freeman code: 0..7 */ +#define CV_SEQ_ELTYPE_GENERIC 0 +#define CV_SEQ_ELTYPE_PTR CV_USRTYPE1 +#define CV_SEQ_ELTYPE_PPOINT CV_SEQ_ELTYPE_PTR /**< &(x,y) */ +#define CV_SEQ_ELTYPE_INDEX CV_32SC1 /**< #(x,y) */ +#define CV_SEQ_ELTYPE_GRAPH_EDGE 0 /**< &next_o, &next_d, &vtx_o, &vtx_d */ +#define CV_SEQ_ELTYPE_GRAPH_VERTEX 0 /**< first_edge, &(x,y) */ +#define CV_SEQ_ELTYPE_TRIAN_ATR 0 /**< vertex of the binary tree */ +#define CV_SEQ_ELTYPE_CONNECTED_COMP 0 /**< connected component */ +#define CV_SEQ_ELTYPE_POINT3D CV_32FC3 /**< (x,y,z) */ + +#define CV_SEQ_KIND_BITS 2 +#define CV_SEQ_KIND_MASK (((1 << CV_SEQ_KIND_BITS) - 1)<flags & CV_SEQ_ELTYPE_MASK) +#define CV_SEQ_KIND( seq ) ((seq)->flags & CV_SEQ_KIND_MASK ) + +/** flag checking */ +#define CV_IS_SEQ_INDEX( seq ) ((CV_SEQ_ELTYPE(seq) == CV_SEQ_ELTYPE_INDEX) && \ + (CV_SEQ_KIND(seq) == CV_SEQ_KIND_GENERIC)) + +#define CV_IS_SEQ_CURVE( seq ) (CV_SEQ_KIND(seq) == CV_SEQ_KIND_CURVE) +#define CV_IS_SEQ_CLOSED( seq ) (((seq)->flags & CV_SEQ_FLAG_CLOSED) != 0) +#define CV_IS_SEQ_CONVEX( seq ) 0 +#define CV_IS_SEQ_HOLE( seq ) (((seq)->flags & CV_SEQ_FLAG_HOLE) != 0) +#define CV_IS_SEQ_SIMPLE( seq ) 1 + +/** type checking macros */ +#define CV_IS_SEQ_POINT_SET( seq ) \ + ((CV_SEQ_ELTYPE(seq) == CV_32SC2 || CV_SEQ_ELTYPE(seq) == CV_32FC2)) + +#define CV_IS_SEQ_POINT_SUBSET( seq ) \ + (CV_IS_SEQ_INDEX( seq ) || CV_SEQ_ELTYPE(seq) == CV_SEQ_ELTYPE_PPOINT) + +#define CV_IS_SEQ_POLYLINE( seq ) \ + (CV_SEQ_KIND(seq) == CV_SEQ_KIND_CURVE && CV_IS_SEQ_POINT_SET(seq)) + +#define CV_IS_SEQ_POLYGON( seq ) \ + (CV_IS_SEQ_POLYLINE(seq) && CV_IS_SEQ_CLOSED(seq)) + +#define CV_IS_SEQ_CHAIN( seq ) \ + (CV_SEQ_KIND(seq) == CV_SEQ_KIND_CURVE && (seq)->elem_size == 1) + +#define CV_IS_SEQ_CONTOUR( seq ) \ + (CV_IS_SEQ_CLOSED(seq) && (CV_IS_SEQ_POLYLINE(seq) || CV_IS_SEQ_CHAIN(seq))) + +#define CV_IS_SEQ_CHAIN_CONTOUR( seq ) \ + (CV_IS_SEQ_CHAIN( seq ) && CV_IS_SEQ_CLOSED( seq )) + +#define CV_IS_SEQ_POLYGON_TREE( seq ) \ + (CV_SEQ_ELTYPE (seq) == CV_SEQ_ELTYPE_TRIAN_ATR && \ + CV_SEQ_KIND( seq ) == CV_SEQ_KIND_BIN_TREE ) + +#define CV_IS_GRAPH( seq ) \ + (CV_IS_SET(seq) && CV_SEQ_KIND((CvSet*)(seq)) == CV_SEQ_KIND_GRAPH) + +#define CV_IS_GRAPH_ORIENTED( seq ) \ + (((seq)->flags & CV_GRAPH_FLAG_ORIENTED) != 0) + +#define CV_IS_SUBDIV2D( seq ) \ + (CV_IS_SET(seq) && CV_SEQ_KIND((CvSet*)(seq)) == CV_SEQ_KIND_SUBDIV2D) + +/****************************************************************************************/ +/* Sequence writer & reader */ +/****************************************************************************************/ + +#define CV_SEQ_WRITER_FIELDS() \ + int header_size; \ + CvSeq* seq; /**< the sequence written */ \ + CvSeqBlock* block; /**< current block */ \ + schar* ptr; /**< pointer to free space */ \ + schar* block_min; /**< pointer to the beginning of block*/\ + schar* block_max; /**< pointer to the end of block */ + +typedef struct CvSeqWriter +{ + CV_SEQ_WRITER_FIELDS() +} +CvSeqWriter; + + +#define CV_SEQ_READER_FIELDS() \ + int header_size; \ + CvSeq* seq; /**< sequence, beign read */ \ + CvSeqBlock* block; /**< current block */ \ + schar* ptr; /**< pointer to element be read next */ \ + schar* block_min; /**< pointer to the beginning of block */\ + schar* block_max; /**< pointer to the end of block */ \ + int delta_index;/**< = seq->first->start_index */ \ + schar* prev_elem; /**< pointer to previous element */ + +typedef struct CvSeqReader +{ + CV_SEQ_READER_FIELDS() +} +CvSeqReader; + +/****************************************************************************************/ +/* Operations on sequences */ +/****************************************************************************************/ + +#define CV_SEQ_ELEM( seq, elem_type, index ) \ +/** assert gives some guarantee that parameter is valid */ \ +( assert(sizeof((seq)->first[0]) == sizeof(CvSeqBlock) && \ + (seq)->elem_size == sizeof(elem_type)), \ + (elem_type*)((seq)->first && (unsigned)index < \ + (unsigned)((seq)->first->count) ? \ + (seq)->first->data + (index) * sizeof(elem_type) : \ + cvGetSeqElem( (CvSeq*)(seq), (index) ))) +#define CV_GET_SEQ_ELEM( elem_type, seq, index ) CV_SEQ_ELEM( (seq), elem_type, (index) ) + +/** Add element to sequence: */ +#define CV_WRITE_SEQ_ELEM_VAR( elem_ptr, writer ) \ +{ \ + if( (writer).ptr >= (writer).block_max ) \ + { \ + cvCreateSeqBlock( &writer); \ + } \ + memcpy((writer).ptr, elem_ptr, (writer).seq->elem_size);\ + (writer).ptr += (writer).seq->elem_size; \ +} + +#define CV_WRITE_SEQ_ELEM( elem, writer ) \ +{ \ + assert( (writer).seq->elem_size == sizeof(elem)); \ + if( (writer).ptr >= (writer).block_max ) \ + { \ + cvCreateSeqBlock( &writer); \ + } \ + assert( (writer).ptr <= (writer).block_max - sizeof(elem));\ + memcpy((writer).ptr, &(elem), sizeof(elem)); \ + (writer).ptr += sizeof(elem); \ +} + + +/** Move reader position forward: */ +#define CV_NEXT_SEQ_ELEM( elem_size, reader ) \ +{ \ + if( ((reader).ptr += (elem_size)) >= (reader).block_max ) \ + { \ + cvChangeSeqBlock( &(reader), 1 ); \ + } \ +} + + +/** Move reader position backward: */ +#define CV_PREV_SEQ_ELEM( elem_size, reader ) \ +{ \ + if( ((reader).ptr -= (elem_size)) < (reader).block_min ) \ + { \ + cvChangeSeqBlock( &(reader), -1 ); \ + } \ +} + +/** Read element and move read position forward: */ +#define CV_READ_SEQ_ELEM( elem, reader ) \ +{ \ + assert( (reader).seq->elem_size == sizeof(elem)); \ + memcpy( &(elem), (reader).ptr, sizeof((elem))); \ + CV_NEXT_SEQ_ELEM( sizeof(elem), reader ) \ +} + +/** Read element and move read position backward: */ +#define CV_REV_READ_SEQ_ELEM( elem, reader ) \ +{ \ + assert( (reader).seq->elem_size == sizeof(elem)); \ + memcpy(&(elem), (reader).ptr, sizeof((elem))); \ + CV_PREV_SEQ_ELEM( sizeof(elem), reader ) \ +} + + +#define CV_READ_CHAIN_POINT( _pt, reader ) \ +{ \ + (_pt) = (reader).pt; \ + if( (reader).ptr ) \ + { \ + CV_READ_SEQ_ELEM( (reader).code, (reader)); \ + assert( ((reader).code & ~7) == 0 ); \ + (reader).pt.x += (reader).deltas[(int)(reader).code][0]; \ + (reader).pt.y += (reader).deltas[(int)(reader).code][1]; \ + } \ +} + +#define CV_CURRENT_POINT( reader ) (*((CvPoint*)((reader).ptr))) +#define CV_PREV_POINT( reader ) (*((CvPoint*)((reader).prev_elem))) + +#define CV_READ_EDGE( pt1, pt2, reader ) \ +{ \ + assert( sizeof(pt1) == sizeof(CvPoint) && \ + sizeof(pt2) == sizeof(CvPoint) && \ + reader.seq->elem_size == sizeof(CvPoint)); \ + (pt1) = CV_PREV_POINT( reader ); \ + (pt2) = CV_CURRENT_POINT( reader ); \ + (reader).prev_elem = (reader).ptr; \ + CV_NEXT_SEQ_ELEM( sizeof(CvPoint), (reader)); \ +} + +/************ Graph macros ************/ + +/** Return next graph edge for given vertex: */ +#define CV_NEXT_GRAPH_EDGE( edge, vertex ) \ + (assert((edge)->vtx[0] == (vertex) || (edge)->vtx[1] == (vertex)), \ + (edge)->next[(edge)->vtx[1] == (vertex)]) + + + +/****************************************************************************************\ +* Data structures for persistence (a.k.a serialization) functionality * +\****************************************************************************************/ + +/** "black box" file storage */ +typedef struct CvFileStorage CvFileStorage; + +/** Storage flags: */ +#define CV_STORAGE_READ 0 +#define CV_STORAGE_WRITE 1 +#define CV_STORAGE_WRITE_TEXT CV_STORAGE_WRITE +#define CV_STORAGE_WRITE_BINARY CV_STORAGE_WRITE +#define CV_STORAGE_APPEND 2 +#define CV_STORAGE_MEMORY 4 +#define CV_STORAGE_FORMAT_MASK (7<<3) +#define CV_STORAGE_FORMAT_AUTO 0 +#define CV_STORAGE_FORMAT_XML 8 +#define CV_STORAGE_FORMAT_YAML 16 +#define CV_STORAGE_FORMAT_JSON 24 +#define CV_STORAGE_BASE64 64 +#define CV_STORAGE_WRITE_BASE64 (CV_STORAGE_BASE64 | CV_STORAGE_WRITE) + +/** @brief List of attributes. : + +In the current implementation, attributes are used to pass extra parameters when writing user +objects (see cvWrite). XML attributes inside tags are not supported, aside from the object type +specification (type_id attribute). +@see cvAttrList, cvAttrValue + */ +typedef struct CvAttrList +{ + const char** attr; /**< NULL-terminated array of (attribute_name,attribute_value) pairs. */ + struct CvAttrList* next; /**< Pointer to next chunk of the attributes list. */ +} +CvAttrList; + +/** initializes CvAttrList structure */ +CV_INLINE CvAttrList cvAttrList( const char** attr CV_DEFAULT(NULL), + CvAttrList* next CV_DEFAULT(NULL) ) +{ + CvAttrList l; + l.attr = attr; + l.next = next; + + return l; +} + +struct CvTypeInfo; + +#define CV_NODE_NONE 0 +#define CV_NODE_INT 1 +#define CV_NODE_INTEGER CV_NODE_INT +#define CV_NODE_REAL 2 +#define CV_NODE_FLOAT CV_NODE_REAL +#define CV_NODE_STR 3 +#define CV_NODE_STRING CV_NODE_STR +#define CV_NODE_REF 4 /**< not used */ +#define CV_NODE_SEQ 5 +#define CV_NODE_MAP 6 +#define CV_NODE_TYPE_MASK 7 + +#define CV_NODE_TYPE(flags) ((flags) & CV_NODE_TYPE_MASK) + +/** file node flags */ +#define CV_NODE_FLOW 8 /**= CV_NODE_SEQ) +#define CV_NODE_IS_FLOW(flags) (((flags) & CV_NODE_FLOW) != 0) +#define CV_NODE_IS_EMPTY(flags) (((flags) & CV_NODE_EMPTY) != 0) +#define CV_NODE_IS_USER(flags) (((flags) & CV_NODE_USER) != 0) +#define CV_NODE_HAS_NAME(flags) (((flags) & CV_NODE_NAMED) != 0) + +#define CV_NODE_SEQ_SIMPLE 256 +#define CV_NODE_SEQ_IS_SIMPLE(seq) (((seq)->flags & CV_NODE_SEQ_SIMPLE) != 0) + +typedef struct CvString +{ + int len; + char* ptr; +} +CvString; + +/** All the keys (names) of elements in the read file storage + are stored in the hash to speed up the lookup operations: */ +typedef struct CvStringHashNode +{ + unsigned hashval; + CvString str; + struct CvStringHashNode* next; +} +CvStringHashNode; + +typedef struct CvGenericHash CvFileNodeHash; + +/** Basic element of the file storage - scalar or collection: */ +typedef struct CvFileNode +{ + int tag; + struct CvTypeInfo* info; /**< type information + (only for user-defined object, for others it is 0) */ + union + { + double f; /**< scalar floating-point number */ + int i; /**< scalar integer number */ + CvString str; /**< text string */ + CvSeq* seq; /**< sequence (ordered collection of file nodes) */ + CvFileNodeHash* map; /**< map (collection of named file nodes) */ + } data; +} +CvFileNode; + +#ifdef __cplusplus +extern "C" { +#endif +typedef int (CV_CDECL *CvIsInstanceFunc)( const void* struct_ptr ); +typedef void (CV_CDECL *CvReleaseFunc)( void** struct_dblptr ); +typedef void* (CV_CDECL *CvReadFunc)( CvFileStorage* storage, CvFileNode* node ); +typedef void (CV_CDECL *CvWriteFunc)( CvFileStorage* storage, const char* name, + const void* struct_ptr, CvAttrList attributes ); +typedef void* (CV_CDECL *CvCloneFunc)( const void* struct_ptr ); +#ifdef __cplusplus +} +#endif + +/** @brief Type information + +The structure contains information about one of the standard or user-defined types. Instances of the +type may or may not contain a pointer to the corresponding CvTypeInfo structure. In any case, there +is a way to find the type info structure for a given object using the cvTypeOf function. +Alternatively, type info can be found by type name using cvFindType, which is used when an object +is read from file storage. The user can register a new type with cvRegisterType that adds the type +information structure into the beginning of the type list. Thus, it is possible to create +specialized types from generic standard types and override the basic methods. + */ +typedef struct CvTypeInfo +{ + int flags; /**< not used */ + int header_size; /**< sizeof(CvTypeInfo) */ + struct CvTypeInfo* prev; /**< previous registered type in the list */ + struct CvTypeInfo* next; /**< next registered type in the list */ + const char* type_name; /**< type name, written to file storage */ + CvIsInstanceFunc is_instance; /**< checks if the passed object belongs to the type */ + CvReleaseFunc release; /**< releases object (memory etc.) */ + CvReadFunc read; /**< reads object from file storage */ + CvWriteFunc write; /**< writes object to file storage */ + CvCloneFunc clone; /**< creates a copy of the object */ +} +CvTypeInfo; + + +/**** System data types ******/ + +typedef struct CvPluginFuncInfo +{ + void** func_addr; + void* default_func_addr; + const char* func_names; + int search_modules; + int loaded_from; +} +CvPluginFuncInfo; + +typedef struct CvModuleInfo +{ + struct CvModuleInfo* next; + const char* name; + const char* version; + CvPluginFuncInfo* func_tab; +} +CvModuleInfo; + +/** @} */ + +#endif /*OPENCV_CORE_TYPES_H*/ + +/* End of file. */ diff --git a/3rdparty/opencv/include/opencv2/core/utility.hpp b/3rdparty/opencv/include/opencv2/core/utility.hpp new file mode 100644 index 00000000..7a7158f5 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/utility.hpp @@ -0,0 +1,1358 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2015, Itseez Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_CORE_UTILITY_H +#define OPENCV_CORE_UTILITY_H + +#ifndef __cplusplus +# error utility.hpp header must be compiled as C++ +#endif + +#if defined(check) +# warning Detected Apple 'check' macro definition, it can cause build conflicts. Please, include this header before any Apple headers. +#endif + +#include "opencv2/core.hpp" +#include + +#ifdef CV_CXX11 +#include +#endif + +namespace cv +{ + +#ifdef CV_COLLECT_IMPL_DATA +CV_EXPORTS void setImpl(int flags); // set implementation flags and reset storage arrays +CV_EXPORTS void addImpl(int flag, const char* func = 0); // add implementation and function name to storage arrays +// Get stored implementation flags and functions names arrays +// Each implementation entry correspond to function name entry, so you can find which implementation was executed in which function +CV_EXPORTS int getImpl(std::vector &impl, std::vector &funName); + +CV_EXPORTS bool useCollection(); // return implementation collection state +CV_EXPORTS void setUseCollection(bool flag); // set implementation collection state + +#define CV_IMPL_PLAIN 0x01 // native CPU OpenCV implementation +#define CV_IMPL_OCL 0x02 // OpenCL implementation +#define CV_IMPL_IPP 0x04 // IPP implementation +#define CV_IMPL_MT 0x10 // multithreaded implementation + +#define CV_IMPL_ADD(impl) \ + if(cv::useCollection()) \ + { \ + cv::addImpl(impl, CV_Func); \ + } +#else +#define CV_IMPL_ADD(impl) +#endif + +//! @addtogroup core_utils +//! @{ + +/** @brief Automatically Allocated Buffer Class + + The class is used for temporary buffers in functions and methods. + If a temporary buffer is usually small (a few K's of memory), + but its size depends on the parameters, it makes sense to create a small + fixed-size array on stack and use it if it's large enough. If the required buffer size + is larger than the fixed size, another buffer of sufficient size is allocated dynamically + and released after the processing. Therefore, in typical cases, when the buffer size is small, + there is no overhead associated with malloc()/free(). + At the same time, there is no limit on the size of processed data. + + This is what AutoBuffer does. The template takes 2 parameters - type of the buffer elements and + the number of stack-allocated elements. Here is how the class is used: + + \code + void my_func(const cv::Mat& m) + { + cv::AutoBuffer buf(1000); // create automatic buffer containing 1000 floats + + buf.allocate(m.rows); // if m.rows <= 1000, the pre-allocated buffer is used, + // otherwise the buffer of "m.rows" floats will be allocated + // dynamically and deallocated in cv::AutoBuffer destructor + ... + } + \endcode +*/ +template class AutoBuffer +{ +public: + typedef _Tp value_type; + + //! the default constructor + AutoBuffer(); + //! constructor taking the real buffer size + explicit AutoBuffer(size_t _size); + + //! the copy constructor + AutoBuffer(const AutoBuffer<_Tp, fixed_size>& buf); + //! the assignment operator + AutoBuffer<_Tp, fixed_size>& operator = (const AutoBuffer<_Tp, fixed_size>& buf); + + //! destructor. calls deallocate() + ~AutoBuffer(); + + //! allocates the new buffer of size _size. if the _size is small enough, stack-allocated buffer is used + void allocate(size_t _size); + //! deallocates the buffer if it was dynamically allocated + void deallocate(); + //! resizes the buffer and preserves the content + void resize(size_t _size); + //! returns the current buffer size + size_t size() const; + //! returns pointer to the real buffer, stack-allocated or heap-allocated + inline _Tp* data() { return ptr; } + //! returns read-only pointer to the real buffer, stack-allocated or heap-allocated + inline const _Tp* data() const { return ptr; } + +#if !defined(OPENCV_DISABLE_DEPRECATED_COMPATIBILITY) // use to .data() calls instead + //! returns pointer to the real buffer, stack-allocated or heap-allocated + operator _Tp* () { return ptr; } + //! returns read-only pointer to the real buffer, stack-allocated or heap-allocated + operator const _Tp* () const { return ptr; } +#else + //! returns a reference to the element at specified location. No bounds checking is performed in Release builds. + inline _Tp& operator[] (size_t i) { CV_DbgCheckLT(i, sz, "out of range"); return ptr[i]; } + //! returns a reference to the element at specified location. No bounds checking is performed in Release builds. + inline const _Tp& operator[] (size_t i) const { CV_DbgCheckLT(i, sz, "out of range"); return ptr[i]; } +#endif + +protected: + //! pointer to the real buffer, can point to buf if the buffer is small enough + _Tp* ptr; + //! size of the real buffer + size_t sz; + //! pre-allocated buffer. At least 1 element to confirm C++ standard requirements + _Tp buf[(fixed_size > 0) ? fixed_size : 1]; +}; + +/** @brief Sets/resets the break-on-error mode. + +When the break-on-error mode is set, the default error handler issues a hardware exception, which +can make debugging more convenient. + +\return the previous state + */ +CV_EXPORTS bool setBreakOnError(bool flag); + +extern "C" typedef int (*ErrorCallback)( int status, const char* func_name, + const char* err_msg, const char* file_name, + int line, void* userdata ); + + +/** @brief Sets the new error handler and the optional user data. + + The function sets the new error handler, called from cv::error(). + + \param errCallback the new error handler. If NULL, the default error handler is used. + \param userdata the optional user data pointer, passed to the callback. + \param prevUserdata the optional output parameter where the previous user data pointer is stored + + \return the previous error handler +*/ +CV_EXPORTS ErrorCallback redirectError( ErrorCallback errCallback, void* userdata=0, void** prevUserdata=0); + +CV_EXPORTS String tempfile( const char* suffix = 0); +CV_EXPORTS void glob(String pattern, std::vector& result, bool recursive = false); + +/** @brief OpenCV will try to set the number of threads for the next parallel region. + +If threads == 0, OpenCV will disable threading optimizations and run all it's functions +sequentially. Passing threads \< 0 will reset threads number to system default. This function must +be called outside of parallel region. + +OpenCV will try to run its functions with specified threads number, but some behaviour differs from +framework: +- `TBB` - User-defined parallel constructions will run with the same threads number, if + another is not specified. If later on user creates his own scheduler, OpenCV will use it. +- `OpenMP` - No special defined behaviour. +- `Concurrency` - If threads == 1, OpenCV will disable threading optimizations and run its + functions sequentially. +- `GCD` - Supports only values \<= 0. +- `C=` - No special defined behaviour. +@param nthreads Number of threads used by OpenCV. +@sa getNumThreads, getThreadNum + */ +CV_EXPORTS_W void setNumThreads(int nthreads); + +/** @brief Returns the number of threads used by OpenCV for parallel regions. + +Always returns 1 if OpenCV is built without threading support. + +The exact meaning of return value depends on the threading framework used by OpenCV library: +- `TBB` - The number of threads, that OpenCV will try to use for parallel regions. If there is + any tbb::thread_scheduler_init in user code conflicting with OpenCV, then function returns + default number of threads used by TBB library. +- `OpenMP` - An upper bound on the number of threads that could be used to form a new team. +- `Concurrency` - The number of threads, that OpenCV will try to use for parallel regions. +- `GCD` - Unsupported; returns the GCD thread pool limit (512) for compatibility. +- `C=` - The number of threads, that OpenCV will try to use for parallel regions, if before + called setNumThreads with threads \> 0, otherwise returns the number of logical CPUs, + available for the process. +@sa setNumThreads, getThreadNum + */ +CV_EXPORTS_W int getNumThreads(); + +/** @brief Returns the index of the currently executed thread within the current parallel region. Always +returns 0 if called outside of parallel region. + +@deprecated Current implementation doesn't corresponding to this documentation. + +The exact meaning of the return value depends on the threading framework used by OpenCV library: +- `TBB` - Unsupported with current 4.1 TBB release. Maybe will be supported in future. +- `OpenMP` - The thread number, within the current team, of the calling thread. +- `Concurrency` - An ID for the virtual processor that the current context is executing on (0 + for master thread and unique number for others, but not necessary 1,2,3,...). +- `GCD` - System calling thread's ID. Never returns 0 inside parallel region. +- `C=` - The index of the current parallel task. +@sa setNumThreads, getNumThreads + */ +CV_EXPORTS_W int getThreadNum(); + +/** @brief Returns full configuration time cmake output. + +Returned value is raw cmake output including version control system revision, compiler version, +compiler flags, enabled modules and third party libraries, etc. Output format depends on target +architecture. + */ +CV_EXPORTS_W const String& getBuildInformation(); + +/** @brief Returns library version string + +For example "3.4.1-dev". + +@sa getMajorVersion, getMinorVersion, getRevisionVersion +*/ +CV_EXPORTS_W String getVersionString(); + +/** @brief Returns major library version */ +CV_EXPORTS_W int getVersionMajor(); + +/** @brief Returns minor library version */ +CV_EXPORTS_W int getVersionMinor(); + +/** @brief Returns revision field of the library version */ +CV_EXPORTS_W int getVersionRevision(); + +/** @brief Returns the number of ticks. + +The function returns the number of ticks after the certain event (for example, when the machine was +turned on). It can be used to initialize RNG or to measure a function execution time by reading the +tick count before and after the function call. +@sa getTickFrequency, TickMeter + */ +CV_EXPORTS_W int64 getTickCount(); + +/** @brief Returns the number of ticks per second. + +The function returns the number of ticks per second. That is, the following code computes the +execution time in seconds: +@code + double t = (double)getTickCount(); + // do something ... + t = ((double)getTickCount() - t)/getTickFrequency(); +@endcode +@sa getTickCount, TickMeter + */ +CV_EXPORTS_W double getTickFrequency(); + +/** @brief a Class to measure passing time. + +The class computes passing time by counting the number of ticks per second. That is, the following code computes the +execution time in seconds: +@code +TickMeter tm; +tm.start(); +// do something ... +tm.stop(); +std::cout << tm.getTimeSec(); +@endcode + +It is also possible to compute the average time over multiple runs: +@code +TickMeter tm; +for (int i = 0; i < 100; i++) +{ + tm.start(); + // do something ... + tm.stop(); +} +double average_time = tm.getTimeSec() / tm.getCounter(); +std::cout << "Average time in second per iteration is: " << average_time << std::endl; +@endcode +@sa getTickCount, getTickFrequency +*/ + +class CV_EXPORTS_W TickMeter +{ +public: + //! the default constructor + CV_WRAP TickMeter() + { + reset(); + } + + /** + starts counting ticks. + */ + CV_WRAP void start() + { + startTime = cv::getTickCount(); + } + + /** + stops counting ticks. + */ + CV_WRAP void stop() + { + int64 time = cv::getTickCount(); + if (startTime == 0) + return; + ++counter; + sumTime += (time - startTime); + startTime = 0; + } + + /** + returns counted ticks. + */ + CV_WRAP int64 getTimeTicks() const + { + return sumTime; + } + + /** + returns passed time in microseconds. + */ + CV_WRAP double getTimeMicro() const + { + return getTimeMilli()*1e3; + } + + /** + returns passed time in milliseconds. + */ + CV_WRAP double getTimeMilli() const + { + return getTimeSec()*1e3; + } + + /** + returns passed time in seconds. + */ + CV_WRAP double getTimeSec() const + { + return (double)getTimeTicks() / getTickFrequency(); + } + + /** + returns internal counter value. + */ + CV_WRAP int64 getCounter() const + { + return counter; + } + + /** + resets internal values. + */ + CV_WRAP void reset() + { + startTime = 0; + sumTime = 0; + counter = 0; + } + +private: + int64 counter; + int64 sumTime; + int64 startTime; +}; + +/** @brief output operator +@code +TickMeter tm; +tm.start(); +// do something ... +tm.stop(); +std::cout << tm; +@endcode +*/ + +static inline +std::ostream& operator << (std::ostream& out, const TickMeter& tm) +{ + return out << tm.getTimeSec() << "sec"; +} + +/** @brief Returns the number of CPU ticks. + +The function returns the current number of CPU ticks on some architectures (such as x86, x64, +PowerPC). On other platforms the function is equivalent to getTickCount. It can also be used for +very accurate time measurements, as well as for RNG initialization. Note that in case of multi-CPU +systems a thread, from which getCPUTickCount is called, can be suspended and resumed at another CPU +with its own counter. So, theoretically (and practically) the subsequent calls to the function do +not necessary return the monotonously increasing values. Also, since a modern CPU varies the CPU +frequency depending on the load, the number of CPU clocks spent in some code cannot be directly +converted to time units. Therefore, getTickCount is generally a preferable solution for measuring +execution time. + */ +CV_EXPORTS_W int64 getCPUTickCount(); + +/** @brief Returns true if the specified feature is supported by the host hardware. + +The function returns true if the host hardware supports the specified feature. When user calls +setUseOptimized(false), the subsequent calls to checkHardwareSupport() will return false until +setUseOptimized(true) is called. This way user can dynamically switch on and off the optimized code +in OpenCV. +@param feature The feature of interest, one of cv::CpuFeatures + */ +CV_EXPORTS_W bool checkHardwareSupport(int feature); + +/** @brief Returns feature name by ID + +Returns empty string if feature is not defined +*/ +CV_EXPORTS_W String getHardwareFeatureName(int feature); + +/** @brief Returns list of CPU features enabled during compilation. + +Returned value is a string containing space separated list of CPU features with following markers: + +- no markers - baseline features +- prefix `*` - features enabled in dispatcher +- suffix `?` - features enabled but not available in HW + +Example: `SSE SSE2 SSE3 *SSE4.1 *SSE4.2 *FP16 *AVX *AVX2 *AVX512-SKX?` +*/ +CV_EXPORTS std::string getCPUFeaturesLine(); + +/** @brief Returns the number of logical CPUs available for the process. + */ +CV_EXPORTS_W int getNumberOfCPUs(); + + +/** @brief Aligns a pointer to the specified number of bytes. + +The function returns the aligned pointer of the same type as the input pointer: +\f[\texttt{(_Tp*)(((size_t)ptr + n-1) & -n)}\f] +@param ptr Aligned pointer. +@param n Alignment size that must be a power of two. + */ +template static inline _Tp* alignPtr(_Tp* ptr, int n=(int)sizeof(_Tp)) +{ + CV_DbgAssert((n & (n - 1)) == 0); // n is a power of 2 + return (_Tp*)(((size_t)ptr + n-1) & -n); +} + +/** @brief Aligns a buffer size to the specified number of bytes. + +The function returns the minimum number that is greater than or equal to sz and is divisible by n : +\f[\texttt{(sz + n-1) & -n}\f] +@param sz Buffer size to align. +@param n Alignment size that must be a power of two. + */ +static inline size_t alignSize(size_t sz, int n) +{ + CV_DbgAssert((n & (n - 1)) == 0); // n is a power of 2 + return (sz + n-1) & -n; +} + +/** @brief Integer division with result round up. + +Use this function instead of `ceil((float)a / b)` expressions. + +@sa alignSize +*/ +static inline int divUp(int a, unsigned int b) +{ + CV_DbgAssert(a >= 0); + return (a + b - 1) / b; +} +/** @overload */ +static inline size_t divUp(size_t a, unsigned int b) +{ + return (a + b - 1) / b; +} + +/** @brief Round first value up to the nearest multiple of second value. + +Use this function instead of `ceil((float)a / b) * b` expressions. + +@sa divUp +*/ +static inline int roundUp(int a, unsigned int b) +{ + CV_DbgAssert(a >= 0); + return a + b - 1 - (a + b -1) % b; +} +/** @overload */ +static inline size_t roundUp(size_t a, unsigned int b) +{ + return a + b - 1 - (a + b - 1) % b; +} + +/** @brief Enables or disables the optimized code. + +The function can be used to dynamically turn on and off optimized dispatched code (code that uses SSE4.2, AVX/AVX2, +and other instructions on the platforms that support it). It sets a global flag that is further +checked by OpenCV functions. Since the flag is not checked in the inner OpenCV loops, it is only +safe to call the function on the very top level in your application where you can be sure that no +other OpenCV function is currently executed. + +By default, the optimized code is enabled unless you disable it in CMake. The current status can be +retrieved using useOptimized. +@param onoff The boolean flag specifying whether the optimized code should be used (onoff=true) +or not (onoff=false). + */ +CV_EXPORTS_W void setUseOptimized(bool onoff); + +/** @brief Returns the status of optimized code usage. + +The function returns true if the optimized code is enabled. Otherwise, it returns false. + */ +CV_EXPORTS_W bool useOptimized(); + +static inline size_t getElemSize(int type) { return (size_t)CV_ELEM_SIZE(type); } + +/////////////////////////////// Parallel Primitives ////////////////////////////////// + +/** @brief Base class for parallel data processors +*/ +class CV_EXPORTS ParallelLoopBody +{ +public: + virtual ~ParallelLoopBody(); + virtual void operator() (const Range& range) const = 0; +}; + +/** @brief Parallel data processor +*/ +CV_EXPORTS void parallel_for_(const Range& range, const ParallelLoopBody& body, double nstripes=-1.); + +#ifdef CV_CXX11 +class ParallelLoopBodyLambdaWrapper : public ParallelLoopBody +{ +private: + std::function m_functor; +public: + ParallelLoopBodyLambdaWrapper(std::function functor) : + m_functor(functor) + { } + + virtual void operator() (const cv::Range& range) const CV_OVERRIDE + { + m_functor(range); + } +}; + +inline void parallel_for_(const Range& range, std::function functor, double nstripes=-1.) +{ + parallel_for_(range, ParallelLoopBodyLambdaWrapper(functor), nstripes); +} +#endif + +/////////////////////////////// forEach method of cv::Mat //////////////////////////// +template inline +void Mat::forEach_impl(const Functor& operation) { + if (false) { + operation(*reinterpret_cast<_Tp*>(0), reinterpret_cast(0)); + // If your compiler fails in this line. + // Please check that your functor signature is + // (_Tp&, const int*) <- multi-dimensional + // or (_Tp&, void*) <- in case you don't need current idx. + } + + CV_Assert(this->total() / this->size[this->dims - 1] <= INT_MAX); + const int LINES = static_cast(this->total() / this->size[this->dims - 1]); + + class PixelOperationWrapper :public ParallelLoopBody + { + public: + PixelOperationWrapper(Mat_<_Tp>* const frame, const Functor& _operation) + : mat(frame), op(_operation) {} + virtual ~PixelOperationWrapper(){} + // ! Overloaded virtual operator + // convert range call to row call. + virtual void operator()(const Range &range) const CV_OVERRIDE + { + const int DIMS = mat->dims; + const int COLS = mat->size[DIMS - 1]; + if (DIMS <= 2) { + for (int row = range.start; row < range.end; ++row) { + this->rowCall2(row, COLS); + } + } else { + std::vector idx(DIMS); /// idx is modified in this->rowCall + idx[DIMS - 2] = range.start - 1; + + for (int line_num = range.start; line_num < range.end; ++line_num) { + idx[DIMS - 2]++; + for (int i = DIMS - 2; i >= 0; --i) { + if (idx[i] >= mat->size[i]) { + idx[i - 1] += idx[i] / mat->size[i]; + idx[i] %= mat->size[i]; + continue; // carry-over; + } + else { + break; + } + } + this->rowCall(&idx[0], COLS, DIMS); + } + } + } + private: + Mat_<_Tp>* const mat; + const Functor op; + // ! Call operator for each elements in this row. + inline void rowCall(int* const idx, const int COLS, const int DIMS) const { + int &col = idx[DIMS - 1]; + col = 0; + _Tp* pixel = &(mat->template at<_Tp>(idx)); + + while (col < COLS) { + op(*pixel, const_cast(idx)); + pixel++; col++; + } + col = 0; + } + // ! Call operator for each elements in this row. 2d mat special version. + inline void rowCall2(const int row, const int COLS) const { + union Index{ + int body[2]; + operator const int*() const { + return reinterpret_cast(this); + } + int& operator[](const int i) { + return body[i]; + } + } idx = {{row, 0}}; + // Special union is needed to avoid + // "error: array subscript is above array bounds [-Werror=array-bounds]" + // when call the functor `op` such that access idx[3]. + + _Tp* pixel = &(mat->template at<_Tp>(idx)); + const _Tp* const pixel_end = pixel + COLS; + while(pixel < pixel_end) { + op(*pixel++, static_cast(idx)); + idx[1]++; + } + } + PixelOperationWrapper& operator=(const PixelOperationWrapper &) { + CV_Assert(false); + // We can not remove this implementation because Visual Studio warning C4822. + return *this; + } + }; + + parallel_for_(cv::Range(0, LINES), PixelOperationWrapper(reinterpret_cast*>(this), operation)); +} + +/////////////////////////// Synchronization Primitives /////////////////////////////// + +class CV_EXPORTS Mutex +{ +public: + Mutex(); + ~Mutex(); + Mutex(const Mutex& m); + Mutex& operator = (const Mutex& m); + + void lock(); + bool trylock(); + void unlock(); + + struct Impl; +protected: + Impl* impl; +}; + +class CV_EXPORTS AutoLock +{ +public: + AutoLock(Mutex& m) : mutex(&m) { mutex->lock(); } + ~AutoLock() { mutex->unlock(); } +protected: + Mutex* mutex; +private: + AutoLock(const AutoLock&); + AutoLock& operator = (const AutoLock&); +}; + +// TLS interface +class CV_EXPORTS TLSDataContainer +{ +protected: + TLSDataContainer(); + virtual ~TLSDataContainer(); + + void gatherData(std::vector &data) const; +#if OPENCV_ABI_COMPATIBILITY > 300 + void* getData() const; + void release(); + +private: +#else + void release(); + +public: + void* getData() const; +#endif + virtual void* createDataInstance() const = 0; + virtual void deleteDataInstance(void* pData) const = 0; + + int key_; + +public: + void cleanup(); //! Release created TLS data container objects. It is similar to release() call, but it keeps TLS container valid. +}; + +// Main TLS data class +template +class TLSData : protected TLSDataContainer +{ +public: + inline TLSData() {} + inline ~TLSData() { release(); } // Release key and delete associated data + inline T* get() const { return (T*)getData(); } // Get data associated with key + inline T& getRef() const { T* ptr = (T*)getData(); CV_Assert(ptr); return *ptr; } // Get data associated with key + + // Get data from all threads + inline void gather(std::vector &data) const + { + std::vector &dataVoid = reinterpret_cast&>(data); + gatherData(dataVoid); + } + + inline void cleanup() { TLSDataContainer::cleanup(); } + +private: + virtual void* createDataInstance() const CV_OVERRIDE {return new T;} // Wrapper to allocate data by template + virtual void deleteDataInstance(void* pData) const CV_OVERRIDE {delete (T*)pData;} // Wrapper to release data by template + + // Disable TLS copy operations + TLSData(TLSData &) {} + TLSData& operator =(const TLSData &) {return *this;} +}; + +/** @brief Designed for command line parsing + +The sample below demonstrates how to use CommandLineParser: +@code + CommandLineParser parser(argc, argv, keys); + parser.about("Application name v1.0.0"); + + if (parser.has("help")) + { + parser.printMessage(); + return 0; + } + + int N = parser.get("N"); + double fps = parser.get("fps"); + String path = parser.get("path"); + + use_time_stamp = parser.has("timestamp"); + + String img1 = parser.get(0); + String img2 = parser.get(1); + + int repeat = parser.get(2); + + if (!parser.check()) + { + parser.printErrors(); + return 0; + } +@endcode + +### Keys syntax + +The keys parameter is a string containing several blocks, each one is enclosed in curly braces and +describes one argument. Each argument contains three parts separated by the `|` symbol: + +-# argument names is a space-separated list of option synonyms (to mark argument as positional, prefix it with the `@` symbol) +-# default value will be used if the argument was not provided (can be empty) +-# help message (can be empty) + +For example: + +@code{.cpp} + const String keys = + "{help h usage ? | | print this message }" + "{@image1 | | image1 for compare }" + "{@image2 || image2 for compare }" + "{@repeat |1 | number }" + "{path |. | path to file }" + "{fps | -1.0 | fps for output video }" + "{N count |100 | count of objects }" + "{ts timestamp | | use time stamp }" + ; +} +@endcode + +Note that there are no default values for `help` and `timestamp` so we can check their presence using the `has()` method. +Arguments with default values are considered to be always present. Use the `get()` method in these cases to check their +actual value instead. + +String keys like `get("@image1")` return the empty string `""` by default - even with an empty default value. +Use the special `` default value to enforce that the returned string must not be empty. (like in `get("@image2")`) + +### Usage + +For the described keys: + +@code{.sh} + # Good call (3 positional parameters: image1, image2 and repeat; N is 200, ts is true) + $ ./app -N=200 1.png 2.jpg 19 -ts + + # Bad call + $ ./app -fps=aaa + ERRORS: + Parameter 'fps': can not convert: [aaa] to [double] +@endcode + */ +class CV_EXPORTS CommandLineParser +{ +public: + + /** @brief Constructor + + Initializes command line parser object + + @param argc number of command line arguments (from main()) + @param argv array of command line arguments (from main()) + @param keys string describing acceptable command line parameters (see class description for syntax) + */ + CommandLineParser(int argc, const char* const argv[], const String& keys); + + /** @brief Copy constructor */ + CommandLineParser(const CommandLineParser& parser); + + /** @brief Assignment operator */ + CommandLineParser& operator = (const CommandLineParser& parser); + + /** @brief Destructor */ + ~CommandLineParser(); + + /** @brief Returns application path + + This method returns the path to the executable from the command line (`argv[0]`). + + For example, if the application has been started with such a command: + @code{.sh} + $ ./bin/my-executable + @endcode + this method will return `./bin`. + */ + String getPathToApplication() const; + + /** @brief Access arguments by name + + Returns argument converted to selected type. If the argument is not known or can not be + converted to selected type, the error flag is set (can be checked with @ref check). + + For example, define: + @code{.cpp} + String keys = "{N count||}"; + @endcode + + Call: + @code{.sh} + $ ./my-app -N=20 + # or + $ ./my-app --count=20 + @endcode + + Access: + @code{.cpp} + int N = parser.get("N"); + @endcode + + @param name name of the argument + @param space_delete remove spaces from the left and right of the string + @tparam T the argument will be converted to this type if possible + + @note You can access positional arguments by their `@`-prefixed name: + @code{.cpp} + parser.get("@image"); + @endcode + */ + template + T get(const String& name, bool space_delete = true) const + { + T val = T(); + getByName(name, space_delete, ParamType::type, (void*)&val); + return val; + } + + /** @brief Access positional arguments by index + + Returns argument converted to selected type. Indexes are counted from zero. + + For example, define: + @code{.cpp} + String keys = "{@arg1||}{@arg2||}" + @endcode + + Call: + @code{.sh} + ./my-app abc qwe + @endcode + + Access arguments: + @code{.cpp} + String val_1 = parser.get(0); // returns "abc", arg1 + String val_2 = parser.get(1); // returns "qwe", arg2 + @endcode + + @param index index of the argument + @param space_delete remove spaces from the left and right of the string + @tparam T the argument will be converted to this type if possible + */ + template + T get(int index, bool space_delete = true) const + { + T val = T(); + getByIndex(index, space_delete, ParamType::type, (void*)&val); + return val; + } + + /** @brief Check if field was provided in the command line + + @param name argument name to check + */ + bool has(const String& name) const; + + /** @brief Check for parsing errors + + Returns false if error occurred while accessing the parameters (bad conversion, missing arguments, + etc.). Call @ref printErrors to print error messages list. + */ + bool check() const; + + /** @brief Set the about message + + The about message will be shown when @ref printMessage is called, right before arguments table. + */ + void about(const String& message); + + /** @brief Print help message + + This method will print standard help message containing the about message and arguments description. + + @sa about + */ + void printMessage() const; + + /** @brief Print list of errors occurred + + @sa check + */ + void printErrors() const; + +protected: + void getByName(const String& name, bool space_delete, int type, void* dst) const; + void getByIndex(int index, bool space_delete, int type, void* dst) const; + + struct Impl; + Impl* impl; +}; + +//! @} core_utils + +//! @cond IGNORED + +/////////////////////////////// AutoBuffer implementation //////////////////////////////////////// + +template inline +AutoBuffer<_Tp, fixed_size>::AutoBuffer() +{ + ptr = buf; + sz = fixed_size; +} + +template inline +AutoBuffer<_Tp, fixed_size>::AutoBuffer(size_t _size) +{ + ptr = buf; + sz = fixed_size; + allocate(_size); +} + +template inline +AutoBuffer<_Tp, fixed_size>::AutoBuffer(const AutoBuffer<_Tp, fixed_size>& abuf ) +{ + ptr = buf; + sz = fixed_size; + allocate(abuf.size()); + for( size_t i = 0; i < sz; i++ ) + ptr[i] = abuf.ptr[i]; +} + +template inline AutoBuffer<_Tp, fixed_size>& +AutoBuffer<_Tp, fixed_size>::operator = (const AutoBuffer<_Tp, fixed_size>& abuf) +{ + if( this != &abuf ) + { + deallocate(); + allocate(abuf.size()); + for( size_t i = 0; i < sz; i++ ) + ptr[i] = abuf.ptr[i]; + } + return *this; +} + +template inline +AutoBuffer<_Tp, fixed_size>::~AutoBuffer() +{ deallocate(); } + +template inline void +AutoBuffer<_Tp, fixed_size>::allocate(size_t _size) +{ + if(_size <= sz) + { + sz = _size; + return; + } + deallocate(); + sz = _size; + if(_size > fixed_size) + { + ptr = new _Tp[_size]; + } +} + +template inline void +AutoBuffer<_Tp, fixed_size>::deallocate() +{ + if( ptr != buf ) + { + delete[] ptr; + ptr = buf; + sz = fixed_size; + } +} + +template inline void +AutoBuffer<_Tp, fixed_size>::resize(size_t _size) +{ + if(_size <= sz) + { + sz = _size; + return; + } + size_t i, prevsize = sz, minsize = MIN(prevsize, _size); + _Tp* prevptr = ptr; + + ptr = _size > fixed_size ? new _Tp[_size] : buf; + sz = _size; + + if( ptr != prevptr ) + for( i = 0; i < minsize; i++ ) + ptr[i] = prevptr[i]; + for( i = prevsize; i < _size; i++ ) + ptr[i] = _Tp(); + + if( prevptr != buf ) + delete[] prevptr; +} + +template inline size_t +AutoBuffer<_Tp, fixed_size>::size() const +{ return sz; } + +template<> inline std::string CommandLineParser::get(int index, bool space_delete) const +{ + return get(index, space_delete); +} +template<> inline std::string CommandLineParser::get(const String& name, bool space_delete) const +{ + return get(name, space_delete); +} + +//! @endcond + + +// Basic Node class for tree building +template +class CV_EXPORTS Node +{ +public: + Node() + { + m_pParent = 0; + } + Node(OBJECT& payload) : m_payload(payload) + { + m_pParent = 0; + } + ~Node() + { + removeChilds(); + if (m_pParent) + { + int idx = m_pParent->findChild(this); + if (idx >= 0) + m_pParent->m_childs.erase(m_pParent->m_childs.begin() + idx); + } + } + + Node* findChild(OBJECT& payload) const + { + for(size_t i = 0; i < this->m_childs.size(); i++) + { + if(this->m_childs[i]->m_payload == payload) + return this->m_childs[i]; + } + return NULL; + } + + int findChild(Node *pNode) const + { + for (size_t i = 0; i < this->m_childs.size(); i++) + { + if(this->m_childs[i] == pNode) + return (int)i; + } + return -1; + } + + void addChild(Node *pNode) + { + if(!pNode) + return; + + CV_Assert(pNode->m_pParent == 0); + pNode->m_pParent = this; + this->m_childs.push_back(pNode); + } + + void removeChilds() + { + for(size_t i = 0; i < m_childs.size(); i++) + { + m_childs[i]->m_pParent = 0; // avoid excessive parent vector trimming + delete m_childs[i]; + } + m_childs.clear(); + } + + int getDepth() + { + int count = 0; + Node *pParent = m_pParent; + while(pParent) count++, pParent = pParent->m_pParent; + return count; + } + +public: + OBJECT m_payload; + Node* m_pParent; + std::vector*> m_childs; +}; + +// Instrumentation external interface +namespace instr +{ + +#if !defined OPENCV_ABI_CHECK + +enum TYPE +{ + TYPE_GENERAL = 0, // OpenCV API function, e.g. exported function + TYPE_MARKER, // Information marker + TYPE_WRAPPER, // Wrapper function for implementation + TYPE_FUN, // Simple function call +}; + +enum IMPL +{ + IMPL_PLAIN = 0, + IMPL_IPP, + IMPL_OPENCL, +}; + +struct NodeDataTls +{ + NodeDataTls() + { + m_ticksTotal = 0; + } + uint64 m_ticksTotal; +}; + +class CV_EXPORTS NodeData +{ +public: + NodeData(const char* funName = 0, const char* fileName = NULL, int lineNum = 0, void* retAddress = NULL, bool alwaysExpand = false, cv::instr::TYPE instrType = TYPE_GENERAL, cv::instr::IMPL implType = IMPL_PLAIN); + NodeData(NodeData &ref); + ~NodeData(); + NodeData& operator=(const NodeData&); + + cv::String m_funName; + cv::instr::TYPE m_instrType; + cv::instr::IMPL m_implType; + const char* m_fileName; + int m_lineNum; + void* m_retAddress; + bool m_alwaysExpand; + bool m_funError; + + volatile int m_counter; + volatile uint64 m_ticksTotal; + TLSData m_tls; + int m_threads; + + // No synchronization + double getTotalMs() const { return ((double)m_ticksTotal / cv::getTickFrequency()) * 1000; } + double getMeanMs() const { return (((double)m_ticksTotal/m_counter) / cv::getTickFrequency()) * 1000; } +}; +bool operator==(const NodeData& lhs, const NodeData& rhs); + +typedef Node InstrNode; + +CV_EXPORTS InstrNode* getTrace(); + +#endif // !defined OPENCV_ABI_CHECK + + +CV_EXPORTS bool useInstrumentation(); +CV_EXPORTS void setUseInstrumentation(bool flag); +CV_EXPORTS void resetTrace(); + +enum FLAGS +{ + FLAGS_NONE = 0, + FLAGS_MAPPING = 0x01, + FLAGS_EXPAND_SAME_NAMES = 0x02, +}; + +CV_EXPORTS void setFlags(FLAGS modeFlags); +static inline void setFlags(int modeFlags) { setFlags((FLAGS)modeFlags); } +CV_EXPORTS FLAGS getFlags(); + +} // namespace instr + + +namespace samples { + +//! @addtogroup core_utils_samples +// This section describes utility functions for OpenCV samples. +// +// @note Implementation of these utilities is not thread-safe. +// +//! @{ + +/** @brief Try to find requested data file + +Search directories: + +1. Directories passed via `addSamplesDataSearchPath()` +2. OPENCV_SAMPLES_DATA_PATH_HINT environment variable +3. OPENCV_SAMPLES_DATA_PATH environment variable + If parameter value is not empty and nothing is found then stop searching. +4. Detects build/install path based on: + a. current working directory (CWD) + b. and/or binary module location (opencv_core/opencv_world, doesn't work with static linkage) +5. Scan `/{,data,samples/data}` directories if build directory is detected or the current directory is in source tree. +6. Scan `/share/OpenCV` directory if install directory is detected. + +@see cv::utils::findDataFile + +@param relative_path Relative path to data file +@param required Specify "file not found" handling. + If true, function prints information message and raises cv::Exception. + If false, function returns empty result +@param silentMode Disables messages +@return Returns path (absolute or relative to the current directory) or empty string if file is not found +*/ +CV_EXPORTS_W cv::String findFile(const cv::String& relative_path, bool required = true, bool silentMode = false); + +CV_EXPORTS_W cv::String findFileOrKeep(const cv::String& relative_path, bool silentMode = false); + +inline cv::String findFileOrKeep(const cv::String& relative_path, bool silentMode) +{ + cv::String res = findFile(relative_path, false, silentMode); + if (res.empty()) + return relative_path; + return res; +} + +/** @brief Override search data path by adding new search location + +Use this only to override default behavior +Passed paths are used in LIFO order. + +@param path Path to used samples data +*/ +CV_EXPORTS_W void addSamplesDataSearchPath(const cv::String& path); + +/** @brief Append samples search data sub directory + +General usage is to add OpenCV modules name (`/modules//samples/data` -> `/samples/data` + `modules//samples/data`). +Passed subdirectories are used in LIFO order. + +@param subdir samples data sub directory +*/ +CV_EXPORTS_W void addSamplesDataSearchSubDirectory(const cv::String& subdir); + +//! @} +} // namespace samples + +namespace utils { + +CV_EXPORTS int getThreadID(); + +} // namespace + +} //namespace cv + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/core/core_c.h" +#endif + +#endif //OPENCV_CORE_UTILITY_H diff --git a/3rdparty/opencv/include/opencv2/core/utils/filesystem.hpp b/3rdparty/opencv/include/opencv2/core/utils/filesystem.hpp new file mode 100644 index 00000000..00b0dd1c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/utils/filesystem.hpp @@ -0,0 +1,78 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_UTILS_FILESYSTEM_HPP +#define OPENCV_UTILS_FILESYSTEM_HPP + +namespace cv { namespace utils { namespace fs { + + +CV_EXPORTS bool exists(const cv::String& path); +CV_EXPORTS bool isDirectory(const cv::String& path); + +CV_EXPORTS void remove_all(const cv::String& path); + + +CV_EXPORTS cv::String getcwd(); + +/** @brief Converts path p to a canonical absolute path + * Symlinks are processed if there is support for them on running platform. + * + * @param path input path. Target file/directory should exist. + */ +CV_EXPORTS cv::String canonical(const cv::String& path); + +/** Join path components */ +CV_EXPORTS cv::String join(const cv::String& base, const cv::String& path); + +/** + * Generate a list of all files that match the globbing pattern. + * + * Result entries are prefixed by base directory path. + * + * @param directory base directory + * @param pattern filter pattern (based on '*'/'?' symbols). Use empty string to disable filtering and return all results + * @param[out] result result of globing. + * @param recursive scan nested directories too + * @param includeDirectories include directories into results list + */ +CV_EXPORTS void glob(const cv::String& directory, const cv::String& pattern, + CV_OUT std::vector& result, + bool recursive = false, bool includeDirectories = false); + +/** + * Generate a list of all files that match the globbing pattern. + * + * @param directory base directory + * @param pattern filter pattern (based on '*'/'?' symbols). Use empty string to disable filtering and return all results + * @param[out] result globbing result with relative paths from base directory + * @param recursive scan nested directories too + * @param includeDirectories include directories into results list + */ +CV_EXPORTS void glob_relative(const cv::String& directory, const cv::String& pattern, + CV_OUT std::vector& result, + bool recursive = false, bool includeDirectories = false); + + +CV_EXPORTS bool createDirectory(const cv::String& path); +CV_EXPORTS bool createDirectories(const cv::String& path); + +#ifdef __OPENCV_BUILD +// TODO +//CV_EXPORTS cv::String getTempDirectory(); + +/** + * @brief Returns directory to store OpenCV cache files + * Create sub-directory in common OpenCV cache directory if it doesn't exist. + * @param sub_directory_name name of sub-directory. NULL or "" value asks to return root cache directory. + * @param configuration_name optional name of configuration parameter name which overrides default behavior. + * @return Path to cache directory. Returns empty string if cache directories support is not available. Returns "disabled" if cache disabled by user. + */ +CV_EXPORTS cv::String getCacheDirectory(const char* sub_directory_name, const char* configuration_name = NULL); + +#endif + +}}} // namespace + +#endif // OPENCV_UTILS_FILESYSTEM_HPP diff --git a/3rdparty/opencv/include/opencv2/core/utils/logger.defines.hpp b/3rdparty/opencv/include/opencv2/core/utils/logger.defines.hpp new file mode 100644 index 00000000..b2dfc417 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/utils/logger.defines.hpp @@ -0,0 +1,22 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_LOGGER_DEFINES_HPP +#define OPENCV_LOGGER_DEFINES_HPP + +//! @addtogroup core_logging +//! @{ + +// Supported logging levels and their semantic +#define CV_LOG_LEVEL_SILENT 0 //!< for using in setLogLevel() call +#define CV_LOG_LEVEL_FATAL 1 //!< Fatal (critical) error (unrecoverable internal error) +#define CV_LOG_LEVEL_ERROR 2 //!< Error message +#define CV_LOG_LEVEL_WARN 3 //!< Warning message +#define CV_LOG_LEVEL_INFO 4 //!< Info message +#define CV_LOG_LEVEL_DEBUG 5 //!< Debug message. Disabled in the "Release" build. +#define CV_LOG_LEVEL_VERBOSE 6 //!< Verbose (trace) messages. Requires verbosity level. Disabled in the "Release" build. + +//! @} + +#endif // OPENCV_LOGGER_DEFINES_HPP diff --git a/3rdparty/opencv/include/opencv2/core/utils/logger.hpp b/3rdparty/opencv/include/opencv2/core/utils/logger.hpp new file mode 100644 index 00000000..47094f99 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/utils/logger.hpp @@ -0,0 +1,87 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_LOGGER_HPP +#define OPENCV_LOGGER_HPP + +#include +#include +#include // INT_MAX + +#include "logger.defines.hpp" + +//! @addtogroup core_logging +// This section describes OpenCV logging utilities. +// +//! @{ + +namespace cv { +namespace utils { +namespace logging { + +//! Supported logging levels and their semantic +enum LogLevel { + LOG_LEVEL_SILENT = 0, //!< for using in setLogVevel() call + LOG_LEVEL_FATAL = 1, //!< Fatal (critical) error (unrecoverable internal error) + LOG_LEVEL_ERROR = 2, //!< Error message + LOG_LEVEL_WARNING = 3, //!< Warning message + LOG_LEVEL_INFO = 4, //!< Info message + LOG_LEVEL_DEBUG = 5, //!< Debug message. Disabled in the "Release" build. + LOG_LEVEL_VERBOSE = 6, //!< Verbose (trace) messages. Requires verbosity level. Disabled in the "Release" build. +#ifndef CV_DOXYGEN + ENUM_LOG_LEVEL_FORCE_INT = INT_MAX +#endif +}; + +/** Set global logging level +@return previous logging level +*/ +CV_EXPORTS LogLevel setLogLevel(LogLevel logLevel); +/** Get global logging level */ +CV_EXPORTS LogLevel getLogLevel(); + +namespace internal { +/** Write log message */ +CV_EXPORTS void writeLogMessage(LogLevel logLevel, const char* message); +} // namespace + +/** + * \def CV_LOG_STRIP_LEVEL + * + * Define CV_LOG_STRIP_LEVEL=CV_LOG_LEVEL_[DEBUG|INFO|WARN|ERROR|FATAL|DISABLED] to compile out anything at that and before that logging level + */ +#ifndef CV_LOG_STRIP_LEVEL +# if defined NDEBUG +# define CV_LOG_STRIP_LEVEL CV_LOG_LEVEL_DEBUG +# else +# define CV_LOG_STRIP_LEVEL CV_LOG_LEVEL_VERBOSE +# endif +#endif + + +#define CV_LOG_FATAL(tag, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_FATAL) break; std::stringstream ss; ss << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_FATAL, ss.str().c_str()); break; } +#define CV_LOG_ERROR(tag, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_ERROR) break; std::stringstream ss; ss << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_ERROR, ss.str().c_str()); break; } +#define CV_LOG_WARNING(tag, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_WARNING) break; std::stringstream ss; ss << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_WARNING, ss.str().c_str()); break; } +#if CV_LOG_STRIP_LEVEL <= CV_LOG_LEVEL_INFO +#define CV_LOG_INFO(tag, ...) +#else +#define CV_LOG_INFO(tag, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_INFO) break; std::stringstream ss; ss << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_INFO, ss.str().c_str()); break; } +#endif +#if CV_LOG_STRIP_LEVEL <= CV_LOG_LEVEL_DEBUG +#define CV_LOG_DEBUG(tag, ...) +#else +#define CV_LOG_DEBUG(tag, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_DEBUG) break; std::stringstream ss; ss << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_DEBUG, ss.str().c_str()); break; } +#endif +#if CV_LOG_STRIP_LEVEL <= CV_LOG_LEVEL_VERBOSE +#define CV_LOG_VERBOSE(tag, v, ...) +#else +#define CV_LOG_VERBOSE(tag, v, ...) for(;;) { if (cv::utils::logging::getLogLevel() < cv::utils::logging::LOG_LEVEL_VERBOSE) break; std::stringstream ss; ss << "[VERB" << v << ":" << cv::utils::getThreadID() << "] " << __VA_ARGS__; cv::utils::logging::internal::writeLogMessage(cv::utils::logging::LOG_LEVEL_VERBOSE, ss.str().c_str()); break; } +#endif + + +}}} // namespace + +//! @} + +#endif // OPENCV_LOGGER_HPP diff --git a/3rdparty/opencv/include/opencv2/core/utils/trace.hpp b/3rdparty/opencv/include/opencv2/core/utils/trace.hpp new file mode 100644 index 00000000..858e973a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/utils/trace.hpp @@ -0,0 +1,254 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_TRACE_HPP +#define OPENCV_TRACE_HPP + +#include + +//! @addtogroup core_logging +// This section describes OpenCV tracing utilities. +// +//! @{ + +namespace cv { +namespace utils { +namespace trace { + +//! Macro to trace function +#define CV_TRACE_FUNCTION() + +#define CV_TRACE_FUNCTION_SKIP_NESTED() + +//! Trace code scope. +//! @note Dynamic names are not supported in this macro (on stack or heap). Use string literals here only, like "initialize". +#define CV_TRACE_REGION(name_as_static_string_literal) +//! mark completed of the current opened region and create new one +//! @note Dynamic names are not supported in this macro (on stack or heap). Use string literals here only, like "step1". +#define CV_TRACE_REGION_NEXT(name_as_static_string_literal) + +//! Macro to trace argument value +#define CV_TRACE_ARG(arg_id) + +//! Macro to trace argument value (expanded version) +#define CV_TRACE_ARG_VALUE(arg_id, arg_name, value) + +//! @cond IGNORED +#define CV_TRACE_NS cv::utils::trace + +#if !defined(OPENCV_DISABLE_TRACE) && defined(__EMSCRIPTEN__) +#define OPENCV_DISABLE_TRACE 1 +#endif + +namespace details { + +#ifndef __OPENCV_TRACE +# if defined __OPENCV_BUILD && !defined __OPENCV_TESTS && !defined __OPENCV_APPS +# define __OPENCV_TRACE 1 +# else +# define __OPENCV_TRACE 0 +# endif +#endif + +#ifndef CV_TRACE_FILENAME +# define CV_TRACE_FILENAME __FILE__ +#endif + +#ifndef CV__TRACE_FUNCTION +# if defined _MSC_VER +# define CV__TRACE_FUNCTION __FUNCSIG__ +# elif defined __GNUC__ +# define CV__TRACE_FUNCTION __PRETTY_FUNCTION__ +# else +# define CV__TRACE_FUNCTION "" +# endif +#endif + +//! Thread-local instance (usually allocated on stack) +class CV_EXPORTS Region +{ +public: + struct LocationExtraData; + struct LocationStaticStorage + { + LocationExtraData** ppExtra; //< implementation specific data + const char* name; //< region name (function name or other custom name) + const char* filename; //< source code filename + int line; //< source code line + int flags; //< flags (implementation code path: Plain, IPP, OpenCL) + }; + + Region(const LocationStaticStorage& location); + inline ~Region() + { + if (implFlags != 0) + destroy(); + CV_DbgAssert(implFlags == 0); + CV_DbgAssert(pImpl == NULL); + } + + class Impl; + Impl* pImpl; // NULL if current region is not active + int implFlags; // see RegionFlag, 0 if region is ignored + + bool isActive() const { return pImpl != NULL; } + + void destroy(); +private: + Region(const Region&); // disabled + Region& operator= (const Region&); // disabled +}; + +//! Specify region flags +enum RegionLocationFlag { + REGION_FLAG_FUNCTION = (1 << 0), //< region is function (=1) / nested named region (=0) + REGION_FLAG_APP_CODE = (1 << 1), //< region is Application code (=1) / OpenCV library code (=0) + REGION_FLAG_SKIP_NESTED = (1 << 2), //< avoid processing of nested regions + + REGION_FLAG_IMPL_IPP = (1 << 16), //< region is part of IPP code path + REGION_FLAG_IMPL_OPENCL = (2 << 16), //< region is part of OpenCL code path + REGION_FLAG_IMPL_OPENVX = (3 << 16), //< region is part of OpenVX code path + + REGION_FLAG_IMPL_MASK = (15 << 16), + + REGION_FLAG_REGION_FORCE = (1 << 30), + REGION_FLAG_REGION_NEXT = (1 << 31), //< close previous region (see #CV_TRACE_REGION_NEXT macro) + + ENUM_REGION_FLAG_FORCE_INT = INT_MAX +}; + +struct CV_EXPORTS TraceArg { +public: + struct ExtraData; + ExtraData** ppExtra; + const char* name; + int flags; +}; +/** @brief Add meta information to current region (function) + * See CV_TRACE_ARG macro + * @param arg argument information structure (global static cache) + * @param value argument value (can by dynamic string literal in case of string, static allocation is not required) + */ +CV_EXPORTS void traceArg(const TraceArg& arg, const char* value); +//! @overload +CV_EXPORTS void traceArg(const TraceArg& arg, int value); +//! @overload +CV_EXPORTS void traceArg(const TraceArg& arg, int64 value); +//! @overload +CV_EXPORTS void traceArg(const TraceArg& arg, double value); + +#define CV__TRACE_LOCATION_VARNAME(loc_id) CVAUX_CONCAT(CVAUX_CONCAT(__cv_trace_location_, loc_id), __LINE__) +#define CV__TRACE_LOCATION_EXTRA_VARNAME(loc_id) CVAUX_CONCAT(CVAUX_CONCAT(__cv_trace_location_extra_, loc_id) , __LINE__) + +#define CV__TRACE_DEFINE_LOCATION_(loc_id, name, flags) \ + static CV_TRACE_NS::details::Region::LocationExtraData* CV__TRACE_LOCATION_EXTRA_VARNAME(loc_id) = 0; \ + static const CV_TRACE_NS::details::Region::LocationStaticStorage \ + CV__TRACE_LOCATION_VARNAME(loc_id) = { &(CV__TRACE_LOCATION_EXTRA_VARNAME(loc_id)), name, CV_TRACE_FILENAME, __LINE__, flags}; + +#define CV__TRACE_DEFINE_LOCATION_FN(name, flags) CV__TRACE_DEFINE_LOCATION_(fn, name, ((flags) | CV_TRACE_NS::details::REGION_FLAG_FUNCTION)) + + +#define CV__TRACE_OPENCV_FUNCTION() \ + CV__TRACE_DEFINE_LOCATION_FN(CV__TRACE_FUNCTION, 0); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + +#define CV__TRACE_OPENCV_FUNCTION_NAME(name) \ + CV__TRACE_DEFINE_LOCATION_FN(name, 0); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + +#define CV__TRACE_APP_FUNCTION() \ + CV__TRACE_DEFINE_LOCATION_FN(CV__TRACE_FUNCTION, CV_TRACE_NS::details::REGION_FLAG_APP_CODE); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + +#define CV__TRACE_APP_FUNCTION_NAME(name) \ + CV__TRACE_DEFINE_LOCATION_FN(name, CV_TRACE_NS::details::REGION_FLAG_APP_CODE); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + + +#define CV__TRACE_OPENCV_FUNCTION_SKIP_NESTED() \ + CV__TRACE_DEFINE_LOCATION_FN(CV__TRACE_FUNCTION, CV_TRACE_NS::details::REGION_FLAG_SKIP_NESTED); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + +#define CV__TRACE_OPENCV_FUNCTION_NAME_SKIP_NESTED(name) \ + CV__TRACE_DEFINE_LOCATION_FN(name, CV_TRACE_NS::details::REGION_FLAG_SKIP_NESTED); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + +#define CV__TRACE_APP_FUNCTION_SKIP_NESTED() \ + CV__TRACE_DEFINE_LOCATION_FN(CV__TRACE_FUNCTION, CV_TRACE_NS::details::REGION_FLAG_SKIP_NESTED | CV_TRACE_NS::details::REGION_FLAG_APP_CODE); \ + const CV_TRACE_NS::details::Region __region_fn(CV__TRACE_LOCATION_VARNAME(fn)); + + +#define CV__TRACE_REGION_(name_as_static_string_literal, flags) \ + CV__TRACE_DEFINE_LOCATION_(region, name_as_static_string_literal, flags); \ + CV_TRACE_NS::details::Region CVAUX_CONCAT(__region_, __LINE__)(CV__TRACE_LOCATION_VARNAME(region)); + +#define CV__TRACE_REGION(name_as_static_string_literal) CV__TRACE_REGION_(name_as_static_string_literal, 0) +#define CV__TRACE_REGION_NEXT(name_as_static_string_literal) CV__TRACE_REGION_(name_as_static_string_literal, CV_TRACE_NS::details::REGION_FLAG_REGION_NEXT) + +#define CV__TRACE_ARG_VARNAME(arg_id) CVAUX_CONCAT(__cv_trace_arg_ ## arg_id, __LINE__) +#define CV__TRACE_ARG_EXTRA_VARNAME(arg_id) CVAUX_CONCAT(__cv_trace_arg_extra_ ## arg_id, __LINE__) + +#define CV__TRACE_DEFINE_ARG_(arg_id, name, flags) \ + static CV_TRACE_NS::details::TraceArg::ExtraData* CV__TRACE_ARG_EXTRA_VARNAME(arg_id) = 0; \ + static const CV_TRACE_NS::details::TraceArg \ + CV__TRACE_ARG_VARNAME(arg_id) = { &(CV__TRACE_ARG_EXTRA_VARNAME(arg_id)), name, flags }; + +#define CV__TRACE_ARG_VALUE(arg_id, arg_name, value) \ + CV__TRACE_DEFINE_ARG_(arg_id, arg_name, 0); \ + CV_TRACE_NS::details::traceArg((CV__TRACE_ARG_VARNAME(arg_id)), value); + +#define CV__TRACE_ARG(arg_id) CV_TRACE_ARG_VALUE(arg_id, #arg_id, (arg_id)) + +} // namespace + +#ifndef OPENCV_DISABLE_TRACE +#undef CV_TRACE_FUNCTION +#undef CV_TRACE_FUNCTION_SKIP_NESTED +#if __OPENCV_TRACE +#define CV_TRACE_FUNCTION CV__TRACE_OPENCV_FUNCTION +#define CV_TRACE_FUNCTION_SKIP_NESTED CV__TRACE_OPENCV_FUNCTION_SKIP_NESTED +#else +#define CV_TRACE_FUNCTION CV__TRACE_APP_FUNCTION +#define CV_TRACE_FUNCTION_SKIP_NESTED CV__TRACE_APP_FUNCTION_SKIP_NESTED +#endif + +#undef CV_TRACE_REGION +#define CV_TRACE_REGION CV__TRACE_REGION + +#undef CV_TRACE_REGION_NEXT +#define CV_TRACE_REGION_NEXT CV__TRACE_REGION_NEXT + +#undef CV_TRACE_ARG_VALUE +#define CV_TRACE_ARG_VALUE(arg_id, arg_name, value) \ + if (__region_fn.isActive()) \ + { \ + CV__TRACE_ARG_VALUE(arg_id, arg_name, value); \ + } + +#undef CV_TRACE_ARG +#define CV_TRACE_ARG CV__TRACE_ARG + +#endif // OPENCV_DISABLE_TRACE + +#ifdef OPENCV_TRACE_VERBOSE +#define CV_TRACE_FUNCTION_VERBOSE CV_TRACE_FUNCTION +#define CV_TRACE_REGION_VERBOSE CV_TRACE_REGION +#define CV_TRACE_REGION_NEXT_VERBOSE CV_TRACE_REGION_NEXT +#define CV_TRACE_ARG_VALUE_VERBOSE CV_TRACE_ARG_VALUE +#define CV_TRACE_ARG_VERBOSE CV_TRACE_ARG +#else +#define CV_TRACE_FUNCTION_VERBOSE(...) +#define CV_TRACE_REGION_VERBOSE(...) +#define CV_TRACE_REGION_NEXT_VERBOSE(...) +#define CV_TRACE_ARG_VALUE_VERBOSE(...) +#define CV_TRACE_ARG_VERBOSE(...) +#endif + +//! @endcond + +}}} // namespace + +//! @} + +#endif // OPENCV_TRACE_HPP diff --git a/3rdparty/opencv/include/opencv2/core/va_intel.hpp b/3rdparty/opencv/include/opencv2/core/va_intel.hpp new file mode 100644 index 00000000..f6654709 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/va_intel.hpp @@ -0,0 +1,78 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +// Copyright (C) 2015, Itseez, Inc., all rights reserved. +// Third party copyrights are property of their respective owners. + +#ifndef OPENCV_CORE_VA_INTEL_HPP +#define OPENCV_CORE_VA_INTEL_HPP + +#ifndef __cplusplus +# error va_intel.hpp header must be compiled as C++ +#endif + +#include "opencv2/core.hpp" +#include "ocl.hpp" + +#if defined(HAVE_VA) +# include "va/va.h" +#else // HAVE_VA +# if !defined(_VA_H_) + typedef void* VADisplay; + typedef unsigned int VASurfaceID; +# endif // !_VA_H_ +#endif // HAVE_VA + +namespace cv { namespace va_intel { + +/** @addtogroup core_va_intel +This section describes Intel VA-API/OpenCL (CL-VA) interoperability. + +To enable CL-VA interoperability support, configure OpenCV using CMake with WITH_VA_INTEL=ON . Currently VA-API is +supported on Linux only. You should also install Intel Media Server Studio (MSS) to use this feature. You may +have to specify the path(s) to MSS components for cmake in environment variables: + +- VA_INTEL_IOCL_ROOT for Intel OpenCL (default is "/opt/intel/opencl"). + +To use CL-VA interoperability you should first create VADisplay (libva), and then call initializeContextFromVA() +function to create OpenCL context and set up interoperability. +*/ +//! @{ + +/////////////////// CL-VA Interoperability Functions /////////////////// + +namespace ocl { +using namespace cv::ocl; + +// TODO static functions in the Context class +/** @brief Creates OpenCL context from VA. +@param display - VADisplay for which CL interop should be established. +@param tryInterop - try to set up for interoperability, if true; set up for use slow copy if false. +@return Returns reference to OpenCL Context + */ +CV_EXPORTS Context& initializeContextFromVA(VADisplay display, bool tryInterop = true); + +} // namespace cv::va_intel::ocl + +/** @brief Converts InputArray to VASurfaceID object. +@param display - VADisplay object. +@param src - source InputArray. +@param surface - destination VASurfaceID object. +@param size - size of image represented by VASurfaceID object. + */ +CV_EXPORTS void convertToVASurface(VADisplay display, InputArray src, VASurfaceID surface, Size size); + +/** @brief Converts VASurfaceID object to OutputArray. +@param display - VADisplay object. +@param surface - source VASurfaceID object. +@param size - size of image represented by VASurfaceID object. +@param dst - destination OutputArray. + */ +CV_EXPORTS void convertFromVASurface(VADisplay display, VASurfaceID surface, Size size, OutputArray dst); + +//! @} + +}} // namespace cv::va_intel + +#endif /* OPENCV_CORE_VA_INTEL_HPP */ diff --git a/3rdparty/opencv/include/opencv2/core/version.hpp b/3rdparty/opencv/include/opencv2/core/version.hpp new file mode 100644 index 00000000..fe6df950 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/version.hpp @@ -0,0 +1,26 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_VERSION_HPP +#define OPENCV_VERSION_HPP + +#define CV_VERSION_MAJOR 3 +#define CV_VERSION_MINOR 4 +#define CV_VERSION_REVISION 6 +#define CV_VERSION_STATUS "" + +#define CVAUX_STR_EXP(__A) #__A +#define CVAUX_STR(__A) CVAUX_STR_EXP(__A) + +#define CVAUX_STRW_EXP(__A) L ## #__A +#define CVAUX_STRW(__A) CVAUX_STRW_EXP(__A) + +#define CV_VERSION CVAUX_STR(CV_VERSION_MAJOR) "." CVAUX_STR(CV_VERSION_MINOR) "." CVAUX_STR(CV_VERSION_REVISION) CV_VERSION_STATUS + +/* old style version constants*/ +#define CV_MAJOR_VERSION CV_VERSION_MAJOR +#define CV_MINOR_VERSION CV_VERSION_MINOR +#define CV_SUBMINOR_VERSION CV_VERSION_REVISION + +#endif // OPENCV_VERSION_HPP diff --git a/3rdparty/opencv/include/opencv2/core/vsx_utils.hpp b/3rdparty/opencv/include/opencv2/core/vsx_utils.hpp new file mode 100644 index 00000000..6e2baeac --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/vsx_utils.hpp @@ -0,0 +1,1013 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html + +#ifndef OPENCV_HAL_VSX_UTILS_HPP +#define OPENCV_HAL_VSX_UTILS_HPP + +#include "opencv2/core/cvdef.h" + +#ifndef SKIP_INCLUDES +# include +#endif + +//! @addtogroup core_utils_vsx +//! @{ +#if CV_VSX + +#define __VSX_S16__(c, v) (c){v, v, v, v, v, v, v, v, v, v, v, v, v, v, v, v} +#define __VSX_S8__(c, v) (c){v, v, v, v, v, v, v, v} +#define __VSX_S4__(c, v) (c){v, v, v, v} +#define __VSX_S2__(c, v) (c){v, v} + +typedef __vector unsigned char vec_uchar16; +#define vec_uchar16_set(...) (vec_uchar16){__VA_ARGS__} +#define vec_uchar16_sp(c) (__VSX_S16__(vec_uchar16, (unsigned char)c)) +#define vec_uchar16_c(v) ((vec_uchar16)(v)) +#define vec_uchar16_z vec_uchar16_sp(0) + +typedef __vector signed char vec_char16; +#define vec_char16_set(...) (vec_char16){__VA_ARGS__} +#define vec_char16_sp(c) (__VSX_S16__(vec_char16, (signed char)c)) +#define vec_char16_c(v) ((vec_char16)(v)) +#define vec_char16_z vec_char16_sp(0) + +typedef __vector unsigned short vec_ushort8; +#define vec_ushort8_set(...) (vec_ushort8){__VA_ARGS__} +#define vec_ushort8_sp(c) (__VSX_S8__(vec_ushort8, (unsigned short)c)) +#define vec_ushort8_c(v) ((vec_ushort8)(v)) +#define vec_ushort8_z vec_ushort8_sp(0) + +typedef __vector signed short vec_short8; +#define vec_short8_set(...) (vec_short8){__VA_ARGS__} +#define vec_short8_sp(c) (__VSX_S8__(vec_short8, (signed short)c)) +#define vec_short8_c(v) ((vec_short8)(v)) +#define vec_short8_z vec_short8_sp(0) + +typedef __vector unsigned int vec_uint4; +#define vec_uint4_set(...) (vec_uint4){__VA_ARGS__} +#define vec_uint4_sp(c) (__VSX_S4__(vec_uint4, (unsigned int)c)) +#define vec_uint4_c(v) ((vec_uint4)(v)) +#define vec_uint4_z vec_uint4_sp(0) + +typedef __vector signed int vec_int4; +#define vec_int4_set(...) (vec_int4){__VA_ARGS__} +#define vec_int4_sp(c) (__VSX_S4__(vec_int4, (signed int)c)) +#define vec_int4_c(v) ((vec_int4)(v)) +#define vec_int4_z vec_int4_sp(0) + +typedef __vector float vec_float4; +#define vec_float4_set(...) (vec_float4){__VA_ARGS__} +#define vec_float4_sp(c) (__VSX_S4__(vec_float4, c)) +#define vec_float4_c(v) ((vec_float4)(v)) +#define vec_float4_z vec_float4_sp(0) + +typedef __vector unsigned long long vec_udword2; +#define vec_udword2_set(...) (vec_udword2){__VA_ARGS__} +#define vec_udword2_sp(c) (__VSX_S2__(vec_udword2, (unsigned long long)c)) +#define vec_udword2_c(v) ((vec_udword2)(v)) +#define vec_udword2_z vec_udword2_sp(0) + +typedef __vector signed long long vec_dword2; +#define vec_dword2_set(...) (vec_dword2){__VA_ARGS__} +#define vec_dword2_sp(c) (__VSX_S2__(vec_dword2, (signed long long)c)) +#define vec_dword2_c(v) ((vec_dword2)(v)) +#define vec_dword2_z vec_dword2_sp(0) + +typedef __vector double vec_double2; +#define vec_double2_set(...) (vec_double2){__VA_ARGS__} +#define vec_double2_c(v) ((vec_double2)(v)) +#define vec_double2_sp(c) (__VSX_S2__(vec_double2, c)) +#define vec_double2_z vec_double2_sp(0) + +#define vec_bchar16 __vector __bool char +#define vec_bchar16_set(...) (vec_bchar16){__VA_ARGS__} +#define vec_bchar16_c(v) ((vec_bchar16)(v)) + +#define vec_bshort8 __vector __bool short +#define vec_bshort8_set(...) (vec_bshort8){__VA_ARGS__} +#define vec_bshort8_c(v) ((vec_bshort8)(v)) + +#define vec_bint4 __vector __bool int +#define vec_bint4_set(...) (vec_bint4){__VA_ARGS__} +#define vec_bint4_c(v) ((vec_bint4)(v)) + +#define vec_bdword2 __vector __bool long long +#define vec_bdword2_set(...) (vec_bdword2){__VA_ARGS__} +#define vec_bdword2_c(v) ((vec_bdword2)(v)) + +#define VSX_FINLINE(tp) extern inline tp __attribute__((always_inline)) + +#define VSX_REDIRECT_1RG(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a) { return fn2(a); } + +#define VSX_REDIRECT_2RG(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a, const rg& b) { return fn2(a, b); } + +/* + * GCC VSX compatibility +**/ +#if defined(__GNUG__) && !defined(__clang__) + +// inline asm helper +#define VSX_IMPL_1RG(rt, rto, rg, rgo, opc, fnm) \ +VSX_FINLINE(rt) fnm(const rg& a) \ +{ rt rs; __asm__ __volatile__(#opc" %x0,%x1" : "="#rto (rs) : #rgo (a)); return rs; } + +#define VSX_IMPL_1VRG(rt, rg, opc, fnm) \ +VSX_FINLINE(rt) fnm(const rg& a) \ +{ rt rs; __asm__ __volatile__(#opc" %0,%1" : "=v" (rs) : "v" (a)); return rs; } + +#define VSX_IMPL_2VRG_F(rt, rg, fopc, fnm) \ +VSX_FINLINE(rt) fnm(const rg& a, const rg& b) \ +{ rt rs; __asm__ __volatile__(fopc : "=v" (rs) : "v" (a), "v" (b)); return rs; } + +#define VSX_IMPL_2VRG(rt, rg, opc, fnm) VSX_IMPL_2VRG_F(rt, rg, #opc" %0,%1,%2", fnm) + +#if __GNUG__ < 7 +// up to GCC 6 vec_mul only supports precisions and llong +# ifdef vec_mul +# undef vec_mul +# endif +/* + * there's no a direct instruction for supporting 8-bit, 16-bit multiplication in ISA 2.07, + * XLC Implement it by using instruction "multiply even", "multiply odd" and "permute" +**/ +# define VSX_IMPL_MULH(Tvec, cperm) \ + VSX_FINLINE(Tvec) vec_mul(const Tvec& a, const Tvec& b) \ + { \ + static const vec_uchar16 ev_od = {cperm}; \ + return vec_perm((Tvec)vec_mule(a, b), (Tvec)vec_mulo(a, b), ev_od); \ + } + #define VSX_IMPL_MULH_P16 0, 16, 2, 18, 4, 20, 6, 22, 8, 24, 10, 26, 12, 28, 14, 30 + VSX_IMPL_MULH(vec_char16, VSX_IMPL_MULH_P16) + VSX_IMPL_MULH(vec_uchar16, VSX_IMPL_MULH_P16) + #define VSX_IMPL_MULH_P8 0, 1, 16, 17, 4, 5, 20, 21, 8, 9, 24, 25, 12, 13, 28, 29 + VSX_IMPL_MULH(vec_short8, VSX_IMPL_MULH_P8) + VSX_IMPL_MULH(vec_ushort8, VSX_IMPL_MULH_P8) + // vmuluwm can be used for unsigned or signed integers, that's what they said + VSX_IMPL_2VRG(vec_int4, vec_int4, vmuluwm, vec_mul) + VSX_IMPL_2VRG(vec_uint4, vec_uint4, vmuluwm, vec_mul) + // redirect to GCC builtin vec_mul, since it already supports precisions and llong + VSX_REDIRECT_2RG(vec_float4, vec_float4, vec_mul, __builtin_vec_mul) + VSX_REDIRECT_2RG(vec_double2, vec_double2, vec_mul, __builtin_vec_mul) + VSX_REDIRECT_2RG(vec_dword2, vec_dword2, vec_mul, __builtin_vec_mul) + VSX_REDIRECT_2RG(vec_udword2, vec_udword2, vec_mul, __builtin_vec_mul) +#endif // __GNUG__ < 7 + +#if __GNUG__ < 6 +/* + * Instruction "compare greater than or equal" in ISA 2.07 only supports single + * and double precision. + * In XLC and new versions of GCC implement integers by using instruction "greater than" and NOR. +**/ +# ifdef vec_cmpge +# undef vec_cmpge +# endif +# ifdef vec_cmple +# undef vec_cmple +# endif +# define vec_cmple(a, b) vec_cmpge(b, a) +# define VSX_IMPL_CMPGE(rt, rg, opc, fnm) \ + VSX_IMPL_2VRG_F(rt, rg, #opc" %0,%2,%1\n\t xxlnor %x0,%x0,%x0", fnm) + + VSX_IMPL_CMPGE(vec_bchar16, vec_char16, vcmpgtsb, vec_cmpge) + VSX_IMPL_CMPGE(vec_bchar16, vec_uchar16, vcmpgtub, vec_cmpge) + VSX_IMPL_CMPGE(vec_bshort8, vec_short8, vcmpgtsh, vec_cmpge) + VSX_IMPL_CMPGE(vec_bshort8, vec_ushort8, vcmpgtuh, vec_cmpge) + VSX_IMPL_CMPGE(vec_bint4, vec_int4, vcmpgtsw, vec_cmpge) + VSX_IMPL_CMPGE(vec_bint4, vec_uint4, vcmpgtuw, vec_cmpge) + VSX_IMPL_CMPGE(vec_bdword2, vec_dword2, vcmpgtsd, vec_cmpge) + VSX_IMPL_CMPGE(vec_bdword2, vec_udword2, vcmpgtud, vec_cmpge) + +// redirect to GCC builtin cmpge, since it already supports precisions + VSX_REDIRECT_2RG(vec_bint4, vec_float4, vec_cmpge, __builtin_vec_cmpge) + VSX_REDIRECT_2RG(vec_bdword2, vec_double2, vec_cmpge, __builtin_vec_cmpge) + +// up to gcc5 vec_nor doesn't support bool long long +# undef vec_nor + template + VSX_REDIRECT_2RG(T, T, vec_nor, __builtin_vec_nor) + + VSX_FINLINE(vec_bdword2) vec_nor(const vec_bdword2& a, const vec_bdword2& b) + { return vec_bdword2_c(__builtin_vec_nor(vec_dword2_c(a), vec_dword2_c(b))); } + +// vec_packs doesn't support double words in gcc4 and old versions of gcc5 +# undef vec_packs + VSX_REDIRECT_2RG(vec_char16, vec_short8, vec_packs, __builtin_vec_packs) + VSX_REDIRECT_2RG(vec_uchar16, vec_ushort8, vec_packs, __builtin_vec_packs) + VSX_REDIRECT_2RG(vec_short8, vec_int4, vec_packs, __builtin_vec_packs) + VSX_REDIRECT_2RG(vec_ushort8, vec_uint4, vec_packs, __builtin_vec_packs) + + VSX_IMPL_2VRG_F(vec_int4, vec_dword2, "vpksdss %0,%2,%1", vec_packs) + VSX_IMPL_2VRG_F(vec_uint4, vec_udword2, "vpkudus %0,%2,%1", vec_packs) +#endif // __GNUG__ < 6 + +#if __GNUG__ < 5 +// vec_xxpermdi in gcc4 missing little-endian supports just like clang +# define vec_permi(a, b, c) vec_xxpermdi(b, a, (3 ^ (((c) & 1) << 1 | (c) >> 1))) +#else +# define vec_permi vec_xxpermdi +#endif // __GNUG__ < 5 + +// shift left double by word immediate +#ifndef vec_sldw +# define vec_sldw __builtin_vsx_xxsldwi +#endif + +// vector population count +VSX_IMPL_1VRG(vec_uchar16, vec_uchar16, vpopcntb, vec_popcntu) +VSX_IMPL_1VRG(vec_uchar16, vec_char16, vpopcntb, vec_popcntu) +VSX_IMPL_1VRG(vec_ushort8, vec_ushort8, vpopcnth, vec_popcntu) +VSX_IMPL_1VRG(vec_ushort8, vec_short8, vpopcnth, vec_popcntu) +VSX_IMPL_1VRG(vec_uint4, vec_uint4, vpopcntw, vec_popcntu) +VSX_IMPL_1VRG(vec_uint4, vec_int4, vpopcntw, vec_popcntu) +VSX_IMPL_1VRG(vec_udword2, vec_udword2, vpopcntd, vec_popcntu) +VSX_IMPL_1VRG(vec_udword2, vec_dword2, vpopcntd, vec_popcntu) + +// converts between single and double-precision +VSX_REDIRECT_1RG(vec_float4, vec_double2, vec_cvfo, __builtin_vsx_xvcvdpsp) +VSX_REDIRECT_1RG(vec_double2, vec_float4, vec_cvfo, __builtin_vsx_xvcvspdp) + +// converts word and doubleword to double-precision +#ifdef vec_ctd +# undef vec_ctd +#endif +VSX_IMPL_1RG(vec_double2, wd, vec_int4, wa, xvcvsxwdp, vec_ctdo) +VSX_IMPL_1RG(vec_double2, wd, vec_uint4, wa, xvcvuxwdp, vec_ctdo) +VSX_IMPL_1RG(vec_double2, wd, vec_dword2, wi, xvcvsxddp, vec_ctd) +VSX_IMPL_1RG(vec_double2, wd, vec_udword2, wi, xvcvuxddp, vec_ctd) + +// converts word and doubleword to single-precision +#undef vec_ctf +VSX_IMPL_1RG(vec_float4, wf, vec_int4, wa, xvcvsxwsp, vec_ctf) +VSX_IMPL_1RG(vec_float4, wf, vec_uint4, wa, xvcvuxwsp, vec_ctf) +VSX_IMPL_1RG(vec_float4, wf, vec_dword2, wi, xvcvsxdsp, vec_ctfo) +VSX_IMPL_1RG(vec_float4, wf, vec_udword2, wi, xvcvuxdsp, vec_ctfo) + +// converts single and double precision to signed word +#undef vec_cts +VSX_IMPL_1RG(vec_int4, wa, vec_double2, wd, xvcvdpsxws, vec_ctso) +VSX_IMPL_1RG(vec_int4, wa, vec_float4, wf, xvcvspsxws, vec_cts) + +// converts single and double precision to unsigned word +#undef vec_ctu +VSX_IMPL_1RG(vec_uint4, wa, vec_double2, wd, xvcvdpuxws, vec_ctuo) +VSX_IMPL_1RG(vec_uint4, wa, vec_float4, wf, xvcvspuxws, vec_ctu) + +// converts single and double precision to signed doubleword +#ifdef vec_ctsl +# undef vec_ctsl +#endif +VSX_IMPL_1RG(vec_dword2, wi, vec_double2, wd, xvcvdpsxds, vec_ctsl) +VSX_IMPL_1RG(vec_dword2, wi, vec_float4, wf, xvcvspsxds, vec_ctslo) + +// converts single and double precision to unsigned doubleword +#ifdef vec_ctul +# undef vec_ctul +#endif +VSX_IMPL_1RG(vec_udword2, wi, vec_double2, wd, xvcvdpuxds, vec_ctul) +VSX_IMPL_1RG(vec_udword2, wi, vec_float4, wf, xvcvspuxds, vec_ctulo) + +// just in case if GCC doesn't define it +#ifndef vec_xl +# define vec_xl vec_vsx_ld +# define vec_xst vec_vsx_st +#endif + +#endif // GCC VSX compatibility + +/* + * CLANG VSX compatibility +**/ +#if defined(__clang__) && !defined(__IBMCPP__) + +/* + * CLANG doesn't support %x in the inline asm template which fixes register number + * when using any of the register constraints wa, wd, wf + * + * For more explanation checkout PowerPC and IBM RS6000 in https://gcc.gnu.org/onlinedocs/gcc/Machine-Constraints.html + * Also there's already an open bug https://bugs.llvm.org/show_bug.cgi?id=31837 + * + * So we're not able to use inline asm and only use built-in functions that CLANG supports + * and use __builtin_convertvector if clang missng any of vector conversions built-in functions + * + * todo: clang asm template bug is fixed, need to reconsider the current workarounds. +*/ + +// convert vector helper +#define VSX_IMPL_CONVERT(rt, rg, fnm) \ +VSX_FINLINE(rt) fnm(const rg& a) { return __builtin_convertvector(a, rt); } + +#if __clang_major__ < 5 +// implement vec_permi in a dirty way +# define VSX_IMPL_CLANG_4_PERMI(Tvec) \ + VSX_FINLINE(Tvec) vec_permi(const Tvec& a, const Tvec& b, unsigned const char c) \ + { \ + switch (c) \ + { \ + case 0: \ + return vec_mergeh(a, b); \ + case 1: \ + return vec_mergel(vec_mergeh(a, a), b); \ + case 2: \ + return vec_mergeh(vec_mergel(a, a), b); \ + default: \ + return vec_mergel(a, b); \ + } \ + } + VSX_IMPL_CLANG_4_PERMI(vec_udword2) + VSX_IMPL_CLANG_4_PERMI(vec_dword2) + VSX_IMPL_CLANG_4_PERMI(vec_double2) + +// vec_xxsldwi is missing in clang 4 +# define vec_xxsldwi(a, b, c) vec_sld(a, b, (c) * 4) +#else +// vec_xxpermdi is missing little-endian supports in clang 4 just like gcc4 +# define vec_permi(a, b, c) vec_xxpermdi(b, a, (3 ^ (((c) & 1) << 1 | (c) >> 1))) +#endif // __clang_major__ < 5 + +// shift left double by word immediate +#ifndef vec_sldw +# define vec_sldw vec_xxsldwi +#endif + +// Implement vec_rsqrt since clang only supports vec_rsqrte +#ifndef vec_rsqrt + VSX_FINLINE(vec_float4) vec_rsqrt(const vec_float4& a) + { return vec_div(vec_float4_sp(1), vec_sqrt(a)); } + + VSX_FINLINE(vec_double2) vec_rsqrt(const vec_double2& a) + { return vec_div(vec_double2_sp(1), vec_sqrt(a)); } +#endif + +// vec_promote missing support for doubleword +VSX_FINLINE(vec_dword2) vec_promote(long long a, int b) +{ + vec_dword2 ret = vec_dword2_z; + ret[b & 1] = a; + return ret; +} + +VSX_FINLINE(vec_udword2) vec_promote(unsigned long long a, int b) +{ + vec_udword2 ret = vec_udword2_z; + ret[b & 1] = a; + return ret; +} + +// vec_popcnt should return unsigned but clang has different thought just like gcc in vec_vpopcnt +#define VSX_IMPL_POPCNTU(Tvec, Tvec2, ucast) \ +VSX_FINLINE(Tvec) vec_popcntu(const Tvec2& a) \ +{ return ucast(vec_popcnt(a)); } +VSX_IMPL_POPCNTU(vec_uchar16, vec_char16, vec_uchar16_c); +VSX_IMPL_POPCNTU(vec_ushort8, vec_short8, vec_ushort8_c); +VSX_IMPL_POPCNTU(vec_uint4, vec_int4, vec_uint4_c); +// redirect unsigned types +VSX_REDIRECT_1RG(vec_uchar16, vec_uchar16, vec_popcntu, vec_popcnt) +VSX_REDIRECT_1RG(vec_ushort8, vec_ushort8, vec_popcntu, vec_popcnt) +VSX_REDIRECT_1RG(vec_uint4, vec_uint4, vec_popcntu, vec_popcnt) + +// converts between single and double precision +VSX_REDIRECT_1RG(vec_float4, vec_double2, vec_cvfo, __builtin_vsx_xvcvdpsp) +VSX_REDIRECT_1RG(vec_double2, vec_float4, vec_cvfo, __builtin_vsx_xvcvspdp) + +// converts word and doubleword to double-precision +#ifdef vec_ctd +# undef vec_ctd +#endif +VSX_REDIRECT_1RG(vec_double2, vec_int4, vec_ctdo, __builtin_vsx_xvcvsxwdp) +VSX_REDIRECT_1RG(vec_double2, vec_uint4, vec_ctdo, __builtin_vsx_xvcvuxwdp) + +VSX_IMPL_CONVERT(vec_double2, vec_dword2, vec_ctd) +VSX_IMPL_CONVERT(vec_double2, vec_udword2, vec_ctd) + +// converts word and doubleword to single-precision +#if __clang_major__ > 4 +# undef vec_ctf +#endif +VSX_IMPL_CONVERT(vec_float4, vec_int4, vec_ctf) +VSX_IMPL_CONVERT(vec_float4, vec_uint4, vec_ctf) +VSX_REDIRECT_1RG(vec_float4, vec_dword2, vec_ctfo, __builtin_vsx_xvcvsxdsp) +VSX_REDIRECT_1RG(vec_float4, vec_udword2, vec_ctfo, __builtin_vsx_xvcvuxdsp) + +// converts single and double precision to signed word +#if __clang_major__ > 4 +# undef vec_cts +#endif +VSX_REDIRECT_1RG(vec_int4, vec_double2, vec_ctso, __builtin_vsx_xvcvdpsxws) +VSX_IMPL_CONVERT(vec_int4, vec_float4, vec_cts) + +// converts single and double precision to unsigned word +#if __clang_major__ > 4 +# undef vec_ctu +#endif +VSX_REDIRECT_1RG(vec_uint4, vec_double2, vec_ctuo, __builtin_vsx_xvcvdpuxws) +VSX_IMPL_CONVERT(vec_uint4, vec_float4, vec_ctu) + +// converts single and double precision to signed doubleword +#ifdef vec_ctsl +# undef vec_ctsl +#endif +VSX_IMPL_CONVERT(vec_dword2, vec_double2, vec_ctsl) +// __builtin_convertvector unable to convert, xvcvspsxds is missing on it +VSX_FINLINE(vec_dword2) vec_ctslo(const vec_float4& a) +{ return vec_ctsl(vec_cvfo(a)); } + +// converts single and double precision to unsigned doubleword +#ifdef vec_ctul +# undef vec_ctul +#endif +VSX_IMPL_CONVERT(vec_udword2, vec_double2, vec_ctul) +// __builtin_convertvector unable to convert, xvcvspuxds is missing on it +VSX_FINLINE(vec_udword2) vec_ctulo(const vec_float4& a) +{ return vec_ctul(vec_cvfo(a)); } + +#endif // CLANG VSX compatibility + +/* + * Common GCC, CLANG compatibility +**/ +#if defined(__GNUG__) && !defined(__IBMCPP__) + +#ifdef vec_cvf +# undef vec_cvf +#endif + +#define VSX_IMPL_CONV_EVEN_4_2(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a) \ +{ return fn2(vec_sldw(a, a, 1)); } + +VSX_IMPL_CONV_EVEN_4_2(vec_double2, vec_float4, vec_cvf, vec_cvfo) +VSX_IMPL_CONV_EVEN_4_2(vec_double2, vec_int4, vec_ctd, vec_ctdo) +VSX_IMPL_CONV_EVEN_4_2(vec_double2, vec_uint4, vec_ctd, vec_ctdo) + +VSX_IMPL_CONV_EVEN_4_2(vec_dword2, vec_float4, vec_ctsl, vec_ctslo) +VSX_IMPL_CONV_EVEN_4_2(vec_udword2, vec_float4, vec_ctul, vec_ctulo) + +#define VSX_IMPL_CONV_EVEN_2_4(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a) \ +{ \ + rt v4 = fn2(a); \ + return vec_sldw(v4, v4, 3); \ +} + +VSX_IMPL_CONV_EVEN_2_4(vec_float4, vec_double2, vec_cvf, vec_cvfo) +VSX_IMPL_CONV_EVEN_2_4(vec_float4, vec_dword2, vec_ctf, vec_ctfo) +VSX_IMPL_CONV_EVEN_2_4(vec_float4, vec_udword2, vec_ctf, vec_ctfo) + +VSX_IMPL_CONV_EVEN_2_4(vec_int4, vec_double2, vec_cts, vec_ctso) +VSX_IMPL_CONV_EVEN_2_4(vec_uint4, vec_double2, vec_ctu, vec_ctuo) + +// Only for Eigen! +/* + * changing behavior of conversion intrinsics for gcc has effect on Eigen + * so we redfine old behavior again only on gcc, clang +*/ +#if !defined(__clang__) || __clang_major__ > 4 + // ignoring second arg since Eigen only truncates toward zero +# define VSX_IMPL_CONV_2VARIANT(rt, rg, fnm, fn2) \ + VSX_FINLINE(rt) fnm(const rg& a, int only_truncate) \ + { \ + assert(only_truncate == 0); \ + CV_UNUSED(only_truncate); \ + return fn2(a); \ + } + VSX_IMPL_CONV_2VARIANT(vec_int4, vec_float4, vec_cts, vec_cts) + VSX_IMPL_CONV_2VARIANT(vec_float4, vec_int4, vec_ctf, vec_ctf) + // define vec_cts for converting double precision to signed doubleword + // which isn't combitable with xlc but its okay since Eigen only use it for gcc + VSX_IMPL_CONV_2VARIANT(vec_dword2, vec_double2, vec_cts, vec_ctsl) +#endif // Eigen + +#endif // Common GCC, CLANG compatibility + +/* + * XLC VSX compatibility +**/ +#if defined(__IBMCPP__) + +// vector population count +#define vec_popcntu vec_popcnt + +// overload and redirect with setting second arg to zero +// since we only support conversions without the second arg +#define VSX_IMPL_OVERLOAD_Z2(rt, rg, fnm) \ +VSX_FINLINE(rt) fnm(const rg& a) { return fnm(a, 0); } + +VSX_IMPL_OVERLOAD_Z2(vec_double2, vec_int4, vec_ctd) +VSX_IMPL_OVERLOAD_Z2(vec_double2, vec_uint4, vec_ctd) +VSX_IMPL_OVERLOAD_Z2(vec_double2, vec_dword2, vec_ctd) +VSX_IMPL_OVERLOAD_Z2(vec_double2, vec_udword2, vec_ctd) + +VSX_IMPL_OVERLOAD_Z2(vec_float4, vec_int4, vec_ctf) +VSX_IMPL_OVERLOAD_Z2(vec_float4, vec_uint4, vec_ctf) +VSX_IMPL_OVERLOAD_Z2(vec_float4, vec_dword2, vec_ctf) +VSX_IMPL_OVERLOAD_Z2(vec_float4, vec_udword2, vec_ctf) + +VSX_IMPL_OVERLOAD_Z2(vec_int4, vec_double2, vec_cts) +VSX_IMPL_OVERLOAD_Z2(vec_int4, vec_float4, vec_cts) + +VSX_IMPL_OVERLOAD_Z2(vec_uint4, vec_double2, vec_ctu) +VSX_IMPL_OVERLOAD_Z2(vec_uint4, vec_float4, vec_ctu) + +VSX_IMPL_OVERLOAD_Z2(vec_dword2, vec_double2, vec_ctsl) +VSX_IMPL_OVERLOAD_Z2(vec_dword2, vec_float4, vec_ctsl) + +VSX_IMPL_OVERLOAD_Z2(vec_udword2, vec_double2, vec_ctul) +VSX_IMPL_OVERLOAD_Z2(vec_udword2, vec_float4, vec_ctul) + +// fixme: implement conversions of odd-numbered elements in a dirty way +// since xlc doesn't support VSX registers operand in inline asm. +#define VSX_IMPL_CONV_ODD_4_2(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a) { return fn2(vec_sldw(a, a, 3)); } + +VSX_IMPL_CONV_ODD_4_2(vec_double2, vec_float4, vec_cvfo, vec_cvf) +VSX_IMPL_CONV_ODD_4_2(vec_double2, vec_int4, vec_ctdo, vec_ctd) +VSX_IMPL_CONV_ODD_4_2(vec_double2, vec_uint4, vec_ctdo, vec_ctd) + +VSX_IMPL_CONV_ODD_4_2(vec_dword2, vec_float4, vec_ctslo, vec_ctsl) +VSX_IMPL_CONV_ODD_4_2(vec_udword2, vec_float4, vec_ctulo, vec_ctul) + +#define VSX_IMPL_CONV_ODD_2_4(rt, rg, fnm, fn2) \ +VSX_FINLINE(rt) fnm(const rg& a) \ +{ \ + rt v4 = fn2(a); \ + return vec_sldw(v4, v4, 1); \ +} + +VSX_IMPL_CONV_ODD_2_4(vec_float4, vec_double2, vec_cvfo, vec_cvf) +VSX_IMPL_CONV_ODD_2_4(vec_float4, vec_dword2, vec_ctfo, vec_ctf) +VSX_IMPL_CONV_ODD_2_4(vec_float4, vec_udword2, vec_ctfo, vec_ctf) + +VSX_IMPL_CONV_ODD_2_4(vec_int4, vec_double2, vec_ctso, vec_cts) +VSX_IMPL_CONV_ODD_2_4(vec_uint4, vec_double2, vec_ctuo, vec_ctu) + +#endif // XLC VSX compatibility + +// ignore GCC warning that caused by -Wunused-but-set-variable in rare cases +#if defined(__GNUG__) && !defined(__clang__) +# define VSX_UNUSED(Tvec) Tvec __attribute__((__unused__)) +#else // CLANG, XLC +# define VSX_UNUSED(Tvec) Tvec +#endif + +// gcc can find his way in casting log int and XLC, CLANG ambiguous +#if defined(__clang__) || defined(__IBMCPP__) + VSX_FINLINE(vec_udword2) vec_splats(uint64 v) + { return vec_splats((unsigned long long) v); } + + VSX_FINLINE(vec_dword2) vec_splats(int64 v) + { return vec_splats((long long) v); } + + VSX_FINLINE(vec_udword2) vec_promote(uint64 a, int b) + { return vec_promote((unsigned long long) a, b); } + + VSX_FINLINE(vec_dword2) vec_promote(int64 a, int b) + { return vec_promote((long long) a, b); } +#endif + +/* + * implement vsx_ld(offset, pointer), vsx_st(vector, offset, pointer) + * load and set using offset depend on the pointer type + * + * implement vsx_ldf(offset, pointer), vsx_stf(vector, offset, pointer) + * load and set using offset depend on fixed bytes size + * + * Note: In clang vec_xl and vec_xst fails to load unaligned addresses + * so we are using vec_vsx_ld, vec_vsx_st instead +*/ + +#if defined(__clang__) && !defined(__IBMCPP__) +# define vsx_ldf vec_vsx_ld +# define vsx_stf vec_vsx_st +#else // GCC , XLC +# define vsx_ldf vec_xl +# define vsx_stf vec_xst +#endif + +#define VSX_OFFSET(o, p) ((o) * sizeof(*(p))) +#define vsx_ld(o, p) vsx_ldf(VSX_OFFSET(o, p), p) +#define vsx_st(v, o, p) vsx_stf(v, VSX_OFFSET(o, p), p) + +/* + * implement vsx_ld2(offset, pointer), vsx_st2(vector, offset, pointer) to load and store double words + * In GCC vec_xl and vec_xst it maps to vec_vsx_ld, vec_vsx_st which doesn't support long long + * and in CLANG we are using vec_vsx_ld, vec_vsx_st because vec_xl, vec_xst fails to load unaligned addresses + * + * In XLC vec_xl and vec_xst fail to cast int64(long int) to long long +*/ +#if (defined(__GNUG__) || defined(__clang__)) && !defined(__IBMCPP__) + VSX_FINLINE(vec_udword2) vsx_ld2(long o, const uint64* p) + { return vec_udword2_c(vsx_ldf(VSX_OFFSET(o, p), (unsigned int*)p)); } + + VSX_FINLINE(vec_dword2) vsx_ld2(long o, const int64* p) + { return vec_dword2_c(vsx_ldf(VSX_OFFSET(o, p), (int*)p)); } + + VSX_FINLINE(void) vsx_st2(const vec_udword2& vec, long o, uint64* p) + { vsx_stf(vec_uint4_c(vec), VSX_OFFSET(o, p), (unsigned int*)p); } + + VSX_FINLINE(void) vsx_st2(const vec_dword2& vec, long o, int64* p) + { vsx_stf(vec_int4_c(vec), VSX_OFFSET(o, p), (int*)p); } +#else // XLC + VSX_FINLINE(vec_udword2) vsx_ld2(long o, const uint64* p) + { return vsx_ldf(VSX_OFFSET(o, p), (unsigned long long*)p); } + + VSX_FINLINE(vec_dword2) vsx_ld2(long o, const int64* p) + { return vsx_ldf(VSX_OFFSET(o, p), (long long*)p); } + + VSX_FINLINE(void) vsx_st2(const vec_udword2& vec, long o, uint64* p) + { vsx_stf(vec, VSX_OFFSET(o, p), (unsigned long long*)p); } + + VSX_FINLINE(void) vsx_st2(const vec_dword2& vec, long o, int64* p) + { vsx_stf(vec, VSX_OFFSET(o, p), (long long*)p); } +#endif + +// Store lower 8 byte +#define vec_st_l8(v, p) *((uint64*)(p)) = vec_extract(vec_udword2_c(v), 0) + +// Store higher 8 byte +#define vec_st_h8(v, p) *((uint64*)(p)) = vec_extract(vec_udword2_c(v), 1) + +// Load 64-bits of integer data to lower part +#define VSX_IMPL_LOAD_L8(Tvec, Tp) \ +VSX_FINLINE(Tvec) vec_ld_l8(const Tp *p) \ +{ return ((Tvec)vec_promote(*((uint64*)p), 0)); } + +VSX_IMPL_LOAD_L8(vec_uchar16, uchar) +VSX_IMPL_LOAD_L8(vec_char16, schar) +VSX_IMPL_LOAD_L8(vec_ushort8, ushort) +VSX_IMPL_LOAD_L8(vec_short8, short) +VSX_IMPL_LOAD_L8(vec_uint4, uint) +VSX_IMPL_LOAD_L8(vec_int4, int) +VSX_IMPL_LOAD_L8(vec_float4, float) +VSX_IMPL_LOAD_L8(vec_udword2, uint64) +VSX_IMPL_LOAD_L8(vec_dword2, int64) +VSX_IMPL_LOAD_L8(vec_double2, double) + +// logical not +#define vec_not(a) vec_nor(a, a) + +// power9 yaya +// not equal +#ifndef vec_cmpne +# define vec_cmpne(a, b) vec_not(vec_cmpeq(a, b)) +#endif + +// absolute difference +#ifndef vec_absd +# define vec_absd(a, b) vec_sub(vec_max(a, b), vec_min(a, b)) +#endif + +/* + * Implement vec_unpacklu and vec_unpackhu + * since vec_unpackl, vec_unpackh only support signed integers +**/ +#define VSX_IMPL_UNPACKU(rt, rg, zero) \ +VSX_FINLINE(rt) vec_unpacklu(const rg& a) \ +{ return (rt)(vec_mergel(a, zero)); } \ +VSX_FINLINE(rt) vec_unpackhu(const rg& a) \ +{ return (rt)(vec_mergeh(a, zero)); } + +VSX_IMPL_UNPACKU(vec_ushort8, vec_uchar16, vec_uchar16_z) +VSX_IMPL_UNPACKU(vec_uint4, vec_ushort8, vec_ushort8_z) +VSX_IMPL_UNPACKU(vec_udword2, vec_uint4, vec_uint4_z) + +/* + * Implement vec_mergesqe and vec_mergesqo + * Merges the sequence values of even and odd elements of two vectors +*/ +#define VSX_IMPL_PERM(rt, fnm, ...) \ +VSX_FINLINE(rt) fnm(const rt& a, const rt& b) \ +{ static const vec_uchar16 perm = {__VA_ARGS__}; return vec_perm(a, b, perm); } + +// 16 +#define perm16_mergesqe 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30 +#define perm16_mergesqo 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31 +VSX_IMPL_PERM(vec_uchar16, vec_mergesqe, perm16_mergesqe) +VSX_IMPL_PERM(vec_uchar16, vec_mergesqo, perm16_mergesqo) +VSX_IMPL_PERM(vec_char16, vec_mergesqe, perm16_mergesqe) +VSX_IMPL_PERM(vec_char16, vec_mergesqo, perm16_mergesqo) +// 8 +#define perm8_mergesqe 0, 1, 4, 5, 8, 9, 12, 13, 16, 17, 20, 21, 24, 25, 28, 29 +#define perm8_mergesqo 2, 3, 6, 7, 10, 11, 14, 15, 18, 19, 22, 23, 26, 27, 30, 31 +VSX_IMPL_PERM(vec_ushort8, vec_mergesqe, perm8_mergesqe) +VSX_IMPL_PERM(vec_ushort8, vec_mergesqo, perm8_mergesqo) +VSX_IMPL_PERM(vec_short8, vec_mergesqe, perm8_mergesqe) +VSX_IMPL_PERM(vec_short8, vec_mergesqo, perm8_mergesqo) +// 4 +#define perm4_mergesqe 0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27 +#define perm4_mergesqo 4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31 +VSX_IMPL_PERM(vec_uint4, vec_mergesqe, perm4_mergesqe) +VSX_IMPL_PERM(vec_uint4, vec_mergesqo, perm4_mergesqo) +VSX_IMPL_PERM(vec_int4, vec_mergesqe, perm4_mergesqe) +VSX_IMPL_PERM(vec_int4, vec_mergesqo, perm4_mergesqo) +VSX_IMPL_PERM(vec_float4, vec_mergesqe, perm4_mergesqe) +VSX_IMPL_PERM(vec_float4, vec_mergesqo, perm4_mergesqo) +// 2 +VSX_REDIRECT_2RG(vec_double2, vec_double2, vec_mergesqe, vec_mergeh) +VSX_REDIRECT_2RG(vec_double2, vec_double2, vec_mergesqo, vec_mergel) +VSX_REDIRECT_2RG(vec_dword2, vec_dword2, vec_mergesqe, vec_mergeh) +VSX_REDIRECT_2RG(vec_dword2, vec_dword2, vec_mergesqo, vec_mergel) +VSX_REDIRECT_2RG(vec_udword2, vec_udword2, vec_mergesqe, vec_mergeh) +VSX_REDIRECT_2RG(vec_udword2, vec_udword2, vec_mergesqo, vec_mergel) + +/* + * Implement vec_mergesqh and vec_mergesql + * Merges the sequence most and least significant halves of two vectors +*/ +#define VSX_IMPL_MERGESQHL(Tvec) \ +VSX_FINLINE(Tvec) vec_mergesqh(const Tvec& a, const Tvec& b) \ +{ return (Tvec)vec_mergeh(vec_udword2_c(a), vec_udword2_c(b)); } \ +VSX_FINLINE(Tvec) vec_mergesql(const Tvec& a, const Tvec& b) \ +{ return (Tvec)vec_mergel(vec_udword2_c(a), vec_udword2_c(b)); } +VSX_IMPL_MERGESQHL(vec_uchar16) +VSX_IMPL_MERGESQHL(vec_char16) +VSX_IMPL_MERGESQHL(vec_ushort8) +VSX_IMPL_MERGESQHL(vec_short8) +VSX_IMPL_MERGESQHL(vec_uint4) +VSX_IMPL_MERGESQHL(vec_int4) +VSX_IMPL_MERGESQHL(vec_float4) +VSX_REDIRECT_2RG(vec_udword2, vec_udword2, vec_mergesqh, vec_mergeh) +VSX_REDIRECT_2RG(vec_udword2, vec_udword2, vec_mergesql, vec_mergel) +VSX_REDIRECT_2RG(vec_dword2, vec_dword2, vec_mergesqh, vec_mergeh) +VSX_REDIRECT_2RG(vec_dword2, vec_dword2, vec_mergesql, vec_mergel) +VSX_REDIRECT_2RG(vec_double2, vec_double2, vec_mergesqh, vec_mergeh) +VSX_REDIRECT_2RG(vec_double2, vec_double2, vec_mergesql, vec_mergel) + + +// 2 and 4 channels interleave for all types except 2 lanes +#define VSX_IMPL_ST_INTERLEAVE(Tp, Tvec) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, Tp* ptr) \ +{ \ + vsx_stf(vec_mergeh(a, b), 0, ptr); \ + vsx_stf(vec_mergel(a, b), 16, ptr); \ +} \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, const Tvec& d, Tp* ptr) \ +{ \ + Tvec ac = vec_mergeh(a, c); \ + Tvec bd = vec_mergeh(b, d); \ + vsx_stf(vec_mergeh(ac, bd), 0, ptr); \ + vsx_stf(vec_mergel(ac, bd), 16, ptr); \ + ac = vec_mergel(a, c); \ + bd = vec_mergel(b, d); \ + vsx_stf(vec_mergeh(ac, bd), 32, ptr); \ + vsx_stf(vec_mergel(ac, bd), 48, ptr); \ +} +VSX_IMPL_ST_INTERLEAVE(uchar, vec_uchar16) +VSX_IMPL_ST_INTERLEAVE(schar, vec_char16) +VSX_IMPL_ST_INTERLEAVE(ushort, vec_ushort8) +VSX_IMPL_ST_INTERLEAVE(short, vec_short8) +VSX_IMPL_ST_INTERLEAVE(uint, vec_uint4) +VSX_IMPL_ST_INTERLEAVE(int, vec_int4) +VSX_IMPL_ST_INTERLEAVE(float, vec_float4) + +// 2 and 4 channels deinterleave for 16 lanes +#define VSX_IMPL_ST_DINTERLEAVE_8(Tp, Tvec) \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b) \ +{ \ + Tvec v0 = vsx_ld(0, ptr); \ + Tvec v1 = vsx_ld(16, ptr); \ + a = vec_mergesqe(v0, v1); \ + b = vec_mergesqo(v0, v1); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, \ + Tvec& c, Tvec& d) \ +{ \ + Tvec v0 = vsx_ld(0, ptr); \ + Tvec v1 = vsx_ld(16, ptr); \ + Tvec v2 = vsx_ld(32, ptr); \ + Tvec v3 = vsx_ld(48, ptr); \ + Tvec m0 = vec_mergesqe(v0, v1); \ + Tvec m1 = vec_mergesqe(v2, v3); \ + a = vec_mergesqe(m0, m1); \ + c = vec_mergesqo(m0, m1); \ + m0 = vec_mergesqo(v0, v1); \ + m1 = vec_mergesqo(v2, v3); \ + b = vec_mergesqe(m0, m1); \ + d = vec_mergesqo(m0, m1); \ +} +VSX_IMPL_ST_DINTERLEAVE_8(uchar, vec_uchar16) +VSX_IMPL_ST_DINTERLEAVE_8(schar, vec_char16) + +// 2 and 4 channels deinterleave for 8 lanes +#define VSX_IMPL_ST_DINTERLEAVE_16(Tp, Tvec) \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b) \ +{ \ + Tvec v0 = vsx_ld(0, ptr); \ + Tvec v1 = vsx_ld(8, ptr); \ + a = vec_mergesqe(v0, v1); \ + b = vec_mergesqo(v0, v1); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, \ + Tvec& c, Tvec& d) \ +{ \ + Tvec v0 = vsx_ld(0, ptr); \ + Tvec v1 = vsx_ld(8, ptr); \ + Tvec m0 = vec_mergeh(v0, v1); \ + Tvec m1 = vec_mergel(v0, v1); \ + Tvec ab0 = vec_mergeh(m0, m1); \ + Tvec cd0 = vec_mergel(m0, m1); \ + v0 = vsx_ld(16, ptr); \ + v1 = vsx_ld(24, ptr); \ + m0 = vec_mergeh(v0, v1); \ + m1 = vec_mergel(v0, v1); \ + Tvec ab1 = vec_mergeh(m0, m1); \ + Tvec cd1 = vec_mergel(m0, m1); \ + a = vec_mergesqh(ab0, ab1); \ + b = vec_mergesql(ab0, ab1); \ + c = vec_mergesqh(cd0, cd1); \ + d = vec_mergesql(cd0, cd1); \ +} +VSX_IMPL_ST_DINTERLEAVE_16(ushort, vec_ushort8) +VSX_IMPL_ST_DINTERLEAVE_16(short, vec_short8) + +// 2 and 4 channels deinterleave for 4 lanes +#define VSX_IMPL_ST_DINTERLEAVE_32(Tp, Tvec) \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b) \ +{ \ + a = vsx_ld(0, ptr); \ + b = vsx_ld(4, ptr); \ + Tvec m0 = vec_mergeh(a, b); \ + Tvec m1 = vec_mergel(a, b); \ + a = vec_mergeh(m0, m1); \ + b = vec_mergel(m0, m1); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, \ + Tvec& c, Tvec& d) \ +{ \ + Tvec v0 = vsx_ld(0, ptr); \ + Tvec v1 = vsx_ld(4, ptr); \ + Tvec v2 = vsx_ld(8, ptr); \ + Tvec v3 = vsx_ld(12, ptr); \ + Tvec m0 = vec_mergeh(v0, v2); \ + Tvec m1 = vec_mergeh(v1, v3); \ + a = vec_mergeh(m0, m1); \ + b = vec_mergel(m0, m1); \ + m0 = vec_mergel(v0, v2); \ + m1 = vec_mergel(v1, v3); \ + c = vec_mergeh(m0, m1); \ + d = vec_mergel(m0, m1); \ +} +VSX_IMPL_ST_DINTERLEAVE_32(uint, vec_uint4) +VSX_IMPL_ST_DINTERLEAVE_32(int, vec_int4) +VSX_IMPL_ST_DINTERLEAVE_32(float, vec_float4) + +// 2 and 4 channels interleave and deinterleave for 2 lanes +#define VSX_IMPL_ST_D_INTERLEAVE_64(Tp, Tvec, ld_func, st_func) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, Tp* ptr) \ +{ \ + st_func(vec_mergeh(a, b), 0, ptr); \ + st_func(vec_mergel(a, b), 2, ptr); \ +} \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, const Tvec& d, Tp* ptr) \ +{ \ + st_func(vec_mergeh(a, b), 0, ptr); \ + st_func(vec_mergeh(c, d), 2, ptr); \ + st_func(vec_mergel(a, b), 4, ptr); \ + st_func(vec_mergel(c, d), 6, ptr); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b) \ +{ \ + Tvec m0 = ld_func(0, ptr); \ + Tvec m1 = ld_func(2, ptr); \ + a = vec_mergeh(m0, m1); \ + b = vec_mergel(m0, m1); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, \ + Tvec& c, Tvec& d) \ +{ \ + Tvec v0 = ld_func(0, ptr); \ + Tvec v1 = ld_func(2, ptr); \ + Tvec v2 = ld_func(4, ptr); \ + Tvec v3 = ld_func(6, ptr); \ + a = vec_mergeh(v0, v2); \ + b = vec_mergel(v0, v2); \ + c = vec_mergeh(v1, v3); \ + d = vec_mergel(v1, v3); \ +} +VSX_IMPL_ST_D_INTERLEAVE_64(int64, vec_dword2, vsx_ld2, vsx_st2) +VSX_IMPL_ST_D_INTERLEAVE_64(uint64, vec_udword2, vsx_ld2, vsx_st2) +VSX_IMPL_ST_D_INTERLEAVE_64(double, vec_double2, vsx_ld, vsx_st) + +/* 3 channels */ +#define VSX_IMPL_ST_INTERLEAVE_3CH_16(Tp, Tvec) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, Tp* ptr) \ +{ \ + static const vec_uchar16 a12 = {0, 16, 0, 1, 17, 0, 2, 18, 0, 3, 19, 0, 4, 20, 0, 5}; \ + static const vec_uchar16 a123 = {0, 1, 16, 3, 4, 17, 6, 7, 18, 9, 10, 19, 12, 13, 20, 15}; \ + vsx_st(vec_perm(vec_perm(a, b, a12), c, a123), 0, ptr); \ + static const vec_uchar16 b12 = {21, 0, 6, 22, 0, 7, 23, 0, 8, 24, 0, 9, 25, 0, 10, 26}; \ + static const vec_uchar16 b123 = {0, 21, 2, 3, 22, 5, 6, 23, 8, 9, 24, 11, 12, 25, 14, 15}; \ + vsx_st(vec_perm(vec_perm(a, b, b12), c, b123), 16, ptr); \ + static const vec_uchar16 c12 = {0, 11, 27, 0, 12, 28, 0, 13, 29, 0, 14, 30, 0, 15, 31, 0}; \ + static const vec_uchar16 c123 = {26, 1, 2, 27, 4, 5, 28, 7, 8, 29, 10, 11, 30, 13, 14, 31}; \ + vsx_st(vec_perm(vec_perm(a, b, c12), c, c123), 32, ptr); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, Tvec& c) \ +{ \ + Tvec v1 = vsx_ld(0, ptr); \ + Tvec v2 = vsx_ld(16, ptr); \ + Tvec v3 = vsx_ld(32, ptr); \ + static const vec_uchar16 a12_perm = {0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 0, 0, 0, 0, 0}; \ + static const vec_uchar16 a123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 17, 20, 23, 26, 29}; \ + a = vec_perm(vec_perm(v1, v2, a12_perm), v3, a123_perm); \ + static const vec_uchar16 b12_perm = {1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31, 0, 0, 0, 0, 0}; \ + static const vec_uchar16 b123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 18, 21, 24, 27, 30}; \ + b = vec_perm(vec_perm(v1, v2, b12_perm), v3, b123_perm); \ + static const vec_uchar16 c12_perm = {2, 5, 8, 11, 14, 17, 20, 23, 26, 29, 0, 0, 0, 0, 0, 0}; \ + static const vec_uchar16 c123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 16, 19, 22, 25, 28, 31}; \ + c = vec_perm(vec_perm(v1, v2, c12_perm), v3, c123_perm); \ +} +VSX_IMPL_ST_INTERLEAVE_3CH_16(uchar, vec_uchar16) +VSX_IMPL_ST_INTERLEAVE_3CH_16(schar, vec_char16) + +#define VSX_IMPL_ST_INTERLEAVE_3CH_8(Tp, Tvec) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, Tp* ptr) \ +{ \ + static const vec_uchar16 a12 = {0, 1, 16, 17, 0, 0, 2, 3, 18, 19, 0, 0, 4, 5, 20, 21}; \ + static const vec_uchar16 a123 = {0, 1, 2, 3, 16, 17, 6, 7, 8, 9, 18, 19, 12, 13, 14, 15}; \ + vsx_st(vec_perm(vec_perm(a, b, a12), c, a123), 0, ptr); \ + static const vec_uchar16 b12 = {0, 0, 6, 7, 22, 23, 0, 0, 8, 9, 24, 25, 0, 0, 10, 11}; \ + static const vec_uchar16 b123 = {20, 21, 2, 3, 4, 5, 22, 23, 8, 9, 10, 11, 24, 25, 14, 15}; \ + vsx_st(vec_perm(vec_perm(a, b, b12), c, b123), 8, ptr); \ + static const vec_uchar16 c12 = {26, 27, 0, 0, 12, 13, 28, 29, 0, 0, 14, 15, 30, 31, 0, 0}; \ + static const vec_uchar16 c123 = {0, 1, 26, 27, 4, 5, 6, 7, 28, 29, 10, 11, 12, 13, 30, 31}; \ + vsx_st(vec_perm(vec_perm(a, b, c12), c, c123), 16, ptr); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, Tvec& c) \ +{ \ + Tvec v1 = vsx_ld(0, ptr); \ + Tvec v2 = vsx_ld(8, ptr); \ + Tvec v3 = vsx_ld(16, ptr); \ + static const vec_uchar16 a12_perm = {0, 1, 6, 7, 12, 13, 18, 19, 24, 25, 30, 31, 0, 0, 0, 0}; \ + static const vec_uchar16 a123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 20, 21, 26, 27}; \ + a = vec_perm(vec_perm(v1, v2, a12_perm), v3, a123_perm); \ + static const vec_uchar16 b12_perm = {2, 3, 8, 9, 14, 15, 20, 21, 26, 27, 0, 0, 0, 0, 0, 0}; \ + static const vec_uchar16 b123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 16, 17, 22, 23, 28, 29}; \ + b = vec_perm(vec_perm(v1, v2, b12_perm), v3, b123_perm); \ + static const vec_uchar16 c12_perm = {4, 5, 10, 11, 16, 17, 22, 23, 28, 29, 0, 0, 0, 0, 0, 0}; \ + static const vec_uchar16 c123_perm = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 18, 19, 24, 25, 30, 31}; \ + c = vec_perm(vec_perm(v1, v2, c12_perm), v3, c123_perm); \ +} +VSX_IMPL_ST_INTERLEAVE_3CH_8(ushort, vec_ushort8) +VSX_IMPL_ST_INTERLEAVE_3CH_8(short, vec_short8) + +#define VSX_IMPL_ST_INTERLEAVE_3CH_4(Tp, Tvec) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, Tp* ptr) \ +{ \ + Tvec hbc = vec_mergeh(b, c); \ + static const vec_uchar16 ahbc = {0, 1, 2, 3, 16, 17, 18, 19, 20, 21, 22, 23, 4, 5, 6, 7}; \ + vsx_st(vec_perm(a, hbc, ahbc), 0, ptr); \ + Tvec lab = vec_mergel(a, b); \ + vsx_st(vec_sld(lab, hbc, 8), 4, ptr); \ + static const vec_uchar16 clab = {8, 9, 10, 11, 24, 25, 26, 27, 28, 29, 30, 31, 12, 13, 14, 15};\ + vsx_st(vec_perm(c, lab, clab), 8, ptr); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, Tvec& b, Tvec& c) \ +{ \ + Tvec v1 = vsx_ld(0, ptr); \ + Tvec v2 = vsx_ld(4, ptr); \ + Tvec v3 = vsx_ld(8, ptr); \ + static const vec_uchar16 flp = {0, 1, 2, 3, 12, 13, 14, 15, 16, 17, 18, 19, 28, 29, 30, 31}; \ + a = vec_perm(v1, vec_sld(v3, v2, 8), flp); \ + static const vec_uchar16 flp2 = {28, 29, 30, 31, 0, 1, 2, 3, 12, 13, 14, 15, 16, 17, 18, 19}; \ + b = vec_perm(v2, vec_sld(v1, v3, 8), flp2); \ + c = vec_perm(vec_sld(v2, v1, 8), v3, flp); \ +} +VSX_IMPL_ST_INTERLEAVE_3CH_4(uint, vec_uint4) +VSX_IMPL_ST_INTERLEAVE_3CH_4(int, vec_int4) +VSX_IMPL_ST_INTERLEAVE_3CH_4(float, vec_float4) + +#define VSX_IMPL_ST_INTERLEAVE_3CH_2(Tp, Tvec, ld_func, st_func) \ +VSX_FINLINE(void) vec_st_interleave(const Tvec& a, const Tvec& b, \ + const Tvec& c, Tp* ptr) \ +{ \ + st_func(vec_mergeh(a, b), 0, ptr); \ + st_func(vec_permi(c, a, 1), 2, ptr); \ + st_func(vec_mergel(b, c), 4, ptr); \ +} \ +VSX_FINLINE(void) vec_ld_deinterleave(const Tp* ptr, Tvec& a, \ + Tvec& b, Tvec& c) \ +{ \ + Tvec v1 = ld_func(0, ptr); \ + Tvec v2 = ld_func(2, ptr); \ + Tvec v3 = ld_func(4, ptr); \ + a = vec_permi(v1, v2, 1); \ + b = vec_permi(v1, v3, 2); \ + c = vec_permi(v2, v3, 1); \ +} +VSX_IMPL_ST_INTERLEAVE_3CH_2(int64, vec_dword2, vsx_ld2, vsx_st2) +VSX_IMPL_ST_INTERLEAVE_3CH_2(uint64, vec_udword2, vsx_ld2, vsx_st2) +VSX_IMPL_ST_INTERLEAVE_3CH_2(double, vec_double2, vsx_ld, vsx_st) + +#endif // CV_VSX + +//! @} + +#endif // OPENCV_HAL_VSX_UTILS_HPP diff --git a/3rdparty/opencv/include/opencv2/core/wimage.hpp b/3rdparty/opencv/include/opencv2/core/wimage.hpp new file mode 100644 index 00000000..c7b6efa0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/core/wimage.hpp @@ -0,0 +1,603 @@ +/*M////////////////////////////////////////////////////////////////////////////// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to +// this license. If you do not agree to this license, do not download, +// install, copy or use the software. +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2008, Google, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without +// modification, are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation or contributors may not be used to endorse +// or promote products derived from this software without specific +// prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" +// and any express or implied warranties, including, but not limited to, the +// implied warranties of merchantability and fitness for a particular purpose +// are disclaimed. In no event shall the Intel Corporation or contributors be +// liable for any direct, indirect, incidental, special, exemplary, or +// consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +///////////////////////////////////////////////////////////////////////////////// +//M*/ + +#ifndef OPENCV_CORE_WIMAGE_HPP +#define OPENCV_CORE_WIMAGE_HPP + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus + +namespace cv { + +//! @addtogroup core +//! @{ + +template class WImage; +template class WImageBuffer; +template class WImageView; + +template class WImageC; +template class WImageBufferC; +template class WImageViewC; + +// Commonly used typedefs. +typedef WImage WImage_b; +typedef WImageView WImageView_b; +typedef WImageBuffer WImageBuffer_b; + +typedef WImageC WImage1_b; +typedef WImageViewC WImageView1_b; +typedef WImageBufferC WImageBuffer1_b; + +typedef WImageC WImage3_b; +typedef WImageViewC WImageView3_b; +typedef WImageBufferC WImageBuffer3_b; + +typedef WImage WImage_f; +typedef WImageView WImageView_f; +typedef WImageBuffer WImageBuffer_f; + +typedef WImageC WImage1_f; +typedef WImageViewC WImageView1_f; +typedef WImageBufferC WImageBuffer1_f; + +typedef WImageC WImage3_f; +typedef WImageViewC WImageView3_f; +typedef WImageBufferC WImageBuffer3_f; + +// There isn't a standard for signed and unsigned short so be more +// explicit in the typename for these cases. +typedef WImage WImage_16s; +typedef WImageView WImageView_16s; +typedef WImageBuffer WImageBuffer_16s; + +typedef WImageC WImage1_16s; +typedef WImageViewC WImageView1_16s; +typedef WImageBufferC WImageBuffer1_16s; + +typedef WImageC WImage3_16s; +typedef WImageViewC WImageView3_16s; +typedef WImageBufferC WImageBuffer3_16s; + +typedef WImage WImage_16u; +typedef WImageView WImageView_16u; +typedef WImageBuffer WImageBuffer_16u; + +typedef WImageC WImage1_16u; +typedef WImageViewC WImageView1_16u; +typedef WImageBufferC WImageBuffer1_16u; + +typedef WImageC WImage3_16u; +typedef WImageViewC WImageView3_16u; +typedef WImageBufferC WImageBuffer3_16u; + +/** @brief Image class which provides a thin layer around an IplImage. + +The goals of the class design are: + + -# All the data has explicit ownership to avoid memory leaks + -# No hidden allocations or copies for performance. + -# Easy access to OpenCV methods (which will access IPP if available) + -# Can easily treat external data as an image + -# Easy to create images which are subsets of other images + -# Fast pixel access which can take advantage of number of channels if known at compile time. + +The WImage class is the image class which provides the data accessors. The 'W' comes from the fact +that it is also a wrapper around the popular but inconvenient IplImage class. A WImage can be +constructed either using a WImageBuffer class which allocates and frees the data, or using a +WImageView class which constructs a subimage or a view into external data. The view class does no +memory management. Each class actually has two versions, one when the number of channels is known +at compile time and one when it isn't. Using the one with the number of channels specified can +provide some compile time optimizations by using the fact that the number of channels is a +constant. + +We use the convention (c,r) to refer to column c and row r with (0,0) being the upper left corner. +This is similar to standard Euclidean coordinates with the first coordinate varying in the +horizontal direction and the second coordinate varying in the vertical direction. Thus (c,r) is +usually in the domain [0, width) X [0, height) + +Example usage: +@code +WImageBuffer3_b im(5,7); // Make a 5X7 3 channel image of type uchar +WImageView3_b sub_im(im, 2,2, 3,3); // 3X3 submatrix +vector vec(10, 3.0f); +WImageView1_f user_im(&vec[0], 2, 5); // 2X5 image w/ supplied data + +im.SetZero(); // same as cvSetZero(im.Ipl()) +*im(2, 3) = 15; // Modify the element at column 2, row 3 +MySetRand(&sub_im); + +// Copy the second row into the first. This can be done with no memory +// allocation and will use SSE if IPP is available. +int w = im.Width(); +im.View(0,0, w,1).CopyFrom(im.View(0,1, w,1)); + +// Doesn't care about source of data since using WImage +void MySetRand(WImage_b* im) { // Works with any number of channels +for (int r = 0; r < im->Height(); ++r) { + float* row = im->Row(r); + for (int c = 0; c < im->Width(); ++c) { + for (int ch = 0; ch < im->Channels(); ++ch, ++row) { + *row = uchar(rand() & 255); + } + } +} +} +@endcode + +Functions that are not part of the basic image allocation, viewing, and access should come from +OpenCV, except some useful functions that are not part of OpenCV can be found in wimage_util.h +*/ +template +class WImage +{ +public: + typedef T BaseType; + + // WImage is an abstract class with no other virtual methods so make the + // destructor virtual. + virtual ~WImage() = 0; + + // Accessors + IplImage* Ipl() {return image_; } + const IplImage* Ipl() const {return image_; } + T* ImageData() { return reinterpret_cast(image_->imageData); } + const T* ImageData() const { + return reinterpret_cast(image_->imageData); + } + + int Width() const {return image_->width; } + int Height() const {return image_->height; } + + // WidthStep is the number of bytes to go to the pixel with the next y coord + int WidthStep() const {return image_->widthStep; } + + int Channels() const {return image_->nChannels; } + int ChannelSize() const {return sizeof(T); } // number of bytes per channel + + // Number of bytes per pixel + int PixelSize() const {return Channels() * ChannelSize(); } + + // Return depth type (e.g. IPL_DEPTH_8U, IPL_DEPTH_32F) which is the number + // of bits per channel and with the signed bit set. + // This is known at compile time using specializations. + int Depth() const; + + inline const T* Row(int r) const { + return reinterpret_cast(image_->imageData + r*image_->widthStep); + } + + inline T* Row(int r) { + return reinterpret_cast(image_->imageData + r*image_->widthStep); + } + + // Pixel accessors which returns a pointer to the start of the channel + inline T* operator() (int c, int r) { + return reinterpret_cast(image_->imageData + r*image_->widthStep) + + c*Channels(); + } + + inline const T* operator() (int c, int r) const { + return reinterpret_cast(image_->imageData + r*image_->widthStep) + + c*Channels(); + } + + // Copy the contents from another image which is just a convenience to cvCopy + void CopyFrom(const WImage& src) { cvCopy(src.Ipl(), image_); } + + // Set contents to zero which is just a convenient to cvSetZero + void SetZero() { cvSetZero(image_); } + + // Construct a view into a region of this image + WImageView View(int c, int r, int width, int height); + +protected: + // Disallow copy and assignment + WImage(const WImage&); + void operator=(const WImage&); + + explicit WImage(IplImage* img) : image_(img) { + assert(!img || img->depth == Depth()); + } + + void SetIpl(IplImage* image) { + assert(!image || image->depth == Depth()); + image_ = image; + } + + IplImage* image_; +}; + + +/** Image class when both the pixel type and number of channels +are known at compile time. This wrapper will speed up some of the operations +like accessing individual pixels using the () operator. +*/ +template +class WImageC : public WImage +{ +public: + typedef typename WImage::BaseType BaseType; + enum { kChannels = C }; + + explicit WImageC(IplImage* img) : WImage(img) { + assert(!img || img->nChannels == Channels()); + } + + // Construct a view into a region of this image + WImageViewC View(int c, int r, int width, int height); + + // Copy the contents from another image which is just a convenience to cvCopy + void CopyFrom(const WImageC& src) { + cvCopy(src.Ipl(), WImage::image_); + } + + // WImageC is an abstract class with no other virtual methods so make the + // destructor virtual. + virtual ~WImageC() = 0; + + int Channels() const {return C; } + +protected: + // Disallow copy and assignment + WImageC(const WImageC&); + void operator=(const WImageC&); + + void SetIpl(IplImage* image) { + assert(!image || image->depth == WImage::Depth()); + WImage::SetIpl(image); + } +}; + +/** Image class which owns the data, so it can be allocated and is always +freed. It cannot be copied but can be explicitly cloned. +*/ +template +class WImageBuffer : public WImage +{ +public: + typedef typename WImage::BaseType BaseType; + + // Default constructor which creates an object that can be + WImageBuffer() : WImage(0) {} + + WImageBuffer(int width, int height, int nchannels) : WImage(0) { + Allocate(width, height, nchannels); + } + + // Constructor which takes ownership of a given IplImage so releases + // the image on destruction. + explicit WImageBuffer(IplImage* img) : WImage(img) {} + + // Allocate an image. Does nothing if current size is the same as + // the new size. + void Allocate(int width, int height, int nchannels); + + // Set the data to point to an image, releasing the old data + void SetIpl(IplImage* img) { + ReleaseImage(); + WImage::SetIpl(img); + } + + // Clone an image which reallocates the image if of a different dimension. + void CloneFrom(const WImage& src) { + Allocate(src.Width(), src.Height(), src.Channels()); + CopyFrom(src); + } + + ~WImageBuffer() { + ReleaseImage(); + } + + // Release the image if it isn't null. + void ReleaseImage() { + if (WImage::image_) { + IplImage* image = WImage::image_; + cvReleaseImage(&image); + WImage::SetIpl(0); + } + } + + bool IsNull() const {return WImage::image_ == NULL; } + +private: + // Disallow copy and assignment + WImageBuffer(const WImageBuffer&); + void operator=(const WImageBuffer&); +}; + +/** Like a WImageBuffer class but when the number of channels is known at compile time. +*/ +template +class WImageBufferC : public WImageC +{ +public: + typedef typename WImage::BaseType BaseType; + enum { kChannels = C }; + + // Default constructor which creates an object that can be + WImageBufferC() : WImageC(0) {} + + WImageBufferC(int width, int height) : WImageC(0) { + Allocate(width, height); + } + + // Constructor which takes ownership of a given IplImage so releases + // the image on destruction. + explicit WImageBufferC(IplImage* img) : WImageC(img) {} + + // Allocate an image. Does nothing if current size is the same as + // the new size. + void Allocate(int width, int height); + + // Set the data to point to an image, releasing the old data + void SetIpl(IplImage* img) { + ReleaseImage(); + WImageC::SetIpl(img); + } + + // Clone an image which reallocates the image if of a different dimension. + void CloneFrom(const WImageC& src) { + Allocate(src.Width(), src.Height()); + CopyFrom(src); + } + + ~WImageBufferC() { + ReleaseImage(); + } + + // Release the image if it isn't null. + void ReleaseImage() { + if (WImage::image_) { + IplImage* image = WImage::image_; + cvReleaseImage(&image); + WImageC::SetIpl(0); + } + } + + bool IsNull() const {return WImage::image_ == NULL; } + +private: + // Disallow copy and assignment + WImageBufferC(const WImageBufferC&); + void operator=(const WImageBufferC&); +}; + +/** View into an image class which allows treating a subimage as an image or treating external data +as an image +*/ +template class WImageView : public WImage +{ +public: + typedef typename WImage::BaseType BaseType; + + // Construct a subimage. No checks are done that the subimage lies + // completely inside the original image. + WImageView(WImage* img, int c, int r, int width, int height); + + // Refer to external data. + // If not given width_step assumed to be same as width. + WImageView(T* data, int width, int height, int channels, int width_step = -1); + + // Refer to external data. This does NOT take ownership + // of the supplied IplImage. + WImageView(IplImage* img) : WImage(img) {} + + // Copy constructor + WImageView(const WImage& img) : WImage(0) { + header_ = *(img.Ipl()); + WImage::SetIpl(&header_); + } + + WImageView& operator=(const WImage& img) { + header_ = *(img.Ipl()); + WImage::SetIpl(&header_); + return *this; + } + +protected: + IplImage header_; +}; + + +template +class WImageViewC : public WImageC +{ +public: + typedef typename WImage::BaseType BaseType; + enum { kChannels = C }; + + // Default constructor needed for vectors of views. + WImageViewC(); + + virtual ~WImageViewC() {} + + // Construct a subimage. No checks are done that the subimage lies + // completely inside the original image. + WImageViewC(WImageC* img, + int c, int r, int width, int height); + + // Refer to external data + WImageViewC(T* data, int width, int height, int width_step = -1); + + // Refer to external data. This does NOT take ownership + // of the supplied IplImage. + WImageViewC(IplImage* img) : WImageC(img) {} + + // Copy constructor which does a shallow copy to allow multiple views + // of same data. gcc-4.1.1 gets confused if both versions of + // the constructor and assignment operator are not provided. + WImageViewC(const WImageC& img) : WImageC(0) { + header_ = *(img.Ipl()); + WImageC::SetIpl(&header_); + } + WImageViewC(const WImageViewC& img) : WImageC(0) { + header_ = *(img.Ipl()); + WImageC::SetIpl(&header_); + } + + WImageViewC& operator=(const WImageC& img) { + header_ = *(img.Ipl()); + WImageC::SetIpl(&header_); + return *this; + } + WImageViewC& operator=(const WImageViewC& img) { + header_ = *(img.Ipl()); + WImageC::SetIpl(&header_); + return *this; + } + +protected: + IplImage header_; +}; + + +// Specializations for depth +template<> +inline int WImage::Depth() const {return IPL_DEPTH_8U; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_8S; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_16S; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_16U; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_32S; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_32F; } +template<> +inline int WImage::Depth() const {return IPL_DEPTH_64F; } + +template inline WImage::~WImage() {} +template inline WImageC::~WImageC() {} + +template +inline void WImageBuffer::Allocate(int width, int height, int nchannels) +{ + if (IsNull() || WImage::Width() != width || + WImage::Height() != height || WImage::Channels() != nchannels) { + ReleaseImage(); + WImage::image_ = cvCreateImage(cvSize(width, height), + WImage::Depth(), nchannels); + } +} + +template +inline void WImageBufferC::Allocate(int width, int height) +{ + if (IsNull() || WImage::Width() != width || WImage::Height() != height) { + ReleaseImage(); + WImageC::SetIpl(cvCreateImage(cvSize(width, height),WImage::Depth(), C)); + } +} + +template +WImageView::WImageView(WImage* img, int c, int r, int width, int height) + : WImage(0) +{ + header_ = *(img->Ipl()); + header_.imageData = reinterpret_cast((*img)(c, r)); + header_.width = width; + header_.height = height; + WImage::SetIpl(&header_); +} + +template +WImageView::WImageView(T* data, int width, int height, int nchannels, int width_step) + : WImage(0) +{ + cvInitImageHeader(&header_, cvSize(width, height), WImage::Depth(), nchannels); + header_.imageData = reinterpret_cast(data); + if (width_step > 0) { + header_.widthStep = width_step; + } + WImage::SetIpl(&header_); +} + +template +WImageViewC::WImageViewC(WImageC* img, int c, int r, int width, int height) + : WImageC(0) +{ + header_ = *(img->Ipl()); + header_.imageData = reinterpret_cast((*img)(c, r)); + header_.width = width; + header_.height = height; + WImageC::SetIpl(&header_); +} + +template +WImageViewC::WImageViewC() : WImageC(0) { + cvInitImageHeader(&header_, cvSize(0, 0), WImage::Depth(), C); + header_.imageData = reinterpret_cast(0); + WImageC::SetIpl(&header_); +} + +template +WImageViewC::WImageViewC(T* data, int width, int height, int width_step) + : WImageC(0) +{ + cvInitImageHeader(&header_, cvSize(width, height), WImage::Depth(), C); + header_.imageData = reinterpret_cast(data); + if (width_step > 0) { + header_.widthStep = width_step; + } + WImageC::SetIpl(&header_); +} + +// Construct a view into a region of an image +template +WImageView WImage::View(int c, int r, int width, int height) { + return WImageView(this, c, r, width, height); +} + +template +WImageViewC WImageC::View(int c, int r, int width, int height) { + return WImageViewC(this, c, r, width, height); +} + +//! @} core + +} // end of namespace + +#endif // __cplusplus + +#endif diff --git a/3rdparty/opencv/include/opencv2/cvconfig.h b/3rdparty/opencv/include/opencv2/cvconfig.h new file mode 100644 index 00000000..1c91916f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/cvconfig.h @@ -0,0 +1,251 @@ +#ifndef OPENCV_CVCONFIG_H_INCLUDED +#define OPENCV_CVCONFIG_H_INCLUDED + +/* OpenCV compiled as static or dynamic libs */ +#define BUILD_SHARED_LIBS + +/* OpenCV intrinsics optimized code */ +#define CV_ENABLE_INTRINSICS + +/* OpenCV additional optimized code */ +/* #undef CV_DISABLE_OPTIMIZATION */ + +/* Compile for 'real' NVIDIA GPU architectures */ +#define CUDA_ARCH_BIN "" + +/* Create PTX or BIN for 1.0 compute capability */ +/* #undef CUDA_ARCH_BIN_OR_PTX_10 */ + +/* NVIDIA GPU features are used */ +#define CUDA_ARCH_FEATURES "" + +/* Compile for 'virtual' NVIDIA PTX architectures */ +#define CUDA_ARCH_PTX "" + +/* AVFoundation video libraries */ +/* #undef HAVE_AVFOUNDATION */ + +/* V4L capturing support */ +/* #undef HAVE_CAMV4L */ + +/* V4L2 capturing support */ +/* #undef HAVE_CAMV4L2 */ + +/* Carbon windowing environment */ +/* #undef HAVE_CARBON */ + +/* AMD's Basic Linear Algebra Subprograms Library*/ +/* #undef HAVE_CLAMDBLAS */ + +/* AMD's OpenCL Fast Fourier Transform Library*/ +/* #undef HAVE_CLAMDFFT */ + +/* Clp support */ +/* #undef HAVE_CLP */ + +/* Cocoa API */ +/* #undef HAVE_COCOA */ + +/* C= */ +/* #undef HAVE_CSTRIPES */ + +/* NVIDIA CUDA Basic Linear Algebra Subprograms (BLAS) API*/ +/* #undef HAVE_CUBLAS */ + +/* NVIDIA CUDA Runtime API*/ +/* #undef HAVE_CUDA */ + +/* NVIDIA CUDA Fast Fourier Transform (FFT) API*/ +/* #undef HAVE_CUFFT */ + +/* IEEE1394 capturing support */ +/* #undef HAVE_DC1394 */ + +/* IEEE1394 capturing support - libdc1394 v2.x */ +/* #undef HAVE_DC1394_2 */ + +/* DirectX */ +#define HAVE_DIRECTX +#define HAVE_DIRECTX_NV12 +#define HAVE_D3D11 +#define HAVE_D3D10 +#define HAVE_D3D9 + +/* DirectShow Video Capture library */ +#define HAVE_DSHOW + +/* Eigen Matrix & Linear Algebra Library */ +/* #undef HAVE_EIGEN */ + +/* FFMpeg video library */ +/* #undef HAVE_FFMPEG */ + +/* Geospatial Data Abstraction Library */ +/* #undef HAVE_GDAL */ + +/* GStreamer multimedia framework */ +/* #undef HAVE_GSTREAMER */ + +/* GTK+ 2.0 Thread support */ +/* #undef HAVE_GTHREAD */ + +/* GTK+ 2.x toolkit */ +/* #undef HAVE_GTK */ + +/* Halide support */ +/* #undef HAVE_HALIDE */ + +/* Define to 1 if you have the header file. */ +#define HAVE_INTTYPES_H 1 + +/* Intel Perceptual Computing SDK library */ +/* #undef HAVE_INTELPERC */ + +/* Intel Integrated Performance Primitives */ +/* #undef HAVE_IPP */ +/* #undef HAVE_IPP_ICV */ +/* #undef HAVE_IPP_IW */ +/* #undef HAVE_IPP_IW_LL */ + +/* JPEG-2000 codec */ +#define HAVE_JASPER + +/* IJG JPEG codec */ +#define HAVE_JPEG + +/* libpng/png.h needs to be included */ +/* #undef HAVE_LIBPNG_PNG_H */ + +/* GDCM DICOM codec */ +/* #undef HAVE_GDCM */ + +/* V4L/V4L2 capturing support via libv4l */ +/* #undef HAVE_LIBV4L */ + +/* Microsoft Media Foundation Capture library */ +#define HAVE_MSMF + +/* NVIDIA Video Decoding API*/ +/* #undef HAVE_NVCUVID */ + +/* NVIDIA Video Encoding API*/ +/* #undef HAVE_NVCUVENC */ + +/* OpenCL Support */ +#define HAVE_OPENCL +/* #undef HAVE_OPENCL_STATIC */ +/* #undef HAVE_OPENCL_SVM */ + +/* NVIDIA OpenCL D3D Extensions support */ +#define HAVE_OPENCL_D3D11_NV + +/* OpenEXR codec */ +#define HAVE_OPENEXR + +/* OpenGL support*/ +/* #undef HAVE_OPENGL */ + +/* OpenNI library */ +/* #undef HAVE_OPENNI */ + +/* OpenNI library */ +/* #undef HAVE_OPENNI2 */ + +/* PNG codec */ +#define HAVE_PNG + +/* Posix threads (pthreads) */ +/* #undef HAVE_PTHREAD */ + +/* parallel_for with pthreads */ +/* #undef HAVE_PTHREADS_PF */ + +/* Qt support */ +/* #undef HAVE_QT */ + +/* Qt OpenGL support */ +/* #undef HAVE_QT_OPENGL */ + +/* QuickTime video libraries */ +/* #undef HAVE_QUICKTIME */ + +/* QTKit video libraries */ +/* #undef HAVE_QTKIT */ + +/* Intel Threading Building Blocks */ +/* #undef HAVE_TBB */ + +/* TIFF codec */ +#define HAVE_TIFF + +/* Unicap video capture library */ +/* #undef HAVE_UNICAP */ + +/* Video for Windows support */ +/* #undef HAVE_VFW */ + +/* V4L2 capturing support in videoio.h */ +/* #undef HAVE_VIDEOIO */ + +/* Win32 UI */ +#define HAVE_WIN32UI + +/* XIMEA camera support */ +/* #undef HAVE_XIMEA */ + +/* Xine video library */ +/* #undef HAVE_XINE */ + +/* Define if your processor stores words with the most significant byte + first (like Motorola and SPARC, unlike Intel and VAX). */ +/* #undef WORDS_BIGENDIAN */ + +/* gPhoto2 library */ +/* #undef HAVE_GPHOTO2 */ + +/* VA library (libva) */ +/* #undef HAVE_VA */ + +/* Intel VA-API/OpenCL */ +/* #undef HAVE_VA_INTEL */ + +/* Intel Media SDK */ +/* #undef HAVE_MFX */ + +/* Lapack */ +/* #undef HAVE_LAPACK */ + +/* Library was compiled with functions instrumentation */ +/* #undef ENABLE_INSTRUMENTATION */ + +/* OpenVX */ +/* #undef HAVE_OPENVX */ + +#if defined(HAVE_XINE) || \ + defined(HAVE_GSTREAMER) || \ + defined(HAVE_QUICKTIME) || \ + defined(HAVE_QTKIT) || \ + defined(HAVE_AVFOUNDATION) || \ + /*defined(HAVE_OPENNI) || too specialized */ \ + defined(HAVE_FFMPEG) || \ + defined(HAVE_MSMF) +#define HAVE_VIDEO_INPUT +#endif + +#if /*defined(HAVE_XINE) || */\ + defined(HAVE_GSTREAMER) || \ + defined(HAVE_QUICKTIME) || \ + defined(HAVE_QTKIT) || \ + defined(HAVE_AVFOUNDATION) || \ + defined(HAVE_FFMPEG) || \ + defined(HAVE_MSMF) +#define HAVE_VIDEO_OUTPUT +#endif + +/* OpenCV trace utilities */ +#define OPENCV_TRACE + +/* Library QR-code decoding */ +#define HAVE_QUIRC + +#endif // OPENCV_CVCONFIG_H_INCLUDED diff --git a/3rdparty/opencv/include/opencv2/dnn.hpp b/3rdparty/opencv/include/opencv2/dnn.hpp new file mode 100644 index 00000000..97f2fe3f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn.hpp @@ -0,0 +1,78 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_HPP +#define OPENCV_DNN_HPP + +// This is an umbrella header to include into you project. +// We are free to change headers layout in dnn subfolder, so please include +// this header for future compatibility + + +/** @defgroup dnn Deep Neural Network module + @{ + This module contains: + - API for new layers creation, layers are building bricks of neural networks; + - set of built-in most-useful Layers; + - API to construct and modify comprehensive neural networks from layers; + - functionality for loading serialized networks models from different frameworks. + + Functionality of this module is designed only for forward pass computations (i.e. network testing). + A network training is in principle not supported. + @} +*/ +/** @example samples/dnn/classification.cpp +Check @ref tutorial_dnn_googlenet "the corresponding tutorial" for more details +*/ +/** @example samples/dnn/colorization.cpp +*/ +/** @example samples/dnn/object_detection.cpp +Check @ref tutorial_dnn_yolo "the corresponding tutorial" for more details +*/ +/** @example samples/dnn/openpose.cpp +*/ +/** @example samples/dnn/segmentation.cpp +*/ +/** @example samples/dnn/text_detection.cpp +*/ +#include + +#endif /* OPENCV_DNN_HPP */ diff --git a/3rdparty/opencv/include/opencv2/dnn/all_layers.hpp b/3rdparty/opencv/include/opencv2/dnn/all_layers.hpp new file mode 100644 index 00000000..c6fe6d05 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/all_layers.hpp @@ -0,0 +1,634 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_DNN_ALL_LAYERS_HPP +#define OPENCV_DNN_DNN_ALL_LAYERS_HPP +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN +//! @addtogroup dnn +//! @{ + +/** @defgroup dnnLayerList Partial List of Implemented Layers + @{ + This subsection of dnn module contains information about built-in layers and their descriptions. + + Classes listed here, in fact, provides C++ API for creating instances of built-in layers. + In addition to this way of layers instantiation, there is a more common factory API (see @ref dnnLayerFactory), it allows to create layers dynamically (by name) and register new ones. + You can use both API, but factory API is less convenient for native C++ programming and basically designed for use inside importers (see @ref readNetFromCaffe(), @ref readNetFromTorch(), @ref readNetFromTensorflow()). + + Built-in layers partially reproduce functionality of corresponding Caffe and Torch7 layers. + In particular, the following layers and Caffe importer were tested to reproduce Caffe functionality: + - Convolution + - Deconvolution + - Pooling + - InnerProduct + - TanH, ReLU, Sigmoid, BNLL, Power, AbsVal + - Softmax + - Reshape, Flatten, Slice, Split + - LRN + - MVN + - Dropout (since it does nothing on forward pass -)) +*/ + + class CV_EXPORTS BlankLayer : public Layer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + /** + * Constant layer produces the same data blob at an every forward pass. + */ + class CV_EXPORTS ConstLayer : public Layer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + //! LSTM recurrent layer + class CV_EXPORTS LSTMLayer : public Layer + { + public: + /** Creates instance of LSTM layer */ + static Ptr create(const LayerParams& params); + + /** @deprecated Use LayerParams::blobs instead. + @brief Set trained weights for LSTM layer. + + LSTM behavior on each step is defined by current input, previous output, previous cell state and learned weights. + + Let @f$x_t@f$ be current input, @f$h_t@f$ be current output, @f$c_t@f$ be current state. + Than current output and current cell state is computed as follows: + @f{eqnarray*}{ + h_t &= o_t \odot tanh(c_t), \\ + c_t &= f_t \odot c_{t-1} + i_t \odot g_t, \\ + @f} + where @f$\odot@f$ is per-element multiply operation and @f$i_t, f_t, o_t, g_t@f$ is internal gates that are computed using learned wights. + + Gates are computed as follows: + @f{eqnarray*}{ + i_t &= sigmoid&(W_{xi} x_t + W_{hi} h_{t-1} + b_i), \\ + f_t &= sigmoid&(W_{xf} x_t + W_{hf} h_{t-1} + b_f), \\ + o_t &= sigmoid&(W_{xo} x_t + W_{ho} h_{t-1} + b_o), \\ + g_t &= tanh &(W_{xg} x_t + W_{hg} h_{t-1} + b_g), \\ + @f} + where @f$W_{x?}@f$, @f$W_{h?}@f$ and @f$b_{?}@f$ are learned weights represented as matrices: + @f$W_{x?} \in R^{N_h \times N_x}@f$, @f$W_{h?} \in R^{N_h \times N_h}@f$, @f$b_? \in R^{N_h}@f$. + + For simplicity and performance purposes we use @f$ W_x = [W_{xi}; W_{xf}; W_{xo}, W_{xg}] @f$ + (i.e. @f$W_x@f$ is vertical concatenation of @f$ W_{x?} @f$), @f$ W_x \in R^{4N_h \times N_x} @f$. + The same for @f$ W_h = [W_{hi}; W_{hf}; W_{ho}, W_{hg}], W_h \in R^{4N_h \times N_h} @f$ + and for @f$ b = [b_i; b_f, b_o, b_g]@f$, @f$b \in R^{4N_h} @f$. + + @param Wh is matrix defining how previous output is transformed to internal gates (i.e. according to above mentioned notation is @f$ W_h @f$) + @param Wx is matrix defining how current input is transformed to internal gates (i.e. according to above mentioned notation is @f$ W_x @f$) + @param b is bias vector (i.e. according to above mentioned notation is @f$ b @f$) + */ + CV_DEPRECATED virtual void setWeights(const Mat &Wh, const Mat &Wx, const Mat &b) = 0; + + /** @brief Specifies shape of output blob which will be [[`T`], `N`] + @p outTailShape. + * @details If this parameter is empty or unset then @p outTailShape = [`Wh`.size(0)] will be used, + * where `Wh` is parameter from setWeights(). + */ + virtual void setOutShape(const MatShape &outTailShape = MatShape()) = 0; + + /** @deprecated Use flag `produce_cell_output` in LayerParams. + * @brief Specifies either interpret first dimension of input blob as timestamp dimenion either as sample. + * + * If flag is set to true then shape of input blob will be interpreted as [`T`, `N`, `[data dims]`] where `T` specifies number of timestamps, `N` is number of independent streams. + * In this case each forward() call will iterate through `T` timestamps and update layer's state `T` times. + * + * If flag is set to false then shape of input blob will be interpreted as [`N`, `[data dims]`]. + * In this case each forward() call will make one iteration and produce one timestamp with shape [`N`, `[out dims]`]. + */ + CV_DEPRECATED virtual void setUseTimstampsDim(bool use = true) = 0; + + /** @deprecated Use flag `use_timestamp_dim` in LayerParams. + * @brief If this flag is set to true then layer will produce @f$ c_t @f$ as second output. + * @details Shape of the second output is the same as first output. + */ + CV_DEPRECATED virtual void setProduceCellOutput(bool produce = false) = 0; + + /* In common case it use single input with @f$x_t@f$ values to compute output(s) @f$h_t@f$ (and @f$c_t@f$). + * @param input should contain packed values @f$x_t@f$ + * @param output contains computed outputs: @f$h_t@f$ (and @f$c_t@f$ if setProduceCellOutput() flag was set to true). + * + * If setUseTimstampsDim() is set to true then @p input[0] should has at least two dimensions with the following shape: [`T`, `N`, `[data dims]`], + * where `T` specifies number of timestamps, `N` is number of independent streams (i.e. @f$ x_{t_0 + t}^{stream} @f$ is stored inside @p input[0][t, stream, ...]). + * + * If setUseTimstampsDim() is set to false then @p input[0] should contain single timestamp, its shape should has form [`N`, `[data dims]`] with at least one dimension. + * (i.e. @f$ x_{t}^{stream} @f$ is stored inside @p input[0][stream, ...]). + */ + + int inputNameToIndex(String inputName) CV_OVERRIDE; + int outputNameToIndex(const String& outputName) CV_OVERRIDE; + }; + + /** @brief Classical recurrent layer + + Accepts two inputs @f$x_t@f$ and @f$h_{t-1}@f$ and compute two outputs @f$o_t@f$ and @f$h_t@f$. + + - input: should contain packed input @f$x_t@f$. + - output: should contain output @f$o_t@f$ (and @f$h_t@f$ if setProduceHiddenOutput() is set to true). + + input[0] should have shape [`T`, `N`, `data_dims`] where `T` and `N` is number of timestamps and number of independent samples of @f$x_t@f$ respectively. + + output[0] will have shape [`T`, `N`, @f$N_o@f$], where @f$N_o@f$ is number of rows in @f$ W_{xo} @f$ matrix. + + If setProduceHiddenOutput() is set to true then @p output[1] will contain a Mat with shape [`T`, `N`, @f$N_h@f$], where @f$N_h@f$ is number of rows in @f$ W_{hh} @f$ matrix. + */ + class CV_EXPORTS RNNLayer : public Layer + { + public: + /** Creates instance of RNNLayer */ + static Ptr create(const LayerParams& params); + + /** Setups learned weights. + + Recurrent-layer behavior on each step is defined by current input @f$ x_t @f$, previous state @f$ h_t @f$ and learned weights as follows: + @f{eqnarray*}{ + h_t &= tanh&(W_{hh} h_{t-1} + W_{xh} x_t + b_h), \\ + o_t &= tanh&(W_{ho} h_t + b_o), + @f} + + @param Wxh is @f$ W_{xh} @f$ matrix + @param bh is @f$ b_{h} @f$ vector + @param Whh is @f$ W_{hh} @f$ matrix + @param Who is @f$ W_{xo} @f$ matrix + @param bo is @f$ b_{o} @f$ vector + */ + virtual void setWeights(const Mat &Wxh, const Mat &bh, const Mat &Whh, const Mat &Who, const Mat &bo) = 0; + + /** @brief If this flag is set to true then layer will produce @f$ h_t @f$ as second output. + * @details Shape of the second output is the same as first output. + */ + virtual void setProduceHiddenOutput(bool produce = false) = 0; + + }; + + class CV_EXPORTS BaseConvolutionLayer : public Layer + { + public: + Size kernel, stride, pad, dilation, adjustPad; + String padMode; + int numOutput; + }; + + class CV_EXPORTS ConvolutionLayer : public BaseConvolutionLayer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS DeconvolutionLayer : public BaseConvolutionLayer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS LRNLayer : public Layer + { + public: + int type; + + int size; + float alpha, beta, bias; + bool normBySize; + + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS PoolingLayer : public Layer + { + public: + int type; + Size kernel, stride; + int pad_l, pad_t, pad_r, pad_b; + CV_DEPRECATED_EXTERNAL Size pad; + bool globalPooling; + bool computeMaxIdx; + String padMode; + bool ceilMode; + // If true for average pooling with padding, divide an every output region + // by a whole kernel area. Otherwise exclude zero padded values and divide + // by number of real values. + bool avePoolPaddedArea; + // ROIPooling parameters. + Size pooledSize; + float spatialScale; + // PSROIPooling parameters. + int psRoiOutChannels; + + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS SoftmaxLayer : public Layer + { + public: + bool logSoftMax; + + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS InnerProductLayer : public Layer + { + public: + int axis; + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS MVNLayer : public Layer + { + public: + float eps; + bool normVariance, acrossChannels; + + static Ptr create(const LayerParams& params); + }; + + /* Reshaping */ + + class CV_EXPORTS ReshapeLayer : public Layer + { + public: + MatShape newShapeDesc; + Range newShapeRange; + + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS FlattenLayer : public Layer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS ConcatLayer : public Layer + { + public: + int axis; + /** + * @brief Add zero padding in case of concatenation of blobs with different + * spatial sizes. + * + * Details: https://github.com/torch/nn/blob/master/doc/containers.md#depthconcat + */ + bool padding; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS SplitLayer : public Layer + { + public: + int outputsCount; //!< Number of copies that will be produced (is ignored when negative). + + static Ptr create(const LayerParams ¶ms); + }; + + /** + * Slice layer has several modes: + * 1. Caffe mode + * @param[in] axis Axis of split operation + * @param[in] slice_point Array of split points + * + * Number of output blobs equals to number of split points plus one. The + * first blob is a slice on input from 0 to @p slice_point[0] - 1 by @p axis, + * the second output blob is a slice of input from @p slice_point[0] to + * @p slice_point[1] - 1 by @p axis and the last output blob is a slice of + * input from @p slice_point[-1] up to the end of @p axis size. + * + * 2. TensorFlow mode + * @param begin Vector of start indices + * @param size Vector of sizes + * + * More convenient numpy-like slice. One and only output blob + * is a slice `input[begin[0]:begin[0]+size[0], begin[1]:begin[1]+size[1], ...]` + * + * 3. Torch mode + * @param axis Axis of split operation + * + * Split input blob on the equal parts by @p axis. + */ + class CV_EXPORTS SliceLayer : public Layer + { + public: + /** + * @brief Vector of slice ranges. + * + * The first dimension equals number of output blobs. + * Inner vector has slice ranges for the first number of input dimensions. + */ + std::vector > sliceRanges; + int axis; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS PermuteLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + /** + * Permute channels of 4-dimensional input blob. + * @param group Number of groups to split input channels and pick in turns + * into output blob. + * + * \f[ groupSize = \frac{number\ of\ channels}{group} \f] + * \f[ output(n, c, h, w) = input(n, groupSize \times (c \% group) + \lfloor \frac{c}{group} \rfloor, h, w) \f] + * Read more at https://arxiv.org/pdf/1707.01083.pdf + */ + class CV_EXPORTS ShuffleChannelLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + + int group; + }; + + /** + * @brief Adds extra values for specific axes. + * @param paddings Vector of paddings in format + * @code + * [ pad_before, pad_after, // [0]th dimension + * pad_before, pad_after, // [1]st dimension + * ... + * pad_before, pad_after ] // [n]th dimension + * @endcode + * that represents number of padded values at every dimension + * starting from the first one. The rest of dimensions won't + * be padded. + * @param value Value to be padded. Defaults to zero. + * @param type Padding type: 'constant', 'reflect' + * @param input_dims Torch's parameter. If @p input_dims is not equal to the + * actual input dimensionality then the `[0]th` dimension + * is considered as a batch dimension and @p paddings are shifted + * to a one dimension. Defaults to `-1` that means padding + * corresponding to @p paddings. + */ + class CV_EXPORTS PaddingLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + /* Activations */ + class CV_EXPORTS ActivationLayer : public Layer + { + public: + virtual void forwardSlice(const float* src, float* dst, int len, + size_t outPlaneSize, int cn0, int cn1) const = 0; + }; + + class CV_EXPORTS ReLULayer : public ActivationLayer + { + public: + float negativeSlope; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS ReLU6Layer : public ActivationLayer + { + public: + float minValue, maxValue; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS ChannelsPReLULayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS ELULayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS TanHLayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS SigmoidLayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS BNLLLayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS AbsLayer : public ActivationLayer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS PowerLayer : public ActivationLayer + { + public: + float power, scale, shift; + + static Ptr create(const LayerParams ¶ms); + }; + + /* Layers used in semantic segmentation */ + + class CV_EXPORTS CropLayer : public Layer + { + public: + int startAxis; + std::vector offset; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS EltwiseLayer : public Layer + { + public: + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS BatchNormLayer : public ActivationLayer + { + public: + bool hasWeights, hasBias; + float epsilon; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS MaxUnpoolLayer : public Layer + { + public: + Size poolKernel; + Size poolPad; + Size poolStride; + + static Ptr create(const LayerParams ¶ms); + }; + + class CV_EXPORTS ScaleLayer : public Layer + { + public: + bool hasBias; + int axis; + + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS ShiftLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS PriorBoxLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS ReorgLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS RegionLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS DetectionOutputLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + /** + * @brief \f$ L_p \f$ - normalization layer. + * @param p Normalization factor. The most common `p = 1` for \f$ L_1 \f$ - + * normalization or `p = 2` for \f$ L_2 \f$ - normalization or a custom one. + * @param eps Parameter \f$ \epsilon \f$ to prevent a division by zero. + * @param across_spatial If true, normalize an input across all non-batch dimensions. + * Otherwise normalize an every channel separately. + * + * Across spatial: + * @f[ + * norm = \sqrt[p]{\epsilon + \sum_{x, y, c} |src(x, y, c)|^p } \\ + * dst(x, y, c) = \frac{ src(x, y, c) }{norm} + * @f] + * + * Channel wise normalization: + * @f[ + * norm(c) = \sqrt[p]{\epsilon + \sum_{x, y} |src(x, y, c)|^p } \\ + * dst(x, y, c) = \frac{ src(x, y, c) }{norm(c)} + * @f] + * + * Where `x, y` - spatial coordinates, `c` - channel. + * + * An every sample in the batch is normalized separately. Optionally, + * output is scaled by the trained parameters. + */ + class CV_EXPORTS NormalizeBBoxLayer : public Layer + { + public: + float pnorm, epsilon; + CV_DEPRECATED_EXTERNAL bool acrossSpatial; + + static Ptr create(const LayerParams& params); + }; + + /** + * @brief Resize input 4-dimensional blob by nearest neighbor or bilinear strategy. + * + * Layer is used to support TensorFlow's resize_nearest_neighbor and resize_bilinear ops. + */ + class CV_EXPORTS ResizeLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + /** + * @brief Bilinear resize layer from https://github.com/cdmh/deeplab-public + * + * It differs from @ref ResizeLayer in output shape and resize scales computations. + */ + class CV_EXPORTS InterpLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS ProposalLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + + class CV_EXPORTS CropAndResizeLayer : public Layer + { + public: + static Ptr create(const LayerParams& params); + }; + +//! @} +//! @} +CV__DNN_EXPERIMENTAL_NS_END +} +} +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/dict.hpp b/3rdparty/opencv/include/opencv2/dnn/dict.hpp new file mode 100644 index 00000000..60c2aa5d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/dict.hpp @@ -0,0 +1,160 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#include +#include +#include + +#include + +#ifndef OPENCV_DNN_DNN_DICT_HPP +#define OPENCV_DNN_DNN_DICT_HPP + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN +//! @addtogroup dnn +//! @{ + +/** @brief This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64. + * @todo Maybe int64 is useless because double type exactly stores at least 2^52 integers. + */ +struct CV_EXPORTS_W DictValue +{ + DictValue(const DictValue &r); + DictValue(bool i) : type(Param::INT), pi(new AutoBuffer) { (*pi)[0] = i ? 1 : 0; } //!< Constructs integer scalar + DictValue(int64 i = 0) : type(Param::INT), pi(new AutoBuffer) { (*pi)[0] = i; } //!< Constructs integer scalar + CV_WRAP DictValue(int i) : type(Param::INT), pi(new AutoBuffer) { (*pi)[0] = i; } //!< Constructs integer scalar + DictValue(unsigned p) : type(Param::INT), pi(new AutoBuffer) { (*pi)[0] = p; } //!< Constructs integer scalar + CV_WRAP DictValue(double p) : type(Param::REAL), pd(new AutoBuffer) { (*pd)[0] = p; } //!< Constructs floating point scalar + CV_WRAP DictValue(const String &s) : type(Param::STRING), ps(new AutoBuffer) { (*ps)[0] = s; } //!< Constructs string scalar + DictValue(const char *s) : type(Param::STRING), ps(new AutoBuffer) { (*ps)[0] = s; } //!< @overload + + template + static DictValue arrayInt(TypeIter begin, int size); //!< Constructs integer array + template + static DictValue arrayReal(TypeIter begin, int size); //!< Constructs floating point array + template + static DictValue arrayString(TypeIter begin, int size); //!< Constructs array of strings + + template + T get(int idx = -1) const; //!< Tries to convert array element with specified index to requested type and returns its. + + int size() const; + + CV_WRAP bool isInt() const; + CV_WRAP bool isString() const; + CV_WRAP bool isReal() const; + + CV_WRAP int getIntValue(int idx = -1) const; + CV_WRAP double getRealValue(int idx = -1) const; + CV_WRAP String getStringValue(int idx = -1) const; + + DictValue &operator=(const DictValue &r); + + friend std::ostream &operator<<(std::ostream &stream, const DictValue &dictv); + + ~DictValue(); + +private: + + int type; + + union + { + AutoBuffer *pi; + AutoBuffer *pd; + AutoBuffer *ps; + void *pv; + }; + + DictValue(int _type, void *_p) : type(_type), pv(_p) {} + void release(); +}; + +/** @brief This class implements name-value dictionary, values are instances of DictValue. */ +class CV_EXPORTS Dict +{ + typedef std::map _Dict; + _Dict dict; + +public: + + //! Checks a presence of the @p key in the dictionary. + bool has(const String &key) const; + + //! If the @p key in the dictionary then returns pointer to its value, else returns NULL. + DictValue *ptr(const String &key); + + /** @overload */ + const DictValue *ptr(const String &key) const; + + //! If the @p key in the dictionary then returns its value, else an error will be generated. + const DictValue &get(const String &key) const; + + /** @overload */ + template + T get(const String &key) const; + + //! If the @p key in the dictionary then returns its value, else returns @p defaultValue. + template + T get(const String &key, const T &defaultValue) const; + + //! Sets new @p value for the @p key, or adds new key-value pair into the dictionary. + template + const T &set(const String &key, const T &value); + + //! Erase @p key from the dictionary. + void erase(const String &key); + + friend std::ostream &operator<<(std::ostream &stream, const Dict &dict); + + std::map::const_iterator begin() const; + + std::map::const_iterator end() const; +}; + +//! @} +CV__DNN_EXPERIMENTAL_NS_END +} +} + +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/dnn.hpp b/3rdparty/opencv/include/opencv2/dnn/dnn.hpp new file mode 100644 index 00000000..144fc11f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/dnn.hpp @@ -0,0 +1,973 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_DNN_HPP +#define OPENCV_DNN_DNN_HPP + +#include +#include + +#if !defined CV_DOXYGEN && !defined CV_DNN_DONT_ADD_EXPERIMENTAL_NS +#define CV__DNN_EXPERIMENTAL_NS_BEGIN namespace experimental_dnn_34_v11 { +#define CV__DNN_EXPERIMENTAL_NS_END } +namespace cv { namespace dnn { namespace experimental_dnn_34_v11 { } using namespace experimental_dnn_34_v11; }} +#else +#define CV__DNN_EXPERIMENTAL_NS_BEGIN +#define CV__DNN_EXPERIMENTAL_NS_END +#endif + +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN +//! @addtogroup dnn +//! @{ + + typedef std::vector MatShape; + + /** + * @brief Enum of computation backends supported by layers. + * @see Net::setPreferableBackend + */ + enum Backend + { + //! DNN_BACKEND_DEFAULT equals to DNN_BACKEND_INFERENCE_ENGINE if + //! OpenCV is built with Intel's Inference Engine library or + //! DNN_BACKEND_OPENCV otherwise. + DNN_BACKEND_DEFAULT, + DNN_BACKEND_HALIDE, + DNN_BACKEND_INFERENCE_ENGINE, + DNN_BACKEND_OPENCV + }; + + /** + * @brief Enum of target devices for computations. + * @see Net::setPreferableTarget + */ + enum Target + { + DNN_TARGET_CPU, + DNN_TARGET_OPENCL, + DNN_TARGET_OPENCL_FP16, + DNN_TARGET_MYRIAD, + //! FPGA device with CPU fallbacks using Inference Engine's Heterogeneous plugin. + DNN_TARGET_FPGA + }; + + CV_EXPORTS std::vector< std::pair > getAvailableBackends(); + CV_EXPORTS std::vector getAvailableTargets(Backend be); + + /** @brief This class provides all data needed to initialize layer. + * + * It includes dictionary with scalar params (which can be read by using Dict interface), + * blob params #blobs and optional meta information: #name and #type of layer instance. + */ + class CV_EXPORTS LayerParams : public Dict + { + public: + //TODO: Add ability to name blob params + std::vector blobs; //!< List of learned parameters stored as blobs. + + String name; //!< Name of the layer instance (optional, can be used internal purposes). + String type; //!< Type name which was used for creating layer by layer factory (optional). + }; + + /** + * @brief Derivatives of this class encapsulates functions of certain backends. + */ + class BackendNode + { + public: + BackendNode(int backendId); + + virtual ~BackendNode(); //!< Virtual destructor to make polymorphism. + + int backendId; //!< Backend identifier. + }; + + /** + * @brief Derivatives of this class wraps cv::Mat for different backends and targets. + */ + class BackendWrapper + { + public: + BackendWrapper(int backendId, int targetId); + + /** + * @brief Wrap cv::Mat for specific backend and target. + * @param[in] targetId Target identifier. + * @param[in] m cv::Mat for wrapping. + * + * Make CPU->GPU data transfer if it's require for the target. + */ + BackendWrapper(int targetId, const cv::Mat& m); + + /** + * @brief Make wrapper for reused cv::Mat. + * @param[in] base Wrapper of cv::Mat that will be reused. + * @param[in] shape Specific shape. + * + * Initialize wrapper from another one. It'll wrap the same host CPU + * memory and mustn't allocate memory on device(i.e. GPU). It might + * has different shape. Use in case of CPU memory reusing for reuse + * associated memory on device too. + */ + BackendWrapper(const Ptr& base, const MatShape& shape); + + virtual ~BackendWrapper(); //!< Virtual destructor to make polymorphism. + + /** + * @brief Transfer data to CPU host memory. + */ + virtual void copyToHost() = 0; + + /** + * @brief Indicate that an actual data is on CPU. + */ + virtual void setHostDirty() = 0; + + int backendId; //!< Backend identifier. + int targetId; //!< Target identifier. + }; + + class CV_EXPORTS ActivationLayer; + + /** @brief This interface class allows to build new Layers - are building blocks of networks. + * + * Each class, derived from Layer, must implement allocate() methods to declare own outputs and forward() to compute outputs. + * Also before using the new layer into networks you must register your layer by using one of @ref dnnLayerFactory "LayerFactory" macros. + */ + class CV_EXPORTS_W Layer : public Algorithm + { + public: + + //! List of learned parameters must be stored here to allow read them by using Net::getParam(). + CV_PROP_RW std::vector blobs; + + /** @brief Computes and sets internal parameters according to inputs, outputs and blobs. + * @deprecated Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead + * @param[in] input vector of already allocated input blobs + * @param[out] output vector of already allocated output blobs + * + * If this method is called after network has allocated all memory for input and output blobs + * and before inferencing. + */ + CV_DEPRECATED_EXTERNAL + virtual void finalize(const std::vector &input, std::vector &output); + + /** @brief Computes and sets internal parameters according to inputs, outputs and blobs. + * @param[in] inputs vector of already allocated input blobs + * @param[out] outputs vector of already allocated output blobs + * + * If this method is called after network has allocated all memory for input and output blobs + * and before inferencing. + */ + CV_WRAP virtual void finalize(InputArrayOfArrays inputs, OutputArrayOfArrays outputs); + + /** @brief Given the @p input blobs, computes the output @p blobs. + * @deprecated Use Layer::forward(InputArrayOfArrays, OutputArrayOfArrays, OutputArrayOfArrays) instead + * @param[in] input the input blobs. + * @param[out] output allocated output blobs, which will store results of the computation. + * @param[out] internals allocated internal blobs + */ + CV_DEPRECATED_EXTERNAL + virtual void forward(std::vector &input, std::vector &output, std::vector &internals); + + /** @brief Given the @p input blobs, computes the output @p blobs. + * @param[in] inputs the input blobs. + * @param[out] outputs allocated output blobs, which will store results of the computation. + * @param[out] internals allocated internal blobs + */ + virtual void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals); + + /** @brief Given the @p input blobs, computes the output @p blobs. + * @param[in] inputs the input blobs. + * @param[out] outputs allocated output blobs, which will store results of the computation. + * @param[out] internals allocated internal blobs + */ + void forward_fallback(InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals); + + /** @brief + * @overload + * @deprecated Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead + */ + CV_DEPRECATED_EXTERNAL + void finalize(const std::vector &inputs, CV_OUT std::vector &outputs); + + /** @brief + * @overload + * @deprecated Use Layer::finalize(InputArrayOfArrays, OutputArrayOfArrays) instead + */ + CV_DEPRECATED std::vector finalize(const std::vector &inputs); + + /** @brief Allocates layer and computes output. + * @deprecated This method will be removed in the future release. + */ + CV_DEPRECATED CV_WRAP void run(const std::vector &inputs, CV_OUT std::vector &outputs, + CV_IN_OUT std::vector &internals); + + /** @brief Returns index of input blob into the input array. + * @param inputName label of input blob + * + * Each layer input and output can be labeled to easily identify them using "%[.output_name]" notation. + * This method maps label of input blob to its index into input vector. + */ + virtual int inputNameToIndex(String inputName); + /** @brief Returns index of output blob in output array. + * @see inputNameToIndex() + */ + CV_WRAP virtual int outputNameToIndex(const String& outputName); + + /** + * @brief Ask layer if it support specific backend for doing computations. + * @param[in] backendId computation backend identifier. + * @see Backend + */ + virtual bool supportBackend(int backendId); + + /** + * @brief Returns Halide backend node. + * @param[in] inputs Input Halide buffers. + * @see BackendNode, BackendWrapper + * + * Input buffers should be exactly the same that will be used in forward invocations. + * Despite we can use Halide::ImageParam based on input shape only, + * it helps prevent some memory management issues (if something wrong, + * Halide tests will be failed). + */ + virtual Ptr initHalide(const std::vector > &inputs); + + virtual Ptr initInfEngine(const std::vector > &inputs); + + /** + * @brief Automatic Halide scheduling based on layer hyper-parameters. + * @param[in] node Backend node with Halide functions. + * @param[in] inputs Blobs that will be used in forward invocations. + * @param[in] outputs Blobs that will be used in forward invocations. + * @param[in] targetId Target identifier + * @see BackendNode, Target + * + * Layer don't use own Halide::Func members because we can have applied + * layers fusing. In this way the fused function should be scheduled. + */ + virtual void applyHalideScheduler(Ptr& node, + const std::vector &inputs, + const std::vector &outputs, + int targetId) const; + + /** + * @brief Implement layers fusing. + * @param[in] node Backend node of bottom layer. + * @see BackendNode + * + * Actual for graph-based backends. If layer attached successfully, + * returns non-empty cv::Ptr to node of the same backend. + * Fuse only over the last function. + */ + virtual Ptr tryAttach(const Ptr& node); + + /** + * @brief Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case. + * @param[in] layer The subsequent activation layer. + * + * Returns true if the activation layer has been attached successfully. + */ + virtual bool setActivation(const Ptr& layer); + + /** + * @brief Try to fuse current layer with a next one + * @param[in] top Next layer to be fused. + * @returns True if fusion was performed. + */ + virtual bool tryFuse(Ptr& top); + + /** + * @brief Returns parameters of layers with channel-wise multiplication and addition. + * @param[out] scale Channel-wise multipliers. Total number of values should + * be equal to number of channels. + * @param[out] shift Channel-wise offsets. Total number of values should + * be equal to number of channels. + * + * Some layers can fuse their transformations with further layers. + * In example, convolution + batch normalization. This way base layer + * use weights from layer after it. Fused layer is skipped. + * By default, @p scale and @p shift are empty that means layer has no + * element-wise multiplications or additions. + */ + virtual void getScaleShift(Mat& scale, Mat& shift) const; + + /** + * @brief "Deattaches" all the layers, attached to particular layer. + */ + virtual void unsetAttached(); + + virtual bool getMemoryShapes(const std::vector &inputs, + const int requiredOutputs, + std::vector &outputs, + std::vector &internals) const; + virtual int64 getFLOPS(const std::vector &inputs, + const std::vector &outputs) const {CV_UNUSED(inputs); CV_UNUSED(outputs); return 0;} + + CV_PROP String name; //!< Name of the layer instance, can be used for logging or other internal purposes. + CV_PROP String type; //!< Type name which was used for creating layer by layer factory. + CV_PROP int preferableTarget; //!< prefer target for layer forwarding + + Layer(); + explicit Layer(const LayerParams ¶ms); //!< Initializes only #name, #type and #blobs fields. + void setParamsFrom(const LayerParams ¶ms); //!< Initializes only #name, #type and #blobs fields. + virtual ~Layer(); + }; + + /** @brief This class allows to create and manipulate comprehensive artificial neural networks. + * + * Neural network is presented as directed acyclic graph (DAG), where vertices are Layer instances, + * and edges specify relationships between layers inputs and outputs. + * + * Each network layer has unique integer id and unique string name inside its network. + * LayerId can store either layer name or layer id. + * + * This class supports reference counting of its instances, i. e. copies point to the same instance. + */ + class CV_EXPORTS_W_SIMPLE Net + { + public: + + CV_WRAP Net(); //!< Default constructor. + CV_WRAP ~Net(); //!< Destructor frees the net only if there aren't references to the net anymore. + + /** @brief Create a network from Intel's Model Optimizer intermediate representation. + * @param[in] xml XML configuration file with network's topology. + * @param[in] bin Binary file with trained weights. + * Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine + * backend. + */ + CV_WRAP static Net readFromModelOptimizer(const String& xml, const String& bin); + + /** Returns true if there are no layers in the network. */ + CV_WRAP bool empty() const; + + /** @brief Adds new layer to the net. + * @param name unique name of the adding layer. + * @param type typename of the adding layer (type must be registered in LayerRegister). + * @param params parameters which will be used to initialize the creating layer. + * @returns unique identifier of created layer, or -1 if a failure will happen. + */ + int addLayer(const String &name, const String &type, LayerParams ¶ms); + /** @brief Adds new layer and connects its first input to the first output of previously added layer. + * @see addLayer() + */ + int addLayerToPrev(const String &name, const String &type, LayerParams ¶ms); + + /** @brief Converts string name of the layer to the integer identifier. + * @returns id of the layer, or -1 if the layer wasn't found. + */ + CV_WRAP int getLayerId(const String &layer); + + CV_WRAP std::vector getLayerNames() const; + + /** @brief Container for strings and integers. */ + typedef DictValue LayerId; + + /** @brief Returns pointer to layer with specified id or name which the network use. */ + CV_WRAP Ptr getLayer(LayerId layerId); + + /** @brief Returns pointers to input layers of specific layer. */ + std::vector > getLayerInputs(LayerId layerId); // FIXIT: CV_WRAP + + /** @brief Connects output of the first layer to input of the second layer. + * @param outPin descriptor of the first layer output. + * @param inpPin descriptor of the second layer input. + * + * Descriptors have the following template <layer_name>[.input_number]: + * - the first part of the template layer_name is sting name of the added layer. + * If this part is empty then the network input pseudo layer will be used; + * - the second optional part of the template input_number + * is either number of the layer input, either label one. + * If this part is omitted then the first layer input will be used. + * + * @see setNetInputs(), Layer::inputNameToIndex(), Layer::outputNameToIndex() + */ + CV_WRAP void connect(String outPin, String inpPin); + + /** @brief Connects #@p outNum output of the first layer to #@p inNum input of the second layer. + * @param outLayerId identifier of the first layer + * @param outNum number of the first layer output + * @param inpLayerId identifier of the second layer + * @param inpNum number of the second layer input + */ + void connect(int outLayerId, int outNum, int inpLayerId, int inpNum); + + /** @brief Sets outputs names of the network input pseudo layer. + * + * Each net always has special own the network input pseudo layer with id=0. + * This layer stores the user blobs only and don't make any computations. + * In fact, this layer provides the only way to pass user data into the network. + * As any other layer, this layer can label its outputs and this function provides an easy way to do this. + */ + CV_WRAP void setInputsNames(const std::vector &inputBlobNames); + + /** @brief Runs forward pass to compute output of layer with name @p outputName. + * @param outputName name for layer which output is needed to get + * @return blob for first output of specified layer. + * @details By default runs forward pass for the whole network. + */ + CV_WRAP Mat forward(const String& outputName = String()); + + /** @brief Runs forward pass to compute output of layer with name @p outputName. + * @param outputBlobs contains all output blobs for specified layer. + * @param outputName name for layer which output is needed to get + * @details If @p outputName is empty, runs forward pass for the whole network. + */ + CV_WRAP void forward(OutputArrayOfArrays outputBlobs, const String& outputName = String()); + + /** @brief Runs forward pass to compute outputs of layers listed in @p outBlobNames. + * @param outputBlobs contains blobs for first outputs of specified layers. + * @param outBlobNames names for layers which outputs are needed to get + */ + CV_WRAP void forward(OutputArrayOfArrays outputBlobs, + const std::vector& outBlobNames); + + /** @brief Runs forward pass to compute outputs of layers listed in @p outBlobNames. + * @param outputBlobs contains all output blobs for each layer specified in @p outBlobNames. + * @param outBlobNames names for layers which outputs are needed to get + */ + CV_WRAP_AS(forwardAndRetrieve) void forward(CV_OUT std::vector >& outputBlobs, + const std::vector& outBlobNames); + + /** + * @brief Compile Halide layers. + * @param[in] scheduler Path to YAML file with scheduling directives. + * @see setPreferableBackend + * + * Schedule layers that support Halide backend. Then compile them for + * specific target. For layers that not represented in scheduling file + * or if no manual scheduling used at all, automatic scheduling will be applied. + */ + CV_WRAP void setHalideScheduler(const String& scheduler); + + /** + * @brief Ask network to use specific computation backend where it supported. + * @param[in] backendId backend identifier. + * @see Backend + * + * If OpenCV is compiled with Intel's Inference Engine library, DNN_BACKEND_DEFAULT + * means DNN_BACKEND_INFERENCE_ENGINE. Otherwise it equals to DNN_BACKEND_OPENCV. + */ + CV_WRAP void setPreferableBackend(int backendId); + + /** + * @brief Ask network to make computations on specific target device. + * @param[in] targetId target identifier. + * @see Target + * + * List of supported combinations backend / target: + * | | DNN_BACKEND_OPENCV | DNN_BACKEND_INFERENCE_ENGINE | DNN_BACKEND_HALIDE | + * |------------------------|--------------------|------------------------------|--------------------| + * | DNN_TARGET_CPU | + | + | + | + * | DNN_TARGET_OPENCL | + | + | + | + * | DNN_TARGET_OPENCL_FP16 | + | + | | + * | DNN_TARGET_MYRIAD | | + | | + * | DNN_TARGET_FPGA | | + | | + */ + CV_WRAP void setPreferableTarget(int targetId); + + /** @brief Sets the new input value for the network + * @param blob A new blob. Should have CV_32F or CV_8U depth. + * @param name A name of input layer. + * @param scalefactor An optional normalization scale. + * @param mean An optional mean subtraction values. + * @see connect(String, String) to know format of the descriptor. + * + * If scale or mean values are specified, a final input blob is computed + * as: + * \f[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\f] + */ + CV_WRAP void setInput(InputArray blob, const String& name = "", + double scalefactor = 1.0, const Scalar& mean = Scalar()); + + /** @brief Sets the new value for the learned param of the layer. + * @param layer name or id of the layer. + * @param numParam index of the layer parameter in the Layer::blobs array. + * @param blob the new value. + * @see Layer::blobs + * @note If shape of the new blob differs from the previous shape, + * then the following forward pass may fail. + */ + CV_WRAP void setParam(LayerId layer, int numParam, const Mat &blob); + + /** @brief Returns parameter blob of the layer. + * @param layer name or id of the layer. + * @param numParam index of the layer parameter in the Layer::blobs array. + * @see Layer::blobs + */ + CV_WRAP Mat getParam(LayerId layer, int numParam = 0); + + /** @brief Returns indexes of layers with unconnected outputs. + */ + CV_WRAP std::vector getUnconnectedOutLayers() const; + + /** @brief Returns names of layers with unconnected outputs. + */ + CV_WRAP std::vector getUnconnectedOutLayersNames() const; + + /** @brief Returns input and output shapes for all layers in loaded model; + * preliminary inferencing isn't necessary. + * @param netInputShapes shapes for all input blobs in net input layer. + * @param layersIds output parameter for layer IDs. + * @param inLayersShapes output parameter for input layers shapes; + * order is the same as in layersIds + * @param outLayersShapes output parameter for output layers shapes; + * order is the same as in layersIds + */ + CV_WRAP void getLayersShapes(const std::vector& netInputShapes, + CV_OUT std::vector& layersIds, + CV_OUT std::vector >& inLayersShapes, + CV_OUT std::vector >& outLayersShapes) const; + + /** @overload */ + CV_WRAP void getLayersShapes(const MatShape& netInputShape, + CV_OUT std::vector& layersIds, + CV_OUT std::vector >& inLayersShapes, + CV_OUT std::vector >& outLayersShapes) const; + + /** @brief Returns input and output shapes for layer with specified + * id in loaded model; preliminary inferencing isn't necessary. + * @param netInputShape shape input blob in net input layer. + * @param layerId id for layer. + * @param inLayerShapes output parameter for input layers shapes; + * order is the same as in layersIds + * @param outLayerShapes output parameter for output layers shapes; + * order is the same as in layersIds + */ + void getLayerShapes(const MatShape& netInputShape, + const int layerId, + CV_OUT std::vector& inLayerShapes, + CV_OUT std::vector& outLayerShapes) const; // FIXIT: CV_WRAP + + /** @overload */ + void getLayerShapes(const std::vector& netInputShapes, + const int layerId, + CV_OUT std::vector& inLayerShapes, + CV_OUT std::vector& outLayerShapes) const; // FIXIT: CV_WRAP + + /** @brief Computes FLOP for whole loaded model with specified input shapes. + * @param netInputShapes vector of shapes for all net inputs. + * @returns computed FLOP. + */ + CV_WRAP int64 getFLOPS(const std::vector& netInputShapes) const; + /** @overload */ + CV_WRAP int64 getFLOPS(const MatShape& netInputShape) const; + /** @overload */ + CV_WRAP int64 getFLOPS(const int layerId, + const std::vector& netInputShapes) const; + /** @overload */ + CV_WRAP int64 getFLOPS(const int layerId, + const MatShape& netInputShape) const; + + /** @brief Returns list of types for layer used in model. + * @param layersTypes output parameter for returning types. + */ + CV_WRAP void getLayerTypes(CV_OUT std::vector& layersTypes) const; + + /** @brief Returns count of layers of specified type. + * @param layerType type. + * @returns count of layers + */ + CV_WRAP int getLayersCount(const String& layerType) const; + + /** @brief Computes bytes number which are required to store + * all weights and intermediate blobs for model. + * @param netInputShapes vector of shapes for all net inputs. + * @param weights output parameter to store resulting bytes for weights. + * @param blobs output parameter to store resulting bytes for intermediate blobs. + */ + void getMemoryConsumption(const std::vector& netInputShapes, + CV_OUT size_t& weights, CV_OUT size_t& blobs) const; // FIXIT: CV_WRAP + /** @overload */ + CV_WRAP void getMemoryConsumption(const MatShape& netInputShape, + CV_OUT size_t& weights, CV_OUT size_t& blobs) const; + /** @overload */ + CV_WRAP void getMemoryConsumption(const int layerId, + const std::vector& netInputShapes, + CV_OUT size_t& weights, CV_OUT size_t& blobs) const; + /** @overload */ + CV_WRAP void getMemoryConsumption(const int layerId, + const MatShape& netInputShape, + CV_OUT size_t& weights, CV_OUT size_t& blobs) const; + + /** @brief Computes bytes number which are required to store + * all weights and intermediate blobs for each layer. + * @param netInputShapes vector of shapes for all net inputs. + * @param layerIds output vector to save layer IDs. + * @param weights output parameter to store resulting bytes for weights. + * @param blobs output parameter to store resulting bytes for intermediate blobs. + */ + void getMemoryConsumption(const std::vector& netInputShapes, + CV_OUT std::vector& layerIds, + CV_OUT std::vector& weights, + CV_OUT std::vector& blobs) const; // FIXIT: CV_WRAP + /** @overload */ + void getMemoryConsumption(const MatShape& netInputShape, + CV_OUT std::vector& layerIds, + CV_OUT std::vector& weights, + CV_OUT std::vector& blobs) const; // FIXIT: CV_WRAP + + /** @brief Enables or disables layer fusion in the network. + * @param fusion true to enable the fusion, false to disable. The fusion is enabled by default. + */ + CV_WRAP void enableFusion(bool fusion); + + /** @brief Returns overall time for inference and timings (in ticks) for layers. + * Indexes in returned vector correspond to layers ids. Some layers can be fused with others, + * in this case zero ticks count will be return for that skipped layers. + * @param timings vector for tick timings for all layers. + * @return overall ticks for model inference. + */ + CV_WRAP int64 getPerfProfile(CV_OUT std::vector& timings); + + private: + struct Impl; + Ptr impl; + }; + + /** @brief Reads a network model stored in Darknet model files. + * @param cfgFile path to the .cfg file with text description of the network architecture. + * @param darknetModel path to the .weights file with learned network. + * @returns Network object that ready to do forward, throw an exception in failure cases. + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromDarknet(const String &cfgFile, const String &darknetModel = String()); + + /** @brief Reads a network model stored in Darknet model files. + * @param bufferCfg A buffer contains a content of .cfg file with text description of the network architecture. + * @param bufferModel A buffer contains a content of .weights file with learned network. + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromDarknet(const std::vector& bufferCfg, + const std::vector& bufferModel = std::vector()); + + /** @brief Reads a network model stored in Darknet model files. + * @param bufferCfg A buffer contains a content of .cfg file with text description of the network architecture. + * @param lenCfg Number of bytes to read from bufferCfg + * @param bufferModel A buffer contains a content of .weights file with learned network. + * @param lenModel Number of bytes to read from bufferModel + * @returns Net object. + */ + CV_EXPORTS Net readNetFromDarknet(const char *bufferCfg, size_t lenCfg, + const char *bufferModel = NULL, size_t lenModel = 0); + + /** @brief Reads a network model stored in Caffe framework's format. + * @param prototxt path to the .prototxt file with text description of the network architecture. + * @param caffeModel path to the .caffemodel file with learned network. + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromCaffe(const String &prototxt, const String &caffeModel = String()); + + /** @brief Reads a network model stored in Caffe model in memory. + * @param bufferProto buffer containing the content of the .prototxt file + * @param bufferModel buffer containing the content of the .caffemodel file + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromCaffe(const std::vector& bufferProto, + const std::vector& bufferModel = std::vector()); + + /** @brief Reads a network model stored in Caffe model in memory. + * @details This is an overloaded member function, provided for convenience. + * It differs from the above function only in what argument(s) it accepts. + * @param bufferProto buffer containing the content of the .prototxt file + * @param lenProto length of bufferProto + * @param bufferModel buffer containing the content of the .caffemodel file + * @param lenModel length of bufferModel + * @returns Net object. + */ + CV_EXPORTS Net readNetFromCaffe(const char *bufferProto, size_t lenProto, + const char *bufferModel = NULL, size_t lenModel = 0); + + /** @brief Reads a network model stored in TensorFlow framework's format. + * @param model path to the .pb file with binary protobuf description of the network architecture + * @param config path to the .pbtxt file that contains text graph definition in protobuf format. + * Resulting Net object is built by text graph using weights from a binary one that + * let us make it more flexible. + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromTensorflow(const String &model, const String &config = String()); + + /** @brief Reads a network model stored in TensorFlow framework's format. + * @param bufferModel buffer containing the content of the pb file + * @param bufferConfig buffer containing the content of the pbtxt file + * @returns Net object. + */ + CV_EXPORTS_W Net readNetFromTensorflow(const std::vector& bufferModel, + const std::vector& bufferConfig = std::vector()); + + /** @brief Reads a network model stored in TensorFlow framework's format. + * @details This is an overloaded member function, provided for convenience. + * It differs from the above function only in what argument(s) it accepts. + * @param bufferModel buffer containing the content of the pb file + * @param lenModel length of bufferModel + * @param bufferConfig buffer containing the content of the pbtxt file + * @param lenConfig length of bufferConfig + */ + CV_EXPORTS Net readNetFromTensorflow(const char *bufferModel, size_t lenModel, + const char *bufferConfig = NULL, size_t lenConfig = 0); + + /** + * @brief Reads a network model stored in Torch7 framework's format. + * @param model path to the file, dumped from Torch by using torch.save() function. + * @param isBinary specifies whether the network was serialized in ascii mode or binary. + * @param evaluate specifies testing phase of network. If true, it's similar to evaluate() method in Torch. + * @returns Net object. + * + * @note Ascii mode of Torch serializer is more preferable, because binary mode extensively use `long` type of C language, + * which has various bit-length on different systems. + * + * The loading file must contain serialized nn.Module object + * with importing network. Try to eliminate a custom objects from serialazing data to avoid importing errors. + * + * List of supported layers (i.e. object instances derived from Torch nn.Module class): + * - nn.Sequential + * - nn.Parallel + * - nn.Concat + * - nn.Linear + * - nn.SpatialConvolution + * - nn.SpatialMaxPooling, nn.SpatialAveragePooling + * - nn.ReLU, nn.TanH, nn.Sigmoid + * - nn.Reshape + * - nn.SoftMax, nn.LogSoftMax + * + * Also some equivalents of these classes from cunn, cudnn, and fbcunn may be successfully imported. + */ + CV_EXPORTS_W Net readNetFromTorch(const String &model, bool isBinary = true, bool evaluate = true); + + /** + * @brief Read deep learning network represented in one of the supported formats. + * @param[in] model Binary file contains trained weights. The following file + * extensions are expected for models from different frameworks: + * * `*.caffemodel` (Caffe, http://caffe.berkeleyvision.org/) + * * `*.pb` (TensorFlow, https://www.tensorflow.org/) + * * `*.t7` | `*.net` (Torch, http://torch.ch/) + * * `*.weights` (Darknet, https://pjreddie.com/darknet/) + * * `*.bin` (DLDT, https://software.intel.com/openvino-toolkit) + * @param[in] config Text file contains network configuration. It could be a + * file with the following extensions: + * * `*.prototxt` (Caffe, http://caffe.berkeleyvision.org/) + * * `*.pbtxt` (TensorFlow, https://www.tensorflow.org/) + * * `*.cfg` (Darknet, https://pjreddie.com/darknet/) + * * `*.xml` (DLDT, https://software.intel.com/openvino-toolkit) + * @param[in] framework Explicit framework name tag to determine a format. + * @returns Net object. + * + * This function automatically detects an origin framework of trained model + * and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow, + * @ref readNetFromTorch or @ref readNetFromDarknet. An order of @p model and @p config + * arguments does not matter. + */ + CV_EXPORTS_W Net readNet(const String& model, const String& config = "", const String& framework = ""); + + /** + * @brief Read deep learning network represented in one of the supported formats. + * @details This is an overloaded member function, provided for convenience. + * It differs from the above function only in what argument(s) it accepts. + * @param[in] framework Name of origin framework. + * @param[in] bufferModel A buffer with a content of binary file with weights + * @param[in] bufferConfig A buffer with a content of text file contains network configuration. + * @returns Net object. + */ + CV_EXPORTS_W Net readNet(const String& framework, const std::vector& bufferModel, + const std::vector& bufferConfig = std::vector()); + + /** @brief Loads blob which was serialized as torch.Tensor object of Torch7 framework. + * @warning This function has the same limitations as readNetFromTorch(). + */ + CV_EXPORTS_W Mat readTorchBlob(const String &filename, bool isBinary = true); + + /** @brief Load a network from Intel's Model Optimizer intermediate representation. + * @param[in] xml XML configuration file with network's topology. + * @param[in] bin Binary file with trained weights. + * @returns Net object. + * Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine + * backend. + */ + CV_EXPORTS_W Net readNetFromModelOptimizer(const String &xml, const String &bin); + + /** @brief Reads a network model ONNX. + * @param onnxFile path to the .onnx file with text description of the network architecture. + * @returns Network object that ready to do forward, throw an exception in failure cases. + */ + CV_EXPORTS_W Net readNetFromONNX(const String &onnxFile); + + /** @brief Creates blob from .pb file. + * @param path to the .pb file with input tensor. + * @returns Mat. + */ + CV_EXPORTS_W Mat readTensorFromONNX(const String& path); + + /** @brief Creates 4-dimensional blob from image. Optionally resizes and crops @p image from center, + * subtract @p mean values, scales values by @p scalefactor, swap Blue and Red channels. + * @param image input image (with 1-, 3- or 4-channels). + * @param size spatial size for output image + * @param mean scalar with mean values which are subtracted from channels. Values are intended + * to be in (mean-R, mean-G, mean-B) order if @p image has BGR ordering and @p swapRB is true. + * @param scalefactor multiplier for @p image values. + * @param swapRB flag which indicates that swap first and last channels + * in 3-channel image is necessary. + * @param crop flag which indicates whether image will be cropped after resize or not + * @param ddepth Depth of output blob. Choose CV_32F or CV_8U. + * @details if @p crop is true, input image is resized so one side after resize is equal to corresponding + * dimension in @p size and another one is equal or larger. Then, crop from the center is performed. + * If @p crop is false, direct resize without cropping and preserving aspect ratio is performed. + * @returns 4-dimensional Mat with NCHW dimensions order. + */ + CV_EXPORTS_W Mat blobFromImage(InputArray image, double scalefactor=1.0, const Size& size = Size(), + const Scalar& mean = Scalar(), bool swapRB=false, bool crop=false, + int ddepth=CV_32F); + + /** @brief Creates 4-dimensional blob from image. + * @details This is an overloaded member function, provided for convenience. + * It differs from the above function only in what argument(s) it accepts. + */ + CV_EXPORTS void blobFromImage(InputArray image, OutputArray blob, double scalefactor=1.0, + const Size& size = Size(), const Scalar& mean = Scalar(), + bool swapRB=false, bool crop=false, int ddepth=CV_32F); + + + /** @brief Creates 4-dimensional blob from series of images. Optionally resizes and + * crops @p images from center, subtract @p mean values, scales values by @p scalefactor, + * swap Blue and Red channels. + * @param images input images (all with 1-, 3- or 4-channels). + * @param size spatial size for output image + * @param mean scalar with mean values which are subtracted from channels. Values are intended + * to be in (mean-R, mean-G, mean-B) order if @p image has BGR ordering and @p swapRB is true. + * @param scalefactor multiplier for @p images values. + * @param swapRB flag which indicates that swap first and last channels + * in 3-channel image is necessary. + * @param crop flag which indicates whether image will be cropped after resize or not + * @param ddepth Depth of output blob. Choose CV_32F or CV_8U. + * @details if @p crop is true, input image is resized so one side after resize is equal to corresponding + * dimension in @p size and another one is equal or larger. Then, crop from the center is performed. + * If @p crop is false, direct resize without cropping and preserving aspect ratio is performed. + * @returns 4-dimensional Mat with NCHW dimensions order. + */ + CV_EXPORTS_W Mat blobFromImages(InputArrayOfArrays images, double scalefactor=1.0, + Size size = Size(), const Scalar& mean = Scalar(), bool swapRB=false, bool crop=false, + int ddepth=CV_32F); + + /** @brief Creates 4-dimensional blob from series of images. + * @details This is an overloaded member function, provided for convenience. + * It differs from the above function only in what argument(s) it accepts. + */ + CV_EXPORTS void blobFromImages(InputArrayOfArrays images, OutputArray blob, + double scalefactor=1.0, Size size = Size(), + const Scalar& mean = Scalar(), bool swapRB=false, bool crop=false, + int ddepth=CV_32F); + + /** @brief Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure + * (std::vector). + * @param[in] blob_ 4 dimensional array (images, channels, height, width) in floating point precision (CV_32F) from + * which you would like to extract the images. + * @param[out] images_ array of 2D Mat containing the images extracted from the blob in floating point precision + * (CV_32F). They are non normalized neither mean added. The number of returned images equals the first dimension + * of the blob (batch size). Every image has a number of channels equals to the second dimension of the blob (depth). + */ + CV_EXPORTS_W void imagesFromBlob(const cv::Mat& blob_, OutputArrayOfArrays images_); + + /** @brief Convert all weights of Caffe network to half precision floating point. + * @param src Path to origin model from Caffe framework contains single + * precision floating point weights (usually has `.caffemodel` extension). + * @param dst Path to destination model with updated weights. + * @param layersTypes Set of layers types which parameters will be converted. + * By default, converts only Convolutional and Fully-Connected layers' + * weights. + * + * @note Shrinked model has no origin float32 weights so it can't be used + * in origin Caffe framework anymore. However the structure of data + * is taken from NVidia's Caffe fork: https://github.com/NVIDIA/caffe. + * So the resulting model may be used there. + */ + CV_EXPORTS_W void shrinkCaffeModel(const String& src, const String& dst, + const std::vector& layersTypes = std::vector()); + + /** @brief Create a text representation for a binary network stored in protocol buffer format. + * @param[in] model A path to binary network. + * @param[in] output A path to output text file to be created. + * + * @note To reduce output file size, trained weights are not included. + */ + CV_EXPORTS_W void writeTextGraph(const String& model, const String& output); + + /** @brief Performs non maximum suppression given boxes and corresponding scores. + + * @param bboxes a set of bounding boxes to apply NMS. + * @param scores a set of corresponding confidences. + * @param score_threshold a threshold used to filter boxes by score. + * @param nms_threshold a threshold used in non maximum suppression. + * @param indices the kept indices of bboxes after NMS. + * @param eta a coefficient in adaptive threshold formula: \f$nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\f$. + * @param top_k if `>0`, keep at most @p top_k picked indices. + */ + CV_EXPORTS_W void NMSBoxes(const std::vector& bboxes, const std::vector& scores, + const float score_threshold, const float nms_threshold, + CV_OUT std::vector& indices, + const float eta = 1.f, const int top_k = 0); + + CV_EXPORTS_W void NMSBoxes(const std::vector& bboxes, const std::vector& scores, + const float score_threshold, const float nms_threshold, + CV_OUT std::vector& indices, + const float eta = 1.f, const int top_k = 0); + + CV_EXPORTS_AS(NMSBoxesRotated) void NMSBoxes(const std::vector& bboxes, const std::vector& scores, + const float score_threshold, const float nms_threshold, + CV_OUT std::vector& indices, + const float eta = 1.f, const int top_k = 0); + +//! @} +CV__DNN_EXPERIMENTAL_NS_END +} +} + +#include +#include + +/// @deprecated Include this header directly from application. Automatic inclusion will be removed +#include + +#endif /* OPENCV_DNN_DNN_HPP */ diff --git a/3rdparty/opencv/include/opencv2/dnn/dnn.inl.hpp b/3rdparty/opencv/include/opencv2/dnn/dnn.inl.hpp new file mode 100644 index 00000000..17d4c200 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/dnn.inl.hpp @@ -0,0 +1,395 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_DNN_INL_HPP +#define OPENCV_DNN_DNN_INL_HPP + +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN + +template +DictValue DictValue::arrayInt(TypeIter begin, int size) +{ + DictValue res(Param::INT, new AutoBuffer(size)); + for (int j = 0; j < size; begin++, j++) + (*res.pi)[j] = *begin; + return res; +} + +template +DictValue DictValue::arrayReal(TypeIter begin, int size) +{ + DictValue res(Param::REAL, new AutoBuffer(size)); + for (int j = 0; j < size; begin++, j++) + (*res.pd)[j] = *begin; + return res; +} + +template +DictValue DictValue::arrayString(TypeIter begin, int size) +{ + DictValue res(Param::STRING, new AutoBuffer(size)); + for (int j = 0; j < size; begin++, j++) + (*res.ps)[j] = *begin; + return res; +} + +template<> +inline DictValue DictValue::get(int idx) const +{ + CV_Assert(idx == -1); + return *this; +} + +template<> +inline int64 DictValue::get(int idx) const +{ + CV_Assert((idx == -1 && size() == 1) || (idx >= 0 && idx < size())); + idx = (idx == -1) ? 0 : idx; + + if (type == Param::INT) + { + return (*pi)[idx]; + } + else if (type == Param::REAL) + { + double doubleValue = (*pd)[idx]; + + double fracpart, intpart; + fracpart = std::modf(doubleValue, &intpart); + CV_Assert(fracpart == 0.0); + + return (int64)doubleValue; + } + else if (type == Param::STRING) + { + return std::atoi((*ps)[idx].c_str()); + } + else + { + CV_Assert(isInt() || isReal() || isString()); + return 0; + } +} + +template<> +inline int DictValue::get(int idx) const +{ + return (int)get(idx); +} + +inline int DictValue::getIntValue(int idx) const +{ + return (int)get(idx); +} + +template<> +inline unsigned DictValue::get(int idx) const +{ + return (unsigned)get(idx); +} + +template<> +inline bool DictValue::get(int idx) const +{ + return (get(idx) != 0); +} + +template<> +inline double DictValue::get(int idx) const +{ + CV_Assert((idx == -1 && size() == 1) || (idx >= 0 && idx < size())); + idx = (idx == -1) ? 0 : idx; + + if (type == Param::REAL) + { + return (*pd)[idx]; + } + else if (type == Param::INT) + { + return (double)(*pi)[idx]; + } + else if (type == Param::STRING) + { + return std::atof((*ps)[idx].c_str()); + } + else + { + CV_Assert(isReal() || isInt() || isString()); + return 0; + } +} + +inline double DictValue::getRealValue(int idx) const +{ + return get(idx); +} + +template<> +inline float DictValue::get(int idx) const +{ + return (float)get(idx); +} + +template<> +inline String DictValue::get(int idx) const +{ + CV_Assert(isString()); + CV_Assert((idx == -1 && ps->size() == 1) || (idx >= 0 && idx < (int)ps->size())); + return (*ps)[(idx == -1) ? 0 : idx]; +} + + +inline String DictValue::getStringValue(int idx) const +{ + return get(idx); +} + +inline void DictValue::release() +{ + switch (type) + { + case Param::INT: + delete pi; + break; + case Param::STRING: + delete ps; + break; + case Param::REAL: + delete pd; + break; + } +} + +inline DictValue::~DictValue() +{ + release(); +} + +inline DictValue & DictValue::operator=(const DictValue &r) +{ + if (&r == this) + return *this; + + if (r.type == Param::INT) + { + AutoBuffer *tmp = new AutoBuffer(*r.pi); + release(); + pi = tmp; + } + else if (r.type == Param::STRING) + { + AutoBuffer *tmp = new AutoBuffer(*r.ps); + release(); + ps = tmp; + } + else if (r.type == Param::REAL) + { + AutoBuffer *tmp = new AutoBuffer(*r.pd); + release(); + pd = tmp; + } + + type = r.type; + + return *this; +} + +inline DictValue::DictValue(const DictValue &r) +{ + type = r.type; + + if (r.type == Param::INT) + pi = new AutoBuffer(*r.pi); + else if (r.type == Param::STRING) + ps = new AutoBuffer(*r.ps); + else if (r.type == Param::REAL) + pd = new AutoBuffer(*r.pd); +} + +inline bool DictValue::isString() const +{ + return (type == Param::STRING); +} + +inline bool DictValue::isInt() const +{ + return (type == Param::INT); +} + +inline bool DictValue::isReal() const +{ + return (type == Param::REAL || type == Param::INT); +} + +inline int DictValue::size() const +{ + switch (type) + { + case Param::INT: + return (int)pi->size(); + case Param::STRING: + return (int)ps->size(); + case Param::REAL: + return (int)pd->size(); + } +#ifdef __OPENCV_BUILD + CV_Error(Error::StsInternal, ""); +#else + CV_ErrorNoReturn(Error::StsInternal, ""); +#endif +} + +inline std::ostream &operator<<(std::ostream &stream, const DictValue &dictv) +{ + int i; + + if (dictv.isInt()) + { + for (i = 0; i < dictv.size() - 1; i++) + stream << dictv.get(i) << ", "; + stream << dictv.get(i); + } + else if (dictv.isReal()) + { + for (i = 0; i < dictv.size() - 1; i++) + stream << dictv.get(i) << ", "; + stream << dictv.get(i); + } + else if (dictv.isString()) + { + for (i = 0; i < dictv.size() - 1; i++) + stream << "\"" << dictv.get(i) << "\", "; + stream << dictv.get(i); + } + + return stream; +} + +///////////////////////////////////////////////////////////////// + +inline bool Dict::has(const String &key) const +{ + return dict.count(key) != 0; +} + +inline DictValue *Dict::ptr(const String &key) +{ + _Dict::iterator i = dict.find(key); + return (i == dict.end()) ? NULL : &i->second; +} + +inline const DictValue *Dict::ptr(const String &key) const +{ + _Dict::const_iterator i = dict.find(key); + return (i == dict.end()) ? NULL : &i->second; +} + +inline const DictValue &Dict::get(const String &key) const +{ + _Dict::const_iterator i = dict.find(key); + if (i == dict.end()) + CV_Error(Error::StsObjectNotFound, "Required argument \"" + key + "\" not found into dictionary"); + return i->second; +} + +template +inline T Dict::get(const String &key) const +{ + return this->get(key).get(); +} + +template +inline T Dict::get(const String &key, const T &defaultValue) const +{ + _Dict::const_iterator i = dict.find(key); + + if (i != dict.end()) + return i->second.get(); + else + return defaultValue; +} + +template +inline const T &Dict::set(const String &key, const T &value) +{ + _Dict::iterator i = dict.find(key); + + if (i != dict.end()) + i->second = DictValue(value); + else + dict.insert(std::make_pair(key, DictValue(value))); + + return value; +} + +inline void Dict::erase(const String &key) +{ + dict.erase(key); +} + +inline std::ostream &operator<<(std::ostream &stream, const Dict &dict) +{ + Dict::_Dict::const_iterator it; + for (it = dict.dict.begin(); it != dict.dict.end(); it++) + stream << it->first << " : " << it->second << "\n"; + + return stream; +} + +inline std::map::const_iterator Dict::begin() const +{ + return dict.begin(); +} + +inline std::map::const_iterator Dict::end() const +{ + return dict.end(); +} + +CV__DNN_EXPERIMENTAL_NS_END +} +} + +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/layer.details.hpp b/3rdparty/opencv/include/opencv2/dnn/layer.details.hpp new file mode 100644 index 00000000..619514e8 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/layer.details.hpp @@ -0,0 +1,78 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +#ifndef OPENCV_DNN_LAYER_DETAILS_HPP +#define OPENCV_DNN_LAYER_DETAILS_HPP + +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN + +/** @brief Registers layer constructor in runtime. +* @param type string, containing type name of the layer. +* @param constructorFunc pointer to the function of type LayerRegister::Constructor, which creates the layer. +* @details This macros must be placed inside the function code. +*/ +#define CV_DNN_REGISTER_LAYER_FUNC(type, constructorFunc) \ + cv::dnn::LayerFactory::registerLayer(#type, constructorFunc); + +/** @brief Registers layer class in runtime. + * @param type string, containing type name of the layer. + * @param class C++ class, derived from Layer. + * @details This macros must be placed inside the function code. + */ +#define CV_DNN_REGISTER_LAYER_CLASS(type, class) \ + cv::dnn::LayerFactory::registerLayer(#type, cv::dnn::details::_layerDynamicRegisterer); + +/** @brief Registers layer constructor on module load time. +* @param type string, containing type name of the layer. +* @param constructorFunc pointer to the function of type LayerRegister::Constructor, which creates the layer. +* @details This macros must be placed outside the function code. +*/ +#define CV_DNN_REGISTER_LAYER_FUNC_STATIC(type, constructorFunc) \ +static cv::dnn::details::_LayerStaticRegisterer __LayerStaticRegisterer_##type(#type, constructorFunc); + +/** @brief Registers layer class on module load time. + * @param type string, containing type name of the layer. + * @param class C++ class, derived from Layer. + * @details This macros must be placed outside the function code. + */ +#define CV_DNN_REGISTER_LAYER_CLASS_STATIC(type, class) \ +Ptr __LayerStaticRegisterer_func_##type(LayerParams ¶ms) \ + { return Ptr(new class(params)); } \ +static cv::dnn::details::_LayerStaticRegisterer __LayerStaticRegisterer_##type(#type, __LayerStaticRegisterer_func_##type); + +namespace details { + +template +Ptr _layerDynamicRegisterer(LayerParams ¶ms) +{ + return Ptr(LayerClass::create(params)); +} + +//allows automatically register created layer on module load time +class _LayerStaticRegisterer +{ + String type; +public: + + _LayerStaticRegisterer(const String &layerType, LayerFactory::Constructor layerConstructor) + { + this->type = layerType; + LayerFactory::registerLayer(layerType, layerConstructor); + } + + ~_LayerStaticRegisterer() + { + LayerFactory::unregisterLayer(type); + } +}; + +} // namespace +CV__DNN_EXPERIMENTAL_NS_END +}} // namespace + +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/layer.hpp b/3rdparty/opencv/include/opencv2/dnn/layer.hpp new file mode 100644 index 00000000..c4712b8e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/layer.hpp @@ -0,0 +1,85 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_LAYER_HPP +#define OPENCV_DNN_LAYER_HPP +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN +//! @addtogroup dnn +//! @{ +//! +//! @defgroup dnnLayerFactory Utilities for New Layers Registration +//! @{ + +/** @brief %Layer factory allows to create instances of registered layers. */ +class CV_EXPORTS LayerFactory +{ +public: + + //! Each Layer class must provide this function to the factory + typedef Ptr(*Constructor)(LayerParams ¶ms); + + //! Registers the layer class with typename @p type and specified @p constructor. Thread-safe. + static void registerLayer(const String &type, Constructor constructor); + + //! Unregisters registered layer with specified type name. Thread-safe. + static void unregisterLayer(const String &type); + + /** @brief Creates instance of registered layer. + * @param type type name of creating layer. + * @param params parameters which will be used for layer initialization. + * @note Thread-safe. + */ + static Ptr createLayerInstance(const String &type, LayerParams& params); + +private: + LayerFactory(); +}; + +//! @} +//! @} +CV__DNN_EXPERIMENTAL_NS_END +} +} +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/shape_utils.hpp b/3rdparty/opencv/include/opencv2/dnn/shape_utils.hpp new file mode 100644 index 00000000..b0ed3afc --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/shape_utils.hpp @@ -0,0 +1,219 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_DNN_DNN_SHAPE_UTILS_HPP +#define OPENCV_DNN_DNN_SHAPE_UTILS_HPP + +#include +#include // CV_MAX_DIM +#include +#include +#include + +namespace cv { +namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN + +//Slicing + +struct _Range : public cv::Range +{ + _Range(const Range &r) : cv::Range(r) {} + _Range(int start_, int size_ = 1) : cv::Range(start_, start_ + size_) {} +}; + +static inline Mat slice(const Mat &m, const _Range &r0) +{ + Range ranges[CV_MAX_DIM]; + for (int i = 1; i < m.dims; i++) + ranges[i] = Range::all(); + ranges[0] = r0; + return m(&ranges[0]); +} + +static inline Mat slice(const Mat &m, const _Range &r0, const _Range &r1) +{ + CV_Assert(m.dims >= 2); + Range ranges[CV_MAX_DIM]; + for (int i = 2; i < m.dims; i++) + ranges[i] = Range::all(); + ranges[0] = r0; + ranges[1] = r1; + return m(&ranges[0]); +} + +static inline Mat slice(const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2) +{ + CV_Assert(m.dims >= 3); + Range ranges[CV_MAX_DIM]; + for (int i = 3; i < m.dims; i++) + ranges[i] = Range::all(); + ranges[0] = r0; + ranges[1] = r1; + ranges[2] = r2; + return m(&ranges[0]); +} + +static inline Mat slice(const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2, const _Range &r3) +{ + CV_Assert(m.dims >= 4); + Range ranges[CV_MAX_DIM]; + for (int i = 4; i < m.dims; i++) + ranges[i] = Range::all(); + ranges[0] = r0; + ranges[1] = r1; + ranges[2] = r2; + ranges[3] = r3; + return m(&ranges[0]); +} + +static inline Mat getPlane(const Mat &m, int n, int cn) +{ + CV_Assert(m.dims > 2); + int sz[CV_MAX_DIM]; + for(int i = 2; i < m.dims; i++) + { + sz[i-2] = m.size.p[i]; + } + return Mat(m.dims - 2, sz, m.type(), (void*)m.ptr(n, cn)); +} + +static inline MatShape shape(const int* dims, const int n) +{ + MatShape shape; + shape.assign(dims, dims + n); + return shape; +} + +static inline MatShape shape(const Mat& mat) +{ + return shape(mat.size.p, mat.dims); +} + +static inline MatShape shape(const MatSize& sz) +{ + return shape(sz.p, sz.dims()); +} + +static inline MatShape shape(const UMat& mat) +{ + return shape(mat.size.p, mat.dims); +} + +namespace {inline bool is_neg(int i) { return i < 0; }} + +static inline MatShape shape(int a0, int a1=-1, int a2=-1, int a3=-1) +{ + int dims[] = {a0, a1, a2, a3}; + MatShape s = shape(dims, 4); + s.erase(std::remove_if(s.begin(), s.end(), is_neg), s.end()); + return s; +} + +static inline int total(const MatShape& shape, int start = -1, int end = -1) +{ + if (start == -1) start = 0; + if (end == -1) end = (int)shape.size(); + + if (shape.empty()) + return 0; + + int elems = 1; + CV_Assert(start <= (int)shape.size() && end <= (int)shape.size() && + start <= end); + for(int i = start; i < end; i++) + { + elems *= shape[i]; + } + return elems; +} + +static inline MatShape concat(const MatShape& a, const MatShape& b) +{ + MatShape c = a; + c.insert(c.end(), b.begin(), b.end()); + + return c; +} + +static inline std::string toString(const MatShape& shape, const String& name = "") +{ + std::ostringstream ss; + if (!name.empty()) + ss << name << ' '; + ss << '['; + for(size_t i = 0, n = shape.size(); i < n; ++i) + ss << ' ' << shape[i]; + ss << " ]"; + return ss.str(); +} +static inline void print(const MatShape& shape, const String& name = "") +{ + std::cout << toString(shape, name) << std::endl; +} +static inline std::ostream& operator<<(std::ostream &out, const MatShape& shape) +{ + out << toString(shape); + return out; +} + +inline int clamp(int ax, int dims) +{ + return ax < 0 ? ax + dims : ax; +} + +inline int clamp(int ax, const MatShape& shape) +{ + return clamp(ax, (int)shape.size()); +} + +inline Range clamp(const Range& r, int axisSize) +{ + Range clamped(std::max(r.start, 0), + r.end > 0 ? std::min(r.end, axisSize) : axisSize + r.end + 1); + CV_Assert_N(clamped.start < clamped.end, clamped.end <= axisSize); + return clamped; +} + +CV__DNN_EXPERIMENTAL_NS_END +} +} +#endif diff --git a/3rdparty/opencv/include/opencv2/dnn/utils/inference_engine.hpp b/3rdparty/opencv/include/opencv2/dnn/utils/inference_engine.hpp new file mode 100644 index 00000000..0211096a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/dnn/utils/inference_engine.hpp @@ -0,0 +1,43 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. +// +// Copyright (C) 2018-2019, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. + +#ifndef OPENCV_DNN_UTILS_INF_ENGINE_HPP +#define OPENCV_DNN_UTILS_INF_ENGINE_HPP + +#include "../dnn.hpp" + +namespace cv { namespace dnn { +CV__DNN_EXPERIMENTAL_NS_BEGIN + + +/** @brief Release a Myriad device (binded by OpenCV). + * + * Single Myriad device cannot be shared across multiple processes which uses + * Inference Engine's Myriad plugin. + */ +CV_EXPORTS_W void resetMyriadDevice(); + + +/* Values for 'OPENCV_DNN_IE_VPU_TYPE' parameter */ +#define CV_DNN_INFERENCE_ENGINE_VPU_TYPE_UNSPECIFIED "" +/// Intel(R) Movidius(TM) Neural Compute Stick, NCS (USB 03e7:2150), Myriad2 (https://software.intel.com/en-us/movidius-ncs) +#define CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_2 "Myriad2" +/// Intel(R) Neural Compute Stick 2, NCS2 (USB 03e7:2485), MyriadX (https://software.intel.com/ru-ru/neural-compute-stick) +#define CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X "MyriadX" + + +/** @brief Returns Inference Engine VPU type. + * + * See values of `CV_DNN_INFERENCE_ENGINE_VPU_TYPE_*` macros. + */ +CV_EXPORTS_W cv::String getInferenceEngineVPUType(); + + +CV__DNN_EXPERIMENTAL_NS_END +}} // namespace + +#endif // OPENCV_DNN_UTILS_INF_ENGINE_HPP diff --git a/3rdparty/opencv/include/opencv2/features2d.hpp b/3rdparty/opencv/include/opencv2/features2d.hpp new file mode 100644 index 00000000..ee81ebe3 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/features2d.hpp @@ -0,0 +1,1428 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_FEATURES_2D_HPP +#define OPENCV_FEATURES_2D_HPP + +#include "opencv2/opencv_modules.hpp" +#include "opencv2/core.hpp" + +#ifdef HAVE_OPENCV_FLANN +#include "opencv2/flann/miniflann.hpp" +#endif + +/** + @defgroup features2d 2D Features Framework + @{ + @defgroup features2d_main Feature Detection and Description + @defgroup features2d_match Descriptor Matchers + +Matchers of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to +easily switch between different algorithms solving the same problem. This section is devoted to +matching descriptors that are represented as vectors in a multidimensional space. All objects that +implement vector descriptor matchers inherit the DescriptorMatcher interface. + +@note + - An example explaining keypoint matching can be found at + opencv_source_code/samples/cpp/descriptor_extractor_matcher.cpp + - An example on descriptor matching evaluation can be found at + opencv_source_code/samples/cpp/detector_descriptor_matcher_evaluation.cpp + - An example on one to many image matching can be found at + opencv_source_code/samples/cpp/matching_to_many_images.cpp + + @defgroup features2d_draw Drawing Function of Keypoints and Matches + @defgroup features2d_category Object Categorization + +This section describes approaches based on local 2D features and used to categorize objects. + +@note + - A complete Bag-Of-Words sample can be found at + opencv_source_code/samples/cpp/bagofwords_classification.cpp + - (Python) An example using the features2D framework to perform object categorization can be + found at opencv_source_code/samples/python/find_obj.py + + @} + */ + +namespace cv +{ + +//! @addtogroup features2d +//! @{ + +// //! writes vector of keypoints to the file storage +// CV_EXPORTS void write(FileStorage& fs, const String& name, const std::vector& keypoints); +// //! reads vector of keypoints from the specified file storage node +// CV_EXPORTS void read(const FileNode& node, CV_OUT std::vector& keypoints); + +/** @brief A class filters a vector of keypoints. + + Because now it is difficult to provide a convenient interface for all usage scenarios of the + keypoints filter class, it has only several needed by now static methods. + */ +class CV_EXPORTS KeyPointsFilter +{ +public: + KeyPointsFilter(){} + + /* + * Remove keypoints within borderPixels of an image edge. + */ + static void runByImageBorder( std::vector& keypoints, Size imageSize, int borderSize ); + /* + * Remove keypoints of sizes out of range. + */ + static void runByKeypointSize( std::vector& keypoints, float minSize, + float maxSize=FLT_MAX ); + /* + * Remove keypoints from some image by mask for pixels of this image. + */ + static void runByPixelsMask( std::vector& keypoints, const Mat& mask ); + /* + * Remove duplicated keypoints. + */ + static void removeDuplicated( std::vector& keypoints ); + /* + * Remove duplicated keypoints and sort the remaining keypoints + */ + static void removeDuplicatedSorted( std::vector& keypoints ); + + /* + * Retain the specified number of the best keypoints (according to the response) + */ + static void retainBest( std::vector& keypoints, int npoints ); +}; + + +/************************************ Base Classes ************************************/ + +/** @brief Abstract base class for 2D image feature detectors and descriptor extractors +*/ +#ifdef __EMSCRIPTEN__ +class CV_EXPORTS_W Feature2D : public Algorithm +#else +class CV_EXPORTS_W Feature2D : public virtual Algorithm +#endif +{ +public: + virtual ~Feature2D(); + + /** @brief Detects keypoints in an image (first variant) or image set (second variant). + + @param image Image. + @param keypoints The detected keypoints. In the second variant of the method keypoints[i] is a set + of keypoints detected in images[i] . + @param mask Mask specifying where to look for keypoints (optional). It must be a 8-bit integer + matrix with non-zero values in the region of interest. + */ + CV_WRAP virtual void detect( InputArray image, + CV_OUT std::vector& keypoints, + InputArray mask=noArray() ); + + /** @overload + @param images Image set. + @param keypoints The detected keypoints. In the second variant of the method keypoints[i] is a set + of keypoints detected in images[i] . + @param masks Masks for each input image specifying where to look for keypoints (optional). + masks[i] is a mask for images[i]. + */ + CV_WRAP virtual void detect( InputArrayOfArrays images, + CV_OUT std::vector >& keypoints, + InputArrayOfArrays masks=noArray() ); + + /** @brief Computes the descriptors for a set of keypoints detected in an image (first variant) or image set + (second variant). + + @param image Image. + @param keypoints Input collection of keypoints. Keypoints for which a descriptor cannot be + computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint + with several dominant orientations (for each orientation). + @param descriptors Computed descriptors. In the second variant of the method descriptors[i] are + descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the + descriptor for keypoint j-th keypoint. + */ + CV_WRAP virtual void compute( InputArray image, + CV_OUT CV_IN_OUT std::vector& keypoints, + OutputArray descriptors ); + + /** @overload + + @param images Image set. + @param keypoints Input collection of keypoints. Keypoints for which a descriptor cannot be + computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint + with several dominant orientations (for each orientation). + @param descriptors Computed descriptors. In the second variant of the method descriptors[i] are + descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the + descriptor for keypoint j-th keypoint. + */ + CV_WRAP virtual void compute( InputArrayOfArrays images, + CV_OUT CV_IN_OUT std::vector >& keypoints, + OutputArrayOfArrays descriptors ); + + /** Detects keypoints and computes the descriptors */ + CV_WRAP virtual void detectAndCompute( InputArray image, InputArray mask, + CV_OUT std::vector& keypoints, + OutputArray descriptors, + bool useProvidedKeypoints=false ); + + CV_WRAP virtual int descriptorSize() const; + CV_WRAP virtual int descriptorType() const; + CV_WRAP virtual int defaultNorm() const; + + CV_WRAP void write( const String& fileName ) const; + + CV_WRAP void read( const String& fileName ); + + virtual void write( FileStorage&) const CV_OVERRIDE; + + // see corresponding cv::Algorithm method + CV_WRAP virtual void read( const FileNode&) CV_OVERRIDE; + + //! Return true if detector object is empty + CV_WRAP virtual bool empty() const CV_OVERRIDE; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; + + // see corresponding cv::Algorithm method + CV_WRAP inline void write(const Ptr& fs, const String& name = String()) const { Algorithm::write(fs, name); } +}; + +/** Feature detectors in OpenCV have wrappers with a common interface that enables you to easily switch +between different algorithms solving the same problem. All objects that implement keypoint detectors +inherit the FeatureDetector interface. */ +typedef Feature2D FeatureDetector; + +/** Extractors of keypoint descriptors in OpenCV have wrappers with a common interface that enables you +to easily switch between different algorithms solving the same problem. This section is devoted to +computing descriptors represented as vectors in a multidimensional space. All objects that implement +the vector descriptor extractors inherit the DescriptorExtractor interface. + */ +typedef Feature2D DescriptorExtractor; + +//! @addtogroup features2d_main +//! @{ + +/** @brief Class implementing the BRISK keypoint detector and descriptor extractor, described in @cite LCS11 . + */ +class CV_EXPORTS_W BRISK : public Feature2D +{ +public: + /** @brief The BRISK constructor + + @param thresh AGAST detection threshold score. + @param octaves detection octaves. Use 0 to do single scale. + @param patternScale apply this scale to the pattern used for sampling the neighbourhood of a + keypoint. + */ + CV_WRAP static Ptr create(int thresh=30, int octaves=3, float patternScale=1.0f); + + /** @brief The BRISK constructor for a custom pattern + + @param radiusList defines the radii (in pixels) where the samples around a keypoint are taken (for + keypoint scale 1). + @param numberList defines the number of sampling points on the sampling circle. Must be the same + size as radiusList.. + @param dMax threshold for the short pairings used for descriptor formation (in pixels for keypoint + scale 1). + @param dMin threshold for the long pairings used for orientation determination (in pixels for + keypoint scale 1). + @param indexChange index remapping of the bits. */ + CV_WRAP static Ptr create(const std::vector &radiusList, const std::vector &numberList, + float dMax=5.85f, float dMin=8.2f, const std::vector& indexChange=std::vector()); + + /** @brief The BRISK constructor for a custom pattern, detection threshold and octaves + + @param thresh AGAST detection threshold score. + @param octaves detection octaves. Use 0 to do single scale. + @param radiusList defines the radii (in pixels) where the samples around a keypoint are taken (for + keypoint scale 1). + @param numberList defines the number of sampling points on the sampling circle. Must be the same + size as radiusList.. + @param dMax threshold for the short pairings used for descriptor formation (in pixels for keypoint + scale 1). + @param dMin threshold for the long pairings used for orientation determination (in pixels for + keypoint scale 1). + @param indexChange index remapping of the bits. */ + CV_WRAP static Ptr create(int thresh, int octaves, const std::vector &radiusList, + const std::vector &numberList, float dMax=5.85f, float dMin=8.2f, + const std::vector& indexChange=std::vector()); + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @brief Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor + +described in @cite RRKB11 . The algorithm uses FAST in pyramids to detect stable keypoints, selects +the strongest features using FAST or Harris response, finds their orientation using first-order +moments and computes the descriptors using BRIEF (where the coordinates of random point pairs (or +k-tuples) are rotated according to the measured orientation). + */ +class CV_EXPORTS_W ORB : public Feature2D +{ +public: + enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 }; + + /** @brief The ORB constructor + + @param nfeatures The maximum number of features to retain. + @param scaleFactor Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical + pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor + will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor + will mean that to cover certain scale range you will need more pyramid levels and so the speed + will suffer. + @param nlevels The number of pyramid levels. The smallest level will have linear size equal to + input_image_linear_size/pow(scaleFactor, nlevels - firstLevel). + @param edgeThreshold This is size of the border where the features are not detected. It should + roughly match the patchSize parameter. + @param firstLevel The level of pyramid to put source image to. Previous layers are filled + with upscaled source image. + @param WTA_K The number of points that produce each element of the oriented BRIEF descriptor. The + default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, + so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 + random points (of course, those point coordinates are random, but they are generated from the + pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel + rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such + output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, + denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each + bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3). + @param scoreType The default HARRIS_SCORE means that Harris algorithm is used to rank features + (the score is written to KeyPoint::score and is used to retain best nfeatures features); + FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints, + but it is a little faster to compute. + @param patchSize size of the patch used by the oriented BRIEF descriptor. Of course, on smaller + pyramid layers the perceived image area covered by a feature will be larger. + @param fastThreshold + */ + CV_WRAP static Ptr create(int nfeatures=500, float scaleFactor=1.2f, int nlevels=8, int edgeThreshold=31, + int firstLevel=0, int WTA_K=2, int scoreType=ORB::HARRIS_SCORE, int patchSize=31, int fastThreshold=20); + + CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0; + CV_WRAP virtual int getMaxFeatures() const = 0; + + CV_WRAP virtual void setScaleFactor(double scaleFactor) = 0; + CV_WRAP virtual double getScaleFactor() const = 0; + + CV_WRAP virtual void setNLevels(int nlevels) = 0; + CV_WRAP virtual int getNLevels() const = 0; + + CV_WRAP virtual void setEdgeThreshold(int edgeThreshold) = 0; + CV_WRAP virtual int getEdgeThreshold() const = 0; + + CV_WRAP virtual void setFirstLevel(int firstLevel) = 0; + CV_WRAP virtual int getFirstLevel() const = 0; + + CV_WRAP virtual void setWTA_K(int wta_k) = 0; + CV_WRAP virtual int getWTA_K() const = 0; + + CV_WRAP virtual void setScoreType(int scoreType) = 0; + CV_WRAP virtual int getScoreType() const = 0; + + CV_WRAP virtual void setPatchSize(int patchSize) = 0; + CV_WRAP virtual int getPatchSize() const = 0; + + CV_WRAP virtual void setFastThreshold(int fastThreshold) = 0; + CV_WRAP virtual int getFastThreshold() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @brief Maximally stable extremal region extractor + +The class encapsulates all the parameters of the %MSER extraction algorithm (see [wiki +article](http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions)). + +- there are two different implementation of %MSER: one for grey image, one for color image + +- the grey image algorithm is taken from: @cite nister2008linear ; the paper claims to be faster +than union-find method; it actually get 1.5~2m/s on my centrino L7200 1.2GHz laptop. + +- the color image algorithm is taken from: @cite forssen2007maximally ; it should be much slower +than grey image method ( 3~4 times ); the chi_table.h file is taken directly from paper's source +code which is distributed under GPL. + +- (Python) A complete example showing the use of the %MSER detector can be found at samples/python/mser.py +*/ +class CV_EXPORTS_W MSER : public Feature2D +{ +public: + /** @brief Full consturctor for %MSER detector + + @param _delta it compares \f$(size_{i}-size_{i-delta})/size_{i-delta}\f$ + @param _min_area prune the area which smaller than minArea + @param _max_area prune the area which bigger than maxArea + @param _max_variation prune the area have similar size to its children + @param _min_diversity for color image, trace back to cut off mser with diversity less than min_diversity + @param _max_evolution for color image, the evolution steps + @param _area_threshold for color image, the area threshold to cause re-initialize + @param _min_margin for color image, ignore too small margin + @param _edge_blur_size for color image, the aperture size for edge blur + */ + CV_WRAP static Ptr create( int _delta=5, int _min_area=60, int _max_area=14400, + double _max_variation=0.25, double _min_diversity=.2, + int _max_evolution=200, double _area_threshold=1.01, + double _min_margin=0.003, int _edge_blur_size=5 ); + + /** @brief Detect %MSER regions + + @param image input image (8UC1, 8UC3 or 8UC4, must be greater or equal than 3x3) + @param msers resulting list of point sets + @param bboxes resulting bounding boxes + */ + CV_WRAP virtual void detectRegions( InputArray image, + CV_OUT std::vector >& msers, + CV_OUT std::vector& bboxes ) = 0; + + CV_WRAP virtual void setDelta(int delta) = 0; + CV_WRAP virtual int getDelta() const = 0; + + CV_WRAP virtual void setMinArea(int minArea) = 0; + CV_WRAP virtual int getMinArea() const = 0; + + CV_WRAP virtual void setMaxArea(int maxArea) = 0; + CV_WRAP virtual int getMaxArea() const = 0; + + CV_WRAP virtual void setPass2Only(bool f) = 0; + CV_WRAP virtual bool getPass2Only() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @overload */ +CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector& keypoints, + int threshold, bool nonmaxSuppression=true ); + +/** @brief Detects corners using the FAST algorithm + +@param image grayscale image where keypoints (corners) are detected. +@param keypoints keypoints detected on the image. +@param threshold threshold on difference between intensity of the central pixel and pixels of a +circle around this pixel. +@param nonmaxSuppression if true, non-maximum suppression is applied to detected corners +(keypoints). +@param type one of the three neighborhoods as defined in the paper: +FastFeatureDetector::TYPE_9_16, FastFeatureDetector::TYPE_7_12, +FastFeatureDetector::TYPE_5_8 + +Detects corners using the FAST algorithm by @cite Rosten06 . + +@note In Python API, types are given as cv2.FAST_FEATURE_DETECTOR_TYPE_5_8, +cv2.FAST_FEATURE_DETECTOR_TYPE_7_12 and cv2.FAST_FEATURE_DETECTOR_TYPE_9_16. For corner +detection, use cv2.FAST.detect() method. + */ +CV_EXPORTS void FAST( InputArray image, CV_OUT std::vector& keypoints, + int threshold, bool nonmaxSuppression, int type ); + +//! @} features2d_main + +//! @addtogroup features2d_main +//! @{ + +/** @brief Wrapping class for feature detection using the FAST method. : + */ +class CV_EXPORTS_W FastFeatureDetector : public Feature2D +{ +public: + enum + { + TYPE_5_8 = 0, TYPE_7_12 = 1, TYPE_9_16 = 2, + THRESHOLD = 10000, NONMAX_SUPPRESSION=10001, FAST_N=10002, + }; + + CV_WRAP static Ptr create( int threshold=10, + bool nonmaxSuppression=true, + int type=FastFeatureDetector::TYPE_9_16 ); + + CV_WRAP virtual void setThreshold(int threshold) = 0; + CV_WRAP virtual int getThreshold() const = 0; + + CV_WRAP virtual void setNonmaxSuppression(bool f) = 0; + CV_WRAP virtual bool getNonmaxSuppression() const = 0; + + CV_WRAP virtual void setType(int type) = 0; + CV_WRAP virtual int getType() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @overload */ +CV_EXPORTS void AGAST( InputArray image, CV_OUT std::vector& keypoints, + int threshold, bool nonmaxSuppression=true ); + +/** @brief Detects corners using the AGAST algorithm + +@param image grayscale image where keypoints (corners) are detected. +@param keypoints keypoints detected on the image. +@param threshold threshold on difference between intensity of the central pixel and pixels of a +circle around this pixel. +@param nonmaxSuppression if true, non-maximum suppression is applied to detected corners +(keypoints). +@param type one of the four neighborhoods as defined in the paper: +AgastFeatureDetector::AGAST_5_8, AgastFeatureDetector::AGAST_7_12d, +AgastFeatureDetector::AGAST_7_12s, AgastFeatureDetector::OAST_9_16 + +For non-Intel platforms, there is a tree optimised variant of AGAST with same numerical results. +The 32-bit binary tree tables were generated automatically from original code using perl script. +The perl script and examples of tree generation are placed in features2d/doc folder. +Detects corners using the AGAST algorithm by @cite mair2010_agast . + + */ +CV_EXPORTS void AGAST( InputArray image, CV_OUT std::vector& keypoints, + int threshold, bool nonmaxSuppression, int type ); +//! @} features2d_main + +//! @addtogroup features2d_main +//! @{ + +/** @brief Wrapping class for feature detection using the AGAST method. : + */ +class CV_EXPORTS_W AgastFeatureDetector : public Feature2D +{ +public: + enum + { + AGAST_5_8 = 0, AGAST_7_12d = 1, AGAST_7_12s = 2, OAST_9_16 = 3, + THRESHOLD = 10000, NONMAX_SUPPRESSION = 10001, + }; + + CV_WRAP static Ptr create( int threshold=10, + bool nonmaxSuppression=true, + int type=AgastFeatureDetector::OAST_9_16 ); + + CV_WRAP virtual void setThreshold(int threshold) = 0; + CV_WRAP virtual int getThreshold() const = 0; + + CV_WRAP virtual void setNonmaxSuppression(bool f) = 0; + CV_WRAP virtual bool getNonmaxSuppression() const = 0; + + CV_WRAP virtual void setType(int type) = 0; + CV_WRAP virtual int getType() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @brief Wrapping class for feature detection using the goodFeaturesToTrack function. : + */ +class CV_EXPORTS_W GFTTDetector : public Feature2D +{ +public: + CV_WRAP static Ptr create( int maxCorners=1000, double qualityLevel=0.01, double minDistance=1, + int blockSize=3, bool useHarrisDetector=false, double k=0.04 ); + CV_WRAP static Ptr create( int maxCorners, double qualityLevel, double minDistance, + int blockSize, int gradiantSize, bool useHarrisDetector=false, double k=0.04 ); + CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0; + CV_WRAP virtual int getMaxFeatures() const = 0; + + CV_WRAP virtual void setQualityLevel(double qlevel) = 0; + CV_WRAP virtual double getQualityLevel() const = 0; + + CV_WRAP virtual void setMinDistance(double minDistance) = 0; + CV_WRAP virtual double getMinDistance() const = 0; + + CV_WRAP virtual void setBlockSize(int blockSize) = 0; + CV_WRAP virtual int getBlockSize() const = 0; + + CV_WRAP virtual void setHarrisDetector(bool val) = 0; + CV_WRAP virtual bool getHarrisDetector() const = 0; + + CV_WRAP virtual void setK(double k) = 0; + CV_WRAP virtual double getK() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @brief Class for extracting blobs from an image. : + +The class implements a simple algorithm for extracting blobs from an image: + +1. Convert the source image to binary images by applying thresholding with several thresholds from + minThreshold (inclusive) to maxThreshold (exclusive) with distance thresholdStep between + neighboring thresholds. +2. Extract connected components from every binary image by findContours and calculate their + centers. +3. Group centers from several binary images by their coordinates. Close centers form one group that + corresponds to one blob, which is controlled by the minDistBetweenBlobs parameter. +4. From the groups, estimate final centers of blobs and their radiuses and return as locations and + sizes of keypoints. + +This class performs several filtrations of returned blobs. You should set filterBy\* to true/false +to turn on/off corresponding filtration. Available filtrations: + +- **By color**. This filter compares the intensity of a binary image at the center of a blob to +blobColor. If they differ, the blob is filtered out. Use blobColor = 0 to extract dark blobs +and blobColor = 255 to extract light blobs. +- **By area**. Extracted blobs have an area between minArea (inclusive) and maxArea (exclusive). +- **By circularity**. Extracted blobs have circularity +(\f$\frac{4*\pi*Area}{perimeter * perimeter}\f$) between minCircularity (inclusive) and +maxCircularity (exclusive). +- **By ratio of the minimum inertia to maximum inertia**. Extracted blobs have this ratio +between minInertiaRatio (inclusive) and maxInertiaRatio (exclusive). +- **By convexity**. Extracted blobs have convexity (area / area of blob convex hull) between +minConvexity (inclusive) and maxConvexity (exclusive). + +Default values of parameters are tuned to extract dark circular blobs. + */ +class CV_EXPORTS_W SimpleBlobDetector : public Feature2D +{ +public: + struct CV_EXPORTS_W_SIMPLE Params + { + CV_WRAP Params(); + CV_PROP_RW float thresholdStep; + CV_PROP_RW float minThreshold; + CV_PROP_RW float maxThreshold; + CV_PROP_RW size_t minRepeatability; + CV_PROP_RW float minDistBetweenBlobs; + + CV_PROP_RW bool filterByColor; + CV_PROP_RW uchar blobColor; + + CV_PROP_RW bool filterByArea; + CV_PROP_RW float minArea, maxArea; + + CV_PROP_RW bool filterByCircularity; + CV_PROP_RW float minCircularity, maxCircularity; + + CV_PROP_RW bool filterByInertia; + CV_PROP_RW float minInertiaRatio, maxInertiaRatio; + + CV_PROP_RW bool filterByConvexity; + CV_PROP_RW float minConvexity, maxConvexity; + + void read( const FileNode& fn ); + void write( FileStorage& fs ) const; + }; + + CV_WRAP static Ptr + create(const SimpleBlobDetector::Params ¶meters = SimpleBlobDetector::Params()); + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +//! @} features2d_main + +//! @addtogroup features2d_main +//! @{ + +/** @brief Class implementing the KAZE keypoint detector and descriptor extractor, described in @cite ABD12 . + +@note AKAZE descriptor can only be used with KAZE or AKAZE keypoints .. [ABD12] KAZE Features. Pablo +F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. In European Conference on Computer Vision +(ECCV), Fiorenze, Italy, October 2012. +*/ +class CV_EXPORTS_W KAZE : public Feature2D +{ +public: + enum + { + DIFF_PM_G1 = 0, + DIFF_PM_G2 = 1, + DIFF_WEICKERT = 2, + DIFF_CHARBONNIER = 3 + }; + + /** @brief The KAZE constructor + + @param extended Set to enable extraction of extended (128-byte) descriptor. + @param upright Set to enable use of upright descriptors (non rotation-invariant). + @param threshold Detector response threshold to accept point + @param nOctaves Maximum octave evolution of the image + @param nOctaveLayers Default number of sublevels per scale level + @param diffusivity Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or + DIFF_CHARBONNIER + */ + CV_WRAP static Ptr create(bool extended=false, bool upright=false, + float threshold = 0.001f, + int nOctaves = 4, int nOctaveLayers = 4, + int diffusivity = KAZE::DIFF_PM_G2); + + CV_WRAP virtual void setExtended(bool extended) = 0; + CV_WRAP virtual bool getExtended() const = 0; + + CV_WRAP virtual void setUpright(bool upright) = 0; + CV_WRAP virtual bool getUpright() const = 0; + + CV_WRAP virtual void setThreshold(double threshold) = 0; + CV_WRAP virtual double getThreshold() const = 0; + + CV_WRAP virtual void setNOctaves(int octaves) = 0; + CV_WRAP virtual int getNOctaves() const = 0; + + CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0; + CV_WRAP virtual int getNOctaveLayers() const = 0; + + CV_WRAP virtual void setDiffusivity(int diff) = 0; + CV_WRAP virtual int getDiffusivity() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +/** @brief Class implementing the AKAZE keypoint detector and descriptor extractor, described in @cite ANB13. + +@details AKAZE descriptors can only be used with KAZE or AKAZE keypoints. This class is thread-safe. + +@note When you need descriptors use Feature2D::detectAndCompute, which +provides better performance. When using Feature2D::detect followed by +Feature2D::compute scale space pyramid is computed twice. + +@note AKAZE implements T-API. When image is passed as UMat some parts of the algorithm +will use OpenCL. + +@note [ANB13] Fast Explicit Diffusion for Accelerated Features in Nonlinear +Scale Spaces. Pablo F. Alcantarilla, Jesús Nuevo and Adrien Bartoli. In +British Machine Vision Conference (BMVC), Bristol, UK, September 2013. + +*/ +class CV_EXPORTS_W AKAZE : public Feature2D +{ +public: + // AKAZE descriptor type + enum + { + DESCRIPTOR_KAZE_UPRIGHT = 2, ///< Upright descriptors, not invariant to rotation + DESCRIPTOR_KAZE = 3, + DESCRIPTOR_MLDB_UPRIGHT = 4, ///< Upright descriptors, not invariant to rotation + DESCRIPTOR_MLDB = 5 + }; + + /** @brief The AKAZE constructor + + @param descriptor_type Type of the extracted descriptor: DESCRIPTOR_KAZE, + DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT. + @param descriptor_size Size of the descriptor in bits. 0 -\> Full size + @param descriptor_channels Number of channels in the descriptor (1, 2, 3) + @param threshold Detector response threshold to accept point + @param nOctaves Maximum octave evolution of the image + @param nOctaveLayers Default number of sublevels per scale level + @param diffusivity Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or + DIFF_CHARBONNIER + */ + CV_WRAP static Ptr create(int descriptor_type=AKAZE::DESCRIPTOR_MLDB, + int descriptor_size = 0, int descriptor_channels = 3, + float threshold = 0.001f, int nOctaves = 4, + int nOctaveLayers = 4, int diffusivity = KAZE::DIFF_PM_G2); + + CV_WRAP virtual void setDescriptorType(int dtype) = 0; + CV_WRAP virtual int getDescriptorType() const = 0; + + CV_WRAP virtual void setDescriptorSize(int dsize) = 0; + CV_WRAP virtual int getDescriptorSize() const = 0; + + CV_WRAP virtual void setDescriptorChannels(int dch) = 0; + CV_WRAP virtual int getDescriptorChannels() const = 0; + + CV_WRAP virtual void setThreshold(double threshold) = 0; + CV_WRAP virtual double getThreshold() const = 0; + + CV_WRAP virtual void setNOctaves(int octaves) = 0; + CV_WRAP virtual int getNOctaves() const = 0; + + CV_WRAP virtual void setNOctaveLayers(int octaveLayers) = 0; + CV_WRAP virtual int getNOctaveLayers() const = 0; + + CV_WRAP virtual void setDiffusivity(int diff) = 0; + CV_WRAP virtual int getDiffusivity() const = 0; + CV_WRAP virtual String getDefaultName() const CV_OVERRIDE; +}; + +//! @} features2d_main + +/****************************************************************************************\ +* Distance * +\****************************************************************************************/ + +template +struct CV_EXPORTS Accumulator +{ + typedef T Type; +}; + +template<> struct Accumulator { typedef float Type; }; +template<> struct Accumulator { typedef float Type; }; +template<> struct Accumulator { typedef float Type; }; +template<> struct Accumulator { typedef float Type; }; + +/* + * Squared Euclidean distance functor + */ +template +struct CV_EXPORTS SL2 +{ + enum { normType = NORM_L2SQR }; + typedef T ValueType; + typedef typename Accumulator::Type ResultType; + + ResultType operator()( const T* a, const T* b, int size ) const + { + return normL2Sqr(a, b, size); + } +}; + +/* + * Euclidean distance functor + */ +template +struct L2 +{ + enum { normType = NORM_L2 }; + typedef T ValueType; + typedef typename Accumulator::Type ResultType; + + ResultType operator()( const T* a, const T* b, int size ) const + { + return (ResultType)std::sqrt((double)normL2Sqr(a, b, size)); + } +}; + +/* + * Manhattan distance (city block distance) functor + */ +template +struct L1 +{ + enum { normType = NORM_L1 }; + typedef T ValueType; + typedef typename Accumulator::Type ResultType; + + ResultType operator()( const T* a, const T* b, int size ) const + { + return normL1(a, b, size); + } +}; + +/****************************************************************************************\ +* DescriptorMatcher * +\****************************************************************************************/ + +//! @addtogroup features2d_match +//! @{ + +/** @brief Abstract base class for matching keypoint descriptors. + +It has two groups of match methods: for matching descriptors of an image with another image or with +an image set. + */ +class CV_EXPORTS_W DescriptorMatcher : public Algorithm +{ +public: + enum + { + FLANNBASED = 1, + BRUTEFORCE = 2, + BRUTEFORCE_L1 = 3, + BRUTEFORCE_HAMMING = 4, + BRUTEFORCE_HAMMINGLUT = 5, + BRUTEFORCE_SL2 = 6 + }; + virtual ~DescriptorMatcher(); + + /** @brief Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor + collection. + + If the collection is not empty, the new descriptors are added to existing train descriptors. + + @param descriptors Descriptors to add. Each descriptors[i] is a set of descriptors from the same + train image. + */ + CV_WRAP virtual void add( InputArrayOfArrays descriptors ); + + /** @brief Returns a constant link to the train descriptor collection trainDescCollection . + */ + CV_WRAP const std::vector& getTrainDescriptors() const; + + /** @brief Clears the train descriptor collections. + */ + CV_WRAP virtual void clear() CV_OVERRIDE; + + /** @brief Returns true if there are no train descriptors in the both collections. + */ + CV_WRAP virtual bool empty() const CV_OVERRIDE; + + /** @brief Returns true if the descriptor matcher supports masking permissible matches. + */ + CV_WRAP virtual bool isMaskSupported() const = 0; + + /** @brief Trains a descriptor matcher + + Trains a descriptor matcher (for example, the flann index). In all methods to match, the method + train() is run every time before matching. Some descriptor matchers (for example, BruteForceMatcher) + have an empty implementation of this method. Other matchers really train their inner structures (for + example, FlannBasedMatcher trains flann::Index ). + */ + CV_WRAP virtual void train(); + + /** @brief Finds the best match for each descriptor from a query set. + + @param queryDescriptors Query set of descriptors. + @param trainDescriptors Train set of descriptors. This set is not added to the train descriptors + collection stored in the class object. + @param matches Matches. If a query descriptor is masked out in mask , no match is added for this + descriptor. So, matches size may be smaller than the query descriptors count. + @param mask Mask specifying permissible matches between an input query and train matrices of + descriptors. + + In the first variant of this method, the train descriptors are passed as an input argument. In the + second variant of the method, train descriptors collection that was set by DescriptorMatcher::add is + used. Optional mask (or masks) can be passed to specify which query and training descriptors can be + matched. Namely, queryDescriptors[i] can be matched with trainDescriptors[j] only if + mask.at\(i,j) is non-zero. + */ + CV_WRAP void match( InputArray queryDescriptors, InputArray trainDescriptors, + CV_OUT std::vector& matches, InputArray mask=noArray() ) const; + + /** @brief Finds the k best matches for each descriptor from a query set. + + @param queryDescriptors Query set of descriptors. + @param trainDescriptors Train set of descriptors. This set is not added to the train descriptors + collection stored in the class object. + @param mask Mask specifying permissible matches between an input query and train matrices of + descriptors. + @param matches Matches. Each matches[i] is k or less matches for the same query descriptor. + @param k Count of best matches found per each query descriptor or less if a query descriptor has + less than k possible matches in total. + @param compactResult Parameter used when the mask (or masks) is not empty. If compactResult is + false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, + the matches vector does not contain matches for fully masked-out query descriptors. + + These extended variants of DescriptorMatcher::match methods find several best matches for each query + descriptor. The matches are returned in the distance increasing order. See DescriptorMatcher::match + for the details about query and train descriptors. + */ + CV_WRAP void knnMatch( InputArray queryDescriptors, InputArray trainDescriptors, + CV_OUT std::vector >& matches, int k, + InputArray mask=noArray(), bool compactResult=false ) const; + + /** @brief For each query descriptor, finds the training descriptors not farther than the specified distance. + + @param queryDescriptors Query set of descriptors. + @param trainDescriptors Train set of descriptors. This set is not added to the train descriptors + collection stored in the class object. + @param matches Found matches. + @param compactResult Parameter used when the mask (or masks) is not empty. If compactResult is + false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, + the matches vector does not contain matches for fully masked-out query descriptors. + @param maxDistance Threshold for the distance between matched descriptors. Distance means here + metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured + in Pixels)! + @param mask Mask specifying permissible matches between an input query and train matrices of + descriptors. + + For each query descriptor, the methods find such training descriptors that the distance between the + query descriptor and the training descriptor is equal or smaller than maxDistance. Found matches are + returned in the distance increasing order. + */ + CV_WRAP void radiusMatch( InputArray queryDescriptors, InputArray trainDescriptors, + CV_OUT std::vector >& matches, float maxDistance, + InputArray mask=noArray(), bool compactResult=false ) const; + + /** @overload + @param queryDescriptors Query set of descriptors. + @param matches Matches. If a query descriptor is masked out in mask , no match is added for this + descriptor. So, matches size may be smaller than the query descriptors count. + @param masks Set of masks. Each masks[i] specifies permissible matches between the input query + descriptors and stored train descriptors from the i-th image trainDescCollection[i]. + */ + CV_WRAP void match( InputArray queryDescriptors, CV_OUT std::vector& matches, + InputArrayOfArrays masks=noArray() ); + /** @overload + @param queryDescriptors Query set of descriptors. + @param matches Matches. Each matches[i] is k or less matches for the same query descriptor. + @param k Count of best matches found per each query descriptor or less if a query descriptor has + less than k possible matches in total. + @param masks Set of masks. Each masks[i] specifies permissible matches between the input query + descriptors and stored train descriptors from the i-th image trainDescCollection[i]. + @param compactResult Parameter used when the mask (or masks) is not empty. If compactResult is + false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, + the matches vector does not contain matches for fully masked-out query descriptors. + */ + CV_WRAP void knnMatch( InputArray queryDescriptors, CV_OUT std::vector >& matches, int k, + InputArrayOfArrays masks=noArray(), bool compactResult=false ); + /** @overload + @param queryDescriptors Query set of descriptors. + @param matches Found matches. + @param maxDistance Threshold for the distance between matched descriptors. Distance means here + metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured + in Pixels)! + @param masks Set of masks. Each masks[i] specifies permissible matches between the input query + descriptors and stored train descriptors from the i-th image trainDescCollection[i]. + @param compactResult Parameter used when the mask (or masks) is not empty. If compactResult is + false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, + the matches vector does not contain matches for fully masked-out query descriptors. + */ + CV_WRAP void radiusMatch( InputArray queryDescriptors, CV_OUT std::vector >& matches, float maxDistance, + InputArrayOfArrays masks=noArray(), bool compactResult=false ); + + + CV_WRAP void write( const String& fileName ) const + { + FileStorage fs(fileName, FileStorage::WRITE); + write(fs); + } + + CV_WRAP void read( const String& fileName ) + { + FileStorage fs(fileName, FileStorage::READ); + read(fs.root()); + } + // Reads matcher object from a file node + // see corresponding cv::Algorithm method + CV_WRAP virtual void read( const FileNode& ) CV_OVERRIDE; + // Writes matcher object to a file storage + virtual void write( FileStorage& ) const CV_OVERRIDE; + + /** @brief Clones the matcher. + + @param emptyTrainData If emptyTrainData is false, the method creates a deep copy of the object, + that is, copies both parameters and train data. If emptyTrainData is true, the method creates an + object copy with the current parameters but with empty train data. + */ + CV_WRAP virtual Ptr clone( bool emptyTrainData=false ) const = 0; + + /** @brief Creates a descriptor matcher of a given type with the default parameters (using default + constructor). + + @param descriptorMatcherType Descriptor matcher type. Now the following matcher types are + supported: + - `BruteForce` (it uses L2 ) + - `BruteForce-L1` + - `BruteForce-Hamming` + - `BruteForce-Hamming(2)` + - `FlannBased` + */ + CV_WRAP static Ptr create( const String& descriptorMatcherType ); + + CV_WRAP static Ptr create( int matcherType ); + + + // see corresponding cv::Algorithm method + CV_WRAP inline void write(const Ptr& fs, const String& name = String()) const { Algorithm::write(fs, name); } + +protected: + /** + * Class to work with descriptors from several images as with one merged matrix. + * It is used e.g. in FlannBasedMatcher. + */ + class CV_EXPORTS DescriptorCollection + { + public: + DescriptorCollection(); + DescriptorCollection( const DescriptorCollection& collection ); + virtual ~DescriptorCollection(); + + // Vector of matrices "descriptors" will be merged to one matrix "mergedDescriptors" here. + void set( const std::vector& descriptors ); + virtual void clear(); + + const Mat& getDescriptors() const; + const Mat getDescriptor( int imgIdx, int localDescIdx ) const; + const Mat getDescriptor( int globalDescIdx ) const; + void getLocalIdx( int globalDescIdx, int& imgIdx, int& localDescIdx ) const; + + int size() const; + + protected: + Mat mergedDescriptors; + std::vector startIdxs; + }; + + //! In fact the matching is implemented only by the following two methods. These methods suppose + //! that the class object has been trained already. Public match methods call these methods + //! after calling train(). + virtual void knnMatchImpl( InputArray queryDescriptors, std::vector >& matches, int k, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) = 0; + virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector >& matches, float maxDistance, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) = 0; + + static bool isPossibleMatch( InputArray mask, int queryIdx, int trainIdx ); + static bool isMaskedOut( InputArrayOfArrays masks, int queryIdx ); + + static Mat clone_op( Mat m ) { return m.clone(); } + void checkMasks( InputArrayOfArrays masks, int queryDescriptorsCount ) const; + + //! Collection of descriptors from train images. + std::vector trainDescCollection; + std::vector utrainDescCollection; +}; + +/** @brief Brute-force descriptor matcher. + +For each descriptor in the first set, this matcher finds the closest descriptor in the second set +by trying each one. This descriptor matcher supports masking permissible matches of descriptor +sets. + */ +class CV_EXPORTS_W BFMatcher : public DescriptorMatcher +{ +public: + /** @brief Brute-force matcher constructor (obsolete). Please use BFMatcher.create() + * + * + */ + CV_WRAP BFMatcher( int normType=NORM_L2, bool crossCheck=false ); + + virtual ~BFMatcher() {} + + virtual bool isMaskSupported() const CV_OVERRIDE { return true; } + + /** @brief Brute-force matcher create method. + @param normType One of NORM_L1, NORM_L2, NORM_HAMMING, NORM_HAMMING2. L1 and L2 norms are + preferable choices for SIFT and SURF descriptors, NORM_HAMMING should be used with ORB, BRISK and + BRIEF, NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 (see ORB::ORB constructor + description). + @param crossCheck If it is false, this is will be default BFMatcher behaviour when it finds the k + nearest neighbors for each query descriptor. If crossCheck==true, then the knnMatch() method with + k=1 will only return pairs (i,j) such that for i-th query descriptor the j-th descriptor in the + matcher's collection is the nearest and vice versa, i.e. the BFMatcher will only return consistent + pairs. Such technique usually produces best results with minimal number of outliers when there are + enough matches. This is alternative to the ratio test, used by D. Lowe in SIFT paper. + */ + CV_WRAP static Ptr create( int normType=NORM_L2, bool crossCheck=false ) ; + + virtual Ptr clone( bool emptyTrainData=false ) const CV_OVERRIDE; +protected: + virtual void knnMatchImpl( InputArray queryDescriptors, std::vector >& matches, int k, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE; + virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector >& matches, float maxDistance, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE; + + int normType; + bool crossCheck; +}; + +#if defined(HAVE_OPENCV_FLANN) || defined(CV_DOXYGEN) + +/** @brief Flann-based descriptor matcher. + +This matcher trains cv::flann::Index on a train descriptor collection and calls its nearest search +methods to find the best matches. So, this matcher may be faster when matching a large train +collection than the brute force matcher. FlannBasedMatcher does not support masking permissible +matches of descriptor sets because flann::Index does not support this. : + */ +class CV_EXPORTS_W FlannBasedMatcher : public DescriptorMatcher +{ +public: + CV_WRAP FlannBasedMatcher( const Ptr& indexParams=makePtr(), + const Ptr& searchParams=makePtr() ); + + virtual void add( InputArrayOfArrays descriptors ) CV_OVERRIDE; + virtual void clear() CV_OVERRIDE; + + // Reads matcher object from a file node + virtual void read( const FileNode& ) CV_OVERRIDE; + // Writes matcher object to a file storage + virtual void write( FileStorage& ) const CV_OVERRIDE; + + virtual void train() CV_OVERRIDE; + virtual bool isMaskSupported() const CV_OVERRIDE; + + CV_WRAP static Ptr create(); + + virtual Ptr clone( bool emptyTrainData=false ) const CV_OVERRIDE; +protected: + static void convertToDMatches( const DescriptorCollection& descriptors, + const Mat& indices, const Mat& distances, + std::vector >& matches ); + + virtual void knnMatchImpl( InputArray queryDescriptors, std::vector >& matches, int k, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE; + virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector >& matches, float maxDistance, + InputArrayOfArrays masks=noArray(), bool compactResult=false ) CV_OVERRIDE; + + Ptr indexParams; + Ptr searchParams; + Ptr flannIndex; + + DescriptorCollection mergedDescriptors; + int addedDescCount; +}; + +#endif + +//! @} features2d_match + +/****************************************************************************************\ +* Drawing functions * +\****************************************************************************************/ + +//! @addtogroup features2d_draw +//! @{ + +struct CV_EXPORTS DrawMatchesFlags +{ + enum{ DEFAULT = 0, //!< Output image matrix will be created (Mat::create), + //!< i.e. existing memory of output image may be reused. + //!< Two source image, matches and single keypoints will be drawn. + //!< For each keypoint only the center point will be drawn (without + //!< the circle around keypoint with keypoint size and orientation). + DRAW_OVER_OUTIMG = 1, //!< Output image matrix will not be created (Mat::create). + //!< Matches will be drawn on existing content of output image. + NOT_DRAW_SINGLE_POINTS = 2, //!< Single keypoints will not be drawn. + DRAW_RICH_KEYPOINTS = 4 //!< For each keypoint the circle around keypoint with keypoint size and + //!< orientation will be drawn. + }; +}; + +/** @brief Draws keypoints. + +@param image Source image. +@param keypoints Keypoints from the source image. +@param outImage Output image. Its content depends on the flags value defining what is drawn in the +output image. See possible flags bit values below. +@param color Color of keypoints. +@param flags Flags setting drawing features. Possible flags bit values are defined by +DrawMatchesFlags. See details above in drawMatches . + +@note +For Python API, flags are modified as cv2.DRAW_MATCHES_FLAGS_DEFAULT, +cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS, cv2.DRAW_MATCHES_FLAGS_DRAW_OVER_OUTIMG, +cv2.DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS + */ +CV_EXPORTS_W void drawKeypoints( InputArray image, const std::vector& keypoints, InputOutputArray outImage, + const Scalar& color=Scalar::all(-1), int flags=DrawMatchesFlags::DEFAULT ); + +/** @brief Draws the found matches of keypoints from two images. + +@param img1 First source image. +@param keypoints1 Keypoints from the first source image. +@param img2 Second source image. +@param keypoints2 Keypoints from the second source image. +@param matches1to2 Matches from the first image to the second one, which means that keypoints1[i] +has a corresponding point in keypoints2[matches[i]] . +@param outImg Output image. Its content depends on the flags value defining what is drawn in the +output image. See possible flags bit values below. +@param matchColor Color of matches (lines and connected keypoints). If matchColor==Scalar::all(-1) +, the color is generated randomly. +@param singlePointColor Color of single keypoints (circles), which means that keypoints do not +have the matches. If singlePointColor==Scalar::all(-1) , the color is generated randomly. +@param matchesMask Mask determining which matches are drawn. If the mask is empty, all matches are +drawn. +@param flags Flags setting drawing features. Possible flags bit values are defined by +DrawMatchesFlags. + +This function draws matches of keypoints from two images in the output image. Match is a line +connecting two keypoints (circles). See cv::DrawMatchesFlags. + */ +CV_EXPORTS_W void drawMatches( InputArray img1, const std::vector& keypoints1, + InputArray img2, const std::vector& keypoints2, + const std::vector& matches1to2, InputOutputArray outImg, + const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), + const std::vector& matchesMask=std::vector(), int flags=DrawMatchesFlags::DEFAULT ); + +/** @overload */ +CV_EXPORTS_AS(drawMatchesKnn) void drawMatches( InputArray img1, const std::vector& keypoints1, + InputArray img2, const std::vector& keypoints2, + const std::vector >& matches1to2, InputOutputArray outImg, + const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1), + const std::vector >& matchesMask=std::vector >(), int flags=DrawMatchesFlags::DEFAULT ); + +//! @} features2d_draw + +/****************************************************************************************\ +* Functions to evaluate the feature detectors and [generic] descriptor extractors * +\****************************************************************************************/ + +CV_EXPORTS void evaluateFeatureDetector( const Mat& img1, const Mat& img2, const Mat& H1to2, + std::vector* keypoints1, std::vector* keypoints2, + float& repeatability, int& correspCount, + const Ptr& fdetector=Ptr() ); + +CV_EXPORTS void computeRecallPrecisionCurve( const std::vector >& matches1to2, + const std::vector >& correctMatches1to2Mask, + std::vector& recallPrecisionCurve ); + +CV_EXPORTS float getRecall( const std::vector& recallPrecisionCurve, float l_precision ); +CV_EXPORTS int getNearestPoint( const std::vector& recallPrecisionCurve, float l_precision ); + +/****************************************************************************************\ +* Bag of visual words * +\****************************************************************************************/ + +//! @addtogroup features2d_category +//! @{ + +/** @brief Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors. + +For details, see, for example, *Visual Categorization with Bags of Keypoints* by Gabriella Csurka, +Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. : + */ +class CV_EXPORTS_W BOWTrainer +{ +public: + BOWTrainer(); + virtual ~BOWTrainer(); + + /** @brief Adds descriptors to a training set. + + @param descriptors Descriptors to add to a training set. Each row of the descriptors matrix is a + descriptor. + + The training set is clustered using clustermethod to construct the vocabulary. + */ + CV_WRAP void add( const Mat& descriptors ); + + /** @brief Returns a training set of descriptors. + */ + CV_WRAP const std::vector& getDescriptors() const; + + /** @brief Returns the count of all descriptors stored in the training set. + */ + CV_WRAP int descriptorsCount() const; + + CV_WRAP virtual void clear(); + + /** @overload */ + CV_WRAP virtual Mat cluster() const = 0; + + /** @brief Clusters train descriptors. + + @param descriptors Descriptors to cluster. Each row of the descriptors matrix is a descriptor. + Descriptors are not added to the inner train descriptor set. + + The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first + variant of the method, train descriptors stored in the object are clustered. In the second variant, + input descriptors are clustered. + */ + CV_WRAP virtual Mat cluster( const Mat& descriptors ) const = 0; + +protected: + std::vector descriptors; + int size; +}; + +/** @brief kmeans -based class to train visual vocabulary using the *bag of visual words* approach. : + */ +class CV_EXPORTS_W BOWKMeansTrainer : public BOWTrainer +{ +public: + /** @brief The constructor. + + @see cv::kmeans + */ + CV_WRAP BOWKMeansTrainer( int clusterCount, const TermCriteria& termcrit=TermCriteria(), + int attempts=3, int flags=KMEANS_PP_CENTERS ); + virtual ~BOWKMeansTrainer(); + + // Returns trained vocabulary (i.e. cluster centers). + CV_WRAP virtual Mat cluster() const CV_OVERRIDE; + CV_WRAP virtual Mat cluster( const Mat& descriptors ) const CV_OVERRIDE; + +protected: + + int clusterCount; + TermCriteria termcrit; + int attempts; + int flags; +}; + +/** @brief Class to compute an image descriptor using the *bag of visual words*. + +Such a computation consists of the following steps: + +1. Compute descriptors for a given image and its keypoints set. +2. Find the nearest visual words from the vocabulary for each keypoint descriptor. +3. Compute the bag-of-words image descriptor as is a normalized histogram of vocabulary words +encountered in the image. The i-th bin of the histogram is a frequency of i-th word of the +vocabulary in the given image. + */ +class CV_EXPORTS_W BOWImgDescriptorExtractor +{ +public: + /** @brief The constructor. + + @param dextractor Descriptor extractor that is used to compute descriptors for an input image and + its keypoints. + @param dmatcher Descriptor matcher that is used to find the nearest word of the trained vocabulary + for each keypoint descriptor of the image. + */ + CV_WRAP BOWImgDescriptorExtractor( const Ptr& dextractor, + const Ptr& dmatcher ); + /** @overload */ + BOWImgDescriptorExtractor( const Ptr& dmatcher ); + virtual ~BOWImgDescriptorExtractor(); + + /** @brief Sets a visual vocabulary. + + @param vocabulary Vocabulary (can be trained using the inheritor of BOWTrainer ). Each row of the + vocabulary is a visual word (cluster center). + */ + CV_WRAP void setVocabulary( const Mat& vocabulary ); + + /** @brief Returns the set vocabulary. + */ + CV_WRAP const Mat& getVocabulary() const; + + /** @brief Computes an image descriptor using the set visual vocabulary. + + @param image Image, for which the descriptor is computed. + @param keypoints Keypoints detected in the input image. + @param imgDescriptor Computed output image descriptor. + @param pointIdxsOfClusters Indices of keypoints that belong to the cluster. This means that + pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) + returned if it is non-zero. + @param descriptors Descriptors of the image keypoints that are returned if they are non-zero. + */ + void compute( InputArray image, std::vector& keypoints, OutputArray imgDescriptor, + std::vector >* pointIdxsOfClusters=0, Mat* descriptors=0 ); + /** @overload + @param keypointDescriptors Computed descriptors to match with vocabulary. + @param imgDescriptor Computed output image descriptor. + @param pointIdxsOfClusters Indices of keypoints that belong to the cluster. This means that + pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) + returned if it is non-zero. + */ + void compute( InputArray keypointDescriptors, OutputArray imgDescriptor, + std::vector >* pointIdxsOfClusters=0 ); + // compute() is not constant because DescriptorMatcher::match is not constant + + CV_WRAP_AS(compute) void compute2( const Mat& image, std::vector& keypoints, CV_OUT Mat& imgDescriptor ) + { compute(image,keypoints,imgDescriptor); } + + /** @brief Returns an image descriptor size if the vocabulary is set. Otherwise, it returns 0. + */ + CV_WRAP int descriptorSize() const; + + /** @brief Returns an image descriptor type. + */ + CV_WRAP int descriptorType() const; + +protected: + Mat vocabulary; + Ptr dextractor; + Ptr dmatcher; +}; + +//! @} features2d_category + +//! @} features2d + +} /* namespace cv */ + +#endif diff --git a/3rdparty/opencv/include/opencv2/features2d/features2d.hpp b/3rdparty/opencv/include/opencv2/features2d/features2d.hpp new file mode 100644 index 00000000..e81df0ad --- /dev/null +++ b/3rdparty/opencv/include/opencv2/features2d/features2d.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/features2d.hpp" diff --git a/3rdparty/opencv/include/opencv2/features2d/hal/interface.h b/3rdparty/opencv/include/opencv2/features2d/hal/interface.h new file mode 100644 index 00000000..bcc6577c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/features2d/hal/interface.h @@ -0,0 +1,33 @@ +#ifndef OPENCV_FEATURE2D_HAL_INTERFACE_H +#define OPENCV_FEATURE2D_HAL_INTERFACE_H + +#include "opencv2/core/cvdef.h" +//! @addtogroup featrure2d_hal_interface +//! @{ + +//! @name Fast feature detector types +//! @sa cv::FastFeatureDetector +//! @{ +#define CV_HAL_TYPE_5_8 0 +#define CV_HAL_TYPE_7_12 1 +#define CV_HAL_TYPE_9_16 2 +//! @} + +//! @name Key point +//! @sa cv::KeyPoint +//! @{ +struct CV_EXPORTS cvhalKeyPoint +{ + float x; + float y; + float size; + float angle; + float response; + int octave; + int class_id; +}; +//! @} + +//! @} + +#endif diff --git a/3rdparty/opencv/include/opencv2/flann.hpp b/3rdparty/opencv/include/opencv2/flann.hpp new file mode 100644 index 00000000..fec3d067 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann.hpp @@ -0,0 +1,594 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_FLANN_HPP +#define OPENCV_FLANN_HPP + +#include "opencv2/core.hpp" +#include "opencv2/flann/miniflann.hpp" +#include "opencv2/flann/flann_base.hpp" + +/** +@defgroup flann Clustering and Search in Multi-Dimensional Spaces + +This section documents OpenCV's interface to the FLANN library. FLANN (Fast Library for Approximate +Nearest Neighbors) is a library that contains a collection of algorithms optimized for fast nearest +neighbor search in large datasets and for high dimensional features. More information about FLANN +can be found in @cite Muja2009 . +*/ + +namespace cvflann +{ + CV_EXPORTS flann_distance_t flann_distance_type(); + CV_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order); +} + + +namespace cv +{ +namespace flann +{ + + +//! @addtogroup flann +//! @{ + +template struct CvType {}; +template <> struct CvType { static int type() { return CV_8U; } }; +template <> struct CvType { static int type() { return CV_8S; } }; +template <> struct CvType { static int type() { return CV_16U; } }; +template <> struct CvType { static int type() { return CV_16S; } }; +template <> struct CvType { static int type() { return CV_32S; } }; +template <> struct CvType { static int type() { return CV_32F; } }; +template <> struct CvType { static int type() { return CV_64F; } }; + + +// bring the flann parameters into this namespace +using ::cvflann::get_param; +using ::cvflann::print_params; + +// bring the flann distances into this namespace +using ::cvflann::L2_Simple; +using ::cvflann::L2; +using ::cvflann::L1; +using ::cvflann::MinkowskiDistance; +using ::cvflann::MaxDistance; +using ::cvflann::HammingLUT; +using ::cvflann::Hamming; +using ::cvflann::Hamming2; +using ::cvflann::HistIntersectionDistance; +using ::cvflann::HellingerDistance; +using ::cvflann::ChiSquareDistance; +using ::cvflann::KL_Divergence; + + +/** @brief The FLANN nearest neighbor index class. This class is templated with the type of elements for which +the index is built. + +`Distance` functor specifies the metric to be used to calculate the distance between two points. +There are several `Distance` functors that are readily available: + +@link cvflann::L2_Simple cv::flann::L2_Simple @endlink- Squared Euclidean distance functor. +This is the simpler, unrolled version. This is preferable for very low dimensionality data (eg 3D points) + +@link cvflann::L2 cv::flann::L2 @endlink- Squared Euclidean distance functor, optimized version. + +@link cvflann::L1 cv::flann::L1 @endlink - Manhattan distance functor, optimized version. + +@link cvflann::MinkowskiDistance cv::flann::MinkowskiDistance @endlink - The Minkowsky distance functor. +This is highly optimised with loop unrolling. +The computation of squared root at the end is omitted for efficiency. + +@link cvflann::MaxDistance cv::flann::MaxDistance @endlink - The max distance functor. It computes the +maximum distance between two vectors. This distance is not a valid kdtree distance, it's not +dimensionwise additive. + +@link cvflann::HammingLUT cv::flann::HammingLUT @endlink - %Hamming distance functor. It counts the bit +differences between two strings using a lookup table implementation. + +@link cvflann::Hamming cv::flann::Hamming @endlink - %Hamming distance functor. Population count is +performed using library calls, if available. Lookup table implementation is used as a fallback. + +@link cvflann::Hamming2 cv::flann::Hamming2 @endlink- %Hamming distance functor. Population count is +implemented in 12 arithmetic operations (one of which is multiplication). + +@link cvflann::HistIntersectionDistance cv::flann::HistIntersectionDistance @endlink - The histogram +intersection distance functor. + +@link cvflann::HellingerDistance cv::flann::HellingerDistance @endlink - The Hellinger distance functor. + +@link cvflann::ChiSquareDistance cv::flann::ChiSquareDistance @endlink - The chi-square distance functor. + +@link cvflann::KL_Divergence cv::flann::KL_Divergence @endlink - The Kullback-Leibler divergence functor. + +Although the provided implementations cover a vast range of cases, it is also possible to use +a custom implementation. The distance functor is a class whose `operator()` computes the distance +between two features. If the distance is also a kd-tree compatible distance, it should also provide an +`accum_dist()` method that computes the distance between individual feature dimensions. + +In addition to `operator()` and `accum_dist()`, a distance functor should also define the +`ElementType` and the `ResultType` as the types of the elements it operates on and the type of the +result it computes. If a distance functor can be used as a kd-tree distance (meaning that the full +distance between a pair of features can be accumulated from the partial distances between the +individual dimensions) a typedef `is_kdtree_distance` should be present inside the distance functor. +If the distance is not a kd-tree distance, but it's a distance in a vector space (the individual +dimensions of the elements it operates on can be accessed independently) a typedef +`is_vector_space_distance` should be defined inside the functor. If neither typedef is defined, the +distance is assumed to be a metric distance and will only be used with indexes operating on +generic metric distances. + */ +template +class GenericIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + /** @brief Constructs a nearest neighbor search index for a given dataset. + + @param features Matrix of containing the features(points) to index. The size of the matrix is + num_features x feature_dimensionality and the data type of the elements in the matrix must + coincide with the type of the index. + @param params Structure containing the index parameters. The type of index that will be + constructed depends on the type of this parameter. See the description. + @param distance + + The method constructs a fast search structure from a set of features using the specified algorithm + with specified parameters, as defined by params. params is a reference to one of the following class + IndexParams descendants: + + - **LinearIndexParams** When passing an object of this type, the index will perform a linear, + brute-force search. : + @code + struct LinearIndexParams : public IndexParams + { + }; + @endcode + - **KDTreeIndexParams** When passing an object of this type the index constructed will consist of + a set of randomized kd-trees which will be searched in parallel. : + @code + struct KDTreeIndexParams : public IndexParams + { + KDTreeIndexParams( int trees = 4 ); + }; + @endcode + - **KMeansIndexParams** When passing an object of this type the index constructed will be a + hierarchical k-means tree. : + @code + struct KMeansIndexParams : public IndexParams + { + KMeansIndexParams( + int branching = 32, + int iterations = 11, + flann_centers_init_t centers_init = CENTERS_RANDOM, + float cb_index = 0.2 ); + }; + @endcode + - **CompositeIndexParams** When using a parameters object of this type the index created + combines the randomized kd-trees and the hierarchical k-means tree. : + @code + struct CompositeIndexParams : public IndexParams + { + CompositeIndexParams( + int trees = 4, + int branching = 32, + int iterations = 11, + flann_centers_init_t centers_init = CENTERS_RANDOM, + float cb_index = 0.2 ); + }; + @endcode + - **LshIndexParams** When using a parameters object of this type the index created uses + multi-probe LSH (by Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search + by Qin Lv, William Josephson, Zhe Wang, Moses Charikar, Kai Li., Proceedings of the 33rd + International Conference on Very Large Data Bases (VLDB). Vienna, Austria. September 2007) : + @code + struct LshIndexParams : public IndexParams + { + LshIndexParams( + unsigned int table_number, + unsigned int key_size, + unsigned int multi_probe_level ); + }; + @endcode + - **AutotunedIndexParams** When passing an object of this type the index created is + automatically tuned to offer the best performance, by choosing the optimal index type + (randomized kd-trees, hierarchical kmeans, linear) and parameters for the dataset provided. : + @code + struct AutotunedIndexParams : public IndexParams + { + AutotunedIndexParams( + float target_precision = 0.9, + float build_weight = 0.01, + float memory_weight = 0, + float sample_fraction = 0.1 ); + }; + @endcode + - **SavedIndexParams** This object type is used for loading a previously saved index from the + disk. : + @code + struct SavedIndexParams : public IndexParams + { + SavedIndexParams( String filename ); + }; + @endcode + */ + GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance()); + + ~GenericIndex(); + + /** @brief Performs a K-nearest neighbor search for a given query point using the index. + + @param query The query point + @param indices Vector that will contain the indices of the K-nearest neighbors found. It must have + at least knn size. + @param dists Vector that will contain the distances to the K-nearest neighbors found. It must have + at least knn size. + @param knn Number of nearest neighbors to search for. + @param params SearchParams + */ + void knnSearch(const std::vector& query, std::vector& indices, + std::vector& dists, int knn, const ::cvflann::SearchParams& params); + void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params); + + /** @brief Performs a radius nearest neighbor search for a given query point using the index. + + @param query The query point. + @param indices Vector that will contain the indices of the nearest neighbors found. + @param dists Vector that will contain the distances to the nearest neighbors found. It has the same + number of elements as indices. + @param radius The search radius. + @param params SearchParams + + This function returns the number of nearest neighbors found. + */ + int radiusSearch(const std::vector& query, std::vector& indices, + std::vector& dists, DistanceType radius, const ::cvflann::SearchParams& params); + int radiusSearch(const Mat& query, Mat& indices, Mat& dists, + DistanceType radius, const ::cvflann::SearchParams& params); + + void save(String filename) { nnIndex->save(filename); } + + int veclen() const { return nnIndex->veclen(); } + + int size() const { return nnIndex->size(); } + + ::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); } + + CV_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); } + +private: + ::cvflann::Index* nnIndex; +}; + +//! @cond IGNORED + +#define FLANN_DISTANCE_CHECK \ + if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \ + printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\ + "the distance using cvflann::set_distance_type. This is no longer working as expected "\ + "(cv::flann::Index always uses L2). You should create the index templated on the distance, "\ + "for example for L1 distance use: GenericIndex< L1 > \n"); \ + } + + +template +GenericIndex::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance) +{ + CV_Assert(dataset.type() == CvType::type()); + CV_Assert(dataset.isContinuous()); + ::cvflann::Matrix m_dataset((ElementType*)dataset.ptr(0), dataset.rows, dataset.cols); + + nnIndex = new ::cvflann::Index(m_dataset, params, distance); + + FLANN_DISTANCE_CHECK + + nnIndex->buildIndex(); +} + +template +GenericIndex::~GenericIndex() +{ + delete nnIndex; +} + +template +void GenericIndex::knnSearch(const std::vector& query, std::vector& indices, std::vector& dists, int knn, const ::cvflann::SearchParams& searchParams) +{ + ::cvflann::Matrix m_query((ElementType*)&query[0], 1, query.size()); + ::cvflann::Matrix m_indices(&indices[0], 1, indices.size()); + ::cvflann::Matrix m_dists(&dists[0], 1, dists.size()); + + FLANN_DISTANCE_CHECK + + nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams); +} + + +template +void GenericIndex::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams) +{ + CV_Assert(queries.type() == CvType::type()); + CV_Assert(queries.isContinuous()); + ::cvflann::Matrix m_queries((ElementType*)queries.ptr(0), queries.rows, queries.cols); + + CV_Assert(indices.type() == CV_32S); + CV_Assert(indices.isContinuous()); + ::cvflann::Matrix m_indices((int*)indices.ptr(0), indices.rows, indices.cols); + + CV_Assert(dists.type() == CvType::type()); + CV_Assert(dists.isContinuous()); + ::cvflann::Matrix m_dists((DistanceType*)dists.ptr(0), dists.rows, dists.cols); + + FLANN_DISTANCE_CHECK + + nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams); +} + +template +int GenericIndex::radiusSearch(const std::vector& query, std::vector& indices, std::vector& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams) +{ + ::cvflann::Matrix m_query((ElementType*)&query[0], 1, query.size()); + ::cvflann::Matrix m_indices(&indices[0], 1, indices.size()); + ::cvflann::Matrix m_dists(&dists[0], 1, dists.size()); + + FLANN_DISTANCE_CHECK + + return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); +} + +template +int GenericIndex::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams) +{ + CV_Assert(query.type() == CvType::type()); + CV_Assert(query.isContinuous()); + ::cvflann::Matrix m_query((ElementType*)query.ptr(0), query.rows, query.cols); + + CV_Assert(indices.type() == CV_32S); + CV_Assert(indices.isContinuous()); + ::cvflann::Matrix m_indices((int*)indices.ptr(0), indices.rows, indices.cols); + + CV_Assert(dists.type() == CvType::type()); + CV_Assert(dists.isContinuous()); + ::cvflann::Matrix m_dists((DistanceType*)dists.ptr(0), dists.rows, dists.cols); + + FLANN_DISTANCE_CHECK + + return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); +} + +//! @endcond + +/** + * @deprecated Use GenericIndex class instead + */ +template +class Index_ +{ +public: + typedef typename L2::ElementType ElementType; + typedef typename L2::ResultType DistanceType; + + CV_DEPRECATED Index_(const Mat& dataset, const ::cvflann::IndexParams& params) + { + printf("[WARNING] The cv::flann::Index_ class is deperecated, use cv::flann::GenericIndex instead\n"); + + CV_Assert(dataset.type() == CvType::type()); + CV_Assert(dataset.isContinuous()); + ::cvflann::Matrix m_dataset((ElementType*)dataset.ptr(0), dataset.rows, dataset.cols); + + if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) { + nnIndex_L1 = NULL; + nnIndex_L2 = new ::cvflann::Index< L2 >(m_dataset, params); + } + else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) { + nnIndex_L1 = new ::cvflann::Index< L1 >(m_dataset, params); + nnIndex_L2 = NULL; + } + else { + printf("[ERROR] cv::flann::Index_ only provides backwards compatibility for the L1 and L2 distances. " + "For other distance types you must use cv::flann::GenericIndex\n"); + CV_Assert(0); + } + if (nnIndex_L1) nnIndex_L1->buildIndex(); + if (nnIndex_L2) nnIndex_L2->buildIndex(); + } + CV_DEPRECATED ~Index_() + { + if (nnIndex_L1) delete nnIndex_L1; + if (nnIndex_L2) delete nnIndex_L2; + } + + CV_DEPRECATED void knnSearch(const std::vector& query, std::vector& indices, std::vector& dists, int knn, const ::cvflann::SearchParams& searchParams) + { + ::cvflann::Matrix m_query((ElementType*)&query[0], 1, query.size()); + ::cvflann::Matrix m_indices(&indices[0], 1, indices.size()); + ::cvflann::Matrix m_dists(&dists[0], 1, dists.size()); + + if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams); + if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams); + } + CV_DEPRECATED void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams) + { + CV_Assert(queries.type() == CvType::type()); + CV_Assert(queries.isContinuous()); + ::cvflann::Matrix m_queries((ElementType*)queries.ptr(0), queries.rows, queries.cols); + + CV_Assert(indices.type() == CV_32S); + CV_Assert(indices.isContinuous()); + ::cvflann::Matrix m_indices((int*)indices.ptr(0), indices.rows, indices.cols); + + CV_Assert(dists.type() == CvType::type()); + CV_Assert(dists.isContinuous()); + ::cvflann::Matrix m_dists((DistanceType*)dists.ptr(0), dists.rows, dists.cols); + + if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams); + if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams); + } + + CV_DEPRECATED int radiusSearch(const std::vector& query, std::vector& indices, std::vector& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams) + { + ::cvflann::Matrix m_query((ElementType*)&query[0], 1, query.size()); + ::cvflann::Matrix m_indices(&indices[0], 1, indices.size()); + ::cvflann::Matrix m_dists(&dists[0], 1, dists.size()); + + if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); + if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); + } + + CV_DEPRECATED int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams) + { + CV_Assert(query.type() == CvType::type()); + CV_Assert(query.isContinuous()); + ::cvflann::Matrix m_query((ElementType*)query.ptr(0), query.rows, query.cols); + + CV_Assert(indices.type() == CV_32S); + CV_Assert(indices.isContinuous()); + ::cvflann::Matrix m_indices((int*)indices.ptr(0), indices.rows, indices.cols); + + CV_Assert(dists.type() == CvType::type()); + CV_Assert(dists.isContinuous()); + ::cvflann::Matrix m_dists((DistanceType*)dists.ptr(0), dists.rows, dists.cols); + + if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); + if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams); + } + + CV_DEPRECATED void save(String filename) + { + if (nnIndex_L1) nnIndex_L1->save(filename); + if (nnIndex_L2) nnIndex_L2->save(filename); + } + + CV_DEPRECATED int veclen() const + { + if (nnIndex_L1) return nnIndex_L1->veclen(); + if (nnIndex_L2) return nnIndex_L2->veclen(); + } + + CV_DEPRECATED int size() const + { + if (nnIndex_L1) return nnIndex_L1->size(); + if (nnIndex_L2) return nnIndex_L2->size(); + } + + CV_DEPRECATED ::cvflann::IndexParams getParameters() + { + if (nnIndex_L1) return nnIndex_L1->getParameters(); + if (nnIndex_L2) return nnIndex_L2->getParameters(); + + } + + CV_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() + { + if (nnIndex_L1) return nnIndex_L1->getIndexParameters(); + if (nnIndex_L2) return nnIndex_L2->getIndexParameters(); + } + +private: + // providing backwards compatibility for L2 and L1 distances (most common) + ::cvflann::Index< L2 >* nnIndex_L2; + ::cvflann::Index< L1 >* nnIndex_L1; +}; + + +/** @brief Clusters features using hierarchical k-means algorithm. + +@param features The points to be clustered. The matrix must have elements of type +Distance::ElementType. +@param centers The centers of the clusters obtained. The matrix must have type +Distance::ResultType. The number of rows in this matrix represents the number of clusters desired, +however, because of the way the cut in the hierarchical tree is chosen, the number of clusters +computed will be the highest number of the form (branching-1)\*k+1 that's lower than the number of +clusters desired, where branching is the tree's branching factor (see description of the +KMeansIndexParams). +@param params Parameters used in the construction of the hierarchical k-means tree. +@param d Distance to be used for clustering. + +The method clusters the given feature vectors by constructing a hierarchical k-means tree and +choosing a cut in the tree that minimizes the cluster's variance. It returns the number of clusters +found. + */ +template +int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params, + Distance d = Distance()) +{ + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + CV_Assert(features.type() == CvType::type()); + CV_Assert(features.isContinuous()); + ::cvflann::Matrix m_features((ElementType*)features.ptr(0), features.rows, features.cols); + + CV_Assert(centers.type() == CvType::type()); + CV_Assert(centers.isContinuous()); + ::cvflann::Matrix m_centers((DistanceType*)centers.ptr(0), centers.rows, centers.cols); + + return ::cvflann::hierarchicalClustering(m_features, m_centers, params, d); +} + +/** @deprecated +*/ +template +CV_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params) +{ + printf("[WARNING] cv::flann::hierarchicalClustering is deprecated, use " + "cv::flann::hierarchicalClustering instead\n"); + + if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) { + return hierarchicalClustering< L2 >(features, centers, params); + } + else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) { + return hierarchicalClustering< L1 >(features, centers, params); + } + else { + printf("[ERROR] cv::flann::hierarchicalClustering only provides backwards " + "compatibility for the L1 and L2 distances. " + "For other distance types you must use cv::flann::hierarchicalClustering\n"); + CV_Assert(0); + } +} + +//! @} flann + +} } // namespace cv::flann + +#endif diff --git a/3rdparty/opencv/include/opencv2/flann/all_indices.h b/3rdparty/opencv/include/opencv2/flann/all_indices.h new file mode 100644 index 00000000..ff53fd84 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/all_indices.h @@ -0,0 +1,155 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_ALL_INDICES_H_ +#define OPENCV_FLANN_ALL_INDICES_H_ + +#include "general.h" + +#include "nn_index.h" +#include "kdtree_index.h" +#include "kdtree_single_index.h" +#include "kmeans_index.h" +#include "composite_index.h" +#include "linear_index.h" +#include "hierarchical_clustering_index.h" +#include "lsh_index.h" +#include "autotuned_index.h" + + +namespace cvflann +{ + +template +struct index_creator +{ + static NNIndex* create(const Matrix& dataset, const IndexParams& params, const Distance& distance) + { + flann_algorithm_t index_type = get_param(params, "algorithm"); + + NNIndex* nnIndex; + switch (index_type) { + case FLANN_INDEX_LINEAR: + nnIndex = new LinearIndex(dataset, params, distance); + break; + case FLANN_INDEX_KDTREE_SINGLE: + nnIndex = new KDTreeSingleIndex(dataset, params, distance); + break; + case FLANN_INDEX_KDTREE: + nnIndex = new KDTreeIndex(dataset, params, distance); + break; + case FLANN_INDEX_KMEANS: + nnIndex = new KMeansIndex(dataset, params, distance); + break; + case FLANN_INDEX_COMPOSITE: + nnIndex = new CompositeIndex(dataset, params, distance); + break; + case FLANN_INDEX_AUTOTUNED: + nnIndex = new AutotunedIndex(dataset, params, distance); + break; + case FLANN_INDEX_HIERARCHICAL: + nnIndex = new HierarchicalClusteringIndex(dataset, params, distance); + break; + case FLANN_INDEX_LSH: + nnIndex = new LshIndex(dataset, params, distance); + break; + default: + throw FLANNException("Unknown index type"); + } + + return nnIndex; + } +}; + +template +struct index_creator +{ + static NNIndex* create(const Matrix& dataset, const IndexParams& params, const Distance& distance) + { + flann_algorithm_t index_type = get_param(params, "algorithm"); + + NNIndex* nnIndex; + switch (index_type) { + case FLANN_INDEX_LINEAR: + nnIndex = new LinearIndex(dataset, params, distance); + break; + case FLANN_INDEX_KMEANS: + nnIndex = new KMeansIndex(dataset, params, distance); + break; + case FLANN_INDEX_HIERARCHICAL: + nnIndex = new HierarchicalClusteringIndex(dataset, params, distance); + break; + case FLANN_INDEX_LSH: + nnIndex = new LshIndex(dataset, params, distance); + break; + default: + throw FLANNException("Unknown index type"); + } + + return nnIndex; + } +}; + +template +struct index_creator +{ + static NNIndex* create(const Matrix& dataset, const IndexParams& params, const Distance& distance) + { + flann_algorithm_t index_type = get_param(params, "algorithm"); + + NNIndex* nnIndex; + switch (index_type) { + case FLANN_INDEX_LINEAR: + nnIndex = new LinearIndex(dataset, params, distance); + break; + case FLANN_INDEX_HIERARCHICAL: + nnIndex = new HierarchicalClusteringIndex(dataset, params, distance); + break; + case FLANN_INDEX_LSH: + nnIndex = new LshIndex(dataset, params, distance); + break; + default: + throw FLANNException("Unknown index type"); + } + + return nnIndex; + } +}; + +template +NNIndex* create_index_by_type(const Matrix& dataset, const IndexParams& params, const Distance& distance) +{ + return index_creator::create(dataset, params,distance); +} + +} + +#endif /* OPENCV_FLANN_ALL_INDICES_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/allocator.h b/3rdparty/opencv/include/opencv2/flann/allocator.h new file mode 100644 index 00000000..f347f88e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/allocator.h @@ -0,0 +1,192 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_ALLOCATOR_H_ +#define OPENCV_FLANN_ALLOCATOR_H_ + +#include +#include + + +namespace cvflann +{ + +/** + * Allocates (using C's malloc) a generic type T. + * + * Params: + * count = number of instances to allocate. + * Returns: pointer (of type T*) to memory buffer + */ +template +T* allocate(size_t count = 1) +{ + T* mem = (T*) ::malloc(sizeof(T)*count); + return mem; +} + + +/** + * Pooled storage allocator + * + * The following routines allow for the efficient allocation of storage in + * small chunks from a specified pool. Rather than allowing each structure + * to be freed individually, an entire pool of storage is freed at once. + * This method has two advantages over just using malloc() and free(). First, + * it is far more efficient for allocating small objects, as there is + * no overhead for remembering all the information needed to free each + * object or consolidating fragmented memory. Second, the decision about + * how long to keep an object is made at the time of allocation, and there + * is no need to track down all the objects to free them. + * + */ + +const size_t WORDSIZE=16; +const size_t BLOCKSIZE=8192; + +class PooledAllocator +{ + /* We maintain memory alignment to word boundaries by requiring that all + allocations be in multiples of the machine wordsize. */ + /* Size of machine word in bytes. Must be power of 2. */ + /* Minimum number of bytes requested at a time from the system. Must be multiple of WORDSIZE. */ + + + int remaining; /* Number of bytes left in current block of storage. */ + void* base; /* Pointer to base of current block of storage. */ + void* loc; /* Current location in block to next allocate memory. */ + int blocksize; + + +public: + int usedMemory; + int wastedMemory; + + /** + Default constructor. Initializes a new pool. + */ + PooledAllocator(int blockSize = BLOCKSIZE) + { + blocksize = blockSize; + remaining = 0; + base = NULL; + loc = NULL; + + usedMemory = 0; + wastedMemory = 0; + } + + /** + * Destructor. Frees all the memory allocated in this pool. + */ + ~PooledAllocator() + { + void* prev; + + while (base != NULL) { + prev = *((void**) base); /* Get pointer to prev block. */ + ::free(base); + base = prev; + } + } + + /** + * Returns a pointer to a piece of new memory of the given size in bytes + * allocated from the pool. + */ + void* allocateMemory(int size) + { + int blockSize; + + /* Round size up to a multiple of wordsize. The following expression + only works for WORDSIZE that is a power of 2, by masking last bits of + incremented size to zero. + */ + size = (size + (WORDSIZE - 1)) & ~(WORDSIZE - 1); + + /* Check whether a new block must be allocated. Note that the first word + of a block is reserved for a pointer to the previous block. + */ + if (size > remaining) { + + wastedMemory += remaining; + + /* Allocate new storage. */ + blockSize = (size + sizeof(void*) + (WORDSIZE-1) > BLOCKSIZE) ? + size + sizeof(void*) + (WORDSIZE-1) : BLOCKSIZE; + + // use the standard C malloc to allocate memory + void* m = ::malloc(blockSize); + if (!m) { + fprintf(stderr,"Failed to allocate memory.\n"); + return NULL; + } + + /* Fill first word of new block with pointer to previous block. */ + ((void**) m)[0] = base; + base = m; + + int shift = 0; + //int shift = (WORDSIZE - ( (((size_t)m) + sizeof(void*)) & (WORDSIZE-1))) & (WORDSIZE-1); + + remaining = blockSize - sizeof(void*) - shift; + loc = ((char*)m + sizeof(void*) + shift); + } + void* rloc = loc; + loc = (char*)loc + size; + remaining -= size; + + usedMemory += size; + + return rloc; + } + + /** + * Allocates (using this pool) a generic type T. + * + * Params: + * count = number of instances to allocate. + * Returns: pointer (of type T*) to memory buffer + */ + template + T* allocate(size_t count = 1) + { + T* mem = (T*) this->allocateMemory((int)(sizeof(T)*count)); + return mem; + } + +private: + PooledAllocator(const PooledAllocator &); // copy disabled + PooledAllocator& operator=(const PooledAllocator &); // assign disabled +}; + +} + +#endif //OPENCV_FLANN_ALLOCATOR_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/any.h b/3rdparty/opencv/include/opencv2/flann/any.h new file mode 100644 index 00000000..5b57aa3d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/any.h @@ -0,0 +1,330 @@ +#ifndef OPENCV_FLANN_ANY_H_ +#define OPENCV_FLANN_ANY_H_ +/* + * (C) Copyright Christopher Diggins 2005-2011 + * (C) Copyright Pablo Aguilar 2005 + * (C) Copyright Kevlin Henney 2001 + * + * Distributed under the Boost Software License, Version 1.0. (See + * accompanying file LICENSE_1_0.txt or copy at + * http://www.boost.org/LICENSE_1_0.txt + * + * Adapted for FLANN by Marius Muja + */ + +#include "defines.h" +#include +#include +#include + +namespace cvflann +{ + +namespace anyimpl +{ + +struct bad_any_cast +{ +}; + +struct empty_any +{ +}; + +inline std::ostream& operator <<(std::ostream& out, const empty_any&) +{ + out << "[empty_any]"; + return out; +} + +struct base_any_policy +{ + virtual void static_delete(void** x) = 0; + virtual void copy_from_value(void const* src, void** dest) = 0; + virtual void clone(void* const* src, void** dest) = 0; + virtual void move(void* const* src, void** dest) = 0; + virtual void* get_value(void** src) = 0; + virtual const void* get_value(void* const * src) = 0; + virtual ::size_t get_size() = 0; + virtual const std::type_info& type() = 0; + virtual void print(std::ostream& out, void* const* src) = 0; + virtual ~base_any_policy() {} +}; + +template +struct typed_base_any_policy : base_any_policy +{ + virtual ::size_t get_size() CV_OVERRIDE { return sizeof(T); } + virtual const std::type_info& type() CV_OVERRIDE { return typeid(T); } + +}; + +template +struct small_any_policy CV_FINAL : typed_base_any_policy +{ + virtual void static_delete(void**) CV_OVERRIDE { } + virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE + { + new (dest) T(* reinterpret_cast(src)); + } + virtual void clone(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; } + virtual void move(void* const* src, void** dest) CV_OVERRIDE { *dest = *src; } + virtual void* get_value(void** src) CV_OVERRIDE { return reinterpret_cast(src); } + virtual const void* get_value(void* const * src) CV_OVERRIDE { return reinterpret_cast(src); } + virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast(src); } +}; + +template +struct big_any_policy CV_FINAL : typed_base_any_policy +{ + virtual void static_delete(void** x) CV_OVERRIDE + { + if (* x) delete (* reinterpret_cast(x)); + *x = NULL; + } + virtual void copy_from_value(void const* src, void** dest) CV_OVERRIDE + { + *dest = new T(*reinterpret_cast(src)); + } + virtual void clone(void* const* src, void** dest) CV_OVERRIDE + { + *dest = new T(**reinterpret_cast(src)); + } + virtual void move(void* const* src, void** dest) CV_OVERRIDE + { + (*reinterpret_cast(dest))->~T(); + **reinterpret_cast(dest) = **reinterpret_cast(src); + } + virtual void* get_value(void** src) CV_OVERRIDE { return *src; } + virtual const void* get_value(void* const * src) CV_OVERRIDE { return *src; } + virtual void print(std::ostream& out, void* const* src) CV_OVERRIDE { out << *reinterpret_cast(*src); } +}; + +template<> inline void big_any_policy::print(std::ostream& out, void* const* src) +{ + out << int(*reinterpret_cast(*src)); +} + +template<> inline void big_any_policy::print(std::ostream& out, void* const* src) +{ + out << int(*reinterpret_cast(*src)); +} + +template<> inline void big_any_policy::print(std::ostream& out, void* const* src) +{ + out << (*reinterpret_cast(*src)).c_str(); +} + +template +struct choose_policy +{ + typedef big_any_policy type; +}; + +template +struct choose_policy +{ + typedef small_any_policy type; +}; + +struct any; + +/// Choosing the policy for an any type is illegal, but should never happen. +/// This is designed to throw a compiler error. +template<> +struct choose_policy +{ + typedef void type; +}; + +/// Specializations for small types. +#define SMALL_POLICY(TYPE) \ + template<> \ + struct choose_policy { typedef small_any_policy type; \ + } + +SMALL_POLICY(signed char); +SMALL_POLICY(unsigned char); +SMALL_POLICY(signed short); +SMALL_POLICY(unsigned short); +SMALL_POLICY(signed int); +SMALL_POLICY(unsigned int); +SMALL_POLICY(signed long); +SMALL_POLICY(unsigned long); +SMALL_POLICY(float); +SMALL_POLICY(bool); + +#undef SMALL_POLICY + +template +class SinglePolicy +{ + SinglePolicy(); + SinglePolicy(const SinglePolicy& other); + SinglePolicy& operator=(const SinglePolicy& other); + +public: + static base_any_policy* get_policy(); + +private: + static typename choose_policy::type policy; +}; + +template +typename choose_policy::type SinglePolicy::policy; + +/// This function will return a different policy for each type. +template +inline base_any_policy* SinglePolicy::get_policy() { return &policy; } + +} // namespace anyimpl + +struct any +{ +private: + // fields + anyimpl::base_any_policy* policy; + void* object; + +public: + /// Initializing constructor. + template + any(const T& x) + : policy(anyimpl::SinglePolicy::get_policy()), object(NULL) + { + assign(x); + } + + /// Empty constructor. + any() + : policy(anyimpl::SinglePolicy::get_policy()), object(NULL) + { } + + /// Special initializing constructor for string literals. + any(const char* x) + : policy(anyimpl::SinglePolicy::get_policy()), object(NULL) + { + assign(x); + } + + /// Copy constructor. + any(const any& x) + : policy(anyimpl::SinglePolicy::get_policy()), object(NULL) + { + assign(x); + } + + /// Destructor. + ~any() + { + policy->static_delete(&object); + } + + /// Assignment function from another any. + any& assign(const any& x) + { + reset(); + policy = x.policy; + policy->clone(&x.object, &object); + return *this; + } + + /// Assignment function. + template + any& assign(const T& x) + { + reset(); + policy = anyimpl::SinglePolicy::get_policy(); + policy->copy_from_value(&x, &object); + return *this; + } + + /// Assignment operator. + template + any& operator=(const T& x) + { + return assign(x); + } + + /// Assignment operator. Template-based version above doesn't work as expected. We need regular assignment operator here. + any& operator=(const any& x) + { + return assign(x); + } + + /// Assignment operator, specialed for literal strings. + /// They have types like const char [6] which don't work as expected. + any& operator=(const char* x) + { + return assign(x); + } + + /// Utility functions + any& swap(any& x) + { + std::swap(policy, x.policy); + std::swap(object, x.object); + return *this; + } + + /// Cast operator. You can only cast to the original type. + template + T& cast() + { + if (policy->type() != typeid(T)) throw anyimpl::bad_any_cast(); + T* r = reinterpret_cast(policy->get_value(&object)); + return *r; + } + + /// Cast operator. You can only cast to the original type. + template + const T& cast() const + { + if (policy->type() != typeid(T)) throw anyimpl::bad_any_cast(); + const T* r = reinterpret_cast(policy->get_value(&object)); + return *r; + } + + /// Returns true if the any contains no value. + bool empty() const + { + return policy->type() == typeid(anyimpl::empty_any); + } + + /// Frees any allocated memory, and sets the value to NULL. + void reset() + { + policy->static_delete(&object); + policy = anyimpl::SinglePolicy::get_policy(); + } + + /// Returns true if the two types are the same. + bool compatible(const any& x) const + { + return policy->type() == x.policy->type(); + } + + /// Returns if the type is compatible with the policy + template + bool has_type() + { + return policy->type() == typeid(T); + } + + const std::type_info& type() const + { + return policy->type(); + } + + friend std::ostream& operator <<(std::ostream& out, const any& any_val); +}; + +inline std::ostream& operator <<(std::ostream& out, const any& any_val) +{ + any_val.policy->print(out,&any_val.object); + return out; +} + +} + +#endif // OPENCV_FLANN_ANY_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/autotuned_index.h b/3rdparty/opencv/include/opencv2/flann/autotuned_index.h new file mode 100644 index 00000000..2fbc6c9a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/autotuned_index.h @@ -0,0 +1,591 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ +#ifndef OPENCV_FLANN_AUTOTUNED_INDEX_H_ +#define OPENCV_FLANN_AUTOTUNED_INDEX_H_ + +#include + +#include "general.h" +#include "nn_index.h" +#include "ground_truth.h" +#include "index_testing.h" +#include "sampling.h" +#include "kdtree_index.h" +#include "kdtree_single_index.h" +#include "kmeans_index.h" +#include "composite_index.h" +#include "linear_index.h" +#include "logger.h" + +namespace cvflann +{ + +template +NNIndex* create_index_by_type(const Matrix& dataset, const IndexParams& params, const Distance& distance); + + +struct AutotunedIndexParams : public IndexParams +{ + AutotunedIndexParams(float target_precision = 0.8, float build_weight = 0.01, float memory_weight = 0, float sample_fraction = 0.1) + { + (*this)["algorithm"] = FLANN_INDEX_AUTOTUNED; + // precision desired (used for autotuning, -1 otherwise) + (*this)["target_precision"] = target_precision; + // build tree time weighting factor + (*this)["build_weight"] = build_weight; + // index memory weighting factor + (*this)["memory_weight"] = memory_weight; + // what fraction of the dataset to use for autotuning + (*this)["sample_fraction"] = sample_fraction; + } +}; + + +template +class AutotunedIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + AutotunedIndex(const Matrix& inputData, const IndexParams& params = AutotunedIndexParams(), Distance d = Distance()) : + dataset_(inputData), distance_(d) + { + target_precision_ = get_param(params, "target_precision",0.8f); + build_weight_ = get_param(params,"build_weight", 0.01f); + memory_weight_ = get_param(params, "memory_weight", 0.0f); + sample_fraction_ = get_param(params,"sample_fraction", 0.1f); + bestIndex_ = NULL; + speedup_ = 0; + } + + AutotunedIndex(const AutotunedIndex&); + AutotunedIndex& operator=(const AutotunedIndex&); + + virtual ~AutotunedIndex() + { + if (bestIndex_ != NULL) { + delete bestIndex_; + bestIndex_ = NULL; + } + } + + /** + * Method responsible with building the index. + */ + virtual void buildIndex() CV_OVERRIDE + { + std::ostringstream stream; + bestParams_ = estimateBuildParams(); + print_params(bestParams_, stream); + Logger::info("----------------------------------------------------\n"); + Logger::info("Autotuned parameters:\n"); + Logger::info("%s", stream.str().c_str()); + Logger::info("----------------------------------------------------\n"); + + bestIndex_ = create_index_by_type(dataset_, bestParams_, distance_); + bestIndex_->buildIndex(); + speedup_ = estimateSearchParams(bestSearchParams_); + stream.str(std::string()); + print_params(bestSearchParams_, stream); + Logger::info("----------------------------------------------------\n"); + Logger::info("Search parameters:\n"); + Logger::info("%s", stream.str().c_str()); + Logger::info("----------------------------------------------------\n"); + } + + /** + * Saves the index to a stream + */ + virtual void saveIndex(FILE* stream) CV_OVERRIDE + { + save_value(stream, (int)bestIndex_->getType()); + bestIndex_->saveIndex(stream); + save_value(stream, get_param(bestSearchParams_, "checks")); + } + + /** + * Loads the index from a stream + */ + virtual void loadIndex(FILE* stream) CV_OVERRIDE + { + int index_type; + + load_value(stream, index_type); + IndexParams params; + params["algorithm"] = (flann_algorithm_t)index_type; + bestIndex_ = create_index_by_type(dataset_, params, distance_); + bestIndex_->loadIndex(stream); + int checks; + load_value(stream, checks); + bestSearchParams_["checks"] = checks; + } + + /** + * Method that searches for nearest-neighbors + */ + virtual void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + int checks = get_param(searchParams,"checks",FLANN_CHECKS_AUTOTUNED); + if (checks == FLANN_CHECKS_AUTOTUNED) { + bestIndex_->findNeighbors(result, vec, bestSearchParams_); + } + else { + bestIndex_->findNeighbors(result, vec, searchParams); + } + } + + + IndexParams getParameters() const CV_OVERRIDE + { + return bestIndex_->getParameters(); + } + + SearchParams getSearchParameters() const + { + return bestSearchParams_; + } + + float getSpeedup() const + { + return speedup_; + } + + + /** + * Number of features in this index. + */ + virtual size_t size() const CV_OVERRIDE + { + return bestIndex_->size(); + } + + /** + * The length of each vector in this index. + */ + virtual size_t veclen() const CV_OVERRIDE + { + return bestIndex_->veclen(); + } + + /** + * The amount of memory (in bytes) this index uses. + */ + virtual int usedMemory() const CV_OVERRIDE + { + return bestIndex_->usedMemory(); + } + + /** + * Algorithm name + */ + virtual flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_AUTOTUNED; + } + +private: + + struct CostData + { + float searchTimeCost; + float buildTimeCost; + float memoryCost; + float totalCost; + IndexParams params; + }; + + void evaluate_kmeans(CostData& cost) + { + StartStopTimer t; + int checks; + const int nn = 1; + + Logger::info("KMeansTree using params: max_iterations=%d, branching=%d\n", + get_param(cost.params,"iterations"), + get_param(cost.params,"branching")); + KMeansIndex kmeans(sampledDataset_, cost.params, distance_); + // measure index build time + t.start(); + kmeans.buildIndex(); + t.stop(); + float buildTime = (float)t.value; + + // measure search time + float searchTime = test_index_precision(kmeans, sampledDataset_, testDataset_, gt_matches_, target_precision_, checks, distance_, nn); + + float datasetMemory = float(sampledDataset_.rows * sampledDataset_.cols * sizeof(float)); + cost.memoryCost = (kmeans.usedMemory() + datasetMemory) / datasetMemory; + cost.searchTimeCost = searchTime; + cost.buildTimeCost = buildTime; + Logger::info("KMeansTree buildTime=%g, searchTime=%g, build_weight=%g\n", buildTime, searchTime, build_weight_); + } + + + void evaluate_kdtree(CostData& cost) + { + StartStopTimer t; + int checks; + const int nn = 1; + + Logger::info("KDTree using params: trees=%d\n", get_param(cost.params,"trees")); + KDTreeIndex kdtree(sampledDataset_, cost.params, distance_); + + t.start(); + kdtree.buildIndex(); + t.stop(); + float buildTime = (float)t.value; + + //measure search time + float searchTime = test_index_precision(kdtree, sampledDataset_, testDataset_, gt_matches_, target_precision_, checks, distance_, nn); + + float datasetMemory = float(sampledDataset_.rows * sampledDataset_.cols * sizeof(float)); + cost.memoryCost = (kdtree.usedMemory() + datasetMemory) / datasetMemory; + cost.searchTimeCost = searchTime; + cost.buildTimeCost = buildTime; + Logger::info("KDTree buildTime=%g, searchTime=%g\n", buildTime, searchTime); + } + + + // struct KMeansSimpleDownhillFunctor { + // + // Autotune& autotuner; + // KMeansSimpleDownhillFunctor(Autotune& autotuner_) : autotuner(autotuner_) {} + // + // float operator()(int* params) { + // + // float maxFloat = numeric_limits::max(); + // + // if (params[0]<2) return maxFloat; + // if (params[1]<0) return maxFloat; + // + // CostData c; + // c.params["algorithm"] = KMEANS; + // c.params["centers-init"] = CENTERS_RANDOM; + // c.params["branching"] = params[0]; + // c.params["max-iterations"] = params[1]; + // + // autotuner.evaluate_kmeans(c); + // + // return c.timeCost; + // + // } + // }; + // + // struct KDTreeSimpleDownhillFunctor { + // + // Autotune& autotuner; + // KDTreeSimpleDownhillFunctor(Autotune& autotuner_) : autotuner(autotuner_) {} + // + // float operator()(int* params) { + // float maxFloat = numeric_limits::max(); + // + // if (params[0]<1) return maxFloat; + // + // CostData c; + // c.params["algorithm"] = KDTREE; + // c.params["trees"] = params[0]; + // + // autotuner.evaluate_kdtree(c); + // + // return c.timeCost; + // + // } + // }; + + + + void optimizeKMeans(std::vector& costs) + { + Logger::info("KMEANS, Step 1: Exploring parameter space\n"); + + // explore kmeans parameters space using combinations of the parameters below + int maxIterations[] = { 1, 5, 10, 15 }; + int branchingFactors[] = { 16, 32, 64, 128, 256 }; + + int kmeansParamSpaceSize = FLANN_ARRAY_LEN(maxIterations) * FLANN_ARRAY_LEN(branchingFactors); + costs.reserve(costs.size() + kmeansParamSpaceSize); + + // evaluate kmeans for all parameter combinations + for (size_t i = 0; i < FLANN_ARRAY_LEN(maxIterations); ++i) { + for (size_t j = 0; j < FLANN_ARRAY_LEN(branchingFactors); ++j) { + CostData cost; + cost.params["algorithm"] = FLANN_INDEX_KMEANS; + cost.params["centers_init"] = FLANN_CENTERS_RANDOM; + cost.params["iterations"] = maxIterations[i]; + cost.params["branching"] = branchingFactors[j]; + + evaluate_kmeans(cost); + costs.push_back(cost); + } + } + + // Logger::info("KMEANS, Step 2: simplex-downhill optimization\n"); + // + // const int n = 2; + // // choose initial simplex points as the best parameters so far + // int kmeansNMPoints[n*(n+1)]; + // float kmeansVals[n+1]; + // for (int i=0;i& costs) + { + Logger::info("KD-TREE, Step 1: Exploring parameter space\n"); + + // explore kd-tree parameters space using the parameters below + int testTrees[] = { 1, 4, 8, 16, 32 }; + + // evaluate kdtree for all parameter combinations + for (size_t i = 0; i < FLANN_ARRAY_LEN(testTrees); ++i) { + CostData cost; + cost.params["algorithm"] = FLANN_INDEX_KDTREE; + cost.params["trees"] = testTrees[i]; + + evaluate_kdtree(cost); + costs.push_back(cost); + } + + // Logger::info("KD-TREE, Step 2: simplex-downhill optimization\n"); + // + // const int n = 1; + // // choose initial simplex points as the best parameters so far + // int kdtreeNMPoints[n*(n+1)]; + // float kdtreeVals[n+1]; + // for (int i=0;i costs; + + int sampleSize = int(sample_fraction_ * dataset_.rows); + int testSampleSize = std::min(sampleSize / 10, 1000); + + Logger::info("Entering autotuning, dataset size: %d, sampleSize: %d, testSampleSize: %d, target precision: %g\n", dataset_.rows, sampleSize, testSampleSize, target_precision_); + + // For a very small dataset, it makes no sense to build any fancy index, just + // use linear search + if (testSampleSize < 10) { + Logger::info("Choosing linear, dataset too small\n"); + return LinearIndexParams(); + } + + // We use a fraction of the original dataset to speedup the autotune algorithm + sampledDataset_ = random_sample(dataset_, sampleSize); + // We use a cross-validation approach, first we sample a testset from the dataset + testDataset_ = random_sample(sampledDataset_, testSampleSize, true); + + // We compute the ground truth using linear search + Logger::info("Computing ground truth... \n"); + gt_matches_ = Matrix(new int[testDataset_.rows], testDataset_.rows, 1); + StartStopTimer t; + t.start(); + compute_ground_truth(sampledDataset_, testDataset_, gt_matches_, 0, distance_); + t.stop(); + + CostData linear_cost; + linear_cost.searchTimeCost = (float)t.value; + linear_cost.buildTimeCost = 0; + linear_cost.memoryCost = 0; + linear_cost.params["algorithm"] = FLANN_INDEX_LINEAR; + + costs.push_back(linear_cost); + + // Start parameter autotune process + Logger::info("Autotuning parameters...\n"); + + optimizeKMeans(costs); + optimizeKDTree(costs); + + float bestTimeCost = costs[0].searchTimeCost; + for (size_t i = 0; i < costs.size(); ++i) { + float timeCost = costs[i].buildTimeCost * build_weight_ + costs[i].searchTimeCost; + if (timeCost < bestTimeCost) { + bestTimeCost = timeCost; + } + } + + float bestCost = costs[0].searchTimeCost / bestTimeCost; + IndexParams bestParams = costs[0].params; + if (bestTimeCost > 0) { + for (size_t i = 0; i < costs.size(); ++i) { + float crtCost = (costs[i].buildTimeCost * build_weight_ + costs[i].searchTimeCost) / bestTimeCost + + memory_weight_ * costs[i].memoryCost; + if (crtCost < bestCost) { + bestCost = crtCost; + bestParams = costs[i].params; + } + } + } + + delete[] gt_matches_.data; + delete[] testDataset_.data; + delete[] sampledDataset_.data; + + return bestParams; + } + + + + /** + * Estimates the search time parameters needed to get the desired precision. + * Precondition: the index is built + * Postcondition: the searchParams will have the optimum params set, also the speedup obtained over linear search. + */ + float estimateSearchParams(SearchParams& searchParams) + { + const int nn = 1; + const size_t SAMPLE_COUNT = 1000; + + assert(bestIndex_ != NULL); // must have a valid index + + float speedup = 0; + + int samples = (int)std::min(dataset_.rows / 10, SAMPLE_COUNT); + if (samples > 0) { + Matrix testDataset = random_sample(dataset_, samples); + + Logger::info("Computing ground truth\n"); + + // we need to compute the ground truth first + Matrix gt_matches(new int[testDataset.rows], testDataset.rows, 1); + StartStopTimer t; + t.start(); + compute_ground_truth(dataset_, testDataset, gt_matches, 1, distance_); + t.stop(); + float linear = (float)t.value; + + int checks; + Logger::info("Estimating number of checks\n"); + + float searchTime; + float cb_index; + if (bestIndex_->getType() == FLANN_INDEX_KMEANS) { + Logger::info("KMeans algorithm, estimating cluster border factor\n"); + KMeansIndex* kmeans = (KMeansIndex*)bestIndex_; + float bestSearchTime = -1; + float best_cb_index = -1; + int best_checks = -1; + for (cb_index = 0; cb_index < 1.1f; cb_index += 0.2f) { + kmeans->set_cb_index(cb_index); + searchTime = test_index_precision(*kmeans, dataset_, testDataset, gt_matches, target_precision_, checks, distance_, nn, 1); + if ((searchTime < bestSearchTime) || (bestSearchTime == -1)) { + bestSearchTime = searchTime; + best_cb_index = cb_index; + best_checks = checks; + } + } + searchTime = bestSearchTime; + cb_index = best_cb_index; + checks = best_checks; + + kmeans->set_cb_index(best_cb_index); + Logger::info("Optimum cb_index: %g\n", cb_index); + bestParams_["cb_index"] = cb_index; + } + else { + searchTime = test_index_precision(*bestIndex_, dataset_, testDataset, gt_matches, target_precision_, checks, distance_, nn, 1); + } + + Logger::info("Required number of checks: %d \n", checks); + searchParams["checks"] = checks; + + speedup = linear / searchTime; + + delete[] gt_matches.data; + delete[] testDataset.data; + } + + return speedup; + } + +private: + NNIndex* bestIndex_; + + IndexParams bestParams_; + SearchParams bestSearchParams_; + + Matrix sampledDataset_; + Matrix testDataset_; + Matrix gt_matches_; + + float speedup_; + + /** + * The dataset used by this index + */ + const Matrix dataset_; + + /** + * Index parameters + */ + float target_precision_; + float build_weight_; + float memory_weight_; + float sample_fraction_; + + Distance distance_; + + +}; +} + +#endif /* OPENCV_FLANN_AUTOTUNED_INDEX_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/composite_index.h b/3rdparty/opencv/include/opencv2/flann/composite_index.h new file mode 100644 index 00000000..5e12a177 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/composite_index.h @@ -0,0 +1,194 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_COMPOSITE_INDEX_H_ +#define OPENCV_FLANN_COMPOSITE_INDEX_H_ + +#include "general.h" +#include "nn_index.h" +#include "kdtree_index.h" +#include "kmeans_index.h" + +namespace cvflann +{ + +/** + * Index parameters for the CompositeIndex. + */ +struct CompositeIndexParams : public IndexParams +{ + CompositeIndexParams(int trees = 4, int branching = 32, int iterations = 11, + flann_centers_init_t centers_init = FLANN_CENTERS_RANDOM, float cb_index = 0.2 ) + { + (*this)["algorithm"] = FLANN_INDEX_KMEANS; + // number of randomized trees to use (for kdtree) + (*this)["trees"] = trees; + // branching factor + (*this)["branching"] = branching; + // max iterations to perform in one kmeans clustering (kmeans tree) + (*this)["iterations"] = iterations; + // algorithm used for picking the initial cluster centers for kmeans tree + (*this)["centers_init"] = centers_init; + // cluster boundary index. Used when searching the kmeans tree + (*this)["cb_index"] = cb_index; + } +}; + + +/** + * This index builds a kd-tree index and a k-means index and performs nearest + * neighbour search both indexes. This gives a slight boost in search performance + * as some of the neighbours that are missed by one index are found by the other. + */ +template +class CompositeIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + /** + * Index constructor + * @param inputData dataset containing the points to index + * @param params Index parameters + * @param d Distance functor + * @return + */ + CompositeIndex(const Matrix& inputData, const IndexParams& params = CompositeIndexParams(), + Distance d = Distance()) : index_params_(params) + { + kdtree_index_ = new KDTreeIndex(inputData, params, d); + kmeans_index_ = new KMeansIndex(inputData, params, d); + + } + + CompositeIndex(const CompositeIndex&); + CompositeIndex& operator=(const CompositeIndex&); + + virtual ~CompositeIndex() + { + delete kdtree_index_; + delete kmeans_index_; + } + + /** + * @return The index type + */ + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_COMPOSITE; + } + + /** + * @return Size of the index + */ + size_t size() const CV_OVERRIDE + { + return kdtree_index_->size(); + } + + /** + * \returns The dimensionality of the features in this index. + */ + size_t veclen() const CV_OVERRIDE + { + return kdtree_index_->veclen(); + } + + /** + * \returns The amount of memory (in bytes) used by the index. + */ + int usedMemory() const CV_OVERRIDE + { + return kmeans_index_->usedMemory() + kdtree_index_->usedMemory(); + } + + /** + * \brief Builds the index + */ + void buildIndex() CV_OVERRIDE + { + Logger::info("Building kmeans tree...\n"); + kmeans_index_->buildIndex(); + Logger::info("Building kdtree tree...\n"); + kdtree_index_->buildIndex(); + } + + /** + * \brief Saves the index to a stream + * \param stream The stream to save the index to + */ + void saveIndex(FILE* stream) CV_OVERRIDE + { + kmeans_index_->saveIndex(stream); + kdtree_index_->saveIndex(stream); + } + + /** + * \brief Loads the index from a stream + * \param stream The stream from which the index is loaded + */ + void loadIndex(FILE* stream) CV_OVERRIDE + { + kmeans_index_->loadIndex(stream); + kdtree_index_->loadIndex(stream); + } + + /** + * \returns The index parameters + */ + IndexParams getParameters() const CV_OVERRIDE + { + return index_params_; + } + + /** + * \brief Method that searches for nearest-neighbours + */ + void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + kmeans_index_->findNeighbors(result, vec, searchParams); + kdtree_index_->findNeighbors(result, vec, searchParams); + } + +private: + /** The k-means index */ + KMeansIndex* kmeans_index_; + + /** The kd-tree index */ + KDTreeIndex* kdtree_index_; + + /** The index parameters */ + const IndexParams index_params_; +}; + +} + +#endif //OPENCV_FLANN_COMPOSITE_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/config.h b/3rdparty/opencv/include/opencv2/flann/config.h new file mode 100644 index 00000000..56832fd3 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/config.h @@ -0,0 +1,38 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2011 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2011 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_CONFIG_H_ +#define OPENCV_FLANN_CONFIG_H_ + +#ifdef FLANN_VERSION_ +#undef FLANN_VERSION_ +#endif +#define FLANN_VERSION_ "1.6.10" + +#endif /* OPENCV_FLANN_CONFIG_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/defines.h b/3rdparty/opencv/include/opencv2/flann/defines.h new file mode 100644 index 00000000..6fd53c2f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/defines.h @@ -0,0 +1,164 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2011 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2011 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_DEFINES_H_ +#define OPENCV_FLANN_DEFINES_H_ + +#include "config.h" + +#ifdef FLANN_EXPORT +#undef FLANN_EXPORT +#endif +#ifdef _WIN32 +/* win32 dll export/import directives */ + #ifdef FLANN_EXPORTS + #define FLANN_EXPORT __declspec(dllexport) + #elif defined(FLANN_STATIC) + #define FLANN_EXPORT + #else + #define FLANN_EXPORT __declspec(dllimport) + #endif +#else +/* unix needs nothing */ + #define FLANN_EXPORT +#endif + + +#undef FLANN_PLATFORM_32_BIT +#undef FLANN_PLATFORM_64_BIT +#if defined __amd64__ || defined __x86_64__ || defined _WIN64 || defined _M_X64 +#define FLANN_PLATFORM_64_BIT +#else +#define FLANN_PLATFORM_32_BIT +#endif + + +#undef FLANN_ARRAY_LEN +#define FLANN_ARRAY_LEN(a) (sizeof(a)/sizeof(a[0])) + +namespace cvflann { + +/* Nearest neighbour index algorithms */ +enum flann_algorithm_t +{ + FLANN_INDEX_LINEAR = 0, + FLANN_INDEX_KDTREE = 1, + FLANN_INDEX_KMEANS = 2, + FLANN_INDEX_COMPOSITE = 3, + FLANN_INDEX_KDTREE_SINGLE = 4, + FLANN_INDEX_HIERARCHICAL = 5, + FLANN_INDEX_LSH = 6, + FLANN_INDEX_SAVED = 254, + FLANN_INDEX_AUTOTUNED = 255, + + // deprecated constants, should use the FLANN_INDEX_* ones instead + LINEAR = 0, + KDTREE = 1, + KMEANS = 2, + COMPOSITE = 3, + KDTREE_SINGLE = 4, + SAVED = 254, + AUTOTUNED = 255 +}; + + + +enum flann_centers_init_t +{ + FLANN_CENTERS_RANDOM = 0, + FLANN_CENTERS_GONZALES = 1, + FLANN_CENTERS_KMEANSPP = 2, + FLANN_CENTERS_GROUPWISE = 3, + + // deprecated constants, should use the FLANN_CENTERS_* ones instead + CENTERS_RANDOM = 0, + CENTERS_GONZALES = 1, + CENTERS_KMEANSPP = 2 +}; + +enum flann_log_level_t +{ + FLANN_LOG_NONE = 0, + FLANN_LOG_FATAL = 1, + FLANN_LOG_ERROR = 2, + FLANN_LOG_WARN = 3, + FLANN_LOG_INFO = 4 +}; + +enum flann_distance_t +{ + FLANN_DIST_EUCLIDEAN = 1, + FLANN_DIST_L2 = 1, + FLANN_DIST_MANHATTAN = 2, + FLANN_DIST_L1 = 2, + FLANN_DIST_MINKOWSKI = 3, + FLANN_DIST_MAX = 4, + FLANN_DIST_HIST_INTERSECT = 5, + FLANN_DIST_HELLINGER = 6, + FLANN_DIST_CHI_SQUARE = 7, + FLANN_DIST_CS = 7, + FLANN_DIST_KULLBACK_LEIBLER = 8, + FLANN_DIST_KL = 8, + FLANN_DIST_HAMMING = 9, + + // deprecated constants, should use the FLANN_DIST_* ones instead + EUCLIDEAN = 1, + MANHATTAN = 2, + MINKOWSKI = 3, + MAX_DIST = 4, + HIST_INTERSECT = 5, + HELLINGER = 6, + CS = 7, + KL = 8, + KULLBACK_LEIBLER = 8 +}; + +enum flann_datatype_t +{ + FLANN_INT8 = 0, + FLANN_INT16 = 1, + FLANN_INT32 = 2, + FLANN_INT64 = 3, + FLANN_UINT8 = 4, + FLANN_UINT16 = 5, + FLANN_UINT32 = 6, + FLANN_UINT64 = 7, + FLANN_FLOAT32 = 8, + FLANN_FLOAT64 = 9 +}; + +enum +{ + FLANN_CHECKS_UNLIMITED = -1, + FLANN_CHECKS_AUTOTUNED = -2 +}; + +} + +#endif /* OPENCV_FLANN_DEFINES_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/dist.h b/3rdparty/opencv/include/opencv2/flann/dist.h new file mode 100644 index 00000000..2bb4fc94 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/dist.h @@ -0,0 +1,904 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_DIST_H_ +#define OPENCV_FLANN_DIST_H_ + +#include +#include +#include +#ifdef _MSC_VER +typedef unsigned __int32 uint32_t; +typedef unsigned __int64 uint64_t; +#else +#include +#endif + +#include "defines.h" + +#if defined _WIN32 && defined(_M_ARM) +# include +#endif + +#if defined(__ARM_NEON__) && !defined(__CUDACC__) +# include "arm_neon.h" +#endif + +namespace cvflann +{ + +template +inline T abs(T x) { return (x<0) ? -x : x; } + +template<> +inline int abs(int x) { return ::abs(x); } + +template<> +inline float abs(float x) { return fabsf(x); } + +template<> +inline double abs(double x) { return fabs(x); } + +template +struct Accumulator { typedef T Type; }; +template<> +struct Accumulator { typedef float Type; }; +template<> +struct Accumulator { typedef float Type; }; +template<> +struct Accumulator { typedef float Type; }; +template<> +struct Accumulator { typedef float Type; }; +template<> +struct Accumulator { typedef float Type; }; +template<> +struct Accumulator { typedef float Type; }; + +#undef True +#undef False + +class True +{ +}; + +class False +{ +}; + + +/** + * Squared Euclidean distance functor. + * + * This is the simpler, unrolled version. This is preferable for + * very low dimensionality data (eg 3D points) + */ +template +struct L2_Simple +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType /*worst_dist*/ = -1) const + { + ResultType result = ResultType(); + ResultType diff; + for(size_t i = 0; i < size; ++i ) { + diff = *a++ - *b++; + result += diff*diff; + } + return result; + } + + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + return (a-b)*(a-b); + } +}; + + + +/** + * Squared Euclidean distance functor, optimized version + */ +template +struct L2 +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the squared Euclidean distance between two vectors. + * + * This is highly optimised, with loop unrolling, as it is one + * of the most expensive inner loops. + * + * The computation of squared root at the end is omitted for + * efficiency. + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType diff0, diff1, diff2, diff3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + diff0 = (ResultType)(a[0] - b[0]); + diff1 = (ResultType)(a[1] - b[1]); + diff2 = (ResultType)(a[2] - b[2]); + diff3 = (ResultType)(a[3] - b[3]); + result += diff0 * diff0 + diff1 * diff1 + diff2 * diff2 + diff3 * diff3; + a += 4; + b += 4; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + /* Process last 0-3 pixels. Not needed for standard vector lengths. */ + while (a < last) { + diff0 = (ResultType)(*a++ - *b++); + result += diff0 * diff0; + } + return result; + } + + /** + * Partial euclidean distance, using just one dimension. This is used by the + * kd-tree when computing partial distances while traversing the tree. + * + * Squared root is omitted for efficiency. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + return (a-b)*(a-b); + } +}; + + +/* + * Manhattan distance functor, optimized version + */ +template +struct L1 +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the Manhattan (L_1) distance between two vectors. + * + * This is highly optimised, with loop unrolling, as it is one + * of the most expensive inner loops. + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType diff0, diff1, diff2, diff3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + diff0 = (ResultType)abs(a[0] - b[0]); + diff1 = (ResultType)abs(a[1] - b[1]); + diff2 = (ResultType)abs(a[2] - b[2]); + diff3 = (ResultType)abs(a[3] - b[3]); + result += diff0 + diff1 + diff2 + diff3; + a += 4; + b += 4; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + /* Process last 0-3 pixels. Not needed for standard vector lengths. */ + while (a < last) { + diff0 = (ResultType)abs(*a++ - *b++); + result += diff0; + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + return abs(a-b); + } +}; + + + +template +struct MinkowskiDistance +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + int order; + + MinkowskiDistance(int order_) : order(order_) {} + + /** + * Compute the Minkowsky (L_p) distance between two vectors. + * + * This is highly optimised, with loop unrolling, as it is one + * of the most expensive inner loops. + * + * The computation of squared root at the end is omitted for + * efficiency. + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType diff0, diff1, diff2, diff3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + diff0 = (ResultType)abs(a[0] - b[0]); + diff1 = (ResultType)abs(a[1] - b[1]); + diff2 = (ResultType)abs(a[2] - b[2]); + diff3 = (ResultType)abs(a[3] - b[3]); + result += pow(diff0,order) + pow(diff1,order) + pow(diff2,order) + pow(diff3,order); + a += 4; + b += 4; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + /* Process last 0-3 pixels. Not needed for standard vector lengths. */ + while (a < last) { + diff0 = (ResultType)abs(*a++ - *b++); + result += pow(diff0,order); + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + return pow(static_cast(abs(a-b)),order); + } +}; + + + +template +struct MaxDistance +{ + typedef False is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the max distance (L_infinity) between two vectors. + * + * This distance is not a valid kdtree distance, it's not dimensionwise additive. + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType diff0, diff1, diff2, diff3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + diff0 = abs(a[0] - b[0]); + diff1 = abs(a[1] - b[1]); + diff2 = abs(a[2] - b[2]); + diff3 = abs(a[3] - b[3]); + if (diff0>result) {result = diff0; } + if (diff1>result) {result = diff1; } + if (diff2>result) {result = diff2; } + if (diff3>result) {result = diff3; } + a += 4; + b += 4; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + /* Process last 0-3 pixels. Not needed for standard vector lengths. */ + while (a < last) { + diff0 = abs(*a++ - *b++); + result = (diff0>result) ? diff0 : result; + } + return result; + } + + /* This distance functor is not dimension-wise additive, which + * makes it an invalid kd-tree distance, not implementing the accum_dist method */ + +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** + * Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor + * bit count of A exclusive XOR'ed with B + */ +struct HammingLUT +{ + typedef False is_kdtree_distance; + typedef False is_vector_space_distance; + + typedef unsigned char ElementType; + typedef int ResultType; + + /** this will count the bits in a ^ b + */ + ResultType operator()(const unsigned char* a, const unsigned char* b, size_t size) const + { + static const uchar popCountTable[] = + { + 0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4, 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, + 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8 + }; + ResultType result = 0; + for (size_t i = 0; i < size; i++) { + result += popCountTable[a[i] ^ b[i]]; + } + return result; + } +}; + +/** + * Hamming distance functor (pop count between two binary vectors, i.e. xor them and count the number of bits set) + * That code was taken from brief.cpp in OpenCV + */ +template +struct Hamming +{ + typedef False is_kdtree_distance; + typedef False is_vector_space_distance; + + + typedef T ElementType; + typedef int ResultType; + + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType /*worst_dist*/ = -1) const + { + ResultType result = 0; +#if defined(__ARM_NEON__) && !defined(__CUDACC__) + { + uint32x4_t bits = vmovq_n_u32(0); + for (size_t i = 0; i < size; i += 16) { + uint8x16_t A_vec = vld1q_u8 (a + i); + uint8x16_t B_vec = vld1q_u8 (b + i); + uint8x16_t AxorB = veorq_u8 (A_vec, B_vec); + uint8x16_t bitsSet = vcntq_u8 (AxorB); + uint16x8_t bitSet8 = vpaddlq_u8 (bitsSet); + uint32x4_t bitSet4 = vpaddlq_u16 (bitSet8); + bits = vaddq_u32(bits, bitSet4); + } + uint64x2_t bitSet2 = vpaddlq_u32 (bits); + result = vgetq_lane_s32 (vreinterpretq_s32_u64(bitSet2),0); + result += vgetq_lane_s32 (vreinterpretq_s32_u64(bitSet2),2); + } +#elif __GNUC__ + { + //for portability just use unsigned long -- and use the __builtin_popcountll (see docs for __builtin_popcountll) + typedef unsigned long long pop_t; + const size_t modulo = size % sizeof(pop_t); + const pop_t* a2 = reinterpret_cast (a); + const pop_t* b2 = reinterpret_cast (b); + const pop_t* a2_end = a2 + (size / sizeof(pop_t)); + + for (; a2 != a2_end; ++a2, ++b2) result += __builtin_popcountll((*a2) ^ (*b2)); + + if (modulo) { + //in the case where size is not dividable by sizeof(size_t) + //need to mask off the bits at the end + pop_t a_final = 0, b_final = 0; + memcpy(&a_final, a2, modulo); + memcpy(&b_final, b2, modulo); + result += __builtin_popcountll(a_final ^ b_final); + } + } +#else // NO NEON and NOT GNUC + HammingLUT lut; + result = lut(reinterpret_cast (a), + reinterpret_cast (b), size); +#endif + return result; + } +}; + +template +struct Hamming2 +{ + typedef False is_kdtree_distance; + typedef False is_vector_space_distance; + + typedef T ElementType; + typedef int ResultType; + + /** This is popcount_3() from: + * http://en.wikipedia.org/wiki/Hamming_weight */ + unsigned int popcnt32(uint32_t n) const + { + n -= ((n >> 1) & 0x55555555); + n = (n & 0x33333333) + ((n >> 2) & 0x33333333); + return (((n + (n >> 4))& 0xF0F0F0F)* 0x1010101) >> 24; + } + +#ifdef FLANN_PLATFORM_64_BIT + unsigned int popcnt64(uint64_t n) const + { + n -= ((n >> 1) & 0x5555555555555555); + n = (n & 0x3333333333333333) + ((n >> 2) & 0x3333333333333333); + return (((n + (n >> 4))& 0x0f0f0f0f0f0f0f0f)* 0x0101010101010101) >> 56; + } +#endif + + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType /*worst_dist*/ = -1) const + { +#ifdef FLANN_PLATFORM_64_BIT + const uint64_t* pa = reinterpret_cast(a); + const uint64_t* pb = reinterpret_cast(b); + ResultType result = 0; + size /= (sizeof(uint64_t)/sizeof(unsigned char)); + for(size_t i = 0; i < size; ++i ) { + result += popcnt64(*pa ^ *pb); + ++pa; + ++pb; + } +#else + const uint32_t* pa = reinterpret_cast(a); + const uint32_t* pb = reinterpret_cast(b); + ResultType result = 0; + size /= (sizeof(uint32_t)/sizeof(unsigned char)); + for(size_t i = 0; i < size; ++i ) { + result += popcnt32(*pa ^ *pb); + ++pa; + ++pb; + } +#endif + return result; + } +}; + + + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +template +struct HistIntersectionDistance +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the histogram intersection distance + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType min0, min1, min2, min3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + min0 = (ResultType)(a[0] < b[0] ? a[0] : b[0]); + min1 = (ResultType)(a[1] < b[1] ? a[1] : b[1]); + min2 = (ResultType)(a[2] < b[2] ? a[2] : b[2]); + min3 = (ResultType)(a[3] < b[3] ? a[3] : b[3]); + result += min0 + min1 + min2 + min3; + a += 4; + b += 4; + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + /* Process last 0-3 pixels. Not needed for standard vector lengths. */ + while (a < last) { + min0 = (ResultType)(*a < *b ? *a : *b); + result += min0; + ++a; + ++b; + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + return a +struct HellingerDistance +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the Hellinger distance + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType /*worst_dist*/ = -1) const + { + ResultType result = ResultType(); + ResultType diff0, diff1, diff2, diff3; + Iterator1 last = a + size; + Iterator1 lastgroup = last - 3; + + /* Process 4 items with each loop for efficiency. */ + while (a < lastgroup) { + diff0 = sqrt(static_cast(a[0])) - sqrt(static_cast(b[0])); + diff1 = sqrt(static_cast(a[1])) - sqrt(static_cast(b[1])); + diff2 = sqrt(static_cast(a[2])) - sqrt(static_cast(b[2])); + diff3 = sqrt(static_cast(a[3])) - sqrt(static_cast(b[3])); + result += diff0 * diff0 + diff1 * diff1 + diff2 * diff2 + diff3 * diff3; + a += 4; + b += 4; + } + while (a < last) { + diff0 = sqrt(static_cast(*a++)) - sqrt(static_cast(*b++)); + result += diff0 * diff0; + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + ResultType diff = sqrt(static_cast(a)) - sqrt(static_cast(b)); + return diff * diff; + } +}; + + +template +struct ChiSquareDistance +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the chi-square distance + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + ResultType sum, diff; + Iterator1 last = a + size; + + while (a < last) { + sum = (ResultType)(*a + *b); + if (sum>0) { + diff = (ResultType)(*a - *b); + result += diff*diff/sum; + } + ++a; + ++b; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + ResultType result = ResultType(); + ResultType sum, diff; + + sum = (ResultType)(a+b); + if (sum>0) { + diff = (ResultType)(a-b); + result = diff*diff/sum; + } + return result; + } +}; + + +template +struct KL_Divergence +{ + typedef True is_kdtree_distance; + typedef True is_vector_space_distance; + + typedef T ElementType; + typedef typename Accumulator::Type ResultType; + + /** + * Compute the Kullback-Leibler divergence + */ + template + ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const + { + ResultType result = ResultType(); + Iterator1 last = a + size; + + while (a < last) { + if (* b != 0) { + ResultType ratio = (ResultType)(*a / *b); + if (ratio>0) { + result += *a * log(ratio); + } + } + ++a; + ++b; + + if ((worst_dist>0)&&(result>worst_dist)) { + return result; + } + } + return result; + } + + /** + * Partial distance, used by the kd-tree. + */ + template + inline ResultType accum_dist(const U& a, const V& b, int) const + { + ResultType result = ResultType(); + if( *b != 0 ) { + ResultType ratio = (ResultType)(a / b); + if (ratio>0) { + result = a * log(ratio); + } + } + return result; + } +}; + + + +/* + * This is a "zero iterator". It basically behaves like a zero filled + * array to all algorithms that use arrays as iterators (STL style). + * It's useful when there's a need to compute the distance between feature + * and origin it and allows for better compiler optimisation than using a + * zero-filled array. + */ +template +struct ZeroIterator +{ + + T operator*() + { + return 0; + } + + T operator[](int) + { + return 0; + } + + const ZeroIterator& operator ++() + { + return *this; + } + + ZeroIterator operator ++(int) + { + return *this; + } + + ZeroIterator& operator+=(int) + { + return *this; + } + +}; + + +/* + * Depending on processed distances, some of them are already squared (e.g. L2) + * and some are not (e.g.Hamming). In KMeans++ for instance we want to be sure + * we are working on ^2 distances, thus following templates to ensure that. + */ +template +struct squareDistance +{ + typedef typename Distance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist*dist; } +}; + + +template +struct squareDistance, ElementType> +{ + typedef typename L2_Simple::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + +template +struct squareDistance, ElementType> +{ + typedef typename L2::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + + +template +struct squareDistance, ElementType> +{ + typedef typename MinkowskiDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + +template +struct squareDistance, ElementType> +{ + typedef typename HellingerDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + +template +struct squareDistance, ElementType> +{ + typedef typename ChiSquareDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + + +template +typename Distance::ResultType ensureSquareDistance( typename Distance::ResultType dist ) +{ + typedef typename Distance::ElementType ElementType; + + squareDistance dummy; + return dummy( dist ); +} + + +/* + * ...and a template to ensure the user that he will process the normal distance, + * and not squared distance, without losing processing time calling sqrt(ensureSquareDistance) + * that will result in doing actually sqrt(dist*dist) for L1 distance for instance. + */ +template +struct simpleDistance +{ + typedef typename Distance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return dist; } +}; + + +template +struct simpleDistance, ElementType> +{ + typedef typename L2_Simple::ResultType ResultType; + ResultType operator()( ResultType dist ) { return sqrt(dist); } +}; + +template +struct simpleDistance, ElementType> +{ + typedef typename L2::ResultType ResultType; + ResultType operator()( ResultType dist ) { return sqrt(dist); } +}; + + +template +struct simpleDistance, ElementType> +{ + typedef typename MinkowskiDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return sqrt(dist); } +}; + +template +struct simpleDistance, ElementType> +{ + typedef typename HellingerDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return sqrt(dist); } +}; + +template +struct simpleDistance, ElementType> +{ + typedef typename ChiSquareDistance::ResultType ResultType; + ResultType operator()( ResultType dist ) { return sqrt(dist); } +}; + + +template +typename Distance::ResultType ensureSimpleDistance( typename Distance::ResultType dist ) +{ + typedef typename Distance::ElementType ElementType; + + simpleDistance dummy; + return dummy( dist ); +} + +} + +#endif //OPENCV_FLANN_DIST_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/dummy.h b/3rdparty/opencv/include/opencv2/flann/dummy.h new file mode 100644 index 00000000..d6837e53 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/dummy.h @@ -0,0 +1,13 @@ + +#ifndef OPENCV_FLANN_DUMMY_H_ +#define OPENCV_FLANN_DUMMY_H_ + +namespace cvflann +{ + +CV_DEPRECATED inline void dummyfunc() {} + +} + + +#endif /* OPENCV_FLANN_DUMMY_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/dynamic_bitset.h b/3rdparty/opencv/include/opencv2/flann/dynamic_bitset.h new file mode 100644 index 00000000..923b6583 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/dynamic_bitset.h @@ -0,0 +1,159 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +/*********************************************************************** + * Author: Vincent Rabaud + *************************************************************************/ + +#ifndef OPENCV_FLANN_DYNAMIC_BITSET_H_ +#define OPENCV_FLANN_DYNAMIC_BITSET_H_ + +#ifndef FLANN_USE_BOOST +# define FLANN_USE_BOOST 0 +#endif +//#define FLANN_USE_BOOST 1 +#if FLANN_USE_BOOST +#include +typedef boost::dynamic_bitset<> DynamicBitset; +#else + +#include + +#include "dist.h" + +namespace cvflann { + +/** Class re-implementing the boost version of it + * This helps not depending on boost, it also does not do the bound checks + * and has a way to reset a block for speed + */ +class DynamicBitset +{ +public: + /** default constructor + */ + DynamicBitset() : size_(0) + { + } + + /** only constructor we use in our code + * @param sz the size of the bitset (in bits) + */ + DynamicBitset(size_t sz) + { + resize(sz); + reset(); + } + + /** Sets all the bits to 0 + */ + void clear() + { + std::fill(bitset_.begin(), bitset_.end(), 0); + } + + /** @brief checks if the bitset is empty + * @return true if the bitset is empty + */ + bool empty() const + { + return bitset_.empty(); + } + + /** set all the bits to 0 + */ + void reset() + { + std::fill(bitset_.begin(), bitset_.end(), 0); + } + + /** @brief set one bit to 0 + * @param index + */ + void reset(size_t index) + { + bitset_[index / cell_bit_size_] &= ~(size_t(1) << (index % cell_bit_size_)); + } + + /** @brief sets a specific bit to 0, and more bits too + * This function is useful when resetting a given set of bits so that the + * whole bitset ends up being 0: if that's the case, we don't care about setting + * other bits to 0 + * @param index + */ + void reset_block(size_t index) + { + bitset_[index / cell_bit_size_] = 0; + } + + /** resize the bitset so that it contains at least sz bits + * @param sz + */ + void resize(size_t sz) + { + size_ = sz; + bitset_.resize(sz / cell_bit_size_ + 1); + } + + /** set a bit to true + * @param index the index of the bit to set to 1 + */ + void set(size_t index) + { + bitset_[index / cell_bit_size_] |= size_t(1) << (index % cell_bit_size_); + } + + /** gives the number of contained bits + */ + size_t size() const + { + return size_; + } + + /** check if a bit is set + * @param index the index of the bit to check + * @return true if the bit is set + */ + bool test(size_t index) const + { + return (bitset_[index / cell_bit_size_] & (size_t(1) << (index % cell_bit_size_))) != 0; + } + +private: + std::vector bitset_; + size_t size_; + static const unsigned int cell_bit_size_ = CHAR_BIT * sizeof(size_t); +}; + +} // namespace cvflann + +#endif + +#endif // OPENCV_FLANN_DYNAMIC_BITSET_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/flann.hpp b/3rdparty/opencv/include/opencv2/flann/flann.hpp new file mode 100644 index 00000000..227683f9 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/flann.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/flann.hpp" diff --git a/3rdparty/opencv/include/opencv2/flann/flann_base.hpp b/3rdparty/opencv/include/opencv2/flann/flann_base.hpp new file mode 100644 index 00000000..0ffb857c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/flann_base.hpp @@ -0,0 +1,295 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_BASE_HPP_ +#define OPENCV_FLANN_BASE_HPP_ + +#include +#include +#include + +#include "general.h" +#include "matrix.h" +#include "params.h" +#include "saving.h" + +#include "all_indices.h" + +namespace cvflann +{ + +/** + * Sets the log level used for all flann functions + * @param level Verbosity level + */ +inline void log_verbosity(int level) +{ + if (level >= 0) { + Logger::setLevel(level); + } +} + +/** + * (Deprecated) Index parameters for creating a saved index. + */ +struct SavedIndexParams : public IndexParams +{ + SavedIndexParams(cv::String filename) + { + (* this)["algorithm"] = FLANN_INDEX_SAVED; + (*this)["filename"] = filename; + } +}; + + +template +NNIndex* load_saved_index(const Matrix& dataset, const cv::String& filename, Distance distance) +{ + typedef typename Distance::ElementType ElementType; + + FILE* fin = fopen(filename.c_str(), "rb"); + if (fin == NULL) { + return NULL; + } + IndexHeader header = load_header(fin); + if (header.data_type != Datatype::type()) { + fclose(fin); + throw FLANNException("Datatype of saved index is different than of the one to be created."); + } + if ((size_t(header.rows) != dataset.rows)||(size_t(header.cols) != dataset.cols)) { + fclose(fin); + throw FLANNException("The index saved belongs to a different dataset"); + } + + IndexParams params; + params["algorithm"] = header.index_type; + NNIndex* nnIndex = create_index_by_type(dataset, params, distance); + nnIndex->loadIndex(fin); + fclose(fin); + + return nnIndex; +} + + +template +class Index : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + Index(const Matrix& features, const IndexParams& params, Distance distance = Distance() ) + : index_params_(params) + { + flann_algorithm_t index_type = get_param(params,"algorithm"); + loaded_ = false; + + if (index_type == FLANN_INDEX_SAVED) { + nnIndex_ = load_saved_index(features, get_param(params,"filename"), distance); + loaded_ = true; + } + else { + nnIndex_ = create_index_by_type(features, params, distance); + } + } + + ~Index() + { + delete nnIndex_; + } + + /** + * Builds the index. + */ + void buildIndex() CV_OVERRIDE + { + if (!loaded_) { + nnIndex_->buildIndex(); + } + } + + void save(cv::String filename) + { + FILE* fout = fopen(filename.c_str(), "wb"); + if (fout == NULL) { + throw FLANNException("Cannot open file"); + } + save_header(fout, *nnIndex_); + saveIndex(fout); + fclose(fout); + } + + /** + * \brief Saves the index to a stream + * \param stream The stream to save the index to + */ + virtual void saveIndex(FILE* stream) CV_OVERRIDE + { + nnIndex_->saveIndex(stream); + } + + /** + * \brief Loads the index from a stream + * \param stream The stream from which the index is loaded + */ + virtual void loadIndex(FILE* stream) CV_OVERRIDE + { + nnIndex_->loadIndex(stream); + } + + /** + * \returns number of features in this index. + */ + size_t veclen() const CV_OVERRIDE + { + return nnIndex_->veclen(); + } + + /** + * \returns The dimensionality of the features in this index. + */ + size_t size() const CV_OVERRIDE + { + return nnIndex_->size(); + } + + /** + * \returns The index type (kdtree, kmeans,...) + */ + flann_algorithm_t getType() const CV_OVERRIDE + { + return nnIndex_->getType(); + } + + /** + * \returns The amount of memory (in bytes) used by the index. + */ + virtual int usedMemory() const CV_OVERRIDE + { + return nnIndex_->usedMemory(); + } + + + /** + * \returns The index parameters + */ + IndexParams getParameters() const CV_OVERRIDE + { + return nnIndex_->getParameters(); + } + + /** + * \brief Perform k-nearest neighbor search + * \param[in] queries The query points for which to find the nearest neighbors + * \param[out] indices The indices of the nearest neighbors found + * \param[out] dists Distances to the nearest neighbors found + * \param[in] knn Number of nearest neighbors to return + * \param[in] params Search parameters + */ + void knnSearch(const Matrix& queries, Matrix& indices, Matrix& dists, int knn, const SearchParams& params) CV_OVERRIDE + { + nnIndex_->knnSearch(queries, indices, dists, knn, params); + } + + /** + * \brief Perform radius search + * \param[in] query The query point + * \param[out] indices The indinces of the neighbors found within the given radius + * \param[out] dists The distances to the nearest neighbors found + * \param[in] radius The radius used for search + * \param[in] params Search parameters + * \returns Number of neighbors found + */ + int radiusSearch(const Matrix& query, Matrix& indices, Matrix& dists, float radius, const SearchParams& params) CV_OVERRIDE + { + return nnIndex_->radiusSearch(query, indices, dists, radius, params); + } + + /** + * \brief Method that searches for nearest-neighbours + */ + void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + nnIndex_->findNeighbors(result, vec, searchParams); + } + + /** + * \brief Returns actual index + */ + CV_DEPRECATED NNIndex* getIndex() + { + return nnIndex_; + } + + /** + * \brief Returns index parameters. + * \deprecated use getParameters() instead. + */ + CV_DEPRECATED const IndexParams* getIndexParameters() + { + return &index_params_; + } + +private: + /** Pointer to actual index class */ + NNIndex* nnIndex_; + /** Indices if the index was loaded from a file */ + bool loaded_; + /** Parameters passed to the index */ + IndexParams index_params_; + + Index(const Index &); // copy disabled + Index& operator=(const Index &); // assign disabled +}; + +/** + * Performs a hierarchical clustering of the points passed as argument and then takes a cut in the + * the clustering tree to return a flat clustering. + * @param[in] points Points to be clustered + * @param centers The computed cluster centres. Matrix should be preallocated and centers.rows is the + * number of clusters requested. + * @param params Clustering parameters (The same as for cvflann::KMeansIndex) + * @param d Distance to be used for clustering (eg: cvflann::L2) + * @return number of clusters computed (can be different than clusters.rows and is the highest number + * of the form (branching-1)*K+1 smaller than clusters.rows). + */ +template +int hierarchicalClustering(const Matrix& points, Matrix& centers, + const KMeansIndexParams& params, Distance d = Distance()) +{ + KMeansIndex kmeans(points, params, d); + kmeans.buildIndex(); + + int clusterNum = kmeans.getClusterCenters(centers); + return clusterNum; +} + +} +#endif /* OPENCV_FLANN_BASE_HPP_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/general.h b/3rdparty/opencv/include/opencv2/flann/general.h new file mode 100644 index 00000000..9d5402a6 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/general.h @@ -0,0 +1,50 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_GENERAL_H_ +#define OPENCV_FLANN_GENERAL_H_ + +#include "opencv2/core.hpp" + +namespace cvflann +{ + +class FLANNException : public cv::Exception +{ +public: + FLANNException(const char* message) : cv::Exception(0, message, "", __FILE__, __LINE__) { } + + FLANNException(const cv::String& message) : cv::Exception(0, message, "", __FILE__, __LINE__) { } +}; + +} + + +#endif /* OPENCV_FLANN_GENERAL_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/ground_truth.h b/3rdparty/opencv/include/opencv2/flann/ground_truth.h new file mode 100644 index 00000000..fd8f3ae7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/ground_truth.h @@ -0,0 +1,94 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_GROUND_TRUTH_H_ +#define OPENCV_FLANN_GROUND_TRUTH_H_ + +#include "dist.h" +#include "matrix.h" + + +namespace cvflann +{ + +template +void find_nearest(const Matrix& dataset, typename Distance::ElementType* query, int* matches, int nn, + int skip = 0, Distance distance = Distance()) +{ + typedef typename Distance::ResultType DistanceType; + int n = nn + skip; + + std::vector match(n); + std::vector dists(n); + + dists[0] = distance(dataset[0], query, dataset.cols); + match[0] = 0; + int dcnt = 1; + + for (size_t i=1; i=1 && dists[j] +void compute_ground_truth(const Matrix& dataset, const Matrix& testset, Matrix& matches, + int skip=0, Distance d = Distance()) +{ + for (size_t i=0; i(dataset, testset[i], matches[i], (int)matches.cols, skip, d); + } +} + + +} + +#endif //OPENCV_FLANN_GROUND_TRUTH_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/hdf5.h b/3rdparty/opencv/include/opencv2/flann/hdf5.h new file mode 100644 index 00000000..80d23b97 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/hdf5.h @@ -0,0 +1,231 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_HDF5_H_ +#define OPENCV_FLANN_HDF5_H_ + +#include + +#include "matrix.h" + + +namespace cvflann +{ + +namespace +{ + +template +hid_t get_hdf5_type() +{ + throw FLANNException("Unsupported type for IO operations"); +} + +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_CHAR; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_UCHAR; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_SHORT; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_USHORT; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_INT; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_UINT; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_LONG; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_ULONG; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_FLOAT; } +template<> +hid_t get_hdf5_type() { return H5T_NATIVE_DOUBLE; } +} + + +#define CHECK_ERROR(x,y) if ((x)<0) throw FLANNException((y)); + +template +void save_to_file(const cvflann::Matrix& dataset, const String& filename, const String& name) +{ + +#if H5Eset_auto_vers == 2 + H5Eset_auto( H5E_DEFAULT, NULL, NULL ); +#else + H5Eset_auto( NULL, NULL ); +#endif + + herr_t status; + hid_t file_id; + file_id = H5Fopen(filename.c_str(), H5F_ACC_RDWR, H5P_DEFAULT); + if (file_id < 0) { + file_id = H5Fcreate(filename.c_str(), H5F_ACC_EXCL, H5P_DEFAULT, H5P_DEFAULT); + } + CHECK_ERROR(file_id,"Error creating hdf5 file."); + + hsize_t dimsf[2]; // dataset dimensions + dimsf[0] = dataset.rows; + dimsf[1] = dataset.cols; + + hid_t space_id = H5Screate_simple(2, dimsf, NULL); + hid_t memspace_id = H5Screate_simple(2, dimsf, NULL); + + hid_t dataset_id; +#if H5Dcreate_vers == 2 + dataset_id = H5Dcreate2(file_id, name.c_str(), get_hdf5_type(), space_id, H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); +#else + dataset_id = H5Dcreate(file_id, name.c_str(), get_hdf5_type(), space_id, H5P_DEFAULT); +#endif + + if (dataset_id<0) { +#if H5Dopen_vers == 2 + dataset_id = H5Dopen2(file_id, name.c_str(), H5P_DEFAULT); +#else + dataset_id = H5Dopen(file_id, name.c_str()); +#endif + } + CHECK_ERROR(dataset_id,"Error creating or opening dataset in file."); + + status = H5Dwrite(dataset_id, get_hdf5_type(), memspace_id, space_id, H5P_DEFAULT, dataset.data ); + CHECK_ERROR(status, "Error writing to dataset"); + + H5Sclose(memspace_id); + H5Sclose(space_id); + H5Dclose(dataset_id); + H5Fclose(file_id); + +} + + +template +void load_from_file(cvflann::Matrix& dataset, const String& filename, const String& name) +{ + herr_t status; + hid_t file_id = H5Fopen(filename.c_str(), H5F_ACC_RDWR, H5P_DEFAULT); + CHECK_ERROR(file_id,"Error opening hdf5 file."); + + hid_t dataset_id; +#if H5Dopen_vers == 2 + dataset_id = H5Dopen2(file_id, name.c_str(), H5P_DEFAULT); +#else + dataset_id = H5Dopen(file_id, name.c_str()); +#endif + CHECK_ERROR(dataset_id,"Error opening dataset in file."); + + hid_t space_id = H5Dget_space(dataset_id); + + hsize_t dims_out[2]; + H5Sget_simple_extent_dims(space_id, dims_out, NULL); + + dataset = cvflann::Matrix(new T[dims_out[0]*dims_out[1]], dims_out[0], dims_out[1]); + + status = H5Dread(dataset_id, get_hdf5_type(), H5S_ALL, H5S_ALL, H5P_DEFAULT, dataset[0]); + CHECK_ERROR(status, "Error reading dataset"); + + H5Sclose(space_id); + H5Dclose(dataset_id); + H5Fclose(file_id); +} + + +#ifdef HAVE_MPI + +namespace mpi +{ +/** + * Loads a the hyperslice corresponding to this processor from a hdf5 file. + * @param flann_dataset Dataset where the data is loaded + * @param filename HDF5 file name + * @param name Name of dataset inside file + */ +template +void load_from_file(cvflann::Matrix& dataset, const String& filename, const String& name) +{ + MPI_Comm comm = MPI_COMM_WORLD; + MPI_Info info = MPI_INFO_NULL; + + int mpi_size, mpi_rank; + MPI_Comm_size(comm, &mpi_size); + MPI_Comm_rank(comm, &mpi_rank); + + herr_t status; + + hid_t plist_id = H5Pcreate(H5P_FILE_ACCESS); + H5Pset_fapl_mpio(plist_id, comm, info); + hid_t file_id = H5Fopen(filename.c_str(), H5F_ACC_RDWR, plist_id); + CHECK_ERROR(file_id,"Error opening hdf5 file."); + H5Pclose(plist_id); + hid_t dataset_id; +#if H5Dopen_vers == 2 + dataset_id = H5Dopen2(file_id, name.c_str(), H5P_DEFAULT); +#else + dataset_id = H5Dopen(file_id, name.c_str()); +#endif + CHECK_ERROR(dataset_id,"Error opening dataset in file."); + + hid_t space_id = H5Dget_space(dataset_id); + hsize_t dims[2]; + H5Sget_simple_extent_dims(space_id, dims, NULL); + + hsize_t count[2]; + hsize_t offset[2]; + + hsize_t item_cnt = dims[0]/mpi_size+(dims[0]%mpi_size==0 ? 0 : 1); + hsize_t cnt = (mpi_rank(), memspace_id, space_id, plist_id, dataset.data); + CHECK_ERROR(status, "Error reading dataset"); + + H5Pclose(plist_id); + H5Sclose(space_id); + H5Sclose(memspace_id); + H5Dclose(dataset_id); + H5Fclose(file_id); +} +} +#endif // HAVE_MPI +} // namespace cvflann::mpi + +#endif /* OPENCV_FLANN_HDF5_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/heap.h b/3rdparty/opencv/include/opencv2/flann/heap.h new file mode 100644 index 00000000..92a6ea61 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/heap.h @@ -0,0 +1,165 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_HEAP_H_ +#define OPENCV_FLANN_HEAP_H_ + +#include +#include + +namespace cvflann +{ + +/** + * Priority Queue Implementation + * + * The priority queue is implemented with a heap. A heap is a complete + * (full) binary tree in which each parent is less than both of its + * children, but the order of the children is unspecified. + */ +template +class Heap +{ + + /** + * Storage array for the heap. + * Type T must be comparable. + */ + std::vector heap; + int length; + + /** + * Number of element in the heap + */ + int count; + + + +public: + /** + * Constructor. + * + * Params: + * sz = heap size + */ + + Heap(int sz) + { + length = sz; + heap.reserve(length); + count = 0; + } + + /** + * + * Returns: heap size + */ + int size() + { + return count; + } + + /** + * Tests if the heap is empty + * + * Returns: true is heap empty, false otherwise + */ + bool empty() + { + return size()==0; + } + + /** + * Clears the heap. + */ + void clear() + { + heap.clear(); + count = 0; + } + + struct CompareT + { + bool operator()(const T& t_1, const T& t_2) const + { + return t_2 < t_1; + } + }; + + /** + * Insert a new element in the heap. + * + * We select the next empty leaf node, and then keep moving any larger + * parents down until the right location is found to store this element. + * + * Params: + * value = the new element to be inserted in the heap + */ + void insert(T value) + { + /* If heap is full, then return without adding this element. */ + if (count == length) { + return; + } + + heap.push_back(value); + static CompareT compareT; + std::push_heap(heap.begin(), heap.end(), compareT); + ++count; + } + + + + /** + * Returns the node of minimum value from the heap (top of the heap). + * + * Params: + * value = out parameter used to return the min element + * Returns: false if heap empty + */ + bool popMin(T& value) + { + if (count == 0) { + return false; + } + + value = heap[0]; + static CompareT compareT; + std::pop_heap(heap.begin(), heap.end(), compareT); + heap.pop_back(); + --count; + + return true; /* Return old last node. */ + } +}; + +} + +#endif //OPENCV_FLANN_HEAP_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/hierarchical_clustering_index.h b/3rdparty/opencv/include/opencv2/flann/hierarchical_clustering_index.h new file mode 100644 index 00000000..2a947dab --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/hierarchical_clustering_index.h @@ -0,0 +1,848 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2011 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2011 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_HIERARCHICAL_CLUSTERING_INDEX_H_ +#define OPENCV_FLANN_HIERARCHICAL_CLUSTERING_INDEX_H_ + +#include +#include +#include +#include +#include + +#include "general.h" +#include "nn_index.h" +#include "dist.h" +#include "matrix.h" +#include "result_set.h" +#include "heap.h" +#include "allocator.h" +#include "random.h" +#include "saving.h" + + +namespace cvflann +{ + +struct HierarchicalClusteringIndexParams : public IndexParams +{ + HierarchicalClusteringIndexParams(int branching = 32, + flann_centers_init_t centers_init = FLANN_CENTERS_RANDOM, + int trees = 4, int leaf_size = 100) + { + (*this)["algorithm"] = FLANN_INDEX_HIERARCHICAL; + // The branching factor used in the hierarchical clustering + (*this)["branching"] = branching; + // Algorithm used for picking the initial cluster centers + (*this)["centers_init"] = centers_init; + // number of parallel trees to build + (*this)["trees"] = trees; + // maximum leaf size + (*this)["leaf_size"] = leaf_size; + } +}; + + +/** + * Hierarchical index + * + * Contains a tree constructed through a hierarchical clustering + * and other information for indexing a set of points for nearest-neighbour matching. + */ +template +class HierarchicalClusteringIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + +private: + + + typedef void (HierarchicalClusteringIndex::* centersAlgFunction)(int, int*, int, int*, int&); + + /** + * The function used for choosing the cluster centers. + */ + centersAlgFunction chooseCenters; + + + + /** + * Chooses the initial centers in the k-means clustering in a random manner. + * + * Params: + * k = number of centers + * vecs = the dataset of points + * indices = indices in the dataset + * indices_length = length of indices vector + * + */ + void chooseCentersRandom(int k, int* dsindices, int indices_length, int* centers, int& centers_length) + { + UniqueRandom r(indices_length); + + int index; + for (index=0; index=0 && rnd < n); + + centers[0] = dsindices[rnd]; + + int index; + for (index=1; indexbest_val) { + best_val = dist; + best_index = j; + } + } + if (best_index!=-1) { + centers[index] = dsindices[best_index]; + } + else { + break; + } + } + centers_length = index; + } + + + /** + * Chooses the initial centers in the k-means using the algorithm + * proposed in the KMeans++ paper: + * Arthur, David; Vassilvitskii, Sergei - k-means++: The Advantages of Careful Seeding + * + * Implementation of this function was converted from the one provided in Arthur's code. + * + * Params: + * k = number of centers + * vecs = the dataset of points + * indices = indices in the dataset + * Returns: + */ + void chooseCentersKMeanspp(int k, int* dsindices, int indices_length, int* centers, int& centers_length) + { + int n = indices_length; + + double currentPot = 0; + DistanceType* closestDistSq = new DistanceType[n]; + + // Choose one random center and set the closestDistSq values + int index = rand_int(n); + assert(index >=0 && index < n); + centers[0] = dsindices[index]; + + // Computing distance^2 will have the advantage of even higher probability further to pick new centers + // far from previous centers (and this complies to "k-means++: the advantages of careful seeding" article) + for (int i = 0; i < n; i++) { + closestDistSq[i] = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); + closestDistSq[i] = ensureSquareDistance( closestDistSq[i] ); + currentPot += closestDistSq[i]; + } + + + const int numLocalTries = 1; + + // Choose each center + int centerCount; + for (centerCount = 1; centerCount < k; centerCount++) { + + // Repeat several trials + double bestNewPot = -1; + int bestNewIndex = 0; + for (int localTrial = 0; localTrial < numLocalTries; localTrial++) { + + // Choose our center - have to be slightly careful to return a valid answer even accounting + // for possible rounding errors + double randVal = rand_double(currentPot); + for (index = 0; index < n-1; index++) { + if (randVal <= closestDistSq[index]) break; + else randVal -= closestDistSq[index]; + } + + // Compute the new potential + double newPot = 0; + for (int i = 0; i < n; i++) { + DistanceType dist = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); + newPot += std::min( ensureSquareDistance(dist), closestDistSq[i] ); + } + + // Store the best result + if ((bestNewPot < 0)||(newPot < bestNewPot)) { + bestNewPot = newPot; + bestNewIndex = index; + } + } + + // Add the appropriate center + centers[centerCount] = dsindices[bestNewIndex]; + currentPot = bestNewPot; + for (int i = 0; i < n; i++) { + DistanceType dist = distance(dataset[dsindices[i]], dataset[dsindices[bestNewIndex]], dataset.cols); + closestDistSq[i] = std::min( ensureSquareDistance(dist), closestDistSq[i] ); + } + } + + centers_length = centerCount; + + delete[] closestDistSq; + } + + + /** + * Chooses the initial centers in a way inspired by Gonzales (by Pierre-Emmanuel Viel): + * select the first point of the list as a candidate, then parse the points list. If another + * point is further than current candidate from the other centers, test if it is a good center + * of a local aggregation. If it is, replace current candidate by this point. And so on... + * + * Used with KMeansIndex that computes centers coordinates by averaging positions of clusters points, + * this doesn't make a real difference with previous methods. But used with HierarchicalClusteringIndex + * class that pick centers among existing points instead of computing the barycenters, there is a real + * improvement. + * + * Params: + * k = number of centers + * vecs = the dataset of points + * indices = indices in the dataset + * Returns: + */ + void GroupWiseCenterChooser(int k, int* dsindices, int indices_length, int* centers, int& centers_length) + { + const float kSpeedUpFactor = 1.3f; + + int n = indices_length; + + DistanceType* closestDistSq = new DistanceType[n]; + + // Choose one random center and set the closestDistSq values + int index = rand_int(n); + assert(index >=0 && index < n); + centers[0] = dsindices[index]; + + for (int i = 0; i < n; i++) { + closestDistSq[i] = distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols); + } + + + // Choose each center + int centerCount; + for (centerCount = 1; centerCount < k; centerCount++) { + + // Repeat several trials + double bestNewPot = -1; + int bestNewIndex = 0; + DistanceType furthest = 0; + for (index = 0; index < n; index++) { + + // We will test only the potential of the points further than current candidate + if( closestDistSq[index] > kSpeedUpFactor * (float)furthest ) { + + // Compute the new potential + double newPot = 0; + for (int i = 0; i < n; i++) { + newPot += std::min( distance(dataset[dsindices[i]], dataset[dsindices[index]], dataset.cols) + , closestDistSq[i] ); + } + + // Store the best result + if ((bestNewPot < 0)||(newPot <= bestNewPot)) { + bestNewPot = newPot; + bestNewIndex = index; + furthest = closestDistSq[index]; + } + } + } + + // Add the appropriate center + centers[centerCount] = dsindices[bestNewIndex]; + for (int i = 0; i < n; i++) { + closestDistSq[i] = std::min( distance(dataset[dsindices[i]], dataset[dsindices[bestNewIndex]], dataset.cols) + , closestDistSq[i] ); + } + } + + centers_length = centerCount; + + delete[] closestDistSq; + } + + +public: + + + /** + * Index constructor + * + * Params: + * inputData = dataset with the input features + * params = parameters passed to the hierarchical k-means algorithm + */ + HierarchicalClusteringIndex(const Matrix& inputData, const IndexParams& index_params = HierarchicalClusteringIndexParams(), + Distance d = Distance()) + : dataset(inputData), params(index_params), root(NULL), indices(NULL), distance(d) + { + memoryCounter = 0; + + size_ = dataset.rows; + veclen_ = dataset.cols; + + branching_ = get_param(params,"branching",32); + centers_init_ = get_param(params,"centers_init", FLANN_CENTERS_RANDOM); + trees_ = get_param(params,"trees",4); + leaf_size_ = get_param(params,"leaf_size",100); + + if (centers_init_==FLANN_CENTERS_RANDOM) { + chooseCenters = &HierarchicalClusteringIndex::chooseCentersRandom; + } + else if (centers_init_==FLANN_CENTERS_GONZALES) { + chooseCenters = &HierarchicalClusteringIndex::chooseCentersGonzales; + } + else if (centers_init_==FLANN_CENTERS_KMEANSPP) { + chooseCenters = &HierarchicalClusteringIndex::chooseCentersKMeanspp; + } + else if (centers_init_==FLANN_CENTERS_GROUPWISE) { + chooseCenters = &HierarchicalClusteringIndex::GroupWiseCenterChooser; + } + else { + throw FLANNException("Unknown algorithm for choosing initial centers."); + } + + trees_ = get_param(params,"trees",4); + root = new NodePtr[trees_]; + indices = new int*[trees_]; + + for (int i=0; i(); + computeClustering(root[i], indices[i], (int)size_, branching_,0); + } + } + + + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_HIERARCHICAL; + } + + + void saveIndex(FILE* stream) CV_OVERRIDE + { + save_value(stream, branching_); + save_value(stream, trees_); + save_value(stream, centers_init_); + save_value(stream, leaf_size_); + save_value(stream, memoryCounter); + for (int i=0; i& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + + int maxChecks = get_param(searchParams,"checks",32); + + // Priority queue storing intermediate branches in the best-bin-first search + Heap* heap = new Heap((int)size_); + + std::vector checked(size_,false); + int checks = 0; + for (int i=0; ipopMin(branch) && (checks BranchSt; + + + + void save_tree(FILE* stream, NodePtr node, int num) + { + save_value(stream, *node); + if (node->childs==NULL) { + int indices_offset = (int)(node->indices - indices[num]); + save_value(stream, indices_offset); + } + else { + for(int i=0; ichilds[i], num); + } + } + } + + + void load_tree(FILE* stream, NodePtr& node, int num) + { + node = pool.allocate(); + load_value(stream, *node); + if (node->childs==NULL) { + int indices_offset; + load_value(stream, indices_offset); + node->indices = indices[num] + indices_offset; + } + else { + node->childs = pool.allocate(branching_); + for(int i=0; ichilds[i], num); + } + } + } + + + + + void computeLabels(int* dsindices, int indices_length, int* centers, int centers_length, int* labels, DistanceType& cost) + { + cost = 0; + for (int i=0; inew_dist) { + labels[i] = j; + dist = new_dist; + } + } + cost += dist; + } + } + + /** + * The method responsible with actually doing the recursive hierarchical + * clustering + * + * Params: + * node = the node to cluster + * indices = indices of the points belonging to the current node + * branching = the branching factor to use in the clustering + * + * TODO: for 1-sized clusters don't store a cluster center (it's the same as the single cluster point) + */ + void computeClustering(NodePtr node, int* dsindices, int indices_length, int branching, int level) + { + node->size = indices_length; + node->level = level; + + if (indices_length < leaf_size_) { // leaf node + node->indices = dsindices; + std::sort(node->indices,node->indices+indices_length); + node->childs = NULL; + return; + } + + std::vector centers(branching); + std::vector labels(indices_length); + + int centers_length; + (this->*chooseCenters)(branching, dsindices, indices_length, ¢ers[0], centers_length); + + if (centers_lengthindices = dsindices; + std::sort(node->indices,node->indices+indices_length); + node->childs = NULL; + return; + } + + + // assign points to clusters + DistanceType cost; + computeLabels(dsindices, indices_length, ¢ers[0], centers_length, &labels[0], cost); + + node->childs = pool.allocate(branching); + int start = 0; + int end = start; + for (int i=0; ichilds[i] = pool.allocate(); + node->childs[i]->pivot = centers[i]; + node->childs[i]->indices = NULL; + computeClustering(node->childs[i],dsindices+start, end-start, branching, level+1); + start=end; + } + } + + + + /** + * Performs one descent in the hierarchical k-means tree. The branches not + * visited are stored in a priority queue. + * + * Params: + * node = node to explore + * result = container for the k-nearest neighbors found + * vec = query points + * checks = how many points in the dataset have been checked so far + * maxChecks = maximum dataset points to checks + */ + + + void findNN(NodePtr node, ResultSet& result, const ElementType* vec, int& checks, int maxChecks, + Heap* heap, std::vector& checked) + { + if (node->childs==NULL) { + if (checks>=maxChecks) { + if (result.full()) return; + } + for (int i=0; isize; ++i) { + int index = node->indices[i]; + if (!checked[index]) { + DistanceType dist = distance(dataset[index], vec, veclen_); + result.addPoint(dist, index); + checked[index] = true; + ++checks; + } + } + } + else { + DistanceType* domain_distances = new DistanceType[branching_]; + int best_index = 0; + domain_distances[best_index] = distance(vec, dataset[node->childs[best_index]->pivot], veclen_); + for (int i=1; ichilds[i]->pivot], veclen_); + if (domain_distances[i]insert(BranchSt(node->childs[i],domain_distances[i])); + } + } + delete[] domain_distances; + findNN(node->childs[best_index],result,vec, checks, maxChecks, heap, checked); + } + } + +private: + + + /** + * The dataset used by this index + */ + const Matrix dataset; + + /** + * Parameters used by this index + */ + IndexParams params; + + + /** + * Number of features in the dataset. + */ + size_t size_; + + /** + * Length of each feature. + */ + size_t veclen_; + + /** + * The root node in the tree. + */ + NodePtr* root; + + /** + * Array of indices to vectors in the dataset. + */ + int** indices; + + + /** + * The distance + */ + Distance distance; + + /** + * Pooled memory allocator. + * + * Using a pooled memory allocator is more efficient + * than allocating memory directly when there is a large + * number small of memory allocations. + */ + PooledAllocator pool; + + /** + * Memory occupied by the index. + */ + int memoryCounter; + + /** index parameters */ + int branching_; + int trees_; + flann_centers_init_t centers_init_; + int leaf_size_; + + +}; + +} + +#endif /* OPENCV_FLANN_HIERARCHICAL_CLUSTERING_INDEX_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/index_testing.h b/3rdparty/opencv/include/opencv2/flann/index_testing.h new file mode 100644 index 00000000..d7640040 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/index_testing.h @@ -0,0 +1,318 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_INDEX_TESTING_H_ +#define OPENCV_FLANN_INDEX_TESTING_H_ + +#include +#include +#include + +#include "matrix.h" +#include "nn_index.h" +#include "result_set.h" +#include "logger.h" +#include "timer.h" + + +namespace cvflann +{ + +inline int countCorrectMatches(int* neighbors, int* groundTruth, int n) +{ + int count = 0; + for (int i=0; i +typename Distance::ResultType computeDistanceRaport(const Matrix& inputData, typename Distance::ElementType* target, + int* neighbors, int* groundTruth, int veclen, int n, const Distance& distance) +{ + typedef typename Distance::ResultType DistanceType; + + DistanceType ret = 0; + for (int i=0; i +float search_with_ground_truth(NNIndex& index, const Matrix& inputData, + const Matrix& testData, const Matrix& matches, int nn, int checks, + float& time, typename Distance::ResultType& dist, const Distance& distance, int skipMatches) +{ + typedef typename Distance::ResultType DistanceType; + + if (matches.cols resultSet(nn+skipMatches); + SearchParams searchParams(checks); + + std::vector indices(nn+skipMatches); + std::vector dists(nn+skipMatches); + int* neighbors = &indices[skipMatches]; + + int correct = 0; + DistanceType distR = 0; + StartStopTimer t; + int repeats = 0; + while (t.value<0.2) { + repeats++; + t.start(); + correct = 0; + distR = 0; + for (size_t i = 0; i < testData.rows; i++) { + resultSet.init(&indices[0], &dists[0]); + index.findNeighbors(resultSet, testData[i], searchParams); + + correct += countCorrectMatches(neighbors,matches[i], nn); + distR += computeDistanceRaport(inputData, testData[i], neighbors, matches[i], (int)testData.cols, nn, distance); + } + t.stop(); + } + time = float(t.value/repeats); + + float precicion = (float)correct/(nn*testData.rows); + + dist = distR/(testData.rows*nn); + + Logger::info("%8d %10.4g %10.5g %10.5g %10.5g\n", + checks, precicion, time, 1000.0 * time / testData.rows, dist); + + return precicion; +} + + +template +float test_index_checks(NNIndex& index, const Matrix& inputData, + const Matrix& testData, const Matrix& matches, + int checks, float& precision, const Distance& distance, int nn = 1, int skipMatches = 0) +{ + typedef typename Distance::ResultType DistanceType; + + Logger::info(" Nodes Precision(%) Time(s) Time/vec(ms) Mean dist\n"); + Logger::info("---------------------------------------------------------\n"); + + float time = 0; + DistanceType dist = 0; + precision = search_with_ground_truth(index, inputData, testData, matches, nn, checks, time, dist, distance, skipMatches); + + return time; +} + +template +float test_index_precision(NNIndex& index, const Matrix& inputData, + const Matrix& testData, const Matrix& matches, + float precision, int& checks, const Distance& distance, int nn = 1, int skipMatches = 0) +{ + typedef typename Distance::ResultType DistanceType; + const float SEARCH_EPS = 0.001f; + + Logger::info(" Nodes Precision(%) Time(s) Time/vec(ms) Mean dist\n"); + Logger::info("---------------------------------------------------------\n"); + + int c2 = 1; + float p2; + int c1 = 1; + //float p1; + float time; + DistanceType dist; + + p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches); + + if (p2>precision) { + Logger::info("Got as close as I can\n"); + checks = c2; + return time; + } + + while (p2SEARCH_EPS) { + Logger::info("Start linear estimation\n"); + // after we got to values in the vecinity of the desired precision + // use linear approximation get a better estimation + + cx = (c1+c2)/2; + realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches); + while (fabs(realPrecision-precision)>SEARCH_EPS) { + + if (realPrecision +void test_index_precisions(NNIndex& index, const Matrix& inputData, + const Matrix& testData, const Matrix& matches, + float* precisions, int precisions_length, const Distance& distance, int nn = 1, int skipMatches = 0, float maxTime = 0) +{ + typedef typename Distance::ResultType DistanceType; + + const float SEARCH_EPS = 0.001; + + // make sure precisions array is sorted + std::sort(precisions, precisions+precisions_length); + + int pindex = 0; + float precision = precisions[pindex]; + + Logger::info(" Nodes Precision(%) Time(s) Time/vec(ms) Mean dist\n"); + Logger::info("---------------------------------------------------------\n"); + + int c2 = 1; + float p2; + + int c1 = 1; + float p1; + + float time; + DistanceType dist; + + p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches); + + // if precision for 1 run down the tree is already + // better then some of the requested precisions, then + // skip those + while (precisions[pindex] 0)&&(time > maxTime)&&(p2SEARCH_EPS) { + Logger::info("Start linear estimation\n"); + // after we got to values in the vecinity of the desired precision + // use linear approximation get a better estimation + + cx = (c1+c2)/2; + realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches); + while (fabs(realPrecision-precision)>SEARCH_EPS) { + + if (realPrecision +#include +#include +#include + +#include "general.h" +#include "nn_index.h" +#include "dynamic_bitset.h" +#include "matrix.h" +#include "result_set.h" +#include "heap.h" +#include "allocator.h" +#include "random.h" +#include "saving.h" + + +namespace cvflann +{ + +struct KDTreeIndexParams : public IndexParams +{ + KDTreeIndexParams(int trees = 4) + { + (*this)["algorithm"] = FLANN_INDEX_KDTREE; + (*this)["trees"] = trees; + } +}; + + +/** + * Randomized kd-tree index + * + * Contains the k-d trees and other information for indexing a set of points + * for nearest-neighbor matching. + */ +template +class KDTreeIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + + /** + * KDTree constructor + * + * Params: + * inputData = dataset with the input features + * params = parameters passed to the kdtree algorithm + */ + KDTreeIndex(const Matrix& inputData, const IndexParams& params = KDTreeIndexParams(), + Distance d = Distance() ) : + dataset_(inputData), index_params_(params), distance_(d) + { + size_ = dataset_.rows; + veclen_ = dataset_.cols; + + trees_ = get_param(index_params_,"trees",4); + tree_roots_ = new NodePtr[trees_]; + + // Create a permutable array of indices to the input vectors. + vind_.resize(size_); + for (size_t i = 0; i < size_; ++i) { + vind_[i] = int(i); + } + + mean_ = new DistanceType[veclen_]; + var_ = new DistanceType[veclen_]; + } + + + KDTreeIndex(const KDTreeIndex&); + KDTreeIndex& operator=(const KDTreeIndex&); + + /** + * Standard destructor + */ + ~KDTreeIndex() + { + if (tree_roots_!=NULL) { + delete[] tree_roots_; + } + delete[] mean_; + delete[] var_; + } + + /** + * Builds the index + */ + void buildIndex() CV_OVERRIDE + { + /* Construct the randomized trees. */ + for (int i = 0; i < trees_; i++) { + /* Randomize the order of vectors to allow for unbiased sampling. */ +#ifndef OPENCV_FLANN_USE_STD_RAND + cv::randShuffle(vind_); +#else + std::random_shuffle(vind_.begin(), vind_.end()); +#endif + + tree_roots_[i] = divideTree(&vind_[0], int(size_) ); + } + } + + + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_KDTREE; + } + + + void saveIndex(FILE* stream) CV_OVERRIDE + { + save_value(stream, trees_); + for (int i=0; i& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + int maxChecks = get_param(searchParams,"checks", 32); + float epsError = 1+get_param(searchParams,"eps",0.0f); + + if (maxChecks==FLANN_CHECKS_UNLIMITED) { + getExactNeighbors(result, vec, epsError); + } + else { + getNeighbors(result, vec, maxChecks, epsError); + } + } + + IndexParams getParameters() const CV_OVERRIDE + { + return index_params_; + } + +private: + + + /*--------------------- Internal Data Structures --------------------------*/ + struct Node + { + /** + * Dimension used for subdivision. + */ + int divfeat; + /** + * The values used for subdivision. + */ + DistanceType divval; + /** + * The child nodes. + */ + Node* child1, * child2; + }; + typedef Node* NodePtr; + typedef BranchStruct BranchSt; + typedef BranchSt* Branch; + + + + void save_tree(FILE* stream, NodePtr tree) + { + save_value(stream, *tree); + if (tree->child1!=NULL) { + save_tree(stream, tree->child1); + } + if (tree->child2!=NULL) { + save_tree(stream, tree->child2); + } + } + + + void load_tree(FILE* stream, NodePtr& tree) + { + tree = pool_.allocate(); + load_value(stream, *tree); + if (tree->child1!=NULL) { + load_tree(stream, tree->child1); + } + if (tree->child2!=NULL) { + load_tree(stream, tree->child2); + } + } + + + /** + * Create a tree node that subdivides the list of vecs from vind[first] + * to vind[last]. The routine is called recursively on each sublist. + * Place a pointer to this new tree node in the location pTree. + * + * Params: pTree = the new node to create + * first = index of the first vector + * last = index of the last vector + */ + NodePtr divideTree(int* ind, int count) + { + NodePtr node = pool_.allocate(); // allocate memory + + /* If too few exemplars remain, then make this a leaf node. */ + if ( count == 1) { + node->child1 = node->child2 = NULL; /* Mark as leaf node. */ + node->divfeat = *ind; /* Store index of this vec. */ + } + else { + int idx; + int cutfeat; + DistanceType cutval; + meanSplit(ind, count, idx, cutfeat, cutval); + + node->divfeat = cutfeat; + node->divval = cutval; + node->child1 = divideTree(ind, idx); + node->child2 = divideTree(ind+idx, count-idx); + } + + return node; + } + + + /** + * Choose which feature to use in order to subdivide this set of vectors. + * Make a random choice among those with the highest variance, and use + * its variance as the threshold value. + */ + void meanSplit(int* ind, int count, int& index, int& cutfeat, DistanceType& cutval) + { + memset(mean_,0,veclen_*sizeof(DistanceType)); + memset(var_,0,veclen_*sizeof(DistanceType)); + + /* Compute mean values. Only the first SAMPLE_MEAN values need to be + sampled to get a good estimate. + */ + int cnt = std::min((int)SAMPLE_MEAN+1, count); + for (int j = 0; j < cnt; ++j) { + ElementType* v = dataset_[ind[j]]; + for (size_t k=0; kcount/2) index = lim1; + else if (lim2 v[topind[num-1]])) { + /* Put this element at end of topind. */ + if (num < RAND_DIM) { + topind[num++] = i; /* Add to list. */ + } + else { + topind[num-1] = i; /* Replace last element. */ + } + /* Bubble end value down to right location by repeated swapping. */ + int j = num - 1; + while (j > 0 && v[topind[j]] > v[topind[j-1]]) { + std::swap(topind[j], topind[j-1]); + --j; + } + } + } + /* Select a random integer in range [0,num-1], and return that index. */ + int rnd = rand_int(num); + return (int)topind[rnd]; + } + + + /** + * Subdivide the list of points by a plane perpendicular on axe corresponding + * to the 'cutfeat' dimension at 'cutval' position. + * + * On return: + * dataset[ind[0..lim1-1]][cutfeat]cutval + */ + void planeSplit(int* ind, int count, int cutfeat, DistanceType cutval, int& lim1, int& lim2) + { + /* Move vector indices for left subtree to front of list. */ + int left = 0; + int right = count-1; + for (;; ) { + while (left<=right && dataset_[ind[left]][cutfeat]=cutval) --right; + if (left>right) break; + std::swap(ind[left], ind[right]); ++left; --right; + } + lim1 = left; + right = count-1; + for (;; ) { + while (left<=right && dataset_[ind[left]][cutfeat]<=cutval) ++left; + while (left<=right && dataset_[ind[right]][cutfeat]>cutval) --right; + if (left>right) break; + std::swap(ind[left], ind[right]); ++left; --right; + } + lim2 = left; + } + + /** + * Performs an exact nearest neighbor search. The exact search performs a full + * traversal of the tree. + */ + void getExactNeighbors(ResultSet& result, const ElementType* vec, float epsError) + { + // checkID -= 1; /* Set a different unique ID for each search. */ + + if (trees_ > 1) { + fprintf(stderr,"It doesn't make any sense to use more than one tree for exact search"); + } + if (trees_>0) { + searchLevelExact(result, vec, tree_roots_[0], 0.0, epsError); + } + assert(result.full()); + } + + /** + * Performs the approximate nearest-neighbor search. The search is approximate + * because the tree traversal is abandoned after a given number of descends in + * the tree. + */ + void getNeighbors(ResultSet& result, const ElementType* vec, int maxCheck, float epsError) + { + int i; + BranchSt branch; + + int checkCount = 0; + Heap* heap = new Heap((int)size_); + DynamicBitset checked(size_); + + /* Search once through each tree down to root. */ + for (i = 0; i < trees_; ++i) { + searchLevel(result, vec, tree_roots_[i], 0, checkCount, maxCheck, epsError, heap, checked); + } + + /* Keep searching other branches from heap until finished. */ + while ( heap->popMin(branch) && (checkCount < maxCheck || !result.full() )) { + searchLevel(result, vec, branch.node, branch.mindist, checkCount, maxCheck, epsError, heap, checked); + } + + delete heap; + + assert(result.full()); + } + + + /** + * Search starting from a given node of the tree. Based on any mismatches at + * higher levels, all exemplars below this level must have a distance of + * at least "mindistsq". + */ + void searchLevel(ResultSet& result_set, const ElementType* vec, NodePtr node, DistanceType mindist, int& checkCount, int maxCheck, + float epsError, Heap* heap, DynamicBitset& checked) + { + if (result_set.worstDist()child1 == NULL)&&(node->child2 == NULL)) { + /* Do not check same node more than once when searching multiple trees. + Once a vector is checked, we set its location in vind to the + current checkID. + */ + int index = node->divfeat; + if ( checked.test(index) || ((checkCount>=maxCheck)&& result_set.full()) ) return; + checked.set(index); + checkCount++; + + DistanceType dist = distance_(dataset_[index], vec, veclen_); + result_set.addPoint(dist,index); + + return; + } + + /* Which child branch should be taken first? */ + ElementType val = vec[node->divfeat]; + DistanceType diff = val - node->divval; + NodePtr bestChild = (diff < 0) ? node->child1 : node->child2; + NodePtr otherChild = (diff < 0) ? node->child2 : node->child1; + + /* Create a branch record for the branch not taken. Add distance + of this feature boundary (we don't attempt to correct for any + use of this feature in a parent node, which is unlikely to + happen and would have only a small effect). Don't bother + adding more branches to heap after halfway point, as cost of + adding exceeds their value. + */ + + DistanceType new_distsq = mindist + distance_.accum_dist(val, node->divval, node->divfeat); + // if (2 * checkCount < maxCheck || !result.full()) { + if ((new_distsq*epsError < result_set.worstDist())|| !result_set.full()) { + heap->insert( BranchSt(otherChild, new_distsq) ); + } + + /* Call recursively to search next level down. */ + searchLevel(result_set, vec, bestChild, mindist, checkCount, maxCheck, epsError, heap, checked); + } + + /** + * Performs an exact search in the tree starting from a node. + */ + void searchLevelExact(ResultSet& result_set, const ElementType* vec, const NodePtr node, DistanceType mindist, const float epsError) + { + /* If this is a leaf node, then do check and return. */ + if ((node->child1 == NULL)&&(node->child2 == NULL)) { + int index = node->divfeat; + DistanceType dist = distance_(dataset_[index], vec, veclen_); + result_set.addPoint(dist,index); + return; + } + + /* Which child branch should be taken first? */ + ElementType val = vec[node->divfeat]; + DistanceType diff = val - node->divval; + NodePtr bestChild = (diff < 0) ? node->child1 : node->child2; + NodePtr otherChild = (diff < 0) ? node->child2 : node->child1; + + /* Create a branch record for the branch not taken. Add distance + of this feature boundary (we don't attempt to correct for any + use of this feature in a parent node, which is unlikely to + happen and would have only a small effect). Don't bother + adding more branches to heap after halfway point, as cost of + adding exceeds their value. + */ + + DistanceType new_distsq = mindist + distance_.accum_dist(val, node->divval, node->divfeat); + + /* Call recursively to search next level down. */ + searchLevelExact(result_set, vec, bestChild, mindist, epsError); + + if (new_distsq*epsError<=result_set.worstDist()) { + searchLevelExact(result_set, vec, otherChild, new_distsq, epsError); + } + } + + +private: + + enum + { + /** + * To improve efficiency, only SAMPLE_MEAN random values are used to + * compute the mean and variance at each level when building a tree. + * A value of 100 seems to perform as well as using all values. + */ + SAMPLE_MEAN = 100, + /** + * Top random dimensions to consider + * + * When creating random trees, the dimension on which to subdivide is + * selected at random from among the top RAND_DIM dimensions with the + * highest variance. A value of 5 works well. + */ + RAND_DIM=5 + }; + + + /** + * Number of randomized trees that are used + */ + int trees_; + + /** + * Array of indices to vectors in the dataset. + */ + std::vector vind_; + + /** + * The dataset used by this index + */ + const Matrix dataset_; + + IndexParams index_params_; + + size_t size_; + size_t veclen_; + + + DistanceType* mean_; + DistanceType* var_; + + + /** + * Array of k-d trees used to find neighbours. + */ + NodePtr* tree_roots_; + + /** + * Pooled memory allocator. + * + * Using a pooled memory allocator is more efficient + * than allocating memory directly when there is a large + * number small of memory allocations. + */ + PooledAllocator pool_; + + Distance distance_; + + +}; // class KDTreeForest + +} + +#endif //OPENCV_FLANN_KDTREE_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/kdtree_single_index.h b/3rdparty/opencv/include/opencv2/flann/kdtree_single_index.h new file mode 100644 index 00000000..22a28d0c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/kdtree_single_index.h @@ -0,0 +1,635 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_KDTREE_SINGLE_INDEX_H_ +#define OPENCV_FLANN_KDTREE_SINGLE_INDEX_H_ + +#include +#include +#include +#include + +#include "general.h" +#include "nn_index.h" +#include "matrix.h" +#include "result_set.h" +#include "heap.h" +#include "allocator.h" +#include "random.h" +#include "saving.h" + +namespace cvflann +{ + +struct KDTreeSingleIndexParams : public IndexParams +{ + KDTreeSingleIndexParams(int leaf_max_size = 10, bool reorder = true, int dim = -1) + { + (*this)["algorithm"] = FLANN_INDEX_KDTREE_SINGLE; + (*this)["leaf_max_size"] = leaf_max_size; + (*this)["reorder"] = reorder; + (*this)["dim"] = dim; + } +}; + + +/** + * Randomized kd-tree index + * + * Contains the k-d trees and other information for indexing a set of points + * for nearest-neighbor matching. + */ +template +class KDTreeSingleIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + + /** + * KDTree constructor + * + * Params: + * inputData = dataset with the input features + * params = parameters passed to the kdtree algorithm + */ + KDTreeSingleIndex(const Matrix& inputData, const IndexParams& params = KDTreeSingleIndexParams(), + Distance d = Distance() ) : + dataset_(inputData), index_params_(params), distance_(d) + { + size_ = dataset_.rows; + dim_ = dataset_.cols; + root_node_ = 0; + int dim_param = get_param(params,"dim",-1); + if (dim_param>0) dim_ = dim_param; + leaf_max_size_ = get_param(params,"leaf_max_size",10); + reorder_ = get_param(params,"reorder",true); + + // Create a permutable array of indices to the input vectors. + vind_.resize(size_); + for (size_t i = 0; i < size_; i++) { + vind_[i] = (int)i; + } + } + + KDTreeSingleIndex(const KDTreeSingleIndex&); + KDTreeSingleIndex& operator=(const KDTreeSingleIndex&); + + /** + * Standard destructor + */ + ~KDTreeSingleIndex() + { + if (reorder_) delete[] data_.data; + } + + /** + * Builds the index + */ + void buildIndex() CV_OVERRIDE + { + computeBoundingBox(root_bbox_); + root_node_ = divideTree(0, (int)size_, root_bbox_ ); // construct the tree + + if (reorder_) { + delete[] data_.data; + data_ = cvflann::Matrix(new ElementType[size_*dim_], size_, dim_); + for (size_t i=0; i& queries, Matrix& indices, Matrix& dists, int knn, const SearchParams& params) CV_OVERRIDE + { + assert(queries.cols == veclen()); + assert(indices.rows >= queries.rows); + assert(dists.rows >= queries.rows); + assert(int(indices.cols) >= knn); + assert(int(dists.cols) >= knn); + + KNNSimpleResultSet resultSet(knn); + for (size_t i = 0; i < queries.rows; i++) { + resultSet.init(indices[i], dists[i]); + findNeighbors(resultSet, queries[i], params); + } + } + + IndexParams getParameters() const CV_OVERRIDE + { + return index_params_; + } + + /** + * Find set of nearest neighbors to vec. Their indices are stored inside + * the result object. + * + * Params: + * result = the result object in which the indices of the nearest-neighbors are stored + * vec = the vector for which to search the nearest neighbors + * maxCheck = the maximum number of restarts (in a best-bin-first manner) + */ + void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + float epsError = 1+get_param(searchParams,"eps",0.0f); + + std::vector dists(dim_,0); + DistanceType distsq = computeInitialDistances(vec, dists); + searchLevel(result, vec, root_node_, distsq, dists, epsError); + } + +private: + + + /*--------------------- Internal Data Structures --------------------------*/ + struct Node + { + /** + * Indices of points in leaf node + */ + int left, right; + /** + * Dimension used for subdivision. + */ + int divfeat; + /** + * The values used for subdivision. + */ + DistanceType divlow, divhigh; + /** + * The child nodes. + */ + Node* child1, * child2; + }; + typedef Node* NodePtr; + + + struct Interval + { + DistanceType low, high; + }; + + typedef std::vector BoundingBox; + + typedef BranchStruct BranchSt; + typedef BranchSt* Branch; + + + + + void save_tree(FILE* stream, NodePtr tree) + { + save_value(stream, *tree); + if (tree->child1!=NULL) { + save_tree(stream, tree->child1); + } + if (tree->child2!=NULL) { + save_tree(stream, tree->child2); + } + } + + + void load_tree(FILE* stream, NodePtr& tree) + { + tree = pool_.allocate(); + load_value(stream, *tree); + if (tree->child1!=NULL) { + load_tree(stream, tree->child1); + } + if (tree->child2!=NULL) { + load_tree(stream, tree->child2); + } + } + + + void computeBoundingBox(BoundingBox& bbox) + { + bbox.resize(dim_); + for (size_t i=0; ibbox[i].high) bbox[i].high = (DistanceType)dataset_[k][i]; + } + } + } + + + /** + * Create a tree node that subdivides the list of vecs from vind[first] + * to vind[last]. The routine is called recursively on each sublist. + * Place a pointer to this new tree node in the location pTree. + * + * Params: pTree = the new node to create + * first = index of the first vector + * last = index of the last vector + */ + NodePtr divideTree(int left, int right, BoundingBox& bbox) + { + NodePtr node = pool_.allocate(); // allocate memory + + /* If too few exemplars remain, then make this a leaf node. */ + if ( (right-left) <= leaf_max_size_) { + node->child1 = node->child2 = NULL; /* Mark as leaf node. */ + node->left = left; + node->right = right; + + // compute bounding-box of leaf points + for (size_t i=0; idataset_[vind_[k]][i]) bbox[i].low=(DistanceType)dataset_[vind_[k]][i]; + if (bbox[i].highdivfeat = cutfeat; + + BoundingBox left_bbox(bbox); + left_bbox[cutfeat].high = cutval; + node->child1 = divideTree(left, left+idx, left_bbox); + + BoundingBox right_bbox(bbox); + right_bbox[cutfeat].low = cutval; + node->child2 = divideTree(left+idx, right, right_bbox); + + node->divlow = left_bbox[cutfeat].high; + node->divhigh = right_bbox[cutfeat].low; + + for (size_t i=0; imax_elem) max_elem = val; + } + } + + void middleSplit(int* ind, int count, int& index, int& cutfeat, DistanceType& cutval, const BoundingBox& bbox) + { + // find the largest span from the approximate bounding box + ElementType max_span = bbox[0].high-bbox[0].low; + cutfeat = 0; + cutval = (bbox[0].high+bbox[0].low)/2; + for (size_t i=1; imax_span) { + max_span = span; + cutfeat = i; + cutval = (bbox[i].high+bbox[i].low)/2; + } + } + + // compute exact span on the found dimension + ElementType min_elem, max_elem; + computeMinMax(ind, count, cutfeat, min_elem, max_elem); + cutval = (min_elem+max_elem)/2; + max_span = max_elem - min_elem; + + // check if a dimension of a largest span exists + size_t k = cutfeat; + for (size_t i=0; imax_span) { + computeMinMax(ind, count, i, min_elem, max_elem); + span = max_elem - min_elem; + if (span>max_span) { + max_span = span; + cutfeat = i; + cutval = (min_elem+max_elem)/2; + } + } + } + int lim1, lim2; + planeSplit(ind, count, cutfeat, cutval, lim1, lim2); + + if (lim1>count/2) index = lim1; + else if (lim2max_span) { + max_span = span; + } + } + DistanceType max_spread = -1; + cutfeat = 0; + for (size_t i=0; i(DistanceType)((1-EPS)*max_span)) { + ElementType min_elem, max_elem; + computeMinMax(ind, count, cutfeat, min_elem, max_elem); + DistanceType spread = (DistanceType)(max_elem-min_elem); + if (spread>max_spread) { + cutfeat = (int)i; + max_spread = spread; + } + } + } + // split in the middle + DistanceType split_val = (bbox[cutfeat].low+bbox[cutfeat].high)/2; + ElementType min_elem, max_elem; + computeMinMax(ind, count, cutfeat, min_elem, max_elem); + + if (split_valmax_elem) cutval = (DistanceType)max_elem; + else cutval = split_val; + + int lim1, lim2; + planeSplit(ind, count, cutfeat, cutval, lim1, lim2); + + if (lim1>count/2) index = lim1; + else if (lim2cutval + */ + void planeSplit(int* ind, int count, int cutfeat, DistanceType cutval, int& lim1, int& lim2) + { + /* Move vector indices for left subtree to front of list. */ + int left = 0; + int right = count-1; + for (;; ) { + while (left<=right && dataset_[ind[left]][cutfeat]=cutval) --right; + if (left>right) break; + std::swap(ind[left], ind[right]); ++left; --right; + } + /* If either list is empty, it means that all remaining features + * are identical. Split in the middle to maintain a balanced tree. + */ + lim1 = left; + right = count-1; + for (;; ) { + while (left<=right && dataset_[ind[left]][cutfeat]<=cutval) ++left; + while (left<=right && dataset_[ind[right]][cutfeat]>cutval) --right; + if (left>right) break; + std::swap(ind[left], ind[right]); ++left; --right; + } + lim2 = left; + } + + DistanceType computeInitialDistances(const ElementType* vec, std::vector& dists) + { + DistanceType distsq = 0.0; + + for (size_t i = 0; i < dim_; ++i) { + if (vec[i] < root_bbox_[i].low) { + dists[i] = distance_.accum_dist(vec[i], root_bbox_[i].low, (int)i); + distsq += dists[i]; + } + if (vec[i] > root_bbox_[i].high) { + dists[i] = distance_.accum_dist(vec[i], root_bbox_[i].high, (int)i); + distsq += dists[i]; + } + } + + return distsq; + } + + /** + * Performs an exact search in the tree starting from a node. + */ + void searchLevel(ResultSet& result_set, const ElementType* vec, const NodePtr node, DistanceType mindistsq, + std::vector& dists, const float epsError) + { + /* If this is a leaf node, then do check and return. */ + if ((node->child1 == NULL)&&(node->child2 == NULL)) { + DistanceType worst_dist = result_set.worstDist(); + for (int i=node->left; iright; ++i) { + int index = reorder_ ? i : vind_[i]; + DistanceType dist = distance_(vec, data_[index], dim_, worst_dist); + if (distdivfeat; + ElementType val = vec[idx]; + DistanceType diff1 = val - node->divlow; + DistanceType diff2 = val - node->divhigh; + + NodePtr bestChild; + NodePtr otherChild; + DistanceType cut_dist; + if ((diff1+diff2)<0) { + bestChild = node->child1; + otherChild = node->child2; + cut_dist = distance_.accum_dist(val, node->divhigh, idx); + } + else { + bestChild = node->child2; + otherChild = node->child1; + cut_dist = distance_.accum_dist( val, node->divlow, idx); + } + + /* Call recursively to search next level down. */ + searchLevel(result_set, vec, bestChild, mindistsq, dists, epsError); + + DistanceType dst = dists[idx]; + mindistsq = mindistsq + cut_dist - dst; + dists[idx] = cut_dist; + if (mindistsq*epsError<=result_set.worstDist()) { + searchLevel(result_set, vec, otherChild, mindistsq, dists, epsError); + } + dists[idx] = dst; + } + +private: + + /** + * The dataset used by this index + */ + const Matrix dataset_; + + IndexParams index_params_; + + int leaf_max_size_; + bool reorder_; + + + /** + * Array of indices to vectors in the dataset. + */ + std::vector vind_; + + Matrix data_; + + size_t size_; + size_t dim_; + + /** + * Array of k-d trees used to find neighbours. + */ + NodePtr root_node_; + + BoundingBox root_bbox_; + + /** + * Pooled memory allocator. + * + * Using a pooled memory allocator is more efficient + * than allocating memory directly when there is a large + * number small of memory allocations. + */ + PooledAllocator pool_; + + Distance distance_; +}; // class KDTree + +} + +#endif //OPENCV_FLANN_KDTREE_SINGLE_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/kmeans_index.h b/3rdparty/opencv/include/opencv2/flann/kmeans_index.h new file mode 100644 index 00000000..fe91dddd --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/kmeans_index.h @@ -0,0 +1,1172 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_KMEANS_INDEX_H_ +#define OPENCV_FLANN_KMEANS_INDEX_H_ + +#include +#include +#include +#include +#include + +#include "general.h" +#include "nn_index.h" +#include "dist.h" +#include "matrix.h" +#include "result_set.h" +#include "heap.h" +#include "allocator.h" +#include "random.h" +#include "saving.h" +#include "logger.h" + + +namespace cvflann +{ + +struct KMeansIndexParams : public IndexParams +{ + KMeansIndexParams(int branching = 32, int iterations = 11, + flann_centers_init_t centers_init = FLANN_CENTERS_RANDOM, float cb_index = 0.2 ) + { + (*this)["algorithm"] = FLANN_INDEX_KMEANS; + // branching factor + (*this)["branching"] = branching; + // max iterations to perform in one kmeans clustering (kmeans tree) + (*this)["iterations"] = iterations; + // algorithm used for picking the initial cluster centers for kmeans tree + (*this)["centers_init"] = centers_init; + // cluster boundary index. Used when searching the kmeans tree + (*this)["cb_index"] = cb_index; + } +}; + + +/** + * Hierarchical kmeans index + * + * Contains a tree constructed through a hierarchical kmeans clustering + * and other information for indexing a set of points for nearest-neighbour matching. + */ +template +class KMeansIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + + + typedef void (KMeansIndex::* centersAlgFunction)(int, int*, int, int*, int&); + + /** + * The function used for choosing the cluster centers. + */ + centersAlgFunction chooseCenters; + + + + /** + * Chooses the initial centers in the k-means clustering in a random manner. + * + * Params: + * k = number of centers + * vecs = the dataset of points + * indices = indices in the dataset + * indices_length = length of indices vector + * + */ + void chooseCentersRandom(int k, int* indices, int indices_length, int* centers, int& centers_length) + { + UniqueRandom r(indices_length); + + int index; + for (index=0; index=0 && rnd < n); + + centers[0] = indices[rnd]; + + int index; + for (index=1; indexbest_val) { + best_val = dist; + best_index = j; + } + } + if (best_index!=-1) { + centers[index] = indices[best_index]; + } + else { + break; + } + } + centers_length = index; + } + + + /** + * Chooses the initial centers in the k-means using the algorithm + * proposed in the KMeans++ paper: + * Arthur, David; Vassilvitskii, Sergei - k-means++: The Advantages of Careful Seeding + * + * Implementation of this function was converted from the one provided in Arthur's code. + * + * Params: + * k = number of centers + * vecs = the dataset of points + * indices = indices in the dataset + * Returns: + */ + void chooseCentersKMeanspp(int k, int* indices, int indices_length, int* centers, int& centers_length) + { + int n = indices_length; + + double currentPot = 0; + DistanceType* closestDistSq = new DistanceType[n]; + + // Choose one random center and set the closestDistSq values + int index = rand_int(n); + assert(index >=0 && index < n); + centers[0] = indices[index]; + + for (int i = 0; i < n; i++) { + closestDistSq[i] = distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols); + closestDistSq[i] = ensureSquareDistance( closestDistSq[i] ); + currentPot += closestDistSq[i]; + } + + + const int numLocalTries = 1; + + // Choose each center + int centerCount; + for (centerCount = 1; centerCount < k; centerCount++) { + + // Repeat several trials + double bestNewPot = -1; + int bestNewIndex = -1; + for (int localTrial = 0; localTrial < numLocalTries; localTrial++) { + + // Choose our center - have to be slightly careful to return a valid answer even accounting + // for possible rounding errors + double randVal = rand_double(currentPot); + for (index = 0; index < n-1; index++) { + if (randVal <= closestDistSq[index]) break; + else randVal -= closestDistSq[index]; + } + + // Compute the new potential + double newPot = 0; + for (int i = 0; i < n; i++) { + DistanceType dist = distance_(dataset_[indices[i]], dataset_[indices[index]], dataset_.cols); + newPot += std::min( ensureSquareDistance(dist), closestDistSq[i] ); + } + + // Store the best result + if ((bestNewPot < 0)||(newPot < bestNewPot)) { + bestNewPot = newPot; + bestNewIndex = index; + } + } + + // Add the appropriate center + centers[centerCount] = indices[bestNewIndex]; + currentPot = bestNewPot; + for (int i = 0; i < n; i++) { + DistanceType dist = distance_(dataset_[indices[i]], dataset_[indices[bestNewIndex]], dataset_.cols); + closestDistSq[i] = std::min( ensureSquareDistance(dist), closestDistSq[i] ); + } + } + + centers_length = centerCount; + + delete[] closestDistSq; + } + + + +public: + + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_KMEANS; + } + + class KMeansDistanceComputer : public cv::ParallelLoopBody + { + public: + KMeansDistanceComputer(Distance _distance, const Matrix& _dataset, + const int _branching, const int* _indices, const Matrix& _dcenters, const size_t _veclen, + std::vector &_new_centroids, std::vector &_sq_dists) + : distance(_distance) + , dataset(_dataset) + , branching(_branching) + , indices(_indices) + , dcenters(_dcenters) + , veclen(_veclen) + , new_centroids(_new_centroids) + , sq_dists(_sq_dists) + { + } + + void operator()(const cv::Range& range) const CV_OVERRIDE + { + const int begin = range.start; + const int end = range.end; + + for( int i = begin; inew_sq_dist) { + new_centroid = j; + sq_dist = new_sq_dist; + } + } + sq_dists[i] = sq_dist; + new_centroids[i] = new_centroid; + } + } + + private: + Distance distance; + const Matrix& dataset; + const int branching; + const int* indices; + const Matrix& dcenters; + const size_t veclen; + std::vector &new_centroids; + std::vector &sq_dists; + KMeansDistanceComputer& operator=( const KMeansDistanceComputer & ) { return *this; } + }; + + /** + * Index constructor + * + * Params: + * inputData = dataset with the input features + * params = parameters passed to the hierarchical k-means algorithm + */ + KMeansIndex(const Matrix& inputData, const IndexParams& params = KMeansIndexParams(), + Distance d = Distance()) + : dataset_(inputData), index_params_(params), root_(NULL), indices_(NULL), distance_(d) + { + memoryCounter_ = 0; + + size_ = dataset_.rows; + veclen_ = dataset_.cols; + + branching_ = get_param(params,"branching",32); + iterations_ = get_param(params,"iterations",11); + if (iterations_<0) { + iterations_ = (std::numeric_limits::max)(); + } + centers_init_ = get_param(params,"centers_init",FLANN_CENTERS_RANDOM); + + if (centers_init_==FLANN_CENTERS_RANDOM) { + chooseCenters = &KMeansIndex::chooseCentersRandom; + } + else if (centers_init_==FLANN_CENTERS_GONZALES) { + chooseCenters = &KMeansIndex::chooseCentersGonzales; + } + else if (centers_init_==FLANN_CENTERS_KMEANSPP) { + chooseCenters = &KMeansIndex::chooseCentersKMeanspp; + } + else { + throw FLANNException("Unknown algorithm for choosing initial centers."); + } + cb_index_ = 0.4f; + + } + + + KMeansIndex(const KMeansIndex&); + KMeansIndex& operator=(const KMeansIndex&); + + + /** + * Index destructor. + * + * Release the memory used by the index. + */ + virtual ~KMeansIndex() + { + if (root_ != NULL) { + free_centers(root_); + } + if (indices_!=NULL) { + delete[] indices_; + } + } + + /** + * Returns size of index. + */ + size_t size() const CV_OVERRIDE + { + return size_; + } + + /** + * Returns the length of an index feature. + */ + size_t veclen() const CV_OVERRIDE + { + return veclen_; + } + + + void set_cb_index( float index) + { + cb_index_ = index; + } + + /** + * Computes the inde memory usage + * Returns: memory used by the index + */ + int usedMemory() const CV_OVERRIDE + { + return pool_.usedMemory+pool_.wastedMemory+memoryCounter_; + } + + /** + * Builds the index + */ + void buildIndex() CV_OVERRIDE + { + if (branching_<2) { + throw FLANNException("Branching factor must be at least 2"); + } + + indices_ = new int[size_]; + for (size_t i=0; i(); + std::memset(root_, 0, sizeof(KMeansNode)); + + computeNodeStatistics(root_, indices_, (int)size_); + computeClustering(root_, indices_, (int)size_, branching_,0); + } + + + void saveIndex(FILE* stream) CV_OVERRIDE + { + save_value(stream, branching_); + save_value(stream, iterations_); + save_value(stream, memoryCounter_); + save_value(stream, cb_index_); + save_value(stream, *indices_, (int)size_); + + save_tree(stream, root_); + } + + + void loadIndex(FILE* stream) CV_OVERRIDE + { + load_value(stream, branching_); + load_value(stream, iterations_); + load_value(stream, memoryCounter_); + load_value(stream, cb_index_); + if (indices_!=NULL) { + delete[] indices_; + } + indices_ = new int[size_]; + load_value(stream, *indices_, size_); + + if (root_!=NULL) { + free_centers(root_); + } + load_tree(stream, root_); + + index_params_["algorithm"] = getType(); + index_params_["branching"] = branching_; + index_params_["iterations"] = iterations_; + index_params_["centers_init"] = centers_init_; + index_params_["cb_index"] = cb_index_; + + } + + + /** + * Find set of nearest neighbors to vec. Their indices are stored inside + * the result object. + * + * Params: + * result = the result object in which the indices of the nearest-neighbors are stored + * vec = the vector for which to search the nearest neighbors + * searchParams = parameters that influence the search algorithm (checks, cb_index) + */ + void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE + { + + int maxChecks = get_param(searchParams,"checks",32); + + if (maxChecks==FLANN_CHECKS_UNLIMITED) { + findExactNN(root_, result, vec); + } + else { + // Priority queue storing intermediate branches in the best-bin-first search + Heap* heap = new Heap((int)size_); + + int checks = 0; + findNN(root_, result, vec, checks, maxChecks, heap); + + BranchSt branch; + while (heap->popMin(branch) && (checks& centers) + { + int numClusters = centers.rows; + if (numClusters<1) { + throw FLANNException("Number of clusters must be at least 1"); + } + + DistanceType variance; + KMeansNodePtr* clusters = new KMeansNodePtr[numClusters]; + + int clusterCount = getMinVarianceClusters(root_, clusters, numClusters, variance); + + Logger::info("Clusters requested: %d, returning %d\n",numClusters, clusterCount); + + for (int i=0; ipivot; + for (size_t j=0; j BranchSt; + + + + + void save_tree(FILE* stream, KMeansNodePtr node) + { + save_value(stream, *node); + save_value(stream, *(node->pivot), (int)veclen_); + if (node->childs==NULL) { + int indices_offset = (int)(node->indices - indices_); + save_value(stream, indices_offset); + } + else { + for(int i=0; ichilds[i]); + } + } + } + + + void load_tree(FILE* stream, KMeansNodePtr& node) + { + node = pool_.allocate(); + load_value(stream, *node); + node->pivot = new DistanceType[veclen_]; + load_value(stream, *(node->pivot), (int)veclen_); + if (node->childs==NULL) { + int indices_offset; + load_value(stream, indices_offset); + node->indices = indices_ + indices_offset; + } + else { + node->childs = pool_.allocate(branching_); + for(int i=0; ichilds[i]); + } + } + } + + + /** + * Helper function + */ + void free_centers(KMeansNodePtr node) + { + delete[] node->pivot; + if (node->childs!=NULL) { + for (int k=0; kchilds[k]); + } + } + } + + /** + * Computes the statistics of a node (mean, radius, variance). + * + * Params: + * node = the node to use + * indices = the indices of the points belonging to the node + */ + void computeNodeStatistics(KMeansNodePtr node, int* indices, int indices_length) + { + + DistanceType radius = 0; + DistanceType variance = 0; + DistanceType* mean = new DistanceType[veclen_]; + memoryCounter_ += int(veclen_*sizeof(DistanceType)); + + memset(mean,0,veclen_*sizeof(DistanceType)); + + for (size_t i=0; i(), veclen_); + } + for (size_t j=0; j(), veclen_); + + DistanceType tmp = 0; + for (int i=0; iradius) { + radius = tmp; + } + } + + node->variance = variance; + node->radius = radius; + node->pivot = mean; + } + + + /** + * The method responsible with actually doing the recursive hierarchical + * clustering + * + * Params: + * node = the node to cluster + * indices = indices of the points belonging to the current node + * branching = the branching factor to use in the clustering + * + * TODO: for 1-sized clusters don't store a cluster center (it's the same as the single cluster point) + */ + void computeClustering(KMeansNodePtr node, int* indices, int indices_length, int branching, int level) + { + node->size = indices_length; + node->level = level; + + if (indices_length < branching) { + node->indices = indices; + std::sort(node->indices,node->indices+indices_length); + node->childs = NULL; + return; + } + + cv::AutoBuffer centers_idx_buf(branching); + int* centers_idx = centers_idx_buf.data(); + int centers_length; + (this->*chooseCenters)(branching, indices, indices_length, centers_idx, centers_length); + + if (centers_lengthindices = indices; + std::sort(node->indices,node->indices+indices_length); + node->childs = NULL; + return; + } + + + cv::AutoBuffer dcenters_buf(branching*veclen_); + Matrix dcenters(dcenters_buf.data(), branching, veclen_); + for (int i=0; i radiuses(branching); + cv::AutoBuffer count_buf(branching); + int* count = count_buf.data(); + for (int i=0; i belongs_to_buf(indices_length); + int* belongs_to = belongs_to_buf.data(); + for (int i=0; inew_sq_dist) { + belongs_to[i] = j; + sq_dist = new_sq_dist; + } + } + if (sq_dist>radiuses[belongs_to[i]]) { + radiuses[belongs_to[i]] = sq_dist; + } + count[belongs_to[i]]++; + } + + bool converged = false; + int iteration = 0; + while (!converged && iteration new_centroids(indices_length); + std::vector sq_dists(indices_length); + + // reassign points to clusters + KMeansDistanceComputer invoker(distance_, dataset_, branching, indices, dcenters, veclen_, new_centroids, sq_dists); + parallel_for_(cv::Range(0, (int)indices_length), invoker); + + for (int i=0; i < (int)indices_length; ++i) { + DistanceType sq_dist(sq_dists[i]); + int new_centroid(new_centroids[i]); + if (sq_dist > radiuses[new_centroid]) { + radiuses[new_centroid] = sq_dist; + } + if (new_centroid != belongs_to[i]) { + count[belongs_to[i]]--; + count[new_centroid]++; + belongs_to[i] = new_centroid; + converged = false; + } + } + + for (int i=0; ichilds = pool_.allocate(branching); + int start = 0; + int end = start; + for (int c=0; c(), veclen_); + variance += d; + mean_radius += sqrt(d); + std::swap(indices[i],indices[end]); + std::swap(belongs_to[i],belongs_to[end]); + end++; + } + } + variance /= s; + mean_radius /= s; + variance -= distance_(centers[c], ZeroIterator(), veclen_); + + node->childs[c] = pool_.allocate(); + std::memset(node->childs[c], 0, sizeof(KMeansNode)); + node->childs[c]->radius = radiuses[c]; + node->childs[c]->pivot = centers[c]; + node->childs[c]->variance = variance; + node->childs[c]->mean_radius = mean_radius; + computeClustering(node->childs[c],indices+start, end-start, branching, level+1); + start=end; + } + + delete[] centers; + } + + + + /** + * Performs one descent in the hierarchical k-means tree. The branches not + * visited are stored in a priority queue. + * + * Params: + * node = node to explore + * result = container for the k-nearest neighbors found + * vec = query points + * checks = how many points in the dataset have been checked so far + * maxChecks = maximum dataset points to checks + */ + + + void findNN(KMeansNodePtr node, ResultSet& result, const ElementType* vec, int& checks, int maxChecks, + Heap* heap) + { + // Ignore those clusters that are too far away + { + DistanceType bsq = distance_(vec, node->pivot, veclen_); + DistanceType rsq = node->radius; + DistanceType wsq = result.worstDist(); + + DistanceType val = bsq-rsq-wsq; + DistanceType val2 = val*val-4*rsq*wsq; + + //if (val>0) { + if ((val>0)&&(val2>0)) { + return; + } + } + + if (node->childs==NULL) { + if (checks>=maxChecks) { + if (result.full()) return; + } + checks += node->size; + for (int i=0; isize; ++i) { + int index = node->indices[i]; + DistanceType dist = distance_(dataset_[index], vec, veclen_); + result.addPoint(dist, index); + } + } + else { + DistanceType* domain_distances = new DistanceType[branching_]; + int closest_center = exploreNodeBranches(node, vec, domain_distances, heap); + delete[] domain_distances; + findNN(node->childs[closest_center],result,vec, checks, maxChecks, heap); + } + } + + /** + * Helper function that computes the nearest childs of a node to a given query point. + * Params: + * node = the node + * q = the query point + * distances = array with the distances to each child node. + * Returns: + */ + int exploreNodeBranches(KMeansNodePtr node, const ElementType* q, DistanceType* domain_distances, Heap* heap) + { + + int best_index = 0; + domain_distances[best_index] = distance_(q, node->childs[best_index]->pivot, veclen_); + for (int i=1; ichilds[i]->pivot, veclen_); + if (domain_distances[i]childs[best_index]->pivot; + for (int i=0; ichilds[i]->variance; + + // float dist_to_border = getDistanceToBorder(node.childs[i].pivot,best_center,q); + // if (domain_distances[i]insert(BranchSt(node->childs[i],domain_distances[i])); + } + } + + return best_index; + } + + + /** + * Function the performs exact nearest neighbor search by traversing the entire tree. + */ + void findExactNN(KMeansNodePtr node, ResultSet& result, const ElementType* vec) + { + // Ignore those clusters that are too far away + { + DistanceType bsq = distance_(vec, node->pivot, veclen_); + DistanceType rsq = node->radius; + DistanceType wsq = result.worstDist(); + + DistanceType val = bsq-rsq-wsq; + DistanceType val2 = val*val-4*rsq*wsq; + + // if (val>0) { + if ((val>0)&&(val2>0)) { + return; + } + } + + + if (node->childs==NULL) { + for (int i=0; isize; ++i) { + int index = node->indices[i]; + DistanceType dist = distance_(dataset_[index], vec, veclen_); + result.addPoint(dist, index); + } + } + else { + int* sort_indices = new int[branching_]; + + getCenterOrdering(node, vec, sort_indices); + + for (int i=0; ichilds[sort_indices[i]],result,vec); + } + + delete[] sort_indices; + } + } + + + /** + * Helper function. + * + * I computes the order in which to traverse the child nodes of a particular node. + */ + void getCenterOrdering(KMeansNodePtr node, const ElementType* q, int* sort_indices) + { + DistanceType* domain_distances = new DistanceType[branching_]; + for (int i=0; ichilds[i]->pivot, veclen_); + + int j=0; + while (domain_distances[j]j; --k) { + domain_distances[k] = domain_distances[k-1]; + sort_indices[k] = sort_indices[k-1]; + } + domain_distances[j] = dist; + sort_indices[j] = i; + } + delete[] domain_distances; + } + + /** + * Method that computes the squared distance from the query point q + * from inside region with center c to the border between this + * region and the region with center p + */ + DistanceType getDistanceToBorder(DistanceType* p, DistanceType* c, DistanceType* q) + { + DistanceType sum = 0; + DistanceType sum2 = 0; + + for (int i=0; ivariance*root->size; + + while (clusterCount::max)(); + int splitIndex = -1; + + for (int i=0; ichilds != NULL) { + + DistanceType variance = meanVariance - clusters[i]->variance*clusters[i]->size; + + for (int j=0; jchilds[j]->variance*clusters[i]->childs[j]->size; + } + if (variance clusters_length) break; + + meanVariance = minVariance; + + // split node + KMeansNodePtr toSplit = clusters[splitIndex]; + clusters[splitIndex] = toSplit->childs[0]; + for (int i=1; ichilds[i]; + } + } + + varianceValue = meanVariance/root->size; + return clusterCount; + } + +private: + /** The branching factor used in the hierarchical k-means clustering */ + int branching_; + + /** Maximum number of iterations to use when performing k-means clustering */ + int iterations_; + + /** Algorithm for choosing the cluster centers */ + flann_centers_init_t centers_init_; + + /** + * Cluster border index. This is used in the tree search phase when determining + * the closest cluster to explore next. A zero value takes into account only + * the cluster centres, a value greater then zero also take into account the size + * of the cluster. + */ + float cb_index_; + + /** + * The dataset used by this index + */ + const Matrix dataset_; + + /** Index parameters */ + IndexParams index_params_; + + /** + * Number of features in the dataset. + */ + size_t size_; + + /** + * Length of each feature. + */ + size_t veclen_; + + /** + * The root node in the tree. + */ + KMeansNodePtr root_; + + /** + * Array of indices to vectors in the dataset. + */ + int* indices_; + + /** + * The distance + */ + Distance distance_; + + /** + * Pooled memory allocator. + */ + PooledAllocator pool_; + + /** + * Memory occupied by the index. + */ + int memoryCounter_; +}; + +} + +#endif //OPENCV_FLANN_KMEANS_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/linear_index.h b/3rdparty/opencv/include/opencv2/flann/linear_index.h new file mode 100644 index 00000000..ca3f44d0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/linear_index.h @@ -0,0 +1,132 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_LINEAR_INDEX_H_ +#define OPENCV_FLANN_LINEAR_INDEX_H_ + +#include "general.h" +#include "nn_index.h" + +namespace cvflann +{ + +struct LinearIndexParams : public IndexParams +{ + LinearIndexParams() + { + (* this)["algorithm"] = FLANN_INDEX_LINEAR; + } +}; + +template +class LinearIndex : public NNIndex +{ +public: + + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + + LinearIndex(const Matrix& inputData, const IndexParams& params = LinearIndexParams(), + Distance d = Distance()) : + dataset_(inputData), index_params_(params), distance_(d) + { + } + + LinearIndex(const LinearIndex&); + LinearIndex& operator=(const LinearIndex&); + + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_LINEAR; + } + + + size_t size() const CV_OVERRIDE + { + return dataset_.rows; + } + + size_t veclen() const CV_OVERRIDE + { + return dataset_.cols; + } + + + int usedMemory() const CV_OVERRIDE + { + return 0; + } + + void buildIndex() CV_OVERRIDE + { + /* nothing to do here for linear search */ + } + + void saveIndex(FILE*) CV_OVERRIDE + { + /* nothing to do here for linear search */ + } + + + void loadIndex(FILE*) CV_OVERRIDE + { + /* nothing to do here for linear search */ + + index_params_["algorithm"] = getType(); + } + + void findNeighbors(ResultSet& resultSet, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE + { + ElementType* data = dataset_.data; + for (size_t i = 0; i < dataset_.rows; ++i, data += dataset_.cols) { + DistanceType dist = distance_(data, vec, dataset_.cols); + resultSet.addPoint(dist, (int)i); + } + } + + IndexParams getParameters() const CV_OVERRIDE + { + return index_params_; + } + +private: + /** The dataset */ + const Matrix dataset_; + /** Index parameters */ + IndexParams index_params_; + /** Index distance */ + Distance distance_; + +}; + +} + +#endif // OPENCV_FLANN_LINEAR_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/logger.h b/3rdparty/opencv/include/opencv2/flann/logger.h new file mode 100644 index 00000000..32618dbb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/logger.h @@ -0,0 +1,135 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_LOGGER_H +#define OPENCV_FLANN_LOGGER_H + +#include +#include + +#include "defines.h" + + +namespace cvflann +{ + +class Logger +{ + Logger() : stream(stdout), logLevel(FLANN_LOG_WARN) {} + + ~Logger() + { + if ((stream!=NULL)&&(stream!=stdout)) { + fclose(stream); + } + } + + static Logger& instance() + { + static Logger logger; + return logger; + } + + void _setDestination(const char* name) + { + if (name==NULL) { + stream = stdout; + } + else { +#ifdef _MSC_VER + if (fopen_s(&stream, name, "w") != 0) + stream = NULL; +#else + stream = fopen(name,"w"); +#endif + if (stream == NULL) { + stream = stdout; + } + } + } + + int _log(int level, const char* fmt, va_list arglist) + { + if (level > logLevel ) return -1; + int ret = vfprintf(stream, fmt, arglist); + return ret; + } + +public: + /** + * Sets the logging level. All messages with lower priority will be ignored. + * @param level Logging level + */ + static void setLevel(int level) { instance().logLevel = level; } + + /** + * Sets the logging destination + * @param name Filename or NULL for console + */ + static void setDestination(const char* name) { instance()._setDestination(name); } + + /** + * Print log message + * @param level Log level + * @param fmt Message format + * @return + */ + static int log(int level, const char* fmt, ...) + { + va_list arglist; + va_start(arglist, fmt); + int ret = instance()._log(level,fmt,arglist); + va_end(arglist); + return ret; + } + +#define LOG_METHOD(NAME,LEVEL) \ + static int NAME(const char* fmt, ...) \ + { \ + va_list ap; \ + va_start(ap, fmt); \ + int ret = instance()._log(LEVEL, fmt, ap); \ + va_end(ap); \ + return ret; \ + } + + LOG_METHOD(fatal, FLANN_LOG_FATAL) + LOG_METHOD(error, FLANN_LOG_ERROR) + LOG_METHOD(warn, FLANN_LOG_WARN) + LOG_METHOD(info, FLANN_LOG_INFO) + +private: + FILE* stream; + int logLevel; +}; + +} + +#endif //OPENCV_FLANN_LOGGER_H diff --git a/3rdparty/opencv/include/opencv2/flann/lsh_index.h b/3rdparty/opencv/include/opencv2/flann/lsh_index.h new file mode 100644 index 00000000..42afe892 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/lsh_index.h @@ -0,0 +1,392 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +/*********************************************************************** + * Author: Vincent Rabaud + *************************************************************************/ + +#ifndef OPENCV_FLANN_LSH_INDEX_H_ +#define OPENCV_FLANN_LSH_INDEX_H_ + +#include +#include +#include +#include +#include + +#include "general.h" +#include "nn_index.h" +#include "matrix.h" +#include "result_set.h" +#include "heap.h" +#include "lsh_table.h" +#include "allocator.h" +#include "random.h" +#include "saving.h" + +namespace cvflann +{ + +struct LshIndexParams : public IndexParams +{ + LshIndexParams(unsigned int table_number = 12, unsigned int key_size = 20, unsigned int multi_probe_level = 2) + { + (* this)["algorithm"] = FLANN_INDEX_LSH; + // The number of hash tables to use + (*this)["table_number"] = table_number; + // The length of the key in the hash tables + (*this)["key_size"] = key_size; + // Number of levels to use in multi-probe (0 for standard LSH) + (*this)["multi_probe_level"] = multi_probe_level; + } +}; + +/** + * Randomized kd-tree index + * + * Contains the k-d trees and other information for indexing a set of points + * for nearest-neighbor matching. + */ +template +class LshIndex : public NNIndex +{ +public: + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + + /** Constructor + * @param input_data dataset with the input features + * @param params parameters passed to the LSH algorithm + * @param d the distance used + */ + LshIndex(const Matrix& input_data, const IndexParams& params = LshIndexParams(), + Distance d = Distance()) : + dataset_(input_data), index_params_(params), distance_(d) + { + // cv::flann::IndexParams sets integer params as 'int', so it is used with get_param + // in place of 'unsigned int' + table_number_ = (unsigned int)get_param(index_params_,"table_number",12); + key_size_ = (unsigned int)get_param(index_params_,"key_size",20); + multi_probe_level_ = (unsigned int)get_param(index_params_,"multi_probe_level",2); + + feature_size_ = (unsigned)dataset_.cols; + fill_xor_mask(0, key_size_, multi_probe_level_, xor_masks_); + } + + + LshIndex(const LshIndex&); + LshIndex& operator=(const LshIndex&); + + /** + * Builds the index + */ + void buildIndex() CV_OVERRIDE + { + tables_.resize(table_number_); + for (unsigned int i = 0; i < table_number_; ++i) { + lsh::LshTable& table = tables_[i]; + table = lsh::LshTable(feature_size_, key_size_); + + // Add the features to the table + table.add(dataset_); + } + } + + flann_algorithm_t getType() const CV_OVERRIDE + { + return FLANN_INDEX_LSH; + } + + + void saveIndex(FILE* stream) CV_OVERRIDE + { + save_value(stream,table_number_); + save_value(stream,key_size_); + save_value(stream,multi_probe_level_); + save_value(stream, dataset_); + } + + void loadIndex(FILE* stream) CV_OVERRIDE + { + load_value(stream, table_number_); + load_value(stream, key_size_); + load_value(stream, multi_probe_level_); + load_value(stream, dataset_); + // Building the index is so fast we can afford not storing it + buildIndex(); + + index_params_["algorithm"] = getType(); + index_params_["table_number"] = table_number_; + index_params_["key_size"] = key_size_; + index_params_["multi_probe_level"] = multi_probe_level_; + } + + /** + * Returns size of index. + */ + size_t size() const CV_OVERRIDE + { + return dataset_.rows; + } + + /** + * Returns the length of an index feature. + */ + size_t veclen() const CV_OVERRIDE + { + return feature_size_; + } + + /** + * Computes the index memory usage + * Returns: memory used by the index + */ + int usedMemory() const CV_OVERRIDE + { + return (int)(dataset_.rows * sizeof(int)); + } + + + IndexParams getParameters() const CV_OVERRIDE + { + return index_params_; + } + + /** + * \brief Perform k-nearest neighbor search + * \param[in] queries The query points for which to find the nearest neighbors + * \param[out] indices The indices of the nearest neighbors found + * \param[out] dists Distances to the nearest neighbors found + * \param[in] knn Number of nearest neighbors to return + * \param[in] params Search parameters + */ + virtual void knnSearch(const Matrix& queries, Matrix& indices, Matrix& dists, int knn, const SearchParams& params) CV_OVERRIDE + { + assert(queries.cols == veclen()); + assert(indices.rows >= queries.rows); + assert(dists.rows >= queries.rows); + assert(int(indices.cols) >= knn); + assert(int(dists.cols) >= knn); + + + KNNUniqueResultSet resultSet(knn); + for (size_t i = 0; i < queries.rows; i++) { + resultSet.clear(); + std::fill_n(indices[i], knn, -1); + std::fill_n(dists[i], knn, std::numeric_limits::max()); + findNeighbors(resultSet, queries[i], params); + if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices[i], dists[i], knn); + else resultSet.copy(indices[i], dists[i], knn); + } + } + + + /** + * Find set of nearest neighbors to vec. Their indices are stored inside + * the result object. + * + * Params: + * result = the result object in which the indices of the nearest-neighbors are stored + * vec = the vector for which to search the nearest neighbors + * maxCheck = the maximum number of restarts (in a best-bin-first manner) + */ + void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& /*searchParams*/) CV_OVERRIDE + { + getNeighbors(vec, result); + } + +private: + /** Defines the comparator on score and index + */ + typedef std::pair ScoreIndexPair; + struct SortScoreIndexPairOnSecond + { + bool operator()(const ScoreIndexPair& left, const ScoreIndexPair& right) const + { + return left.second < right.second; + } + }; + + /** Fills the different xor masks to use when getting the neighbors in multi-probe LSH + * @param key the key we build neighbors from + * @param lowest_index the lowest index of the bit set + * @param level the multi-probe level we are at + * @param xor_masks all the xor mask + */ + void fill_xor_mask(lsh::BucketKey key, int lowest_index, unsigned int level, + std::vector& xor_masks) + { + xor_masks.push_back(key); + if (level == 0) return; + for (int index = lowest_index - 1; index >= 0; --index) { + // Create a new key + lsh::BucketKey new_key = key | (1 << index); + fill_xor_mask(new_key, index, level - 1, xor_masks); + } + } + + /** Performs the approximate nearest-neighbor search. + * @param vec the feature to analyze + * @param do_radius flag indicating if we check the radius too + * @param radius the radius if it is a radius search + * @param do_k flag indicating if we limit the number of nn + * @param k_nn the number of nearest neighbors + * @param checked_average used for debugging + */ + void getNeighbors(const ElementType* vec, bool /*do_radius*/, float radius, bool do_k, unsigned int k_nn, + float& /*checked_average*/) + { + static std::vector score_index_heap; + + if (do_k) { + unsigned int worst_score = std::numeric_limits::max(); + typename std::vector >::const_iterator table = tables_.begin(); + typename std::vector >::const_iterator table_end = tables_.end(); + for (; table != table_end; ++table) { + size_t key = table->getKey(vec); + std::vector::const_iterator xor_mask = xor_masks_.begin(); + std::vector::const_iterator xor_mask_end = xor_masks_.end(); + for (; xor_mask != xor_mask_end; ++xor_mask) { + size_t sub_key = key ^ (*xor_mask); + const lsh::Bucket* bucket = table->getBucketFromKey(sub_key); + if (bucket == 0) continue; + + // Go over each descriptor index + std::vector::const_iterator training_index = bucket->begin(); + std::vector::const_iterator last_training_index = bucket->end(); + DistanceType hamming_distance; + + // Process the rest of the candidates + for (; training_index < last_training_index; ++training_index) { + hamming_distance = distance_(vec, dataset_[*training_index], dataset_.cols); + + if (hamming_distance < worst_score) { + // Insert the new element + score_index_heap.push_back(ScoreIndexPair(hamming_distance, training_index)); + std::push_heap(score_index_heap.begin(), score_index_heap.end()); + + if (score_index_heap.size() > (unsigned int)k_nn) { + // Remove the highest distance value as we have too many elements + std::pop_heap(score_index_heap.begin(), score_index_heap.end()); + score_index_heap.pop_back(); + // Keep track of the worst score + worst_score = score_index_heap.front().first; + } + } + } + } + } + } + else { + typename std::vector >::const_iterator table = tables_.begin(); + typename std::vector >::const_iterator table_end = tables_.end(); + for (; table != table_end; ++table) { + size_t key = table->getKey(vec); + std::vector::const_iterator xor_mask = xor_masks_.begin(); + std::vector::const_iterator xor_mask_end = xor_masks_.end(); + for (; xor_mask != xor_mask_end; ++xor_mask) { + size_t sub_key = key ^ (*xor_mask); + const lsh::Bucket* bucket = table->getBucketFromKey(sub_key); + if (bucket == 0) continue; + + // Go over each descriptor index + std::vector::const_iterator training_index = bucket->begin(); + std::vector::const_iterator last_training_index = bucket->end(); + DistanceType hamming_distance; + + // Process the rest of the candidates + for (; training_index < last_training_index; ++training_index) { + // Compute the Hamming distance + hamming_distance = distance_(vec, dataset_[*training_index], dataset_.cols); + if (hamming_distance < radius) score_index_heap.push_back(ScoreIndexPair(hamming_distance, training_index)); + } + } + } + } + } + + /** Performs the approximate nearest-neighbor search. + * This is a slower version than the above as it uses the ResultSet + * @param vec the feature to analyze + */ + void getNeighbors(const ElementType* vec, ResultSet& result) + { + typename std::vector >::const_iterator table = tables_.begin(); + typename std::vector >::const_iterator table_end = tables_.end(); + for (; table != table_end; ++table) { + size_t key = table->getKey(vec); + std::vector::const_iterator xor_mask = xor_masks_.begin(); + std::vector::const_iterator xor_mask_end = xor_masks_.end(); + for (; xor_mask != xor_mask_end; ++xor_mask) { + size_t sub_key = key ^ (*xor_mask); + const lsh::Bucket* bucket = table->getBucketFromKey((lsh::BucketKey)sub_key); + if (bucket == 0) continue; + + // Go over each descriptor index + std::vector::const_iterator training_index = bucket->begin(); + std::vector::const_iterator last_training_index = bucket->end(); + DistanceType hamming_distance; + + // Process the rest of the candidates + for (; training_index < last_training_index; ++training_index) { + // Compute the Hamming distance + hamming_distance = distance_(vec, dataset_[*training_index], (int)dataset_.cols); + result.addPoint(hamming_distance, *training_index); + } + } + } + } + + /** The different hash tables */ + std::vector > tables_; + + /** The data the LSH tables where built from */ + Matrix dataset_; + + /** The size of the features (as ElementType[]) */ + unsigned int feature_size_; + + IndexParams index_params_; + + /** table number */ + unsigned int table_number_; + /** key size */ + unsigned int key_size_; + /** How far should we look for neighbors in multi-probe LSH */ + unsigned int multi_probe_level_; + + /** The XOR masks to apply to a key to get the neighboring buckets */ + std::vector xor_masks_; + + Distance distance_; +}; +} + +#endif //OPENCV_FLANN_LSH_INDEX_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/lsh_table.h b/3rdparty/opencv/include/opencv2/flann/lsh_table.h new file mode 100644 index 00000000..b07a9d52 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/lsh_table.h @@ -0,0 +1,513 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +/*********************************************************************** + * Author: Vincent Rabaud + *************************************************************************/ + +#ifndef OPENCV_FLANN_LSH_TABLE_H_ +#define OPENCV_FLANN_LSH_TABLE_H_ + +#include +#include +#include +#include +// TODO as soon as we use C++0x, use the code in USE_UNORDERED_MAP +#ifdef __GXX_EXPERIMENTAL_CXX0X__ +# define USE_UNORDERED_MAP 1 +#else +# define USE_UNORDERED_MAP 0 +#endif +#if USE_UNORDERED_MAP +#include +#else +#include +#endif +#include +#include + +#include "dynamic_bitset.h" +#include "matrix.h" + +namespace cvflann +{ + +namespace lsh +{ + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** What is stored in an LSH bucket + */ +typedef uint32_t FeatureIndex; +/** The id from which we can get a bucket back in an LSH table + */ +typedef unsigned int BucketKey; + +/** A bucket in an LSH table + */ +typedef std::vector Bucket; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** POD for stats about an LSH table + */ +struct LshStats +{ + std::vector bucket_sizes_; + size_t n_buckets_; + size_t bucket_size_mean_; + size_t bucket_size_median_; + size_t bucket_size_min_; + size_t bucket_size_max_; + size_t bucket_size_std_dev; + /** Each contained vector contains three value: beginning/end for interval, number of elements in the bin + */ + std::vector > size_histogram_; +}; + +/** Overload the << operator for LshStats + * @param out the streams + * @param stats the stats to display + * @return the streams + */ +inline std::ostream& operator <<(std::ostream& out, const LshStats& stats) +{ + int w = 20; + out << "Lsh Table Stats:\n" << std::setw(w) << std::setiosflags(std::ios::right) << "N buckets : " + << stats.n_buckets_ << "\n" << std::setw(w) << std::setiosflags(std::ios::right) << "mean size : " + << std::setiosflags(std::ios::left) << stats.bucket_size_mean_ << "\n" << std::setw(w) + << std::setiosflags(std::ios::right) << "median size : " << stats.bucket_size_median_ << "\n" << std::setw(w) + << std::setiosflags(std::ios::right) << "min size : " << std::setiosflags(std::ios::left) + << stats.bucket_size_min_ << "\n" << std::setw(w) << std::setiosflags(std::ios::right) << "max size : " + << std::setiosflags(std::ios::left) << stats.bucket_size_max_; + + // Display the histogram + out << std::endl << std::setw(w) << std::setiosflags(std::ios::right) << "histogram : " + << std::setiosflags(std::ios::left); + for (std::vector >::const_iterator iterator = stats.size_histogram_.begin(), end = + stats.size_histogram_.end(); iterator != end; ++iterator) out << (*iterator)[0] << "-" << (*iterator)[1] << ": " << (*iterator)[2] << ", "; + + return out; +} + + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** Lsh hash table. As its key is a sub-feature, and as usually + * the size of it is pretty small, we keep it as a continuous memory array. + * The value is an index in the corpus of features (we keep it as an unsigned + * int for pure memory reasons, it could be a size_t) + */ +template +class LshTable +{ +public: + /** A container of all the feature indices. Optimized for space + */ +#if USE_UNORDERED_MAP + typedef std::unordered_map BucketsSpace; +#else + typedef std::map BucketsSpace; +#endif + + /** A container of all the feature indices. Optimized for speed + */ + typedef std::vector BucketsSpeed; + + /** Default constructor + */ + LshTable() + { + key_size_ = 0; + feature_size_ = 0; + speed_level_ = kArray; + } + + /** Default constructor + * Create the mask and allocate the memory + * @param feature_size is the size of the feature (considered as a ElementType[]) + * @param key_size is the number of bits that are turned on in the feature + */ + LshTable(unsigned int feature_size, unsigned int key_size) + { + feature_size_ = feature_size; + CV_UNUSED(key_size); + std::cerr << "LSH is not implemented for that type" << std::endl; + assert(0); + } + + /** Add a feature to the table + * @param value the value to store for that feature + * @param feature the feature itself + */ + void add(unsigned int value, const ElementType* feature) + { + // Add the value to the corresponding bucket + BucketKey key = (lsh::BucketKey)getKey(feature); + + switch (speed_level_) { + case kArray: + // That means we get the buckets from an array + buckets_speed_[key].push_back(value); + break; + case kBitsetHash: + // That means we can check the bitset for the presence of a key + key_bitset_.set(key); + buckets_space_[key].push_back(value); + break; + case kHash: + { + // That means we have to check for the hash table for the presence of a key + buckets_space_[key].push_back(value); + break; + } + } + } + + /** Add a set of features to the table + * @param dataset the values to store + */ + void add(Matrix dataset) + { +#if USE_UNORDERED_MAP + buckets_space_.rehash((buckets_space_.size() + dataset.rows) * 1.2); +#endif + // Add the features to the table + for (unsigned int i = 0; i < dataset.rows; ++i) add(i, dataset[i]); + // Now that the table is full, optimize it for speed/space + optimize(); + } + + /** Get a bucket given the key + * @param key + * @return + */ + inline const Bucket* getBucketFromKey(BucketKey key) const + { + // Generate other buckets + switch (speed_level_) { + case kArray: + // That means we get the buckets from an array + return &buckets_speed_[key]; + break; + case kBitsetHash: + // That means we can check the bitset for the presence of a key + if (key_bitset_.test(key)) return &buckets_space_.find(key)->second; + else return 0; + break; + case kHash: + { + // That means we have to check for the hash table for the presence of a key + BucketsSpace::const_iterator bucket_it, bucket_end = buckets_space_.end(); + bucket_it = buckets_space_.find(key); + // Stop here if that bucket does not exist + if (bucket_it == bucket_end) return 0; + else return &bucket_it->second; + break; + } + } + return 0; + } + + /** Compute the sub-signature of a feature + */ + size_t getKey(const ElementType* /*feature*/) const + { + std::cerr << "LSH is not implemented for that type" << std::endl; + assert(0); + return 1; + } + + /** Get statistics about the table + * @return + */ + LshStats getStats() const; + +private: + /** defines the speed fo the implementation + * kArray uses a vector for storing data + * kBitsetHash uses a hash map but checks for the validity of a key with a bitset + * kHash uses a hash map only + */ + enum SpeedLevel + { + kArray, kBitsetHash, kHash + }; + + /** Initialize some variables + */ + void initialize(size_t key_size) + { + const size_t key_size_lower_bound = 1; + //a value (size_t(1) << key_size) must fit the size_t type so key_size has to be strictly less than size of size_t + const size_t key_size_upper_bound = (std::min)(sizeof(BucketKey) * CHAR_BIT + 1, sizeof(size_t) * CHAR_BIT); + if (key_size < key_size_lower_bound || key_size >= key_size_upper_bound) + { + CV_Error(cv::Error::StsBadArg, cv::format("Invalid key_size (=%d). Valid values for your system are %d <= key_size < %d.", (int)key_size, (int)key_size_lower_bound, (int)key_size_upper_bound)); + } + + speed_level_ = kHash; + key_size_ = (unsigned)key_size; + } + + /** Optimize the table for speed/space + */ + void optimize() + { + // If we are already using the fast storage, no need to do anything + if (speed_level_ == kArray) return; + + // Use an array if it will be more than half full + if (buckets_space_.size() > ((size_t(1) << key_size_) / 2)) { + speed_level_ = kArray; + // Fill the array version of it + buckets_speed_.resize(size_t(1) << key_size_); + for (BucketsSpace::const_iterator key_bucket = buckets_space_.begin(); key_bucket != buckets_space_.end(); ++key_bucket) buckets_speed_[key_bucket->first] = key_bucket->second; + + // Empty the hash table + buckets_space_.clear(); + return; + } + + // If the bitset is going to use less than 10% of the RAM of the hash map (at least 1 size_t for the key and two + // for the vector) or less than 512MB (key_size_ <= 30) + if (((std::max(buckets_space_.size(), buckets_speed_.size()) * CHAR_BIT * 3 * sizeof(BucketKey)) / 10 + >= (size_t(1) << key_size_)) || (key_size_ <= 32)) { + speed_level_ = kBitsetHash; + key_bitset_.resize(size_t(1) << key_size_); + key_bitset_.reset(); + // Try with the BucketsSpace + for (BucketsSpace::const_iterator key_bucket = buckets_space_.begin(); key_bucket != buckets_space_.end(); ++key_bucket) key_bitset_.set(key_bucket->first); + } + else { + speed_level_ = kHash; + key_bitset_.clear(); + } + } + + /** The vector of all the buckets if they are held for speed + */ + BucketsSpeed buckets_speed_; + + /** The hash table of all the buckets in case we cannot use the speed version + */ + BucketsSpace buckets_space_; + + /** What is used to store the data */ + SpeedLevel speed_level_; + + /** If the subkey is small enough, it will keep track of which subkeys are set through that bitset + * That is just a speedup so that we don't look in the hash table (which can be mush slower that checking a bitset) + */ + DynamicBitset key_bitset_; + + /** The size of the sub-signature in bits + */ + unsigned int key_size_; + + unsigned int feature_size_; + + // Members only used for the unsigned char specialization + /** The mask to apply to a feature to get the hash key + * Only used in the unsigned char case + */ + std::vector mask_; +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// +// Specialization for unsigned char + +template<> +inline LshTable::LshTable(unsigned int feature_size, unsigned int subsignature_size) +{ + feature_size_ = feature_size; + initialize(subsignature_size); + // Allocate the mask + mask_ = std::vector((feature_size * sizeof(char) + sizeof(size_t) - 1) / sizeof(size_t), 0); + + // A bit brutal but fast to code + std::vector indices(feature_size * CHAR_BIT); + for (size_t i = 0; i < feature_size * CHAR_BIT; ++i) indices[i] = (int)i; +#ifndef OPENCV_FLANN_USE_STD_RAND + cv::randShuffle(indices); +#else + std::random_shuffle(indices.begin(), indices.end()); +#endif + + // Generate a random set of order of subsignature_size_ bits + for (unsigned int i = 0; i < key_size_; ++i) { + size_t index = indices[i]; + + // Set that bit in the mask + size_t divisor = CHAR_BIT * sizeof(size_t); + size_t idx = index / divisor; //pick the right size_t index + mask_[idx] |= size_t(1) << (index % divisor); //use modulo to find the bit offset + } + + // Set to 1 if you want to display the mask for debug +#if 0 + { + size_t bcount = 0; + BOOST_FOREACH(size_t mask_block, mask_){ + out << std::setw(sizeof(size_t) * CHAR_BIT / 4) << std::setfill('0') << std::hex << mask_block + << std::endl; + bcount += __builtin_popcountll(mask_block); + } + out << "bit count : " << std::dec << bcount << std::endl; + out << "mask size : " << mask_.size() << std::endl; + return out; + } +#endif +} + +/** Return the Subsignature of a feature + * @param feature the feature to analyze + */ +template<> +inline size_t LshTable::getKey(const unsigned char* feature) const +{ + // no need to check if T is dividable by sizeof(size_t) like in the Hamming + // distance computation as we have a mask + // FIXIT: This is bad assumption, because we reading tail bytes after of the allocated features buffer + const size_t* feature_block_ptr = reinterpret_cast ((const void*)feature); + + // Figure out the subsignature of the feature + // Given the feature ABCDEF, and the mask 001011, the output will be + // 000CEF + size_t subsignature = 0; + size_t bit_index = 1; + + for (unsigned i = 0; i < feature_size_; i += sizeof(size_t)) { + // get the mask and signature blocks + size_t feature_block; + if (i <= feature_size_ - sizeof(size_t)) + { + feature_block = *feature_block_ptr; + } + else + { + size_t tmp = 0; + memcpy(&tmp, feature_block_ptr, feature_size_ - i); // preserve bytes order + feature_block = tmp; + } + size_t mask_block = mask_[i / sizeof(size_t)]; + while (mask_block) { + // Get the lowest set bit in the mask block + size_t lowest_bit = mask_block & (-(ptrdiff_t)mask_block); + // Add it to the current subsignature if necessary + subsignature += (feature_block & lowest_bit) ? bit_index : 0; + // Reset the bit in the mask block + mask_block ^= lowest_bit; + // increment the bit index for the subsignature + bit_index <<= 1; + } + // Check the next feature block + ++feature_block_ptr; + } + return subsignature; +} + +template<> +inline LshStats LshTable::getStats() const +{ + LshStats stats; + stats.bucket_size_mean_ = 0; + if ((buckets_speed_.empty()) && (buckets_space_.empty())) { + stats.n_buckets_ = 0; + stats.bucket_size_median_ = 0; + stats.bucket_size_min_ = 0; + stats.bucket_size_max_ = 0; + return stats; + } + + if (!buckets_speed_.empty()) { + for (BucketsSpeed::const_iterator pbucket = buckets_speed_.begin(); pbucket != buckets_speed_.end(); ++pbucket) { + stats.bucket_sizes_.push_back((lsh::FeatureIndex)pbucket->size()); + stats.bucket_size_mean_ += pbucket->size(); + } + stats.bucket_size_mean_ /= buckets_speed_.size(); + stats.n_buckets_ = buckets_speed_.size(); + } + else { + for (BucketsSpace::const_iterator x = buckets_space_.begin(); x != buckets_space_.end(); ++x) { + stats.bucket_sizes_.push_back((lsh::FeatureIndex)x->second.size()); + stats.bucket_size_mean_ += x->second.size(); + } + stats.bucket_size_mean_ /= buckets_space_.size(); + stats.n_buckets_ = buckets_space_.size(); + } + + std::sort(stats.bucket_sizes_.begin(), stats.bucket_sizes_.end()); + + // BOOST_FOREACH(int size, stats.bucket_sizes_) + // std::cout << size << " "; + // std::cout << std::endl; + stats.bucket_size_median_ = stats.bucket_sizes_[stats.bucket_sizes_.size() / 2]; + stats.bucket_size_min_ = stats.bucket_sizes_.front(); + stats.bucket_size_max_ = stats.bucket_sizes_.back(); + + // TODO compute mean and std + /*float mean, stddev; + stats.bucket_size_mean_ = mean; + stats.bucket_size_std_dev = stddev;*/ + + // Include a histogram of the buckets + unsigned int bin_start = 0; + unsigned int bin_end = 20; + bool is_new_bin = true; + for (std::vector::iterator iterator = stats.bucket_sizes_.begin(), end = stats.bucket_sizes_.end(); iterator + != end; ) + if (*iterator < bin_end) { + if (is_new_bin) { + stats.size_histogram_.push_back(std::vector(3, 0)); + stats.size_histogram_.back()[0] = bin_start; + stats.size_histogram_.back()[1] = bin_end - 1; + is_new_bin = false; + } + ++stats.size_histogram_.back()[2]; + ++iterator; + } + else { + bin_start += 20; + bin_end += 20; + is_new_bin = true; + } + + return stats; +} + +// End the two namespaces +} +} + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +#endif /* OPENCV_FLANN_LSH_TABLE_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/matrix.h b/3rdparty/opencv/include/opencv2/flann/matrix.h new file mode 100644 index 00000000..f6092d13 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/matrix.h @@ -0,0 +1,116 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_DATASET_H_ +#define OPENCV_FLANN_DATASET_H_ + +#include + +#include "general.h" + +namespace cvflann +{ + +/** + * Class that implements a simple rectangular matrix stored in a memory buffer and + * provides convenient matrix-like access using the [] operators. + */ +template +class Matrix +{ +public: + typedef T type; + + size_t rows; + size_t cols; + size_t stride; + T* data; + + Matrix() : rows(0), cols(0), stride(0), data(NULL) + { + } + + Matrix(T* data_, size_t rows_, size_t cols_, size_t stride_ = 0) : + rows(rows_), cols(cols_), stride(stride_), data(data_) + { + if (stride==0) stride = cols; + } + + /** + * Convenience function for deallocating the storage data. + */ + CV_DEPRECATED void free() + { + fprintf(stderr, "The cvflann::Matrix::free() method is deprecated " + "and it does not do any memory deallocation any more. You are" + "responsible for deallocating the matrix memory (by doing" + "'delete[] matrix.data' for example)"); + } + + /** + * Operator that return a (pointer to a) row of the data. + */ + T* operator[](size_t index) const + { + return data+index*stride; + } +}; + + +class UntypedMatrix +{ +public: + size_t rows; + size_t cols; + void* data; + flann_datatype_t type; + + UntypedMatrix(void* data_, long rows_, long cols_) : + rows(rows_), cols(cols_), data(data_) + { + } + + ~UntypedMatrix() + { + } + + + template + Matrix as() + { + return Matrix((T*)data, rows, cols); + } +}; + + + +} + +#endif //OPENCV_FLANN_DATASET_H_ diff --git a/3rdparty/opencv/include/opencv2/flann/miniflann.hpp b/3rdparty/opencv/include/opencv2/flann/miniflann.hpp new file mode 100644 index 00000000..bda2ed49 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/miniflann.hpp @@ -0,0 +1,162 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_MINIFLANN_HPP +#define OPENCV_MINIFLANN_HPP + +#include "opencv2/core.hpp" +#include "opencv2/flann/defines.h" + +namespace cv +{ + +namespace flann +{ + +struct CV_EXPORTS IndexParams +{ + IndexParams(); + ~IndexParams(); + + String getString(const String& key, const String& defaultVal=String()) const; + int getInt(const String& key, int defaultVal=-1) const; + double getDouble(const String& key, double defaultVal=-1) const; + + void setString(const String& key, const String& value); + void setInt(const String& key, int value); + void setDouble(const String& key, double value); + void setFloat(const String& key, float value); + void setBool(const String& key, bool value); + void setAlgorithm(int value); + + void getAll(std::vector& names, + std::vector& types, + std::vector& strValues, + std::vector& numValues) const; + + void* params; + +private: + IndexParams(const IndexParams &); // copy disabled + IndexParams& operator=(const IndexParams &); // assign disabled +}; + +struct CV_EXPORTS KDTreeIndexParams : public IndexParams +{ + KDTreeIndexParams(int trees=4); +}; + +struct CV_EXPORTS LinearIndexParams : public IndexParams +{ + LinearIndexParams(); +}; + +struct CV_EXPORTS CompositeIndexParams : public IndexParams +{ + CompositeIndexParams(int trees = 4, int branching = 32, int iterations = 11, + cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM, float cb_index = 0.2f ); +}; + +struct CV_EXPORTS AutotunedIndexParams : public IndexParams +{ + AutotunedIndexParams(float target_precision = 0.8f, float build_weight = 0.01f, + float memory_weight = 0, float sample_fraction = 0.1f); +}; + +struct CV_EXPORTS HierarchicalClusteringIndexParams : public IndexParams +{ + HierarchicalClusteringIndexParams(int branching = 32, + cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM, int trees = 4, int leaf_size = 100 ); +}; + +struct CV_EXPORTS KMeansIndexParams : public IndexParams +{ + KMeansIndexParams(int branching = 32, int iterations = 11, + cvflann::flann_centers_init_t centers_init = cvflann::FLANN_CENTERS_RANDOM, float cb_index = 0.2f ); +}; + +struct CV_EXPORTS LshIndexParams : public IndexParams +{ + LshIndexParams(int table_number, int key_size, int multi_probe_level); +}; + +struct CV_EXPORTS SavedIndexParams : public IndexParams +{ + SavedIndexParams(const String& filename); +}; + +struct CV_EXPORTS SearchParams : public IndexParams +{ + SearchParams( int checks = 32, float eps = 0, bool sorted = true ); +}; + +class CV_EXPORTS_W Index +{ +public: + CV_WRAP Index(); + CV_WRAP Index(InputArray features, const IndexParams& params, cvflann::flann_distance_t distType=cvflann::FLANN_DIST_L2); + virtual ~Index(); + + CV_WRAP virtual void build(InputArray features, const IndexParams& params, cvflann::flann_distance_t distType=cvflann::FLANN_DIST_L2); + CV_WRAP virtual void knnSearch(InputArray query, OutputArray indices, + OutputArray dists, int knn, const SearchParams& params=SearchParams()); + + CV_WRAP virtual int radiusSearch(InputArray query, OutputArray indices, + OutputArray dists, double radius, int maxResults, + const SearchParams& params=SearchParams()); + + CV_WRAP virtual void save(const String& filename) const; + CV_WRAP virtual bool load(InputArray features, const String& filename); + CV_WRAP virtual void release(); + CV_WRAP cvflann::flann_distance_t getDistance() const; + CV_WRAP cvflann::flann_algorithm_t getAlgorithm() const; + +protected: + cvflann::flann_distance_t distType; + cvflann::flann_algorithm_t algo; + int featureType; + void* index; +}; + +} } // namespace cv::flann + +#endif diff --git a/3rdparty/opencv/include/opencv2/flann/nn_index.h b/3rdparty/opencv/include/opencv2/flann/nn_index.h new file mode 100644 index 00000000..381d4bc3 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/nn_index.h @@ -0,0 +1,177 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_NNINDEX_H +#define OPENCV_FLANN_NNINDEX_H + +#include "general.h" +#include "matrix.h" +#include "result_set.h" +#include "params.h" + +namespace cvflann +{ + +/** + * Nearest-neighbour index base class + */ +template +class NNIndex +{ + typedef typename Distance::ElementType ElementType; + typedef typename Distance::ResultType DistanceType; + +public: + + virtual ~NNIndex() {} + + /** + * \brief Builds the index + */ + virtual void buildIndex() = 0; + + /** + * \brief Perform k-nearest neighbor search + * \param[in] queries The query points for which to find the nearest neighbors + * \param[out] indices The indices of the nearest neighbors found + * \param[out] dists Distances to the nearest neighbors found + * \param[in] knn Number of nearest neighbors to return + * \param[in] params Search parameters + */ + virtual void knnSearch(const Matrix& queries, Matrix& indices, Matrix& dists, int knn, const SearchParams& params) + { + assert(queries.cols == veclen()); + assert(indices.rows >= queries.rows); + assert(dists.rows >= queries.rows); + assert(int(indices.cols) >= knn); + assert(int(dists.cols) >= knn); + +#if 0 + KNNResultSet resultSet(knn); + for (size_t i = 0; i < queries.rows; i++) { + resultSet.init(indices[i], dists[i]); + findNeighbors(resultSet, queries[i], params); + } +#else + KNNUniqueResultSet resultSet(knn); + for (size_t i = 0; i < queries.rows; i++) { + resultSet.clear(); + findNeighbors(resultSet, queries[i], params); + if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices[i], dists[i], knn); + else resultSet.copy(indices[i], dists[i], knn); + } +#endif + } + + /** + * \brief Perform radius search + * \param[in] query The query point + * \param[out] indices The indinces of the neighbors found within the given radius + * \param[out] dists The distances to the nearest neighbors found + * \param[in] radius The radius used for search + * \param[in] params Search parameters + * \returns Number of neighbors found + */ + virtual int radiusSearch(const Matrix& query, Matrix& indices, Matrix& dists, float radius, const SearchParams& params) + { + if (query.rows != 1) { + fprintf(stderr, "I can only search one feature at a time for range search\n"); + return -1; + } + assert(query.cols == veclen()); + assert(indices.cols == dists.cols); + + int n = 0; + int* indices_ptr = NULL; + DistanceType* dists_ptr = NULL; + if (indices.cols > 0) { + n = (int)indices.cols; + indices_ptr = indices[0]; + dists_ptr = dists[0]; + } + + RadiusUniqueResultSet resultSet((DistanceType)radius); + resultSet.clear(); + findNeighbors(resultSet, query[0], params); + if (n>0) { + if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices_ptr, dists_ptr, n); + else resultSet.copy(indices_ptr, dists_ptr, n); + } + + return (int)resultSet.size(); + } + + /** + * \brief Saves the index to a stream + * \param stream The stream to save the index to + */ + virtual void saveIndex(FILE* stream) = 0; + + /** + * \brief Loads the index from a stream + * \param stream The stream from which the index is loaded + */ + virtual void loadIndex(FILE* stream) = 0; + + /** + * \returns number of features in this index. + */ + virtual size_t size() const = 0; + + /** + * \returns The dimensionality of the features in this index. + */ + virtual size_t veclen() const = 0; + + /** + * \returns The amount of memory (in bytes) used by the index. + */ + virtual int usedMemory() const = 0; + + /** + * \returns The index type (kdtree, kmeans,...) + */ + virtual flann_algorithm_t getType() const = 0; + + /** + * \returns The index parameters + */ + virtual IndexParams getParameters() const = 0; + + + /** + * \brief Method that searches for nearest-neighbours + */ + virtual void findNeighbors(ResultSet& result, const ElementType* vec, const SearchParams& searchParams) = 0; +}; + +} + +#endif //OPENCV_FLANN_NNINDEX_H diff --git a/3rdparty/opencv/include/opencv2/flann/object_factory.h b/3rdparty/opencv/include/opencv2/flann/object_factory.h new file mode 100644 index 00000000..7f971c5a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/object_factory.h @@ -0,0 +1,91 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_OBJECT_FACTORY_H_ +#define OPENCV_FLANN_OBJECT_FACTORY_H_ + +#include + +namespace cvflann +{ + +class CreatorNotFound +{ +}; + +template +class ObjectFactory +{ + typedef ObjectFactory ThisClass; + typedef std::map ObjectRegistry; + + // singleton class, private constructor + ObjectFactory() {} + +public: + + bool subscribe(UniqueIdType id, ObjectCreator creator) + { + if (object_registry.find(id) != object_registry.end()) return false; + + object_registry[id] = creator; + return true; + } + + bool unregister(UniqueIdType id) + { + return object_registry.erase(id) == 1; + } + + ObjectCreator create(UniqueIdType id) + { + typename ObjectRegistry::const_iterator iter = object_registry.find(id); + + if (iter == object_registry.end()) { + throw CreatorNotFound(); + } + + return iter->second; + } + + static ThisClass& instance() + { + static ThisClass the_factory; + return the_factory; + } +private: + ObjectRegistry object_registry; +}; + +} + +#endif /* OPENCV_FLANN_OBJECT_FACTORY_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/params.h b/3rdparty/opencv/include/opencv2/flann/params.h new file mode 100644 index 00000000..95ef4cd2 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/params.h @@ -0,0 +1,99 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2011 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2011 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_PARAMS_H_ +#define OPENCV_FLANN_PARAMS_H_ + +#include "any.h" +#include "general.h" +#include +#include + + +namespace cvflann +{ + +typedef std::map IndexParams; + +struct SearchParams : public IndexParams +{ + SearchParams(int checks = 32, float eps = 0, bool sorted = true ) + { + // how many leafs to visit when searching for neighbours (-1 for unlimited) + (*this)["checks"] = checks; + // search for eps-approximate neighbours (default: 0) + (*this)["eps"] = eps; + // only for radius search, require neighbours sorted by distance (default: true) + (*this)["sorted"] = sorted; + } +}; + + +template +T get_param(const IndexParams& params, cv::String name, const T& default_value) +{ + IndexParams::const_iterator it = params.find(name); + if (it != params.end()) { + return it->second.cast(); + } + else { + return default_value; + } +} + +template +T get_param(const IndexParams& params, cv::String name) +{ + IndexParams::const_iterator it = params.find(name); + if (it != params.end()) { + return it->second.cast(); + } + else { + throw FLANNException(cv::String("Missing parameter '")+name+cv::String("' in the parameters given")); + } +} + +inline void print_params(const IndexParams& params, std::ostream& stream) +{ + IndexParams::const_iterator it; + + for(it=params.begin(); it!=params.end(); ++it) { + stream << it->first << " : " << it->second << std::endl; + } +} + +inline void print_params(const IndexParams& params) +{ + print_params(params, std::cout); +} + +} + + +#endif /* OPENCV_FLANN_PARAMS_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/random.h b/3rdparty/opencv/include/opencv2/flann/random.h new file mode 100644 index 00000000..d6784747 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/random.h @@ -0,0 +1,155 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_RANDOM_H +#define OPENCV_FLANN_RANDOM_H + +#include +#include +#include + +#include "general.h" + +namespace cvflann +{ + +inline int rand() +{ +#ifndef OPENCV_FLANN_USE_STD_RAND +# if INT_MAX == RAND_MAX + int v = cv::theRNG().next() & INT_MAX; +# else + int v = cv::theRNG().uniform(0, RAND_MAX + 1); +# endif +#else + int v = std::rand(); +#endif // OPENCV_FLANN_USE_STD_RAND + return v; +} + +/** + * Seeds the random number generator + * @param seed Random seed + */ +inline void seed_random(unsigned int seed) +{ +#ifndef OPENCV_FLANN_USE_STD_RAND + cv::theRNG() = cv::RNG(seed); +#else + std::srand(seed); +#endif +} + +/* + * Generates a random double value. + */ +/** + * Generates a random double value. + * @param high Upper limit + * @param low Lower limit + * @return Random double value + */ +inline double rand_double(double high = 1.0, double low = 0) +{ + return low + ((high-low) * (rand() / (RAND_MAX + 1.0))); +} + +/** + * Generates a random integer value. + * @param high Upper limit + * @param low Lower limit + * @return Random integer value + */ +inline int rand_int(int high = RAND_MAX, int low = 0) +{ + return low + (int) ( double(high-low) * (rand() / (RAND_MAX + 1.0))); +} + +/** + * Random number generator that returns a distinct number from + * the [0,n) interval each time. + */ +class UniqueRandom +{ + std::vector vals_; + int size_; + int counter_; + +public: + /** + * Constructor. + * @param n Size of the interval from which to generate + * @return + */ + UniqueRandom(int n) + { + init(n); + } + + /** + * Initializes the number generator. + * @param n the size of the interval from which to generate random numbers. + */ + void init(int n) + { + // create and initialize an array of size n + vals_.resize(n); + size_ = n; + for (int i = 0; i < size_; ++i) vals_[i] = i; + + // shuffle the elements in the array +#ifndef OPENCV_FLANN_USE_STD_RAND + cv::randShuffle(vals_); +#else + std::random_shuffle(vals_.begin(), vals_.end()); +#endif + + counter_ = 0; + } + + /** + * Return a distinct random integer in greater or equal to 0 and less + * than 'n' on each call. It should be called maximum 'n' times. + * Returns: a random integer + */ + int next() + { + if (counter_ == size_) { + return -1; + } + else { + return vals_[counter_++]; + } + } +}; + +} + +#endif //OPENCV_FLANN_RANDOM_H diff --git a/3rdparty/opencv/include/opencv2/flann/result_set.h b/3rdparty/opencv/include/opencv2/flann/result_set.h new file mode 100644 index 00000000..5c69ac29 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/result_set.h @@ -0,0 +1,543 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_RESULTSET_H +#define OPENCV_FLANN_RESULTSET_H + +#include +#include +#include +#include +#include +#include + +namespace cvflann +{ + +/* This record represents a branch point when finding neighbors in + the tree. It contains a record of the minimum distance to the query + point, as well as the node at which the search resumes. + */ + +template +struct BranchStruct +{ + T node; /* Tree node at which search resumes */ + DistanceType mindist; /* Minimum distance to query for all nodes below. */ + + BranchStruct() {} + BranchStruct(const T& aNode, DistanceType dist) : node(aNode), mindist(dist) {} + + bool operator<(const BranchStruct& rhs) const + { + return mindist +class ResultSet +{ +public: + virtual ~ResultSet() {} + + virtual bool full() const = 0; + + virtual void addPoint(DistanceType dist, int index) = 0; + + virtual DistanceType worstDist() const = 0; + +}; + +/** + * KNNSimpleResultSet does not ensure that the element it holds are unique. + * Is used in those cases where the nearest neighbour algorithm used does not + * attempt to insert the same element multiple times. + */ +template +class KNNSimpleResultSet : public ResultSet +{ + int* indices; + DistanceType* dists; + int capacity; + int count; + DistanceType worst_distance_; + +public: + KNNSimpleResultSet(int capacity_) : capacity(capacity_), count(0) + { + } + + void init(int* indices_, DistanceType* dists_) + { + indices = indices_; + dists = dists_; + count = 0; + worst_distance_ = (std::numeric_limits::max)(); + dists[capacity-1] = worst_distance_; + } + + size_t size() const + { + return count; + } + + bool full() const CV_OVERRIDE + { + return count == capacity; + } + + + void addPoint(DistanceType dist, int index) CV_OVERRIDE + { + if (dist >= worst_distance_) return; + int i; + for (i=count; i>0; --i) { +#ifdef FLANN_FIRST_MATCH + if ( (dists[i-1]>dist) || ((dist==dists[i-1])&&(indices[i-1]>index)) ) +#else + if (dists[i-1]>dist) +#endif + { + if (i +class KNNResultSet : public ResultSet +{ + int* indices; + DistanceType* dists; + int capacity; + int count; + DistanceType worst_distance_; + +public: + KNNResultSet(int capacity_) : capacity(capacity_), count(0) + { + } + + void init(int* indices_, DistanceType* dists_) + { + indices = indices_; + dists = dists_; + count = 0; + worst_distance_ = (std::numeric_limits::max)(); + dists[capacity-1] = worst_distance_; + } + + size_t size() const + { + return count; + } + + bool full() const CV_OVERRIDE + { + return count == capacity; + } + + + void addPoint(DistanceType dist, int index) CV_OVERRIDE + { + if (dist >= worst_distance_) return; + int i; + for (i = count; i > 0; --i) { +#ifdef FLANN_FIRST_MATCH + if ( (dists[i-1]<=dist) && ((dist!=dists[i-1])||(indices[i-1]<=index)) ) +#else + if (dists[i-1]<=dist) +#endif + { + // Check for duplicate indices + int j = i - 1; + while ((j >= 0) && (dists[j] == dist)) { + if (indices[j] == index) { + return; + } + --j; + } + break; + } + } + + if (count < capacity) ++count; + for (int j = count-1; j > i; --j) { + dists[j] = dists[j-1]; + indices[j] = indices[j-1]; + } + dists[i] = dist; + indices[i] = index; + worst_distance_ = dists[capacity-1]; + } + + DistanceType worstDist() const CV_OVERRIDE + { + return worst_distance_; + } +}; + + +/** + * A result-set class used when performing a radius based search. + */ +template +class RadiusResultSet : public ResultSet +{ + DistanceType radius; + int* indices; + DistanceType* dists; + size_t capacity; + size_t count; + +public: + RadiusResultSet(DistanceType radius_, int* indices_, DistanceType* dists_, int capacity_) : + radius(radius_), indices(indices_), dists(dists_), capacity(capacity_) + { + init(); + } + + ~RadiusResultSet() + { + } + + void init() + { + count = 0; + } + + size_t size() const + { + return count; + } + + bool full() const + { + return true; + } + + void addPoint(DistanceType dist, int index) + { + if (dist0)&&(count < capacity)) { + dists[count] = dist; + indices[count] = index; + } + count++; + } + } + + DistanceType worstDist() const + { + return radius; + } + +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** Class that holds the k NN neighbors + * Faster than KNNResultSet as it uses a binary heap and does not maintain two arrays + */ +template +class UniqueResultSet : public ResultSet +{ +public: + struct DistIndex + { + DistIndex(DistanceType dist, unsigned int index) : + dist_(dist), index_(index) + { + } + bool operator<(const DistIndex dist_index) const + { + return (dist_ < dist_index.dist_) || ((dist_ == dist_index.dist_) && index_ < dist_index.index_); + } + DistanceType dist_; + unsigned int index_; + }; + + /** Default cosntructor */ + UniqueResultSet() : + is_full_(false), worst_distance_(std::numeric_limits::max()) + { + } + + /** Check the status of the set + * @return true if we have k NN + */ + inline bool full() const CV_OVERRIDE + { + return is_full_; + } + + /** Remove all elements in the set + */ + virtual void clear() = 0; + + /** Copy the set to two C arrays + * @param indices pointer to a C array of indices + * @param dist pointer to a C array of distances + * @param n_neighbors the number of neighbors to copy + */ + virtual void copy(int* indices, DistanceType* dist, int n_neighbors = -1) const + { + if (n_neighbors < 0) { + for (typename std::set::const_iterator dist_index = dist_indices_.begin(), dist_index_end = + dist_indices_.end(); dist_index != dist_index_end; ++dist_index, ++indices, ++dist) { + *indices = dist_index->index_; + *dist = dist_index->dist_; + } + } + else { + int i = 0; + for (typename std::set::const_iterator dist_index = dist_indices_.begin(), dist_index_end = + dist_indices_.end(); (dist_index != dist_index_end) && (i < n_neighbors); ++dist_index, ++indices, ++dist, ++i) { + *indices = dist_index->index_; + *dist = dist_index->dist_; + } + } + } + + /** Copy the set to two C arrays but sort it according to the distance first + * @param indices pointer to a C array of indices + * @param dist pointer to a C array of distances + * @param n_neighbors the number of neighbors to copy + */ + virtual void sortAndCopy(int* indices, DistanceType* dist, int n_neighbors = -1) const + { + copy(indices, dist, n_neighbors); + } + + /** The number of neighbors in the set + * @return + */ + size_t size() const + { + return dist_indices_.size(); + } + + /** The distance of the furthest neighbor + * If we don't have enough neighbors, it returns the max possible value + * @return + */ + inline DistanceType worstDist() const CV_OVERRIDE + { + return worst_distance_; + } +protected: + /** Flag to say if the set is full */ + bool is_full_; + + /** The worst distance found so far */ + DistanceType worst_distance_; + + /** The best candidates so far */ + std::set dist_indices_; +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** Class that holds the k NN neighbors + * Faster than KNNResultSet as it uses a binary heap and does not maintain two arrays + */ +template +class KNNUniqueResultSet : public UniqueResultSet +{ +public: + /** Constructor + * @param capacity the number of neighbors to store at max + */ + KNNUniqueResultSet(unsigned int capacity) : capacity_(capacity) + { + this->is_full_ = false; + this->clear(); + } + + /** Add a possible candidate to the best neighbors + * @param dist distance for that neighbor + * @param index index of that neighbor + */ + inline void addPoint(DistanceType dist, int index) CV_OVERRIDE + { + // Don't do anything if we are worse than the worst + if (dist >= worst_distance_) return; + dist_indices_.insert(DistIndex(dist, index)); + + if (is_full_) { + if (dist_indices_.size() > capacity_) { + dist_indices_.erase(*dist_indices_.rbegin()); + worst_distance_ = dist_indices_.rbegin()->dist_; + } + } + else if (dist_indices_.size() == capacity_) { + is_full_ = true; + worst_distance_ = dist_indices_.rbegin()->dist_; + } + } + + /** Remove all elements in the set + */ + void clear() CV_OVERRIDE + { + dist_indices_.clear(); + worst_distance_ = std::numeric_limits::max(); + is_full_ = false; + } + +protected: + typedef typename UniqueResultSet::DistIndex DistIndex; + using UniqueResultSet::is_full_; + using UniqueResultSet::worst_distance_; + using UniqueResultSet::dist_indices_; + + /** The number of neighbors to keep */ + unsigned int capacity_; +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** Class that holds the radius nearest neighbors + * It is more accurate than RadiusResult as it is not limited in the number of neighbors + */ +template +class RadiusUniqueResultSet : public UniqueResultSet +{ +public: + /** Constructor + * @param radius the maximum distance of a neighbor + */ + RadiusUniqueResultSet(DistanceType radius) : + radius_(radius) + { + is_full_ = true; + } + + /** Add a possible candidate to the best neighbors + * @param dist distance for that neighbor + * @param index index of that neighbor + */ + void addPoint(DistanceType dist, int index) CV_OVERRIDE + { + if (dist <= radius_) dist_indices_.insert(DistIndex(dist, index)); + } + + /** Remove all elements in the set + */ + inline void clear() CV_OVERRIDE + { + dist_indices_.clear(); + } + + + /** Check the status of the set + * @return alwys false + */ + inline bool full() const CV_OVERRIDE + { + return true; + } + + /** The distance of the furthest neighbor + * If we don't have enough neighbors, it returns the max possible value + * @return + */ + inline DistanceType worstDist() const CV_OVERRIDE + { + return radius_; + } +private: + typedef typename UniqueResultSet::DistIndex DistIndex; + using UniqueResultSet::dist_indices_; + using UniqueResultSet::is_full_; + + /** The furthest distance a neighbor can be */ + DistanceType radius_; +}; + +//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// + +/** Class that holds the k NN neighbors within a radius distance + */ +template +class KNNRadiusUniqueResultSet : public KNNUniqueResultSet +{ +public: + /** Constructor + * @param capacity the number of neighbors to store at max + * @param radius the maximum distance of a neighbor + */ + KNNRadiusUniqueResultSet(unsigned int capacity, DistanceType radius) + { + this->capacity_ = capacity; + this->radius_ = radius; + this->dist_indices_.reserve(capacity_); + this->clear(); + } + + /** Remove all elements in the set + */ + void clear() + { + dist_indices_.clear(); + worst_distance_ = radius_; + is_full_ = false; + } +private: + using KNNUniqueResultSet::dist_indices_; + using KNNUniqueResultSet::is_full_; + using KNNUniqueResultSet::worst_distance_; + + /** The maximum number of neighbors to consider */ + unsigned int capacity_; + + /** The maximum distance of a neighbor */ + DistanceType radius_; +}; +} + +#endif //OPENCV_FLANN_RESULTSET_H diff --git a/3rdparty/opencv/include/opencv2/flann/sampling.h b/3rdparty/opencv/include/opencv2/flann/sampling.h new file mode 100644 index 00000000..396f177a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/sampling.h @@ -0,0 +1,81 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + + +#ifndef OPENCV_FLANN_SAMPLING_H_ +#define OPENCV_FLANN_SAMPLING_H_ + +#include "matrix.h" +#include "random.h" + +namespace cvflann +{ + +template +Matrix random_sample(Matrix& srcMatrix, long size, bool remove = false) +{ + Matrix newSet(new T[size * srcMatrix.cols], size,srcMatrix.cols); + + T* src,* dest; + for (long i=0; i +Matrix random_sample(const Matrix& srcMatrix, size_t size) +{ + UniqueRandom rand((int)srcMatrix.rows); + Matrix newSet(new T[size * srcMatrix.cols], size,srcMatrix.cols); + + T* src,* dest; + for (size_t i=0; i +#include + +#include "general.h" +#include "nn_index.h" + +#ifdef FLANN_SIGNATURE_ +#undef FLANN_SIGNATURE_ +#endif +#define FLANN_SIGNATURE_ "FLANN_INDEX" + +namespace cvflann +{ + +template +struct Datatype {}; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_INT8; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_INT16; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_INT32; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_UINT8; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_UINT16; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_UINT32; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_FLOAT32; } }; +template<> +struct Datatype { static flann_datatype_t type() { return FLANN_FLOAT64; } }; + + +/** + * Structure representing the index header. + */ +struct IndexHeader +{ + char signature[16]; + char version[16]; + flann_datatype_t data_type; + flann_algorithm_t index_type; + size_t rows; + size_t cols; +}; + +/** + * Saves index header to stream + * + * @param stream - Stream to save to + * @param index - The index to save + */ +template +void save_header(FILE* stream, const NNIndex& index) +{ + IndexHeader header; + memset(header.signature, 0, sizeof(header.signature)); + strcpy(header.signature, FLANN_SIGNATURE_); + memset(header.version, 0, sizeof(header.version)); + strcpy(header.version, FLANN_VERSION_); + header.data_type = Datatype::type(); + header.index_type = index.getType(); + header.rows = index.size(); + header.cols = index.veclen(); + + std::fwrite(&header, sizeof(header),1,stream); +} + + +/** + * + * @param stream - Stream to load from + * @return Index header + */ +inline IndexHeader load_header(FILE* stream) +{ + IndexHeader header; + size_t read_size = fread(&header,sizeof(header),1,stream); + + if (read_size!=(size_t)1) { + throw FLANNException("Invalid index file, cannot read"); + } + + if (strcmp(header.signature,FLANN_SIGNATURE_)!=0) { + throw FLANNException("Invalid index file, wrong signature"); + } + + return header; + +} + + +template +void save_value(FILE* stream, const T& value, size_t count = 1) +{ + fwrite(&value, sizeof(value),count, stream); +} + +template +void save_value(FILE* stream, const cvflann::Matrix& value) +{ + fwrite(&value, sizeof(value),1, stream); + fwrite(value.data, sizeof(T),value.rows*value.cols, stream); +} + +template +void save_value(FILE* stream, const std::vector& value) +{ + size_t size = value.size(); + fwrite(&size, sizeof(size_t), 1, stream); + fwrite(&value[0], sizeof(T), size, stream); +} + +template +void load_value(FILE* stream, T& value, size_t count = 1) +{ + size_t read_cnt = fread(&value, sizeof(value), count, stream); + if (read_cnt != count) { + throw FLANNException("Cannot read from file"); + } +} + +template +void load_value(FILE* stream, cvflann::Matrix& value) +{ + size_t read_cnt = fread(&value, sizeof(value), 1, stream); + if (read_cnt != 1) { + throw FLANNException("Cannot read from file"); + } + value.data = new T[value.rows*value.cols]; + read_cnt = fread(value.data, sizeof(T), value.rows*value.cols, stream); + if (read_cnt != (size_t)(value.rows*value.cols)) { + throw FLANNException("Cannot read from file"); + } +} + + +template +void load_value(FILE* stream, std::vector& value) +{ + size_t size; + size_t read_cnt = fread(&size, sizeof(size_t), 1, stream); + if (read_cnt!=1) { + throw FLANNException("Cannot read from file"); + } + value.resize(size); + read_cnt = fread(&value[0], sizeof(T), size, stream); + if (read_cnt != size) { + throw FLANNException("Cannot read from file"); + } +} + +} + +#endif /* OPENCV_FLANN_SAVING_H_ */ diff --git a/3rdparty/opencv/include/opencv2/flann/simplex_downhill.h b/3rdparty/opencv/include/opencv2/flann/simplex_downhill.h new file mode 100644 index 00000000..145901ab --- /dev/null +++ b/3rdparty/opencv/include/opencv2/flann/simplex_downhill.h @@ -0,0 +1,186 @@ +/*********************************************************************** + * Software License Agreement (BSD License) + * + * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. + * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. + * + * THE BSD LICENSE + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR + * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES + * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. + * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT + * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF + * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + *************************************************************************/ + +#ifndef OPENCV_FLANN_SIMPLEX_DOWNHILL_H_ +#define OPENCV_FLANN_SIMPLEX_DOWNHILL_H_ + +namespace cvflann +{ + +/** + Adds val to array vals (and point to array points) and keeping the arrays sorted by vals. + */ +template +void addValue(int pos, float val, float* vals, T* point, T* points, int n) +{ + vals[pos] = val; + for (int i=0; i0 && vals[j] +float optimizeSimplexDownhill(T* points, int n, F func, float* vals = NULL ) +{ + const int MAX_ITERATIONS = 10; + + assert(n>0); + + T* p_o = new T[n]; + T* p_r = new T[n]; + T* p_e = new T[n]; + + int alpha = 1; + + int iterations = 0; + + bool ownVals = false; + if (vals == NULL) { + ownVals = true; + vals = new float[n+1]; + for (int i=0; i MAX_ITERATIONS) break; + + // compute average of simplex points (except the highest point) + for (int j=0; j=vals[0])&&(val_r=vals[n]) { + for (int i=0; i +#include "opencv2/core.hpp" +#include "opencv2/core/utility.hpp" + +namespace cvflann +{ + +/** + * A start-stop timer class. + * + * Can be used to time portions of code. + */ +class StartStopTimer +{ + int64 startTime; + +public: + /** + * Value of the timer. + */ + double value; + + + /** + * Constructor. + */ + StartStopTimer() + { + reset(); + } + + /** + * Starts the timer. + */ + void start() + { + startTime = cv::getTickCount(); + } + + /** + * Stops the timer and updates timer value. + */ + void stop() + { + int64 stopTime = cv::getTickCount(); + value += ( (double)stopTime - startTime) / cv::getTickFrequency(); + } + + /** + * Resets the timer value to 0. + */ + void reset() + { + value = 0; + } + +}; + +} + +#endif // FLANN_TIMER_H diff --git a/3rdparty/opencv/include/opencv2/highgui.hpp b/3rdparty/opencv/include/opencv2/highgui.hpp new file mode 100644 index 00000000..994a1d1e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/highgui.hpp @@ -0,0 +1,845 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HIGHGUI_HPP +#define OPENCV_HIGHGUI_HPP + +#include "opencv2/core.hpp" +#ifdef HAVE_OPENCV_IMGCODECS +#include "opencv2/imgcodecs.hpp" +#endif +#ifdef HAVE_OPENCV_VIDEOIO +#include "opencv2/videoio.hpp" +#endif + +/** +@defgroup highgui High-level GUI + +While OpenCV was designed for use in full-scale applications and can be used within functionally +rich UI frameworks (such as Qt\*, WinForms\*, or Cocoa\*) or without any UI at all, sometimes there +it is required to try functionality quickly and visualize the results. This is what the HighGUI +module has been designed for. + +It provides easy interface to: + +- Create and manipulate windows that can display images and "remember" their content (no need to + handle repaint events from OS). +- Add trackbars to the windows, handle simple mouse events as well as keyboard commands. + +@{ + @defgroup highgui_opengl OpenGL support + @defgroup highgui_qt Qt New Functions + + ![image](pics/qtgui.png) + + This figure explains new functionality implemented with Qt\* GUI. The new GUI provides a statusbar, + a toolbar, and a control panel. The control panel can have trackbars and buttonbars attached to it. + If you cannot see the control panel, press Ctrl+P or right-click any Qt window and select **Display + properties window**. + + - To attach a trackbar, the window name parameter must be NULL. + + - To attach a buttonbar, a button must be created. If the last bar attached to the control panel + is a buttonbar, the new button is added to the right of the last button. If the last bar + attached to the control panel is a trackbar, or the control panel is empty, a new buttonbar is + created. Then, a new button is attached to it. + + See below the example used to generate the figure: + @code + int main(int argc, char *argv[]) + { + + int value = 50; + int value2 = 0; + + + namedWindow("main1",WINDOW_NORMAL); + namedWindow("main2",WINDOW_AUTOSIZE | CV_GUI_NORMAL); + createTrackbar( "track1", "main1", &value, 255, NULL); + + String nameb1 = "button1"; + String nameb2 = "button2"; + + createButton(nameb1,callbackButton,&nameb1,QT_CHECKBOX,1); + createButton(nameb2,callbackButton,NULL,QT_CHECKBOX,0); + createTrackbar( "track2", NULL, &value2, 255, NULL); + createButton("button5",callbackButton1,NULL,QT_RADIOBOX,0); + createButton("button6",callbackButton2,NULL,QT_RADIOBOX,1); + + setMouseCallback( "main2",on_mouse,NULL ); + + Mat img1 = imread("files/flower.jpg"); + VideoCapture video; + video.open("files/hockey.avi"); + + Mat img2,img3; + + while( waitKey(33) != 27 ) + { + img1.convertTo(img2,-1,1,value); + video >> img3; + + imshow("main1",img2); + imshow("main2",img3); + } + + destroyAllWindows(); + + return 0; + } + @endcode + + + @defgroup highgui_winrt WinRT support + + This figure explains new functionality implemented with WinRT GUI. The new GUI provides an Image control, + and a slider panel. Slider panel holds trackbars attached to it. + + Sliders are attached below the image control. Every new slider is added below the previous one. + + See below the example used to generate the figure: + @code + void sample_app::MainPage::ShowWindow() + { + static cv::String windowName("sample"); + cv::winrt_initContainer(this->cvContainer); + cv::namedWindow(windowName); // not required + + cv::Mat image = cv::imread("Assets/sample.jpg"); + cv::Mat converted = cv::Mat(image.rows, image.cols, CV_8UC4); + cv::cvtColor(image, converted, COLOR_BGR2BGRA); + cv::imshow(windowName, converted); // this will create window if it hasn't been created before + + int state = 42; + cv::TrackbarCallback callback = [](int pos, void* userdata) + { + if (pos == 0) { + cv::destroyWindow(windowName); + } + }; + cv::TrackbarCallback callbackTwin = [](int pos, void* userdata) + { + if (pos >= 70) { + cv::destroyAllWindows(); + } + }; + cv::createTrackbar("Sample trackbar", windowName, &state, 100, callback); + cv::createTrackbar("Twin brother", windowName, &state, 100, callbackTwin); + } + @endcode + + @defgroup highgui_c C API +@} +*/ + +///////////////////////// graphical user interface ////////////////////////// +namespace cv +{ + +//! @addtogroup highgui +//! @{ + +//! Flags for cv::namedWindow +enum WindowFlags { + WINDOW_NORMAL = 0x00000000, //!< the user can resize the window (no constraint) / also use to switch a fullscreen window to a normal size. + WINDOW_AUTOSIZE = 0x00000001, //!< the user cannot resize the window, the size is constrainted by the image displayed. + WINDOW_OPENGL = 0x00001000, //!< window with opengl support. + + WINDOW_FULLSCREEN = 1, //!< change the window to fullscreen. + WINDOW_FREERATIO = 0x00000100, //!< the image expends as much as it can (no ratio constraint). + WINDOW_KEEPRATIO = 0x00000000, //!< the ratio of the image is respected. + WINDOW_GUI_EXPANDED=0x00000000, //!< status bar and tool bar + WINDOW_GUI_NORMAL = 0x00000010, //!< old fashious way + }; + +//! Flags for cv::setWindowProperty / cv::getWindowProperty +enum WindowPropertyFlags { + WND_PROP_FULLSCREEN = 0, //!< fullscreen property (can be WINDOW_NORMAL or WINDOW_FULLSCREEN). + WND_PROP_AUTOSIZE = 1, //!< autosize property (can be WINDOW_NORMAL or WINDOW_AUTOSIZE). + WND_PROP_ASPECT_RATIO = 2, //!< window's aspect ration (can be set to WINDOW_FREERATIO or WINDOW_KEEPRATIO). + WND_PROP_OPENGL = 3, //!< opengl support. + WND_PROP_VISIBLE = 4 //!< checks whether the window exists and is visible + }; + +//! Mouse Events see cv::MouseCallback +enum MouseEventTypes { + EVENT_MOUSEMOVE = 0, //!< indicates that the mouse pointer has moved over the window. + EVENT_LBUTTONDOWN = 1, //!< indicates that the left mouse button is pressed. + EVENT_RBUTTONDOWN = 2, //!< indicates that the right mouse button is pressed. + EVENT_MBUTTONDOWN = 3, //!< indicates that the middle mouse button is pressed. + EVENT_LBUTTONUP = 4, //!< indicates that left mouse button is released. + EVENT_RBUTTONUP = 5, //!< indicates that right mouse button is released. + EVENT_MBUTTONUP = 6, //!< indicates that middle mouse button is released. + EVENT_LBUTTONDBLCLK = 7, //!< indicates that left mouse button is double clicked. + EVENT_RBUTTONDBLCLK = 8, //!< indicates that right mouse button is double clicked. + EVENT_MBUTTONDBLCLK = 9, //!< indicates that middle mouse button is double clicked. + EVENT_MOUSEWHEEL = 10,//!< positive and negative values mean forward and backward scrolling, respectively. + EVENT_MOUSEHWHEEL = 11 //!< positive and negative values mean right and left scrolling, respectively. + }; + +//! Mouse Event Flags see cv::MouseCallback +enum MouseEventFlags { + EVENT_FLAG_LBUTTON = 1, //!< indicates that the left mouse button is down. + EVENT_FLAG_RBUTTON = 2, //!< indicates that the right mouse button is down. + EVENT_FLAG_MBUTTON = 4, //!< indicates that the middle mouse button is down. + EVENT_FLAG_CTRLKEY = 8, //!< indicates that CTRL Key is pressed. + EVENT_FLAG_SHIFTKEY = 16,//!< indicates that SHIFT Key is pressed. + EVENT_FLAG_ALTKEY = 32 //!< indicates that ALT Key is pressed. + }; + +//! Qt font weight +enum QtFontWeights { + QT_FONT_LIGHT = 25, //!< Weight of 25 + QT_FONT_NORMAL = 50, //!< Weight of 50 + QT_FONT_DEMIBOLD = 63, //!< Weight of 63 + QT_FONT_BOLD = 75, //!< Weight of 75 + QT_FONT_BLACK = 87 //!< Weight of 87 + }; + +//! Qt font style +enum QtFontStyles { + QT_STYLE_NORMAL = 0, //!< Normal font. + QT_STYLE_ITALIC = 1, //!< Italic font. + QT_STYLE_OBLIQUE = 2 //!< Oblique font. + }; + +//! Qt "button" type +enum QtButtonTypes { + QT_PUSH_BUTTON = 0, //!< Push button. + QT_CHECKBOX = 1, //!< Checkbox button. + QT_RADIOBOX = 2, //!< Radiobox button. + QT_NEW_BUTTONBAR = 1024 //!< Button should create a new buttonbar + }; + +/** @brief Callback function for mouse events. see cv::setMouseCallback +@param event one of the cv::MouseEventTypes constants. +@param x The x-coordinate of the mouse event. +@param y The y-coordinate of the mouse event. +@param flags one of the cv::MouseEventFlags constants. +@param userdata The optional parameter. + */ +typedef void (*MouseCallback)(int event, int x, int y, int flags, void* userdata); + +/** @brief Callback function for Trackbar see cv::createTrackbar +@param pos current position of the specified trackbar. +@param userdata The optional parameter. + */ +typedef void (*TrackbarCallback)(int pos, void* userdata); + +/** @brief Callback function defined to be called every frame. See cv::setOpenGlDrawCallback +@param userdata The optional parameter. + */ +typedef void (*OpenGlDrawCallback)(void* userdata); + +/** @brief Callback function for a button created by cv::createButton +@param state current state of the button. It could be -1 for a push button, 0 or 1 for a check/radio box button. +@param userdata The optional parameter. + */ +typedef void (*ButtonCallback)(int state, void* userdata); + +/** @brief Creates a window. + +The function namedWindow creates a window that can be used as a placeholder for images and +trackbars. Created windows are referred to by their names. + +If a window with the same name already exists, the function does nothing. + +You can call cv::destroyWindow or cv::destroyAllWindows to close the window and de-allocate any associated +memory usage. For a simple program, you do not really have to call these functions because all the +resources and windows of the application are closed automatically by the operating system upon exit. + +@note + +Qt backend supports additional flags: + - **WINDOW_NORMAL or WINDOW_AUTOSIZE:** WINDOW_NORMAL enables you to resize the + window, whereas WINDOW_AUTOSIZE adjusts automatically the window size to fit the + displayed image (see imshow ), and you cannot change the window size manually. + - **WINDOW_FREERATIO or WINDOW_KEEPRATIO:** WINDOW_FREERATIO adjusts the image + with no respect to its ratio, whereas WINDOW_KEEPRATIO keeps the image ratio. + - **WINDOW_GUI_NORMAL or WINDOW_GUI_EXPANDED:** WINDOW_GUI_NORMAL is the old way to draw the window + without statusbar and toolbar, whereas WINDOW_GUI_EXPANDED is a new enhanced GUI. +By default, flags == WINDOW_AUTOSIZE | WINDOW_KEEPRATIO | WINDOW_GUI_EXPANDED + +@param winname Name of the window in the window caption that may be used as a window identifier. +@param flags Flags of the window. The supported flags are: (cv::WindowFlags) + */ +CV_EXPORTS_W void namedWindow(const String& winname, int flags = WINDOW_AUTOSIZE); + +/** @brief Destroys the specified window. + +The function destroyWindow destroys the window with the given name. + +@param winname Name of the window to be destroyed. + */ +CV_EXPORTS_W void destroyWindow(const String& winname); + +/** @brief Destroys all of the HighGUI windows. + +The function destroyAllWindows destroys all of the opened HighGUI windows. + */ +CV_EXPORTS_W void destroyAllWindows(); + +CV_EXPORTS_W int startWindowThread(); + +/** @brief Similar to #waitKey, but returns full key code. + +@note + +Key code is implementation specific and depends on used backend: QT/GTK/Win32/etc + +*/ +CV_EXPORTS_W int waitKeyEx(int delay = 0); + +/** @brief Waits for a pressed key. + +The function waitKey waits for a key event infinitely (when \f$\texttt{delay}\leq 0\f$ ) or for delay +milliseconds, when it is positive. Since the OS has a minimum time between switching threads, the +function will not wait exactly delay ms, it will wait at least delay ms, depending on what else is +running on your computer at that time. It returns the code of the pressed key or -1 if no key was +pressed before the specified time had elapsed. + +@note + +This function is the only method in HighGUI that can fetch and handle events, so it needs to be +called periodically for normal event processing unless HighGUI is used within an environment that +takes care of event processing. + +@note + +The function only works if there is at least one HighGUI window created and the window is active. +If there are several HighGUI windows, any of them can be active. + +@param delay Delay in milliseconds. 0 is the special value that means "forever". + */ +CV_EXPORTS_W int waitKey(int delay = 0); + +/** @brief Displays an image in the specified window. + +The function imshow displays an image in the specified window. If the window was created with the +cv::WINDOW_AUTOSIZE flag, the image is shown with its original size, however it is still limited by the screen resolution. +Otherwise, the image is scaled to fit the window. The function may scale the image, depending on its depth: + +- If the image is 8-bit unsigned, it is displayed as is. +- If the image is 16-bit unsigned or 32-bit integer, the pixels are divided by 256. That is, the + value range [0,255\*256] is mapped to [0,255]. +- If the image is 32-bit or 64-bit floating-point, the pixel values are multiplied by 255. That is, the + value range [0,1] is mapped to [0,255]. + +If window was created with OpenGL support, cv::imshow also support ogl::Buffer , ogl::Texture2D and +cuda::GpuMat as input. + +If the window was not created before this function, it is assumed creating a window with cv::WINDOW_AUTOSIZE. + +If you need to show an image that is bigger than the screen resolution, you will need to call namedWindow("", WINDOW_NORMAL) before the imshow. + +@note This function should be followed by cv::waitKey function which displays the image for specified +milliseconds. Otherwise, it won't display the image. For example, **waitKey(0)** will display the window +infinitely until any keypress (it is suitable for image display). **waitKey(25)** will display a frame +for 25 ms, after which display will be automatically closed. (If you put it in a loop to read +videos, it will display the video frame-by-frame) + +@note + +[__Windows Backend Only__] Pressing Ctrl+C will copy the image to the clipboard. + +[__Windows Backend Only__] Pressing Ctrl+S will show a dialog to save the image. + +@param winname Name of the window. +@param mat Image to be shown. + */ +CV_EXPORTS_W void imshow(const String& winname, InputArray mat); + +/** @brief Resizes window to the specified size + +@note + +- The specified window size is for the image area. Toolbars are not counted. +- Only windows created without cv::WINDOW_AUTOSIZE flag can be resized. + +@param winname Window name. +@param width The new window width. +@param height The new window height. + */ +CV_EXPORTS_W void resizeWindow(const String& winname, int width, int height); + +/** @overload +@param winname Window name. +@param size The new window size. +*/ +CV_EXPORTS_W void resizeWindow(const String& winname, const cv::Size& size); + +/** @brief Moves window to the specified position + +@param winname Name of the window. +@param x The new x-coordinate of the window. +@param y The new y-coordinate of the window. + */ +CV_EXPORTS_W void moveWindow(const String& winname, int x, int y); + +/** @brief Changes parameters of a window dynamically. + +The function setWindowProperty enables changing properties of a window. + +@param winname Name of the window. +@param prop_id Window property to edit. The supported operation flags are: (cv::WindowPropertyFlags) +@param prop_value New value of the window property. The supported flags are: (cv::WindowFlags) + */ +CV_EXPORTS_W void setWindowProperty(const String& winname, int prop_id, double prop_value); + +/** @brief Updates window title +@param winname Name of the window. +@param title New title. +*/ +CV_EXPORTS_W void setWindowTitle(const String& winname, const String& title); + +/** @brief Provides parameters of a window. + +The function getWindowProperty returns properties of a window. + +@param winname Name of the window. +@param prop_id Window property to retrieve. The following operation flags are available: (cv::WindowPropertyFlags) + +@sa setWindowProperty + */ +CV_EXPORTS_W double getWindowProperty(const String& winname, int prop_id); + +/** @brief Provides rectangle of image in the window. + +The function getWindowImageRect returns the client screen coordinates, width and height of the image rendering area. + +@param winname Name of the window. + +@sa resizeWindow moveWindow + */ +CV_EXPORTS_W Rect getWindowImageRect(const String& winname); + +/** @example samples/cpp/create_mask.cpp +This program demonstrates using mouse events and how to make and use a mask image (black and white) . +*/ +/** @brief Sets mouse handler for the specified window + +@param winname Name of the window. +@param onMouse Callback function for mouse events. See OpenCV samples on how to specify and use the callback. +@param userdata The optional parameter passed to the callback. + */ +CV_EXPORTS void setMouseCallback(const String& winname, MouseCallback onMouse, void* userdata = 0); + +/** @brief Gets the mouse-wheel motion delta, when handling mouse-wheel events cv::EVENT_MOUSEWHEEL and +cv::EVENT_MOUSEHWHEEL. + +For regular mice with a scroll-wheel, delta will be a multiple of 120. The value 120 corresponds to +a one notch rotation of the wheel or the threshold for action to be taken and one such action should +occur for each delta. Some high-precision mice with higher-resolution freely-rotating wheels may +generate smaller values. + +For cv::EVENT_MOUSEWHEEL positive and negative values mean forward and backward scrolling, +respectively. For cv::EVENT_MOUSEHWHEEL, where available, positive and negative values mean right and +left scrolling, respectively. + +With the C API, the macro CV_GET_WHEEL_DELTA(flags) can be used alternatively. + +@note + +Mouse-wheel events are currently supported only on Windows. + +@param flags The mouse callback flags parameter. + */ +CV_EXPORTS int getMouseWheelDelta(int flags); + +/** @brief Selects ROI on the given image. +Function creates a window and allows user to select a ROI using mouse. +Controls: use `space` or `enter` to finish selection, use key `c` to cancel selection (function will return the zero cv::Rect). + +@param windowName name of the window where selection process will be shown. +@param img image to select a ROI. +@param showCrosshair if true crosshair of selection rectangle will be shown. +@param fromCenter if true center of selection will match initial mouse position. In opposite case a corner of +selection rectangle will correspont to the initial mouse position. +@return selected ROI or empty rect if selection canceled. + +@note The function sets it's own mouse callback for specified window using cv::setMouseCallback(windowName, ...). +After finish of work an empty callback will be set for the used window. + */ +CV_EXPORTS_W Rect selectROI(const String& windowName, InputArray img, bool showCrosshair = true, bool fromCenter = false); + +/** @overload + */ +CV_EXPORTS_W Rect selectROI(InputArray img, bool showCrosshair = true, bool fromCenter = false); + +/** @brief Selects ROIs on the given image. +Function creates a window and allows user to select a ROIs using mouse. +Controls: use `space` or `enter` to finish current selection and start a new one, +use `esc` to terminate multiple ROI selection process. + +@param windowName name of the window where selection process will be shown. +@param img image to select a ROI. +@param boundingBoxes selected ROIs. +@param showCrosshair if true crosshair of selection rectangle will be shown. +@param fromCenter if true center of selection will match initial mouse position. In opposite case a corner of +selection rectangle will correspont to the initial mouse position. + +@note The function sets it's own mouse callback for specified window using cv::setMouseCallback(windowName, ...). +After finish of work an empty callback will be set for the used window. + */ +CV_EXPORTS_W void selectROIs(const String& windowName, InputArray img, + CV_OUT std::vector& boundingBoxes, bool showCrosshair = true, bool fromCenter = false); + +/** @brief Creates a trackbar and attaches it to the specified window. + +The function createTrackbar creates a trackbar (a slider or range control) with the specified name +and range, assigns a variable value to be a position synchronized with the trackbar and specifies +the callback function onChange to be called on the trackbar position change. The created trackbar is +displayed in the specified window winname. + +@note + +[__Qt Backend Only__] winname can be empty (or NULL) if the trackbar should be attached to the +control panel. + +Clicking the label of each trackbar enables editing the trackbar values manually. + +@param trackbarname Name of the created trackbar. +@param winname Name of the window that will be used as a parent of the created trackbar. +@param value Optional pointer to an integer variable whose value reflects the position of the +slider. Upon creation, the slider position is defined by this variable. +@param count Maximal position of the slider. The minimal position is always 0. +@param onChange Pointer to the function to be called every time the slider changes position. This +function should be prototyped as void Foo(int,void\*); , where the first parameter is the trackbar +position and the second parameter is the user data (see the next parameter). If the callback is +the NULL pointer, no callbacks are called, but only value is updated. +@param userdata User data that is passed as is to the callback. It can be used to handle trackbar +events without using global variables. + */ +CV_EXPORTS int createTrackbar(const String& trackbarname, const String& winname, + int* value, int count, + TrackbarCallback onChange = 0, + void* userdata = 0); + +/** @brief Returns the trackbar position. + +The function returns the current position of the specified trackbar. + +@note + +[__Qt Backend Only__] winname can be empty (or NULL) if the trackbar is attached to the control +panel. + +@param trackbarname Name of the trackbar. +@param winname Name of the window that is the parent of the trackbar. + */ +CV_EXPORTS_W int getTrackbarPos(const String& trackbarname, const String& winname); + +/** @brief Sets the trackbar position. + +The function sets the position of the specified trackbar in the specified window. + +@note + +[__Qt Backend Only__] winname can be empty (or NULL) if the trackbar is attached to the control +panel. + +@param trackbarname Name of the trackbar. +@param winname Name of the window that is the parent of trackbar. +@param pos New position. + */ +CV_EXPORTS_W void setTrackbarPos(const String& trackbarname, const String& winname, int pos); + +/** @brief Sets the trackbar maximum position. + +The function sets the maximum position of the specified trackbar in the specified window. + +@note + +[__Qt Backend Only__] winname can be empty (or NULL) if the trackbar is attached to the control +panel. + +@param trackbarname Name of the trackbar. +@param winname Name of the window that is the parent of trackbar. +@param maxval New maximum position. + */ +CV_EXPORTS_W void setTrackbarMax(const String& trackbarname, const String& winname, int maxval); + +/** @brief Sets the trackbar minimum position. + +The function sets the minimum position of the specified trackbar in the specified window. + +@note + +[__Qt Backend Only__] winname can be empty (or NULL) if the trackbar is attached to the control +panel. + +@param trackbarname Name of the trackbar. +@param winname Name of the window that is the parent of trackbar. +@param minval New minimum position. + */ +CV_EXPORTS_W void setTrackbarMin(const String& trackbarname, const String& winname, int minval); + +//! @addtogroup highgui_opengl OpenGL support +//! @{ + +/** @brief Displays OpenGL 2D texture in the specified window. + +@param winname Name of the window. +@param tex OpenGL 2D texture data. + */ +CV_EXPORTS void imshow(const String& winname, const ogl::Texture2D& tex); + +/** @brief Sets a callback function to be called to draw on top of displayed image. + +The function setOpenGlDrawCallback can be used to draw 3D data on the window. See the example of +callback function below: +@code + void on_opengl(void* param) + { + glLoadIdentity(); + + glTranslated(0.0, 0.0, -1.0); + + glRotatef( 55, 1, 0, 0 ); + glRotatef( 45, 0, 1, 0 ); + glRotatef( 0, 0, 0, 1 ); + + static const int coords[6][4][3] = { + { { +1, -1, -1 }, { -1, -1, -1 }, { -1, +1, -1 }, { +1, +1, -1 } }, + { { +1, +1, -1 }, { -1, +1, -1 }, { -1, +1, +1 }, { +1, +1, +1 } }, + { { +1, -1, +1 }, { +1, -1, -1 }, { +1, +1, -1 }, { +1, +1, +1 } }, + { { -1, -1, -1 }, { -1, -1, +1 }, { -1, +1, +1 }, { -1, +1, -1 } }, + { { +1, -1, +1 }, { -1, -1, +1 }, { -1, -1, -1 }, { +1, -1, -1 } }, + { { -1, -1, +1 }, { +1, -1, +1 }, { +1, +1, +1 }, { -1, +1, +1 } } + }; + + for (int i = 0; i < 6; ++i) { + glColor3ub( i*20, 100+i*10, i*42 ); + glBegin(GL_QUADS); + for (int j = 0; j < 4; ++j) { + glVertex3d(0.2 * coords[i][j][0], 0.2 * coords[i][j][1], 0.2 * coords[i][j][2]); + } + glEnd(); + } + } +@endcode + +@param winname Name of the window. +@param onOpenGlDraw Pointer to the function to be called every frame. This function should be +prototyped as void Foo(void\*) . +@param userdata Pointer passed to the callback function.(__Optional__) + */ +CV_EXPORTS void setOpenGlDrawCallback(const String& winname, OpenGlDrawCallback onOpenGlDraw, void* userdata = 0); + +/** @brief Sets the specified window as current OpenGL context. + +@param winname Name of the window. + */ +CV_EXPORTS void setOpenGlContext(const String& winname); + +/** @brief Force window to redraw its context and call draw callback ( See cv::setOpenGlDrawCallback ). + +@param winname Name of the window. + */ +CV_EXPORTS void updateWindow(const String& winname); + +//! @} highgui_opengl + +//! @addtogroup highgui_qt +//! @{ + +/** @brief QtFont available only for Qt. See cv::fontQt + */ +struct QtFont +{ + const char* nameFont; //!< Name of the font + Scalar color; //!< Color of the font. Scalar(blue_component, green_component, red_component[, alpha_component]) + int font_face; //!< See cv::QtFontStyles + const int* ascii; //!< font data and metrics + const int* greek; + const int* cyrillic; + float hscale, vscale; + float shear; //!< slope coefficient: 0 - normal, >0 - italic + int thickness; //!< See cv::QtFontWeights + float dx; //!< horizontal interval between letters + int line_type; //!< PointSize +}; + +/** @brief Creates the font to draw a text on an image. + +The function fontQt creates a cv::QtFont object. This cv::QtFont is not compatible with putText . + +A basic usage of this function is the following: : +@code + QtFont font = fontQt("Times"); + addText( img1, "Hello World !", Point(50,50), font); +@endcode + +@param nameFont Name of the font. The name should match the name of a system font (such as +*Times*). If the font is not found, a default one is used. +@param pointSize Size of the font. If not specified, equal zero or negative, the point size of the +font is set to a system-dependent default value. Generally, this is 12 points. +@param color Color of the font in BGRA where A = 255 is fully transparent. Use the macro CV_RGB +for simplicity. +@param weight Font weight. Available operation flags are : cv::QtFontWeights You can also specify a positive integer for better control. +@param style Font style. Available operation flags are : cv::QtFontStyles +@param spacing Spacing between characters. It can be negative or positive. + */ +CV_EXPORTS QtFont fontQt(const String& nameFont, int pointSize = -1, + Scalar color = Scalar::all(0), int weight = QT_FONT_NORMAL, + int style = QT_STYLE_NORMAL, int spacing = 0); + +/** @brief Draws a text on the image. + +The function addText draws *text* on the image *img* using a specific font *font* (see example cv::fontQt +) + +@param img 8-bit 3-channel image where the text should be drawn. +@param text Text to write on an image. +@param org Point(x,y) where the text should start on an image. +@param font Font to use to draw a text. + */ +CV_EXPORTS void addText( const Mat& img, const String& text, Point org, const QtFont& font); + +/** @brief Draws a text on the image. + +@param img 8-bit 3-channel image where the text should be drawn. +@param text Text to write on an image. +@param org Point(x,y) where the text should start on an image. +@param nameFont Name of the font. The name should match the name of a system font (such as +*Times*). If the font is not found, a default one is used. +@param pointSize Size of the font. If not specified, equal zero or negative, the point size of the +font is set to a system-dependent default value. Generally, this is 12 points. +@param color Color of the font in BGRA where A = 255 is fully transparent. +@param weight Font weight. Available operation flags are : cv::QtFontWeights You can also specify a positive integer for better control. +@param style Font style. Available operation flags are : cv::QtFontStyles +@param spacing Spacing between characters. It can be negative or positive. + */ +CV_EXPORTS_W void addText(const Mat& img, const String& text, Point org, const String& nameFont, int pointSize = -1, Scalar color = Scalar::all(0), + int weight = QT_FONT_NORMAL, int style = QT_STYLE_NORMAL, int spacing = 0); + +/** @brief Displays a text on a window image as an overlay for a specified duration. + +The function displayOverlay displays useful information/tips on top of the window for a certain +amount of time *delayms*. The function does not modify the image, displayed in the window, that is, +after the specified delay the original content of the window is restored. + +@param winname Name of the window. +@param text Overlay text to write on a window image. +@param delayms The period (in milliseconds), during which the overlay text is displayed. If this +function is called before the previous overlay text timed out, the timer is restarted and the text +is updated. If this value is zero, the text never disappears. + */ +CV_EXPORTS_W void displayOverlay(const String& winname, const String& text, int delayms = 0); + +/** @brief Displays a text on the window statusbar during the specified period of time. + +The function displayStatusBar displays useful information/tips on top of the window for a certain +amount of time *delayms* . This information is displayed on the window statusbar (the window must be +created with the CV_GUI_EXPANDED flags). + +@param winname Name of the window. +@param text Text to write on the window statusbar. +@param delayms Duration (in milliseconds) to display the text. If this function is called before +the previous text timed out, the timer is restarted and the text is updated. If this value is +zero, the text never disappears. + */ +CV_EXPORTS_W void displayStatusBar(const String& winname, const String& text, int delayms = 0); + +/** @brief Saves parameters of the specified window. + +The function saveWindowParameters saves size, location, flags, trackbars value, zoom and panning +location of the window windowName. + +@param windowName Name of the window. + */ +CV_EXPORTS void saveWindowParameters(const String& windowName); + +/** @brief Loads parameters of the specified window. + +The function loadWindowParameters loads size, location, flags, trackbars value, zoom and panning +location of the window windowName. + +@param windowName Name of the window. + */ +CV_EXPORTS void loadWindowParameters(const String& windowName); + +CV_EXPORTS int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]); + +CV_EXPORTS void stopLoop(); + +/** @brief Attaches a button to the control panel. + +The function createButton attaches a button to the control panel. Each button is added to a +buttonbar to the right of the last button. A new buttonbar is created if nothing was attached to the +control panel before, or if the last element attached to the control panel was a trackbar or if the +QT_NEW_BUTTONBAR flag is added to the type. + +See below various examples of the cv::createButton function call: : +@code + createButton(NULL,callbackButton);//create a push button "button 0", that will call callbackButton. + createButton("button2",callbackButton,NULL,QT_CHECKBOX,0); + createButton("button3",callbackButton,&value); + createButton("button5",callbackButton1,NULL,QT_RADIOBOX); + createButton("button6",callbackButton2,NULL,QT_PUSH_BUTTON,1); + createButton("button6",callbackButton2,NULL,QT_PUSH_BUTTON|QT_NEW_BUTTONBAR);// create a push button in a new row +@endcode + +@param bar_name Name of the button. +@param on_change Pointer to the function to be called every time the button changes its state. +This function should be prototyped as void Foo(int state,\*void); . *state* is the current state +of the button. It could be -1 for a push button, 0 or 1 for a check/radio box button. +@param userdata Pointer passed to the callback function. +@param type Optional type of the button. Available types are: (cv::QtButtonTypes) +@param initial_button_state Default state of the button. Use for checkbox and radiobox. Its +value could be 0 or 1. (__Optional__) +*/ +CV_EXPORTS int createButton( const String& bar_name, ButtonCallback on_change, + void* userdata = 0, int type = QT_PUSH_BUTTON, + bool initial_button_state = false); + +//! @} highgui_qt + +//! @} highgui + +} // cv + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/highgui/highgui_c.h" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/highgui/highgui.hpp b/3rdparty/opencv/include/opencv2/highgui/highgui.hpp new file mode 100644 index 00000000..160c9cf4 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/highgui/highgui.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/highgui.hpp" diff --git a/3rdparty/opencv/include/opencv2/highgui/highgui_c.h b/3rdparty/opencv/include/opencv2/highgui/highgui_c.h new file mode 100644 index 00000000..35413139 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/highgui/highgui_c.h @@ -0,0 +1,262 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HIGHGUI_H +#define OPENCV_HIGHGUI_H + +#include "opencv2/core/core_c.h" +#include "opencv2/imgproc/imgproc_c.h" +#ifdef HAVE_OPENCV_IMGCODECS +#include "opencv2/imgcodecs/imgcodecs_c.h" +#endif +#ifdef HAVE_OPENCV_VIDEOIO +#include "opencv2/videoio/videoio_c.h" +#endif + +#ifdef __cplusplus +extern "C" { +#endif /* __cplusplus */ + +/** @addtogroup highgui_c + @{ + */ + +/****************************************************************************************\ +* Basic GUI functions * +\****************************************************************************************/ +//YV +//-----------New for Qt +/* For font */ +enum { CV_FONT_LIGHT = 25,//QFont::Light, + CV_FONT_NORMAL = 50,//QFont::Normal, + CV_FONT_DEMIBOLD = 63,//QFont::DemiBold, + CV_FONT_BOLD = 75,//QFont::Bold, + CV_FONT_BLACK = 87 //QFont::Black +}; + +enum { CV_STYLE_NORMAL = 0,//QFont::StyleNormal, + CV_STYLE_ITALIC = 1,//QFont::StyleItalic, + CV_STYLE_OBLIQUE = 2 //QFont::StyleOblique +}; +/* ---------*/ + +//for color cvScalar(blue_component, green_component, red_component[, alpha_component]) +//and alpha= 0 <-> 0xFF (not transparent <-> transparent) +CVAPI(CvFont) cvFontQt(const char* nameFont, int pointSize CV_DEFAULT(-1), CvScalar color CV_DEFAULT(cvScalarAll(0)), int weight CV_DEFAULT(CV_FONT_NORMAL), int style CV_DEFAULT(CV_STYLE_NORMAL), int spacing CV_DEFAULT(0)); + +CVAPI(void) cvAddText(const CvArr* img, const char* text, CvPoint org, CvFont *arg2); + +CVAPI(void) cvDisplayOverlay(const char* name, const char* text, int delayms CV_DEFAULT(0)); +CVAPI(void) cvDisplayStatusBar(const char* name, const char* text, int delayms CV_DEFAULT(0)); + +CVAPI(void) cvSaveWindowParameters(const char* name); +CVAPI(void) cvLoadWindowParameters(const char* name); +CVAPI(int) cvStartLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]); +CVAPI(void) cvStopLoop( void ); + +typedef void (CV_CDECL *CvButtonCallback)(int state, void* userdata); +enum {CV_PUSH_BUTTON = 0, CV_CHECKBOX = 1, CV_RADIOBOX = 2}; +CVAPI(int) cvCreateButton( const char* button_name CV_DEFAULT(NULL),CvButtonCallback on_change CV_DEFAULT(NULL), void* userdata CV_DEFAULT(NULL) , int button_type CV_DEFAULT(CV_PUSH_BUTTON), int initial_button_state CV_DEFAULT(0)); +//---------------------- + + +/* this function is used to set some external parameters in case of X Window */ +CVAPI(int) cvInitSystem( int argc, char** argv ); + +CVAPI(int) cvStartWindowThread( void ); + +// --------- YV --------- +enum +{ + //These 3 flags are used by cvSet/GetWindowProperty + CV_WND_PROP_FULLSCREEN = 0, //to change/get window's fullscreen property + CV_WND_PROP_AUTOSIZE = 1, //to change/get window's autosize property + CV_WND_PROP_ASPECTRATIO= 2, //to change/get window's aspectratio property + CV_WND_PROP_OPENGL = 3, //to change/get window's opengl support + CV_WND_PROP_VISIBLE = 4, + + //These 2 flags are used by cvNamedWindow and cvSet/GetWindowProperty + CV_WINDOW_NORMAL = 0x00000000, //the user can resize the window (no constraint) / also use to switch a fullscreen window to a normal size + CV_WINDOW_AUTOSIZE = 0x00000001, //the user cannot resize the window, the size is constrainted by the image displayed + CV_WINDOW_OPENGL = 0x00001000, //window with opengl support + + //Those flags are only for Qt + CV_GUI_EXPANDED = 0x00000000, //status bar and tool bar + CV_GUI_NORMAL = 0x00000010, //old fashious way + + //These 3 flags are used by cvNamedWindow and cvSet/GetWindowProperty + CV_WINDOW_FULLSCREEN = 1,//change the window to fullscreen + CV_WINDOW_FREERATIO = 0x00000100,//the image expends as much as it can (no ratio constraint) + CV_WINDOW_KEEPRATIO = 0x00000000//the ration image is respected. +}; + +/* create window */ +CVAPI(int) cvNamedWindow( const char* name, int flags CV_DEFAULT(CV_WINDOW_AUTOSIZE) ); + +/* Set and Get Property of the window */ +CVAPI(void) cvSetWindowProperty(const char* name, int prop_id, double prop_value); +CVAPI(double) cvGetWindowProperty(const char* name, int prop_id); + +#ifdef __cplusplus // FIXIT remove in OpenCV 4.0 +/* Get window image rectangle coordinates, width and height */ +CVAPI(cv::Rect)cvGetWindowImageRect(const char* name); +#endif + +/* display image within window (highgui windows remember their content) */ +CVAPI(void) cvShowImage( const char* name, const CvArr* image ); + +/* resize/move window */ +CVAPI(void) cvResizeWindow( const char* name, int width, int height ); +CVAPI(void) cvMoveWindow( const char* name, int x, int y ); + + +/* destroy window and all the trackers associated with it */ +CVAPI(void) cvDestroyWindow( const char* name ); + +CVAPI(void) cvDestroyAllWindows(void); + +/* get native window handle (HWND in case of Win32 and Widget in case of X Window) */ +CVAPI(void*) cvGetWindowHandle( const char* name ); + +/* get name of highgui window given its native handle */ +CVAPI(const char*) cvGetWindowName( void* window_handle ); + + +typedef void (CV_CDECL *CvTrackbarCallback)(int pos); + +/* create trackbar and display it on top of given window, set callback */ +CVAPI(int) cvCreateTrackbar( const char* trackbar_name, const char* window_name, + int* value, int count, CvTrackbarCallback on_change CV_DEFAULT(NULL)); + +typedef void (CV_CDECL *CvTrackbarCallback2)(int pos, void* userdata); + +CVAPI(int) cvCreateTrackbar2( const char* trackbar_name, const char* window_name, + int* value, int count, CvTrackbarCallback2 on_change, + void* userdata CV_DEFAULT(0)); + +/* retrieve or set trackbar position */ +CVAPI(int) cvGetTrackbarPos( const char* trackbar_name, const char* window_name ); +CVAPI(void) cvSetTrackbarPos( const char* trackbar_name, const char* window_name, int pos ); +CVAPI(void) cvSetTrackbarMax(const char* trackbar_name, const char* window_name, int maxval); +CVAPI(void) cvSetTrackbarMin(const char* trackbar_name, const char* window_name, int minval); + +enum +{ + CV_EVENT_MOUSEMOVE =0, + CV_EVENT_LBUTTONDOWN =1, + CV_EVENT_RBUTTONDOWN =2, + CV_EVENT_MBUTTONDOWN =3, + CV_EVENT_LBUTTONUP =4, + CV_EVENT_RBUTTONUP =5, + CV_EVENT_MBUTTONUP =6, + CV_EVENT_LBUTTONDBLCLK =7, + CV_EVENT_RBUTTONDBLCLK =8, + CV_EVENT_MBUTTONDBLCLK =9, + CV_EVENT_MOUSEWHEEL =10, + CV_EVENT_MOUSEHWHEEL =11 +}; + +enum +{ + CV_EVENT_FLAG_LBUTTON =1, + CV_EVENT_FLAG_RBUTTON =2, + CV_EVENT_FLAG_MBUTTON =4, + CV_EVENT_FLAG_CTRLKEY =8, + CV_EVENT_FLAG_SHIFTKEY =16, + CV_EVENT_FLAG_ALTKEY =32 +}; + + +#define CV_GET_WHEEL_DELTA(flags) ((short)((flags >> 16) & 0xffff)) // upper 16 bits + +typedef void (CV_CDECL *CvMouseCallback )(int event, int x, int y, int flags, void* param); + +/* assign callback for mouse events */ +CVAPI(void) cvSetMouseCallback( const char* window_name, CvMouseCallback on_mouse, + void* param CV_DEFAULT(NULL)); + +/* wait for key event infinitely (delay<=0) or for "delay" milliseconds */ +CVAPI(int) cvWaitKey(int delay CV_DEFAULT(0)); + +// OpenGL support + +typedef void (CV_CDECL *CvOpenGlDrawCallback)(void* userdata); +CVAPI(void) cvSetOpenGlDrawCallback(const char* window_name, CvOpenGlDrawCallback callback, void* userdata CV_DEFAULT(NULL)); + +CVAPI(void) cvSetOpenGlContext(const char* window_name); +CVAPI(void) cvUpdateWindow(const char* window_name); + + +/****************************************************************************************\ + +* Obsolete functions/synonyms * +\****************************************************************************************/ + +#define cvAddSearchPath(path) +#define cvvInitSystem cvInitSystem +#define cvvNamedWindow cvNamedWindow +#define cvvShowImage cvShowImage +#define cvvResizeWindow cvResizeWindow +#define cvvDestroyWindow cvDestroyWindow +#define cvvCreateTrackbar cvCreateTrackbar +#define cvvAddSearchPath cvAddSearchPath +#define cvvWaitKey(name) cvWaitKey(0) +#define cvvWaitKeyEx(name,delay) cvWaitKey(delay) +#define HG_AUTOSIZE CV_WINDOW_AUTOSIZE +#define set_preprocess_func cvSetPreprocessFuncWin32 +#define set_postprocess_func cvSetPostprocessFuncWin32 + +#if defined _WIN32 + +CVAPI(void) cvSetPreprocessFuncWin32_(const void* callback); +CVAPI(void) cvSetPostprocessFuncWin32_(const void* callback); +#define cvSetPreprocessFuncWin32(callback) cvSetPreprocessFuncWin32_((const void*)(callback)) +#define cvSetPostprocessFuncWin32(callback) cvSetPostprocessFuncWin32_((const void*)(callback)) + +#endif + +/** @} highgui_c */ + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/imgcodecs.hpp b/3rdparty/opencv/include/opencv2/imgcodecs.hpp new file mode 100644 index 00000000..ab75990e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgcodecs.hpp @@ -0,0 +1,260 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGCODECS_HPP +#define OPENCV_IMGCODECS_HPP + +#include "opencv2/core.hpp" + +/** + @defgroup imgcodecs Image file reading and writing + @{ + @defgroup imgcodecs_c C API + @defgroup imgcodecs_ios iOS glue + @} +*/ + +//////////////////////////////// image codec //////////////////////////////// +namespace cv +{ + +//! @addtogroup imgcodecs +//! @{ + +//! Imread flags +enum ImreadModes { + IMREAD_UNCHANGED = -1, //!< If set, return the loaded image as is (with alpha channel, otherwise it gets cropped). + IMREAD_GRAYSCALE = 0, //!< If set, always convert image to the single channel grayscale image (codec internal conversion). + IMREAD_COLOR = 1, //!< If set, always convert image to the 3 channel BGR color image. + IMREAD_ANYDEPTH = 2, //!< If set, return 16-bit/32-bit image when the input has the corresponding depth, otherwise convert it to 8-bit. + IMREAD_ANYCOLOR = 4, //!< If set, the image is read in any possible color format. + IMREAD_LOAD_GDAL = 8, //!< If set, use the gdal driver for loading the image. + IMREAD_REDUCED_GRAYSCALE_2 = 16, //!< If set, always convert image to the single channel grayscale image and the image size reduced 1/2. + IMREAD_REDUCED_COLOR_2 = 17, //!< If set, always convert image to the 3 channel BGR color image and the image size reduced 1/2. + IMREAD_REDUCED_GRAYSCALE_4 = 32, //!< If set, always convert image to the single channel grayscale image and the image size reduced 1/4. + IMREAD_REDUCED_COLOR_4 = 33, //!< If set, always convert image to the 3 channel BGR color image and the image size reduced 1/4. + IMREAD_REDUCED_GRAYSCALE_8 = 64, //!< If set, always convert image to the single channel grayscale image and the image size reduced 1/8. + IMREAD_REDUCED_COLOR_8 = 65, //!< If set, always convert image to the 3 channel BGR color image and the image size reduced 1/8. + IMREAD_IGNORE_ORIENTATION = 128 //!< If set, do not rotate the image according to EXIF's orientation flag. + }; + +//! Imwrite flags +enum ImwriteFlags { + IMWRITE_JPEG_QUALITY = 1, //!< For JPEG, it can be a quality from 0 to 100 (the higher is the better). Default value is 95. + IMWRITE_JPEG_PROGRESSIVE = 2, //!< Enable JPEG features, 0 or 1, default is False. + IMWRITE_JPEG_OPTIMIZE = 3, //!< Enable JPEG features, 0 or 1, default is False. + IMWRITE_JPEG_RST_INTERVAL = 4, //!< JPEG restart interval, 0 - 65535, default is 0 - no restart. + IMWRITE_JPEG_LUMA_QUALITY = 5, //!< Separate luma quality level, 0 - 100, default is 0 - don't use. + IMWRITE_JPEG_CHROMA_QUALITY = 6, //!< Separate chroma quality level, 0 - 100, default is 0 - don't use. + IMWRITE_PNG_COMPRESSION = 16, //!< For PNG, it can be the compression level from 0 to 9. A higher value means a smaller size and longer compression time. If specified, strategy is changed to IMWRITE_PNG_STRATEGY_DEFAULT (Z_DEFAULT_STRATEGY). Default value is 1 (best speed setting). + IMWRITE_PNG_STRATEGY = 17, //!< One of cv::ImwritePNGFlags, default is IMWRITE_PNG_STRATEGY_RLE. + IMWRITE_PNG_BILEVEL = 18, //!< Binary level PNG, 0 or 1, default is 0. + IMWRITE_PXM_BINARY = 32, //!< For PPM, PGM, or PBM, it can be a binary format flag, 0 or 1. Default value is 1. + IMWRITE_EXR_TYPE = (3 << 4) + 0, /* 48 */ //!< override EXR storage type (FLOAT (FP32) is default) + IMWRITE_WEBP_QUALITY = 64, //!< For WEBP, it can be a quality from 1 to 100 (the higher is the better). By default (without any parameter) and for quality above 100 the lossless compression is used. + IMWRITE_PAM_TUPLETYPE = 128,//!< For PAM, sets the TUPLETYPE field to the corresponding string value that is defined for the format + IMWRITE_TIFF_RESUNIT = 256,//!< For TIFF, use to specify which DPI resolution unit to set; see libtiff documentation for valid values. + IMWRITE_TIFF_XDPI = 257,//!< For TIFF, use to specify the X direction DPI. + IMWRITE_TIFF_YDPI = 258, //!< For TIFF, use to specify the Y direction DPI. + IMWRITE_TIFF_COMPRESSION = 259 //!< For TIFF, use to specify the image compression scheme. See libtiff for integer constants corresponding to compression formats. Note, for images whose depth is CV_32F, only libtiff's SGILOG compression scheme is used. For other supported depths, the compression scheme can be specified by this flag; LZW compression is the default. + }; + +enum ImwriteEXRTypeFlags { + /*IMWRITE_EXR_TYPE_UNIT = 0, //!< not supported */ + IMWRITE_EXR_TYPE_HALF = 1, //!< store as HALF (FP16) + IMWRITE_EXR_TYPE_FLOAT = 2 //!< store as FP32 (default) + }; + +//! Imwrite PNG specific flags used to tune the compression algorithm. +/** These flags will be modify the way of PNG image compression and will be passed to the underlying zlib processing stage. + +- The effect of IMWRITE_PNG_STRATEGY_FILTERED is to force more Huffman coding and less string matching; it is somewhat intermediate between IMWRITE_PNG_STRATEGY_DEFAULT and IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY. +- IMWRITE_PNG_STRATEGY_RLE is designed to be almost as fast as IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY, but give better compression for PNG image data. +- The strategy parameter only affects the compression ratio but not the correctness of the compressed output even if it is not set appropriately. +- IMWRITE_PNG_STRATEGY_FIXED prevents the use of dynamic Huffman codes, allowing for a simpler decoder for special applications. +*/ +enum ImwritePNGFlags { + IMWRITE_PNG_STRATEGY_DEFAULT = 0, //!< Use this value for normal data. + IMWRITE_PNG_STRATEGY_FILTERED = 1, //!< Use this value for data produced by a filter (or predictor).Filtered data consists mostly of small values with a somewhat random distribution. In this case, the compression algorithm is tuned to compress them better. + IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY = 2, //!< Use this value to force Huffman encoding only (no string match). + IMWRITE_PNG_STRATEGY_RLE = 3, //!< Use this value to limit match distances to one (run-length encoding). + IMWRITE_PNG_STRATEGY_FIXED = 4 //!< Using this value prevents the use of dynamic Huffman codes, allowing for a simpler decoder for special applications. + }; + +//! Imwrite PAM specific tupletype flags used to define the 'TUPETYPE' field of a PAM file. +enum ImwritePAMFlags { + IMWRITE_PAM_FORMAT_NULL = 0, + IMWRITE_PAM_FORMAT_BLACKANDWHITE = 1, + IMWRITE_PAM_FORMAT_GRAYSCALE = 2, + IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA = 3, + IMWRITE_PAM_FORMAT_RGB = 4, + IMWRITE_PAM_FORMAT_RGB_ALPHA = 5, + }; + +/** @brief Loads an image from a file. + +@anchor imread + +The function imread loads an image from the specified file and returns it. If the image cannot be +read (because of missing file, improper permissions, unsupported or invalid format), the function +returns an empty matrix ( Mat::data==NULL ). + +Currently, the following file formats are supported: + +- Windows bitmaps - \*.bmp, \*.dib (always supported) +- JPEG files - \*.jpeg, \*.jpg, \*.jpe (see the *Note* section) +- JPEG 2000 files - \*.jp2 (see the *Note* section) +- Portable Network Graphics - \*.png (see the *Note* section) +- WebP - \*.webp (see the *Note* section) +- Portable image format - \*.pbm, \*.pgm, \*.ppm \*.pxm, \*.pnm (always supported) +- Sun rasters - \*.sr, \*.ras (always supported) +- TIFF files - \*.tiff, \*.tif (see the *Note* section) +- OpenEXR Image files - \*.exr (see the *Note* section) +- Radiance HDR - \*.hdr, \*.pic (always supported) +- Raster and Vector geospatial data supported by GDAL (see the *Note* section) + +@note +- The function determines the type of an image by the content, not by the file extension. +- In the case of color images, the decoded images will have the channels stored in **B G R** order. +- When using IMREAD_GRAYSCALE, the codec's internal grayscale conversion will be used, if available. + Results may differ to the output of cvtColor() +- On Microsoft Windows\* OS and MacOSX\*, the codecs shipped with an OpenCV image (libjpeg, + libpng, libtiff, and libjasper) are used by default. So, OpenCV can always read JPEGs, PNGs, + and TIFFs. On MacOSX, there is also an option to use native MacOSX image readers. But beware + that currently these native image loaders give images with different pixel values because of + the color management embedded into MacOSX. +- On Linux\*, BSD flavors and other Unix-like open-source operating systems, OpenCV looks for + codecs supplied with an OS image. Install the relevant packages (do not forget the development + files, for example, "libjpeg-dev", in Debian\* and Ubuntu\*) to get the codec support or turn + on the OPENCV_BUILD_3RDPARTY_LIBS flag in CMake. +- In the case you set *WITH_GDAL* flag to true in CMake and @ref IMREAD_LOAD_GDAL to load the image, + then the [GDAL](http://www.gdal.org) driver will be used in order to decode the image, supporting + the following formats: [Raster](http://www.gdal.org/formats_list.html), + [Vector](http://www.gdal.org/ogr_formats.html). +- If EXIF information are embedded in the image file, the EXIF orientation will be taken into account + and thus the image will be rotated accordingly except if the flag @ref IMREAD_IGNORE_ORIENTATION is passed. +- By default number of pixels must be less than 2^30. Limit can be set using system + variable OPENCV_IO_MAX_IMAGE_PIXELS + +@param filename Name of file to be loaded. +@param flags Flag that can take values of cv::ImreadModes +*/ +CV_EXPORTS_W Mat imread( const String& filename, int flags = IMREAD_COLOR ); + +/** @brief Loads a multi-page image from a file. + +The function imreadmulti loads a multi-page image from the specified file into a vector of Mat objects. +@param filename Name of file to be loaded. +@param flags Flag that can take values of cv::ImreadModes, default with cv::IMREAD_ANYCOLOR. +@param mats A vector of Mat objects holding each page, if more than one. +@sa cv::imread +*/ +CV_EXPORTS_W bool imreadmulti(const String& filename, CV_OUT std::vector& mats, int flags = IMREAD_ANYCOLOR); + +/** @brief Saves an image to a specified file. + +The function imwrite saves the image to the specified file. The image format is chosen based on the +filename extension (see cv::imread for the list of extensions). In general, only 8-bit +single-channel or 3-channel (with 'BGR' channel order) images +can be saved using this function, with these exceptions: + +- 16-bit unsigned (CV_16U) images can be saved in the case of PNG, JPEG 2000, and TIFF formats +- 32-bit float (CV_32F) images can be saved in TIFF, OpenEXR, and Radiance HDR formats; 3-channel +(CV_32FC3) TIFF images will be saved using the LogLuv high dynamic range encoding (4 bytes per pixel) +- PNG images with an alpha channel can be saved using this function. To do this, create +8-bit (or 16-bit) 4-channel image BGRA, where the alpha channel goes last. Fully transparent pixels +should have alpha set to 0, fully opaque pixels should have alpha set to 255/65535 (see the code sample below). + +If the format, depth or channel order is different, use +Mat::convertTo and cv::cvtColor to convert it before saving. Or, use the universal FileStorage I/O +functions to save the image to XML or YAML format. + +The sample below shows how to create a BGRA image and save it to a PNG file. It also demonstrates how to set custom +compression parameters: +@include snippets/imgcodecs_imwrite.cpp +@param filename Name of the file. +@param img Image to be saved. +@param params Format-specific parameters encoded as pairs (paramId_1, paramValue_1, paramId_2, paramValue_2, ... .) see cv::ImwriteFlags +*/ +CV_EXPORTS_W bool imwrite( const String& filename, InputArray img, + const std::vector& params = std::vector()); + +/** @brief Reads an image from a buffer in memory. + +The function imdecode reads an image from the specified buffer in the memory. If the buffer is too short or +contains invalid data, the function returns an empty matrix ( Mat::data==NULL ). + +See cv::imread for the list of supported formats and flags description. + +@note In the case of color images, the decoded images will have the channels stored in **B G R** order. +@param buf Input array or vector of bytes. +@param flags The same flags as in cv::imread, see cv::ImreadModes. +*/ +CV_EXPORTS_W Mat imdecode( InputArray buf, int flags ); + +/** @overload +@param buf +@param flags +@param dst The optional output placeholder for the decoded matrix. It can save the image +reallocations when the function is called repeatedly for images of the same size. +*/ +CV_EXPORTS Mat imdecode( InputArray buf, int flags, Mat* dst); + +/** @brief Encodes an image into a memory buffer. + +The function imencode compresses the image and stores it in the memory buffer that is resized to fit the +result. See cv::imwrite for the list of supported formats and flags description. + +@param ext File extension that defines the output format. +@param img Image to be written. +@param buf Output buffer resized to fit the compressed image. +@param params Format-specific parameters. See cv::imwrite and cv::ImwriteFlags. +*/ +CV_EXPORTS_W bool imencode( const String& ext, InputArray img, + CV_OUT std::vector& buf, + const std::vector& params = std::vector()); + +//! @} imgcodecs + +} // cv + +#endif //OPENCV_IMGCODECS_HPP diff --git a/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs.hpp b/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs.hpp new file mode 100644 index 00000000..a3cd2326 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/imgcodecs.hpp" diff --git a/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs_c.h b/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs_c.h new file mode 100644 index 00000000..c36dac33 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgcodecs/imgcodecs_c.h @@ -0,0 +1,149 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGCODECS_H +#define OPENCV_IMGCODECS_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +extern "C" { +#endif /* __cplusplus */ + +/** @addtogroup imgcodecs_c + @{ + */ + +enum +{ +/* 8bit, color or not */ + CV_LOAD_IMAGE_UNCHANGED =-1, +/* 8bit, gray */ + CV_LOAD_IMAGE_GRAYSCALE =0, +/* ?, color */ + CV_LOAD_IMAGE_COLOR =1, +/* any depth, ? */ + CV_LOAD_IMAGE_ANYDEPTH =2, +/* ?, any color */ + CV_LOAD_IMAGE_ANYCOLOR =4, +/* ?, no rotate */ + CV_LOAD_IMAGE_IGNORE_ORIENTATION =128 +}; + +/* load image from file + iscolor can be a combination of above flags where CV_LOAD_IMAGE_UNCHANGED + overrides the other flags + using CV_LOAD_IMAGE_ANYCOLOR alone is equivalent to CV_LOAD_IMAGE_UNCHANGED + unless CV_LOAD_IMAGE_ANYDEPTH is specified images are converted to 8bit +*/ +CVAPI(IplImage*) cvLoadImage( const char* filename, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR)); +CVAPI(CvMat*) cvLoadImageM( const char* filename, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR)); + +enum +{ + CV_IMWRITE_JPEG_QUALITY =1, + CV_IMWRITE_JPEG_PROGRESSIVE =2, + CV_IMWRITE_JPEG_OPTIMIZE =3, + CV_IMWRITE_JPEG_RST_INTERVAL =4, + CV_IMWRITE_JPEG_LUMA_QUALITY =5, + CV_IMWRITE_JPEG_CHROMA_QUALITY =6, + CV_IMWRITE_PNG_COMPRESSION =16, + CV_IMWRITE_PNG_STRATEGY =17, + CV_IMWRITE_PNG_BILEVEL =18, + CV_IMWRITE_PNG_STRATEGY_DEFAULT =0, + CV_IMWRITE_PNG_STRATEGY_FILTERED =1, + CV_IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY =2, + CV_IMWRITE_PNG_STRATEGY_RLE =3, + CV_IMWRITE_PNG_STRATEGY_FIXED =4, + CV_IMWRITE_PXM_BINARY =32, + CV_IMWRITE_EXR_TYPE = 48, + CV_IMWRITE_WEBP_QUALITY =64, + CV_IMWRITE_PAM_TUPLETYPE = 128, + CV_IMWRITE_PAM_FORMAT_NULL = 0, + CV_IMWRITE_PAM_FORMAT_BLACKANDWHITE = 1, + CV_IMWRITE_PAM_FORMAT_GRAYSCALE = 2, + CV_IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA = 3, + CV_IMWRITE_PAM_FORMAT_RGB = 4, + CV_IMWRITE_PAM_FORMAT_RGB_ALPHA = 5, +}; + + + +/* save image to file */ +CVAPI(int) cvSaveImage( const char* filename, const CvArr* image, + const int* params CV_DEFAULT(0) ); + +/* decode image stored in the buffer */ +CVAPI(IplImage*) cvDecodeImage( const CvMat* buf, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR)); +CVAPI(CvMat*) cvDecodeImageM( const CvMat* buf, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR)); + +/* encode image and store the result as a byte vector (single-row 8uC1 matrix) */ +CVAPI(CvMat*) cvEncodeImage( const char* ext, const CvArr* image, + const int* params CV_DEFAULT(0) ); + +enum +{ + CV_CVTIMG_FLIP =1, + CV_CVTIMG_SWAP_RB =2 +}; + +/* utility function: convert one image to another with optional vertical flip */ +CVAPI(void) cvConvertImage( const CvArr* src, CvArr* dst, int flags CV_DEFAULT(0)); + +CVAPI(int) cvHaveImageReader(const char* filename); +CVAPI(int) cvHaveImageWriter(const char* filename); + + +/****************************************************************************************\ +* Obsolete functions/synonyms * +\****************************************************************************************/ + +#define cvvLoadImage(name) cvLoadImage((name),1) +#define cvvSaveImage cvSaveImage +#define cvvConvertImage cvConvertImage + +/** @} imgcodecs_c */ + +#ifdef __cplusplus +} +#endif + +#endif // OPENCV_IMGCODECS_H diff --git a/3rdparty/opencv/include/opencv2/imgcodecs/ios.h b/3rdparty/opencv/include/opencv2/imgcodecs/ios.h new file mode 100644 index 00000000..a90c6d37 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgcodecs/ios.h @@ -0,0 +1,57 @@ + +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#import +#import +#import +#import +#include "opencv2/core/core.hpp" + +//! @addtogroup imgcodecs_ios +//! @{ + +CV_EXPORTS UIImage* MatToUIImage(const cv::Mat& image); +CV_EXPORTS void UIImageToMat(const UIImage* image, + cv::Mat& m, bool alphaExist = false); + +//! @} diff --git a/3rdparty/opencv/include/opencv2/imgproc.hpp b/3rdparty/opencv/include/opencv2/imgproc.hpp new file mode 100644 index 00000000..ab7d0e6b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc.hpp @@ -0,0 +1,4922 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGPROC_HPP +#define OPENCV_IMGPROC_HPP + +#include "opencv2/core.hpp" + +/** + @defgroup imgproc Image Processing + +This module includes image-processing functions. + + @{ + @defgroup imgproc_filter Image Filtering + +Functions and classes described in this section are used to perform various linear or non-linear +filtering operations on 2D images (represented as Mat's). It means that for each pixel location +\f$(x,y)\f$ in the source image (normally, rectangular), its neighborhood is considered and used to +compute the response. In case of a linear filter, it is a weighted sum of pixel values. In case of +morphological operations, it is the minimum or maximum values, and so on. The computed response is +stored in the destination image at the same location \f$(x,y)\f$. It means that the output image +will be of the same size as the input image. Normally, the functions support multi-channel arrays, +in which case every channel is processed independently. Therefore, the output image will also have +the same number of channels as the input one. + +Another common feature of the functions and classes described in this section is that, unlike +simple arithmetic functions, they need to extrapolate values of some non-existing pixels. For +example, if you want to smooth an image using a Gaussian \f$3 \times 3\f$ filter, then, when +processing the left-most pixels in each row, you need pixels to the left of them, that is, outside +of the image. You can let these pixels be the same as the left-most image pixels ("replicated +border" extrapolation method), or assume that all the non-existing pixels are zeros ("constant +border" extrapolation method), and so on. OpenCV enables you to specify the extrapolation method. +For details, see #BorderTypes + +@anchor filter_depths +### Depth combinations +Input depth (src.depth()) | Output depth (ddepth) +--------------------------|---------------------- +CV_8U | -1/CV_16S/CV_32F/CV_64F +CV_16U/CV_16S | -1/CV_32F/CV_64F +CV_32F | -1/CV_32F/CV_64F +CV_64F | -1/CV_64F + +@note when ddepth=-1, the output image will have the same depth as the source. + + @defgroup imgproc_transform Geometric Image Transformations + +The functions in this section perform various geometrical transformations of 2D images. They do not +change the image content but deform the pixel grid and map this deformed grid to the destination +image. In fact, to avoid sampling artifacts, the mapping is done in the reverse order, from +destination to the source. That is, for each pixel \f$(x, y)\f$ of the destination image, the +functions compute coordinates of the corresponding "donor" pixel in the source image and copy the +pixel value: + +\f[\texttt{dst} (x,y)= \texttt{src} (f_x(x,y), f_y(x,y))\f] + +In case when you specify the forward mapping \f$\left: \texttt{src} \rightarrow +\texttt{dst}\f$, the OpenCV functions first compute the corresponding inverse mapping +\f$\left: \texttt{dst} \rightarrow \texttt{src}\f$ and then use the above formula. + +The actual implementations of the geometrical transformations, from the most generic remap and to +the simplest and the fastest resize, need to solve two main problems with the above formula: + +- Extrapolation of non-existing pixels. Similarly to the filtering functions described in the +previous section, for some \f$(x,y)\f$, either one of \f$f_x(x,y)\f$, or \f$f_y(x,y)\f$, or both +of them may fall outside of the image. In this case, an extrapolation method needs to be used. +OpenCV provides the same selection of extrapolation methods as in the filtering functions. In +addition, it provides the method #BORDER_TRANSPARENT. This means that the corresponding pixels in +the destination image will not be modified at all. + +- Interpolation of pixel values. Usually \f$f_x(x,y)\f$ and \f$f_y(x,y)\f$ are floating-point +numbers. This means that \f$\left\f$ can be either an affine or perspective +transformation, or radial lens distortion correction, and so on. So, a pixel value at fractional +coordinates needs to be retrieved. In the simplest case, the coordinates can be just rounded to the +nearest integer coordinates and the corresponding pixel can be used. This is called a +nearest-neighbor interpolation. However, a better result can be achieved by using more +sophisticated [interpolation methods](http://en.wikipedia.org/wiki/Multivariate_interpolation) , +where a polynomial function is fit into some neighborhood of the computed pixel \f$(f_x(x,y), +f_y(x,y))\f$, and then the value of the polynomial at \f$(f_x(x,y), f_y(x,y))\f$ is taken as the +interpolated pixel value. In OpenCV, you can choose between several interpolation methods. See +resize for details. + +@note The geometrical transformations do not work with `CV_8S` or `CV_32S` images. + + @defgroup imgproc_misc Miscellaneous Image Transformations + @defgroup imgproc_draw Drawing Functions + +Drawing functions work with matrices/images of arbitrary depth. The boundaries of the shapes can be +rendered with antialiasing (implemented only for 8-bit images for now). All the functions include +the parameter color that uses an RGB value (that may be constructed with the Scalar constructor ) +for color images and brightness for grayscale images. For color images, the channel ordering is +normally *Blue, Green, Red*. This is what imshow, imread, and imwrite expect. So, if you form a +color using the Scalar constructor, it should look like: + +\f[\texttt{Scalar} (blue \_ component, green \_ component, red \_ component[, alpha \_ component])\f] + +If you are using your own image rendering and I/O functions, you can use any channel ordering. The +drawing functions process each channel independently and do not depend on the channel order or even +on the used color space. The whole image can be converted from BGR to RGB or to a different color +space using cvtColor . + +If a drawn figure is partially or completely outside the image, the drawing functions clip it. Also, +many drawing functions can handle pixel coordinates specified with sub-pixel accuracy. This means +that the coordinates can be passed as fixed-point numbers encoded as integers. The number of +fractional bits is specified by the shift parameter and the real point coordinates are calculated as +\f$\texttt{Point}(x,y)\rightarrow\texttt{Point2f}(x*2^{-shift},y*2^{-shift})\f$ . This feature is +especially effective when rendering antialiased shapes. + +@note The functions do not support alpha-transparency when the target image is 4-channel. In this +case, the color[3] is simply copied to the repainted pixels. Thus, if you want to paint +semi-transparent shapes, you can paint them in a separate buffer and then blend it with the main +image. + + @defgroup imgproc_color_conversions Color Space Conversions + @defgroup imgproc_colormap ColorMaps in OpenCV + +The human perception isn't built for observing fine changes in grayscale images. Human eyes are more +sensitive to observing changes between colors, so you often need to recolor your grayscale images to +get a clue about them. OpenCV now comes with various colormaps to enhance the visualization in your +computer vision application. + +In OpenCV you only need applyColorMap to apply a colormap on a given image. The following sample +code reads the path to an image from command line, applies a Jet colormap on it and shows the +result: + +@include snippets/imgproc_applyColorMap.cpp + +@see #ColormapTypes + + @defgroup imgproc_subdiv2d Planar Subdivision + +The Subdiv2D class described in this section is used to perform various planar subdivision on +a set of 2D points (represented as vector of Point2f). OpenCV subdivides a plane into triangles +using the Delaunay's algorithm, which corresponds to the dual graph of the Voronoi diagram. +In the figure below, the Delaunay's triangulation is marked with black lines and the Voronoi +diagram with red lines. + +![Delaunay triangulation (black) and Voronoi (red)](pics/delaunay_voronoi.png) + +The subdivisions can be used for the 3D piece-wise transformation of a plane, morphing, fast +location of points on the plane, building special graphs (such as NNG,RNG), and so forth. + + @defgroup imgproc_hist Histograms + @defgroup imgproc_shape Structural Analysis and Shape Descriptors + @defgroup imgproc_motion Motion Analysis and Object Tracking + @defgroup imgproc_feature Feature Detection + @defgroup imgproc_object Object Detection + @defgroup imgproc_c C API + @defgroup imgproc_hal Hardware Acceleration Layer + @{ + @defgroup imgproc_hal_functions Functions + @defgroup imgproc_hal_interface Interface + @} + @} +*/ + +namespace cv +{ + +/** @addtogroup imgproc +@{ +*/ + +//! @addtogroup imgproc_filter +//! @{ + +//! type of morphological operation +enum MorphTypes{ + MORPH_ERODE = 0, //!< see #erode + MORPH_DILATE = 1, //!< see #dilate + MORPH_OPEN = 2, //!< an opening operation + //!< \f[\texttt{dst} = \mathrm{open} ( \texttt{src} , \texttt{element} )= \mathrm{dilate} ( \mathrm{erode} ( \texttt{src} , \texttt{element} ))\f] + MORPH_CLOSE = 3, //!< a closing operation + //!< \f[\texttt{dst} = \mathrm{close} ( \texttt{src} , \texttt{element} )= \mathrm{erode} ( \mathrm{dilate} ( \texttt{src} , \texttt{element} ))\f] + MORPH_GRADIENT = 4, //!< a morphological gradient + //!< \f[\texttt{dst} = \mathrm{morph\_grad} ( \texttt{src} , \texttt{element} )= \mathrm{dilate} ( \texttt{src} , \texttt{element} )- \mathrm{erode} ( \texttt{src} , \texttt{element} )\f] + MORPH_TOPHAT = 5, //!< "top hat" + //!< \f[\texttt{dst} = \mathrm{tophat} ( \texttt{src} , \texttt{element} )= \texttt{src} - \mathrm{open} ( \texttt{src} , \texttt{element} )\f] + MORPH_BLACKHAT = 6, //!< "black hat" + //!< \f[\texttt{dst} = \mathrm{blackhat} ( \texttt{src} , \texttt{element} )= \mathrm{close} ( \texttt{src} , \texttt{element} )- \texttt{src}\f] + MORPH_HITMISS = 7 //!< "hit or miss" + //!< .- Only supported for CV_8UC1 binary images. A tutorial can be found in the documentation +}; + +//! shape of the structuring element +enum MorphShapes { + MORPH_RECT = 0, //!< a rectangular structuring element: \f[E_{ij}=1\f] + MORPH_CROSS = 1, //!< a cross-shaped structuring element: + //!< \f[E_{ij} = \fork{1}{if i=\texttt{anchor.y} or j=\texttt{anchor.x}}{0}{otherwise}\f] + MORPH_ELLIPSE = 2 //!< an elliptic structuring element, that is, a filled ellipse inscribed + //!< into the rectangle Rect(0, 0, esize.width, 0.esize.height) +}; + +//! @} imgproc_filter + +//! @addtogroup imgproc_transform +//! @{ + +//! interpolation algorithm +enum InterpolationFlags{ + /** nearest neighbor interpolation */ + INTER_NEAREST = 0, + /** bilinear interpolation */ + INTER_LINEAR = 1, + /** bicubic interpolation */ + INTER_CUBIC = 2, + /** resampling using pixel area relation. It may be a preferred method for image decimation, as + it gives moire'-free results. But when the image is zoomed, it is similar to the INTER_NEAREST + method. */ + INTER_AREA = 3, + /** Lanczos interpolation over 8x8 neighborhood */ + INTER_LANCZOS4 = 4, + /** Bit exact bilinear interpolation */ + INTER_LINEAR_EXACT = 5, + /** mask for interpolation codes */ + INTER_MAX = 7, + /** flag, fills all of the destination image pixels. If some of them correspond to outliers in the + source image, they are set to zero */ + WARP_FILL_OUTLIERS = 8, + /** flag, inverse transformation + + For example, #linearPolar or #logPolar transforms: + - flag is __not__ set: \f$dst( \rho , \phi ) = src(x,y)\f$ + - flag is set: \f$dst(x,y) = src( \rho , \phi )\f$ + */ + WARP_INVERSE_MAP = 16 +}; + +/** \brief Specify the polar mapping mode +@sa warpPolar +*/ +enum WarpPolarMode +{ + WARP_POLAR_LINEAR = 0, ///< Remaps an image to/from polar space. + WARP_POLAR_LOG = 256 ///< Remaps an image to/from semilog-polar space. +}; + +enum InterpolationMasks { + INTER_BITS = 5, + INTER_BITS2 = INTER_BITS * 2, + INTER_TAB_SIZE = 1 << INTER_BITS, + INTER_TAB_SIZE2 = INTER_TAB_SIZE * INTER_TAB_SIZE + }; + +//! @} imgproc_transform + +//! @addtogroup imgproc_misc +//! @{ + +//! Distance types for Distance Transform and M-estimators +//! @see distanceTransform, fitLine +enum DistanceTypes { + DIST_USER = -1, //!< User defined distance + DIST_L1 = 1, //!< distance = |x1-x2| + |y1-y2| + DIST_L2 = 2, //!< the simple euclidean distance + DIST_C = 3, //!< distance = max(|x1-x2|,|y1-y2|) + DIST_L12 = 4, //!< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) + DIST_FAIR = 5, //!< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 + DIST_WELSCH = 6, //!< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 + DIST_HUBER = 7 //!< distance = |x| \texttt{thresh}\)}{0}{otherwise}\f] + THRESH_BINARY_INV = 1, //!< \f[\texttt{dst} (x,y) = \fork{0}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{maxval}}{otherwise}\f] + THRESH_TRUNC = 2, //!< \f[\texttt{dst} (x,y) = \fork{\texttt{threshold}}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{src}(x,y)}{otherwise}\f] + THRESH_TOZERO = 3, //!< \f[\texttt{dst} (x,y) = \fork{\texttt{src}(x,y)}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{0}{otherwise}\f] + THRESH_TOZERO_INV = 4, //!< \f[\texttt{dst} (x,y) = \fork{0}{if \(\texttt{src}(x,y) > \texttt{thresh}\)}{\texttt{src}(x,y)}{otherwise}\f] + THRESH_MASK = 7, + THRESH_OTSU = 8, //!< flag, use Otsu algorithm to choose the optimal threshold value + THRESH_TRIANGLE = 16 //!< flag, use Triangle algorithm to choose the optimal threshold value +}; + +//! adaptive threshold algorithm +//! @see adaptiveThreshold +enum AdaptiveThresholdTypes { + /** the threshold value \f$T(x,y)\f$ is a mean of the \f$\texttt{blockSize} \times + \texttt{blockSize}\f$ neighborhood of \f$(x, y)\f$ minus C */ + ADAPTIVE_THRESH_MEAN_C = 0, + /** the threshold value \f$T(x, y)\f$ is a weighted sum (cross-correlation with a Gaussian + window) of the \f$\texttt{blockSize} \times \texttt{blockSize}\f$ neighborhood of \f$(x, y)\f$ + minus C . The default sigma (standard deviation) is used for the specified blockSize . See + #getGaussianKernel*/ + ADAPTIVE_THRESH_GAUSSIAN_C = 1 +}; + +//! cv::undistort mode +enum UndistortTypes { + PROJ_SPHERICAL_ORTHO = 0, + PROJ_SPHERICAL_EQRECT = 1 + }; + +//! class of the pixel in GrabCut algorithm +enum GrabCutClasses { + GC_BGD = 0, //!< an obvious background pixels + GC_FGD = 1, //!< an obvious foreground (object) pixel + GC_PR_BGD = 2, //!< a possible background pixel + GC_PR_FGD = 3 //!< a possible foreground pixel +}; + +//! GrabCut algorithm flags +enum GrabCutModes { + /** The function initializes the state and the mask using the provided rectangle. After that it + runs iterCount iterations of the algorithm. */ + GC_INIT_WITH_RECT = 0, + /** The function initializes the state using the provided mask. Note that GC_INIT_WITH_RECT + and GC_INIT_WITH_MASK can be combined. Then, all the pixels outside of the ROI are + automatically initialized with GC_BGD .*/ + GC_INIT_WITH_MASK = 1, + /** The value means that the algorithm should just resume. */ + GC_EVAL = 2, + /** The value means that the algorithm should just run the grabCut algorithm (a single iteration) with the fixed model */ + GC_EVAL_FREEZE_MODEL = 3 +}; + +//! distanceTransform algorithm flags +enum DistanceTransformLabelTypes { + /** each connected component of zeros in src (as well as all the non-zero pixels closest to the + connected component) will be assigned the same label */ + DIST_LABEL_CCOMP = 0, + /** each zero pixel (and all the non-zero pixels closest to it) gets its own label. */ + DIST_LABEL_PIXEL = 1 +}; + +//! floodfill algorithm flags +enum FloodFillFlags { + /** If set, the difference between the current pixel and seed pixel is considered. Otherwise, + the difference between neighbor pixels is considered (that is, the range is floating). */ + FLOODFILL_FIXED_RANGE = 1 << 16, + /** If set, the function does not change the image ( newVal is ignored), and only fills the + mask with the value specified in bits 8-16 of flags as described above. This option only make + sense in function variants that have the mask parameter. */ + FLOODFILL_MASK_ONLY = 1 << 17 +}; + +//! @} imgproc_misc + +//! @addtogroup imgproc_shape +//! @{ + +//! connected components algorithm output formats +enum ConnectedComponentsTypes { + CC_STAT_LEFT = 0, //!< The leftmost (x) coordinate which is the inclusive start of the bounding + //!< box in the horizontal direction. + CC_STAT_TOP = 1, //!< The topmost (y) coordinate which is the inclusive start of the bounding + //!< box in the vertical direction. + CC_STAT_WIDTH = 2, //!< The horizontal size of the bounding box + CC_STAT_HEIGHT = 3, //!< The vertical size of the bounding box + CC_STAT_AREA = 4, //!< The total area (in pixels) of the connected component + CC_STAT_MAX = 5 +}; + +//! connected components algorithm +enum ConnectedComponentsAlgorithmsTypes { + CCL_WU = 0, //!< SAUF algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity + CCL_DEFAULT = -1, //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity + CCL_GRANA = 1 //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity +}; + +//! mode of the contour retrieval algorithm +enum RetrievalModes { + /** retrieves only the extreme outer contours. It sets `hierarchy[i][2]=hierarchy[i][3]=-1` for + all the contours. */ + RETR_EXTERNAL = 0, + /** retrieves all of the contours without establishing any hierarchical relationships. */ + RETR_LIST = 1, + /** retrieves all of the contours and organizes them into a two-level hierarchy. At the top + level, there are external boundaries of the components. At the second level, there are + boundaries of the holes. If there is another contour inside a hole of a connected component, it + is still put at the top level. */ + RETR_CCOMP = 2, + /** retrieves all of the contours and reconstructs a full hierarchy of nested contours.*/ + RETR_TREE = 3, + RETR_FLOODFILL = 4 //!< +}; + +//! the contour approximation algorithm +enum ContourApproximationModes { + /** stores absolutely all the contour points. That is, any 2 subsequent points (x1,y1) and + (x2,y2) of the contour will be either horizontal, vertical or diagonal neighbors, that is, + max(abs(x1-x2),abs(y2-y1))==1. */ + CHAIN_APPROX_NONE = 1, + /** compresses horizontal, vertical, and diagonal segments and leaves only their end points. + For example, an up-right rectangular contour is encoded with 4 points. */ + CHAIN_APPROX_SIMPLE = 2, + /** applies one of the flavors of the Teh-Chin chain approximation algorithm @cite TehChin89 */ + CHAIN_APPROX_TC89_L1 = 3, + /** applies one of the flavors of the Teh-Chin chain approximation algorithm @cite TehChin89 */ + CHAIN_APPROX_TC89_KCOS = 4 +}; + +/** @brief Shape matching methods + +\f$A\f$ denotes object1,\f$B\f$ denotes object2 + +\f$\begin{array}{l} m^A_i = \mathrm{sign} (h^A_i) \cdot \log{h^A_i} \\ m^B_i = \mathrm{sign} (h^B_i) \cdot \log{h^B_i} \end{array}\f$ + +and \f$h^A_i, h^B_i\f$ are the Hu moments of \f$A\f$ and \f$B\f$ , respectively. +*/ +enum ShapeMatchModes { + CONTOURS_MATCH_I1 =1, //!< \f[I_1(A,B) = \sum _{i=1...7} \left | \frac{1}{m^A_i} - \frac{1}{m^B_i} \right |\f] + CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f] + CONTOURS_MATCH_I3 =3 //!< \f[I_3(A,B) = \max _{i=1...7} \frac{ \left| m^A_i - m^B_i \right| }{ \left| m^A_i \right| }\f] +}; + +//! @} imgproc_shape + +//! @addtogroup imgproc_feature +//! @{ + +//! Variants of a Hough transform +enum HoughModes { + + /** classical or standard Hough transform. Every line is represented by two floating-point + numbers \f$(\rho, \theta)\f$ , where \f$\rho\f$ is a distance between (0,0) point and the line, + and \f$\theta\f$ is the angle between x-axis and the normal to the line. Thus, the matrix must + be (the created sequence will be) of CV_32FC2 type */ + HOUGH_STANDARD = 0, + /** probabilistic Hough transform (more efficient in case if the picture contains a few long + linear segments). It returns line segments rather than the whole line. Each segment is + represented by starting and ending points, and the matrix must be (the created sequence will + be) of the CV_32SC4 type. */ + HOUGH_PROBABILISTIC = 1, + /** multi-scale variant of the classical Hough transform. The lines are encoded the same way as + HOUGH_STANDARD. */ + HOUGH_MULTI_SCALE = 2, + HOUGH_GRADIENT = 3 //!< basically *21HT*, described in @cite Yuen90 +}; + +//! Variants of Line Segment %Detector +enum LineSegmentDetectorModes { + LSD_REFINE_NONE = 0, //!< No refinement applied + LSD_REFINE_STD = 1, //!< Standard refinement is applied. E.g. breaking arches into smaller straighter line approximations. + LSD_REFINE_ADV = 2 //!< Advanced refinement. Number of false alarms is calculated, lines are + //!< refined through increase of precision, decrement in size, etc. +}; + +//! @} imgproc_feature + +/** Histogram comparison methods + @ingroup imgproc_hist +*/ +enum HistCompMethods { + /** Correlation + \f[d(H_1,H_2) = \frac{\sum_I (H_1(I) - \bar{H_1}) (H_2(I) - \bar{H_2})}{\sqrt{\sum_I(H_1(I) - \bar{H_1})^2 \sum_I(H_2(I) - \bar{H_2})^2}}\f] + where + \f[\bar{H_k} = \frac{1}{N} \sum _J H_k(J)\f] + and \f$N\f$ is a total number of histogram bins. */ + HISTCMP_CORREL = 0, + /** Chi-Square + \f[d(H_1,H_2) = \sum _I \frac{\left(H_1(I)-H_2(I)\right)^2}{H_1(I)}\f] */ + HISTCMP_CHISQR = 1, + /** Intersection + \f[d(H_1,H_2) = \sum _I \min (H_1(I), H_2(I))\f] */ + HISTCMP_INTERSECT = 2, + /** Bhattacharyya distance + (In fact, OpenCV computes Hellinger distance, which is related to Bhattacharyya coefficient.) + \f[d(H_1,H_2) = \sqrt{1 - \frac{1}{\sqrt{\bar{H_1} \bar{H_2} N^2}} \sum_I \sqrt{H_1(I) \cdot H_2(I)}}\f] */ + HISTCMP_BHATTACHARYYA = 3, + HISTCMP_HELLINGER = HISTCMP_BHATTACHARYYA, //!< Synonym for HISTCMP_BHATTACHARYYA + /** Alternative Chi-Square + \f[d(H_1,H_2) = 2 * \sum _I \frac{\left(H_1(I)-H_2(I)\right)^2}{H_1(I)+H_2(I)}\f] + This alternative formula is regularly used for texture comparison. See e.g. @cite Puzicha1997 */ + HISTCMP_CHISQR_ALT = 4, + /** Kullback-Leibler divergence + \f[d(H_1,H_2) = \sum _I H_1(I) \log \left(\frac{H_1(I)}{H_2(I)}\right)\f] */ + HISTCMP_KL_DIV = 5 +}; + +/** the color conversion codes +@see @ref imgproc_color_conversions +@ingroup imgproc_color_conversions + */ +enum ColorConversionCodes { + COLOR_BGR2BGRA = 0, //!< add alpha channel to RGB or BGR image + COLOR_RGB2RGBA = COLOR_BGR2BGRA, + + COLOR_BGRA2BGR = 1, //!< remove alpha channel from RGB or BGR image + COLOR_RGBA2RGB = COLOR_BGRA2BGR, + + COLOR_BGR2RGBA = 2, //!< convert between RGB and BGR color spaces (with or without alpha channel) + COLOR_RGB2BGRA = COLOR_BGR2RGBA, + + COLOR_RGBA2BGR = 3, + COLOR_BGRA2RGB = COLOR_RGBA2BGR, + + COLOR_BGR2RGB = 4, + COLOR_RGB2BGR = COLOR_BGR2RGB, + + COLOR_BGRA2RGBA = 5, + COLOR_RGBA2BGRA = COLOR_BGRA2RGBA, + + COLOR_BGR2GRAY = 6, //!< convert between RGB/BGR and grayscale, @ref color_convert_rgb_gray "color conversions" + COLOR_RGB2GRAY = 7, + COLOR_GRAY2BGR = 8, + COLOR_GRAY2RGB = COLOR_GRAY2BGR, + COLOR_GRAY2BGRA = 9, + COLOR_GRAY2RGBA = COLOR_GRAY2BGRA, + COLOR_BGRA2GRAY = 10, + COLOR_RGBA2GRAY = 11, + + COLOR_BGR2BGR565 = 12, //!< convert between RGB/BGR and BGR565 (16-bit images) + COLOR_RGB2BGR565 = 13, + COLOR_BGR5652BGR = 14, + COLOR_BGR5652RGB = 15, + COLOR_BGRA2BGR565 = 16, + COLOR_RGBA2BGR565 = 17, + COLOR_BGR5652BGRA = 18, + COLOR_BGR5652RGBA = 19, + + COLOR_GRAY2BGR565 = 20, //!< convert between grayscale to BGR565 (16-bit images) + COLOR_BGR5652GRAY = 21, + + COLOR_BGR2BGR555 = 22, //!< convert between RGB/BGR and BGR555 (16-bit images) + COLOR_RGB2BGR555 = 23, + COLOR_BGR5552BGR = 24, + COLOR_BGR5552RGB = 25, + COLOR_BGRA2BGR555 = 26, + COLOR_RGBA2BGR555 = 27, + COLOR_BGR5552BGRA = 28, + COLOR_BGR5552RGBA = 29, + + COLOR_GRAY2BGR555 = 30, //!< convert between grayscale and BGR555 (16-bit images) + COLOR_BGR5552GRAY = 31, + + COLOR_BGR2XYZ = 32, //!< convert RGB/BGR to CIE XYZ, @ref color_convert_rgb_xyz "color conversions" + COLOR_RGB2XYZ = 33, + COLOR_XYZ2BGR = 34, + COLOR_XYZ2RGB = 35, + + COLOR_BGR2YCrCb = 36, //!< convert RGB/BGR to luma-chroma (aka YCC), @ref color_convert_rgb_ycrcb "color conversions" + COLOR_RGB2YCrCb = 37, + COLOR_YCrCb2BGR = 38, + COLOR_YCrCb2RGB = 39, + + COLOR_BGR2HSV = 40, //!< convert RGB/BGR to HSV (hue saturation value), @ref color_convert_rgb_hsv "color conversions" + COLOR_RGB2HSV = 41, + + COLOR_BGR2Lab = 44, //!< convert RGB/BGR to CIE Lab, @ref color_convert_rgb_lab "color conversions" + COLOR_RGB2Lab = 45, + + COLOR_BGR2Luv = 50, //!< convert RGB/BGR to CIE Luv, @ref color_convert_rgb_luv "color conversions" + COLOR_RGB2Luv = 51, + COLOR_BGR2HLS = 52, //!< convert RGB/BGR to HLS (hue lightness saturation), @ref color_convert_rgb_hls "color conversions" + COLOR_RGB2HLS = 53, + + COLOR_HSV2BGR = 54, //!< backward conversions to RGB/BGR + COLOR_HSV2RGB = 55, + + COLOR_Lab2BGR = 56, + COLOR_Lab2RGB = 57, + COLOR_Luv2BGR = 58, + COLOR_Luv2RGB = 59, + COLOR_HLS2BGR = 60, + COLOR_HLS2RGB = 61, + + COLOR_BGR2HSV_FULL = 66, + COLOR_RGB2HSV_FULL = 67, + COLOR_BGR2HLS_FULL = 68, + COLOR_RGB2HLS_FULL = 69, + + COLOR_HSV2BGR_FULL = 70, + COLOR_HSV2RGB_FULL = 71, + COLOR_HLS2BGR_FULL = 72, + COLOR_HLS2RGB_FULL = 73, + + COLOR_LBGR2Lab = 74, + COLOR_LRGB2Lab = 75, + COLOR_LBGR2Luv = 76, + COLOR_LRGB2Luv = 77, + + COLOR_Lab2LBGR = 78, + COLOR_Lab2LRGB = 79, + COLOR_Luv2LBGR = 80, + COLOR_Luv2LRGB = 81, + + COLOR_BGR2YUV = 82, //!< convert between RGB/BGR and YUV + COLOR_RGB2YUV = 83, + COLOR_YUV2BGR = 84, + COLOR_YUV2RGB = 85, + + //! YUV 4:2:0 family to RGB + COLOR_YUV2RGB_NV12 = 90, + COLOR_YUV2BGR_NV12 = 91, + COLOR_YUV2RGB_NV21 = 92, + COLOR_YUV2BGR_NV21 = 93, + COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21, + COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21, + + COLOR_YUV2RGBA_NV12 = 94, + COLOR_YUV2BGRA_NV12 = 95, + COLOR_YUV2RGBA_NV21 = 96, + COLOR_YUV2BGRA_NV21 = 97, + COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21, + COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21, + + COLOR_YUV2RGB_YV12 = 98, + COLOR_YUV2BGR_YV12 = 99, + COLOR_YUV2RGB_IYUV = 100, + COLOR_YUV2BGR_IYUV = 101, + COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV, + COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV, + COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12, + COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12, + + COLOR_YUV2RGBA_YV12 = 102, + COLOR_YUV2BGRA_YV12 = 103, + COLOR_YUV2RGBA_IYUV = 104, + COLOR_YUV2BGRA_IYUV = 105, + COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV, + COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV, + COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12, + COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12, + + COLOR_YUV2GRAY_420 = 106, + COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420, + COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420, + COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420, + COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420, + COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420, + COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420, + COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420, + + //! YUV 4:2:2 family to RGB + COLOR_YUV2RGB_UYVY = 107, + COLOR_YUV2BGR_UYVY = 108, + //COLOR_YUV2RGB_VYUY = 109, + //COLOR_YUV2BGR_VYUY = 110, + COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY, + COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY, + COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY, + COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY, + + COLOR_YUV2RGBA_UYVY = 111, + COLOR_YUV2BGRA_UYVY = 112, + //COLOR_YUV2RGBA_VYUY = 113, + //COLOR_YUV2BGRA_VYUY = 114, + COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY, + COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY, + COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY, + COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY, + + COLOR_YUV2RGB_YUY2 = 115, + COLOR_YUV2BGR_YUY2 = 116, + COLOR_YUV2RGB_YVYU = 117, + COLOR_YUV2BGR_YVYU = 118, + COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2, + COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2, + COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2, + COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2, + + COLOR_YUV2RGBA_YUY2 = 119, + COLOR_YUV2BGRA_YUY2 = 120, + COLOR_YUV2RGBA_YVYU = 121, + COLOR_YUV2BGRA_YVYU = 122, + COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2, + COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2, + COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2, + COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2, + + COLOR_YUV2GRAY_UYVY = 123, + COLOR_YUV2GRAY_YUY2 = 124, + //CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY, + COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY, + COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY, + COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2, + COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2, + COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2, + + //! alpha premultiplication + COLOR_RGBA2mRGBA = 125, + COLOR_mRGBA2RGBA = 126, + + //! RGB to YUV 4:2:0 family + COLOR_RGB2YUV_I420 = 127, + COLOR_BGR2YUV_I420 = 128, + COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420, + COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420, + + COLOR_RGBA2YUV_I420 = 129, + COLOR_BGRA2YUV_I420 = 130, + COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420, + COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420, + COLOR_RGB2YUV_YV12 = 131, + COLOR_BGR2YUV_YV12 = 132, + COLOR_RGBA2YUV_YV12 = 133, + COLOR_BGRA2YUV_YV12 = 134, + + //! Demosaicing + COLOR_BayerBG2BGR = 46, + COLOR_BayerGB2BGR = 47, + COLOR_BayerRG2BGR = 48, + COLOR_BayerGR2BGR = 49, + + COLOR_BayerBG2RGB = COLOR_BayerRG2BGR, + COLOR_BayerGB2RGB = COLOR_BayerGR2BGR, + COLOR_BayerRG2RGB = COLOR_BayerBG2BGR, + COLOR_BayerGR2RGB = COLOR_BayerGB2BGR, + + COLOR_BayerBG2GRAY = 86, + COLOR_BayerGB2GRAY = 87, + COLOR_BayerRG2GRAY = 88, + COLOR_BayerGR2GRAY = 89, + + //! Demosaicing using Variable Number of Gradients + COLOR_BayerBG2BGR_VNG = 62, + COLOR_BayerGB2BGR_VNG = 63, + COLOR_BayerRG2BGR_VNG = 64, + COLOR_BayerGR2BGR_VNG = 65, + + COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG, + COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG, + COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG, + COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG, + + //! Edge-Aware Demosaicing + COLOR_BayerBG2BGR_EA = 135, + COLOR_BayerGB2BGR_EA = 136, + COLOR_BayerRG2BGR_EA = 137, + COLOR_BayerGR2BGR_EA = 138, + + COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA, + COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA, + COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA, + COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA, + + //! Demosaicing with alpha channel + COLOR_BayerBG2BGRA = 139, + COLOR_BayerGB2BGRA = 140, + COLOR_BayerRG2BGRA = 141, + COLOR_BayerGR2BGRA = 142, + + COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA, + COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA, + COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA, + COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA, + + COLOR_COLORCVT_MAX = 143 +}; + +//! @addtogroup imgproc_shape +//! @{ + +//! types of intersection between rectangles +enum RectanglesIntersectTypes { + INTERSECT_NONE = 0, //!< No intersection + INTERSECT_PARTIAL = 1, //!< There is a partial intersection + INTERSECT_FULL = 2 //!< One of the rectangle is fully enclosed in the other +}; + +/** @brief finds arbitrary template in the grayscale image using Generalized Hough Transform +*/ +class CV_EXPORTS GeneralizedHough : public Algorithm +{ +public: + //! set template to search + virtual void setTemplate(InputArray templ, Point templCenter = Point(-1, -1)) = 0; + virtual void setTemplate(InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1)) = 0; + + //! find template on image + virtual void detect(InputArray image, OutputArray positions, OutputArray votes = noArray()) = 0; + virtual void detect(InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = noArray()) = 0; + + //! Canny low threshold. + virtual void setCannyLowThresh(int cannyLowThresh) = 0; + virtual int getCannyLowThresh() const = 0; + + //! Canny high threshold. + virtual void setCannyHighThresh(int cannyHighThresh) = 0; + virtual int getCannyHighThresh() const = 0; + + //! Minimum distance between the centers of the detected objects. + virtual void setMinDist(double minDist) = 0; + virtual double getMinDist() const = 0; + + //! Inverse ratio of the accumulator resolution to the image resolution. + virtual void setDp(double dp) = 0; + virtual double getDp() const = 0; + + //! Maximal size of inner buffers. + virtual void setMaxBufferSize(int maxBufferSize) = 0; + virtual int getMaxBufferSize() const = 0; +}; + +/** @brief finds arbitrary template in the grayscale image using Generalized Hough Transform + +Detects position only without translation and rotation @cite Ballard1981 . +*/ +class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough +{ +public: + //! R-Table levels. + virtual void setLevels(int levels) = 0; + virtual int getLevels() const = 0; + + //! The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected. + virtual void setVotesThreshold(int votesThreshold) = 0; + virtual int getVotesThreshold() const = 0; +}; + +/** @brief finds arbitrary template in the grayscale image using Generalized Hough Transform + +Detects position, translation and rotation @cite Guil1999 . +*/ +class CV_EXPORTS GeneralizedHoughGuil : public GeneralizedHough +{ +public: + //! Angle difference in degrees between two points in feature. + virtual void setXi(double xi) = 0; + virtual double getXi() const = 0; + + //! Feature table levels. + virtual void setLevels(int levels) = 0; + virtual int getLevels() const = 0; + + //! Maximal difference between angles that treated as equal. + virtual void setAngleEpsilon(double angleEpsilon) = 0; + virtual double getAngleEpsilon() const = 0; + + //! Minimal rotation angle to detect in degrees. + virtual void setMinAngle(double minAngle) = 0; + virtual double getMinAngle() const = 0; + + //! Maximal rotation angle to detect in degrees. + virtual void setMaxAngle(double maxAngle) = 0; + virtual double getMaxAngle() const = 0; + + //! Angle step in degrees. + virtual void setAngleStep(double angleStep) = 0; + virtual double getAngleStep() const = 0; + + //! Angle votes threshold. + virtual void setAngleThresh(int angleThresh) = 0; + virtual int getAngleThresh() const = 0; + + //! Minimal scale to detect. + virtual void setMinScale(double minScale) = 0; + virtual double getMinScale() const = 0; + + //! Maximal scale to detect. + virtual void setMaxScale(double maxScale) = 0; + virtual double getMaxScale() const = 0; + + //! Scale step. + virtual void setScaleStep(double scaleStep) = 0; + virtual double getScaleStep() const = 0; + + //! Scale votes threshold. + virtual void setScaleThresh(int scaleThresh) = 0; + virtual int getScaleThresh() const = 0; + + //! Position votes threshold. + virtual void setPosThresh(int posThresh) = 0; + virtual int getPosThresh() const = 0; +}; + +//! @} imgproc_shape + +//! @addtogroup imgproc_hist +//! @{ + +/** @brief Base class for Contrast Limited Adaptive Histogram Equalization. +*/ +class CV_EXPORTS_W CLAHE : public Algorithm +{ +public: + /** @brief Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram Equalization. + + @param src Source image of type CV_8UC1 or CV_16UC1. + @param dst Destination image. + */ + CV_WRAP virtual void apply(InputArray src, OutputArray dst) = 0; + + /** @brief Sets threshold for contrast limiting. + + @param clipLimit threshold value. + */ + CV_WRAP virtual void setClipLimit(double clipLimit) = 0; + + //! Returns threshold value for contrast limiting. + CV_WRAP virtual double getClipLimit() const = 0; + + /** @brief Sets size of grid for histogram equalization. Input image will be divided into + equally sized rectangular tiles. + + @param tileGridSize defines the number of tiles in row and column. + */ + CV_WRAP virtual void setTilesGridSize(Size tileGridSize) = 0; + + //!@brief Returns Size defines the number of tiles in row and column. + CV_WRAP virtual Size getTilesGridSize() const = 0; + + CV_WRAP virtual void collectGarbage() = 0; +}; + +//! @} imgproc_hist + +//! @addtogroup imgproc_subdiv2d +//! @{ + +class CV_EXPORTS_W Subdiv2D +{ +public: + /** Subdiv2D point location cases */ + enum { PTLOC_ERROR = -2, //!< Point location error + PTLOC_OUTSIDE_RECT = -1, //!< Point outside the subdivision bounding rect + PTLOC_INSIDE = 0, //!< Point inside some facet + PTLOC_VERTEX = 1, //!< Point coincides with one of the subdivision vertices + PTLOC_ON_EDGE = 2 //!< Point on some edge + }; + + /** Subdiv2D edge type navigation (see: getEdge()) */ + enum { NEXT_AROUND_ORG = 0x00, + NEXT_AROUND_DST = 0x22, + PREV_AROUND_ORG = 0x11, + PREV_AROUND_DST = 0x33, + NEXT_AROUND_LEFT = 0x13, + NEXT_AROUND_RIGHT = 0x31, + PREV_AROUND_LEFT = 0x20, + PREV_AROUND_RIGHT = 0x02 + }; + + /** creates an empty Subdiv2D object. + To create a new empty Delaunay subdivision you need to use the #initDelaunay function. + */ + CV_WRAP Subdiv2D(); + + /** @overload + + @param rect Rectangle that includes all of the 2D points that are to be added to the subdivision. + + The function creates an empty Delaunay subdivision where 2D points can be added using the function + insert() . All of the points to be added must be within the specified rectangle, otherwise a runtime + error is raised. + */ + CV_WRAP Subdiv2D(Rect rect); + + /** @brief Creates a new empty Delaunay subdivision + + @param rect Rectangle that includes all of the 2D points that are to be added to the subdivision. + + */ + CV_WRAP void initDelaunay(Rect rect); + + /** @brief Insert a single point into a Delaunay triangulation. + + @param pt Point to insert. + + The function inserts a single point into a subdivision and modifies the subdivision topology + appropriately. If a point with the same coordinates exists already, no new point is added. + @returns the ID of the point. + + @note If the point is outside of the triangulation specified rect a runtime error is raised. + */ + CV_WRAP int insert(Point2f pt); + + /** @brief Insert multiple points into a Delaunay triangulation. + + @param ptvec Points to insert. + + The function inserts a vector of points into a subdivision and modifies the subdivision topology + appropriately. + */ + CV_WRAP void insert(const std::vector& ptvec); + + /** @brief Returns the location of a point within a Delaunay triangulation. + + @param pt Point to locate. + @param edge Output edge that the point belongs to or is located to the right of it. + @param vertex Optional output vertex the input point coincides with. + + The function locates the input point within the subdivision and gives one of the triangle edges + or vertices. + + @returns an integer which specify one of the following five cases for point location: + - The point falls into some facet. The function returns #PTLOC_INSIDE and edge will contain one of + edges of the facet. + - The point falls onto the edge. The function returns #PTLOC_ON_EDGE and edge will contain this edge. + - The point coincides with one of the subdivision vertices. The function returns #PTLOC_VERTEX and + vertex will contain a pointer to the vertex. + - The point is outside the subdivision reference rectangle. The function returns #PTLOC_OUTSIDE_RECT + and no pointers are filled. + - One of input arguments is invalid. A runtime error is raised or, if silent or "parent" error + processing mode is selected, #PTLOC_ERROR is returned. + */ + CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex); + + /** @brief Finds the subdivision vertex closest to the given point. + + @param pt Input point. + @param nearestPt Output subdivision vertex point. + + The function is another function that locates the input point within the subdivision. It finds the + subdivision vertex that is the closest to the input point. It is not necessarily one of vertices + of the facet containing the input point, though the facet (located using locate() ) is used as a + starting point. + + @returns vertex ID. + */ + CV_WRAP int findNearest(Point2f pt, CV_OUT Point2f* nearestPt = 0); + + /** @brief Returns a list of all edges. + + @param edgeList Output vector. + + The function gives each edge as a 4 numbers vector, where each two are one of the edge + vertices. i.e. org_x = v[0], org_y = v[1], dst_x = v[2], dst_y = v[3]. + */ + CV_WRAP void getEdgeList(CV_OUT std::vector& edgeList) const; + + /** @brief Returns a list of the leading edge ID connected to each triangle. + + @param leadingEdgeList Output vector. + + The function gives one edge ID for each triangle. + */ + CV_WRAP void getLeadingEdgeList(CV_OUT std::vector& leadingEdgeList) const; + + /** @brief Returns a list of all triangles. + + @param triangleList Output vector. + + The function gives each triangle as a 6 numbers vector, where each two are one of the triangle + vertices. i.e. p1_x = v[0], p1_y = v[1], p2_x = v[2], p2_y = v[3], p3_x = v[4], p3_y = v[5]. + */ + CV_WRAP void getTriangleList(CV_OUT std::vector& triangleList) const; + + /** @brief Returns a list of all Voroni facets. + + @param idx Vector of vertices IDs to consider. For all vertices you can pass empty vector. + @param facetList Output vector of the Voroni facets. + @param facetCenters Output vector of the Voroni facets center points. + + */ + CV_WRAP void getVoronoiFacetList(const std::vector& idx, CV_OUT std::vector >& facetList, + CV_OUT std::vector& facetCenters); + + /** @brief Returns vertex location from vertex ID. + + @param vertex vertex ID. + @param firstEdge Optional. The first edge ID which is connected to the vertex. + @returns vertex (x,y) + + */ + CV_WRAP Point2f getVertex(int vertex, CV_OUT int* firstEdge = 0) const; + + /** @brief Returns one of the edges related to the given edge. + + @param edge Subdivision edge ID. + @param nextEdgeType Parameter specifying which of the related edges to return. + The following values are possible: + - NEXT_AROUND_ORG next around the edge origin ( eOnext on the picture below if e is the input edge) + - NEXT_AROUND_DST next around the edge vertex ( eDnext ) + - PREV_AROUND_ORG previous around the edge origin (reversed eRnext ) + - PREV_AROUND_DST previous around the edge destination (reversed eLnext ) + - NEXT_AROUND_LEFT next around the left facet ( eLnext ) + - NEXT_AROUND_RIGHT next around the right facet ( eRnext ) + - PREV_AROUND_LEFT previous around the left facet (reversed eOnext ) + - PREV_AROUND_RIGHT previous around the right facet (reversed eDnext ) + + ![sample output](pics/quadedge.png) + + @returns edge ID related to the input edge. + */ + CV_WRAP int getEdge( int edge, int nextEdgeType ) const; + + /** @brief Returns next edge around the edge origin. + + @param edge Subdivision edge ID. + + @returns an integer which is next edge ID around the edge origin: eOnext on the + picture above if e is the input edge). + */ + CV_WRAP int nextEdge(int edge) const; + + /** @brief Returns another edge of the same quad-edge. + + @param edge Subdivision edge ID. + @param rotate Parameter specifying which of the edges of the same quad-edge as the input + one to return. The following values are possible: + - 0 - the input edge ( e on the picture below if e is the input edge) + - 1 - the rotated edge ( eRot ) + - 2 - the reversed edge (reversed e (in green)) + - 3 - the reversed rotated edge (reversed eRot (in green)) + + @returns one of the edges ID of the same quad-edge as the input edge. + */ + CV_WRAP int rotateEdge(int edge, int rotate) const; + CV_WRAP int symEdge(int edge) const; + + /** @brief Returns the edge origin. + + @param edge Subdivision edge ID. + @param orgpt Output vertex location. + + @returns vertex ID. + */ + CV_WRAP int edgeOrg(int edge, CV_OUT Point2f* orgpt = 0) const; + + /** @brief Returns the edge destination. + + @param edge Subdivision edge ID. + @param dstpt Output vertex location. + + @returns vertex ID. + */ + CV_WRAP int edgeDst(int edge, CV_OUT Point2f* dstpt = 0) const; + +protected: + int newEdge(); + void deleteEdge(int edge); + int newPoint(Point2f pt, bool isvirtual, int firstEdge = 0); + void deletePoint(int vtx); + void setEdgePoints( int edge, int orgPt, int dstPt ); + void splice( int edgeA, int edgeB ); + int connectEdges( int edgeA, int edgeB ); + void swapEdges( int edge ); + int isRightOf(Point2f pt, int edge) const; + void calcVoronoi(); + void clearVoronoi(); + void checkSubdiv() const; + + struct CV_EXPORTS Vertex + { + Vertex(); + Vertex(Point2f pt, bool _isvirtual, int _firstEdge=0); + bool isvirtual() const; + bool isfree() const; + + int firstEdge; + int type; + Point2f pt; + }; + + struct CV_EXPORTS QuadEdge + { + QuadEdge(); + QuadEdge(int edgeidx); + bool isfree() const; + + int next[4]; + int pt[4]; + }; + + //! All of the vertices + std::vector vtx; + //! All of the edges + std::vector qedges; + int freeQEdge; + int freePoint; + bool validGeometry; + + int recentEdge; + //! Top left corner of the bounding rect + Point2f topLeft; + //! Bottom right corner of the bounding rect + Point2f bottomRight; +}; + +//! @} imgproc_subdiv2d + +//! @addtogroup imgproc_feature +//! @{ + +/** @brief Line segment detector class + +following the algorithm described at @cite Rafael12 . + +@note Implementation has been removed due original code license conflict + +*/ +class CV_EXPORTS_W LineSegmentDetector : public Algorithm +{ +public: + + /** @brief Finds lines in the input image. + + This is the output of the default parameters of the algorithm on the above shown image. + + ![image](pics/building_lsd.png) + + @param _image A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: + `lsd_ptr-\>detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);` + @param _lines A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where + Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly + oriented depending on the gradient. + @param width Vector of widths of the regions, where the lines are found. E.g. Width of line. + @param prec Vector of precisions with which the lines are found. + @param nfa Vector containing number of false alarms in the line region, with precision of 10%. The + bigger the value, logarithmically better the detection. + - -1 corresponds to 10 mean false alarms + - 0 corresponds to 1 mean false alarm + - 1 corresponds to 0.1 mean false alarms + This vector will be calculated only when the objects type is #LSD_REFINE_ADV. + */ + CV_WRAP virtual void detect(InputArray _image, OutputArray _lines, + OutputArray width = noArray(), OutputArray prec = noArray(), + OutputArray nfa = noArray()) = 0; + + /** @brief Draws the line segments on a given image. + @param _image The image, where the lines will be drawn. Should be bigger or equal to the image, + where the lines were found. + @param lines A vector of the lines that needed to be drawn. + */ + CV_WRAP virtual void drawSegments(InputOutputArray _image, InputArray lines) = 0; + + /** @brief Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels. + + @param size The size of the image, where lines1 and lines2 were found. + @param lines1 The first group of lines that needs to be drawn. It is visualized in blue color. + @param lines2 The second group of lines. They visualized in red color. + @param _image Optional image, where the lines will be drawn. The image should be color(3-channel) + in order for lines1 and lines2 to be drawn in the above mentioned colors. + */ + CV_WRAP virtual int compareSegments(const Size& size, InputArray lines1, InputArray lines2, InputOutputArray _image = noArray()) = 0; + + virtual ~LineSegmentDetector() { } +}; + +/** @brief Creates a smart pointer to a LineSegmentDetector object and initializes it. + +The LineSegmentDetector algorithm is defined using the standard values. Only advanced users may want +to edit those, as to tailor it for their own application. + +@param _refine The way found lines will be refined, see #LineSegmentDetectorModes +@param _scale The scale of the image that will be used to find the lines. Range (0..1]. +@param _sigma_scale Sigma for Gaussian filter. It is computed as sigma = _sigma_scale/_scale. +@param _quant Bound to the quantization error on the gradient norm. +@param _ang_th Gradient angle tolerance in degrees. +@param _log_eps Detection threshold: -log10(NFA) \> log_eps. Used only when advance refinement +is chosen. +@param _density_th Minimal density of aligned region points in the enclosing rectangle. +@param _n_bins Number of bins in pseudo-ordering of gradient modulus. + +@note Implementation has been removed due original code license conflict + */ +CV_EXPORTS_W Ptr createLineSegmentDetector( + int _refine = LSD_REFINE_STD, double _scale = 0.8, + double _sigma_scale = 0.6, double _quant = 2.0, double _ang_th = 22.5, + double _log_eps = 0, double _density_th = 0.7, int _n_bins = 1024); + +//! @} imgproc_feature + +//! @addtogroup imgproc_filter +//! @{ + +/** @brief Returns Gaussian filter coefficients. + +The function computes and returns the \f$\texttt{ksize} \times 1\f$ matrix of Gaussian filter +coefficients: + +\f[G_i= \alpha *e^{-(i-( \texttt{ksize} -1)/2)^2/(2* \texttt{sigma}^2)},\f] + +where \f$i=0..\texttt{ksize}-1\f$ and \f$\alpha\f$ is the scale factor chosen so that \f$\sum_i G_i=1\f$. + +Two of such generated kernels can be passed to sepFilter2D. Those functions automatically recognize +smoothing kernels (a symmetrical kernel with sum of weights equal to 1) and handle them accordingly. +You may also use the higher-level GaussianBlur. +@param ksize Aperture size. It should be odd ( \f$\texttt{ksize} \mod 2 = 1\f$ ) and positive. +@param sigma Gaussian standard deviation. If it is non-positive, it is computed from ksize as +`sigma = 0.3*((ksize-1)*0.5 - 1) + 0.8`. +@param ktype Type of filter coefficients. It can be CV_32F or CV_64F . +@sa sepFilter2D, getDerivKernels, getStructuringElement, GaussianBlur + */ +CV_EXPORTS_W Mat getGaussianKernel( int ksize, double sigma, int ktype = CV_64F ); + +/** @brief Returns filter coefficients for computing spatial image derivatives. + +The function computes and returns the filter coefficients for spatial image derivatives. When +`ksize=CV_SCHARR`, the Scharr \f$3 \times 3\f$ kernels are generated (see #Scharr). Otherwise, Sobel +kernels are generated (see #Sobel). The filters are normally passed to #sepFilter2D or to + +@param kx Output matrix of row filter coefficients. It has the type ktype . +@param ky Output matrix of column filter coefficients. It has the type ktype . +@param dx Derivative order in respect of x. +@param dy Derivative order in respect of y. +@param ksize Aperture size. It can be CV_SCHARR, 1, 3, 5, or 7. +@param normalize Flag indicating whether to normalize (scale down) the filter coefficients or not. +Theoretically, the coefficients should have the denominator \f$=2^{ksize*2-dx-dy-2}\f$. If you are +going to filter floating-point images, you are likely to use the normalized kernels. But if you +compute derivatives of an 8-bit image, store the results in a 16-bit image, and wish to preserve +all the fractional bits, you may want to set normalize=false . +@param ktype Type of filter coefficients. It can be CV_32f or CV_64F . + */ +CV_EXPORTS_W void getDerivKernels( OutputArray kx, OutputArray ky, + int dx, int dy, int ksize, + bool normalize = false, int ktype = CV_32F ); + +/** @brief Returns Gabor filter coefficients. + +For more details about gabor filter equations and parameters, see: [Gabor +Filter](http://en.wikipedia.org/wiki/Gabor_filter). + +@param ksize Size of the filter returned. +@param sigma Standard deviation of the gaussian envelope. +@param theta Orientation of the normal to the parallel stripes of a Gabor function. +@param lambd Wavelength of the sinusoidal factor. +@param gamma Spatial aspect ratio. +@param psi Phase offset. +@param ktype Type of filter coefficients. It can be CV_32F or CV_64F . + */ +CV_EXPORTS_W Mat getGaborKernel( Size ksize, double sigma, double theta, double lambd, + double gamma, double psi = CV_PI*0.5, int ktype = CV_64F ); + +//! returns "magic" border value for erosion and dilation. It is automatically transformed to Scalar::all(-DBL_MAX) for dilation. +static inline Scalar morphologyDefaultBorderValue() { return Scalar::all(DBL_MAX); } + +/** @brief Returns a structuring element of the specified size and shape for morphological operations. + +The function constructs and returns the structuring element that can be further passed to #erode, +#dilate or #morphologyEx. But you can also construct an arbitrary binary mask yourself and use it as +the structuring element. + +@param shape Element shape that could be one of #MorphShapes +@param ksize Size of the structuring element. +@param anchor Anchor position within the element. The default value \f$(-1, -1)\f$ means that the +anchor is at the center. Note that only the shape of a cross-shaped element depends on the anchor +position. In other cases the anchor just regulates how much the result of the morphological +operation is shifted. + */ +CV_EXPORTS_W Mat getStructuringElement(int shape, Size ksize, Point anchor = Point(-1,-1)); + +/** @example samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp +Sample code for simple filters +![Sample screenshot](Smoothing_Tutorial_Result_Median_Filter.jpg) +Check @ref tutorial_gausian_median_blur_bilateral_filter "the corresponding tutorial" for more details + */ + +/** @brief Blurs an image using the median filter. + +The function smoothes an image using the median filter with the \f$\texttt{ksize} \times +\texttt{ksize}\f$ aperture. Each channel of a multi-channel image is processed independently. +In-place operation is supported. + +@note The median filter uses #BORDER_REPLICATE internally to cope with border pixels, see #BorderTypes + +@param src input 1-, 3-, or 4-channel image; when ksize is 3 or 5, the image depth should be +CV_8U, CV_16U, or CV_32F, for larger aperture sizes, it can only be CV_8U. +@param dst destination array of the same size and type as src. +@param ksize aperture linear size; it must be odd and greater than 1, for example: 3, 5, 7 ... +@sa bilateralFilter, blur, boxFilter, GaussianBlur + */ +CV_EXPORTS_W void medianBlur( InputArray src, OutputArray dst, int ksize ); + +/** @brief Blurs an image using a Gaussian filter. + +The function convolves the source image with the specified Gaussian kernel. In-place filtering is +supported. + +@param src input image; the image can have any number of channels, which are processed +independently, but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. +@param dst output image of the same size and type as src. +@param ksize Gaussian kernel size. ksize.width and ksize.height can differ but they both must be +positive and odd. Or, they can be zero's and then they are computed from sigma. +@param sigmaX Gaussian kernel standard deviation in X direction. +@param sigmaY Gaussian kernel standard deviation in Y direction; if sigmaY is zero, it is set to be +equal to sigmaX, if both sigmas are zeros, they are computed from ksize.width and ksize.height, +respectively (see #getGaussianKernel for details); to fully control the result regardless of +possible future modifications of all this semantics, it is recommended to specify all of ksize, +sigmaX, and sigmaY. +@param borderType pixel extrapolation method, see #BorderTypes + +@sa sepFilter2D, filter2D, blur, boxFilter, bilateralFilter, medianBlur + */ +CV_EXPORTS_W void GaussianBlur( InputArray src, OutputArray dst, Size ksize, + double sigmaX, double sigmaY = 0, + int borderType = BORDER_DEFAULT ); + +/** @brief Applies the bilateral filter to an image. + +The function applies bilateral filtering to the input image, as described in +http://www.dai.ed.ac.uk/CVonline/LOCAL_COPIES/MANDUCHI1/Bilateral_Filtering.html +bilateralFilter can reduce unwanted noise very well while keeping edges fairly sharp. However, it is +very slow compared to most filters. + +_Sigma values_: For simplicity, you can set the 2 sigma values to be the same. If they are small (\< +10), the filter will not have much effect, whereas if they are large (\> 150), they will have a very +strong effect, making the image look "cartoonish". + +_Filter size_: Large filters (d \> 5) are very slow, so it is recommended to use d=5 for real-time +applications, and perhaps d=9 for offline applications that need heavy noise filtering. + +This filter does not work inplace. +@param src Source 8-bit or floating-point, 1-channel or 3-channel image. +@param dst Destination image of the same size and type as src . +@param d Diameter of each pixel neighborhood that is used during filtering. If it is non-positive, +it is computed from sigmaSpace. +@param sigmaColor Filter sigma in the color space. A larger value of the parameter means that +farther colors within the pixel neighborhood (see sigmaSpace) will be mixed together, resulting +in larger areas of semi-equal color. +@param sigmaSpace Filter sigma in the coordinate space. A larger value of the parameter means that +farther pixels will influence each other as long as their colors are close enough (see sigmaColor +). When d\>0, it specifies the neighborhood size regardless of sigmaSpace. Otherwise, d is +proportional to sigmaSpace. +@param borderType border mode used to extrapolate pixels outside of the image, see #BorderTypes + */ +CV_EXPORTS_W void bilateralFilter( InputArray src, OutputArray dst, int d, + double sigmaColor, double sigmaSpace, + int borderType = BORDER_DEFAULT ); + +/** @brief Blurs an image using the box filter. + +The function smooths an image using the kernel: + +\f[\texttt{K} = \alpha \begin{bmatrix} 1 & 1 & 1 & \cdots & 1 & 1 \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \hdotsfor{6} \\ 1 & 1 & 1 & \cdots & 1 & 1 \end{bmatrix}\f] + +where + +\f[\alpha = \fork{\frac{1}{\texttt{ksize.width*ksize.height}}}{when \texttt{normalize=true}}{1}{otherwise}\f] + +Unnormalized box filter is useful for computing various integral characteristics over each pixel +neighborhood, such as covariance matrices of image derivatives (used in dense optical flow +algorithms, and so on). If you need to compute pixel sums over variable-size windows, use #integral. + +@param src input image. +@param dst output image of the same size and type as src. +@param ddepth the output image depth (-1 to use src.depth()). +@param ksize blurring kernel size. +@param anchor anchor point; default value Point(-1,-1) means that the anchor is at the kernel +center. +@param normalize flag, specifying whether the kernel is normalized by its area or not. +@param borderType border mode used to extrapolate pixels outside of the image, see #BorderTypes +@sa blur, bilateralFilter, GaussianBlur, medianBlur, integral + */ +CV_EXPORTS_W void boxFilter( InputArray src, OutputArray dst, int ddepth, + Size ksize, Point anchor = Point(-1,-1), + bool normalize = true, + int borderType = BORDER_DEFAULT ); + +/** @brief Calculates the normalized sum of squares of the pixel values overlapping the filter. + +For every pixel \f$ (x, y) \f$ in the source image, the function calculates the sum of squares of those neighboring +pixel values which overlap the filter placed over the pixel \f$ (x, y) \f$. + +The unnormalized square box filter can be useful in computing local image statistics such as the the local +variance and standard deviation around the neighborhood of a pixel. + +@param src input image +@param dst output image of the same size and type as _src +@param ddepth the output image depth (-1 to use src.depth()) +@param ksize kernel size +@param anchor kernel anchor point. The default value of Point(-1, -1) denotes that the anchor is at the kernel +center. +@param normalize flag, specifying whether the kernel is to be normalized by it's area or not. +@param borderType border mode used to extrapolate pixels outside of the image, see #BorderTypes +@sa boxFilter +*/ +CV_EXPORTS_W void sqrBoxFilter( InputArray src, OutputArray dst, int ddepth, + Size ksize, Point anchor = Point(-1, -1), + bool normalize = true, + int borderType = BORDER_DEFAULT ); + +/** @brief Blurs an image using the normalized box filter. + +The function smooths an image using the kernel: + +\f[\texttt{K} = \frac{1}{\texttt{ksize.width*ksize.height}} \begin{bmatrix} 1 & 1 & 1 & \cdots & 1 & 1 \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \hdotsfor{6} \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \end{bmatrix}\f] + +The call `blur(src, dst, ksize, anchor, borderType)` is equivalent to `boxFilter(src, dst, src.type(), +anchor, true, borderType)`. + +@param src input image; it can have any number of channels, which are processed independently, but +the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. +@param dst output image of the same size and type as src. +@param ksize blurring kernel size. +@param anchor anchor point; default value Point(-1,-1) means that the anchor is at the kernel +center. +@param borderType border mode used to extrapolate pixels outside of the image, see #BorderTypes +@sa boxFilter, bilateralFilter, GaussianBlur, medianBlur + */ +CV_EXPORTS_W void blur( InputArray src, OutputArray dst, + Size ksize, Point anchor = Point(-1,-1), + int borderType = BORDER_DEFAULT ); + +/** @brief Convolves an image with the kernel. + +The function applies an arbitrary linear filter to an image. In-place operation is supported. When +the aperture is partially outside the image, the function interpolates outlier pixel values +according to the specified border mode. + +The function does actually compute correlation, not the convolution: + +\f[\texttt{dst} (x,y) = \sum _{ \stackrel{0\leq x' < \texttt{kernel.cols},}{0\leq y' < \texttt{kernel.rows}} } \texttt{kernel} (x',y')* \texttt{src} (x+x'- \texttt{anchor.x} ,y+y'- \texttt{anchor.y} )\f] + +That is, the kernel is not mirrored around the anchor point. If you need a real convolution, flip +the kernel using #flip and set the new anchor to `(kernel.cols - anchor.x - 1, kernel.rows - +anchor.y - 1)`. + +The function uses the DFT-based algorithm in case of sufficiently large kernels (~`11 x 11` or +larger) and the direct algorithm for small kernels. + +@param src input image. +@param dst output image of the same size and the same number of channels as src. +@param ddepth desired depth of the destination image, see @ref filter_depths "combinations" +@param kernel convolution kernel (or rather a correlation kernel), a single-channel floating point +matrix; if you want to apply different kernels to different channels, split the image into +separate color planes using split and process them individually. +@param anchor anchor of the kernel that indicates the relative position of a filtered point within +the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor +is at the kernel center. +@param delta optional value added to the filtered pixels before storing them in dst. +@param borderType pixel extrapolation method, see #BorderTypes +@sa sepFilter2D, dft, matchTemplate + */ +CV_EXPORTS_W void filter2D( InputArray src, OutputArray dst, int ddepth, + InputArray kernel, Point anchor = Point(-1,-1), + double delta = 0, int borderType = BORDER_DEFAULT ); + +/** @brief Applies a separable linear filter to an image. + +The function applies a separable linear filter to the image. That is, first, every row of src is +filtered with the 1D kernel kernelX. Then, every column of the result is filtered with the 1D +kernel kernelY. The final result shifted by delta is stored in dst . + +@param src Source image. +@param dst Destination image of the same size and the same number of channels as src . +@param ddepth Destination image depth, see @ref filter_depths "combinations" +@param kernelX Coefficients for filtering each row. +@param kernelY Coefficients for filtering each column. +@param anchor Anchor position within the kernel. The default value \f$(-1,-1)\f$ means that the anchor +is at the kernel center. +@param delta Value added to the filtered results before storing them. +@param borderType Pixel extrapolation method, see #BorderTypes +@sa filter2D, Sobel, GaussianBlur, boxFilter, blur + */ +CV_EXPORTS_W void sepFilter2D( InputArray src, OutputArray dst, int ddepth, + InputArray kernelX, InputArray kernelY, + Point anchor = Point(-1,-1), + double delta = 0, int borderType = BORDER_DEFAULT ); + +/** @example samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp +Sample code using Sobel and/or Scharr OpenCV functions to make a simple Edge Detector +![Sample screenshot](Sobel_Derivatives_Tutorial_Result.jpg) +Check @ref tutorial_sobel_derivatives "the corresponding tutorial" for more details +*/ + +/** @brief Calculates the first, second, third, or mixed image derivatives using an extended Sobel operator. + +In all cases except one, the \f$\texttt{ksize} \times \texttt{ksize}\f$ separable kernel is used to +calculate the derivative. When \f$\texttt{ksize = 1}\f$, the \f$3 \times 1\f$ or \f$1 \times 3\f$ +kernel is used (that is, no Gaussian smoothing is done). `ksize = 1` can only be used for the first +or the second x- or y- derivatives. + +There is also the special value `ksize = #CV_SCHARR (-1)` that corresponds to the \f$3\times3\f$ Scharr +filter that may give more accurate results than the \f$3\times3\f$ Sobel. The Scharr aperture is + +\f[\vecthreethree{-3}{0}{3}{-10}{0}{10}{-3}{0}{3}\f] + +for the x-derivative, or transposed for the y-derivative. + +The function calculates an image derivative by convolving the image with the appropriate kernel: + +\f[\texttt{dst} = \frac{\partial^{xorder+yorder} \texttt{src}}{\partial x^{xorder} \partial y^{yorder}}\f] + +The Sobel operators combine Gaussian smoothing and differentiation, so the result is more or less +resistant to the noise. Most often, the function is called with ( xorder = 1, yorder = 0, ksize = 3) +or ( xorder = 0, yorder = 1, ksize = 3) to calculate the first x- or y- image derivative. The first +case corresponds to a kernel of: + +\f[\vecthreethree{-1}{0}{1}{-2}{0}{2}{-1}{0}{1}\f] + +The second case corresponds to a kernel of: + +\f[\vecthreethree{-1}{-2}{-1}{0}{0}{0}{1}{2}{1}\f] + +@param src input image. +@param dst output image of the same size and the same number of channels as src . +@param ddepth output image depth, see @ref filter_depths "combinations"; in the case of + 8-bit input images it will result in truncated derivatives. +@param dx order of the derivative x. +@param dy order of the derivative y. +@param ksize size of the extended Sobel kernel; it must be 1, 3, 5, or 7. +@param scale optional scale factor for the computed derivative values; by default, no scaling is +applied (see #getDerivKernels for details). +@param delta optional delta value that is added to the results prior to storing them in dst. +@param borderType pixel extrapolation method, see #BorderTypes +@sa Scharr, Laplacian, sepFilter2D, filter2D, GaussianBlur, cartToPolar + */ +CV_EXPORTS_W void Sobel( InputArray src, OutputArray dst, int ddepth, + int dx, int dy, int ksize = 3, + double scale = 1, double delta = 0, + int borderType = BORDER_DEFAULT ); + +/** @brief Calculates the first order image derivative in both x and y using a Sobel operator + +Equivalent to calling: + +@code +Sobel( src, dx, CV_16SC1, 1, 0, 3 ); +Sobel( src, dy, CV_16SC1, 0, 1, 3 ); +@endcode + +@param src input image. +@param dx output image with first-order derivative in x. +@param dy output image with first-order derivative in y. +@param ksize size of Sobel kernel. It must be 3. +@param borderType pixel extrapolation method, see #BorderTypes + +@sa Sobel + */ + +CV_EXPORTS_W void spatialGradient( InputArray src, OutputArray dx, + OutputArray dy, int ksize = 3, + int borderType = BORDER_DEFAULT ); + +/** @brief Calculates the first x- or y- image derivative using Scharr operator. + +The function computes the first x- or y- spatial image derivative using the Scharr operator. The +call + +\f[\texttt{Scharr(src, dst, ddepth, dx, dy, scale, delta, borderType)}\f] + +is equivalent to + +\f[\texttt{Sobel(src, dst, ddepth, dx, dy, CV_SCHARR, scale, delta, borderType)} .\f] + +@param src input image. +@param dst output image of the same size and the same number of channels as src. +@param ddepth output image depth, see @ref filter_depths "combinations" +@param dx order of the derivative x. +@param dy order of the derivative y. +@param scale optional scale factor for the computed derivative values; by default, no scaling is +applied (see #getDerivKernels for details). +@param delta optional delta value that is added to the results prior to storing them in dst. +@param borderType pixel extrapolation method, see #BorderTypes +@sa cartToPolar + */ +CV_EXPORTS_W void Scharr( InputArray src, OutputArray dst, int ddepth, + int dx, int dy, double scale = 1, double delta = 0, + int borderType = BORDER_DEFAULT ); + +/** @example samples/cpp/laplace.cpp +An example using Laplace transformations for edge detection +*/ + +/** @brief Calculates the Laplacian of an image. + +The function calculates the Laplacian of the source image by adding up the second x and y +derivatives calculated using the Sobel operator: + +\f[\texttt{dst} = \Delta \texttt{src} = \frac{\partial^2 \texttt{src}}{\partial x^2} + \frac{\partial^2 \texttt{src}}{\partial y^2}\f] + +This is done when `ksize > 1`. When `ksize == 1`, the Laplacian is computed by filtering the image +with the following \f$3 \times 3\f$ aperture: + +\f[\vecthreethree {0}{1}{0}{1}{-4}{1}{0}{1}{0}\f] + +@param src Source image. +@param dst Destination image of the same size and the same number of channels as src . +@param ddepth Desired depth of the destination image. +@param ksize Aperture size used to compute the second-derivative filters. See #getDerivKernels for +details. The size must be positive and odd. +@param scale Optional scale factor for the computed Laplacian values. By default, no scaling is +applied. See #getDerivKernels for details. +@param delta Optional delta value that is added to the results prior to storing them in dst . +@param borderType Pixel extrapolation method, see #BorderTypes +@sa Sobel, Scharr + */ +CV_EXPORTS_W void Laplacian( InputArray src, OutputArray dst, int ddepth, + int ksize = 1, double scale = 1, double delta = 0, + int borderType = BORDER_DEFAULT ); + +//! @} imgproc_filter + +//! @addtogroup imgproc_feature +//! @{ + +/** @example samples/cpp/edge.cpp +This program demonstrates usage of the Canny edge detector + +Check @ref tutorial_canny_detector "the corresponding tutorial" for more details +*/ + +/** @brief Finds edges in an image using the Canny algorithm @cite Canny86 . + +The function finds edges in the input image and marks them in the output map edges using the +Canny algorithm. The smallest value between threshold1 and threshold2 is used for edge linking. The +largest value is used to find initial segments of strong edges. See + + +@param image 8-bit input image. +@param edges output edge map; single channels 8-bit image, which has the same size as image . +@param threshold1 first threshold for the hysteresis procedure. +@param threshold2 second threshold for the hysteresis procedure. +@param apertureSize aperture size for the Sobel operator. +@param L2gradient a flag, indicating whether a more accurate \f$L_2\f$ norm +\f$=\sqrt{(dI/dx)^2 + (dI/dy)^2}\f$ should be used to calculate the image gradient magnitude ( +L2gradient=true ), or whether the default \f$L_1\f$ norm \f$=|dI/dx|+|dI/dy|\f$ is enough ( +L2gradient=false ). + */ +CV_EXPORTS_W void Canny( InputArray image, OutputArray edges, + double threshold1, double threshold2, + int apertureSize = 3, bool L2gradient = false ); + +/** \overload + +Finds edges in an image using the Canny algorithm with custom image gradient. + +@param dx 16-bit x derivative of input image (CV_16SC1 or CV_16SC3). +@param dy 16-bit y derivative of input image (same type as dx). +@param edges output edge map; single channels 8-bit image, which has the same size as image . +@param threshold1 first threshold for the hysteresis procedure. +@param threshold2 second threshold for the hysteresis procedure. +@param L2gradient a flag, indicating whether a more accurate \f$L_2\f$ norm +\f$=\sqrt{(dI/dx)^2 + (dI/dy)^2}\f$ should be used to calculate the image gradient magnitude ( +L2gradient=true ), or whether the default \f$L_1\f$ norm \f$=|dI/dx|+|dI/dy|\f$ is enough ( +L2gradient=false ). + */ +CV_EXPORTS_W void Canny( InputArray dx, InputArray dy, + OutputArray edges, + double threshold1, double threshold2, + bool L2gradient = false ); + +/** @brief Calculates the minimal eigenvalue of gradient matrices for corner detection. + +The function is similar to cornerEigenValsAndVecs but it calculates and stores only the minimal +eigenvalue of the covariance matrix of derivatives, that is, \f$\min(\lambda_1, \lambda_2)\f$ in terms +of the formulae in the cornerEigenValsAndVecs description. + +@param src Input single-channel 8-bit or floating-point image. +@param dst Image to store the minimal eigenvalues. It has the type CV_32FC1 and the same size as +src . +@param blockSize Neighborhood size (see the details on #cornerEigenValsAndVecs ). +@param ksize Aperture parameter for the Sobel operator. +@param borderType Pixel extrapolation method. See #BorderTypes. + */ +CV_EXPORTS_W void cornerMinEigenVal( InputArray src, OutputArray dst, + int blockSize, int ksize = 3, + int borderType = BORDER_DEFAULT ); + +/** @brief Harris corner detector. + +The function runs the Harris corner detector on the image. Similarly to cornerMinEigenVal and +cornerEigenValsAndVecs , for each pixel \f$(x, y)\f$ it calculates a \f$2\times2\f$ gradient covariance +matrix \f$M^{(x,y)}\f$ over a \f$\texttt{blockSize} \times \texttt{blockSize}\f$ neighborhood. Then, it +computes the following characteristic: + +\f[\texttt{dst} (x,y) = \mathrm{det} M^{(x,y)} - k \cdot \left ( \mathrm{tr} M^{(x,y)} \right )^2\f] + +Corners in the image can be found as the local maxima of this response map. + +@param src Input single-channel 8-bit or floating-point image. +@param dst Image to store the Harris detector responses. It has the type CV_32FC1 and the same +size as src . +@param blockSize Neighborhood size (see the details on #cornerEigenValsAndVecs ). +@param ksize Aperture parameter for the Sobel operator. +@param k Harris detector free parameter. See the formula above. +@param borderType Pixel extrapolation method. See #BorderTypes. + */ +CV_EXPORTS_W void cornerHarris( InputArray src, OutputArray dst, int blockSize, + int ksize, double k, + int borderType = BORDER_DEFAULT ); + +/** @brief Calculates eigenvalues and eigenvectors of image blocks for corner detection. + +For every pixel \f$p\f$ , the function cornerEigenValsAndVecs considers a blockSize \f$\times\f$ blockSize +neighborhood \f$S(p)\f$ . It calculates the covariation matrix of derivatives over the neighborhood as: + +\f[M = \begin{bmatrix} \sum _{S(p)}(dI/dx)^2 & \sum _{S(p)}dI/dx dI/dy \\ \sum _{S(p)}dI/dx dI/dy & \sum _{S(p)}(dI/dy)^2 \end{bmatrix}\f] + +where the derivatives are computed using the Sobel operator. + +After that, it finds eigenvectors and eigenvalues of \f$M\f$ and stores them in the destination image as +\f$(\lambda_1, \lambda_2, x_1, y_1, x_2, y_2)\f$ where + +- \f$\lambda_1, \lambda_2\f$ are the non-sorted eigenvalues of \f$M\f$ +- \f$x_1, y_1\f$ are the eigenvectors corresponding to \f$\lambda_1\f$ +- \f$x_2, y_2\f$ are the eigenvectors corresponding to \f$\lambda_2\f$ + +The output of the function can be used for robust edge or corner detection. + +@param src Input single-channel 8-bit or floating-point image. +@param dst Image to store the results. It has the same size as src and the type CV_32FC(6) . +@param blockSize Neighborhood size (see details below). +@param ksize Aperture parameter for the Sobel operator. +@param borderType Pixel extrapolation method. See #BorderTypes. + +@sa cornerMinEigenVal, cornerHarris, preCornerDetect + */ +CV_EXPORTS_W void cornerEigenValsAndVecs( InputArray src, OutputArray dst, + int blockSize, int ksize, + int borderType = BORDER_DEFAULT ); + +/** @brief Calculates a feature map for corner detection. + +The function calculates the complex spatial derivative-based function of the source image + +\f[\texttt{dst} = (D_x \texttt{src} )^2 \cdot D_{yy} \texttt{src} + (D_y \texttt{src} )^2 \cdot D_{xx} \texttt{src} - 2 D_x \texttt{src} \cdot D_y \texttt{src} \cdot D_{xy} \texttt{src}\f] + +where \f$D_x\f$,\f$D_y\f$ are the first image derivatives, \f$D_{xx}\f$,\f$D_{yy}\f$ are the second image +derivatives, and \f$D_{xy}\f$ is the mixed derivative. + +The corners can be found as local maximums of the functions, as shown below: +@code + Mat corners, dilated_corners; + preCornerDetect(image, corners, 3); + // dilation with 3x3 rectangular structuring element + dilate(corners, dilated_corners, Mat(), 1); + Mat corner_mask = corners == dilated_corners; +@endcode + +@param src Source single-channel 8-bit of floating-point image. +@param dst Output image that has the type CV_32F and the same size as src . +@param ksize %Aperture size of the Sobel . +@param borderType Pixel extrapolation method. See #BorderTypes. + */ +CV_EXPORTS_W void preCornerDetect( InputArray src, OutputArray dst, int ksize, + int borderType = BORDER_DEFAULT ); + +/** @brief Refines the corner locations. + +The function iterates to find the sub-pixel accurate location of corners or radial saddle points, as +shown on the figure below. + +![image](pics/cornersubpix.png) + +Sub-pixel accurate corner locator is based on the observation that every vector from the center \f$q\f$ +to a point \f$p\f$ located within a neighborhood of \f$q\f$ is orthogonal to the image gradient at \f$p\f$ +subject to image and measurement noise. Consider the expression: + +\f[\epsilon _i = {DI_{p_i}}^T \cdot (q - p_i)\f] + +where \f${DI_{p_i}}\f$ is an image gradient at one of the points \f$p_i\f$ in a neighborhood of \f$q\f$ . The +value of \f$q\f$ is to be found so that \f$\epsilon_i\f$ is minimized. A system of equations may be set up +with \f$\epsilon_i\f$ set to zero: + +\f[\sum _i(DI_{p_i} \cdot {DI_{p_i}}^T) \cdot q - \sum _i(DI_{p_i} \cdot {DI_{p_i}}^T \cdot p_i)\f] + +where the gradients are summed within a neighborhood ("search window") of \f$q\f$ . Calling the first +gradient term \f$G\f$ and the second gradient term \f$b\f$ gives: + +\f[q = G^{-1} \cdot b\f] + +The algorithm sets the center of the neighborhood window at this new center \f$q\f$ and then iterates +until the center stays within a set threshold. + +@param image Input single-channel, 8-bit or float image. +@param corners Initial coordinates of the input corners and refined coordinates provided for +output. +@param winSize Half of the side length of the search window. For example, if winSize=Size(5,5) , +then a \f$(5*2+1) \times (5*2+1) = 11 \times 11\f$ search window is used. +@param zeroZone Half of the size of the dead region in the middle of the search zone over which +the summation in the formula below is not done. It is used sometimes to avoid possible +singularities of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such +a size. +@param criteria Criteria for termination of the iterative process of corner refinement. That is, +the process of corner position refinement stops either after criteria.maxCount iterations or when +the corner position moves by less than criteria.epsilon on some iteration. + */ +CV_EXPORTS_W void cornerSubPix( InputArray image, InputOutputArray corners, + Size winSize, Size zeroZone, + TermCriteria criteria ); + +/** @brief Determines strong corners on an image. + +The function finds the most prominent corners in the image or in the specified image region, as +described in @cite Shi94 + +- Function calculates the corner quality measure at every source image pixel using the + #cornerMinEigenVal or #cornerHarris . +- Function performs a non-maximum suppression (the local maximums in *3 x 3* neighborhood are + retained). +- The corners with the minimal eigenvalue less than + \f$\texttt{qualityLevel} \cdot \max_{x,y} qualityMeasureMap(x,y)\f$ are rejected. +- The remaining corners are sorted by the quality measure in the descending order. +- Function throws away each corner for which there is a stronger corner at a distance less than + maxDistance. + +The function can be used to initialize a point-based tracker of an object. + +@note If the function is called with different values A and B of the parameter qualityLevel , and +A \> B, the vector of returned corners with qualityLevel=A will be the prefix of the output vector +with qualityLevel=B . + +@param image Input 8-bit or floating-point 32-bit, single-channel image. +@param corners Output vector of detected corners. +@param maxCorners Maximum number of corners to return. If there are more corners than are found, +the strongest of them is returned. `maxCorners <= 0` implies that no limit on the maximum is set +and all detected corners are returned. +@param qualityLevel Parameter characterizing the minimal accepted quality of image corners. The +parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue +(see #cornerMinEigenVal ) or the Harris function response (see #cornerHarris ). The corners with the +quality measure less than the product are rejected. For example, if the best corner has the +quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure +less than 15 are rejected. +@param minDistance Minimum possible Euclidean distance between the returned corners. +@param mask Optional region of interest. If the image is not empty (it needs to have the type +CV_8UC1 and the same size as image ), it specifies the region in which the corners are detected. +@param blockSize Size of an average block for computing a derivative covariation matrix over each +pixel neighborhood. See cornerEigenValsAndVecs . +@param useHarrisDetector Parameter indicating whether to use a Harris detector (see #cornerHarris) +or #cornerMinEigenVal. +@param k Free parameter of the Harris detector. + +@sa cornerMinEigenVal, cornerHarris, calcOpticalFlowPyrLK, estimateRigidTransform, + */ + +CV_EXPORTS_W void goodFeaturesToTrack( InputArray image, OutputArray corners, + int maxCorners, double qualityLevel, double minDistance, + InputArray mask = noArray(), int blockSize = 3, + bool useHarrisDetector = false, double k = 0.04 ); + +CV_EXPORTS_W void goodFeaturesToTrack( InputArray image, OutputArray corners, + int maxCorners, double qualityLevel, double minDistance, + InputArray mask, int blockSize, + int gradientSize, bool useHarrisDetector = false, + double k = 0.04 ); +/** @example samples/cpp/tutorial_code/ImgTrans/houghlines.cpp +An example using the Hough line detector +![Sample input image](Hough_Lines_Tutorial_Original_Image.jpg) ![Output image](Hough_Lines_Tutorial_Result.jpg) +*/ + +/** @brief Finds lines in a binary image using the standard Hough transform. + +The function implements the standard or standard multi-scale Hough transform algorithm for line +detection. See for a good explanation of Hough +transform. + +@param image 8-bit, single-channel binary source image. The image may be modified by the function. +@param lines Output vector of lines. Each line is represented by a 2 or 3 element vector +\f$(\rho, \theta)\f$ or \f$(\rho, \theta, \textrm{votes})\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of +the image). \f$\theta\f$ is the line rotation angle in radians ( +\f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ). +\f$\textrm{votes}\f$ is the value of accumulator. +@param rho Distance resolution of the accumulator in pixels. +@param theta Angle resolution of the accumulator in radians. +@param threshold Accumulator threshold parameter. Only those lines are returned that get enough +votes ( \f$>\texttt{threshold}\f$ ). +@param srn For the multi-scale Hough transform, it is a divisor for the distance resolution rho . +The coarse accumulator distance resolution is rho and the accurate accumulator resolution is +rho/srn . If both srn=0 and stn=0 , the classical Hough transform is used. Otherwise, both these +parameters should be positive. +@param stn For the multi-scale Hough transform, it is a divisor for the distance resolution theta. +@param min_theta For standard and multi-scale Hough transform, minimum angle to check for lines. +Must fall between 0 and max_theta. +@param max_theta For standard and multi-scale Hough transform, maximum angle to check for lines. +Must fall between min_theta and CV_PI. + */ +CV_EXPORTS_W void HoughLines( InputArray image, OutputArray lines, + double rho, double theta, int threshold, + double srn = 0, double stn = 0, + double min_theta = 0, double max_theta = CV_PI ); + +/** @brief Finds line segments in a binary image using the probabilistic Hough transform. + +The function implements the probabilistic Hough transform algorithm for line detection, described +in @cite Matas00 + +See the line detection example below: +@include snippets/imgproc_HoughLinesP.cpp +This is a sample picture the function parameters have been tuned for: + +![image](pics/building.jpg) + +And this is the output of the above program in case of the probabilistic Hough transform: + +![image](pics/houghp.png) + +@param image 8-bit, single-channel binary source image. The image may be modified by the function. +@param lines Output vector of lines. Each line is represented by a 4-element vector +\f$(x_1, y_1, x_2, y_2)\f$ , where \f$(x_1,y_1)\f$ and \f$(x_2, y_2)\f$ are the ending points of each detected +line segment. +@param rho Distance resolution of the accumulator in pixels. +@param theta Angle resolution of the accumulator in radians. +@param threshold Accumulator threshold parameter. Only those lines are returned that get enough +votes ( \f$>\texttt{threshold}\f$ ). +@param minLineLength Minimum line length. Line segments shorter than that are rejected. +@param maxLineGap Maximum allowed gap between points on the same line to link them. + +@sa LineSegmentDetector + */ +CV_EXPORTS_W void HoughLinesP( InputArray image, OutputArray lines, + double rho, double theta, int threshold, + double minLineLength = 0, double maxLineGap = 0 ); + +/** @brief Finds lines in a set of points using the standard Hough transform. + +The function finds lines in a set of points using a modification of the Hough transform. +@include snippets/imgproc_HoughLinesPointSet.cpp +@param _point Input vector of points. Each vector must be encoded as a Point vector \f$(x,y)\f$. Type must be CV_32FC2 or CV_32SC2. +@param _lines Output vector of found lines. Each vector is encoded as a vector \f$(votes, rho, theta)\f$. +The larger the value of 'votes', the higher the reliability of the Hough line. +@param lines_max Max count of hough lines. +@param threshold Accumulator threshold parameter. Only those lines are returned that get enough +votes ( \f$>\texttt{threshold}\f$ ) +@param min_rho Minimum Distance value of the accumulator in pixels. +@param max_rho Maximum Distance value of the accumulator in pixels. +@param rho_step Distance resolution of the accumulator in pixels. +@param min_theta Minimum angle value of the accumulator in radians. +@param max_theta Maximum angle value of the accumulator in radians. +@param theta_step Angle resolution of the accumulator in radians. + */ +CV_EXPORTS_W void HoughLinesPointSet( InputArray _point, OutputArray _lines, int lines_max, int threshold, + double min_rho, double max_rho, double rho_step, + double min_theta, double max_theta, double theta_step ); + +/** @example samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp +An example using the Hough circle detector +*/ + +/** @brief Finds circles in a grayscale image using the Hough transform. + +The function finds circles in a grayscale image using a modification of the Hough transform. + +Example: : +@include snippets/imgproc_HoughLinesCircles.cpp + +@note Usually the function detects the centers of circles well. However, it may fail to find correct +radii. You can assist to the function by specifying the radius range ( minRadius and maxRadius ) if +you know it. Or, you may set maxRadius to a negative number to return centers only without radius +search, and find the correct radius using an additional procedure. + +@param image 8-bit, single-channel, grayscale input image. +@param circles Output vector of found circles. Each vector is encoded as 3 or 4 element +floating-point vector \f$(x, y, radius)\f$ or \f$(x, y, radius, votes)\f$ . +@param method Detection method, see #HoughModes. Currently, the only implemented method is #HOUGH_GRADIENT +@param dp Inverse ratio of the accumulator resolution to the image resolution. For example, if +dp=1 , the accumulator has the same resolution as the input image. If dp=2 , the accumulator has +half as big width and height. +@param minDist Minimum distance between the centers of the detected circles. If the parameter is +too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is +too large, some circles may be missed. +@param param1 First method-specific parameter. In case of #HOUGH_GRADIENT , it is the higher +threshold of the two passed to the Canny edge detector (the lower one is twice smaller). +@param param2 Second method-specific parameter. In case of #HOUGH_GRADIENT , it is the +accumulator threshold for the circle centers at the detection stage. The smaller it is, the more +false circles may be detected. Circles, corresponding to the larger accumulator values, will be +returned first. +@param minRadius Minimum circle radius. +@param maxRadius Maximum circle radius. If <= 0, uses the maximum image dimension. If < 0, returns +centers without finding the radius. + +@sa fitEllipse, minEnclosingCircle + */ +CV_EXPORTS_W void HoughCircles( InputArray image, OutputArray circles, + int method, double dp, double minDist, + double param1 = 100, double param2 = 100, + int minRadius = 0, int maxRadius = 0 ); + +//! @} imgproc_feature + +//! @addtogroup imgproc_filter +//! @{ + +/** @example samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp +Advanced morphology Transformations sample code +![Sample screenshot](Morphology_2_Tutorial_Result.jpg) +Check @ref tutorial_opening_closing_hats "the corresponding tutorial" for more details +*/ + +/** @brief Erodes an image by using a specific structuring element. + +The function erodes the source image using the specified structuring element that determines the +shape of a pixel neighborhood over which the minimum is taken: + +\f[\texttt{dst} (x,y) = \min _{(x',y'): \, \texttt{element} (x',y') \ne0 } \texttt{src} (x+x',y+y')\f] + +The function supports the in-place mode. Erosion can be applied several ( iterations ) times. In +case of multi-channel images, each channel is processed independently. + +@param src input image; the number of channels can be arbitrary, but the depth should be one of +CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. +@param dst output image of the same size and type as src. +@param kernel structuring element used for erosion; if `element=Mat()`, a `3 x 3` rectangular +structuring element is used. Kernel can be created using #getStructuringElement. +@param anchor position of the anchor within the element; default value (-1, -1) means that the +anchor is at the element center. +@param iterations number of times erosion is applied. +@param borderType pixel extrapolation method, see #BorderTypes +@param borderValue border value in case of a constant border +@sa dilate, morphologyEx, getStructuringElement + */ +CV_EXPORTS_W void erode( InputArray src, OutputArray dst, InputArray kernel, + Point anchor = Point(-1,-1), int iterations = 1, + int borderType = BORDER_CONSTANT, + const Scalar& borderValue = morphologyDefaultBorderValue() ); + +/** @example samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp +Erosion and Dilation sample code +![Sample Screenshot-Erosion](Morphology_1_Tutorial_Erosion_Result.jpg)![Sample Screenshot-Dilation](Morphology_1_Tutorial_Dilation_Result.jpg) +Check @ref tutorial_erosion_dilatation "the corresponding tutorial" for more details +*/ + +/** @brief Dilates an image by using a specific structuring element. + +The function dilates the source image using the specified structuring element that determines the +shape of a pixel neighborhood over which the maximum is taken: +\f[\texttt{dst} (x,y) = \max _{(x',y'): \, \texttt{element} (x',y') \ne0 } \texttt{src} (x+x',y+y')\f] + +The function supports the in-place mode. Dilation can be applied several ( iterations ) times. In +case of multi-channel images, each channel is processed independently. + +@param src input image; the number of channels can be arbitrary, but the depth should be one of +CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. +@param dst output image of the same size and type as src. +@param kernel structuring element used for dilation; if elemenat=Mat(), a 3 x 3 rectangular +structuring element is used. Kernel can be created using #getStructuringElement +@param anchor position of the anchor within the element; default value (-1, -1) means that the +anchor is at the element center. +@param iterations number of times dilation is applied. +@param borderType pixel extrapolation method, see #BorderTypes +@param borderValue border value in case of a constant border +@sa erode, morphologyEx, getStructuringElement + */ +CV_EXPORTS_W void dilate( InputArray src, OutputArray dst, InputArray kernel, + Point anchor = Point(-1,-1), int iterations = 1, + int borderType = BORDER_CONSTANT, + const Scalar& borderValue = morphologyDefaultBorderValue() ); + +/** @brief Performs advanced morphological transformations. + +The function cv::morphologyEx can perform advanced morphological transformations using an erosion and dilation as +basic operations. + +Any of the operations can be done in-place. In case of multi-channel images, each channel is +processed independently. + +@param src Source image. The number of channels can be arbitrary. The depth should be one of +CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. +@param dst Destination image of the same size and type as source image. +@param op Type of a morphological operation, see #MorphTypes +@param kernel Structuring element. It can be created using #getStructuringElement. +@param anchor Anchor position with the kernel. Negative values mean that the anchor is at the +kernel center. +@param iterations Number of times erosion and dilation are applied. +@param borderType Pixel extrapolation method, see #BorderTypes +@param borderValue Border value in case of a constant border. The default value has a special +meaning. +@sa dilate, erode, getStructuringElement +@note The number of iterations is the number of times erosion or dilatation operation will be applied. +For instance, an opening operation (#MORPH_OPEN) with two iterations is equivalent to apply +successively: erode -> erode -> dilate -> dilate (and not erode -> dilate -> erode -> dilate). + */ +CV_EXPORTS_W void morphologyEx( InputArray src, OutputArray dst, + int op, InputArray kernel, + Point anchor = Point(-1,-1), int iterations = 1, + int borderType = BORDER_CONSTANT, + const Scalar& borderValue = morphologyDefaultBorderValue() ); + +//! @} imgproc_filter + +//! @addtogroup imgproc_transform +//! @{ + +/** @brief Resizes an image. + +The function resize resizes the image src down to or up to the specified size. Note that the +initial dst type or size are not taken into account. Instead, the size and type are derived from +the `src`,`dsize`,`fx`, and `fy`. If you want to resize src so that it fits the pre-created dst, +you may call the function as follows: +@code + // explicitly specify dsize=dst.size(); fx and fy will be computed from that. + resize(src, dst, dst.size(), 0, 0, interpolation); +@endcode +If you want to decimate the image by factor of 2 in each direction, you can call the function this +way: +@code + // specify fx and fy and let the function compute the destination image size. + resize(src, dst, Size(), 0.5, 0.5, interpolation); +@endcode +To shrink an image, it will generally look best with #INTER_AREA interpolation, whereas to +enlarge an image, it will generally look best with c#INTER_CUBIC (slow) or #INTER_LINEAR +(faster but still looks OK). + +@param src input image. +@param dst output image; it has the size dsize (when it is non-zero) or the size computed from +src.size(), fx, and fy; the type of dst is the same as of src. +@param dsize output image size; if it equals zero, it is computed as: + \f[\texttt{dsize = Size(round(fx*src.cols), round(fy*src.rows))}\f] + Either dsize or both fx and fy must be non-zero. +@param fx scale factor along the horizontal axis; when it equals 0, it is computed as +\f[\texttt{(double)dsize.width/src.cols}\f] +@param fy scale factor along the vertical axis; when it equals 0, it is computed as +\f[\texttt{(double)dsize.height/src.rows}\f] +@param interpolation interpolation method, see #InterpolationFlags + +@sa warpAffine, warpPerspective, remap + */ +CV_EXPORTS_W void resize( InputArray src, OutputArray dst, + Size dsize, double fx = 0, double fy = 0, + int interpolation = INTER_LINEAR ); + +/** @brief Applies an affine transformation to an image. + +The function warpAffine transforms the source image using the specified matrix: + +\f[\texttt{dst} (x,y) = \texttt{src} ( \texttt{M} _{11} x + \texttt{M} _{12} y + \texttt{M} _{13}, \texttt{M} _{21} x + \texttt{M} _{22} y + \texttt{M} _{23})\f] + +when the flag #WARP_INVERSE_MAP is set. Otherwise, the transformation is first inverted +with #invertAffineTransform and then put in the formula above instead of M. The function cannot +operate in-place. + +@param src input image. +@param dst output image that has the size dsize and the same type as src . +@param M \f$2\times 3\f$ transformation matrix. +@param dsize size of the output image. +@param flags combination of interpolation methods (see #InterpolationFlags) and the optional +flag #WARP_INVERSE_MAP that means that M is the inverse transformation ( +\f$\texttt{dst}\rightarrow\texttt{src}\f$ ). +@param borderMode pixel extrapolation method (see #BorderTypes); when +borderMode=#BORDER_TRANSPARENT, it means that the pixels in the destination image corresponding to +the "outliers" in the source image are not modified by the function. +@param borderValue value used in case of a constant border; by default, it is 0. + +@sa warpPerspective, resize, remap, getRectSubPix, transform + */ +CV_EXPORTS_W void warpAffine( InputArray src, OutputArray dst, + InputArray M, Size dsize, + int flags = INTER_LINEAR, + int borderMode = BORDER_CONSTANT, + const Scalar& borderValue = Scalar()); + +/** @example samples/cpp/warpPerspective_demo.cpp +An example program shows using cv::findHomography and cv::warpPerspective for image warping +*/ + +/** @brief Applies a perspective transformation to an image. + +The function warpPerspective transforms the source image using the specified matrix: + +\f[\texttt{dst} (x,y) = \texttt{src} \left ( \frac{M_{11} x + M_{12} y + M_{13}}{M_{31} x + M_{32} y + M_{33}} , + \frac{M_{21} x + M_{22} y + M_{23}}{M_{31} x + M_{32} y + M_{33}} \right )\f] + +when the flag #WARP_INVERSE_MAP is set. Otherwise, the transformation is first inverted with invert +and then put in the formula above instead of M. The function cannot operate in-place. + +@param src input image. +@param dst output image that has the size dsize and the same type as src . +@param M \f$3\times 3\f$ transformation matrix. +@param dsize size of the output image. +@param flags combination of interpolation methods (#INTER_LINEAR or #INTER_NEAREST) and the +optional flag #WARP_INVERSE_MAP, that sets M as the inverse transformation ( +\f$\texttt{dst}\rightarrow\texttt{src}\f$ ). +@param borderMode pixel extrapolation method (#BORDER_CONSTANT or #BORDER_REPLICATE). +@param borderValue value used in case of a constant border; by default, it equals 0. + +@sa warpAffine, resize, remap, getRectSubPix, perspectiveTransform + */ +CV_EXPORTS_W void warpPerspective( InputArray src, OutputArray dst, + InputArray M, Size dsize, + int flags = INTER_LINEAR, + int borderMode = BORDER_CONSTANT, + const Scalar& borderValue = Scalar()); + +/** @brief Applies a generic geometrical transformation to an image. + +The function remap transforms the source image using the specified map: + +\f[\texttt{dst} (x,y) = \texttt{src} (map_x(x,y),map_y(x,y))\f] + +where values of pixels with non-integer coordinates are computed using one of available +interpolation methods. \f$map_x\f$ and \f$map_y\f$ can be encoded as separate floating-point maps +in \f$map_1\f$ and \f$map_2\f$ respectively, or interleaved floating-point maps of \f$(x,y)\f$ in +\f$map_1\f$, or fixed-point maps created by using convertMaps. The reason you might want to +convert from floating to fixed-point representations of a map is that they can yield much faster +(\~2x) remapping operations. In the converted case, \f$map_1\f$ contains pairs (cvFloor(x), +cvFloor(y)) and \f$map_2\f$ contains indices in a table of interpolation coefficients. + +This function cannot operate in-place. + +@param src Source image. +@param dst Destination image. It has the same size as map1 and the same type as src . +@param map1 The first map of either (x,y) points or just x values having the type CV_16SC2 , +CV_32FC1, or CV_32FC2. See convertMaps for details on converting a floating point +representation to fixed-point for speed. +@param map2 The second map of y values having the type CV_16UC1, CV_32FC1, or none (empty map +if map1 is (x,y) points), respectively. +@param interpolation Interpolation method (see #InterpolationFlags). The method #INTER_AREA is +not supported by this function. +@param borderMode Pixel extrapolation method (see #BorderTypes). When +borderMode=#BORDER_TRANSPARENT, it means that the pixels in the destination image that +corresponds to the "outliers" in the source image are not modified by the function. +@param borderValue Value used in case of a constant border. By default, it is 0. +@note +Due to current implementation limitations the size of an input and output images should be less than 32767x32767. + */ +CV_EXPORTS_W void remap( InputArray src, OutputArray dst, + InputArray map1, InputArray map2, + int interpolation, int borderMode = BORDER_CONSTANT, + const Scalar& borderValue = Scalar()); + +/** @brief Converts image transformation maps from one representation to another. + +The function converts a pair of maps for remap from one representation to another. The following +options ( (map1.type(), map2.type()) \f$\rightarrow\f$ (dstmap1.type(), dstmap2.type()) ) are +supported: + +- \f$\texttt{(CV_32FC1, CV_32FC1)} \rightarrow \texttt{(CV_16SC2, CV_16UC1)}\f$. This is the +most frequently used conversion operation, in which the original floating-point maps (see remap ) +are converted to a more compact and much faster fixed-point representation. The first output array +contains the rounded coordinates and the second array (created only when nninterpolation=false ) +contains indices in the interpolation tables. + +- \f$\texttt{(CV_32FC2)} \rightarrow \texttt{(CV_16SC2, CV_16UC1)}\f$. The same as above but +the original maps are stored in one 2-channel matrix. + +- Reverse conversion. Obviously, the reconstructed floating-point maps will not be exactly the same +as the originals. + +@param map1 The first input map of type CV_16SC2, CV_32FC1, or CV_32FC2 . +@param map2 The second input map of type CV_16UC1, CV_32FC1, or none (empty matrix), +respectively. +@param dstmap1 The first output map that has the type dstmap1type and the same size as src . +@param dstmap2 The second output map. +@param dstmap1type Type of the first output map that should be CV_16SC2, CV_32FC1, or +CV_32FC2 . +@param nninterpolation Flag indicating whether the fixed-point maps are used for the +nearest-neighbor or for a more complex interpolation. + +@sa remap, undistort, initUndistortRectifyMap + */ +CV_EXPORTS_W void convertMaps( InputArray map1, InputArray map2, + OutputArray dstmap1, OutputArray dstmap2, + int dstmap1type, bool nninterpolation = false ); + +/** @brief Calculates an affine matrix of 2D rotation. + +The function calculates the following matrix: + +\f[\begin{bmatrix} \alpha & \beta & (1- \alpha ) \cdot \texttt{center.x} - \beta \cdot \texttt{center.y} \\ - \beta & \alpha & \beta \cdot \texttt{center.x} + (1- \alpha ) \cdot \texttt{center.y} \end{bmatrix}\f] + +where + +\f[\begin{array}{l} \alpha = \texttt{scale} \cdot \cos \texttt{angle} , \\ \beta = \texttt{scale} \cdot \sin \texttt{angle} \end{array}\f] + +The transformation maps the rotation center to itself. If this is not the target, adjust the shift. + +@param center Center of the rotation in the source image. +@param angle Rotation angle in degrees. Positive values mean counter-clockwise rotation (the +coordinate origin is assumed to be the top-left corner). +@param scale Isotropic scale factor. + +@sa getAffineTransform, warpAffine, transform + */ +CV_EXPORTS_W Mat getRotationMatrix2D( Point2f center, double angle, double scale ); + +//! returns 3x3 perspective transformation for the corresponding 4 point pairs. +CV_EXPORTS Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] ); + +/** @brief Calculates an affine transform from three pairs of the corresponding points. + +The function calculates the \f$2 \times 3\f$ matrix of an affine transform so that: + +\f[\begin{bmatrix} x'_i \\ y'_i \end{bmatrix} = \texttt{map_matrix} \cdot \begin{bmatrix} x_i \\ y_i \\ 1 \end{bmatrix}\f] + +where + +\f[dst(i)=(x'_i,y'_i), src(i)=(x_i, y_i), i=0,1,2\f] + +@param src Coordinates of triangle vertices in the source image. +@param dst Coordinates of the corresponding triangle vertices in the destination image. + +@sa warpAffine, transform + */ +CV_EXPORTS Mat getAffineTransform( const Point2f src[], const Point2f dst[] ); + +/** @brief Inverts an affine transformation. + +The function computes an inverse affine transformation represented by \f$2 \times 3\f$ matrix M: + +\f[\begin{bmatrix} a_{11} & a_{12} & b_1 \\ a_{21} & a_{22} & b_2 \end{bmatrix}\f] + +The result is also a \f$2 \times 3\f$ matrix of the same type as M. + +@param M Original affine transformation. +@param iM Output reverse affine transformation. + */ +CV_EXPORTS_W void invertAffineTransform( InputArray M, OutputArray iM ); + +/** @brief Calculates a perspective transform from four pairs of the corresponding points. + +The function calculates the \f$3 \times 3\f$ matrix of a perspective transform so that: + +\f[\begin{bmatrix} t_i x'_i \\ t_i y'_i \\ t_i \end{bmatrix} = \texttt{map_matrix} \cdot \begin{bmatrix} x_i \\ y_i \\ 1 \end{bmatrix}\f] + +where + +\f[dst(i)=(x'_i,y'_i), src(i)=(x_i, y_i), i=0,1,2,3\f] + +@param src Coordinates of quadrangle vertices in the source image. +@param dst Coordinates of the corresponding quadrangle vertices in the destination image. + +@sa findHomography, warpPerspective, perspectiveTransform + */ +CV_EXPORTS_W Mat getPerspectiveTransform( InputArray src, InputArray dst ); + +CV_EXPORTS_W Mat getAffineTransform( InputArray src, InputArray dst ); + +/** @brief Retrieves a pixel rectangle from an image with sub-pixel accuracy. + +The function getRectSubPix extracts pixels from src: + +\f[patch(x, y) = src(x + \texttt{center.x} - ( \texttt{dst.cols} -1)*0.5, y + \texttt{center.y} - ( \texttt{dst.rows} -1)*0.5)\f] + +where the values of the pixels at non-integer coordinates are retrieved using bilinear +interpolation. Every channel of multi-channel images is processed independently. Also +the image should be a single channel or three channel image. While the center of the +rectangle must be inside the image, parts of the rectangle may be outside. + +@param image Source image. +@param patchSize Size of the extracted patch. +@param center Floating point coordinates of the center of the extracted rectangle within the +source image. The center must be inside the image. +@param patch Extracted patch that has the size patchSize and the same number of channels as src . +@param patchType Depth of the extracted pixels. By default, they have the same depth as src . + +@sa warpAffine, warpPerspective + */ +CV_EXPORTS_W void getRectSubPix( InputArray image, Size patchSize, + Point2f center, OutputArray patch, int patchType = -1 ); + +/** @example samples/cpp/polar_transforms.cpp +An example using the cv::linearPolar and cv::logPolar operations +*/ + +/** @brief Remaps an image to semilog-polar coordinates space. + +@deprecated This function produces same result as cv::warpPolar(src, dst, src.size(), center, maxRadius, flags+WARP_POLAR_LOG); + +@internal +Transform the source image using the following transformation (See @ref polar_remaps_reference_image "Polar remaps reference image d)"): +\f[\begin{array}{l} + dst( \rho , \phi ) = src(x,y) \\ + dst.size() \leftarrow src.size() +\end{array}\f] + +where +\f[\begin{array}{l} + I = (dx,dy) = (x - center.x,y - center.y) \\ + \rho = M \cdot log_e(\texttt{magnitude} (I)) ,\\ + \phi = Kangle \cdot \texttt{angle} (I) \\ +\end{array}\f] + +and +\f[\begin{array}{l} + M = src.cols / log_e(maxRadius) \\ + Kangle = src.rows / 2\Pi \\ +\end{array}\f] + +The function emulates the human "foveal" vision and can be used for fast scale and +rotation-invariant template matching, for object tracking and so forth. +@param src Source image +@param dst Destination image. It will have same size and type as src. +@param center The transformation center; where the output precision is maximal +@param M Magnitude scale parameter. It determines the radius of the bounding circle to transform too. +@param flags A combination of interpolation methods, see #InterpolationFlags + +@note +- The function can not operate in-place. +- To calculate magnitude and angle in degrees #cartToPolar is used internally thus angles are measured from 0 to 360 with accuracy about 0.3 degrees. + +@sa cv::linearPolar +@endinternal +*/ +CV_EXPORTS_W void logPolar( InputArray src, OutputArray dst, + Point2f center, double M, int flags ); + +/** @brief Remaps an image to polar coordinates space. + +@deprecated This function produces same result as cv::warpPolar(src, dst, src.size(), center, maxRadius, flags) + +@internal +Transform the source image using the following transformation (See @ref polar_remaps_reference_image "Polar remaps reference image c)"): +\f[\begin{array}{l} + dst( \rho , \phi ) = src(x,y) \\ + dst.size() \leftarrow src.size() +\end{array}\f] + +where +\f[\begin{array}{l} + I = (dx,dy) = (x - center.x,y - center.y) \\ + \rho = Kmag \cdot \texttt{magnitude} (I) ,\\ + \phi = angle \cdot \texttt{angle} (I) +\end{array}\f] + +and +\f[\begin{array}{l} + Kx = src.cols / maxRadius \\ + Ky = src.rows / 2\Pi +\end{array}\f] + + +@param src Source image +@param dst Destination image. It will have same size and type as src. +@param center The transformation center; +@param maxRadius The radius of the bounding circle to transform. It determines the inverse magnitude scale parameter too. +@param flags A combination of interpolation methods, see #InterpolationFlags + +@note +- The function can not operate in-place. +- To calculate magnitude and angle in degrees #cartToPolar is used internally thus angles are measured from 0 to 360 with accuracy about 0.3 degrees. + +@sa cv::logPolar +@endinternal +*/ +CV_EXPORTS_W void linearPolar( InputArray src, OutputArray dst, + Point2f center, double maxRadius, int flags ); + + +/** \brief Remaps an image to polar or semilog-polar coordinates space + +@anchor polar_remaps_reference_image +![Polar remaps reference](pics/polar_remap_doc.png) + +Transform the source image using the following transformation: +\f[ +dst(\rho , \phi ) = src(x,y) +\f] + +where +\f[ +\begin{array}{l} +\vec{I} = (x - center.x, \;y - center.y) \\ +\phi = Kangle \cdot \texttt{angle} (\vec{I}) \\ +\rho = \left\{\begin{matrix} +Klin \cdot \texttt{magnitude} (\vec{I}) & default \\ +Klog \cdot log_e(\texttt{magnitude} (\vec{I})) & if \; semilog \\ +\end{matrix}\right. +\end{array} +\f] + +and +\f[ +\begin{array}{l} +Kangle = dsize.height / 2\Pi \\ +Klin = dsize.width / maxRadius \\ +Klog = dsize.width / log_e(maxRadius) \\ +\end{array} +\f] + + +\par Linear vs semilog mapping + +Polar mapping can be linear or semi-log. Add one of #WarpPolarMode to `flags` to specify the polar mapping mode. + +Linear is the default mode. + +The semilog mapping emulates the human "foveal" vision that permit very high acuity on the line of sight (central vision) +in contrast to peripheral vision where acuity is minor. + +\par Option on `dsize`: + +- if both values in `dsize <=0 ` (default), +the destination image will have (almost) same area of source bounding circle: +\f[\begin{array}{l} +dsize.area \leftarrow (maxRadius^2 \cdot \Pi) \\ +dsize.width = \texttt{cvRound}(maxRadius) \\ +dsize.height = \texttt{cvRound}(maxRadius \cdot \Pi) \\ +\end{array}\f] + + +- if only `dsize.height <= 0`, +the destination image area will be proportional to the bounding circle area but scaled by `Kx * Kx`: +\f[\begin{array}{l} +dsize.height = \texttt{cvRound}(dsize.width \cdot \Pi) \\ +\end{array} +\f] + +- if both values in `dsize > 0 `, +the destination image will have the given size therefore the area of the bounding circle will be scaled to `dsize`. + + +\par Reverse mapping + +You can get reverse mapping adding #WARP_INVERSE_MAP to `flags` +\snippet polar_transforms.cpp InverseMap + +In addiction, to calculate the original coordinate from a polar mapped coordinate \f$(rho, phi)->(x, y)\f$: +\snippet polar_transforms.cpp InverseCoordinate + +@param src Source image. +@param dst Destination image. It will have same type as src. +@param dsize The destination image size (see description for valid options). +@param center The transformation center. +@param maxRadius The radius of the bounding circle to transform. It determines the inverse magnitude scale parameter too. +@param flags A combination of interpolation methods, #InterpolationFlags + #WarpPolarMode. + - Add #WARP_POLAR_LINEAR to select linear polar mapping (default) + - Add #WARP_POLAR_LOG to select semilog polar mapping + - Add #WARP_INVERSE_MAP for reverse mapping. +@note +- The function can not operate in-place. +- To calculate magnitude and angle in degrees #cartToPolar is used internally thus angles are measured from 0 to 360 with accuracy about 0.3 degrees. +- This function uses #remap. Due to current implementation limitations the size of an input and output images should be less than 32767x32767. + +@sa cv::remap +*/ +CV_EXPORTS_W void warpPolar(InputArray src, OutputArray dst, Size dsize, + Point2f center, double maxRadius, int flags); + + +//! @} imgproc_transform + +//! @addtogroup imgproc_misc +//! @{ + +/** @overload */ +CV_EXPORTS_W void integral( InputArray src, OutputArray sum, int sdepth = -1 ); + +/** @overload */ +CV_EXPORTS_AS(integral2) void integral( InputArray src, OutputArray sum, + OutputArray sqsum, int sdepth = -1, int sqdepth = -1 ); + +/** @brief Calculates the integral of an image. + +The function calculates one or more integral images for the source image as follows: + +\f[\texttt{sum} (X,Y) = \sum _{x + +Calculates the cross-power spectrum of two supplied source arrays. The arrays are padded if needed +with getOptimalDFTSize. + +The function performs the following equations: +- First it applies a Hanning window (see ) to each +image to remove possible edge effects. This window is cached until the array size changes to speed +up processing time. +- Next it computes the forward DFTs of each source array: +\f[\mathbf{G}_a = \mathcal{F}\{src_1\}, \; \mathbf{G}_b = \mathcal{F}\{src_2\}\f] +where \f$\mathcal{F}\f$ is the forward DFT. +- It then computes the cross-power spectrum of each frequency domain array: +\f[R = \frac{ \mathbf{G}_a \mathbf{G}_b^*}{|\mathbf{G}_a \mathbf{G}_b^*|}\f] +- Next the cross-correlation is converted back into the time domain via the inverse DFT: +\f[r = \mathcal{F}^{-1}\{R\}\f] +- Finally, it computes the peak location and computes a 5x5 weighted centroid around the peak to +achieve sub-pixel accuracy. +\f[(\Delta x, \Delta y) = \texttt{weightedCentroid} \{\arg \max_{(x, y)}\{r\}\}\f] +- If non-zero, the response parameter is computed as the sum of the elements of r within the 5x5 +centroid around the peak location. It is normalized to a maximum of 1 (meaning there is a single +peak) and will be smaller when there are multiple peaks. + +@param src1 Source floating point array (CV_32FC1 or CV_64FC1) +@param src2 Source floating point array (CV_32FC1 or CV_64FC1) +@param window Floating point array with windowing coefficients to reduce edge effects (optional). +@param response Signal power within the 5x5 centroid around the peak, between 0 and 1 (optional). +@returns detected phase shift (sub-pixel) between the two arrays. + +@sa dft, getOptimalDFTSize, idft, mulSpectrums createHanningWindow + */ +CV_EXPORTS_W Point2d phaseCorrelate(InputArray src1, InputArray src2, + InputArray window = noArray(), CV_OUT double* response = 0); + +/** @brief This function computes a Hanning window coefficients in two dimensions. + +See (http://en.wikipedia.org/wiki/Hann_function) and (http://en.wikipedia.org/wiki/Window_function) +for more information. + +An example is shown below: +@code + // create hanning window of size 100x100 and type CV_32F + Mat hann; + createHanningWindow(hann, Size(100, 100), CV_32F); +@endcode +@param dst Destination array to place Hann coefficients in +@param winSize The window size specifications (both width and height must be > 1) +@param type Created array type + */ +CV_EXPORTS_W void createHanningWindow(OutputArray dst, Size winSize, int type); + +//! @} imgproc_motion + +//! @addtogroup imgproc_misc +//! @{ + +/** @brief Applies a fixed-level threshold to each array element. + +The function applies fixed-level thresholding to a multiple-channel array. The function is typically +used to get a bi-level (binary) image out of a grayscale image ( #compare could be also used for +this purpose) or for removing a noise, that is, filtering out pixels with too small or too large +values. There are several types of thresholding supported by the function. They are determined by +type parameter. + +Also, the special values #THRESH_OTSU or #THRESH_TRIANGLE may be combined with one of the +above values. In these cases, the function determines the optimal threshold value using the Otsu's +or Triangle algorithm and uses it instead of the specified thresh. + +@note Currently, the Otsu's and Triangle methods are implemented only for 8-bit single-channel images. + +@param src input array (multiple-channel, 8-bit or 32-bit floating point). +@param dst output array of the same size and type and the same number of channels as src. +@param thresh threshold value. +@param maxval maximum value to use with the #THRESH_BINARY and #THRESH_BINARY_INV thresholding +types. +@param type thresholding type (see #ThresholdTypes). +@return the computed threshold value if Otsu's or Triangle methods used. + +@sa adaptiveThreshold, findContours, compare, min, max + */ +CV_EXPORTS_W double threshold( InputArray src, OutputArray dst, + double thresh, double maxval, int type ); + + +/** @brief Applies an adaptive threshold to an array. + +The function transforms a grayscale image to a binary image according to the formulae: +- **THRESH_BINARY** + \f[dst(x,y) = \fork{\texttt{maxValue}}{if \(src(x,y) > T(x,y)\)}{0}{otherwise}\f] +- **THRESH_BINARY_INV** + \f[dst(x,y) = \fork{0}{if \(src(x,y) > T(x,y)\)}{\texttt{maxValue}}{otherwise}\f] +where \f$T(x,y)\f$ is a threshold calculated individually for each pixel (see adaptiveMethod parameter). + +The function can process the image in-place. + +@param src Source 8-bit single-channel image. +@param dst Destination image of the same size and the same type as src. +@param maxValue Non-zero value assigned to the pixels for which the condition is satisfied +@param adaptiveMethod Adaptive thresholding algorithm to use, see #AdaptiveThresholdTypes. +The #BORDER_REPLICATE | #BORDER_ISOLATED is used to process boundaries. +@param thresholdType Thresholding type that must be either #THRESH_BINARY or #THRESH_BINARY_INV, +see #ThresholdTypes. +@param blockSize Size of a pixel neighborhood that is used to calculate a threshold value for the +pixel: 3, 5, 7, and so on. +@param C Constant subtracted from the mean or weighted mean (see the details below). Normally, it +is positive but may be zero or negative as well. + +@sa threshold, blur, GaussianBlur + */ +CV_EXPORTS_W void adaptiveThreshold( InputArray src, OutputArray dst, + double maxValue, int adaptiveMethod, + int thresholdType, int blockSize, double C ); + +//! @} imgproc_misc + +//! @addtogroup imgproc_filter +//! @{ + +/** @example samples/cpp/tutorial_code/ImgProc/Pyramids/Pyramids.cpp +An example using pyrDown and pyrUp functions +*/ + +/** @brief Blurs an image and downsamples it. + +By default, size of the output image is computed as `Size((src.cols+1)/2, (src.rows+1)/2)`, but in +any case, the following conditions should be satisfied: + +\f[\begin{array}{l} | \texttt{dstsize.width} *2-src.cols| \leq 2 \\ | \texttt{dstsize.height} *2-src.rows| \leq 2 \end{array}\f] + +The function performs the downsampling step of the Gaussian pyramid construction. First, it +convolves the source image with the kernel: + +\f[\frac{1}{256} \begin{bmatrix} 1 & 4 & 6 & 4 & 1 \\ 4 & 16 & 24 & 16 & 4 \\ 6 & 24 & 36 & 24 & 6 \\ 4 & 16 & 24 & 16 & 4 \\ 1 & 4 & 6 & 4 & 1 \end{bmatrix}\f] + +Then, it downsamples the image by rejecting even rows and columns. + +@param src input image. +@param dst output image; it has the specified size and the same type as src. +@param dstsize size of the output image. +@param borderType Pixel extrapolation method, see #BorderTypes (#BORDER_CONSTANT isn't supported) + */ +CV_EXPORTS_W void pyrDown( InputArray src, OutputArray dst, + const Size& dstsize = Size(), int borderType = BORDER_DEFAULT ); + +/** @brief Upsamples an image and then blurs it. + +By default, size of the output image is computed as `Size(src.cols\*2, (src.rows\*2)`, but in any +case, the following conditions should be satisfied: + +\f[\begin{array}{l} | \texttt{dstsize.width} -src.cols*2| \leq ( \texttt{dstsize.width} \mod 2) \\ | \texttt{dstsize.height} -src.rows*2| \leq ( \texttt{dstsize.height} \mod 2) \end{array}\f] + +The function performs the upsampling step of the Gaussian pyramid construction, though it can +actually be used to construct the Laplacian pyramid. First, it upsamples the source image by +injecting even zero rows and columns and then convolves the result with the same kernel as in +pyrDown multiplied by 4. + +@param src input image. +@param dst output image. It has the specified size and the same type as src . +@param dstsize size of the output image. +@param borderType Pixel extrapolation method, see #BorderTypes (only #BORDER_DEFAULT is supported) + */ +CV_EXPORTS_W void pyrUp( InputArray src, OutputArray dst, + const Size& dstsize = Size(), int borderType = BORDER_DEFAULT ); + +/** @brief Constructs the Gaussian pyramid for an image. + +The function constructs a vector of images and builds the Gaussian pyramid by recursively applying +pyrDown to the previously built pyramid layers, starting from `dst[0]==src`. + +@param src Source image. Check pyrDown for the list of supported types. +@param dst Destination vector of maxlevel+1 images of the same type as src. dst[0] will be the +same as src. dst[1] is the next pyramid layer, a smoothed and down-sized src, and so on. +@param maxlevel 0-based index of the last (the smallest) pyramid layer. It must be non-negative. +@param borderType Pixel extrapolation method, see #BorderTypes (#BORDER_CONSTANT isn't supported) + */ +CV_EXPORTS void buildPyramid( InputArray src, OutputArrayOfArrays dst, + int maxlevel, int borderType = BORDER_DEFAULT ); + +//! @} imgproc_filter + +//! @addtogroup imgproc_transform +//! @{ + +/** @brief Transforms an image to compensate for lens distortion. + +The function transforms an image to compensate radial and tangential lens distortion. + +The function is simply a combination of #initUndistortRectifyMap (with unity R ) and #remap +(with bilinear interpolation). See the former function for details of the transformation being +performed. + +Those pixels in the destination image, for which there is no correspondent pixels in the source +image, are filled with zeros (black color). + +A particular subset of the source image that will be visible in the corrected image can be regulated +by newCameraMatrix. You can use #getOptimalNewCameraMatrix to compute the appropriate +newCameraMatrix depending on your requirements. + +The camera matrix and the distortion parameters can be determined using #calibrateCamera. If +the resolution of images is different from the resolution used at the calibration stage, \f$f_x, +f_y, c_x\f$ and \f$c_y\f$ need to be scaled accordingly, while the distortion coefficients remain +the same. + +@param src Input (distorted) image. +@param dst Output (corrected) image that has the same size and type as src . +@param cameraMatrix Input camera matrix \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ +of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed. +@param newCameraMatrix Camera matrix of the distorted image. By default, it is the same as +cameraMatrix but you may additionally scale and shift the result by using a different matrix. + */ +CV_EXPORTS_W void undistort( InputArray src, OutputArray dst, + InputArray cameraMatrix, + InputArray distCoeffs, + InputArray newCameraMatrix = noArray() ); + +/** @brief Computes the undistortion and rectification transformation map. + +The function computes the joint undistortion and rectification transformation and represents the +result in the form of maps for remap. The undistorted image looks like original, as if it is +captured with a camera using the camera matrix =newCameraMatrix and zero distortion. In case of a +monocular camera, newCameraMatrix is usually equal to cameraMatrix, or it can be computed by +#getOptimalNewCameraMatrix for a better control over scaling. In case of a stereo camera, +newCameraMatrix is normally set to P1 or P2 computed by #stereoRectify . + +Also, this new camera is oriented differently in the coordinate space, according to R. That, for +example, helps to align two heads of a stereo camera so that the epipolar lines on both images +become horizontal and have the same y- coordinate (in case of a horizontally aligned stereo camera). + +The function actually builds the maps for the inverse mapping algorithm that is used by remap. That +is, for each pixel \f$(u, v)\f$ in the destination (corrected and rectified) image, the function +computes the corresponding coordinates in the source image (that is, in the original image from +camera). The following process is applied: +\f[ +\begin{array}{l} +x \leftarrow (u - {c'}_x)/{f'}_x \\ +y \leftarrow (v - {c'}_y)/{f'}_y \\ +{[X\,Y\,W]} ^T \leftarrow R^{-1}*[x \, y \, 1]^T \\ +x' \leftarrow X/W \\ +y' \leftarrow Y/W \\ +r^2 \leftarrow x'^2 + y'^2 \\ +x'' \leftarrow x' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} ++ 2p_1 x' y' + p_2(r^2 + 2 x'^2) + s_1 r^2 + s_2 r^4\\ +y'' \leftarrow y' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} ++ p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' + s_3 r^2 + s_4 r^4 \\ +s\vecthree{x'''}{y'''}{1} = +\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}((\tau_x, \tau_y)} +{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)} +{0}{0}{1} R(\tau_x, \tau_y) \vecthree{x''}{y''}{1}\\ +map_x(u,v) \leftarrow x''' f_x + c_x \\ +map_y(u,v) \leftarrow y''' f_y + c_y +\end{array} +\f] +where \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ +are the distortion coefficients. + +In case of a stereo camera, this function is called twice: once for each camera head, after +stereoRectify, which in its turn is called after #stereoCalibrate. But if the stereo camera +was not calibrated, it is still possible to compute the rectification transformations directly from +the fundamental matrix using #stereoRectifyUncalibrated. For each camera, the function computes +homography H as the rectification transformation in a pixel domain, not a rotation matrix R in 3D +space. R can be computed from H as +\f[\texttt{R} = \texttt{cameraMatrix} ^{-1} \cdot \texttt{H} \cdot \texttt{cameraMatrix}\f] +where cameraMatrix can be chosen arbitrarily. + +@param cameraMatrix Input camera matrix \f$A=\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ +of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed. +@param R Optional rectification transformation in the object space (3x3 matrix). R1 or R2 , +computed by #stereoRectify can be passed here. If the matrix is empty, the identity transformation +is assumed. In cvInitUndistortMap R assumed to be an identity matrix. +@param newCameraMatrix New camera matrix \f$A'=\vecthreethree{f_x'}{0}{c_x'}{0}{f_y'}{c_y'}{0}{0}{1}\f$. +@param size Undistorted image size. +@param m1type Type of the first output map that can be CV_32FC1, CV_32FC2 or CV_16SC2, see #convertMaps +@param map1 The first output map. +@param map2 The second output map. + */ +CV_EXPORTS_W void initUndistortRectifyMap( InputArray cameraMatrix, InputArray distCoeffs, + InputArray R, InputArray newCameraMatrix, + Size size, int m1type, OutputArray map1, OutputArray map2 ); + +//! initializes maps for #remap for wide-angle +CV_EXPORTS_W float initWideAngleProjMap( InputArray cameraMatrix, InputArray distCoeffs, + Size imageSize, int destImageWidth, + int m1type, OutputArray map1, OutputArray map2, + int projType = PROJ_SPHERICAL_EQRECT, double alpha = 0); + +/** @brief Returns the default new camera matrix. + +The function returns the camera matrix that is either an exact copy of the input cameraMatrix (when +centerPrinicipalPoint=false ), or the modified one (when centerPrincipalPoint=true). + +In the latter case, the new camera matrix will be: + +\f[\begin{bmatrix} f_x && 0 && ( \texttt{imgSize.width} -1)*0.5 \\ 0 && f_y && ( \texttt{imgSize.height} -1)*0.5 \\ 0 && 0 && 1 \end{bmatrix} ,\f] + +where \f$f_x\f$ and \f$f_y\f$ are \f$(0,0)\f$ and \f$(1,1)\f$ elements of cameraMatrix, respectively. + +By default, the undistortion functions in OpenCV (see #initUndistortRectifyMap, #undistort) do not +move the principal point. However, when you work with stereo, it is important to move the principal +points in both views to the same y-coordinate (which is required by most of stereo correspondence +algorithms), and may be to the same x-coordinate too. So, you can form the new camera matrix for +each view where the principal points are located at the center. + +@param cameraMatrix Input camera matrix. +@param imgsize Camera view image size in pixels. +@param centerPrincipalPoint Location of the principal point in the new camera matrix. The +parameter indicates whether this location should be at the image center or not. + */ +CV_EXPORTS_W Mat getDefaultNewCameraMatrix( InputArray cameraMatrix, Size imgsize = Size(), + bool centerPrincipalPoint = false ); + +/** @brief Computes the ideal point coordinates from the observed point coordinates. + +The function is similar to #undistort and #initUndistortRectifyMap but it operates on a +sparse set of points instead of a raster image. Also the function performs a reverse transformation +to projectPoints. In case of a 3D object, it does not reconstruct its 3D coordinates, but for a +planar object, it does, up to a translation vector, if the proper R is specified. + +For each observed point coordinate \f$(u, v)\f$ the function computes: +\f[ +\begin{array}{l} +x^{"} \leftarrow (u - c_x)/f_x \\ +y^{"} \leftarrow (v - c_y)/f_y \\ +(x',y') = undistort(x^{"},y^{"}, \texttt{distCoeffs}) \\ +{[X\,Y\,W]} ^T \leftarrow R*[x' \, y' \, 1]^T \\ +x \leftarrow X/W \\ +y \leftarrow Y/W \\ +\text{only performed if P is specified:} \\ +u' \leftarrow x {f'}_x + {c'}_x \\ +v' \leftarrow y {f'}_y + {c'}_y +\end{array} +\f] + +where *undistort* is an approximate iterative algorithm that estimates the normalized original +point coordinates out of the normalized distorted point coordinates ("normalized" means that the +coordinates do not depend on the camera matrix). + +The function can be used for both a stereo camera head or a monocular camera (when R is empty). + +@param src Observed point coordinates, 1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2). +@param dst Output ideal point coordinates after undistortion and reverse perspective +transformation. If matrix P is identity or omitted, dst will contain normalized point coordinates. +@param cameraMatrix Camera matrix \f$\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . +@param distCoeffs Input vector of distortion coefficients +\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$ +of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed. +@param R Rectification transformation in the object space (3x3 matrix). R1 or R2 computed by +#stereoRectify can be passed here. If the matrix is empty, the identity transformation is used. +@param P New camera matrix (3x3) or new projection matrix (3x4) \f$\begin{bmatrix} {f'}_x & 0 & {c'}_x & t_x \\ 0 & {f'}_y & {c'}_y & t_y \\ 0 & 0 & 1 & t_z \end{bmatrix}\f$. P1 or P2 computed by +#stereoRectify can be passed here. If the matrix is empty, the identity new camera matrix is used. + */ +CV_EXPORTS_W void undistortPoints( InputArray src, OutputArray dst, + InputArray cameraMatrix, InputArray distCoeffs, + InputArray R = noArray(), InputArray P = noArray()); +/** @overload + @note Default version of #undistortPoints does 5 iterations to compute undistorted points. + + */ +CV_EXPORTS_AS(undistortPointsIter) void undistortPoints( InputArray src, OutputArray dst, + InputArray cameraMatrix, InputArray distCoeffs, + InputArray R, InputArray P, TermCriteria criteria); + +//! @} imgproc_transform + +//! @addtogroup imgproc_hist +//! @{ + +/** @example samples/cpp/demhist.cpp +An example for creating histograms of an image +*/ + +/** @brief Calculates a histogram of a set of arrays. + +The function cv::calcHist calculates the histogram of one or more arrays. The elements of a tuple used +to increment a histogram bin are taken from the corresponding input arrays at the same location. The +sample below shows how to compute a 2D Hue-Saturation histogram for a color image. : +@include snippets/imgproc_calcHist.cpp + +@param images Source arrays. They all should have the same depth, CV_8U, CV_16U or CV_32F , and the same +size. Each of them can have an arbitrary number of channels. +@param nimages Number of source images. +@param channels List of the dims channels used to compute the histogram. The first array channels +are numerated from 0 to images[0].channels()-1 , the second array channels are counted from +images[0].channels() to images[0].channels() + images[1].channels()-1, and so on. +@param mask Optional mask. If the matrix is not empty, it must be an 8-bit array of the same size +as images[i] . The non-zero mask elements mark the array elements counted in the histogram. +@param hist Output histogram, which is a dense or sparse dims -dimensional array. +@param dims Histogram dimensionality that must be positive and not greater than CV_MAX_DIMS +(equal to 32 in the current OpenCV version). +@param histSize Array of histogram sizes in each dimension. +@param ranges Array of the dims arrays of the histogram bin boundaries in each dimension. When the +histogram is uniform ( uniform =true), then for each dimension i it is enough to specify the lower +(inclusive) boundary \f$L_0\f$ of the 0-th histogram bin and the upper (exclusive) boundary +\f$U_{\texttt{histSize}[i]-1}\f$ for the last histogram bin histSize[i]-1 . That is, in case of a +uniform histogram each of ranges[i] is an array of 2 elements. When the histogram is not uniform ( +uniform=false ), then each of ranges[i] contains histSize[i]+1 elements: +\f$L_0, U_0=L_1, U_1=L_2, ..., U_{\texttt{histSize[i]}-2}=L_{\texttt{histSize[i]}-1}, U_{\texttt{histSize[i]}-1}\f$ +. The array elements, that are not between \f$L_0\f$ and \f$U_{\texttt{histSize[i]}-1}\f$ , are not +counted in the histogram. +@param uniform Flag indicating whether the histogram is uniform or not (see above). +@param accumulate Accumulation flag. If it is set, the histogram is not cleared in the beginning +when it is allocated. This feature enables you to compute a single histogram from several sets of +arrays, or to update the histogram in time. +*/ +CV_EXPORTS void calcHist( const Mat* images, int nimages, + const int* channels, InputArray mask, + OutputArray hist, int dims, const int* histSize, + const float** ranges, bool uniform = true, bool accumulate = false ); + +/** @overload + +this variant uses %SparseMat for output +*/ +CV_EXPORTS void calcHist( const Mat* images, int nimages, + const int* channels, InputArray mask, + SparseMat& hist, int dims, + const int* histSize, const float** ranges, + bool uniform = true, bool accumulate = false ); + +/** @overload */ +CV_EXPORTS_W void calcHist( InputArrayOfArrays images, + const std::vector& channels, + InputArray mask, OutputArray hist, + const std::vector& histSize, + const std::vector& ranges, + bool accumulate = false ); + +/** @brief Calculates the back projection of a histogram. + +The function cv::calcBackProject calculates the back project of the histogram. That is, similarly to +#calcHist , at each location (x, y) the function collects the values from the selected channels +in the input images and finds the corresponding histogram bin. But instead of incrementing it, the +function reads the bin value, scales it by scale , and stores in backProject(x,y) . In terms of +statistics, the function computes probability of each element value in respect with the empirical +probability distribution represented by the histogram. See how, for example, you can find and track +a bright-colored object in a scene: + +- Before tracking, show the object to the camera so that it covers almost the whole frame. +Calculate a hue histogram. The histogram may have strong maximums, corresponding to the dominant +colors in the object. + +- When tracking, calculate a back projection of a hue plane of each input video frame using that +pre-computed histogram. Threshold the back projection to suppress weak colors. It may also make +sense to suppress pixels with non-sufficient color saturation and too dark or too bright pixels. + +- Find connected components in the resulting picture and choose, for example, the largest +component. + +This is an approximate algorithm of the CamShift color object tracker. + +@param images Source arrays. They all should have the same depth, CV_8U, CV_16U or CV_32F , and the same +size. Each of them can have an arbitrary number of channels. +@param nimages Number of source images. +@param channels The list of channels used to compute the back projection. The number of channels +must match the histogram dimensionality. The first array channels are numerated from 0 to +images[0].channels()-1 , the second array channels are counted from images[0].channels() to +images[0].channels() + images[1].channels()-1, and so on. +@param hist Input histogram that can be dense or sparse. +@param backProject Destination back projection array that is a single-channel array of the same +size and depth as images[0] . +@param ranges Array of arrays of the histogram bin boundaries in each dimension. See #calcHist . +@param scale Optional scale factor for the output back projection. +@param uniform Flag indicating whether the histogram is uniform or not (see above). + +@sa calcHist, compareHist + */ +CV_EXPORTS void calcBackProject( const Mat* images, int nimages, + const int* channels, InputArray hist, + OutputArray backProject, const float** ranges, + double scale = 1, bool uniform = true ); + +/** @overload */ +CV_EXPORTS void calcBackProject( const Mat* images, int nimages, + const int* channels, const SparseMat& hist, + OutputArray backProject, const float** ranges, + double scale = 1, bool uniform = true ); + +/** @overload */ +CV_EXPORTS_W void calcBackProject( InputArrayOfArrays images, const std::vector& channels, + InputArray hist, OutputArray dst, + const std::vector& ranges, + double scale ); + +/** @brief Compares two histograms. + +The function cv::compareHist compares two dense or two sparse histograms using the specified method. + +The function returns \f$d(H_1, H_2)\f$ . + +While the function works well with 1-, 2-, 3-dimensional dense histograms, it may not be suitable +for high-dimensional sparse histograms. In such histograms, because of aliasing and sampling +problems, the coordinates of non-zero histogram bins can slightly shift. To compare such histograms +or more general sparse configurations of weighted points, consider using the #EMD function. + +@param H1 First compared histogram. +@param H2 Second compared histogram of the same size as H1 . +@param method Comparison method, see #HistCompMethods + */ +CV_EXPORTS_W double compareHist( InputArray H1, InputArray H2, int method ); + +/** @overload */ +CV_EXPORTS double compareHist( const SparseMat& H1, const SparseMat& H2, int method ); + +/** @brief Equalizes the histogram of a grayscale image. + +The function equalizes the histogram of the input image using the following algorithm: + +- Calculate the histogram \f$H\f$ for src . +- Normalize the histogram so that the sum of histogram bins is 255. +- Compute the integral of the histogram: +\f[H'_i = \sum _{0 \le j < i} H(j)\f] +- Transform the image using \f$H'\f$ as a look-up table: \f$\texttt{dst}(x,y) = H'(\texttt{src}(x,y))\f$ + +The algorithm normalizes the brightness and increases the contrast of the image. + +@param src Source 8-bit single channel image. +@param dst Destination image of the same size and type as src . + */ +CV_EXPORTS_W void equalizeHist( InputArray src, OutputArray dst ); + +/** @brief Creates a smart pointer to a cv::CLAHE class and initializes it. + +@param clipLimit Threshold for contrast limiting. +@param tileGridSize Size of grid for histogram equalization. Input image will be divided into +equally sized rectangular tiles. tileGridSize defines the number of tiles in row and column. + */ +CV_EXPORTS_W Ptr createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8)); + +/** @brief Computes the "minimal work" distance between two weighted point configurations. + +The function computes the earth mover distance and/or a lower boundary of the distance between the +two weighted point configurations. One of the applications described in @cite RubnerSept98, +@cite Rubner2000 is multi-dimensional histogram comparison for image retrieval. EMD is a transportation +problem that is solved using some modification of a simplex algorithm, thus the complexity is +exponential in the worst case, though, on average it is much faster. In the case of a real metric +the lower boundary can be calculated even faster (using linear-time algorithm) and it can be used +to determine roughly whether the two signatures are far enough so that they cannot relate to the +same object. + +@param signature1 First signature, a \f$\texttt{size1}\times \texttt{dims}+1\f$ floating-point matrix. +Each row stores the point weight followed by the point coordinates. The matrix is allowed to have +a single column (weights only) if the user-defined cost matrix is used. The weights must be +non-negative and have at least one non-zero value. +@param signature2 Second signature of the same format as signature1 , though the number of rows +may be different. The total weights may be different. In this case an extra "dummy" point is added +to either signature1 or signature2. The weights must be non-negative and have at least one non-zero +value. +@param distType Used metric. See #DistanceTypes. +@param cost User-defined \f$\texttt{size1}\times \texttt{size2}\f$ cost matrix. Also, if a cost matrix +is used, lower boundary lowerBound cannot be calculated because it needs a metric function. +@param lowerBound Optional input/output parameter: lower boundary of a distance between the two +signatures that is a distance between mass centers. The lower boundary may not be calculated if +the user-defined cost matrix is used, the total weights of point configurations are not equal, or +if the signatures consist of weights only (the signature matrices have a single column). You +**must** initialize \*lowerBound . If the calculated distance between mass centers is greater or +equal to \*lowerBound (it means that the signatures are far enough), the function does not +calculate EMD. In any case \*lowerBound is set to the calculated distance between mass centers on +return. Thus, if you want to calculate both distance between mass centers and EMD, \*lowerBound +should be set to 0. +@param flow Resultant \f$\texttt{size1} \times \texttt{size2}\f$ flow matrix: \f$\texttt{flow}_{i,j}\f$ is +a flow from \f$i\f$ -th point of signature1 to \f$j\f$ -th point of signature2 . + */ +CV_EXPORTS float EMD( InputArray signature1, InputArray signature2, + int distType, InputArray cost=noArray(), + float* lowerBound = 0, OutputArray flow = noArray() ); + +CV_EXPORTS_AS(EMD) float wrapperEMD( InputArray signature1, InputArray signature2, + int distType, InputArray cost=noArray(), + CV_IN_OUT Ptr lowerBound = Ptr(), OutputArray flow = noArray() ); + +//! @} imgproc_hist + +/** @example samples/cpp/watershed.cpp +An example using the watershed algorithm +*/ + +/** @brief Performs a marker-based image segmentation using the watershed algorithm. + +The function implements one of the variants of watershed, non-parametric marker-based segmentation +algorithm, described in @cite Meyer92 . + +Before passing the image to the function, you have to roughly outline the desired regions in the +image markers with positive (\>0) indices. So, every region is represented as one or more connected +components with the pixel values 1, 2, 3, and so on. Such markers can be retrieved from a binary +mask using #findContours and #drawContours (see the watershed.cpp demo). The markers are "seeds" of +the future image regions. All the other pixels in markers , whose relation to the outlined regions +is not known and should be defined by the algorithm, should be set to 0's. In the function output, +each pixel in markers is set to a value of the "seed" components or to -1 at boundaries between the +regions. + +@note Any two neighbor connected components are not necessarily separated by a watershed boundary +(-1's pixels); for example, they can touch each other in the initial marker image passed to the +function. + +@param image Input 8-bit 3-channel image. +@param markers Input/output 32-bit single-channel image (map) of markers. It should have the same +size as image . + +@sa findContours + +@ingroup imgproc_misc + */ +CV_EXPORTS_W void watershed( InputArray image, InputOutputArray markers ); + +//! @addtogroup imgproc_filter +//! @{ + +/** @brief Performs initial step of meanshift segmentation of an image. + +The function implements the filtering stage of meanshift segmentation, that is, the output of the +function is the filtered "posterized" image with color gradients and fine-grain texture flattened. +At every pixel (X,Y) of the input image (or down-sized input image, see below) the function executes +meanshift iterations, that is, the pixel (X,Y) neighborhood in the joint space-color hyperspace is +considered: + +\f[(x,y): X- \texttt{sp} \le x \le X+ \texttt{sp} , Y- \texttt{sp} \le y \le Y+ \texttt{sp} , ||(R,G,B)-(r,g,b)|| \le \texttt{sr}\f] + +where (R,G,B) and (r,g,b) are the vectors of color components at (X,Y) and (x,y), respectively +(though, the algorithm does not depend on the color space used, so any 3-component color space can +be used instead). Over the neighborhood the average spatial value (X',Y') and average color vector +(R',G',B') are found and they act as the neighborhood center on the next iteration: + +\f[(X,Y)~(X',Y'), (R,G,B)~(R',G',B').\f] + +After the iterations over, the color components of the initial pixel (that is, the pixel from where +the iterations started) are set to the final value (average color at the last iteration): + +\f[I(X,Y) <- (R*,G*,B*)\f] + +When maxLevel \> 0, the gaussian pyramid of maxLevel+1 levels is built, and the above procedure is +run on the smallest layer first. After that, the results are propagated to the larger layer and the +iterations are run again only on those pixels where the layer colors differ by more than sr from the +lower-resolution layer of the pyramid. That makes boundaries of color regions sharper. Note that the +results will be actually different from the ones obtained by running the meanshift procedure on the +whole original image (i.e. when maxLevel==0). + +@param src The source 8-bit, 3-channel image. +@param dst The destination image of the same format and the same size as the source. +@param sp The spatial window radius. +@param sr The color window radius. +@param maxLevel Maximum level of the pyramid for the segmentation. +@param termcrit Termination criteria: when to stop meanshift iterations. + */ +CV_EXPORTS_W void pyrMeanShiftFiltering( InputArray src, OutputArray dst, + double sp, double sr, int maxLevel = 1, + TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) ); + +//! @} + +//! @addtogroup imgproc_misc +//! @{ + +/** @example samples/cpp/grabcut.cpp +An example using the GrabCut algorithm +![Sample Screenshot](grabcut_output1.jpg) +*/ + +/** @brief Runs the GrabCut algorithm. + +The function implements the [GrabCut image segmentation algorithm](http://en.wikipedia.org/wiki/GrabCut). + +@param img Input 8-bit 3-channel image. +@param mask Input/output 8-bit single-channel mask. The mask is initialized by the function when +mode is set to #GC_INIT_WITH_RECT. Its elements may have one of the #GrabCutClasses. +@param rect ROI containing a segmented object. The pixels outside of the ROI are marked as +"obvious background". The parameter is only used when mode==#GC_INIT_WITH_RECT . +@param bgdModel Temporary array for the background model. Do not modify it while you are +processing the same image. +@param fgdModel Temporary arrays for the foreground model. Do not modify it while you are +processing the same image. +@param iterCount Number of iterations the algorithm should make before returning the result. Note +that the result can be refined with further calls with mode==#GC_INIT_WITH_MASK or +mode==GC_EVAL . +@param mode Operation mode that could be one of the #GrabCutModes + */ +CV_EXPORTS_W void grabCut( InputArray img, InputOutputArray mask, Rect rect, + InputOutputArray bgdModel, InputOutputArray fgdModel, + int iterCount, int mode = GC_EVAL ); + +/** @example samples/cpp/distrans.cpp +An example on using the distance transform +*/ + +/** @brief Calculates the distance to the closest zero pixel for each pixel of the source image. + +The function cv::distanceTransform calculates the approximate or precise distance from every binary +image pixel to the nearest zero pixel. For zero image pixels, the distance will obviously be zero. + +When maskSize == #DIST_MASK_PRECISE and distanceType == #DIST_L2 , the function runs the +algorithm described in @cite Felzenszwalb04 . This algorithm is parallelized with the TBB library. + +In other cases, the algorithm @cite Borgefors86 is used. This means that for a pixel the function +finds the shortest path to the nearest zero pixel consisting of basic shifts: horizontal, vertical, +diagonal, or knight's move (the latest is available for a \f$5\times 5\f$ mask). The overall +distance is calculated as a sum of these basic distances. Since the distance function should be +symmetric, all of the horizontal and vertical shifts must have the same cost (denoted as a ), all +the diagonal shifts must have the same cost (denoted as `b`), and all knight's moves must have the +same cost (denoted as `c`). For the #DIST_C and #DIST_L1 types, the distance is calculated +precisely, whereas for #DIST_L2 (Euclidean distance) the distance can be calculated only with a +relative error (a \f$5\times 5\f$ mask gives more accurate results). For `a`,`b`, and `c`, OpenCV +uses the values suggested in the original paper: +- DIST_L1: `a = 1, b = 2` +- DIST_L2: + - `3 x 3`: `a=0.955, b=1.3693` + - `5 x 5`: `a=1, b=1.4, c=2.1969` +- DIST_C: `a = 1, b = 1` + +Typically, for a fast, coarse distance estimation #DIST_L2, a \f$3\times 3\f$ mask is used. For a +more accurate distance estimation #DIST_L2, a \f$5\times 5\f$ mask or the precise algorithm is used. +Note that both the precise and the approximate algorithms are linear on the number of pixels. + +This variant of the function does not only compute the minimum distance for each pixel \f$(x, y)\f$ +but also identifies the nearest connected component consisting of zero pixels +(labelType==#DIST_LABEL_CCOMP) or the nearest zero pixel (labelType==#DIST_LABEL_PIXEL). Index of the +component/pixel is stored in `labels(x, y)`. When labelType==#DIST_LABEL_CCOMP, the function +automatically finds connected components of zero pixels in the input image and marks them with +distinct labels. When labelType==#DIST_LABEL_CCOMP, the function scans through the input image and +marks all the zero pixels with distinct labels. + +In this mode, the complexity is still linear. That is, the function provides a very fast way to +compute the Voronoi diagram for a binary image. Currently, the second variant can use only the +approximate distance transform algorithm, i.e. maskSize=#DIST_MASK_PRECISE is not supported +yet. + +@param src 8-bit, single-channel (binary) source image. +@param dst Output image with calculated distances. It is a 8-bit or 32-bit floating-point, +single-channel image of the same size as src. +@param labels Output 2D array of labels (the discrete Voronoi diagram). It has the type +CV_32SC1 and the same size as src. +@param distanceType Type of distance, see #DistanceTypes +@param maskSize Size of the distance transform mask, see #DistanceTransformMasks. +#DIST_MASK_PRECISE is not supported by this variant. In case of the #DIST_L1 or #DIST_C distance type, +the parameter is forced to 3 because a \f$3\times 3\f$ mask gives the same result as \f$5\times +5\f$ or any larger aperture. +@param labelType Type of the label array to build, see #DistanceTransformLabelTypes. + */ +CV_EXPORTS_AS(distanceTransformWithLabels) void distanceTransform( InputArray src, OutputArray dst, + OutputArray labels, int distanceType, int maskSize, + int labelType = DIST_LABEL_CCOMP ); + +/** @overload +@param src 8-bit, single-channel (binary) source image. +@param dst Output image with calculated distances. It is a 8-bit or 32-bit floating-point, +single-channel image of the same size as src . +@param distanceType Type of distance, see #DistanceTypes +@param maskSize Size of the distance transform mask, see #DistanceTransformMasks. In case of the +#DIST_L1 or #DIST_C distance type, the parameter is forced to 3 because a \f$3\times 3\f$ mask gives +the same result as \f$5\times 5\f$ or any larger aperture. +@param dstType Type of output image. It can be CV_8U or CV_32F. Type CV_8U can be used only for +the first variant of the function and distanceType == #DIST_L1. +*/ +CV_EXPORTS_W void distanceTransform( InputArray src, OutputArray dst, + int distanceType, int maskSize, int dstType=CV_32F); + +/** @example samples/cpp/ffilldemo.cpp +An example using the FloodFill technique +*/ + +/** @overload + +variant without `mask` parameter +*/ +CV_EXPORTS int floodFill( InputOutputArray image, + Point seedPoint, Scalar newVal, CV_OUT Rect* rect = 0, + Scalar loDiff = Scalar(), Scalar upDiff = Scalar(), + int flags = 4 ); + +/** @brief Fills a connected component with the given color. + +The function cv::floodFill fills a connected component starting from the seed point with the specified +color. The connectivity is determined by the color/brightness closeness of the neighbor pixels. The +pixel at \f$(x,y)\f$ is considered to belong to the repainted domain if: + +- in case of a grayscale image and floating range +\f[\texttt{src} (x',y')- \texttt{loDiff} \leq \texttt{src} (x,y) \leq \texttt{src} (x',y')+ \texttt{upDiff}\f] + + +- in case of a grayscale image and fixed range +\f[\texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)- \texttt{loDiff} \leq \texttt{src} (x,y) \leq \texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)+ \texttt{upDiff}\f] + + +- in case of a color image and floating range +\f[\texttt{src} (x',y')_r- \texttt{loDiff} _r \leq \texttt{src} (x,y)_r \leq \texttt{src} (x',y')_r+ \texttt{upDiff} _r,\f] +\f[\texttt{src} (x',y')_g- \texttt{loDiff} _g \leq \texttt{src} (x,y)_g \leq \texttt{src} (x',y')_g+ \texttt{upDiff} _g\f] +and +\f[\texttt{src} (x',y')_b- \texttt{loDiff} _b \leq \texttt{src} (x,y)_b \leq \texttt{src} (x',y')_b+ \texttt{upDiff} _b\f] + + +- in case of a color image and fixed range +\f[\texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_r- \texttt{loDiff} _r \leq \texttt{src} (x,y)_r \leq \texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_r+ \texttt{upDiff} _r,\f] +\f[\texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_g- \texttt{loDiff} _g \leq \texttt{src} (x,y)_g \leq \texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_g+ \texttt{upDiff} _g\f] +and +\f[\texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_b- \texttt{loDiff} _b \leq \texttt{src} (x,y)_b \leq \texttt{src} ( \texttt{seedPoint} .x, \texttt{seedPoint} .y)_b+ \texttt{upDiff} _b\f] + + +where \f$src(x',y')\f$ is the value of one of pixel neighbors that is already known to belong to the +component. That is, to be added to the connected component, a color/brightness of the pixel should +be close enough to: +- Color/brightness of one of its neighbors that already belong to the connected component in case +of a floating range. +- Color/brightness of the seed point in case of a fixed range. + +Use these functions to either mark a connected component with the specified color in-place, or build +a mask and then extract the contour, or copy the region to another image, and so on. + +@param image Input/output 1- or 3-channel, 8-bit, or floating-point image. It is modified by the +function unless the #FLOODFILL_MASK_ONLY flag is set in the second variant of the function. See +the details below. +@param mask Operation mask that should be a single-channel 8-bit image, 2 pixels wider and 2 pixels +taller than image. Since this is both an input and output parameter, you must take responsibility +of initializing it. Flood-filling cannot go across non-zero pixels in the input mask. For example, +an edge detector output can be used as a mask to stop filling at edges. On output, pixels in the +mask corresponding to filled pixels in the image are set to 1 or to the a value specified in flags +as described below. Additionally, the function fills the border of the mask with ones to simplify +internal processing. It is therefore possible to use the same mask in multiple calls to the function +to make sure the filled areas do not overlap. +@param seedPoint Starting point. +@param newVal New value of the repainted domain pixels. +@param loDiff Maximal lower brightness/color difference between the currently observed pixel and +one of its neighbors belonging to the component, or a seed pixel being added to the component. +@param upDiff Maximal upper brightness/color difference between the currently observed pixel and +one of its neighbors belonging to the component, or a seed pixel being added to the component. +@param rect Optional output parameter set by the function to the minimum bounding rectangle of the +repainted domain. +@param flags Operation flags. The first 8 bits contain a connectivity value. The default value of +4 means that only the four nearest neighbor pixels (those that share an edge) are considered. A +connectivity value of 8 means that the eight nearest neighbor pixels (those that share a corner) +will be considered. The next 8 bits (8-16) contain a value between 1 and 255 with which to fill +the mask (the default value is 1). For example, 4 | ( 255 \<\< 8 ) will consider 4 nearest +neighbours and fill the mask with a value of 255. The following additional options occupy higher +bits and therefore may be further combined with the connectivity and mask fill values using +bit-wise or (|), see #FloodFillFlags. + +@note Since the mask is larger than the filled image, a pixel \f$(x, y)\f$ in image corresponds to the +pixel \f$(x+1, y+1)\f$ in the mask . + +@sa findContours + */ +CV_EXPORTS_W int floodFill( InputOutputArray image, InputOutputArray mask, + Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0, + Scalar loDiff = Scalar(), Scalar upDiff = Scalar(), + int flags = 4 ); + +//! Performs linear blending of two images: +//! \f[ \texttt{dst}(i,j) = \texttt{weights1}(i,j)*\texttt{src1}(i,j) + \texttt{weights2}(i,j)*\texttt{src2}(i,j) \f] +//! @param src1 It has a type of CV_8UC(n) or CV_32FC(n), where n is a positive integer. +//! @param src2 It has the same type and size as src1. +//! @param weights1 It has a type of CV_32FC1 and the same size with src1. +//! @param weights2 It has a type of CV_32FC1 and the same size with src1. +//! @param dst It is created if it does not have the same size and type with src1. +CV_EXPORTS void blendLinear(InputArray src1, InputArray src2, InputArray weights1, InputArray weights2, OutputArray dst); + +//! @} imgproc_misc + +//! @addtogroup imgproc_color_conversions +//! @{ + +/** @brief Converts an image from one color space to another. + +The function converts an input image from one color space to another. In case of a transformation +to-from RGB color space, the order of the channels should be specified explicitly (RGB or BGR). Note +that the default color format in OpenCV is often referred to as RGB but it is actually BGR (the +bytes are reversed). So the first byte in a standard (24-bit) color image will be an 8-bit Blue +component, the second byte will be Green, and the third byte will be Red. The fourth, fifth, and +sixth bytes would then be the second pixel (Blue, then Green, then Red), and so on. + +The conventional ranges for R, G, and B channel values are: +- 0 to 255 for CV_8U images +- 0 to 65535 for CV_16U images +- 0 to 1 for CV_32F images + +In case of linear transformations, the range does not matter. But in case of a non-linear +transformation, an input RGB image should be normalized to the proper value range to get the correct +results, for example, for RGB \f$\rightarrow\f$ L\*u\*v\* transformation. For example, if you have a +32-bit floating-point image directly converted from an 8-bit image without any scaling, then it will +have the 0..255 value range instead of 0..1 assumed by the function. So, before calling #cvtColor , +you need first to scale the image down: +@code + img *= 1./255; + cvtColor(img, img, COLOR_BGR2Luv); +@endcode +If you use #cvtColor with 8-bit images, the conversion will have some information lost. For many +applications, this will not be noticeable but it is recommended to use 32-bit images in applications +that need the full range of colors or that convert an image before an operation and then convert +back. + +If conversion adds the alpha channel, its value will set to the maximum of corresponding channel +range: 255 for CV_8U, 65535 for CV_16U, 1 for CV_32F. + +@param src input image: 8-bit unsigned, 16-bit unsigned ( CV_16UC... ), or single-precision +floating-point. +@param dst output image of the same size and depth as src. +@param code color space conversion code (see #ColorConversionCodes). +@param dstCn number of channels in the destination image; if the parameter is 0, the number of the +channels is derived automatically from src and code. + +@see @ref imgproc_color_conversions + */ +CV_EXPORTS_W void cvtColor( InputArray src, OutputArray dst, int code, int dstCn = 0 ); + +/** @brief Converts an image from one color space to another where the source image is +stored in two planes. + +This function only supports YUV420 to RGB conversion as of now. + +@param src1: 8-bit image (#CV_8U) of the Y plane. +@param src2: image containing interleaved U/V plane. +@param dst: output image. +@param code: Specifies the type of conversion. It can take any of the following values: +- #COLOR_YUV2BGR_NV12 +- #COLOR_YUV2RGB_NV12 +- #COLOR_YUV2BGRA_NV12 +- #COLOR_YUV2RGBA_NV12 +- #COLOR_YUV2BGR_NV21 +- #COLOR_YUV2RGB_NV21 +- #COLOR_YUV2BGRA_NV21 +- #COLOR_YUV2RGBA_NV21 +*/ +CV_EXPORTS_W void cvtColorTwoPlane( InputArray src1, InputArray src2, OutputArray dst, int code ); + +/** @brief main function for all demosaicing processes + +@param src input image: 8-bit unsigned or 16-bit unsigned. +@param dst output image of the same size and depth as src. +@param code Color space conversion code (see the description below). +@param dstCn number of channels in the destination image; if the parameter is 0, the number of the +channels is derived automatically from src and code. + +The function can do the following transformations: + +- Demosaicing using bilinear interpolation + + #COLOR_BayerBG2BGR , #COLOR_BayerGB2BGR , #COLOR_BayerRG2BGR , #COLOR_BayerGR2BGR + + #COLOR_BayerBG2GRAY , #COLOR_BayerGB2GRAY , #COLOR_BayerRG2GRAY , #COLOR_BayerGR2GRAY + +- Demosaicing using Variable Number of Gradients. + + #COLOR_BayerBG2BGR_VNG , #COLOR_BayerGB2BGR_VNG , #COLOR_BayerRG2BGR_VNG , #COLOR_BayerGR2BGR_VNG + +- Edge-Aware Demosaicing. + + #COLOR_BayerBG2BGR_EA , #COLOR_BayerGB2BGR_EA , #COLOR_BayerRG2BGR_EA , #COLOR_BayerGR2BGR_EA + +- Demosaicing with alpha channel + + #COLOR_BayerBG2BGRA , #COLOR_BayerGB2BGRA , #COLOR_BayerRG2BGRA , #COLOR_BayerGR2BGRA + +@sa cvtColor +*/ +CV_EXPORTS_W void demosaicing(InputArray src, OutputArray dst, int code, int dstCn = 0); + +//! @} imgproc_color_conversions + +//! @addtogroup imgproc_shape +//! @{ + +/** @brief Calculates all of the moments up to the third order of a polygon or rasterized shape. + +The function computes moments, up to the 3rd order, of a vector shape or a rasterized shape. The +results are returned in the structure cv::Moments. + +@param array Raster image (single-channel, 8-bit or floating-point 2D array) or an array ( +\f$1 \times N\f$ or \f$N \times 1\f$ ) of 2D points (Point or Point2f ). +@param binaryImage If it is true, all non-zero image pixels are treated as 1's. The parameter is +used for images only. +@returns moments. + +@note Only applicable to contour moments calculations from Python bindings: Note that the numpy +type for the input array should be either np.int32 or np.float32. + +@sa contourArea, arcLength + */ +CV_EXPORTS_W Moments moments( InputArray array, bool binaryImage = false ); + +/** @brief Calculates seven Hu invariants. + +The function calculates seven Hu invariants (introduced in @cite Hu62; see also +) defined as: + +\f[\begin{array}{l} hu[0]= \eta _{20}+ \eta _{02} \\ hu[1]=( \eta _{20}- \eta _{02})^{2}+4 \eta _{11}^{2} \\ hu[2]=( \eta _{30}-3 \eta _{12})^{2}+ (3 \eta _{21}- \eta _{03})^{2} \\ hu[3]=( \eta _{30}+ \eta _{12})^{2}+ ( \eta _{21}+ \eta _{03})^{2} \\ hu[4]=( \eta _{30}-3 \eta _{12})( \eta _{30}+ \eta _{12})[( \eta _{30}+ \eta _{12})^{2}-3( \eta _{21}+ \eta _{03})^{2}]+(3 \eta _{21}- \eta _{03})( \eta _{21}+ \eta _{03})[3( \eta _{30}+ \eta _{12})^{2}-( \eta _{21}+ \eta _{03})^{2}] \\ hu[5]=( \eta _{20}- \eta _{02})[( \eta _{30}+ \eta _{12})^{2}- ( \eta _{21}+ \eta _{03})^{2}]+4 \eta _{11}( \eta _{30}+ \eta _{12})( \eta _{21}+ \eta _{03}) \\ hu[6]=(3 \eta _{21}- \eta _{03})( \eta _{21}+ \eta _{03})[3( \eta _{30}+ \eta _{12})^{2}-( \eta _{21}+ \eta _{03})^{2}]-( \eta _{30}-3 \eta _{12})( \eta _{21}+ \eta _{03})[3( \eta _{30}+ \eta _{12})^{2}-( \eta _{21}+ \eta _{03})^{2}] \\ \end{array}\f] + +where \f$\eta_{ji}\f$ stands for \f$\texttt{Moments::nu}_{ji}\f$ . + +These values are proved to be invariants to the image scale, rotation, and reflection except the +seventh one, whose sign is changed by reflection. This invariance is proved with the assumption of +infinite image resolution. In case of raster images, the computed Hu invariants for the original and +transformed images are a bit different. + +@param moments Input moments computed with moments . +@param hu Output Hu invariants. + +@sa matchShapes + */ +CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] ); + +/** @overload */ +CV_EXPORTS_W void HuMoments( const Moments& m, OutputArray hu ); + +//! @} imgproc_shape + +//! @addtogroup imgproc_object +//! @{ + +//! type of the template matching operation +enum TemplateMatchModes { + TM_SQDIFF = 0, //!< \f[R(x,y)= \sum _{x',y'} (T(x',y')-I(x+x',y+y'))^2\f] + TM_SQDIFF_NORMED = 1, //!< \f[R(x,y)= \frac{\sum_{x',y'} (T(x',y')-I(x+x',y+y'))^2}{\sqrt{\sum_{x',y'}T(x',y')^2 \cdot \sum_{x',y'} I(x+x',y+y')^2}}\f] + TM_CCORR = 2, //!< \f[R(x,y)= \sum _{x',y'} (T(x',y') \cdot I(x+x',y+y'))\f] + TM_CCORR_NORMED = 3, //!< \f[R(x,y)= \frac{\sum_{x',y'} (T(x',y') \cdot I(x+x',y+y'))}{\sqrt{\sum_{x',y'}T(x',y')^2 \cdot \sum_{x',y'} I(x+x',y+y')^2}}\f] + TM_CCOEFF = 4, //!< \f[R(x,y)= \sum _{x',y'} (T'(x',y') \cdot I'(x+x',y+y'))\f] + //!< where + //!< \f[\begin{array}{l} T'(x',y')=T(x',y') - 1/(w \cdot h) \cdot \sum _{x'',y''} T(x'',y'') \\ I'(x+x',y+y')=I(x+x',y+y') - 1/(w \cdot h) \cdot \sum _{x'',y''} I(x+x'',y+y'') \end{array}\f] + TM_CCOEFF_NORMED = 5 //!< \f[R(x,y)= \frac{ \sum_{x',y'} (T'(x',y') \cdot I'(x+x',y+y')) }{ \sqrt{\sum_{x',y'}T'(x',y')^2 \cdot \sum_{x',y'} I'(x+x',y+y')^2} }\f] +}; + +/** @example samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp +An example using Template Matching algorithm +*/ + +/** @brief Compares a template against overlapped image regions. + +The function slides through image , compares the overlapped patches of size \f$w \times h\f$ against +templ using the specified method and stores the comparison results in result . Here are the formulae +for the available comparison methods ( \f$I\f$ denotes image, \f$T\f$ template, \f$R\f$ result ). The summation +is done over template and/or the image patch: \f$x' = 0...w-1, y' = 0...h-1\f$ + +After the function finishes the comparison, the best matches can be found as global minimums (when +#TM_SQDIFF was used) or maximums (when #TM_CCORR or #TM_CCOEFF was used) using the +#minMaxLoc function. In case of a color image, template summation in the numerator and each sum in +the denominator is done over all of the channels and separate mean values are used for each channel. +That is, the function can take a color template and a color image. The result will still be a +single-channel image, which is easier to analyze. + +@param image Image where the search is running. It must be 8-bit or 32-bit floating-point. +@param templ Searched template. It must be not greater than the source image and have the same +data type. +@param result Map of comparison results. It must be single-channel 32-bit floating-point. If image +is \f$W \times H\f$ and templ is \f$w \times h\f$ , then result is \f$(W-w+1) \times (H-h+1)\f$ . +@param method Parameter specifying the comparison method, see #TemplateMatchModes +@param mask Mask of searched template. It must have the same datatype and size with templ. It is +not set by default. Currently, only the #TM_SQDIFF and #TM_CCORR_NORMED methods are supported. + */ +CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ, + OutputArray result, int method, InputArray mask = noArray() ); + +//! @} + +//! @addtogroup imgproc_shape +//! @{ + +/** @example samples/cpp/connected_components.cpp +This program demonstrates connected components and use of the trackbar +*/ + +/** @brief computes the connected components labeled image of boolean image + +image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 +represents the background label. ltype specifies the output label image type, an important +consideration based on the total number of labels or alternatively the total number of pixels in +the source image. ccltype specifies the connected components labeling algorithm to use, currently +Grana (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes +for details. Note that SAUF algorithm forces a row major ordering of labels while BBDT does not. +This function uses parallel version of both Grana and Wu's algorithms if at least one allowed +parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs. + +@param image the 8-bit single-channel image to be labeled +@param labels destination labeled image +@param connectivity 8 or 4 for 8-way or 4-way connectivity respectively +@param ltype output image label type. Currently CV_32S and CV_16U are supported. +@param ccltype connected components algorithm type (see the #ConnectedComponentsAlgorithmsTypes). +*/ +CV_EXPORTS_AS(connectedComponentsWithAlgorithm) int connectedComponents(InputArray image, OutputArray labels, + int connectivity, int ltype, int ccltype); + + +/** @overload + +@param image the 8-bit single-channel image to be labeled +@param labels destination labeled image +@param connectivity 8 or 4 for 8-way or 4-way connectivity respectively +@param ltype output image label type. Currently CV_32S and CV_16U are supported. +*/ +CV_EXPORTS_W int connectedComponents(InputArray image, OutputArray labels, + int connectivity = 8, int ltype = CV_32S); + + +/** @brief computes the connected components labeled image of boolean image and also produces a statistics output for each label + +image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 +represents the background label. ltype specifies the output label image type, an important +consideration based on the total number of labels or alternatively the total number of pixels in +the source image. ccltype specifies the connected components labeling algorithm to use, currently +Grana's (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes +for details. Note that SAUF algorithm forces a row major ordering of labels while BBDT does not. +This function uses parallel version of both Grana and Wu's algorithms (statistics included) if at least one allowed +parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs. + +@param image the 8-bit single-channel image to be labeled +@param labels destination labeled image +@param stats statistics output for each label, including the background label, see below for +available statistics. Statistics are accessed via stats(label, COLUMN) where COLUMN is one of +#ConnectedComponentsTypes. The data type is CV_32S. +@param centroids centroid output for each label, including the background label. Centroids are +accessed via centroids(label, 0) for x and centroids(label, 1) for y. The data type CV_64F. +@param connectivity 8 or 4 for 8-way or 4-way connectivity respectively +@param ltype output image label type. Currently CV_32S and CV_16U are supported. +@param ccltype connected components algorithm type (see #ConnectedComponentsAlgorithmsTypes). +*/ +CV_EXPORTS_AS(connectedComponentsWithStatsWithAlgorithm) int connectedComponentsWithStats(InputArray image, OutputArray labels, + OutputArray stats, OutputArray centroids, + int connectivity, int ltype, int ccltype); + +/** @overload +@param image the 8-bit single-channel image to be labeled +@param labels destination labeled image +@param stats statistics output for each label, including the background label, see below for +available statistics. Statistics are accessed via stats(label, COLUMN) where COLUMN is one of +#ConnectedComponentsTypes. The data type is CV_32S. +@param centroids centroid output for each label, including the background label. Centroids are +accessed via centroids(label, 0) for x and centroids(label, 1) for y. The data type CV_64F. +@param connectivity 8 or 4 for 8-way or 4-way connectivity respectively +@param ltype output image label type. Currently CV_32S and CV_16U are supported. +*/ +CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labels, + OutputArray stats, OutputArray centroids, + int connectivity = 8, int ltype = CV_32S); + + +/** @brief Finds contours in a binary image. + +The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours +are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the +OpenCV sample directory. +@note Since opencv 3.2 source image is not modified by this function. + +@param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero +pixels remain 0's, so the image is treated as binary . You can use #compare, #inRange, #threshold , +#adaptiveThreshold, #Canny, and others to create a binary image out of a grayscale or color one. +If mode equals to #RETR_CCOMP or #RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1). +@param contours Detected contours. Each contour is stored as a vector of points (e.g. +std::vector >). +@param hierarchy Optional output vector (e.g. std::vector), containing information about the image topology. It has +as many elements as the number of contours. For each i-th contour contours[i], the elements +hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices +in contours of the next and previous contours at the same hierarchical level, the first child +contour and the parent contour, respectively. If for the contour i there are no next, previous, +parent, or nested contours, the corresponding elements of hierarchy[i] will be negative. +@param mode Contour retrieval mode, see #RetrievalModes +@param method Contour approximation method, see #ContourApproximationModes +@param offset Optional offset by which every contour point is shifted. This is useful if the +contours are extracted from the image ROI and then they should be analyzed in the whole image +context. + */ +CV_EXPORTS_W void findContours( InputOutputArray image, OutputArrayOfArrays contours, + OutputArray hierarchy, int mode, + int method, Point offset = Point()); + +/** @overload */ +CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours, + int mode, int method, Point offset = Point()); + +/** @example samples/cpp/squares.cpp +A program using pyramid scaling, Canny, contours and contour simplification to find +squares in a list of images (pic1-6.png). Returns sequence of squares detected on the image. +*/ + +/** @example samples/tapi/squares.cpp +A program using pyramid scaling, Canny, contours and contour simplification to find +squares in the input image. +*/ + +/** @brief Approximates a polygonal curve(s) with the specified precision. + +The function cv::approxPolyDP approximates a curve or a polygon with another curve/polygon with less +vertices so that the distance between them is less or equal to the specified precision. It uses the +Douglas-Peucker algorithm + +@param curve Input vector of a 2D point stored in std::vector or Mat +@param approxCurve Result of the approximation. The type should match the type of the input curve. +@param epsilon Parameter specifying the approximation accuracy. This is the maximum distance +between the original curve and its approximation. +@param closed If true, the approximated curve is closed (its first and last vertices are +connected). Otherwise, it is not closed. + */ +CV_EXPORTS_W void approxPolyDP( InputArray curve, + OutputArray approxCurve, + double epsilon, bool closed ); + +/** @brief Calculates a contour perimeter or a curve length. + +The function computes a curve length or a closed contour perimeter. + +@param curve Input vector of 2D points, stored in std::vector or Mat. +@param closed Flag indicating whether the curve is closed or not. + */ +CV_EXPORTS_W double arcLength( InputArray curve, bool closed ); + +/** @brief Calculates the up-right bounding rectangle of a point set or non-zero pixels of gray-scale image. + +The function calculates and returns the minimal up-right bounding rectangle for the specified point set or +non-zero pixels of gray-scale image. + +@param array Input gray-scale image or 2D point set, stored in std::vector or Mat. + */ +CV_EXPORTS_W Rect boundingRect( InputArray array ); + +/** @brief Calculates a contour area. + +The function computes a contour area. Similarly to moments , the area is computed using the Green +formula. Thus, the returned area and the number of non-zero pixels, if you draw the contour using +#drawContours or #fillPoly , can be different. Also, the function will most certainly give a wrong +results for contours with self-intersections. + +Example: +@code + vector contour; + contour.push_back(Point2f(0, 0)); + contour.push_back(Point2f(10, 0)); + contour.push_back(Point2f(10, 10)); + contour.push_back(Point2f(5, 4)); + + double area0 = contourArea(contour); + vector approx; + approxPolyDP(contour, approx, 5, true); + double area1 = contourArea(approx); + + cout << "area0 =" << area0 << endl << + "area1 =" << area1 << endl << + "approx poly vertices" << approx.size() << endl; +@endcode +@param contour Input vector of 2D points (contour vertices), stored in std::vector or Mat. +@param oriented Oriented area flag. If it is true, the function returns a signed area value, +depending on the contour orientation (clockwise or counter-clockwise). Using this feature you can +determine orientation of a contour by taking the sign of an area. By default, the parameter is +false, which means that the absolute value is returned. + */ +CV_EXPORTS_W double contourArea( InputArray contour, bool oriented = false ); + +/** @brief Finds a rotated rectangle of the minimum area enclosing the input 2D point set. + +The function calculates and returns the minimum-area bounding rectangle (possibly rotated) for a +specified point set. Developer should keep in mind that the returned RotatedRect can contain negative +indices when data is close to the containing Mat element boundary. + +@param points Input vector of 2D points, stored in std::vector\<\> or Mat + */ +CV_EXPORTS_W RotatedRect minAreaRect( InputArray points ); + +/** @brief Finds the four vertices of a rotated rect. Useful to draw the rotated rectangle. + +The function finds the four vertices of a rotated rectangle. This function is useful to draw the +rectangle. In C++, instead of using this function, you can directly use RotatedRect::points method. Please +visit the @ref tutorial_bounding_rotated_ellipses "tutorial on Creating Bounding rotated boxes and ellipses for contours" for more information. + +@param box The input rotated rectangle. It may be the output of +@param points The output array of four vertices of rectangles. + */ +CV_EXPORTS_W void boxPoints(RotatedRect box, OutputArray points); + +/** @brief Finds a circle of the minimum area enclosing a 2D point set. + +The function finds the minimal enclosing circle of a 2D point set using an iterative algorithm. + +@param points Input vector of 2D points, stored in std::vector\<\> or Mat +@param center Output center of the circle. +@param radius Output radius of the circle. + */ +CV_EXPORTS_W void minEnclosingCircle( InputArray points, + CV_OUT Point2f& center, CV_OUT float& radius ); + +/** @example samples/cpp/minarea.cpp +*/ + +/** @brief Finds a triangle of minimum area enclosing a 2D point set and returns its area. + +The function finds a triangle of minimum area enclosing the given set of 2D points and returns its +area. The output for a given 2D point set is shown in the image below. 2D points are depicted in +*red* and the enclosing triangle in *yellow*. + +![Sample output of the minimum enclosing triangle function](pics/minenclosingtriangle.png) + +The implementation of the algorithm is based on O'Rourke's @cite ORourke86 and Klee and Laskowski's +@cite KleeLaskowski85 papers. O'Rourke provides a \f$\theta(n)\f$ algorithm for finding the minimal +enclosing triangle of a 2D convex polygon with n vertices. Since the #minEnclosingTriangle function +takes a 2D point set as input an additional preprocessing step of computing the convex hull of the +2D point set is required. The complexity of the #convexHull function is \f$O(n log(n))\f$ which is higher +than \f$\theta(n)\f$. Thus the overall complexity of the function is \f$O(n log(n))\f$. + +@param points Input vector of 2D points with depth CV_32S or CV_32F, stored in std::vector\<\> or Mat +@param triangle Output vector of three 2D points defining the vertices of the triangle. The depth +of the OutputArray must be CV_32F. + */ +CV_EXPORTS_W double minEnclosingTriangle( InputArray points, CV_OUT OutputArray triangle ); + +/** @brief Compares two shapes. + +The function compares two shapes. All three implemented methods use the Hu invariants (see #HuMoments) + +@param contour1 First contour or grayscale image. +@param contour2 Second contour or grayscale image. +@param method Comparison method, see #ShapeMatchModes +@param parameter Method-specific parameter (not supported now). + */ +CV_EXPORTS_W double matchShapes( InputArray contour1, InputArray contour2, + int method, double parameter ); + +/** @example samples/cpp/convexhull.cpp +An example using the convexHull functionality +*/ + +/** @brief Finds the convex hull of a point set. + +The function cv::convexHull finds the convex hull of a 2D point set using the Sklansky's algorithm @cite Sklansky82 +that has *O(N logN)* complexity in the current implementation. + +@param points Input 2D point set, stored in std::vector or Mat. +@param hull Output convex hull. It is either an integer vector of indices or vector of points. In +the first case, the hull elements are 0-based indices of the convex hull points in the original +array (since the set of convex hull points is a subset of the original point set). In the second +case, hull elements are the convex hull points themselves. +@param clockwise Orientation flag. If it is true, the output convex hull is oriented clockwise. +Otherwise, it is oriented counter-clockwise. The assumed coordinate system has its X axis pointing +to the right, and its Y axis pointing upwards. +@param returnPoints Operation flag. In case of a matrix, when the flag is true, the function +returns convex hull points. Otherwise, it returns indices of the convex hull points. When the +output array is std::vector, the flag is ignored, and the output depends on the type of the +vector: std::vector\ implies returnPoints=false, std::vector\ implies +returnPoints=true. + +@note `points` and `hull` should be different arrays, inplace processing isn't supported. + +Check @ref tutorial_hull "the corresponding tutorial" for more details. + +useful links: + +https://www.learnopencv.com/convex-hull-using-opencv-in-python-and-c/ + */ +CV_EXPORTS_W void convexHull( InputArray points, OutputArray hull, + bool clockwise = false, bool returnPoints = true ); + +/** @brief Finds the convexity defects of a contour. + +The figure below displays convexity defects of a hand contour: + +![image](pics/defects.png) + +@param contour Input contour. +@param convexhull Convex hull obtained using convexHull that should contain indices of the contour +points that make the hull. +@param convexityDefects The output vector of convexity defects. In C++ and the new Python/Java +interface each convexity defect is represented as 4-element integer vector (a.k.a. #Vec4i): +(start_index, end_index, farthest_pt_index, fixpt_depth), where indices are 0-based indices +in the original contour of the convexity defect beginning, end and the farthest point, and +fixpt_depth is fixed-point approximation (with 8 fractional bits) of the distance between the +farthest contour point and the hull. That is, to get the floating-point value of the depth will be +fixpt_depth/256.0. + */ +CV_EXPORTS_W void convexityDefects( InputArray contour, InputArray convexhull, OutputArray convexityDefects ); + +/** @brief Tests a contour convexity. + +The function tests whether the input contour is convex or not. The contour must be simple, that is, +without self-intersections. Otherwise, the function output is undefined. + +@param contour Input vector of 2D points, stored in std::vector\<\> or Mat + */ +CV_EXPORTS_W bool isContourConvex( InputArray contour ); + +//! finds intersection of two convex polygons +CV_EXPORTS_W float intersectConvexConvex( InputArray _p1, InputArray _p2, + OutputArray _p12, bool handleNested = true ); + +/** @example samples/cpp/fitellipse.cpp +An example using the fitEllipse technique +*/ + +/** @brief Fits an ellipse around a set of 2D points. + +The function calculates the ellipse that fits (in a least-squares sense) a set of 2D points best of +all. It returns the rotated rectangle in which the ellipse is inscribed. The first algorithm described by @cite Fitzgibbon95 +is used. Developer should keep in mind that it is possible that the returned +ellipse/rotatedRect data contains negative indices, due to the data points being close to the +border of the containing Mat element. + +@param points Input 2D point set, stored in std::vector\<\> or Mat + */ +CV_EXPORTS_W RotatedRect fitEllipse( InputArray points ); + +/** @brief Fits an ellipse around a set of 2D points. + + The function calculates the ellipse that fits a set of 2D points. + It returns the rotated rectangle in which the ellipse is inscribed. + The Approximate Mean Square (AMS) proposed by @cite Taubin1991 is used. + + For an ellipse, this basis set is \f$ \chi= \left(x^2, x y, y^2, x, y, 1\right) \f$, + which is a set of six free coefficients \f$ A^T=\left\{A_{\text{xx}},A_{\text{xy}},A_{\text{yy}},A_x,A_y,A_0\right\} \f$. + However, to specify an ellipse, all that is needed is five numbers; the major and minor axes lengths \f$ (a,b) \f$, + the position \f$ (x_0,y_0) \f$, and the orientation \f$ \theta \f$. This is because the basis set includes lines, + quadratics, parabolic and hyperbolic functions as well as elliptical functions as possible fits. + If the fit is found to be a parabolic or hyperbolic function then the standard #fitEllipse method is used. + The AMS method restricts the fit to parabolic, hyperbolic and elliptical curves + by imposing the condition that \f$ A^T ( D_x^T D_x + D_y^T D_y) A = 1 \f$ where + the matrices \f$ Dx \f$ and \f$ Dy \f$ are the partial derivatives of the design matrix \f$ D \f$ with + respect to x and y. The matrices are formed row by row applying the following to + each of the points in the set: + \f{align*}{ + D(i,:)&=\left\{x_i^2, x_i y_i, y_i^2, x_i, y_i, 1\right\} & + D_x(i,:)&=\left\{2 x_i,y_i,0,1,0,0\right\} & + D_y(i,:)&=\left\{0,x_i,2 y_i,0,1,0\right\} + \f} + The AMS method minimizes the cost function + \f{equation*}{ + \epsilon ^2=\frac{ A^T D^T D A }{ A^T (D_x^T D_x + D_y^T D_y) A^T } + \f} + + The minimum cost is found by solving the generalized eigenvalue problem. + + \f{equation*}{ + D^T D A = \lambda \left( D_x^T D_x + D_y^T D_y\right) A + \f} + + @param points Input 2D point set, stored in std::vector\<\> or Mat + */ +CV_EXPORTS_W RotatedRect fitEllipseAMS( InputArray points ); + + +/** @brief Fits an ellipse around a set of 2D points. + + The function calculates the ellipse that fits a set of 2D points. + It returns the rotated rectangle in which the ellipse is inscribed. + The Direct least square (Direct) method by @cite Fitzgibbon1999 is used. + + For an ellipse, this basis set is \f$ \chi= \left(x^2, x y, y^2, x, y, 1\right) \f$, + which is a set of six free coefficients \f$ A^T=\left\{A_{\text{xx}},A_{\text{xy}},A_{\text{yy}},A_x,A_y,A_0\right\} \f$. + However, to specify an ellipse, all that is needed is five numbers; the major and minor axes lengths \f$ (a,b) \f$, + the position \f$ (x_0,y_0) \f$, and the orientation \f$ \theta \f$. This is because the basis set includes lines, + quadratics, parabolic and hyperbolic functions as well as elliptical functions as possible fits. + The Direct method confines the fit to ellipses by ensuring that \f$ 4 A_{xx} A_{yy}- A_{xy}^2 > 0 \f$. + The condition imposed is that \f$ 4 A_{xx} A_{yy}- A_{xy}^2=1 \f$ which satisfies the inequality + and as the coefficients can be arbitrarily scaled is not overly restrictive. + + \f{equation*}{ + \epsilon ^2= A^T D^T D A \quad \text{with} \quad A^T C A =1 \quad \text{and} \quad C=\left(\begin{matrix} + 0 & 0 & 2 & 0 & 0 & 0 \\ + 0 & -1 & 0 & 0 & 0 & 0 \\ + 2 & 0 & 0 & 0 & 0 & 0 \\ + 0 & 0 & 0 & 0 & 0 & 0 \\ + 0 & 0 & 0 & 0 & 0 & 0 \\ + 0 & 0 & 0 & 0 & 0 & 0 + \end{matrix} \right) + \f} + + The minimum cost is found by solving the generalized eigenvalue problem. + + \f{equation*}{ + D^T D A = \lambda \left( C\right) A + \f} + + The system produces only one positive eigenvalue \f$ \lambda\f$ which is chosen as the solution + with its eigenvector \f$\mathbf{u}\f$. These are used to find the coefficients + + \f{equation*}{ + A = \sqrt{\frac{1}{\mathbf{u}^T C \mathbf{u}}} \mathbf{u} + \f} + The scaling factor guarantees that \f$A^T C A =1\f$. + + @param points Input 2D point set, stored in std::vector\<\> or Mat + */ +CV_EXPORTS_W RotatedRect fitEllipseDirect( InputArray points ); + +/** @brief Fits a line to a 2D or 3D point set. + +The function fitLine fits a line to a 2D or 3D point set by minimizing \f$\sum_i \rho(r_i)\f$ where +\f$r_i\f$ is a distance between the \f$i^{th}\f$ point, the line and \f$\rho(r)\f$ is a distance function, one +of the following: +- DIST_L2 +\f[\rho (r) = r^2/2 \quad \text{(the simplest and the fastest least-squares method)}\f] +- DIST_L1 +\f[\rho (r) = r\f] +- DIST_L12 +\f[\rho (r) = 2 \cdot ( \sqrt{1 + \frac{r^2}{2}} - 1)\f] +- DIST_FAIR +\f[\rho \left (r \right ) = C^2 \cdot \left ( \frac{r}{C} - \log{\left(1 + \frac{r}{C}\right)} \right ) \quad \text{where} \quad C=1.3998\f] +- DIST_WELSCH +\f[\rho \left (r \right ) = \frac{C^2}{2} \cdot \left ( 1 - \exp{\left(-\left(\frac{r}{C}\right)^2\right)} \right ) \quad \text{where} \quad C=2.9846\f] +- DIST_HUBER +\f[\rho (r) = \fork{r^2/2}{if \(r < C\)}{C \cdot (r-C/2)}{otherwise} \quad \text{where} \quad C=1.345\f] + +The algorithm is based on the M-estimator ( ) technique +that iteratively fits the line using the weighted least-squares algorithm. After each iteration the +weights \f$w_i\f$ are adjusted to be inversely proportional to \f$\rho(r_i)\f$ . + +@param points Input vector of 2D or 3D points, stored in std::vector\<\> or Mat. +@param line Output line parameters. In case of 2D fitting, it should be a vector of 4 elements +(like Vec4f) - (vx, vy, x0, y0), where (vx, vy) is a normalized vector collinear to the line and +(x0, y0) is a point on the line. In case of 3D fitting, it should be a vector of 6 elements (like +Vec6f) - (vx, vy, vz, x0, y0, z0), where (vx, vy, vz) is a normalized vector collinear to the line +and (x0, y0, z0) is a point on the line. +@param distType Distance used by the M-estimator, see #DistanceTypes +@param param Numerical parameter ( C ) for some types of distances. If it is 0, an optimal value +is chosen. +@param reps Sufficient accuracy for the radius (distance between the coordinate origin and the line). +@param aeps Sufficient accuracy for the angle. 0.01 would be a good default value for reps and aeps. + */ +CV_EXPORTS_W void fitLine( InputArray points, OutputArray line, int distType, + double param, double reps, double aeps ); + +/** @brief Performs a point-in-contour test. + +The function determines whether the point is inside a contour, outside, or lies on an edge (or +coincides with a vertex). It returns positive (inside), negative (outside), or zero (on an edge) +value, correspondingly. When measureDist=false , the return value is +1, -1, and 0, respectively. +Otherwise, the return value is a signed distance between the point and the nearest contour edge. + +See below a sample output of the function where each image pixel is tested against the contour: + +![sample output](pics/pointpolygon.png) + +@param contour Input contour. +@param pt Point tested against the contour. +@param measureDist If true, the function estimates the signed distance from the point to the +nearest contour edge. Otherwise, the function only checks if the point is inside a contour or not. + */ +CV_EXPORTS_W double pointPolygonTest( InputArray contour, Point2f pt, bool measureDist ); + +/** @brief Finds out if there is any intersection between two rotated rectangles. + +If there is then the vertices of the intersecting region are returned as well. + +Below are some examples of intersection configurations. The hatched pattern indicates the +intersecting region and the red vertices are returned by the function. + +![intersection examples](pics/intersection.png) + +@param rect1 First rectangle +@param rect2 Second rectangle +@param intersectingRegion The output array of the vertices of the intersecting region. It returns +at most 8 vertices. Stored as std::vector\ or cv::Mat as Mx1 of type CV_32FC2. +@returns One of #RectanglesIntersectTypes + */ +CV_EXPORTS_W int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion ); + +/** @brief Creates a smart pointer to a cv::GeneralizedHoughBallard class and initializes it. +*/ +CV_EXPORTS Ptr createGeneralizedHoughBallard(); + +/** @brief Creates a smart pointer to a cv::GeneralizedHoughGuil class and initializes it. +*/ +CV_EXPORTS Ptr createGeneralizedHoughGuil(); + +//! @} imgproc_shape + +//! @addtogroup imgproc_colormap +//! @{ + +//! GNU Octave/MATLAB equivalent colormaps +enum ColormapTypes +{ + COLORMAP_AUTUMN = 0, //!< ![autumn](pics/colormaps/colorscale_autumn.jpg) + COLORMAP_BONE = 1, //!< ![bone](pics/colormaps/colorscale_bone.jpg) + COLORMAP_JET = 2, //!< ![jet](pics/colormaps/colorscale_jet.jpg) + COLORMAP_WINTER = 3, //!< ![winter](pics/colormaps/colorscale_winter.jpg) + COLORMAP_RAINBOW = 4, //!< ![rainbow](pics/colormaps/colorscale_rainbow.jpg) + COLORMAP_OCEAN = 5, //!< ![ocean](pics/colormaps/colorscale_ocean.jpg) + COLORMAP_SUMMER = 6, //!< ![summer](pics/colormaps/colorscale_summer.jpg) + COLORMAP_SPRING = 7, //!< ![spring](pics/colormaps/colorscale_spring.jpg) + COLORMAP_COOL = 8, //!< ![cool](pics/colormaps/colorscale_cool.jpg) + COLORMAP_HSV = 9, //!< ![HSV](pics/colormaps/colorscale_hsv.jpg) + COLORMAP_PINK = 10, //!< ![pink](pics/colormaps/colorscale_pink.jpg) + COLORMAP_HOT = 11, //!< ![hot](pics/colormaps/colorscale_hot.jpg) + COLORMAP_PARULA = 12, //!< ![parula](pics/colormaps/colorscale_parula.jpg) + COLORMAP_MAGMA = 13, //!< ![magma](pics/colormaps/colorscale_magma.jpg) + COLORMAP_INFERNO = 14, //!< ![inferno](pics/colormaps/colorscale_inferno.jpg) + COLORMAP_PLASMA = 15, //!< ![plasma](pics/colormaps/colorscale_plasma.jpg) + COLORMAP_VIRIDIS = 16, //!< ![viridis](pics/colormaps/colorscale_viridis.jpg) + COLORMAP_CIVIDIS = 17, //!< ![cividis](pics/colormaps/colorscale_cividis.jpg) + COLORMAP_TWILIGHT = 18, //!< ![twilight](pics/colormaps/colorscale_twilight.jpg) + COLORMAP_TWILIGHT_SHIFTED = 19 //!< ![twilight shifted](pics/colormaps/colorscale_twilight_shifted.jpg) +}; + +/** @example samples/cpp/falsecolor.cpp +An example using applyColorMap function +*/ + +/** @brief Applies a GNU Octave/MATLAB equivalent colormap on a given image. + +@param src The source image, grayscale or colored of type CV_8UC1 or CV_8UC3. +@param dst The result is the colormapped source image. Note: Mat::create is called on dst. +@param colormap The colormap to apply, see #ColormapTypes +*/ +CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap); + +/** @brief Applies a user colormap on a given image. + +@param src The source image, grayscale or colored of type CV_8UC1 or CV_8UC3. +@param dst The result is the colormapped source image. Note: Mat::create is called on dst. +@param userColor The colormap to apply of type CV_8UC1 or CV_8UC3 and size 256 +*/ +CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, InputArray userColor); + +//! @} imgproc_colormap + +//! @addtogroup imgproc_draw +//! @{ + + +/** OpenCV color channel order is BGR[A] */ +#define CV_RGB(r, g, b) cv::Scalar((b), (g), (r), 0) + +/** @brief Draws a line segment connecting two points. + +The function line draws the line segment between pt1 and pt2 points in the image. The line is +clipped by the image boundaries. For non-antialiased lines with integer coordinates, the 8-connected +or 4-connected Bresenham algorithm is used. Thick lines are drawn with rounding endings. Antialiased +lines are drawn using Gaussian filtering. + +@param img Image. +@param pt1 First point of the line segment. +@param pt2 Second point of the line segment. +@param color Line color. +@param thickness Line thickness. +@param lineType Type of the line. See #LineTypes. +@param shift Number of fractional bits in the point coordinates. + */ +CV_EXPORTS_W void line(InputOutputArray img, Point pt1, Point pt2, const Scalar& color, + int thickness = 1, int lineType = LINE_8, int shift = 0); + +/** @brief Draws a arrow segment pointing from the first point to the second one. + +The function cv::arrowedLine draws an arrow between pt1 and pt2 points in the image. See also #line. + +@param img Image. +@param pt1 The point the arrow starts from. +@param pt2 The point the arrow points to. +@param color Line color. +@param thickness Line thickness. +@param line_type Type of the line. See #LineTypes +@param shift Number of fractional bits in the point coordinates. +@param tipLength The length of the arrow tip in relation to the arrow length + */ +CV_EXPORTS_W void arrowedLine(InputOutputArray img, Point pt1, Point pt2, const Scalar& color, + int thickness=1, int line_type=8, int shift=0, double tipLength=0.1); + +/** @brief Draws a simple, thick, or filled up-right rectangle. + +The function cv::rectangle draws a rectangle outline or a filled rectangle whose two opposite corners +are pt1 and pt2. + +@param img Image. +@param pt1 Vertex of the rectangle. +@param pt2 Vertex of the rectangle opposite to pt1 . +@param color Rectangle color or brightness (grayscale image). +@param thickness Thickness of lines that make up the rectangle. Negative values, like #FILLED, +mean that the function has to draw a filled rectangle. +@param lineType Type of the line. See #LineTypes +@param shift Number of fractional bits in the point coordinates. + */ +CV_EXPORTS_W void rectangle(InputOutputArray img, Point pt1, Point pt2, + const Scalar& color, int thickness = 1, + int lineType = LINE_8, int shift = 0); + +/** @overload + +use `rec` parameter as alternative specification of the drawn rectangle: `r.tl() and +r.br()-Point(1,1)` are opposite corners +*/ +CV_EXPORTS void rectangle(CV_IN_OUT Mat& img, Rect rec, + const Scalar& color, int thickness = 1, + int lineType = LINE_8, int shift = 0); + +/** @example samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_2.cpp +An example using drawing functions +*/ + +/** @brief Draws a circle. + +The function cv::circle draws a simple or filled circle with a given center and radius. +@param img Image where the circle is drawn. +@param center Center of the circle. +@param radius Radius of the circle. +@param color Circle color. +@param thickness Thickness of the circle outline, if positive. Negative values, like #FILLED, +mean that a filled circle is to be drawn. +@param lineType Type of the circle boundary. See #LineTypes +@param shift Number of fractional bits in the coordinates of the center and in the radius value. + */ +CV_EXPORTS_W void circle(InputOutputArray img, Point center, int radius, + const Scalar& color, int thickness = 1, + int lineType = LINE_8, int shift = 0); + +/** @brief Draws a simple or thick elliptic arc or fills an ellipse sector. + +The function cv::ellipse with more parameters draws an ellipse outline, a filled ellipse, an elliptic +arc, or a filled ellipse sector. The drawing code uses general parametric form. +A piecewise-linear curve is used to approximate the elliptic arc +boundary. If you need more control of the ellipse rendering, you can retrieve the curve using +#ellipse2Poly and then render it with #polylines or fill it with #fillPoly. If you use the first +variant of the function and want to draw the whole ellipse, not an arc, pass `startAngle=0` and +`endAngle=360`. If `startAngle` is greater than `endAngle`, they are swapped. The figure below explains +the meaning of the parameters to draw the blue arc. + +![Parameters of Elliptic Arc](pics/ellipse.svg) + +@param img Image. +@param center Center of the ellipse. +@param axes Half of the size of the ellipse main axes. +@param angle Ellipse rotation angle in degrees. +@param startAngle Starting angle of the elliptic arc in degrees. +@param endAngle Ending angle of the elliptic arc in degrees. +@param color Ellipse color. +@param thickness Thickness of the ellipse arc outline, if positive. Otherwise, this indicates that +a filled ellipse sector is to be drawn. +@param lineType Type of the ellipse boundary. See #LineTypes +@param shift Number of fractional bits in the coordinates of the center and values of axes. + */ +CV_EXPORTS_W void ellipse(InputOutputArray img, Point center, Size axes, + double angle, double startAngle, double endAngle, + const Scalar& color, int thickness = 1, + int lineType = LINE_8, int shift = 0); + +/** @overload +@param img Image. +@param box Alternative ellipse representation via RotatedRect. This means that the function draws +an ellipse inscribed in the rotated rectangle. +@param color Ellipse color. +@param thickness Thickness of the ellipse arc outline, if positive. Otherwise, this indicates that +a filled ellipse sector is to be drawn. +@param lineType Type of the ellipse boundary. See #LineTypes +*/ +CV_EXPORTS_W void ellipse(InputOutputArray img, const RotatedRect& box, const Scalar& color, + int thickness = 1, int lineType = LINE_8); + +/* ----------------------------------------------------------------------------------------- */ +/* ADDING A SET OF PREDEFINED MARKERS WHICH COULD BE USED TO HIGHLIGHT POSITIONS IN AN IMAGE */ +/* ----------------------------------------------------------------------------------------- */ + +//! Possible set of marker types used for the cv::drawMarker function +enum MarkerTypes +{ + MARKER_CROSS = 0, //!< A crosshair marker shape + MARKER_TILTED_CROSS = 1, //!< A 45 degree tilted crosshair marker shape + MARKER_STAR = 2, //!< A star marker shape, combination of cross and tilted cross + MARKER_DIAMOND = 3, //!< A diamond marker shape + MARKER_SQUARE = 4, //!< A square marker shape + MARKER_TRIANGLE_UP = 5, //!< An upwards pointing triangle marker shape + MARKER_TRIANGLE_DOWN = 6 //!< A downwards pointing triangle marker shape +}; + +/** @brief Draws a marker on a predefined position in an image. + +The function cv::drawMarker draws a marker on a given position in the image. For the moment several +marker types are supported, see #MarkerTypes for more information. + +@param img Image. +@param position The point where the crosshair is positioned. +@param color Line color. +@param markerType The specific type of marker you want to use, see #MarkerTypes +@param thickness Line thickness. +@param line_type Type of the line, See #LineTypes +@param markerSize The length of the marker axis [default = 20 pixels] + */ +CV_EXPORTS_W void drawMarker(CV_IN_OUT Mat& img, Point position, const Scalar& color, + int markerType = MARKER_CROSS, int markerSize=20, int thickness=1, + int line_type=8); + +/* ----------------------------------------------------------------------------------------- */ +/* END OF MARKER SECTION */ +/* ----------------------------------------------------------------------------------------- */ + +/** @overload */ +CV_EXPORTS void fillConvexPoly(Mat& img, const Point* pts, int npts, + const Scalar& color, int lineType = LINE_8, + int shift = 0); + +/** @brief Fills a convex polygon. + +The function cv::fillConvexPoly draws a filled convex polygon. This function is much faster than the +function #fillPoly . It can fill not only convex polygons but any monotonic polygon without +self-intersections, that is, a polygon whose contour intersects every horizontal line (scan line) +twice at the most (though, its top-most and/or the bottom edge could be horizontal). + +@param img Image. +@param points Polygon vertices. +@param color Polygon color. +@param lineType Type of the polygon boundaries. See #LineTypes +@param shift Number of fractional bits in the vertex coordinates. + */ +CV_EXPORTS_W void fillConvexPoly(InputOutputArray img, InputArray points, + const Scalar& color, int lineType = LINE_8, + int shift = 0); + +/** @overload */ +CV_EXPORTS void fillPoly(Mat& img, const Point** pts, + const int* npts, int ncontours, + const Scalar& color, int lineType = LINE_8, int shift = 0, + Point offset = Point() ); + +/** @example samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp +An example using drawing functions +Check @ref tutorial_random_generator_and_text "the corresponding tutorial" for more details +*/ + +/** @brief Fills the area bounded by one or more polygons. + +The function cv::fillPoly fills an area bounded by several polygonal contours. The function can fill +complex areas, for example, areas with holes, contours with self-intersections (some of their +parts), and so forth. + +@param img Image. +@param pts Array of polygons where each polygon is represented as an array of points. +@param color Polygon color. +@param lineType Type of the polygon boundaries. See #LineTypes +@param shift Number of fractional bits in the vertex coordinates. +@param offset Optional offset of all points of the contours. + */ +CV_EXPORTS_W void fillPoly(InputOutputArray img, InputArrayOfArrays pts, + const Scalar& color, int lineType = LINE_8, int shift = 0, + Point offset = Point() ); + +/** @overload */ +CV_EXPORTS void polylines(Mat& img, const Point* const* pts, const int* npts, + int ncontours, bool isClosed, const Scalar& color, + int thickness = 1, int lineType = LINE_8, int shift = 0 ); + +/** @brief Draws several polygonal curves. + +@param img Image. +@param pts Array of polygonal curves. +@param isClosed Flag indicating whether the drawn polylines are closed or not. If they are closed, +the function draws a line from the last vertex of each curve to its first vertex. +@param color Polyline color. +@param thickness Thickness of the polyline edges. +@param lineType Type of the line segments. See #LineTypes +@param shift Number of fractional bits in the vertex coordinates. + +The function cv::polylines draws one or more polygonal curves. + */ +CV_EXPORTS_W void polylines(InputOutputArray img, InputArrayOfArrays pts, + bool isClosed, const Scalar& color, + int thickness = 1, int lineType = LINE_8, int shift = 0 ); + +/** @example samples/cpp/contours2.cpp +An example program illustrates the use of cv::findContours and cv::drawContours +\image html WindowsQtContoursOutput.png "Screenshot of the program" +*/ + +/** @example samples/cpp/segment_objects.cpp +An example using drawContours to clean up a background segmentation result +*/ + +/** @brief Draws contours outlines or filled contours. + +The function draws contour outlines in the image if \f$\texttt{thickness} \ge 0\f$ or fills the area +bounded by the contours if \f$\texttt{thickness}<0\f$ . The example below shows how to retrieve +connected components from the binary image and label them: : +@include snippets/imgproc_drawContours.cpp + +@param image Destination image. +@param contours All the input contours. Each contour is stored as a point vector. +@param contourIdx Parameter indicating a contour to draw. If it is negative, all the contours are drawn. +@param color Color of the contours. +@param thickness Thickness of lines the contours are drawn with. If it is negative (for example, +thickness=#FILLED ), the contour interiors are drawn. +@param lineType Line connectivity. See #LineTypes +@param hierarchy Optional information about hierarchy. It is only needed if you want to draw only +some of the contours (see maxLevel ). +@param maxLevel Maximal level for drawn contours. If it is 0, only the specified contour is drawn. +If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function +draws the contours, all the nested contours, all the nested-to-nested contours, and so on. This +parameter is only taken into account when there is hierarchy available. +@param offset Optional contour shift parameter. Shift all the drawn contours by the specified +\f$\texttt{offset}=(dx,dy)\f$ . +@note When thickness=#FILLED, the function is designed to handle connected components with holes correctly +even when no hierarchy date is provided. This is done by analyzing all the outlines together +using even-odd rule. This may give incorrect results if you have a joint collection of separately retrieved +contours. In order to solve this problem, you need to call #drawContours separately for each sub-group +of contours, or iterate over the collection using contourIdx parameter. + */ +CV_EXPORTS_W void drawContours( InputOutputArray image, InputArrayOfArrays contours, + int contourIdx, const Scalar& color, + int thickness = 1, int lineType = LINE_8, + InputArray hierarchy = noArray(), + int maxLevel = INT_MAX, Point offset = Point() ); + +/** @brief Clips the line against the image rectangle. + +The function cv::clipLine calculates a part of the line segment that is entirely within the specified +rectangle. it returns false if the line segment is completely outside the rectangle. Otherwise, +it returns true . +@param imgSize Image size. The image rectangle is Rect(0, 0, imgSize.width, imgSize.height) . +@param pt1 First line point. +@param pt2 Second line point. + */ +CV_EXPORTS bool clipLine(Size imgSize, CV_IN_OUT Point& pt1, CV_IN_OUT Point& pt2); + +/** @overload +@param imgSize Image size. The image rectangle is Rect(0, 0, imgSize.width, imgSize.height) . +@param pt1 First line point. +@param pt2 Second line point. +*/ +CV_EXPORTS bool clipLine(Size2l imgSize, CV_IN_OUT Point2l& pt1, CV_IN_OUT Point2l& pt2); + +/** @overload +@param imgRect Image rectangle. +@param pt1 First line point. +@param pt2 Second line point. +*/ +CV_EXPORTS_W bool clipLine(Rect imgRect, CV_OUT CV_IN_OUT Point& pt1, CV_OUT CV_IN_OUT Point& pt2); + +/** @brief Approximates an elliptic arc with a polyline. + +The function ellipse2Poly computes the vertices of a polyline that approximates the specified +elliptic arc. It is used by #ellipse. If `arcStart` is greater than `arcEnd`, they are swapped. + +@param center Center of the arc. +@param axes Half of the size of the ellipse main axes. See #ellipse for details. +@param angle Rotation angle of the ellipse in degrees. See #ellipse for details. +@param arcStart Starting angle of the elliptic arc in degrees. +@param arcEnd Ending angle of the elliptic arc in degrees. +@param delta Angle between the subsequent polyline vertices. It defines the approximation +accuracy. +@param pts Output vector of polyline vertices. + */ +CV_EXPORTS_W void ellipse2Poly( Point center, Size axes, int angle, + int arcStart, int arcEnd, int delta, + CV_OUT std::vector& pts ); + +/** @overload +@param center Center of the arc. +@param axes Half of the size of the ellipse main axes. See #ellipse for details. +@param angle Rotation angle of the ellipse in degrees. See #ellipse for details. +@param arcStart Starting angle of the elliptic arc in degrees. +@param arcEnd Ending angle of the elliptic arc in degrees. +@param delta Angle between the subsequent polyline vertices. It defines the approximation accuracy. +@param pts Output vector of polyline vertices. +*/ +CV_EXPORTS void ellipse2Poly(Point2d center, Size2d axes, int angle, + int arcStart, int arcEnd, int delta, + CV_OUT std::vector& pts); + +/** @brief Draws a text string. + +The function cv::putText renders the specified text string in the image. Symbols that cannot be rendered +using the specified font are replaced by question marks. See #getTextSize for a text rendering code +example. + +@param img Image. +@param text Text string to be drawn. +@param org Bottom-left corner of the text string in the image. +@param fontFace Font type, see #HersheyFonts. +@param fontScale Font scale factor that is multiplied by the font-specific base size. +@param color Text color. +@param thickness Thickness of the lines used to draw a text. +@param lineType Line type. See #LineTypes +@param bottomLeftOrigin When true, the image data origin is at the bottom-left corner. Otherwise, +it is at the top-left corner. + */ +CV_EXPORTS_W void putText( InputOutputArray img, const String& text, Point org, + int fontFace, double fontScale, Scalar color, + int thickness = 1, int lineType = LINE_8, + bool bottomLeftOrigin = false ); + +/** @brief Calculates the width and height of a text string. + +The function cv::getTextSize calculates and returns the size of a box that contains the specified text. +That is, the following code renders some text, the tight box surrounding it, and the baseline: : +@code + String text = "Funny text inside the box"; + int fontFace = FONT_HERSHEY_SCRIPT_SIMPLEX; + double fontScale = 2; + int thickness = 3; + + Mat img(600, 800, CV_8UC3, Scalar::all(0)); + + int baseline=0; + Size textSize = getTextSize(text, fontFace, + fontScale, thickness, &baseline); + baseline += thickness; + + // center the text + Point textOrg((img.cols - textSize.width)/2, + (img.rows + textSize.height)/2); + + // draw the box + rectangle(img, textOrg + Point(0, baseline), + textOrg + Point(textSize.width, -textSize.height), + Scalar(0,0,255)); + // ... and the baseline first + line(img, textOrg + Point(0, thickness), + textOrg + Point(textSize.width, thickness), + Scalar(0, 0, 255)); + + // then put the text itself + putText(img, text, textOrg, fontFace, fontScale, + Scalar::all(255), thickness, 8); +@endcode + +@param text Input text string. +@param fontFace Font to use, see #HersheyFonts. +@param fontScale Font scale factor that is multiplied by the font-specific base size. +@param thickness Thickness of lines used to render the text. See #putText for details. +@param[out] baseLine y-coordinate of the baseline relative to the bottom-most text +point. +@return The size of a box that contains the specified text. + +@see putText + */ +CV_EXPORTS_W Size getTextSize(const String& text, int fontFace, + double fontScale, int thickness, + CV_OUT int* baseLine); + + +/** @brief Calculates the font-specific size to use to achieve a given height in pixels. + +@param fontFace Font to use, see cv::HersheyFonts. +@param pixelHeight Pixel height to compute the fontScale for +@param thickness Thickness of lines used to render the text.See putText for details. +@return The fontSize to use for cv::putText + +@see cv::putText +*/ +CV_EXPORTS_W double getFontScaleFromHeight(const int fontFace, + const int pixelHeight, + const int thickness = 1); + +/** @brief Line iterator + +The class is used to iterate over all the pixels on the raster line +segment connecting two specified points. + +The class LineIterator is used to get each pixel of a raster line. It +can be treated as versatile implementation of the Bresenham algorithm +where you can stop at each pixel and do some extra processing, for +example, grab pixel values along the line or draw a line with an effect +(for example, with XOR operation). + +The number of pixels along the line is stored in LineIterator::count. +The method LineIterator::pos returns the current position in the image: + +@code{.cpp} +// grabs pixels along the line (pt1, pt2) +// from 8-bit 3-channel image to the buffer +LineIterator it(img, pt1, pt2, 8); +LineIterator it2 = it; +vector buf(it.count); + +for(int i = 0; i < it.count; i++, ++it) + buf[i] = *(const Vec3b*)*it; + +// alternative way of iterating through the line +for(int i = 0; i < it2.count; i++, ++it2) +{ + Vec3b val = img.at(it2.pos()); + CV_Assert(buf[i] == val); +} +@endcode +*/ +class CV_EXPORTS LineIterator +{ +public: + /** @brief initializes the iterator + + creates iterators for the line connecting pt1 and pt2 + the line will be clipped on the image boundaries + the line is 8-connected or 4-connected + If leftToRight=true, then the iteration is always done + from the left-most point to the right most, + not to depend on the ordering of pt1 and pt2 parameters + */ + LineIterator( const Mat& img, Point pt1, Point pt2, + int connectivity = 8, bool leftToRight = false ); + /** @brief returns pointer to the current pixel + */ + uchar* operator *(); + /** @brief prefix increment operator (++it). shifts iterator to the next pixel + */ + LineIterator& operator ++(); + /** @brief postfix increment operator (it++). shifts iterator to the next pixel + */ + LineIterator operator ++(int); + /** @brief returns coordinates of the current pixel + */ + Point pos() const; + + uchar* ptr; + const uchar* ptr0; + int step, elemSize; + int err, count; + int minusDelta, plusDelta; + int minusStep, plusStep; +}; + +//! @cond IGNORED + +// === LineIterator implementation === + +inline +uchar* LineIterator::operator *() +{ + return ptr; +} + +inline +LineIterator& LineIterator::operator ++() +{ + int mask = err < 0 ? -1 : 0; + err += minusDelta + (plusDelta & mask); + ptr += minusStep + (plusStep & mask); + return *this; +} + +inline +LineIterator LineIterator::operator ++(int) +{ + LineIterator it = *this; + ++(*this); + return it; +} + +inline +Point LineIterator::pos() const +{ + Point p; + p.y = (int)((ptr - ptr0)/step); + p.x = (int)(((ptr - ptr0) - p.y*step)/elemSize); + return p; +} + +//! @endcond + +//! @} imgproc_draw + +//! @} imgproc + +} // cv + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/imgproc/imgproc_c.h" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/imgproc/detail/distortion_model.hpp b/3rdparty/opencv/include/opencv2/imgproc/detail/distortion_model.hpp new file mode 100644 index 00000000..a9c3ddec --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/detail/distortion_model.hpp @@ -0,0 +1,123 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP +#define OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP + +//! @cond IGNORED + +namespace cv { namespace detail { +/** +Computes the matrix for the projection onto a tilted image sensor +\param tauX angular parameter rotation around x-axis +\param tauY angular parameter rotation around y-axis +\param matTilt if not NULL returns the matrix +\f[ +\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}((\tau_x, \tau_y)} +{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)} +{0}{0}{1} R(\tau_x, \tau_y) +\f] +where +\f[ +R(\tau_x, \tau_y) = +\vecthreethree{\cos(\tau_y)}{0}{-\sin(\tau_y)}{0}{1}{0}{\sin(\tau_y)}{0}{\cos(\tau_y)} +\vecthreethree{1}{0}{0}{0}{\cos(\tau_x)}{\sin(\tau_x)}{0}{-\sin(\tau_x)}{\cos(\tau_x)} = +\vecthreethree{\cos(\tau_y)}{\sin(\tau_y)\sin(\tau_x)}{-\sin(\tau_y)\cos(\tau_x)} +{0}{\cos(\tau_x)}{\sin(\tau_x)} +{\sin(\tau_y)}{-\cos(\tau_y)\sin(\tau_x)}{\cos(\tau_y)\cos(\tau_x)}. +\f] +\param dMatTiltdTauX if not NULL it returns the derivative of matTilt with +respect to \f$\tau_x\f$. +\param dMatTiltdTauY if not NULL it returns the derivative of matTilt with +respect to \f$\tau_y\f$. +\param invMatTilt if not NULL it returns the inverse of matTilt +**/ +template +void computeTiltProjectionMatrix(FLOAT tauX, + FLOAT tauY, + Matx* matTilt = 0, + Matx* dMatTiltdTauX = 0, + Matx* dMatTiltdTauY = 0, + Matx* invMatTilt = 0) +{ + FLOAT cTauX = cos(tauX); + FLOAT sTauX = sin(tauX); + FLOAT cTauY = cos(tauY); + FLOAT sTauY = sin(tauY); + Matx matRotX = Matx(1,0,0,0,cTauX,sTauX,0,-sTauX,cTauX); + Matx matRotY = Matx(cTauY,0,-sTauY,0,1,0,sTauY,0,cTauY); + Matx matRotXY = matRotY * matRotX; + Matx matProjZ = Matx(matRotXY(2,2),0,-matRotXY(0,2),0,matRotXY(2,2),-matRotXY(1,2),0,0,1); + if (matTilt) + { + // Matrix for trapezoidal distortion of tilted image sensor + *matTilt = matProjZ * matRotXY; + } + if (dMatTiltdTauX) + { + // Derivative with respect to tauX + Matx dMatRotXYdTauX = matRotY * Matx(0,0,0,0,-sTauX,cTauX,0,-cTauX,-sTauX); + Matx dMatProjZdTauX = Matx(dMatRotXYdTauX(2,2),0,-dMatRotXYdTauX(0,2), + 0,dMatRotXYdTauX(2,2),-dMatRotXYdTauX(1,2),0,0,0); + *dMatTiltdTauX = (matProjZ * dMatRotXYdTauX) + (dMatProjZdTauX * matRotXY); + } + if (dMatTiltdTauY) + { + // Derivative with respect to tauY + Matx dMatRotXYdTauY = Matx(-sTauY,0,-cTauY,0,0,0,cTauY,0,-sTauY) * matRotX; + Matx dMatProjZdTauY = Matx(dMatRotXYdTauY(2,2),0,-dMatRotXYdTauY(0,2), + 0,dMatRotXYdTauY(2,2),-dMatRotXYdTauY(1,2),0,0,0); + *dMatTiltdTauY = (matProjZ * dMatRotXYdTauY) + (dMatProjZdTauY * matRotXY); + } + if (invMatTilt) + { + FLOAT inv = 1./matRotXY(2,2); + Matx invMatProjZ = Matx(inv,0,inv*matRotXY(0,2),0,inv,inv*matRotXY(1,2),0,0,1); + *invMatTilt = matRotXY.t()*invMatProjZ; + } +} +}} // namespace detail, cv + + +//! @endcond + +#endif // OPENCV_IMGPROC_DETAIL_DISTORTION_MODEL_HPP diff --git a/3rdparty/opencv/include/opencv2/imgproc/hal/hal.hpp b/3rdparty/opencv/include/opencv2/imgproc/hal/hal.hpp new file mode 100644 index 00000000..a435fd6b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/hal/hal.hpp @@ -0,0 +1,241 @@ +#ifndef CV_IMGPROC_HAL_HPP +#define CV_IMGPROC_HAL_HPP + +#include "opencv2/core/cvdef.h" +#include "opencv2/core/cvstd.hpp" +#include "opencv2/core/hal/interface.h" + +namespace cv { namespace hal { + +//! @addtogroup imgproc_hal_functions +//! @{ + +//--------------------------- +//! @cond IGNORED + +struct CV_EXPORTS Filter2D +{ + CV_DEPRECATED static Ptr create(uchar * , size_t , int , + int , int , + int , int , + int , int , + int , double , + int , int , + bool , bool ); + virtual void apply(uchar * , size_t , + uchar * , size_t , + int , int , + int , int , + int , int ) = 0; + virtual ~Filter2D() {} +}; + +struct CV_EXPORTS SepFilter2D +{ + CV_DEPRECATED static Ptr create(int , int , int , + uchar * , int , + uchar * , int , + int , int , + double , int ); + virtual void apply(uchar * , size_t , + uchar * , size_t , + int , int , + int , int , + int , int ) = 0; + virtual ~SepFilter2D() {} +}; + + +struct CV_EXPORTS Morph +{ + CV_DEPRECATED static Ptr create(int , int , int , int , int , + int , uchar * , size_t , + int , int , + int , int , + int , const double *, + int , bool , bool ); + virtual void apply(uchar * , size_t , uchar * , size_t , int , int , + int , int , int , int , + int , int , int , int ) = 0; + virtual ~Morph() {} +}; + +//! @endcond +//--------------------------- + +CV_EXPORTS void filter2D(int stype, int dtype, int kernel_type, + uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int full_width, int full_height, + int offset_x, int offset_y, + uchar * kernel_data, size_t kernel_step, + int kernel_width, int kernel_height, + int anchor_x, int anchor_y, + double delta, int borderType, + bool isSubmatrix); + +CV_EXPORTS void sepFilter2D(int stype, int dtype, int ktype, + uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int full_width, int full_height, + int offset_x, int offset_y, + uchar * kernelx_data, int kernelx_len, + uchar * kernely_data, int kernely_len, + int anchor_x, int anchor_y, + double delta, int borderType); + +CV_EXPORTS void morph(int op, int src_type, int dst_type, + uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int roi_width, int roi_height, int roi_x, int roi_y, + int roi_width2, int roi_height2, int roi_x2, int roi_y2, + int kernel_type, uchar * kernel_data, size_t kernel_step, + int kernel_width, int kernel_height, int anchor_x, int anchor_y, + int borderType, const double borderValue[4], + int iterations, bool isSubmatrix); + + +CV_EXPORTS void resize(int src_type, + const uchar * src_data, size_t src_step, int src_width, int src_height, + uchar * dst_data, size_t dst_step, int dst_width, int dst_height, + double inv_scale_x, double inv_scale_y, int interpolation); + +CV_EXPORTS void warpAffine(int src_type, + const uchar * src_data, size_t src_step, int src_width, int src_height, + uchar * dst_data, size_t dst_step, int dst_width, int dst_height, + const double M[6], int interpolation, int borderType, const double borderValue[4]); + +CV_EXPORTS void warpPerspectve(int src_type, + const uchar * src_data, size_t src_step, int src_width, int src_height, + uchar * dst_data, size_t dst_step, int dst_width, int dst_height, + const double M[9], int interpolation, int borderType, const double borderValue[4]); + +CV_EXPORTS void cvtBGRtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, int dcn, bool swapBlue); + +CV_EXPORTS void cvtBGRtoBGR5x5(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int scn, bool swapBlue, int greenBits); + +CV_EXPORTS void cvtBGR5x5toBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int dcn, bool swapBlue, int greenBits); + +CV_EXPORTS void cvtBGRtoGray(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, bool swapBlue); + +CV_EXPORTS void cvtGraytoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int dcn); + +CV_EXPORTS void cvtBGR5x5toGray(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int greenBits); + +CV_EXPORTS void cvtGraytoBGR5x5(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int greenBits); +CV_EXPORTS void cvtBGRtoYUV(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, bool swapBlue, bool isCbCr); + +CV_EXPORTS void cvtYUVtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int dcn, bool swapBlue, bool isCbCr); + +CV_EXPORTS void cvtBGRtoXYZ(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, bool swapBlue); + +CV_EXPORTS void cvtXYZtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int dcn, bool swapBlue); + +CV_EXPORTS void cvtBGRtoHSV(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, bool swapBlue, bool isFullRange, bool isHSV); + +CV_EXPORTS void cvtHSVtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int dcn, bool swapBlue, bool isFullRange, bool isHSV); + +CV_EXPORTS void cvtBGRtoLab(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int scn, bool swapBlue, bool isLab, bool srgb); + +CV_EXPORTS void cvtLabtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int depth, int dcn, bool swapBlue, bool isLab, bool srgb); + +CV_EXPORTS void cvtTwoPlaneYUVtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int dst_width, int dst_height, + int dcn, bool swapBlue, int uIdx); + +//! Separate Y and UV planes +CV_EXPORTS void cvtTwoPlaneYUVtoBGR(const uchar * y_data, const uchar * uv_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int dst_width, int dst_height, + int dcn, bool swapBlue, int uIdx); + +CV_EXPORTS void cvtThreePlaneYUVtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int dst_width, int dst_height, + int dcn, bool swapBlue, int uIdx); + +CV_EXPORTS void cvtBGRtoThreePlaneYUV(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int scn, bool swapBlue, int uIdx); + +//! Separate Y and UV planes +CV_EXPORTS void cvtBGRtoTwoPlaneYUV(const uchar * src_data, size_t src_step, + uchar * y_data, uchar * uv_data, size_t dst_step, + int width, int height, + int scn, bool swapBlue, int uIdx); + +CV_EXPORTS void cvtOnePlaneYUVtoBGR(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height, + int dcn, bool swapBlue, int uIdx, int ycn); + +CV_EXPORTS void cvtRGBAtoMultipliedRGBA(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height); + +CV_EXPORTS void cvtMultipliedRGBAtoRGBA(const uchar * src_data, size_t src_step, + uchar * dst_data, size_t dst_step, + int width, int height); + +CV_EXPORTS void integral(int depth, int sdepth, int sqdepth, + const uchar* src, size_t srcstep, + uchar* sum, size_t sumstep, + uchar* sqsum, size_t sqsumstep, + uchar* tilted, size_t tstep, + int width, int height, int cn); + +//! @} + +}} + +#endif // CV_IMGPROC_HAL_HPP diff --git a/3rdparty/opencv/include/opencv2/imgproc/hal/interface.h b/3rdparty/opencv/include/opencv2/imgproc/hal/interface.h new file mode 100644 index 00000000..f8dbcfe7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/hal/interface.h @@ -0,0 +1,46 @@ +#ifndef OPENCV_IMGPROC_HAL_INTERFACE_H +#define OPENCV_IMGPROC_HAL_INTERFACE_H + +//! @addtogroup imgproc_hal_interface +//! @{ + +//! @name Interpolation modes +//! @sa cv::InterpolationFlags +//! @{ +#define CV_HAL_INTER_NEAREST 0 +#define CV_HAL_INTER_LINEAR 1 +#define CV_HAL_INTER_CUBIC 2 +#define CV_HAL_INTER_AREA 3 +#define CV_HAL_INTER_LANCZOS4 4 +//! @} + +//! @name Morphology operations +//! @sa cv::MorphTypes +//! @{ +#define CV_HAL_MORPH_ERODE 0 +#define CV_HAL_MORPH_DILATE 1 +//! @} + +//! @name Threshold types +//! @sa cv::ThresholdTypes +//! @{ +#define CV_HAL_THRESH_BINARY 0 +#define CV_HAL_THRESH_BINARY_INV 1 +#define CV_HAL_THRESH_TRUNC 2 +#define CV_HAL_THRESH_TOZERO 3 +#define CV_HAL_THRESH_TOZERO_INV 4 +#define CV_HAL_THRESH_MASK 7 +#define CV_HAL_THRESH_OTSU 8 +#define CV_HAL_THRESH_TRIANGLE 16 +//! @} + +//! @name Adaptive threshold algorithm +//! @sa cv::AdaptiveThresholdTypes +//! @{ +#define CV_HAL_ADAPTIVE_THRESH_MEAN_C 0 +#define CV_HAL_ADAPTIVE_THRESH_GAUSSIAN_C 1 +//! @} + +//! @} + +#endif diff --git a/3rdparty/opencv/include/opencv2/imgproc/imgproc.hpp b/3rdparty/opencv/include/opencv2/imgproc/imgproc.hpp new file mode 100644 index 00000000..4175bd0b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/imgproc.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/imgproc.hpp" diff --git a/3rdparty/opencv/include/opencv2/imgproc/imgproc_c.h b/3rdparty/opencv/include/opencv2/imgproc/imgproc_c.h new file mode 100644 index 00000000..cec0f365 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/imgproc_c.h @@ -0,0 +1,1210 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGPROC_IMGPROC_C_H +#define OPENCV_IMGPROC_IMGPROC_C_H + +#include "opencv2/imgproc/types_c.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup imgproc_c +@{ +*/ + +/*********************** Background statistics accumulation *****************************/ + +/** @brief Adds image to accumulator +@see cv::accumulate +*/ +CVAPI(void) cvAcc( const CvArr* image, CvArr* sum, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @brief Adds squared image to accumulator +@see cv::accumulateSquare +*/ +CVAPI(void) cvSquareAcc( const CvArr* image, CvArr* sqsum, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @brief Adds a product of two images to accumulator +@see cv::accumulateProduct +*/ +CVAPI(void) cvMultiplyAcc( const CvArr* image1, const CvArr* image2, CvArr* acc, + const CvArr* mask CV_DEFAULT(NULL) ); + +/** @brief Adds image to accumulator with weights: acc = acc*(1-alpha) + image*alpha +@see cv::accumulateWeighted +*/ +CVAPI(void) cvRunningAvg( const CvArr* image, CvArr* acc, double alpha, + const CvArr* mask CV_DEFAULT(NULL) ); + +/****************************************************************************************\ +* Image Processing * +\****************************************************************************************/ + +/** Copies source 2D array inside of the larger destination array and + makes a border of the specified type (IPL_BORDER_*) around the copied area. */ +CVAPI(void) cvCopyMakeBorder( const CvArr* src, CvArr* dst, CvPoint offset, + int bordertype, CvScalar value CV_DEFAULT(cvScalarAll(0))); + +/** @brief Smooths the image in one of several ways. + +@param src The source image +@param dst The destination image +@param smoothtype Type of the smoothing, see SmoothMethod_c +@param size1 The first parameter of the smoothing operation, the aperture width. Must be a +positive odd number (1, 3, 5, ...) +@param size2 The second parameter of the smoothing operation, the aperture height. Ignored by +CV_MEDIAN and CV_BILATERAL methods. In the case of simple scaled/non-scaled and Gaussian blur if +size2 is zero, it is set to size1. Otherwise it must be a positive odd number. +@param sigma1 In the case of a Gaussian parameter this parameter may specify Gaussian \f$\sigma\f$ +(standard deviation). If it is zero, it is calculated from the kernel size: +\f[\sigma = 0.3 (n/2 - 1) + 0.8 \quad \text{where} \quad n= \begin{array}{l l} \mbox{\texttt{size1} for horizontal kernel} \\ \mbox{\texttt{size2} for vertical kernel} \end{array}\f] +Using standard sigma for small kernels ( \f$3\times 3\f$ to \f$7\times 7\f$ ) gives better speed. If +sigma1 is not zero, while size1 and size2 are zeros, the kernel size is calculated from the +sigma (to provide accurate enough operation). +@param sigma2 additional parameter for bilateral filtering + +@see cv::GaussianBlur, cv::blur, cv::medianBlur, cv::bilateralFilter. + */ +CVAPI(void) cvSmooth( const CvArr* src, CvArr* dst, + int smoothtype CV_DEFAULT(CV_GAUSSIAN), + int size1 CV_DEFAULT(3), + int size2 CV_DEFAULT(0), + double sigma1 CV_DEFAULT(0), + double sigma2 CV_DEFAULT(0)); + +/** @brief Convolves an image with the kernel. + +@param src input image. +@param dst output image of the same size and the same number of channels as src. +@param kernel convolution kernel (or rather a correlation kernel), a single-channel floating point +matrix; if you want to apply different kernels to different channels, split the image into +separate color planes using split and process them individually. +@param anchor anchor of the kernel that indicates the relative position of a filtered point within +the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor +is at the kernel center. + +@see cv::filter2D + */ +CVAPI(void) cvFilter2D( const CvArr* src, CvArr* dst, const CvMat* kernel, + CvPoint anchor CV_DEFAULT(cvPoint(-1,-1))); + +/** @brief Finds integral image: SUM(X,Y) = sum(x \texttt{hist1}(I)\)}{\frac{\texttt{hist2}(I) \cdot \texttt{scale}}{\texttt{hist1}(I)}}{if \(\texttt{hist1}(I) \ne 0\) and \(\texttt{hist2}(I) \le \texttt{hist1}(I)\)}\f] + +@param hist1 First histogram (the divisor). +@param hist2 Second histogram. +@param dst_hist Destination histogram. +@param scale Scale factor for the destination histogram. + */ +CVAPI(void) cvCalcProbDensity( const CvHistogram* hist1, const CvHistogram* hist2, + CvHistogram* dst_hist, double scale CV_DEFAULT(255) ); + +/** @brief equalizes histogram of 8-bit single-channel image +@see cv::equalizeHist +*/ +CVAPI(void) cvEqualizeHist( const CvArr* src, CvArr* dst ); + + +/** @brief Applies distance transform to binary image +@see cv::distanceTransform +*/ +CVAPI(void) cvDistTransform( const CvArr* src, CvArr* dst, + int distance_type CV_DEFAULT(CV_DIST_L2), + int mask_size CV_DEFAULT(3), + const float* mask CV_DEFAULT(NULL), + CvArr* labels CV_DEFAULT(NULL), + int labelType CV_DEFAULT(CV_DIST_LABEL_CCOMP)); + + +/** @brief Applies fixed-level threshold to grayscale image. + + This is a basic operation applied before retrieving contours +@see cv::threshold +*/ +CVAPI(double) cvThreshold( const CvArr* src, CvArr* dst, + double threshold, double max_value, + int threshold_type ); + +/** @brief Applies adaptive threshold to grayscale image. + + The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and + CV_ADAPTIVE_THRESH_GAUSSIAN_C are: + neighborhood size (3, 5, 7 etc.), + and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...) +@see cv::adaptiveThreshold +*/ +CVAPI(void) cvAdaptiveThreshold( const CvArr* src, CvArr* dst, double max_value, + int adaptive_method CV_DEFAULT(CV_ADAPTIVE_THRESH_MEAN_C), + int threshold_type CV_DEFAULT(CV_THRESH_BINARY), + int block_size CV_DEFAULT(3), + double param1 CV_DEFAULT(5)); + +/** @brief Fills the connected component until the color difference gets large enough +@see cv::floodFill +*/ +CVAPI(void) cvFloodFill( CvArr* image, CvPoint seed_point, + CvScalar new_val, CvScalar lo_diff CV_DEFAULT(cvScalarAll(0)), + CvScalar up_diff CV_DEFAULT(cvScalarAll(0)), + CvConnectedComp* comp CV_DEFAULT(NULL), + int flags CV_DEFAULT(4), + CvArr* mask CV_DEFAULT(NULL)); + +/****************************************************************************************\ +* Feature detection * +\****************************************************************************************/ + +/** @brief Runs canny edge detector +@see cv::Canny +*/ +CVAPI(void) cvCanny( const CvArr* image, CvArr* edges, double threshold1, + double threshold2, int aperture_size CV_DEFAULT(3) ); + +/** @brief Calculates constraint image for corner detection + + Dx^2 * Dyy + Dxx * Dy^2 - 2 * Dx * Dy * Dxy. + Applying threshold to the result gives coordinates of corners +@see cv::preCornerDetect +*/ +CVAPI(void) cvPreCornerDetect( const CvArr* image, CvArr* corners, + int aperture_size CV_DEFAULT(3) ); + +/** @brief Calculates eigen values and vectors of 2x2 + gradient covariation matrix at every image pixel +@see cv::cornerEigenValsAndVecs +*/ +CVAPI(void) cvCornerEigenValsAndVecs( const CvArr* image, CvArr* eigenvv, + int block_size, int aperture_size CV_DEFAULT(3) ); + +/** @brief Calculates minimal eigenvalue for 2x2 gradient covariation matrix at + every image pixel +@see cv::cornerMinEigenVal +*/ +CVAPI(void) cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval, + int block_size, int aperture_size CV_DEFAULT(3) ); + +/** @brief Harris corner detector: + + Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel +@see cv::cornerHarris +*/ +CVAPI(void) cvCornerHarris( const CvArr* image, CvArr* harris_response, + int block_size, int aperture_size CV_DEFAULT(3), + double k CV_DEFAULT(0.04) ); + +/** @brief Adjust corner position using some sort of gradient search +@see cv::cornerSubPix +*/ +CVAPI(void) cvFindCornerSubPix( const CvArr* image, CvPoint2D32f* corners, + int count, CvSize win, CvSize zero_zone, + CvTermCriteria criteria ); + +/** @brief Finds a sparse set of points within the selected region + that seem to be easy to track +@see cv::goodFeaturesToTrack +*/ +CVAPI(void) cvGoodFeaturesToTrack( const CvArr* image, CvArr* eig_image, + CvArr* temp_image, CvPoint2D32f* corners, + int* corner_count, double quality_level, + double min_distance, + const CvArr* mask CV_DEFAULT(NULL), + int block_size CV_DEFAULT(3), + int use_harris CV_DEFAULT(0), + double k CV_DEFAULT(0.04) ); + +/** @brief Finds lines on binary image using one of several methods. + + line_storage is either memory storage or 1 x _max number of lines_ CvMat, its + number of columns is changed by the function. + method is one of CV_HOUGH_*; + rho, theta and threshold are used for each of those methods; + param1 ~ line length, param2 ~ line gap - for probabilistic, + param1 ~ srn, param2 ~ stn - for multi-scale +@see cv::HoughLines +*/ +CVAPI(CvSeq*) cvHoughLines2( CvArr* image, void* line_storage, int method, + double rho, double theta, int threshold, + double param1 CV_DEFAULT(0), double param2 CV_DEFAULT(0), + double min_theta CV_DEFAULT(0), double max_theta CV_DEFAULT(CV_PI)); + +/** @brief Finds circles in the image +@see cv::HoughCircles +*/ +CVAPI(CvSeq*) cvHoughCircles( CvArr* image, void* circle_storage, + int method, double dp, double min_dist, + double param1 CV_DEFAULT(100), + double param2 CV_DEFAULT(100), + int min_radius CV_DEFAULT(0), + int max_radius CV_DEFAULT(0)); + +/** @brief Fits a line into set of 2d or 3d points in a robust way (M-estimator technique) +@see cv::fitLine +*/ +CVAPI(void) cvFitLine( const CvArr* points, int dist_type, double param, + double reps, double aeps, float* line ); + +/****************************************************************************************\ +* Drawing * +\****************************************************************************************/ + +/****************************************************************************************\ +* Drawing functions work with images/matrices of arbitrary type. * +* For color images the channel order is BGR[A] * +* Antialiasing is supported only for 8-bit image now. * +* All the functions include parameter color that means rgb value (that may be * +* constructed with CV_RGB macro) for color images and brightness * +* for grayscale images. * +* If a drawn figure is partially or completely outside of the image, it is clipped.* +\****************************************************************************************/ + +#define CV_FILLED -1 + +#define CV_AA 16 + +/** @brief Draws 4-connected, 8-connected or antialiased line segment connecting two points +@see cv::line +*/ +CVAPI(void) cvLine( CvArr* img, CvPoint pt1, CvPoint pt2, + CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) ); + +/** @brief Draws a rectangle given two opposite corners of the rectangle (pt1 & pt2) + + if thickness<0 (e.g. thickness == CV_FILLED), the filled box is drawn +@see cv::rectangle +*/ +CVAPI(void) cvRectangle( CvArr* img, CvPoint pt1, CvPoint pt2, + CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), + int shift CV_DEFAULT(0)); + +/** @brief Draws a rectangle specified by a CvRect structure +@see cv::rectangle +*/ +CVAPI(void) cvRectangleR( CvArr* img, CvRect r, + CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), + int shift CV_DEFAULT(0)); + + +/** @brief Draws a circle with specified center and radius. + + Thickness works in the same way as with cvRectangle +@see cv::circle +*/ +CVAPI(void) cvCircle( CvArr* img, CvPoint center, int radius, + CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0)); + +/** @brief Draws ellipse outline, filled ellipse, elliptic arc or filled elliptic sector + + depending on _thickness_, _start_angle_ and _end_angle_ parameters. The resultant figure + is rotated by _angle_. All the angles are in degrees +@see cv::ellipse +*/ +CVAPI(void) cvEllipse( CvArr* img, CvPoint center, CvSize axes, + double angle, double start_angle, double end_angle, + CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0)); + +CV_INLINE void cvEllipseBox( CvArr* img, CvBox2D box, CvScalar color, + int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) ) +{ + CvSize axes = cvSize( + cvRound(box.size.width*0.5), + cvRound(box.size.height*0.5) + ); + + cvEllipse( img, cvPointFrom32f( box.center ), axes, box.angle, + 0, 360, color, thickness, line_type, shift ); +} + +/** @brief Fills convex or monotonous polygon. +@see cv::fillConvexPoly +*/ +CVAPI(void) cvFillConvexPoly( CvArr* img, const CvPoint* pts, int npts, CvScalar color, + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0)); + +/** @brief Fills an area bounded by one or more arbitrary polygons +@see cv::fillPoly +*/ +CVAPI(void) cvFillPoly( CvArr* img, CvPoint** pts, const int* npts, + int contours, CvScalar color, + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) ); + +/** @brief Draws one or more polygonal curves +@see cv::polylines +*/ +CVAPI(void) cvPolyLine( CvArr* img, CvPoint** pts, const int* npts, int contours, + int is_closed, CvScalar color, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) ); + +#define cvDrawRect cvRectangle +#define cvDrawLine cvLine +#define cvDrawCircle cvCircle +#define cvDrawEllipse cvEllipse +#define cvDrawPolyLine cvPolyLine + +/** @brief Clips the line segment connecting *pt1 and *pt2 + by the rectangular window + + (0<=xptr will point to pt1 (or pt2, see left_to_right description) location in +the image. Returns the number of pixels on the line between the ending points. +@see cv::LineIterator +*/ +CVAPI(int) cvInitLineIterator( const CvArr* image, CvPoint pt1, CvPoint pt2, + CvLineIterator* line_iterator, + int connectivity CV_DEFAULT(8), + int left_to_right CV_DEFAULT(0)); + +#define CV_NEXT_LINE_POINT( line_iterator ) \ +{ \ + int _line_iterator_mask = (line_iterator).err < 0 ? -1 : 0; \ + (line_iterator).err += (line_iterator).minus_delta + \ + ((line_iterator).plus_delta & _line_iterator_mask); \ + (line_iterator).ptr += (line_iterator).minus_step + \ + ((line_iterator).plus_step & _line_iterator_mask); \ +} + + +#define CV_FONT_HERSHEY_SIMPLEX 0 +#define CV_FONT_HERSHEY_PLAIN 1 +#define CV_FONT_HERSHEY_DUPLEX 2 +#define CV_FONT_HERSHEY_COMPLEX 3 +#define CV_FONT_HERSHEY_TRIPLEX 4 +#define CV_FONT_HERSHEY_COMPLEX_SMALL 5 +#define CV_FONT_HERSHEY_SCRIPT_SIMPLEX 6 +#define CV_FONT_HERSHEY_SCRIPT_COMPLEX 7 + +#define CV_FONT_ITALIC 16 + +#define CV_FONT_VECTOR0 CV_FONT_HERSHEY_SIMPLEX + + +/** Font structure */ +typedef struct CvFont +{ + const char* nameFont; //Qt:nameFont + CvScalar color; //Qt:ColorFont -> cvScalar(blue_component, green_component, red_component[, alpha_component]) + int font_face; //Qt: bool italic /** =CV_FONT_* */ + const int* ascii; //!< font data and metrics + const int* greek; + const int* cyrillic; + float hscale, vscale; + float shear; //!< slope coefficient: 0 - normal, >0 - italic + int thickness; //!< Qt: weight /** letters thickness */ + float dx; //!< horizontal interval between letters + int line_type; //!< Qt: PointSize +} +CvFont; + +/** @brief Initializes font structure (OpenCV 1.x API). + +The function initializes the font structure that can be passed to text rendering functions. + +@param font Pointer to the font structure initialized by the function +@param font_face Font name identifier. See cv::HersheyFonts and corresponding old CV_* identifiers. +@param hscale Horizontal scale. If equal to 1.0f , the characters have the original width +depending on the font type. If equal to 0.5f , the characters are of half the original width. +@param vscale Vertical scale. If equal to 1.0f , the characters have the original height depending +on the font type. If equal to 0.5f , the characters are of half the original height. +@param shear Approximate tangent of the character slope relative to the vertical line. A zero +value means a non-italic font, 1.0f means about a 45 degree slope, etc. +@param thickness Thickness of the text strokes +@param line_type Type of the strokes, see line description + +@sa cvPutText + */ +CVAPI(void) cvInitFont( CvFont* font, int font_face, + double hscale, double vscale, + double shear CV_DEFAULT(0), + int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8)); + +CV_INLINE CvFont cvFont( double scale, int thickness CV_DEFAULT(1) ) +{ + CvFont font; + cvInitFont( &font, CV_FONT_HERSHEY_PLAIN, scale, scale, 0, thickness, CV_AA ); + return font; +} + +/** @brief Renders text stroke with specified font and color at specified location. + CvFont should be initialized with cvInitFont +@see cvInitFont, cvGetTextSize, cvFont, cv::putText +*/ +CVAPI(void) cvPutText( CvArr* img, const char* text, CvPoint org, + const CvFont* font, CvScalar color ); + +/** @brief Calculates bounding box of text stroke (useful for alignment) +@see cv::getTextSize +*/ +CVAPI(void) cvGetTextSize( const char* text_string, const CvFont* font, + CvSize* text_size, int* baseline ); + +/** @brief Unpacks color value + +if arrtype is CV_8UC?, _color_ is treated as packed color value, otherwise the first channels +(depending on arrtype) of destination scalar are set to the same value = _color_ +*/ +CVAPI(CvScalar) cvColorToScalar( double packed_color, int arrtype ); + +/** @brief Returns the polygon points which make up the given ellipse. + +The ellipse is define by the box of size 'axes' rotated 'angle' around the 'center'. A partial +sweep of the ellipse arc can be done by spcifying arc_start and arc_end to be something other than +0 and 360, respectively. The input array 'pts' must be large enough to hold the result. The total +number of points stored into 'pts' is returned by this function. +@see cv::ellipse2Poly +*/ +CVAPI(int) cvEllipse2Poly( CvPoint center, CvSize axes, + int angle, int arc_start, int arc_end, CvPoint * pts, int delta ); + +/** @brief Draws contour outlines or filled interiors on the image +@see cv::drawContours +*/ +CVAPI(void) cvDrawContours( CvArr *img, CvSeq* contour, + CvScalar external_color, CvScalar hole_color, + int max_level, int thickness CV_DEFAULT(1), + int line_type CV_DEFAULT(8), + CvPoint offset CV_DEFAULT(cvPoint(0,0))); + +/** @} */ + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/imgproc/types_c.h b/3rdparty/opencv/include/opencv2/imgproc/types_c.h new file mode 100644 index 00000000..d3e55f57 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/imgproc/types_c.h @@ -0,0 +1,659 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_IMGPROC_TYPES_C_H +#define OPENCV_IMGPROC_TYPES_C_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup imgproc_c + @{ +*/ + +/** Connected component structure */ +typedef struct CvConnectedComp +{ + double area; /** DBL_EPSILON ? 1./std::sqrt(am00) : 0; + } + operator cv::Moments() const + { + return cv::Moments(m00, m10, m01, m20, m11, m02, m30, m21, m12, m03); + } +#endif +} +CvMoments; + +#ifdef __cplusplus +} // extern "C" + +CV_INLINE CvMoments cvMoments() +{ +#if !defined(CV__ENABLE_C_API_CTORS) + CvMoments self = CV_STRUCT_INITIALIZER; return self; +#else + return CvMoments(); +#endif +} + +CV_INLINE CvMoments cvMoments(const cv::Moments& m) +{ +#if !defined(CV__ENABLE_C_API_CTORS) + double am00 = std::abs(m.m00); + CvMoments self = { + m.m00, m.m10, m.m01, m.m20, m.m11, m.m02, m.m30, m.m21, m.m12, m.m03, + m.mu20, m.mu11, m.mu02, m.mu30, m.mu21, m.mu12, m.mu03, + am00 > DBL_EPSILON ? 1./std::sqrt(am00) : 0 + }; + return self; +#else + return CvMoments(m); +#endif +} + +extern "C" { +#endif // __cplusplus + +/** Hu invariants */ +typedef struct CvHuMoments +{ + double hu1, hu2, hu3, hu4, hu5, hu6, hu7; /**< Hu invariants */ +} +CvHuMoments; + +/** Template matching methods */ +enum +{ + CV_TM_SQDIFF =0, + CV_TM_SQDIFF_NORMED =1, + CV_TM_CCORR =2, + CV_TM_CCORR_NORMED =3, + CV_TM_CCOEFF =4, + CV_TM_CCOEFF_NORMED =5 +}; + +typedef float (CV_CDECL * CvDistanceFunction)( const float* a, const float* b, void* user_param ); + +/** Contour retrieval modes */ +enum +{ + CV_RETR_EXTERNAL=0, + CV_RETR_LIST=1, + CV_RETR_CCOMP=2, + CV_RETR_TREE=3, + CV_RETR_FLOODFILL=4 +}; + +/** Contour approximation methods */ +enum +{ + CV_CHAIN_CODE=0, + CV_CHAIN_APPROX_NONE=1, + CV_CHAIN_APPROX_SIMPLE=2, + CV_CHAIN_APPROX_TC89_L1=3, + CV_CHAIN_APPROX_TC89_KCOS=4, + CV_LINK_RUNS=5 +}; + +/* +Internal structure that is used for sequential retrieving contours from the image. +It supports both hierarchical and plane variants of Suzuki algorithm. +*/ +typedef struct _CvContourScanner* CvContourScanner; + +/** Freeman chain reader state */ +typedef struct CvChainPtReader +{ + CV_SEQ_READER_FIELDS() + char code; + CvPoint pt; + schar deltas[8][2]; +} +CvChainPtReader; + +/** initializes 8-element array for fast access to 3x3 neighborhood of a pixel */ +#define CV_INIT_3X3_DELTAS( deltas, step, nch ) \ + ((deltas)[0] = (nch), (deltas)[1] = -(step) + (nch), \ + (deltas)[2] = -(step), (deltas)[3] = -(step) - (nch), \ + (deltas)[4] = -(nch), (deltas)[5] = (step) - (nch), \ + (deltas)[6] = (step), (deltas)[7] = (step) + (nch)) + + +/** Contour approximation algorithms */ +enum +{ + CV_POLY_APPROX_DP = 0 +}; + +/** Shape matching methods */ +enum +{ + CV_CONTOURS_MATCH_I1 =1, //!< \f[I_1(A,B) = \sum _{i=1...7} \left | \frac{1}{m^A_i} - \frac{1}{m^B_i} \right |\f] + CV_CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f] + CV_CONTOURS_MATCH_I3 =3 //!< \f[I_3(A,B) = \max _{i=1...7} \frac{ \left| m^A_i - m^B_i \right| }{ \left| m^A_i \right| }\f] +}; + +/** Shape orientation */ +enum +{ + CV_CLOCKWISE =1, + CV_COUNTER_CLOCKWISE =2 +}; + + +/** Convexity defect */ +typedef struct CvConvexityDefect +{ + CvPoint* start; /**< point of the contour where the defect begins */ + CvPoint* end; /**< point of the contour where the defect ends */ + CvPoint* depth_point; /**< the farthest from the convex hull point within the defect */ + float depth; /**< distance between the farthest point and the convex hull */ +} CvConvexityDefect; + + +/** Histogram comparison methods */ +enum +{ + CV_COMP_CORREL =0, + CV_COMP_CHISQR =1, + CV_COMP_INTERSECT =2, + CV_COMP_BHATTACHARYYA =3, + CV_COMP_HELLINGER =CV_COMP_BHATTACHARYYA, + CV_COMP_CHISQR_ALT =4, + CV_COMP_KL_DIV =5 +}; + +/** Mask size for distance transform */ +enum +{ + CV_DIST_MASK_3 =3, + CV_DIST_MASK_5 =5, + CV_DIST_MASK_PRECISE =0 +}; + +/** Content of output label array: connected components or pixels */ +enum +{ + CV_DIST_LABEL_CCOMP = 0, + CV_DIST_LABEL_PIXEL = 1 +}; + +/** Distance types for Distance Transform and M-estimators */ +enum +{ + CV_DIST_USER =-1, /**< User defined distance */ + CV_DIST_L1 =1, /**< distance = |x1-x2| + |y1-y2| */ + CV_DIST_L2 =2, /**< the simple euclidean distance */ + CV_DIST_C =3, /**< distance = max(|x1-x2|,|y1-y2|) */ + CV_DIST_L12 =4, /**< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) */ + CV_DIST_FAIR =5, /**< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 */ + CV_DIST_WELSCH =6, /**< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 */ + CV_DIST_HUBER =7 /**< distance = |x| threshold ? max_value : 0 */ + CV_THRESH_BINARY_INV =1, /**< value = value > threshold ? 0 : max_value */ + CV_THRESH_TRUNC =2, /**< value = value > threshold ? threshold : value */ + CV_THRESH_TOZERO =3, /**< value = value > threshold ? value : 0 */ + CV_THRESH_TOZERO_INV =4, /**< value = value > threshold ? 0 : value */ + CV_THRESH_MASK =7, + CV_THRESH_OTSU =8, /**< use Otsu algorithm to choose the optimal threshold value; + combine the flag with one of the above CV_THRESH_* values */ + CV_THRESH_TRIANGLE =16 /**< use Triangle algorithm to choose the optimal threshold value; + combine the flag with one of the above CV_THRESH_* values, but not + with CV_THRESH_OTSU */ +}; + +/** Adaptive threshold methods */ +enum +{ + CV_ADAPTIVE_THRESH_MEAN_C =0, + CV_ADAPTIVE_THRESH_GAUSSIAN_C =1 +}; + +/** FloodFill flags */ +enum +{ + CV_FLOODFILL_FIXED_RANGE =(1 << 16), + CV_FLOODFILL_MASK_ONLY =(1 << 17) +}; + + +/** Canny edge detector flags */ +enum +{ + CV_CANNY_L2_GRADIENT =(1 << 31) +}; + +/** Variants of a Hough transform */ +enum +{ + CV_HOUGH_STANDARD =0, + CV_HOUGH_PROBABILISTIC =1, + CV_HOUGH_MULTI_SCALE =2, + CV_HOUGH_GRADIENT =3 +}; + + +/* Fast search data structures */ +struct CvFeatureTree; +struct CvLSH; +struct CvLSHOperations; + +/** @} */ + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/ml.hpp b/3rdparty/opencv/include/opencv2/ml.hpp new file mode 100644 index 00000000..53482064 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/ml.hpp @@ -0,0 +1,1972 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Copyright (C) 2014, Itseez Inc, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_ML_HPP +#define OPENCV_ML_HPP + +#ifdef __cplusplus +# include "opencv2/core.hpp" +#endif + +#ifdef __cplusplus + +#include +#include +#include + +/** + @defgroup ml Machine Learning + + The Machine Learning Library (MLL) is a set of classes and functions for statistical + classification, regression, and clustering of data. + + Most of the classification and regression algorithms are implemented as C++ classes. As the + algorithms have different sets of features (like an ability to handle missing measurements or + categorical input variables), there is a little common ground between the classes. This common + ground is defined by the class cv::ml::StatModel that all the other ML classes are derived from. + + See detailed overview here: @ref ml_intro. + */ + +namespace cv +{ + +namespace ml +{ + +//! @addtogroup ml +//! @{ + +/** @brief Variable types */ +enum VariableTypes +{ + VAR_NUMERICAL =0, //!< same as VAR_ORDERED + VAR_ORDERED =0, //!< ordered variables + VAR_CATEGORICAL =1 //!< categorical variables +}; + +/** @brief %Error types */ +enum ErrorTypes +{ + TEST_ERROR = 0, + TRAIN_ERROR = 1 +}; + +/** @brief Sample types */ +enum SampleTypes +{ + ROW_SAMPLE = 0, //!< each training sample is a row of samples + COL_SAMPLE = 1 //!< each training sample occupies a column of samples +}; + +/** @brief The structure represents the logarithmic grid range of statmodel parameters. + +It is used for optimizing statmodel accuracy by varying model parameters, the accuracy estimate +being computed by cross-validation. + */ +class CV_EXPORTS_W ParamGrid +{ +public: + /** @brief Default constructor */ + ParamGrid(); + /** @brief Constructor with parameters */ + ParamGrid(double _minVal, double _maxVal, double _logStep); + + CV_PROP_RW double minVal; //!< Minimum value of the statmodel parameter. Default value is 0. + CV_PROP_RW double maxVal; //!< Maximum value of the statmodel parameter. Default value is 0. + /** @brief Logarithmic step for iterating the statmodel parameter. + + The grid determines the following iteration sequence of the statmodel parameter values: + \f[(minVal, minVal*step, minVal*{step}^2, \dots, minVal*{logStep}^n),\f] + where \f$n\f$ is the maximal index satisfying + \f[\texttt{minVal} * \texttt{logStep} ^n < \texttt{maxVal}\f] + The grid is logarithmic, so logStep must always be greater than 1. Default value is 1. + */ + CV_PROP_RW double logStep; + + /** @brief Creates a ParamGrid Ptr that can be given to the %SVM::trainAuto method + + @param minVal minimum value of the parameter grid + @param maxVal maximum value of the parameter grid + @param logstep Logarithmic step for iterating the statmodel parameter + */ + CV_WRAP static Ptr create(double minVal=0., double maxVal=0., double logstep=1.); +}; + +/** @brief Class encapsulating training data. + +Please note that the class only specifies the interface of training data, but not implementation. +All the statistical model classes in _ml_ module accepts Ptr\ as parameter. In other +words, you can create your own class derived from TrainData and pass smart pointer to the instance +of this class into StatModel::train. + +@sa @ref ml_intro_data + */ +class CV_EXPORTS_W TrainData +{ +public: + static inline float missingValue() { return FLT_MAX; } + virtual ~TrainData(); + + CV_WRAP virtual int getLayout() const = 0; + CV_WRAP virtual int getNTrainSamples() const = 0; + CV_WRAP virtual int getNTestSamples() const = 0; + CV_WRAP virtual int getNSamples() const = 0; + CV_WRAP virtual int getNVars() const = 0; + CV_WRAP virtual int getNAllVars() const = 0; + + CV_WRAP virtual void getSample(InputArray varIdx, int sidx, float* buf) const = 0; + CV_WRAP virtual Mat getSamples() const = 0; + CV_WRAP virtual Mat getMissing() const = 0; + + /** @brief Returns matrix of train samples + + @param layout The requested layout. If it's different from the initial one, the matrix is + transposed. See ml::SampleTypes. + @param compressSamples if true, the function returns only the training samples (specified by + sampleIdx) + @param compressVars if true, the function returns the shorter training samples, containing only + the active variables. + + In current implementation the function tries to avoid physical data copying and returns the + matrix stored inside TrainData (unless the transposition or compression is needed). + */ + CV_WRAP virtual Mat getTrainSamples(int layout=ROW_SAMPLE, + bool compressSamples=true, + bool compressVars=true) const = 0; + + /** @brief Returns the vector of responses + + The function returns ordered or the original categorical responses. Usually it's used in + regression algorithms. + */ + CV_WRAP virtual Mat getTrainResponses() const = 0; + + /** @brief Returns the vector of normalized categorical responses + + The function returns vector of responses. Each response is integer from `0` to `-1`. The actual label value can be retrieved then from the class label vector, see + TrainData::getClassLabels. + */ + CV_WRAP virtual Mat getTrainNormCatResponses() const = 0; + CV_WRAP virtual Mat getTestResponses() const = 0; + CV_WRAP virtual Mat getTestNormCatResponses() const = 0; + CV_WRAP virtual Mat getResponses() const = 0; + CV_WRAP virtual Mat getNormCatResponses() const = 0; + CV_WRAP virtual Mat getSampleWeights() const = 0; + CV_WRAP virtual Mat getTrainSampleWeights() const = 0; + CV_WRAP virtual Mat getTestSampleWeights() const = 0; + CV_WRAP virtual Mat getVarIdx() const = 0; + CV_WRAP virtual Mat getVarType() const = 0; + CV_WRAP Mat getVarSymbolFlags() const; + CV_WRAP virtual int getResponseType() const = 0; + CV_WRAP virtual Mat getTrainSampleIdx() const = 0; + CV_WRAP virtual Mat getTestSampleIdx() const = 0; + CV_WRAP virtual void getValues(int vi, InputArray sidx, float* values) const = 0; + virtual void getNormCatValues(int vi, InputArray sidx, int* values) const = 0; + CV_WRAP virtual Mat getDefaultSubstValues() const = 0; + + CV_WRAP virtual int getCatCount(int vi) const = 0; + + /** @brief Returns the vector of class labels + + The function returns vector of unique labels occurred in the responses. + */ + CV_WRAP virtual Mat getClassLabels() const = 0; + + CV_WRAP virtual Mat getCatOfs() const = 0; + CV_WRAP virtual Mat getCatMap() const = 0; + + /** @brief Splits the training data into the training and test parts + @sa TrainData::setTrainTestSplitRatio + */ + CV_WRAP virtual void setTrainTestSplit(int count, bool shuffle=true) = 0; + + /** @brief Splits the training data into the training and test parts + + The function selects a subset of specified relative size and then returns it as the training + set. If the function is not called, all the data is used for training. Please, note that for + each of TrainData::getTrain\* there is corresponding TrainData::getTest\*, so that the test + subset can be retrieved and processed as well. + @sa TrainData::setTrainTestSplit + */ + CV_WRAP virtual void setTrainTestSplitRatio(double ratio, bool shuffle=true) = 0; + CV_WRAP virtual void shuffleTrainTest() = 0; + + /** @brief Returns matrix of test samples */ + CV_WRAP Mat getTestSamples() const; + + /** @brief Returns vector of symbolic names captured in loadFromCSV() */ + CV_WRAP void getNames(std::vector& names) const; + + /** @brief Extract from 1D vector elements specified by passed indexes. + @param vec input vector (supported types: CV_32S, CV_32F, CV_64F) + @param idx 1D index vector + */ + static CV_WRAP Mat getSubVector(const Mat& vec, const Mat& idx); + + /** @brief Extract from matrix rows/cols specified by passed indexes. + @param matrix input matrix (supported types: CV_32S, CV_32F, CV_64F) + @param idx 1D index vector + @param layout specifies to extract rows (cv::ml::ROW_SAMPLES) or to extract columns (cv::ml::COL_SAMPLES) + */ + static CV_WRAP Mat getSubMatrix(const Mat& matrix, const Mat& idx, int layout); + + /** @brief Reads the dataset from a .csv file and returns the ready-to-use training data. + + @param filename The input file name + @param headerLineCount The number of lines in the beginning to skip; besides the header, the + function also skips empty lines and lines staring with `#` + @param responseStartIdx Index of the first output variable. If -1, the function considers the + last variable as the response + @param responseEndIdx Index of the last output variable + 1. If -1, then there is single + response variable at responseStartIdx. + @param varTypeSpec The optional text string that specifies the variables' types. It has the + format `ord[n1-n2,n3,n4-n5,...]cat[n6,n7-n8,...]`. That is, variables from `n1 to n2` + (inclusive range), `n3`, `n4 to n5` ... are considered ordered and `n6`, `n7 to n8` ... are + considered as categorical. The range `[n1..n2] + [n3] + [n4..n5] + ... + [n6] + [n7..n8]` + should cover all the variables. If varTypeSpec is not specified, then algorithm uses the + following rules: + - all input variables are considered ordered by default. If some column contains has non- + numerical values, e.g. 'apple', 'pear', 'apple', 'apple', 'mango', the corresponding + variable is considered categorical. + - if there are several output variables, they are all considered as ordered. Error is + reported when non-numerical values are used. + - if there is a single output variable, then if its values are non-numerical or are all + integers, then it's considered categorical. Otherwise, it's considered ordered. + @param delimiter The character used to separate values in each line. + @param missch The character used to specify missing measurements. It should not be a digit. + Although it's a non-numerical value, it surely does not affect the decision of whether the + variable ordered or categorical. + @note If the dataset only contains input variables and no responses, use responseStartIdx = -2 + and responseEndIdx = 0. The output variables vector will just contain zeros. + */ + static Ptr loadFromCSV(const String& filename, + int headerLineCount, + int responseStartIdx=-1, + int responseEndIdx=-1, + const String& varTypeSpec=String(), + char delimiter=',', + char missch='?'); + + /** @brief Creates training data from in-memory arrays. + + @param samples matrix of samples. It should have CV_32F type. + @param layout see ml::SampleTypes. + @param responses matrix of responses. If the responses are scalar, they should be stored as a + single row or as a single column. The matrix should have type CV_32F or CV_32S (in the + former case the responses are considered as ordered by default; in the latter case - as + categorical) + @param varIdx vector specifying which variables to use for training. It can be an integer vector + (CV_32S) containing 0-based variable indices or byte vector (CV_8U) containing a mask of + active variables. + @param sampleIdx vector specifying which samples to use for training. It can be an integer + vector (CV_32S) containing 0-based sample indices or byte vector (CV_8U) containing a mask + of training samples. + @param sampleWeights optional vector with weights for each sample. It should have CV_32F type. + @param varType optional vector of type CV_8U and size ` + + `, containing types of each input and output variable. See + ml::VariableTypes. + */ + CV_WRAP static Ptr create(InputArray samples, int layout, InputArray responses, + InputArray varIdx=noArray(), InputArray sampleIdx=noArray(), + InputArray sampleWeights=noArray(), InputArray varType=noArray()); +}; + +/** @brief Base class for statistical models in OpenCV ML. + */ +class CV_EXPORTS_W StatModel : public Algorithm +{ +public: + /** Predict options */ + enum Flags { + UPDATE_MODEL = 1, + RAW_OUTPUT=1, //!< makes the method return the raw results (the sum), not the class label + COMPRESSED_INPUT=2, + PREPROCESSED_INPUT=4 + }; + + /** @brief Returns the number of variables in training samples */ + CV_WRAP virtual int getVarCount() const = 0; + + CV_WRAP virtual bool empty() const CV_OVERRIDE; + + /** @brief Returns true if the model is trained */ + CV_WRAP virtual bool isTrained() const = 0; + /** @brief Returns true if the model is classifier */ + CV_WRAP virtual bool isClassifier() const = 0; + + /** @brief Trains the statistical model + + @param trainData training data that can be loaded from file using TrainData::loadFromCSV or + created with TrainData::create. + @param flags optional flags, depending on the model. Some of the models can be updated with the + new training samples, not completely overwritten (such as NormalBayesClassifier or ANN_MLP). + */ + CV_WRAP virtual bool train( const Ptr& trainData, int flags=0 ); + + /** @brief Trains the statistical model + + @param samples training samples + @param layout See ml::SampleTypes. + @param responses vector of responses associated with the training samples. + */ + CV_WRAP virtual bool train( InputArray samples, int layout, InputArray responses ); + + /** @brief Computes error on the training or test dataset + + @param data the training data + @param test if true, the error is computed over the test subset of the data, otherwise it's + computed over the training subset of the data. Please note that if you loaded a completely + different dataset to evaluate already trained classifier, you will probably want not to set + the test subset at all with TrainData::setTrainTestSplitRatio and specify test=false, so + that the error is computed for the whole new set. Yes, this sounds a bit confusing. + @param resp the optional output responses. + + The method uses StatModel::predict to compute the error. For regression models the error is + computed as RMS, for classifiers - as a percent of missclassified samples (0%-100%). + */ + CV_WRAP virtual float calcError( const Ptr& data, bool test, OutputArray resp ) const; + + /** @brief Predicts response(s) for the provided sample(s) + + @param samples The input samples, floating-point matrix + @param results The optional output matrix of results. + @param flags The optional flags, model-dependent. See cv::ml::StatModel::Flags. + */ + CV_WRAP virtual float predict( InputArray samples, OutputArray results=noArray(), int flags=0 ) const = 0; + + /** @brief Create and train model with default parameters + + The class must implement static `create()` method with no parameters or with all default parameter values + */ + template static Ptr<_Tp> train(const Ptr& data, int flags=0) + { + Ptr<_Tp> model = _Tp::create(); + return !model.empty() && model->train(data, flags) ? model : Ptr<_Tp>(); + } +}; + +/****************************************************************************************\ +* Normal Bayes Classifier * +\****************************************************************************************/ + +/** @brief Bayes classifier for normally distributed data. + +@sa @ref ml_intro_bayes + */ +class CV_EXPORTS_W NormalBayesClassifier : public StatModel +{ +public: + /** @brief Predicts the response for sample(s). + + The method estimates the most probable classes for input vectors. Input vectors (one or more) + are stored as rows of the matrix inputs. In case of multiple input vectors, there should be one + output vector outputs. The predicted class for a single input vector is returned by the method. + The vector outputProbs contains the output probabilities corresponding to each element of + result. + */ + CV_WRAP virtual float predictProb( InputArray inputs, OutputArray outputs, + OutputArray outputProbs, int flags=0 ) const = 0; + + /** Creates empty model + Use StatModel::train to train the model after creation. */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized NormalBayesClassifier from a file + * + * Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk. + * Load the NormalBayesClassifier from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized NormalBayesClassifier + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + +/****************************************************************************************\ +* K-Nearest Neighbour Classifier * +\****************************************************************************************/ + +/** @brief The class implements K-Nearest Neighbors model + +@sa @ref ml_intro_knn + */ +class CV_EXPORTS_W KNearest : public StatModel +{ +public: + + /** Default number of neighbors to use in predict method. */ + /** @see setDefaultK */ + CV_WRAP virtual int getDefaultK() const = 0; + /** @copybrief getDefaultK @see getDefaultK */ + CV_WRAP virtual void setDefaultK(int val) = 0; + + /** Whether classification or regression model should be trained. */ + /** @see setIsClassifier */ + CV_WRAP virtual bool getIsClassifier() const = 0; + /** @copybrief getIsClassifier @see getIsClassifier */ + CV_WRAP virtual void setIsClassifier(bool val) = 0; + + /** Parameter for KDTree implementation. */ + /** @see setEmax */ + CV_WRAP virtual int getEmax() const = 0; + /** @copybrief getEmax @see getEmax */ + CV_WRAP virtual void setEmax(int val) = 0; + + /** %Algorithm type, one of KNearest::Types. */ + /** @see setAlgorithmType */ + CV_WRAP virtual int getAlgorithmType() const = 0; + /** @copybrief getAlgorithmType @see getAlgorithmType */ + CV_WRAP virtual void setAlgorithmType(int val) = 0; + + /** @brief Finds the neighbors and predicts responses for input vectors. + + @param samples Input samples stored by rows. It is a single-precision floating-point matrix of + ` * k` size. + @param k Number of used nearest neighbors. Should be greater than 1. + @param results Vector with results of prediction (regression or classification) for each input + sample. It is a single-precision floating-point vector with `` elements. + @param neighborResponses Optional output values for corresponding neighbors. It is a single- + precision floating-point matrix of ` * k` size. + @param dist Optional output distances from the input vectors to the corresponding neighbors. It + is a single-precision floating-point matrix of ` * k` size. + + For each input vector (a row of the matrix samples), the method finds the k nearest neighbors. + In case of regression, the predicted result is a mean value of the particular vector's neighbor + responses. In case of classification, the class is determined by voting. + + For each input vector, the neighbors are sorted by their distances to the vector. + + In case of C++ interface you can use output pointers to empty matrices and the function will + allocate memory itself. + + If only a single input vector is passed, all output matrices are optional and the predicted + value is returned by the method. + + The function is parallelized with the TBB library. + */ + CV_WRAP virtual float findNearest( InputArray samples, int k, + OutputArray results, + OutputArray neighborResponses=noArray(), + OutputArray dist=noArray() ) const = 0; + + /** @brief Implementations of KNearest algorithm + */ + enum Types + { + BRUTE_FORCE=1, + KDTREE=2 + }; + + /** @brief Creates the empty model + + The static method creates empty %KNearest classifier. It should be then trained using StatModel::train method. + */ + CV_WRAP static Ptr create(); +}; + +/****************************************************************************************\ +* Support Vector Machines * +\****************************************************************************************/ + +/** @brief Support Vector Machines. + +@sa @ref ml_intro_svm + */ +class CV_EXPORTS_W SVM : public StatModel +{ +public: + + class CV_EXPORTS Kernel : public Algorithm + { + public: + virtual int getType() const = 0; + virtual void calc( int vcount, int n, const float* vecs, const float* another, float* results ) = 0; + }; + + /** Type of a %SVM formulation. + See SVM::Types. Default value is SVM::C_SVC. */ + /** @see setType */ + CV_WRAP virtual int getType() const = 0; + /** @copybrief getType @see getType */ + CV_WRAP virtual void setType(int val) = 0; + + /** Parameter \f$\gamma\f$ of a kernel function. + For SVM::POLY, SVM::RBF, SVM::SIGMOID or SVM::CHI2. Default value is 1. */ + /** @see setGamma */ + CV_WRAP virtual double getGamma() const = 0; + /** @copybrief getGamma @see getGamma */ + CV_WRAP virtual void setGamma(double val) = 0; + + /** Parameter _coef0_ of a kernel function. + For SVM::POLY or SVM::SIGMOID. Default value is 0.*/ + /** @see setCoef0 */ + CV_WRAP virtual double getCoef0() const = 0; + /** @copybrief getCoef0 @see getCoef0 */ + CV_WRAP virtual void setCoef0(double val) = 0; + + /** Parameter _degree_ of a kernel function. + For SVM::POLY. Default value is 0. */ + /** @see setDegree */ + CV_WRAP virtual double getDegree() const = 0; + /** @copybrief getDegree @see getDegree */ + CV_WRAP virtual void setDegree(double val) = 0; + + /** Parameter _C_ of a %SVM optimization problem. + For SVM::C_SVC, SVM::EPS_SVR or SVM::NU_SVR. Default value is 0. */ + /** @see setC */ + CV_WRAP virtual double getC() const = 0; + /** @copybrief getC @see getC */ + CV_WRAP virtual void setC(double val) = 0; + + /** Parameter \f$\nu\f$ of a %SVM optimization problem. + For SVM::NU_SVC, SVM::ONE_CLASS or SVM::NU_SVR. Default value is 0. */ + /** @see setNu */ + CV_WRAP virtual double getNu() const = 0; + /** @copybrief getNu @see getNu */ + CV_WRAP virtual void setNu(double val) = 0; + + /** Parameter \f$\epsilon\f$ of a %SVM optimization problem. + For SVM::EPS_SVR. Default value is 0. */ + /** @see setP */ + CV_WRAP virtual double getP() const = 0; + /** @copybrief getP @see getP */ + CV_WRAP virtual void setP(double val) = 0; + + /** Optional weights in the SVM::C_SVC problem, assigned to particular classes. + They are multiplied by _C_ so the parameter _C_ of class _i_ becomes `classWeights(i) * C`. Thus + these weights affect the misclassification penalty for different classes. The larger weight, + the larger penalty on misclassification of data from the corresponding class. Default value is + empty Mat. */ + /** @see setClassWeights */ + CV_WRAP virtual cv::Mat getClassWeights() const = 0; + /** @copybrief getClassWeights @see getClassWeights */ + CV_WRAP virtual void setClassWeights(const cv::Mat &val) = 0; + + /** Termination criteria of the iterative %SVM training procedure which solves a partial + case of constrained quadratic optimization problem. + You can specify tolerance and/or the maximum number of iterations. Default value is + `TermCriteria( TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, FLT_EPSILON )`; */ + /** @see setTermCriteria */ + CV_WRAP virtual cv::TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(const cv::TermCriteria &val) = 0; + + /** Type of a %SVM kernel. + See SVM::KernelTypes. Default value is SVM::RBF. */ + CV_WRAP virtual int getKernelType() const = 0; + + /** Initialize with one of predefined kernels. + See SVM::KernelTypes. */ + CV_WRAP virtual void setKernel(int kernelType) = 0; + + /** Initialize with custom kernel. + See SVM::Kernel class for implementation details */ + virtual void setCustomKernel(const Ptr &_kernel) = 0; + + //! %SVM type + enum Types { + /** C-Support Vector Classification. n-class classification (n \f$\geq\f$ 2), allows + imperfect separation of classes with penalty multiplier C for outliers. */ + C_SVC=100, + /** \f$\nu\f$-Support Vector Classification. n-class classification with possible + imperfect separation. Parameter \f$\nu\f$ (in the range 0..1, the larger the value, the smoother + the decision boundary) is used instead of C. */ + NU_SVC=101, + /** Distribution Estimation (One-class %SVM). All the training data are from + the same class, %SVM builds a boundary that separates the class from the rest of the feature + space. */ + ONE_CLASS=102, + /** \f$\epsilon\f$-Support Vector Regression. The distance between feature vectors + from the training set and the fitting hyper-plane must be less than p. For outliers the + penalty multiplier C is used. */ + EPS_SVR=103, + /** \f$\nu\f$-Support Vector Regression. \f$\nu\f$ is used instead of p. + See @cite LibSVM for details. */ + NU_SVR=104 + }; + + /** @brief %SVM kernel type + + A comparison of different kernels on the following 2D test case with four classes. Four + SVM::C_SVC SVMs have been trained (one against rest) with auto_train. Evaluation on three + different kernels (SVM::CHI2, SVM::INTER, SVM::RBF). The color depicts the class with max score. + Bright means max-score \> 0, dark means max-score \< 0. + ![image](pics/SVM_Comparison.png) + */ + enum KernelTypes { + /** Returned by SVM::getKernelType in case when custom kernel has been set */ + CUSTOM=-1, + /** Linear kernel. No mapping is done, linear discrimination (or regression) is + done in the original feature space. It is the fastest option. \f$K(x_i, x_j) = x_i^T x_j\f$. */ + LINEAR=0, + /** Polynomial kernel: + \f$K(x_i, x_j) = (\gamma x_i^T x_j + coef0)^{degree}, \gamma > 0\f$. */ + POLY=1, + /** Radial basis function (RBF), a good choice in most cases. + \f$K(x_i, x_j) = e^{-\gamma ||x_i - x_j||^2}, \gamma > 0\f$. */ + RBF=2, + /** Sigmoid kernel: \f$K(x_i, x_j) = \tanh(\gamma x_i^T x_j + coef0)\f$. */ + SIGMOID=3, + /** Exponential Chi2 kernel, similar to the RBF kernel: + \f$K(x_i, x_j) = e^{-\gamma \chi^2(x_i,x_j)}, \chi^2(x_i,x_j) = (x_i-x_j)^2/(x_i+x_j), \gamma > 0\f$. */ + CHI2=4, + /** Histogram intersection kernel. A fast kernel. \f$K(x_i, x_j) = min(x_i,x_j)\f$. */ + INTER=5 + }; + + //! %SVM params type + enum ParamTypes { + C=0, + GAMMA=1, + P=2, + NU=3, + COEF=4, + DEGREE=5 + }; + + /** @brief Trains an %SVM with optimal parameters. + + @param data the training data that can be constructed using TrainData::create or + TrainData::loadFromCSV. + @param kFold Cross-validation parameter. The training set is divided into kFold subsets. One + subset is used to test the model, the others form the train set. So, the %SVM algorithm is + executed kFold times. + @param Cgrid grid for C + @param gammaGrid grid for gamma + @param pGrid grid for p + @param nuGrid grid for nu + @param coeffGrid grid for coeff + @param degreeGrid grid for degree + @param balanced If true and the problem is 2-class classification then the method creates more + balanced cross-validation subsets that is proportions between classes in subsets are close + to such proportion in the whole train dataset. + + The method trains the %SVM model automatically by choosing the optimal parameters C, gamma, p, + nu, coef0, degree. Parameters are considered optimal when the cross-validation + estimate of the test set error is minimal. + + If there is no need to optimize a parameter, the corresponding grid step should be set to any + value less than or equal to 1. For example, to avoid optimization in gamma, set `gammaGrid.step + = 0`, `gammaGrid.minVal`, `gamma_grid.maxVal` as arbitrary numbers. In this case, the value + `Gamma` is taken for gamma. + + And, finally, if the optimization in a parameter is required but the corresponding grid is + unknown, you may call the function SVM::getDefaultGrid. To generate a grid, for example, for + gamma, call `SVM::getDefaultGrid(SVM::GAMMA)`. + + This function works for the classification (SVM::C_SVC or SVM::NU_SVC) as well as for the + regression (SVM::EPS_SVR or SVM::NU_SVR). If it is SVM::ONE_CLASS, no optimization is made and + the usual %SVM with parameters specified in params is executed. + */ + virtual bool trainAuto( const Ptr& data, int kFold = 10, + ParamGrid Cgrid = getDefaultGrid(C), + ParamGrid gammaGrid = getDefaultGrid(GAMMA), + ParamGrid pGrid = getDefaultGrid(P), + ParamGrid nuGrid = getDefaultGrid(NU), + ParamGrid coeffGrid = getDefaultGrid(COEF), + ParamGrid degreeGrid = getDefaultGrid(DEGREE), + bool balanced=false) = 0; + + /** @brief Trains an %SVM with optimal parameters + + @param samples training samples + @param layout See ml::SampleTypes. + @param responses vector of responses associated with the training samples. + @param kFold Cross-validation parameter. The training set is divided into kFold subsets. One + subset is used to test the model, the others form the train set. So, the %SVM algorithm is + @param Cgrid grid for C + @param gammaGrid grid for gamma + @param pGrid grid for p + @param nuGrid grid for nu + @param coeffGrid grid for coeff + @param degreeGrid grid for degree + @param balanced If true and the problem is 2-class classification then the method creates more + balanced cross-validation subsets that is proportions between classes in subsets are close + to such proportion in the whole train dataset. + + The method trains the %SVM model automatically by choosing the optimal parameters C, gamma, p, + nu, coef0, degree. Parameters are considered optimal when the cross-validation + estimate of the test set error is minimal. + + This function only makes use of SVM::getDefaultGrid for parameter optimization and thus only + offers rudimentary parameter options. + + This function works for the classification (SVM::C_SVC or SVM::NU_SVC) as well as for the + regression (SVM::EPS_SVR or SVM::NU_SVR). If it is SVM::ONE_CLASS, no optimization is made and + the usual %SVM with parameters specified in params is executed. + */ + CV_WRAP bool trainAuto(InputArray samples, + int layout, + InputArray responses, + int kFold = 10, + Ptr Cgrid = SVM::getDefaultGridPtr(SVM::C), + Ptr gammaGrid = SVM::getDefaultGridPtr(SVM::GAMMA), + Ptr pGrid = SVM::getDefaultGridPtr(SVM::P), + Ptr nuGrid = SVM::getDefaultGridPtr(SVM::NU), + Ptr coeffGrid = SVM::getDefaultGridPtr(SVM::COEF), + Ptr degreeGrid = SVM::getDefaultGridPtr(SVM::DEGREE), + bool balanced=false); + + /** @brief Retrieves all the support vectors + + The method returns all the support vectors as a floating-point matrix, where support vectors are + stored as matrix rows. + */ + CV_WRAP virtual Mat getSupportVectors() const = 0; + + /** @brief Retrieves all the uncompressed support vectors of a linear %SVM + + The method returns all the uncompressed support vectors of a linear %SVM that the compressed + support vector, used for prediction, was derived from. They are returned in a floating-point + matrix, where the support vectors are stored as matrix rows. + */ + CV_WRAP Mat getUncompressedSupportVectors() const; + + /** @brief Retrieves the decision function + + @param i the index of the decision function. If the problem solved is regression, 1-class or + 2-class classification, then there will be just one decision function and the index should + always be 0. Otherwise, in the case of N-class classification, there will be \f$N(N-1)/2\f$ + decision functions. + @param alpha the optional output vector for weights, corresponding to different support vectors. + In the case of linear %SVM all the alpha's will be 1's. + @param svidx the optional output vector of indices of support vectors within the matrix of + support vectors (which can be retrieved by SVM::getSupportVectors). In the case of linear + %SVM each decision function consists of a single "compressed" support vector. + + The method returns rho parameter of the decision function, a scalar subtracted from the weighted + sum of kernel responses. + */ + CV_WRAP virtual double getDecisionFunction(int i, OutputArray alpha, OutputArray svidx) const = 0; + + /** @brief Generates a grid for %SVM parameters. + + @param param_id %SVM parameters IDs that must be one of the SVM::ParamTypes. The grid is + generated for the parameter with this ID. + + The function generates a grid for the specified parameter of the %SVM algorithm. The grid may be + passed to the function SVM::trainAuto. + */ + static ParamGrid getDefaultGrid( int param_id ); + + /** @brief Generates a grid for %SVM parameters. + + @param param_id %SVM parameters IDs that must be one of the SVM::ParamTypes. The grid is + generated for the parameter with this ID. + + The function generates a grid pointer for the specified parameter of the %SVM algorithm. + The grid may be passed to the function SVM::trainAuto. + */ + CV_WRAP static Ptr getDefaultGridPtr( int param_id ); + + /** Creates empty model. + Use StatModel::train to train the model. Since %SVM has several parameters, you may want to + find the best parameters for your problem, it can be done with SVM::trainAuto. */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized svm from a file + * + * Use SVM::save to serialize and store an SVM to disk. + * Load the SVM from this file again, by calling this function with the path to the file. + * + * @param filepath path to serialized svm + */ + CV_WRAP static Ptr load(const String& filepath); +}; + +/****************************************************************************************\ +* Expectation - Maximization * +\****************************************************************************************/ + +/** @brief The class implements the Expectation Maximization algorithm. + +@sa @ref ml_intro_em + */ +class CV_EXPORTS_W EM : public StatModel +{ +public: + //! Type of covariation matrices + enum Types { + /** A scaled identity matrix \f$\mu_k * I\f$. There is the only + parameter \f$\mu_k\f$ to be estimated for each matrix. The option may be used in special cases, + when the constraint is relevant, or as a first step in the optimization (for example in case + when the data is preprocessed with PCA). The results of such preliminary estimation may be + passed again to the optimization procedure, this time with + covMatType=EM::COV_MAT_DIAGONAL. */ + COV_MAT_SPHERICAL=0, + /** A diagonal matrix with positive diagonal elements. The number of + free parameters is d for each matrix. This is most commonly used option yielding good + estimation results. */ + COV_MAT_DIAGONAL=1, + /** A symmetric positively defined matrix. The number of free + parameters in each matrix is about \f$d^2/2\f$. It is not recommended to use this option, unless + there is pretty accurate initial estimation of the parameters and/or a huge number of + training samples. */ + COV_MAT_GENERIC=2, + COV_MAT_DEFAULT=COV_MAT_DIAGONAL + }; + + //! Default parameters + enum {DEFAULT_NCLUSTERS=5, DEFAULT_MAX_ITERS=100}; + + //! The initial step + enum {START_E_STEP=1, START_M_STEP=2, START_AUTO_STEP=0}; + + /** The number of mixture components in the Gaussian mixture model. + Default value of the parameter is EM::DEFAULT_NCLUSTERS=5. Some of %EM implementation could + determine the optimal number of mixtures within a specified value range, but that is not the + case in ML yet. */ + /** @see setClustersNumber */ + CV_WRAP virtual int getClustersNumber() const = 0; + /** @copybrief getClustersNumber @see getClustersNumber */ + CV_WRAP virtual void setClustersNumber(int val) = 0; + + /** Constraint on covariance matrices which defines type of matrices. + See EM::Types. */ + /** @see setCovarianceMatrixType */ + CV_WRAP virtual int getCovarianceMatrixType() const = 0; + /** @copybrief getCovarianceMatrixType @see getCovarianceMatrixType */ + CV_WRAP virtual void setCovarianceMatrixType(int val) = 0; + + /** The termination criteria of the %EM algorithm. + The %EM algorithm can be terminated by the number of iterations termCrit.maxCount (number of + M-steps) or when relative change of likelihood logarithm is less than termCrit.epsilon. Default + maximum number of iterations is EM::DEFAULT_MAX_ITERS=100. */ + /** @see setTermCriteria */ + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(const TermCriteria &val) = 0; + + /** @brief Returns weights of the mixtures + + Returns vector with the number of elements equal to the number of mixtures. + */ + CV_WRAP virtual Mat getWeights() const = 0; + /** @brief Returns the cluster centers (means of the Gaussian mixture) + + Returns matrix with the number of rows equal to the number of mixtures and number of columns + equal to the space dimensionality. + */ + CV_WRAP virtual Mat getMeans() const = 0; + /** @brief Returns covariation matrices + + Returns vector of covariation matrices. Number of matrices is the number of gaussian mixtures, + each matrix is a square floating-point matrix NxN, where N is the space dimensionality. + */ + CV_WRAP virtual void getCovs(CV_OUT std::vector& covs) const = 0; + + /** @brief Returns posterior probabilities for the provided samples + + @param samples The input samples, floating-point matrix + @param results The optional output \f$ nSamples \times nClusters\f$ matrix of results. It contains + posterior probabilities for each sample from the input + @param flags This parameter will be ignored + */ + CV_WRAP virtual float predict( InputArray samples, OutputArray results=noArray(), int flags=0 ) const CV_OVERRIDE = 0; + + /** @brief Returns a likelihood logarithm value and an index of the most probable mixture component + for the given sample. + + @param sample A sample for classification. It should be a one-channel matrix of + \f$1 \times dims\f$ or \f$dims \times 1\f$ size. + @param probs Optional output matrix that contains posterior probabilities of each component + given the sample. It has \f$1 \times nclusters\f$ size and CV_64FC1 type. + + The method returns a two-element double vector. Zero element is a likelihood logarithm value for + the sample. First element is an index of the most probable mixture component for the given + sample. + */ + CV_WRAP virtual Vec2d predict2(InputArray sample, OutputArray probs) const = 0; + + /** @brief Estimate the Gaussian mixture parameters from a samples set. + + This variation starts with Expectation step. Initial values of the model parameters will be + estimated by the k-means algorithm. + + Unlike many of the ML models, %EM is an unsupervised learning algorithm and it does not take + responses (class labels or function values) as input. Instead, it computes the *Maximum + Likelihood Estimate* of the Gaussian mixture parameters from an input sample set, stores all the + parameters inside the structure: \f$p_{i,k}\f$ in probs, \f$a_k\f$ in means , \f$S_k\f$ in + covs[k], \f$\pi_k\f$ in weights , and optionally computes the output "class label" for each + sample: \f$\texttt{labels}_i=\texttt{arg max}_k(p_{i,k}), i=1..N\f$ (indices of the most + probable mixture component for each sample). + + The trained model can be used further for prediction, just like any other classifier. The + trained model is similar to the NormalBayesClassifier. + + @param samples Samples from which the Gaussian mixture model will be estimated. It should be a + one-channel matrix, each row of which is a sample. If the matrix does not have CV_64F type + it will be converted to the inner matrix of such type for the further computing. + @param logLikelihoods The optional output matrix that contains a likelihood logarithm value for + each sample. It has \f$nsamples \times 1\f$ size and CV_64FC1 type. + @param labels The optional output "class label" for each sample: + \f$\texttt{labels}_i=\texttt{arg max}_k(p_{i,k}), i=1..N\f$ (indices of the most probable + mixture component for each sample). It has \f$nsamples \times 1\f$ size and CV_32SC1 type. + @param probs The optional output matrix that contains posterior probabilities of each Gaussian + mixture component given the each sample. It has \f$nsamples \times nclusters\f$ size and + CV_64FC1 type. + */ + CV_WRAP virtual bool trainEM(InputArray samples, + OutputArray logLikelihoods=noArray(), + OutputArray labels=noArray(), + OutputArray probs=noArray()) = 0; + + /** @brief Estimate the Gaussian mixture parameters from a samples set. + + This variation starts with Expectation step. You need to provide initial means \f$a_k\f$ of + mixture components. Optionally you can pass initial weights \f$\pi_k\f$ and covariance matrices + \f$S_k\f$ of mixture components. + + @param samples Samples from which the Gaussian mixture model will be estimated. It should be a + one-channel matrix, each row of which is a sample. If the matrix does not have CV_64F type + it will be converted to the inner matrix of such type for the further computing. + @param means0 Initial means \f$a_k\f$ of mixture components. It is a one-channel matrix of + \f$nclusters \times dims\f$ size. If the matrix does not have CV_64F type it will be + converted to the inner matrix of such type for the further computing. + @param covs0 The vector of initial covariance matrices \f$S_k\f$ of mixture components. Each of + covariance matrices is a one-channel matrix of \f$dims \times dims\f$ size. If the matrices + do not have CV_64F type they will be converted to the inner matrices of such type for the + further computing. + @param weights0 Initial weights \f$\pi_k\f$ of mixture components. It should be a one-channel + floating-point matrix with \f$1 \times nclusters\f$ or \f$nclusters \times 1\f$ size. + @param logLikelihoods The optional output matrix that contains a likelihood logarithm value for + each sample. It has \f$nsamples \times 1\f$ size and CV_64FC1 type. + @param labels The optional output "class label" for each sample: + \f$\texttt{labels}_i=\texttt{arg max}_k(p_{i,k}), i=1..N\f$ (indices of the most probable + mixture component for each sample). It has \f$nsamples \times 1\f$ size and CV_32SC1 type. + @param probs The optional output matrix that contains posterior probabilities of each Gaussian + mixture component given the each sample. It has \f$nsamples \times nclusters\f$ size and + CV_64FC1 type. + */ + CV_WRAP virtual bool trainE(InputArray samples, InputArray means0, + InputArray covs0=noArray(), + InputArray weights0=noArray(), + OutputArray logLikelihoods=noArray(), + OutputArray labels=noArray(), + OutputArray probs=noArray()) = 0; + + /** @brief Estimate the Gaussian mixture parameters from a samples set. + + This variation starts with Maximization step. You need to provide initial probabilities + \f$p_{i,k}\f$ to use this option. + + @param samples Samples from which the Gaussian mixture model will be estimated. It should be a + one-channel matrix, each row of which is a sample. If the matrix does not have CV_64F type + it will be converted to the inner matrix of such type for the further computing. + @param probs0 + @param logLikelihoods The optional output matrix that contains a likelihood logarithm value for + each sample. It has \f$nsamples \times 1\f$ size and CV_64FC1 type. + @param labels The optional output "class label" for each sample: + \f$\texttt{labels}_i=\texttt{arg max}_k(p_{i,k}), i=1..N\f$ (indices of the most probable + mixture component for each sample). It has \f$nsamples \times 1\f$ size and CV_32SC1 type. + @param probs The optional output matrix that contains posterior probabilities of each Gaussian + mixture component given the each sample. It has \f$nsamples \times nclusters\f$ size and + CV_64FC1 type. + */ + CV_WRAP virtual bool trainM(InputArray samples, InputArray probs0, + OutputArray logLikelihoods=noArray(), + OutputArray labels=noArray(), + OutputArray probs=noArray()) = 0; + + /** Creates empty %EM model. + The model should be trained then using StatModel::train(traindata, flags) method. Alternatively, you + can use one of the EM::train\* methods or load it from file using Algorithm::load\(filename). + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized EM from a file + * + * Use EM::save to serialize and store an EM to disk. + * Load the EM from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized EM + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + +/****************************************************************************************\ +* Decision Tree * +\****************************************************************************************/ + +/** @brief The class represents a single decision tree or a collection of decision trees. + +The current public interface of the class allows user to train only a single decision tree, however +the class is capable of storing multiple decision trees and using them for prediction (by summing +responses or using a voting schemes), and the derived from DTrees classes (such as RTrees and Boost) +use this capability to implement decision tree ensembles. + +@sa @ref ml_intro_trees +*/ +class CV_EXPORTS_W DTrees : public StatModel +{ +public: + /** Predict options */ + enum Flags { PREDICT_AUTO=0, PREDICT_SUM=(1<<8), PREDICT_MAX_VOTE=(2<<8), PREDICT_MASK=(3<<8) }; + + /** Cluster possible values of a categorical variable into K\<=maxCategories clusters to + find a suboptimal split. + If a discrete variable, on which the training procedure tries to make a split, takes more than + maxCategories values, the precise best subset estimation may take a very long time because the + algorithm is exponential. Instead, many decision trees engines (including our implementation) + try to find sub-optimal split in this case by clustering all the samples into maxCategories + clusters that is some categories are merged together. The clustering is applied only in n \> + 2-class classification problems for categorical variables with N \> max_categories possible + values. In case of regression and 2-class classification the optimal split can be found + efficiently without employing clustering, thus the parameter is not used in these cases. + Default value is 10.*/ + /** @see setMaxCategories */ + CV_WRAP virtual int getMaxCategories() const = 0; + /** @copybrief getMaxCategories @see getMaxCategories */ + CV_WRAP virtual void setMaxCategories(int val) = 0; + + /** The maximum possible depth of the tree. + That is the training algorithms attempts to split a node while its depth is less than maxDepth. + The root node has zero depth. The actual depth may be smaller if the other termination criteria + are met (see the outline of the training procedure @ref ml_intro_trees "here"), and/or if the + tree is pruned. Default value is INT_MAX.*/ + /** @see setMaxDepth */ + CV_WRAP virtual int getMaxDepth() const = 0; + /** @copybrief getMaxDepth @see getMaxDepth */ + CV_WRAP virtual void setMaxDepth(int val) = 0; + + /** If the number of samples in a node is less than this parameter then the node will not be split. + + Default value is 10.*/ + /** @see setMinSampleCount */ + CV_WRAP virtual int getMinSampleCount() const = 0; + /** @copybrief getMinSampleCount @see getMinSampleCount */ + CV_WRAP virtual void setMinSampleCount(int val) = 0; + + /** If CVFolds \> 1 then algorithms prunes the built decision tree using K-fold + cross-validation procedure where K is equal to CVFolds. + Default value is 10.*/ + /** @see setCVFolds */ + CV_WRAP virtual int getCVFolds() const = 0; + /** @copybrief getCVFolds @see getCVFolds */ + CV_WRAP virtual void setCVFolds(int val) = 0; + + /** If true then surrogate splits will be built. + These splits allow to work with missing data and compute variable importance correctly. + Default value is false. + @note currently it's not implemented.*/ + /** @see setUseSurrogates */ + CV_WRAP virtual bool getUseSurrogates() const = 0; + /** @copybrief getUseSurrogates @see getUseSurrogates */ + CV_WRAP virtual void setUseSurrogates(bool val) = 0; + + /** If true then a pruning will be harsher. + This will make a tree more compact and more resistant to the training data noise but a bit less + accurate. Default value is true.*/ + /** @see setUse1SERule */ + CV_WRAP virtual bool getUse1SERule() const = 0; + /** @copybrief getUse1SERule @see getUse1SERule */ + CV_WRAP virtual void setUse1SERule(bool val) = 0; + + /** If true then pruned branches are physically removed from the tree. + Otherwise they are retained and it is possible to get results from the original unpruned (or + pruned less aggressively) tree. Default value is true.*/ + /** @see setTruncatePrunedTree */ + CV_WRAP virtual bool getTruncatePrunedTree() const = 0; + /** @copybrief getTruncatePrunedTree @see getTruncatePrunedTree */ + CV_WRAP virtual void setTruncatePrunedTree(bool val) = 0; + + /** Termination criteria for regression trees. + If all absolute differences between an estimated value in a node and values of train samples + in this node are less than this parameter then the node will not be split further. Default + value is 0.01f*/ + /** @see setRegressionAccuracy */ + CV_WRAP virtual float getRegressionAccuracy() const = 0; + /** @copybrief getRegressionAccuracy @see getRegressionAccuracy */ + CV_WRAP virtual void setRegressionAccuracy(float val) = 0; + + /** @brief The array of a priori class probabilities, sorted by the class label value. + + The parameter can be used to tune the decision tree preferences toward a certain class. For + example, if you want to detect some rare anomaly occurrence, the training base will likely + contain much more normal cases than anomalies, so a very good classification performance + will be achieved just by considering every case as normal. To avoid this, the priors can be + specified, where the anomaly probability is artificially increased (up to 0.5 or even + greater), so the weight of the misclassified anomalies becomes much bigger, and the tree is + adjusted properly. + + You can also think about this parameter as weights of prediction categories which determine + relative weights that you give to misclassification. That is, if the weight of the first + category is 1 and the weight of the second category is 10, then each mistake in predicting + the second category is equivalent to making 10 mistakes in predicting the first category. + Default value is empty Mat.*/ + /** @see setPriors */ + CV_WRAP virtual cv::Mat getPriors() const = 0; + /** @copybrief getPriors @see getPriors */ + CV_WRAP virtual void setPriors(const cv::Mat &val) = 0; + + /** @brief The class represents a decision tree node. + */ + class CV_EXPORTS Node + { + public: + Node(); + double value; //!< Value at the node: a class label in case of classification or estimated + //!< function value in case of regression. + int classIdx; //!< Class index normalized to 0..class_count-1 range and assigned to the + //!< node. It is used internally in classification trees and tree ensembles. + int parent; //!< Index of the parent node + int left; //!< Index of the left child node + int right; //!< Index of right child node + int defaultDir; //!< Default direction where to go (-1: left or +1: right). It helps in the + //!< case of missing values. + int split; //!< Index of the first split + }; + + /** @brief The class represents split in a decision tree. + */ + class CV_EXPORTS Split + { + public: + Split(); + int varIdx; //!< Index of variable on which the split is created. + bool inversed; //!< If true, then the inverse split rule is used (i.e. left and right + //!< branches are exchanged in the rule expressions below). + float quality; //!< The split quality, a positive number. It is used to choose the best split. + int next; //!< Index of the next split in the list of splits for the node + float c; /**< The threshold value in case of split on an ordered variable. + The rule is: + @code{.none} + if var_value < c + then next_node <- left + else next_node <- right + @endcode */ + int subsetOfs; /**< Offset of the bitset used by the split on a categorical variable. + The rule is: + @code{.none} + if bitset[var_value] == 1 + then next_node <- left + else next_node <- right + @endcode */ + }; + + /** @brief Returns indices of root nodes + */ + virtual const std::vector& getRoots() const = 0; + /** @brief Returns all the nodes + + all the node indices are indices in the returned vector + */ + virtual const std::vector& getNodes() const = 0; + /** @brief Returns all the splits + + all the split indices are indices in the returned vector + */ + virtual const std::vector& getSplits() const = 0; + /** @brief Returns all the bitsets for categorical splits + + Split::subsetOfs is an offset in the returned vector + */ + virtual const std::vector& getSubsets() const = 0; + + /** @brief Creates the empty model + + The static method creates empty decision tree with the specified parameters. It should be then + trained using train method (see StatModel::train). Alternatively, you can load the model from + file using Algorithm::load\(filename). + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized DTrees from a file + * + * Use DTree::save to serialize and store an DTree to disk. + * Load the DTree from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized DTree + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + +/****************************************************************************************\ +* Random Trees Classifier * +\****************************************************************************************/ + +/** @brief The class implements the random forest predictor. + +@sa @ref ml_intro_rtrees + */ +class CV_EXPORTS_W RTrees : public DTrees +{ +public: + + /** If true then variable importance will be calculated and then it can be retrieved by RTrees::getVarImportance. + Default value is false.*/ + /** @see setCalculateVarImportance */ + CV_WRAP virtual bool getCalculateVarImportance() const = 0; + /** @copybrief getCalculateVarImportance @see getCalculateVarImportance */ + CV_WRAP virtual void setCalculateVarImportance(bool val) = 0; + + /** The size of the randomly selected subset of features at each tree node and that are used + to find the best split(s). + If you set it to 0 then the size will be set to the square root of the total number of + features. Default value is 0.*/ + /** @see setActiveVarCount */ + CV_WRAP virtual int getActiveVarCount() const = 0; + /** @copybrief getActiveVarCount @see getActiveVarCount */ + CV_WRAP virtual void setActiveVarCount(int val) = 0; + + /** The termination criteria that specifies when the training algorithm stops. + Either when the specified number of trees is trained and added to the ensemble or when + sufficient accuracy (measured as OOB error) is achieved. Typically the more trees you have the + better the accuracy. However, the improvement in accuracy generally diminishes and asymptotes + pass a certain number of trees. Also to keep in mind, the number of tree increases the + prediction time linearly. Default value is TermCriteria(TermCriteria::MAX_ITERS + + TermCriteria::EPS, 50, 0.1)*/ + /** @see setTermCriteria */ + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(const TermCriteria &val) = 0; + + /** Returns the variable importance array. + The method returns the variable importance vector, computed at the training stage when + CalculateVarImportance is set to true. If this flag was set to false, the empty matrix is + returned. + */ + CV_WRAP virtual Mat getVarImportance() const = 0; + + /** Returns the result of each individual tree in the forest. + In case the model is a regression problem, the method will return each of the trees' + results for each of the sample cases. If the model is a classifier, it will return + a Mat with samples + 1 rows, where the first row gives the class number and the + following rows return the votes each class had for each sample. + @param samples Array containing the samples for which votes will be calculated. + @param results Array where the result of the calculation will be written. + @param flags Flags for defining the type of RTrees. + */ + CV_WRAP void getVotes(InputArray samples, OutputArray results, int flags) const; + + /** Creates the empty model. + Use StatModel::train to train the model, StatModel::train to create and train the model, + Algorithm::load to load the pre-trained model. + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized RTree from a file + * + * Use RTree::save to serialize and store an RTree to disk. + * Load the RTree from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized RTree + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + +/****************************************************************************************\ +* Boosted tree classifier * +\****************************************************************************************/ + +/** @brief Boosted tree classifier derived from DTrees + +@sa @ref ml_intro_boost + */ +class CV_EXPORTS_W Boost : public DTrees +{ +public: + /** Type of the boosting algorithm. + See Boost::Types. Default value is Boost::REAL. */ + /** @see setBoostType */ + CV_WRAP virtual int getBoostType() const = 0; + /** @copybrief getBoostType @see getBoostType */ + CV_WRAP virtual void setBoostType(int val) = 0; + + /** The number of weak classifiers. + Default value is 100. */ + /** @see setWeakCount */ + CV_WRAP virtual int getWeakCount() const = 0; + /** @copybrief getWeakCount @see getWeakCount */ + CV_WRAP virtual void setWeakCount(int val) = 0; + + /** A threshold between 0 and 1 used to save computational time. + Samples with summary weight \f$\leq 1 - weight_trim_rate\f$ do not participate in the *next* + iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.*/ + /** @see setWeightTrimRate */ + CV_WRAP virtual double getWeightTrimRate() const = 0; + /** @copybrief getWeightTrimRate @see getWeightTrimRate */ + CV_WRAP virtual void setWeightTrimRate(double val) = 0; + + /** Boosting type. + Gentle AdaBoost and Real AdaBoost are often the preferable choices. */ + enum Types { + DISCRETE=0, //!< Discrete AdaBoost. + REAL=1, //!< Real AdaBoost. It is a technique that utilizes confidence-rated predictions + //!< and works well with categorical data. + LOGIT=2, //!< LogitBoost. It can produce good regression fits. + GENTLE=3 //!< Gentle AdaBoost. It puts less weight on outlier data points and for that + //!(filename) to load the pre-trained model. */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized Boost from a file + * + * Use Boost::save to serialize and store an RTree to disk. + * Load the Boost from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized Boost + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + +/****************************************************************************************\ +* Gradient Boosted Trees * +\****************************************************************************************/ + +/*class CV_EXPORTS_W GBTrees : public DTrees +{ +public: + struct CV_EXPORTS_W_MAP Params : public DTrees::Params + { + CV_PROP_RW int weakCount; + CV_PROP_RW int lossFunctionType; + CV_PROP_RW float subsamplePortion; + CV_PROP_RW float shrinkage; + + Params(); + Params( int lossFunctionType, int weakCount, float shrinkage, + float subsamplePortion, int maxDepth, bool useSurrogates ); + }; + + enum {SQUARED_LOSS=0, ABSOLUTE_LOSS, HUBER_LOSS=3, DEVIANCE_LOSS}; + + virtual void setK(int k) = 0; + + virtual float predictSerial( InputArray samples, + OutputArray weakResponses, int flags) const = 0; + + static Ptr create(const Params& p); +};*/ + +/****************************************************************************************\ +* Artificial Neural Networks (ANN) * +\****************************************************************************************/ + +/////////////////////////////////// Multi-Layer Perceptrons ////////////////////////////// + +/** @brief Artificial Neural Networks - Multi-Layer Perceptrons. + +Unlike many other models in ML that are constructed and trained at once, in the MLP model these +steps are separated. First, a network with the specified topology is created using the non-default +constructor or the method ANN_MLP::create. All the weights are set to zeros. Then, the network is +trained using a set of input and output vectors. The training procedure can be repeated more than +once, that is, the weights can be adjusted based on the new training data. + +Additional flags for StatModel::train are available: ANN_MLP::TrainFlags. + +@sa @ref ml_intro_ann + */ +class CV_EXPORTS_W ANN_MLP : public StatModel +{ +public: + /** Available training methods */ + enum TrainingMethods { + BACKPROP=0, //!< The back-propagation algorithm. + RPROP = 1, //!< The RPROP algorithm. See @cite RPROP93 for details. + ANNEAL = 2 //!< The simulated annealing algorithm. See @cite Kirkpatrick83 for details. + }; + + /** Sets training method and common parameters. + @param method Default value is ANN_MLP::RPROP. See ANN_MLP::TrainingMethods. + @param param1 passed to setRpropDW0 for ANN_MLP::RPROP and to setBackpropWeightScale for ANN_MLP::BACKPROP and to initialT for ANN_MLP::ANNEAL. + @param param2 passed to setRpropDWMin for ANN_MLP::RPROP and to setBackpropMomentumScale for ANN_MLP::BACKPROP and to finalT for ANN_MLP::ANNEAL. + */ + CV_WRAP virtual void setTrainMethod(int method, double param1 = 0, double param2 = 0) = 0; + + /** Returns current training method */ + CV_WRAP virtual int getTrainMethod() const = 0; + + /** Initialize the activation function for each neuron. + Currently the default and the only fully supported activation function is ANN_MLP::SIGMOID_SYM. + @param type The type of activation function. See ANN_MLP::ActivationFunctions. + @param param1 The first parameter of the activation function, \f$\alpha\f$. Default value is 0. + @param param2 The second parameter of the activation function, \f$\beta\f$. Default value is 0. + */ + CV_WRAP virtual void setActivationFunction(int type, double param1 = 0, double param2 = 0) = 0; + + /** Integer vector specifying the number of neurons in each layer including the input and output layers. + The very first element specifies the number of elements in the input layer. + The last element - number of elements in the output layer. Default value is empty Mat. + @sa getLayerSizes */ + CV_WRAP virtual void setLayerSizes(InputArray _layer_sizes) = 0; + + /** Integer vector specifying the number of neurons in each layer including the input and output layers. + The very first element specifies the number of elements in the input layer. + The last element - number of elements in the output layer. + @sa setLayerSizes */ + CV_WRAP virtual cv::Mat getLayerSizes() const = 0; + + /** Termination criteria of the training algorithm. + You can specify the maximum number of iterations (maxCount) and/or how much the error could + change between the iterations to make the algorithm continue (epsilon). Default value is + TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 1000, 0.01).*/ + /** @see setTermCriteria */ + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(TermCriteria val) = 0; + + /** BPROP: Strength of the weight gradient term. + The recommended value is about 0.1. Default value is 0.1.*/ + /** @see setBackpropWeightScale */ + CV_WRAP virtual double getBackpropWeightScale() const = 0; + /** @copybrief getBackpropWeightScale @see getBackpropWeightScale */ + CV_WRAP virtual void setBackpropWeightScale(double val) = 0; + + /** BPROP: Strength of the momentum term (the difference between weights on the 2 previous iterations). + This parameter provides some inertia to smooth the random fluctuations of the weights. It can + vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. + Default value is 0.1.*/ + /** @see setBackpropMomentumScale */ + CV_WRAP virtual double getBackpropMomentumScale() const = 0; + /** @copybrief getBackpropMomentumScale @see getBackpropMomentumScale */ + CV_WRAP virtual void setBackpropMomentumScale(double val) = 0; + + /** RPROP: Initial value \f$\Delta_0\f$ of update-values \f$\Delta_{ij}\f$. + Default value is 0.1.*/ + /** @see setRpropDW0 */ + CV_WRAP virtual double getRpropDW0() const = 0; + /** @copybrief getRpropDW0 @see getRpropDW0 */ + CV_WRAP virtual void setRpropDW0(double val) = 0; + + /** RPROP: Increase factor \f$\eta^+\f$. + It must be \>1. Default value is 1.2.*/ + /** @see setRpropDWPlus */ + CV_WRAP virtual double getRpropDWPlus() const = 0; + /** @copybrief getRpropDWPlus @see getRpropDWPlus */ + CV_WRAP virtual void setRpropDWPlus(double val) = 0; + + /** RPROP: Decrease factor \f$\eta^-\f$. + It must be \<1. Default value is 0.5.*/ + /** @see setRpropDWMinus */ + CV_WRAP virtual double getRpropDWMinus() const = 0; + /** @copybrief getRpropDWMinus @see getRpropDWMinus */ + CV_WRAP virtual void setRpropDWMinus(double val) = 0; + + /** RPROP: Update-values lower limit \f$\Delta_{min}\f$. + It must be positive. Default value is FLT_EPSILON.*/ + /** @see setRpropDWMin */ + CV_WRAP virtual double getRpropDWMin() const = 0; + /** @copybrief getRpropDWMin @see getRpropDWMin */ + CV_WRAP virtual void setRpropDWMin(double val) = 0; + + /** RPROP: Update-values upper limit \f$\Delta_{max}\f$. + It must be \>1. Default value is 50.*/ + /** @see setRpropDWMax */ + CV_WRAP virtual double getRpropDWMax() const = 0; + /** @copybrief getRpropDWMax @see getRpropDWMax */ + CV_WRAP virtual void setRpropDWMax(double val) = 0; + + /** ANNEAL: Update initial temperature. + It must be \>=0. Default value is 10.*/ + /** @see setAnnealInitialT */ + CV_WRAP double getAnnealInitialT() const; + /** @copybrief getAnnealInitialT @see getAnnealInitialT */ + CV_WRAP void setAnnealInitialT(double val); + + /** ANNEAL: Update final temperature. + It must be \>=0 and less than initialT. Default value is 0.1.*/ + /** @see setAnnealFinalT */ + CV_WRAP double getAnnealFinalT() const; + /** @copybrief getAnnealFinalT @see getAnnealFinalT */ + CV_WRAP void setAnnealFinalT(double val); + + /** ANNEAL: Update cooling ratio. + It must be \>0 and less than 1. Default value is 0.95.*/ + /** @see setAnnealCoolingRatio */ + CV_WRAP double getAnnealCoolingRatio() const; + /** @copybrief getAnnealCoolingRatio @see getAnnealCoolingRatio */ + CV_WRAP void setAnnealCoolingRatio(double val); + + /** ANNEAL: Update iteration per step. + It must be \>0 . Default value is 10.*/ + /** @see setAnnealItePerStep */ + CV_WRAP int getAnnealItePerStep() const; + /** @copybrief getAnnealItePerStep @see getAnnealItePerStep */ + CV_WRAP void setAnnealItePerStep(int val); + + /** @brief Set/initialize anneal RNG */ + void setAnnealEnergyRNG(const RNG& rng); + + /** possible activation functions */ + enum ActivationFunctions { + /** Identity function: \f$f(x)=x\f$ */ + IDENTITY = 0, + /** Symmetrical sigmoid: \f$f(x)=\beta*(1-e^{-\alpha x})/(1+e^{-\alpha x})\f$ + @note + If you are using the default sigmoid activation function with the default parameter values + fparam1=0 and fparam2=0 then the function used is y = 1.7159\*tanh(2/3 \* x), so the output + will range from [-1.7159, 1.7159], instead of [0,1].*/ + SIGMOID_SYM = 1, + /** Gaussian function: \f$f(x)=\beta e^{-\alpha x*x}\f$ */ + GAUSSIAN = 2, + /** ReLU function: \f$f(x)=max(0,x)\f$ */ + RELU = 3, + /** Leaky ReLU function: for x>0 \f$f(x)=x \f$ and x<=0 \f$f(x)=\alpha x \f$*/ + LEAKYRELU= 4 + }; + + /** Train options */ + enum TrainFlags { + /** Update the network weights, rather than compute them from scratch. In the latter case + the weights are initialized using the Nguyen-Widrow algorithm. */ + UPDATE_WEIGHTS = 1, + /** Do not normalize the input vectors. If this flag is not set, the training algorithm + normalizes each input feature independently, shifting its mean value to 0 and making the + standard deviation equal to 1. If the network is assumed to be updated frequently, the new + training data could be much different from original one. In this case, you should take care + of proper normalization. */ + NO_INPUT_SCALE = 2, + /** Do not normalize the output vectors. If the flag is not set, the training algorithm + normalizes each output feature independently, by transforming it to the certain range + depending on the used activation function. */ + NO_OUTPUT_SCALE = 4 + }; + + CV_WRAP virtual Mat getWeights(int layerIdx) const = 0; + + /** @brief Creates empty model + + Use StatModel::train to train the model, Algorithm::load\(filename) to load the pre-trained model. + Note that the train method has optional flags: ANN_MLP::TrainFlags. + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized ANN from a file + * + * Use ANN::save to serialize and store an ANN to disk. + * Load the ANN from this file again, by calling this function with the path to the file. + * + * @param filepath path to serialized ANN + */ + CV_WRAP static Ptr load(const String& filepath); + +}; + +/****************************************************************************************\ +* Logistic Regression * +\****************************************************************************************/ + +/** @brief Implements Logistic Regression classifier. + +@sa @ref ml_intro_lr + */ +class CV_EXPORTS_W LogisticRegression : public StatModel +{ +public: + + /** Learning rate. */ + /** @see setLearningRate */ + CV_WRAP virtual double getLearningRate() const = 0; + /** @copybrief getLearningRate @see getLearningRate */ + CV_WRAP virtual void setLearningRate(double val) = 0; + + /** Number of iterations. */ + /** @see setIterations */ + CV_WRAP virtual int getIterations() const = 0; + /** @copybrief getIterations @see getIterations */ + CV_WRAP virtual void setIterations(int val) = 0; + + /** Kind of regularization to be applied. See LogisticRegression::RegKinds. */ + /** @see setRegularization */ + CV_WRAP virtual int getRegularization() const = 0; + /** @copybrief getRegularization @see getRegularization */ + CV_WRAP virtual void setRegularization(int val) = 0; + + /** Kind of training method used. See LogisticRegression::Methods. */ + /** @see setTrainMethod */ + CV_WRAP virtual int getTrainMethod() const = 0; + /** @copybrief getTrainMethod @see getTrainMethod */ + CV_WRAP virtual void setTrainMethod(int val) = 0; + + /** Specifies the number of training samples taken in each step of Mini-Batch Gradient + Descent. Will only be used if using LogisticRegression::MINI_BATCH training algorithm. It + has to take values less than the total number of training samples. */ + /** @see setMiniBatchSize */ + CV_WRAP virtual int getMiniBatchSize() const = 0; + /** @copybrief getMiniBatchSize @see getMiniBatchSize */ + CV_WRAP virtual void setMiniBatchSize(int val) = 0; + + /** Termination criteria of the algorithm. */ + /** @see setTermCriteria */ + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(TermCriteria val) = 0; + + //! Regularization kinds + enum RegKinds { + REG_DISABLE = -1, //!< Regularization disabled + REG_L1 = 0, //!< %L1 norm + REG_L2 = 1 //!< %L2 norm + }; + + //! Training methods + enum Methods { + BATCH = 0, + MINI_BATCH = 1 //!< Set MiniBatchSize to a positive integer when using this method. + }; + + /** @brief Predicts responses for input samples and returns a float type. + + @param samples The input data for the prediction algorithm. Matrix [m x n], where each row + contains variables (features) of one object being classified. Should have data type CV_32F. + @param results Predicted labels as a column matrix of type CV_32S. + @param flags Not used. + */ + CV_WRAP virtual float predict( InputArray samples, OutputArray results=noArray(), int flags=0 ) const CV_OVERRIDE = 0; + + /** @brief This function returns the trained parameters arranged across rows. + + For a two class classifcation problem, it returns a row matrix. It returns learnt parameters of + the Logistic Regression as a matrix of type CV_32F. + */ + CV_WRAP virtual Mat get_learnt_thetas() const = 0; + + /** @brief Creates empty model. + + Creates Logistic Regression model with parameters given. + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized LogisticRegression from a file + * + * Use LogisticRegression::save to serialize and store an LogisticRegression to disk. + * Load the LogisticRegression from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized LogisticRegression + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); +}; + + +/****************************************************************************************\ +* Stochastic Gradient Descent SVM Classifier * +\****************************************************************************************/ + +/*! +@brief Stochastic Gradient Descent SVM classifier + +SVMSGD provides a fast and easy-to-use implementation of the SVM classifier using the Stochastic Gradient Descent approach, +as presented in @cite bottou2010large. + +The classifier has following parameters: +- model type, +- margin type, +- margin regularization (\f$\lambda\f$), +- initial step size (\f$\gamma_0\f$), +- step decreasing power (\f$c\f$), +- and termination criteria. + +The model type may have one of the following values: \ref SGD and \ref ASGD. + +- \ref SGD is the classic version of SVMSGD classifier: every next step is calculated by the formula + \f[w_{t+1} = w_t - \gamma(t) \frac{dQ_i}{dw} |_{w = w_t}\f] + where + - \f$w_t\f$ is the weights vector for decision function at step \f$t\f$, + - \f$\gamma(t)\f$ is the step size of model parameters at the iteration \f$t\f$, it is decreased on each step by the formula + \f$\gamma(t) = \gamma_0 (1 + \lambda \gamma_0 t) ^ {-c}\f$ + - \f$Q_i\f$ is the target functional from SVM task for sample with number \f$i\f$, this sample is chosen stochastically on each step of the algorithm. + +- \ref ASGD is Average Stochastic Gradient Descent SVM Classifier. ASGD classifier averages weights vector on each step of algorithm by the formula +\f$\widehat{w}_{t+1} = \frac{t}{1+t}\widehat{w}_{t} + \frac{1}{1+t}w_{t+1}\f$ + +The recommended model type is ASGD (following @cite bottou2010large). + +The margin type may have one of the following values: \ref SOFT_MARGIN or \ref HARD_MARGIN. + +- You should use \ref HARD_MARGIN type, if you have linearly separable sets. +- You should use \ref SOFT_MARGIN type, if you have non-linearly separable sets or sets with outliers. +- In the general case (if you know nothing about linear separability of your sets), use SOFT_MARGIN. + +The other parameters may be described as follows: +- Margin regularization parameter is responsible for weights decreasing at each step and for the strength of restrictions on outliers + (the less the parameter, the less probability that an outlier will be ignored). + Recommended value for SGD model is 0.0001, for ASGD model is 0.00001. + +- Initial step size parameter is the initial value for the step size \f$\gamma(t)\f$. + You will have to find the best initial step for your problem. + +- Step decreasing power is the power parameter for \f$\gamma(t)\f$ decreasing by the formula, mentioned above. + Recommended value for SGD model is 1, for ASGD model is 0.75. + +- Termination criteria can be TermCriteria::COUNT, TermCriteria::EPS or TermCriteria::COUNT + TermCriteria::EPS. + You will have to find the best termination criteria for your problem. + +Note that the parameters margin regularization, initial step size, and step decreasing power should be positive. + +To use SVMSGD algorithm do as follows: + +- first, create the SVMSGD object. The algoorithm will set optimal parameters by default, but you can set your own parameters via functions setSvmsgdType(), + setMarginType(), setMarginRegularization(), setInitialStepSize(), and setStepDecreasingPower(). + +- then the SVM model can be trained using the train features and the correspondent labels by the method train(). + +- after that, the label of a new feature vector can be predicted using the method predict(). + +@code +// Create empty object +cv::Ptr svmsgd = SVMSGD::create(); + +// Train the Stochastic Gradient Descent SVM +svmsgd->train(trainData); + +// Predict labels for the new samples +svmsgd->predict(samples, responses); +@endcode + +*/ + +class CV_EXPORTS_W SVMSGD : public cv::ml::StatModel +{ +public: + + /** SVMSGD type. + ASGD is often the preferable choice. */ + enum SvmsgdType + { + SGD, //!< Stochastic Gradient Descent + ASGD //!< Average Stochastic Gradient Descent + }; + + /** Margin type.*/ + enum MarginType + { + SOFT_MARGIN, //!< General case, suits to the case of non-linearly separable sets, allows outliers. + HARD_MARGIN //!< More accurate for the case of linearly separable sets. + }; + + /** + * @return the weights of the trained model (decision function f(x) = weights * x + shift). + */ + CV_WRAP virtual Mat getWeights() = 0; + + /** + * @return the shift of the trained model (decision function f(x) = weights * x + shift). + */ + CV_WRAP virtual float getShift() = 0; + + /** @brief Creates empty model. + * Use StatModel::train to train the model. Since %SVMSGD has several parameters, you may want to + * find the best parameters for your problem or use setOptimalParameters() to set some default parameters. + */ + CV_WRAP static Ptr create(); + + /** @brief Loads and creates a serialized SVMSGD from a file + * + * Use SVMSGD::save to serialize and store an SVMSGD to disk. + * Load the SVMSGD from this file again, by calling this function with the path to the file. + * Optionally specify the node for the file containing the classifier + * + * @param filepath path to serialized SVMSGD + * @param nodeName name of node containing the classifier + */ + CV_WRAP static Ptr load(const String& filepath , const String& nodeName = String()); + + /** @brief Function sets optimal parameters values for chosen SVM SGD model. + * @param svmsgdType is the type of SVMSGD classifier. + * @param marginType is the type of margin constraint. + */ + CV_WRAP virtual void setOptimalParameters(int svmsgdType = SVMSGD::ASGD, int marginType = SVMSGD::SOFT_MARGIN) = 0; + + /** @brief %Algorithm type, one of SVMSGD::SvmsgdType. */ + /** @see setSvmsgdType */ + CV_WRAP virtual int getSvmsgdType() const = 0; + /** @copybrief getSvmsgdType @see getSvmsgdType */ + CV_WRAP virtual void setSvmsgdType(int svmsgdType) = 0; + + /** @brief %Margin type, one of SVMSGD::MarginType. */ + /** @see setMarginType */ + CV_WRAP virtual int getMarginType() const = 0; + /** @copybrief getMarginType @see getMarginType */ + CV_WRAP virtual void setMarginType(int marginType) = 0; + + /** @brief Parameter marginRegularization of a %SVMSGD optimization problem. */ + /** @see setMarginRegularization */ + CV_WRAP virtual float getMarginRegularization() const = 0; + /** @copybrief getMarginRegularization @see getMarginRegularization */ + CV_WRAP virtual void setMarginRegularization(float marginRegularization) = 0; + + /** @brief Parameter initialStepSize of a %SVMSGD optimization problem. */ + /** @see setInitialStepSize */ + CV_WRAP virtual float getInitialStepSize() const = 0; + /** @copybrief getInitialStepSize @see getInitialStepSize */ + CV_WRAP virtual void setInitialStepSize(float InitialStepSize) = 0; + + /** @brief Parameter stepDecreasingPower of a %SVMSGD optimization problem. */ + /** @see setStepDecreasingPower */ + CV_WRAP virtual float getStepDecreasingPower() const = 0; + /** @copybrief getStepDecreasingPower @see getStepDecreasingPower */ + CV_WRAP virtual void setStepDecreasingPower(float stepDecreasingPower) = 0; + + /** @brief Termination criteria of the training algorithm. + You can specify the maximum number of iterations (maxCount) and/or how much the error could + change between the iterations to make the algorithm continue (epsilon).*/ + /** @see setTermCriteria */ + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + /** @copybrief getTermCriteria @see getTermCriteria */ + CV_WRAP virtual void setTermCriteria(const cv::TermCriteria &val) = 0; +}; + + +/****************************************************************************************\ +* Auxiliary functions declarations * +\****************************************************************************************/ + +/** @brief Generates _sample_ from multivariate normal distribution + +@param mean an average row vector +@param cov symmetric covariation matrix +@param nsamples returned samples count +@param samples returned samples array +*/ +CV_EXPORTS void randMVNormal( InputArray mean, InputArray cov, int nsamples, OutputArray samples); + +/** @brief Creates test set */ +CV_EXPORTS void createConcentricSpheresTestSet( int nsamples, int nfeatures, int nclasses, + OutputArray samples, OutputArray responses); + +/** @brief Artificial Neural Networks - Multi-Layer Perceptrons. + +@sa @ref ml_intro_ann +*/ +class CV_EXPORTS_W ANN_MLP_ANNEAL : public ANN_MLP +{ +public: + /** @see setAnnealInitialT */ + CV_WRAP virtual double getAnnealInitialT() const = 0; + /** @copybrief getAnnealInitialT @see getAnnealInitialT */ + CV_WRAP virtual void setAnnealInitialT(double val) = 0; + + /** ANNEAL: Update final temperature. + It must be \>=0 and less than initialT. Default value is 0.1.*/ + /** @see setAnnealFinalT */ + CV_WRAP virtual double getAnnealFinalT() const = 0; + /** @copybrief getAnnealFinalT @see getAnnealFinalT */ + CV_WRAP virtual void setAnnealFinalT(double val) = 0; + + /** ANNEAL: Update cooling ratio. + It must be \>0 and less than 1. Default value is 0.95.*/ + /** @see setAnnealCoolingRatio */ + CV_WRAP virtual double getAnnealCoolingRatio() const = 0; + /** @copybrief getAnnealCoolingRatio @see getAnnealCoolingRatio */ + CV_WRAP virtual void setAnnealCoolingRatio(double val) = 0; + + /** ANNEAL: Update iteration per step. + It must be \>0 . Default value is 10.*/ + /** @see setAnnealItePerStep */ + CV_WRAP virtual int getAnnealItePerStep() const = 0; + /** @copybrief getAnnealItePerStep @see getAnnealItePerStep */ + CV_WRAP virtual void setAnnealItePerStep(int val) = 0; + + /** @brief Set/initialize anneal RNG */ + virtual void setAnnealEnergyRNG(const RNG& rng) = 0; +}; + + +/****************************************************************************************\ +* Simulated annealing solver * +\****************************************************************************************/ + +#ifdef CV_DOXYGEN +/** @brief This class declares example interface for system state used in simulated annealing optimization algorithm. + +@note This class is not defined in C++ code and can't be use directly - you need your own implementation with the same methods. +*/ +struct SimulatedAnnealingSolverSystem +{ + /** Give energy value for a state of system.*/ + double energy() const; + /** Function which change the state of system (random perturbation).*/ + void changeState(); + /** Function to reverse to the previous state. Can be called once only after changeState(). */ + void reverseState(); +}; +#endif // CV_DOXYGEN + +/** @brief The class implements simulated annealing for optimization. + +@cite Kirkpatrick83 for details + +@param solverSystem optimization system (see SimulatedAnnealingSolverSystem) +@param initialTemperature initial temperature +@param finalTemperature final temperature +@param coolingRatio temperature step multiplies +@param iterationsPerStep number of iterations per temperature changing step +@param lastTemperature optional output for last used temperature +@param rngEnergy specify custom random numbers generator (cv::theRNG() by default) +*/ +template +int simulatedAnnealingSolver(SimulatedAnnealingSolverSystem& solverSystem, + double initialTemperature, double finalTemperature, double coolingRatio, + size_t iterationsPerStep, + CV_OUT double* lastTemperature = NULL, + cv::RNG& rngEnergy = cv::theRNG() +); + +//! @} ml + +} +} + +#include + +#endif // __cplusplus +#endif // OPENCV_ML_HPP + +/* End of file. */ diff --git a/3rdparty/opencv/include/opencv2/ml/ml.hpp b/3rdparty/opencv/include/opencv2/ml/ml.hpp new file mode 100644 index 00000000..f6f9cd8f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/ml/ml.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/ml.hpp" diff --git a/3rdparty/opencv/include/opencv2/ml/ml.inl.hpp b/3rdparty/opencv/include/opencv2/ml/ml.inl.hpp new file mode 100644 index 00000000..dc9c7839 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/ml/ml.inl.hpp @@ -0,0 +1,60 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_ML_INL_HPP +#define OPENCV_ML_INL_HPP + +namespace cv { namespace ml { + +// declared in ml.hpp +template +int simulatedAnnealingSolver(SimulatedAnnealingSolverSystem& solverSystem, + double initialTemperature, double finalTemperature, double coolingRatio, + size_t iterationsPerStep, + CV_OUT double* lastTemperature, + cv::RNG& rngEnergy +) +{ + CV_Assert(finalTemperature > 0); + CV_Assert(initialTemperature > finalTemperature); + CV_Assert(iterationsPerStep > 0); + CV_Assert(coolingRatio < 1.0f); + double Ti = initialTemperature; + double previousEnergy = solverSystem.energy(); + int exchange = 0; + while (Ti > finalTemperature) + { + for (size_t i = 0; i < iterationsPerStep; i++) + { + solverSystem.changeState(); + double newEnergy = solverSystem.energy(); + if (newEnergy < previousEnergy) + { + previousEnergy = newEnergy; + exchange++; + } + else + { + double r = rngEnergy.uniform(0.0, 1.0); + if (r < std::exp(-(newEnergy - previousEnergy) / Ti)) + { + previousEnergy = newEnergy; + exchange++; + } + else + { + solverSystem.reverseState(); + } + } + } + Ti *= coolingRatio; + } + if (lastTemperature) + *lastTemperature = Ti; + return exchange; +} + +}} //namespace + +#endif // OPENCV_ML_INL_HPP diff --git a/3rdparty/opencv/include/opencv2/objdetect.hpp b/3rdparty/opencv/include/opencv2/objdetect.hpp new file mode 100644 index 00000000..cc9c4e1a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/objdetect.hpp @@ -0,0 +1,743 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OBJDETECT_HPP +#define OPENCV_OBJDETECT_HPP + +#include "opencv2/core.hpp" + +/** +@defgroup objdetect Object Detection + +Haar Feature-based Cascade Classifier for Object Detection +---------------------------------------------------------- + +The object detector described below has been initially proposed by Paul Viola @cite Viola01 and +improved by Rainer Lienhart @cite Lienhart02 . + +First, a classifier (namely a *cascade of boosted classifiers working with haar-like features*) is +trained with a few hundred sample views of a particular object (i.e., a face or a car), called +positive examples, that are scaled to the same size (say, 20x20), and negative examples - arbitrary +images of the same size. + +After a classifier is trained, it can be applied to a region of interest (of the same size as used +during the training) in an input image. The classifier outputs a "1" if the region is likely to show +the object (i.e., face/car), and "0" otherwise. To search for the object in the whole image one can +move the search window across the image and check every location using the classifier. The +classifier is designed so that it can be easily "resized" in order to be able to find the objects of +interest at different sizes, which is more efficient than resizing the image itself. So, to find an +object of an unknown size in the image the scan procedure should be done several times at different +scales. + +The word "cascade" in the classifier name means that the resultant classifier consists of several +simpler classifiers (*stages*) that are applied subsequently to a region of interest until at some +stage the candidate is rejected or all the stages are passed. The word "boosted" means that the +classifiers at every stage of the cascade are complex themselves and they are built out of basic +classifiers using one of four different boosting techniques (weighted voting). Currently Discrete +Adaboost, Real Adaboost, Gentle Adaboost and Logitboost are supported. The basic classifiers are +decision-tree classifiers with at least 2 leaves. Haar-like features are the input to the basic +classifiers, and are calculated as described below. The current algorithm uses the following +Haar-like features: + +![image](pics/haarfeatures.png) + +The feature used in a particular classifier is specified by its shape (1a, 2b etc.), position within +the region of interest and the scale (this scale is not the same as the scale used at the detection +stage, though these two scales are multiplied). For example, in the case of the third line feature +(2c) the response is calculated as the difference between the sum of image pixels under the +rectangle covering the whole feature (including the two white stripes and the black stripe in the +middle) and the sum of the image pixels under the black stripe multiplied by 3 in order to +compensate for the differences in the size of areas. The sums of pixel values over a rectangular +regions are calculated rapidly using integral images (see below and the integral description). + +To see the object detector at work, have a look at the facedetect demo: + + +The following reference is for the detection part only. There is a separate application called +opencv_traincascade that can train a cascade of boosted classifiers from a set of samples. + +@note In the new C++ interface it is also possible to use LBP (local binary pattern) features in +addition to Haar-like features. .. [Viola01] Paul Viola and Michael J. Jones. Rapid Object Detection +using a Boosted Cascade of Simple Features. IEEE CVPR, 2001. The paper is available online at + + +@{ + @defgroup objdetect_c C API +@} + */ + +typedef struct CvHaarClassifierCascade CvHaarClassifierCascade; + +namespace cv +{ + +//! @addtogroup objdetect +//! @{ + +///////////////////////////// Object Detection //////////////////////////// + +//! class for grouping object candidates, detected by Cascade Classifier, HOG etc. +//! instance of the class is to be passed to cv::partition (see cxoperations.hpp) +class CV_EXPORTS SimilarRects +{ +public: + SimilarRects(double _eps) : eps(_eps) {} + inline bool operator()(const Rect& r1, const Rect& r2) const + { + double delta = eps * ((std::min)(r1.width, r2.width) + (std::min)(r1.height, r2.height)) * 0.5; + return std::abs(r1.x - r2.x) <= delta && + std::abs(r1.y - r2.y) <= delta && + std::abs(r1.x + r1.width - r2.x - r2.width) <= delta && + std::abs(r1.y + r1.height - r2.y - r2.height) <= delta; + } + double eps; +}; + +/** @brief Groups the object candidate rectangles. + +@param rectList Input/output vector of rectangles. Output vector includes retained and grouped +rectangles. (The Python list is not modified in place.) +@param groupThreshold Minimum possible number of rectangles minus 1. The threshold is used in a +group of rectangles to retain it. +@param eps Relative difference between sides of the rectangles to merge them into a group. + +The function is a wrapper for the generic function partition . It clusters all the input rectangles +using the rectangle equivalence criteria that combines rectangles with similar sizes and similar +locations. The similarity is defined by eps. When eps=0 , no clustering is done at all. If +\f$\texttt{eps}\rightarrow +\inf\f$ , all the rectangles are put in one cluster. Then, the small +clusters containing less than or equal to groupThreshold rectangles are rejected. In each other +cluster, the average rectangle is computed and put into the output rectangle list. + */ +CV_EXPORTS void groupRectangles(std::vector& rectList, int groupThreshold, double eps = 0.2); +/** @overload */ +CV_EXPORTS_W void groupRectangles(CV_IN_OUT std::vector& rectList, CV_OUT std::vector& weights, + int groupThreshold, double eps = 0.2); +/** @overload */ +CV_EXPORTS void groupRectangles(std::vector& rectList, int groupThreshold, + double eps, std::vector* weights, std::vector* levelWeights ); +/** @overload */ +CV_EXPORTS void groupRectangles(std::vector& rectList, std::vector& rejectLevels, + std::vector& levelWeights, int groupThreshold, double eps = 0.2); +/** @overload */ +CV_EXPORTS void groupRectangles_meanshift(std::vector& rectList, std::vector& foundWeights, + std::vector& foundScales, + double detectThreshold = 0.0, Size winDetSize = Size(64, 128)); + +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvHaarClassifierCascade* obj) const; + +enum { CASCADE_DO_CANNY_PRUNING = 1, + CASCADE_SCALE_IMAGE = 2, + CASCADE_FIND_BIGGEST_OBJECT = 4, + CASCADE_DO_ROUGH_SEARCH = 8 + }; + +class CV_EXPORTS_W BaseCascadeClassifier : public Algorithm +{ +public: + virtual ~BaseCascadeClassifier(); + virtual bool empty() const CV_OVERRIDE = 0; + virtual bool load( const String& filename ) = 0; + virtual void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + double scaleFactor, + int minNeighbors, int flags, + Size minSize, Size maxSize ) = 0; + + virtual void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + CV_OUT std::vector& numDetections, + double scaleFactor, + int minNeighbors, int flags, + Size minSize, Size maxSize ) = 0; + + virtual void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + CV_OUT std::vector& rejectLevels, + CV_OUT std::vector& levelWeights, + double scaleFactor, + int minNeighbors, int flags, + Size minSize, Size maxSize, + bool outputRejectLevels ) = 0; + + virtual bool isOldFormatCascade() const = 0; + virtual Size getOriginalWindowSize() const = 0; + virtual int getFeatureType() const = 0; + virtual void* getOldCascade() = 0; + + class CV_EXPORTS MaskGenerator + { + public: + virtual ~MaskGenerator() {} + virtual Mat generateMask(const Mat& src)=0; + virtual void initializeMask(const Mat& /*src*/) { } + }; + virtual void setMaskGenerator(const Ptr& maskGenerator) = 0; + virtual Ptr getMaskGenerator() = 0; +}; + +/** @example samples/cpp/facedetect.cpp +This program demonstrates usage of the Cascade classifier class +\image html Cascade_Classifier_Tutorial_Result_Haar.jpg "Sample screenshot" width=321 height=254 +*/ +/** @brief Cascade classifier class for object detection. + */ +class CV_EXPORTS_W CascadeClassifier +{ +public: + CV_WRAP CascadeClassifier(); + /** @brief Loads a classifier from a file. + + @param filename Name of the file from which the classifier is loaded. + */ + CV_WRAP CascadeClassifier(const String& filename); + ~CascadeClassifier(); + /** @brief Checks whether the classifier has been loaded. + */ + CV_WRAP bool empty() const; + /** @brief Loads a classifier from a file. + + @param filename Name of the file from which the classifier is loaded. The file may contain an old + HAAR classifier trained by the haartraining application or a new cascade classifier trained by the + traincascade application. + */ + CV_WRAP bool load( const String& filename ); + /** @brief Reads a classifier from a FileStorage node. + + @note The file may contain a new cascade classifier (trained traincascade application) only. + */ + CV_WRAP bool read( const FileNode& node ); + + /** @brief Detects objects of different sizes in the input image. The detected objects are returned as a list + of rectangles. + + @param image Matrix of the type CV_8U containing an image where objects are detected. + @param objects Vector of rectangles where each rectangle contains the detected object, the + rectangles may be partially outside the original image. + @param scaleFactor Parameter specifying how much the image size is reduced at each image scale. + @param minNeighbors Parameter specifying how many neighbors each candidate rectangle should have + to retain it. + @param flags Parameter with the same meaning for an old cascade as in the function + cvHaarDetectObjects. It is not used for a new cascade. + @param minSize Minimum possible object size. Objects smaller than that are ignored. + @param maxSize Maximum possible object size. Objects larger than that are ignored. If `maxSize == minSize` model is evaluated on single scale. + + The function is parallelized with the TBB library. + + @note + - (Python) A face detection example using cascade classifiers can be found at + opencv_source_code/samples/python/facedetect.py + */ + CV_WRAP void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + double scaleFactor = 1.1, + int minNeighbors = 3, int flags = 0, + Size minSize = Size(), + Size maxSize = Size() ); + + /** @overload + @param image Matrix of the type CV_8U containing an image where objects are detected. + @param objects Vector of rectangles where each rectangle contains the detected object, the + rectangles may be partially outside the original image. + @param numDetections Vector of detection numbers for the corresponding objects. An object's number + of detections is the number of neighboring positively classified rectangles that were joined + together to form the object. + @param scaleFactor Parameter specifying how much the image size is reduced at each image scale. + @param minNeighbors Parameter specifying how many neighbors each candidate rectangle should have + to retain it. + @param flags Parameter with the same meaning for an old cascade as in the function + cvHaarDetectObjects. It is not used for a new cascade. + @param minSize Minimum possible object size. Objects smaller than that are ignored. + @param maxSize Maximum possible object size. Objects larger than that are ignored. If `maxSize == minSize` model is evaluated on single scale. + */ + CV_WRAP_AS(detectMultiScale2) void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + CV_OUT std::vector& numDetections, + double scaleFactor=1.1, + int minNeighbors=3, int flags=0, + Size minSize=Size(), + Size maxSize=Size() ); + + /** @overload + This function allows you to retrieve the final stage decision certainty of classification. + For this, one needs to set `outputRejectLevels` on true and provide the `rejectLevels` and `levelWeights` parameter. + For each resulting detection, `levelWeights` will then contain the certainty of classification at the final stage. + This value can then be used to separate strong from weaker classifications. + + A code sample on how to use it efficiently can be found below: + @code + Mat img; + vector weights; + vector levels; + vector detections; + CascadeClassifier model("/path/to/your/model.xml"); + model.detectMultiScale(img, detections, levels, weights, 1.1, 3, 0, Size(), Size(), true); + cerr << "Detection " << detections[0] << " with weight " << weights[0] << endl; + @endcode + */ + CV_WRAP_AS(detectMultiScale3) void detectMultiScale( InputArray image, + CV_OUT std::vector& objects, + CV_OUT std::vector& rejectLevels, + CV_OUT std::vector& levelWeights, + double scaleFactor = 1.1, + int minNeighbors = 3, int flags = 0, + Size minSize = Size(), + Size maxSize = Size(), + bool outputRejectLevels = false ); + + CV_WRAP bool isOldFormatCascade() const; + CV_WRAP Size getOriginalWindowSize() const; + CV_WRAP int getFeatureType() const; + void* getOldCascade(); + + CV_WRAP static bool convert(const String& oldcascade, const String& newcascade); + + void setMaskGenerator(const Ptr& maskGenerator); + Ptr getMaskGenerator(); + + Ptr cc; +}; + +CV_EXPORTS Ptr createFaceDetectionMaskGenerator(); + +//////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector ////////////// + +//! struct for detection region of interest (ROI) +struct DetectionROI +{ + //! scale(size) of the bounding box + double scale; + //! set of requested locations to be evaluated + std::vector locations; + //! vector that will contain confidence values for each location + std::vector confidences; +}; + +/**@brief Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector. + +the HOG descriptor algorithm introduced by Navneet Dalal and Bill Triggs @cite Dalal2005 . + +useful links: + +https://hal.inria.fr/inria-00548512/document/ + +https://en.wikipedia.org/wiki/Histogram_of_oriented_gradients + +https://software.intel.com/en-us/ipp-dev-reference-histogram-of-oriented-gradients-hog-descriptor + +http://www.learnopencv.com/histogram-of-oriented-gradients + +http://www.learnopencv.com/handwritten-digits-classification-an-opencv-c-python-tutorial + + */ +struct CV_EXPORTS_W HOGDescriptor +{ +public: + enum { L2Hys = 0 //!< Default histogramNormType + }; + enum { DEFAULT_NLEVELS = 64 //!< Default nlevels value. + }; + /**@brief Creates the HOG descriptor and detector with default params. + + aqual to HOGDescriptor(Size(64,128), Size(16,16), Size(8,8), Size(8,8), 9, 1 ) + */ + CV_WRAP HOGDescriptor() : winSize(64,128), blockSize(16,16), blockStride(8,8), + cellSize(8,8), nbins(9), derivAperture(1), winSigma(-1), + histogramNormType(HOGDescriptor::L2Hys), L2HysThreshold(0.2), gammaCorrection(true), + free_coef(-1.f), nlevels(HOGDescriptor::DEFAULT_NLEVELS), signedGradient(false) + {} + + /** @overload + @param _winSize sets winSize with given value. + @param _blockSize sets blockSize with given value. + @param _blockStride sets blockStride with given value. + @param _cellSize sets cellSize with given value. + @param _nbins sets nbins with given value. + @param _derivAperture sets derivAperture with given value. + @param _winSigma sets winSigma with given value. + @param _histogramNormType sets histogramNormType with given value. + @param _L2HysThreshold sets L2HysThreshold with given value. + @param _gammaCorrection sets gammaCorrection with given value. + @param _nlevels sets nlevels with given value. + @param _signedGradient sets signedGradient with given value. + */ + CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, + Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1, + int _histogramNormType=HOGDescriptor::L2Hys, + double _L2HysThreshold=0.2, bool _gammaCorrection=false, + int _nlevels=HOGDescriptor::DEFAULT_NLEVELS, bool _signedGradient=false) + : winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize), + nbins(_nbins), derivAperture(_derivAperture), winSigma(_winSigma), + histogramNormType(_histogramNormType), L2HysThreshold(_L2HysThreshold), + gammaCorrection(_gammaCorrection), free_coef(-1.f), nlevels(_nlevels), signedGradient(_signedGradient) + {} + + /** @overload + @param filename the file name containing HOGDescriptor properties and coefficients of the trained classifier + */ + CV_WRAP HOGDescriptor(const String& filename) + { + load(filename); + } + + /** @overload + @param d the HOGDescriptor which cloned to create a new one. + */ + HOGDescriptor(const HOGDescriptor& d) + { + d.copyTo(*this); + } + + /**@brief Default destructor. + */ + virtual ~HOGDescriptor() {} + + /**@brief Returns the number of coefficients required for the classification. + */ + CV_WRAP size_t getDescriptorSize() const; + + /** @brief Checks if detector size equal to descriptor size. + */ + CV_WRAP bool checkDetectorSize() const; + + /** @brief Returns winSigma value + */ + CV_WRAP double getWinSigma() const; + + /**@example samples/cpp/peopledetect.cpp + */ + /**@brief Sets coefficients for the linear SVM classifier. + @param _svmdetector coefficients for the linear SVM classifier. + */ + CV_WRAP virtual void setSVMDetector(InputArray _svmdetector); + + /** @brief Reads HOGDescriptor parameters from a file node. + @param fn File node + */ + virtual bool read(FileNode& fn); + + /** @brief Stores HOGDescriptor parameters in a file storage. + @param fs File storage + @param objname Object name + */ + virtual void write(FileStorage& fs, const String& objname) const; + + /** @brief loads coefficients for the linear SVM classifier from a file + @param filename Name of the file to read. + @param objname The optional name of the node to read (if empty, the first top-level node will be used). + */ + CV_WRAP virtual bool load(const String& filename, const String& objname = String()); + + /** @brief saves coefficients for the linear SVM classifier to a file + @param filename File name + @param objname Object name + */ + CV_WRAP virtual void save(const String& filename, const String& objname = String()) const; + + /** @brief clones the HOGDescriptor + @param c cloned HOGDescriptor + */ + virtual void copyTo(HOGDescriptor& c) const; + + /**@example samples/cpp/train_HOG.cpp + */ + /** @brief Computes HOG descriptors of given image. + @param img Matrix of the type CV_8U containing an image where HOG features will be calculated. + @param descriptors Matrix of the type CV_32F + @param winStride Window stride. It must be a multiple of block stride. + @param padding Padding + @param locations Vector of Point + */ + CV_WRAP virtual void compute(InputArray img, + CV_OUT std::vector& descriptors, + Size winStride = Size(), Size padding = Size(), + const std::vector& locations = std::vector()) const; + + /** @brief Performs object detection without a multi-scale window. + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries. + @param weights Vector that will contain confidence values for each detected object. + @param hitThreshold Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + @param winStride Window stride. It must be a multiple of block stride. + @param padding Padding + @param searchLocations Vector of Point includes set of requested locations to be evaluated. + */ + CV_WRAP virtual void detect(const Mat& img, CV_OUT std::vector& foundLocations, + CV_OUT std::vector& weights, + double hitThreshold = 0, Size winStride = Size(), + Size padding = Size(), + const std::vector& searchLocations = std::vector()) const; + + /** @brief Performs object detection without a multi-scale window. + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries. + @param hitThreshold Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + @param winStride Window stride. It must be a multiple of block stride. + @param padding Padding + @param searchLocations Vector of Point includes locations to search. + */ + virtual void detect(const Mat& img, CV_OUT std::vector& foundLocations, + double hitThreshold = 0, Size winStride = Size(), + Size padding = Size(), + const std::vector& searchLocations=std::vector()) const; + + /** @brief Detects objects of different sizes in the input image. The detected objects are returned as a list + of rectangles. + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param foundLocations Vector of rectangles where each rectangle contains the detected object. + @param foundWeights Vector that will contain confidence values for each detected object. + @param hitThreshold Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + @param winStride Window stride. It must be a multiple of block stride. + @param padding Padding + @param scale Coefficient of the detection window increase. + @param finalThreshold Final threshold + @param useMeanshiftGrouping indicates grouping algorithm + */ + CV_WRAP virtual void detectMultiScale(InputArray img, CV_OUT std::vector& foundLocations, + CV_OUT std::vector& foundWeights, double hitThreshold = 0, + Size winStride = Size(), Size padding = Size(), double scale = 1.05, + double finalThreshold = 2.0,bool useMeanshiftGrouping = false) const; + + /** @brief Detects objects of different sizes in the input image. The detected objects are returned as a list + of rectangles. + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param foundLocations Vector of rectangles where each rectangle contains the detected object. + @param hitThreshold Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + @param winStride Window stride. It must be a multiple of block stride. + @param padding Padding + @param scale Coefficient of the detection window increase. + @param finalThreshold Final threshold + @param useMeanshiftGrouping indicates grouping algorithm + */ + virtual void detectMultiScale(InputArray img, CV_OUT std::vector& foundLocations, + double hitThreshold = 0, Size winStride = Size(), + Size padding = Size(), double scale = 1.05, + double finalThreshold = 2.0, bool useMeanshiftGrouping = false) const; + + /** @brief Computes gradients and quantized gradient orientations. + @param img Matrix contains the image to be computed + @param grad Matrix of type CV_32FC2 contains computed gradients + @param angleOfs Matrix of type CV_8UC2 contains quantized gradient orientations + @param paddingTL Padding from top-left + @param paddingBR Padding from bottom-right + */ + CV_WRAP virtual void computeGradient(const Mat& img, CV_OUT Mat& grad, CV_OUT Mat& angleOfs, + Size paddingTL = Size(), Size paddingBR = Size()) const; + + /** @brief Returns coefficients of the classifier trained for people detection (for 64x128 windows). + */ + CV_WRAP static std::vector getDefaultPeopleDetector(); + + /**@example samples/tapi/hog.cpp + */ + /** @brief Returns coefficients of the classifier trained for people detection (for 48x96 windows). + */ + CV_WRAP static std::vector getDaimlerPeopleDetector(); + + //! Detection window size. Align to block size and block stride. Default value is Size(64,128). + CV_PROP Size winSize; + + //! Block size in pixels. Align to cell size. Default value is Size(16,16). + CV_PROP Size blockSize; + + //! Block stride. It must be a multiple of cell size. Default value is Size(8,8). + CV_PROP Size blockStride; + + //! Cell size. Default value is Size(8,8). + CV_PROP Size cellSize; + + //! Number of bins used in the calculation of histogram of gradients. Default value is 9. + CV_PROP int nbins; + + //! not documented + CV_PROP int derivAperture; + + //! Gaussian smoothing window parameter. + CV_PROP double winSigma; + + //! histogramNormType + CV_PROP int histogramNormType; + + //! L2-Hys normalization method shrinkage. + CV_PROP double L2HysThreshold; + + //! Flag to specify whether the gamma correction preprocessing is required or not. + CV_PROP bool gammaCorrection; + + //! coefficients for the linear SVM classifier. + CV_PROP std::vector svmDetector; + + //! coefficients for the linear SVM classifier used when OpenCL is enabled + UMat oclSvmDetector; + + //! not documented + float free_coef; + + //! Maximum number of detection window increases. Default value is 64 + CV_PROP int nlevels; + + //! Indicates signed gradient will be used or not + CV_PROP bool signedGradient; + + /** @brief evaluate specified ROI and return confidence value for each location + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param locations Vector of Point + @param foundLocations Vector of Point where each Point is detected object's top-left point. + @param confidences confidences + @param hitThreshold Threshold for the distance between features and SVM classifying plane. Usually + it is 0 and should be specified in the detector coefficients (as the last free coefficient). But if + the free coefficient is omitted (which is allowed), you can specify it manually here + @param winStride winStride + @param padding padding + */ + virtual void detectROI(const cv::Mat& img, const std::vector &locations, + CV_OUT std::vector& foundLocations, CV_OUT std::vector& confidences, + double hitThreshold = 0, cv::Size winStride = Size(), + cv::Size padding = Size()) const; + + /** @brief evaluate specified ROI and return confidence value for each location in multiple scales + @param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected. + @param foundLocations Vector of rectangles where each rectangle contains the detected object. + @param locations Vector of DetectionROI + @param hitThreshold Threshold for the distance between features and SVM classifying plane. Usually it is 0 and should be specified + in the detector coefficients (as the last free coefficient). But if the free coefficient is omitted (which is allowed), you can specify it manually here. + @param groupThreshold Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it. + */ + virtual void detectMultiScaleROI(const cv::Mat& img, + CV_OUT std::vector& foundLocations, + std::vector& locations, + double hitThreshold = 0, + int groupThreshold = 0) const; + + /** @brief read/parse Dalal's alt model file + @param modelfile Path of Dalal's alt model file. + */ + void readALTModel(String modelfile); + + /** @brief Groups the object candidate rectangles. + @param rectList Input/output vector of rectangles. Output vector includes retained and grouped rectangles. (The Python list is not modified in place.) + @param weights Input/output vector of weights of rectangles. Output vector includes weights of retained and grouped rectangles. (The Python list is not modified in place.) + @param groupThreshold Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it. + @param eps Relative difference between sides of the rectangles to merge them into a group. + */ + void groupRectangles(std::vector& rectList, std::vector& weights, int groupThreshold, double eps) const; +}; + +class CV_EXPORTS_W QRCodeDetector +{ +public: + CV_WRAP QRCodeDetector(); + ~QRCodeDetector(); + + /** @brief sets the epsilon used during the horizontal scan of QR code stop marker detection. + @param epsX Epsilon neighborhood, which allows you to determine the horizontal pattern + of the scheme 1:1:3:1:1 according to QR code standard. + */ + CV_WRAP void setEpsX(double epsX); + /** @brief sets the epsilon used during the vertical scan of QR code stop marker detection. + @param epsY Epsilon neighborhood, which allows you to determine the vertical pattern + of the scheme 1:1:3:1:1 according to QR code standard. + */ + CV_WRAP void setEpsY(double epsY); + + /** @brief Detects QR code in image and returns the quadrangle containing the code. + @param img grayscale or color (BGR) image containing (or not) QR code. + @param points Output vector of vertices of the minimum-area quadrangle containing the code. + */ + CV_WRAP bool detect(InputArray img, OutputArray points) const; + + /** @brief Decodes QR code in image once it's found by the detect() method. + Returns UTF8-encoded output string or empty string if the code cannot be decoded. + + @param img grayscale or color (BGR) image containing QR code. + @param points Quadrangle vertices found by detect() method (or some other algorithm). + @param straight_qrcode The optional output image containing rectified and binarized QR code + */ + CV_WRAP cv::String decode(InputArray img, InputArray points, OutputArray straight_qrcode = noArray()); + + /** @brief Both detects and decodes QR code + + @param img grayscale or color (BGR) image containing QR code. + @param points opiotnal output array of vertices of the found QR code quadrangle. Will be empty if not found. + @param straight_qrcode The optional output image containing rectified and binarized QR code + */ + CV_WRAP cv::String detectAndDecode(InputArray img, OutputArray points=noArray(), + OutputArray straight_qrcode = noArray()); +protected: + struct Impl; + Ptr p; +}; + +/** @brief Detect QR code in image and return minimum area of quadrangle that describes QR code. + @param in Matrix of the type CV_8UC1 containing an image where QR code are detected. + @param points Output vector of vertices of a quadrangle of minimal area that describes QR code. + @param eps_x Epsilon neighborhood, which allows you to determine the horizontal pattern of the scheme 1:1:3:1:1 according to QR code standard. + @param eps_y Epsilon neighborhood, which allows you to determine the vertical pattern of the scheme 1:1:3:1:1 according to QR code standard. + */ +CV_EXPORTS bool detectQRCode(InputArray in, std::vector &points, double eps_x = 0.2, double eps_y = 0.1); + +/** @brief Decode QR code in image and return text that is encrypted in QR code. + @param in Matrix of the type CV_8UC1 containing an image where QR code are detected. + @param points Input vector of vertices of a quadrangle of minimal area that describes QR code. + @param decoded_info String information that is encrypted in QR code. + @param straight_qrcode Matrix of the type CV_8UC1 containing an binary straight QR code. + */ +CV_EXPORTS bool decodeQRCode(InputArray in, InputArray points, std::string &decoded_info, OutputArray straight_qrcode = noArray()); + +//! @} objdetect +} + +#include "opencv2/objdetect/detection_based_tracker.hpp" + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/objdetect/objdetect_c.h" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/objdetect/detection_based_tracker.hpp b/3rdparty/opencv/include/opencv2/objdetect/detection_based_tracker.hpp new file mode 100644 index 00000000..07dd5874 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/objdetect/detection_based_tracker.hpp @@ -0,0 +1,227 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OBJDETECT_DBT_HPP +#define OPENCV_OBJDETECT_DBT_HPP + +#include + +// After this condition removal update blacklist for bindings: modules/python/common.cmake +#if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(__ANDROID__) || \ + defined(CV_CXX11) + +#include + +namespace cv +{ + +//! @addtogroup objdetect +//! @{ + +class CV_EXPORTS DetectionBasedTracker +{ + public: + struct CV_EXPORTS Parameters + { + int maxTrackLifetime; + int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0 + + Parameters(); + }; + + class IDetector + { + public: + IDetector(): + minObjSize(96, 96), + maxObjSize(INT_MAX, INT_MAX), + minNeighbours(2), + scaleFactor(1.1f) + {} + + virtual void detect(const cv::Mat& image, std::vector& objects) = 0; + + void setMinObjectSize(const cv::Size& min) + { + minObjSize = min; + } + void setMaxObjectSize(const cv::Size& max) + { + maxObjSize = max; + } + cv::Size getMinObjectSize() const + { + return minObjSize; + } + cv::Size getMaxObjectSize() const + { + return maxObjSize; + } + float getScaleFactor() + { + return scaleFactor; + } + void setScaleFactor(float value) + { + scaleFactor = value; + } + int getMinNeighbours() + { + return minNeighbours; + } + void setMinNeighbours(int value) + { + minNeighbours = value; + } + virtual ~IDetector() {} + + protected: + cv::Size minObjSize; + cv::Size maxObjSize; + int minNeighbours; + float scaleFactor; + }; + + DetectionBasedTracker(cv::Ptr mainDetector, cv::Ptr trackingDetector, const Parameters& params); + virtual ~DetectionBasedTracker(); + + virtual bool run(); + virtual void stop(); + virtual void resetTracking(); + + virtual void process(const cv::Mat& imageGray); + + bool setParameters(const Parameters& params); + const Parameters& getParameters() const; + + + typedef std::pair Object; + virtual void getObjects(std::vector& result) const; + virtual void getObjects(std::vector& result) const; + + enum ObjectStatus + { + DETECTED_NOT_SHOWN_YET, + DETECTED, + DETECTED_TEMPORARY_LOST, + WRONG_OBJECT + }; + struct ExtObject + { + int id; + cv::Rect location; + ObjectStatus status; + ExtObject(int _id, cv::Rect _location, ObjectStatus _status) + :id(_id), location(_location), status(_status) + { + } + }; + virtual void getObjects(std::vector& result) const; + + + virtual int addObject(const cv::Rect& location); //returns id of the new object + + protected: + class SeparateDetectionWork; + cv::Ptr separateDetectionWork; + friend void* workcycleObjectDetectorFunction(void* p); + + struct InnerParameters + { + int numLastPositionsToTrack; + int numStepsToWaitBeforeFirstShow; + int numStepsToTrackWithoutDetectingIfObjectHasNotBeenShown; + int numStepsToShowWithoutDetecting; + + float coeffTrackingWindowSize; + float coeffObjectSizeToTrack; + float coeffObjectSpeedUsingInPrediction; + + InnerParameters(); + }; + Parameters parameters; + InnerParameters innerParameters; + + struct TrackedObject + { + typedef std::vector PositionsVector; + + PositionsVector lastPositions; + + int numDetectedFrames; + int numFramesNotDetected; + int id; + + TrackedObject(const cv::Rect& rect):numDetectedFrames(1), numFramesNotDetected(0) + { + lastPositions.push_back(rect); + id=getNextId(); + }; + + static int getNextId() + { + static int _id=0; + return _id++; + } + }; + + int numTrackedSteps; + std::vector trackedObjects; + + std::vector weightsPositionsSmoothing; + std::vector weightsSizesSmoothing; + + cv::Ptr cascadeForTracking; + + void updateTrackedObjects(const std::vector& detectedObjects); + cv::Rect calcTrackedObjectPositionToShow(int i) const; + cv::Rect calcTrackedObjectPositionToShow(int i, ObjectStatus& status) const; + void detectInRegion(const cv::Mat& img, const cv::Rect& r, std::vector& detectedObjectsInRegions); +}; + +//! @} objdetect + +} //end of cv namespace +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/objdetect/objdetect.hpp b/3rdparty/opencv/include/opencv2/objdetect/objdetect.hpp new file mode 100644 index 00000000..3ee284f4 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/objdetect/objdetect.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/objdetect.hpp" diff --git a/3rdparty/opencv/include/opencv2/objdetect/objdetect_c.h b/3rdparty/opencv/include/opencv2/objdetect/objdetect_c.h new file mode 100644 index 00000000..67dc2f4e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/objdetect/objdetect_c.h @@ -0,0 +1,166 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_OBJDETECT_C_H +#define OPENCV_OBJDETECT_C_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +#include +#include + +extern "C" { +#endif + +/** @addtogroup objdetect_c + @{ + */ + +/****************************************************************************************\ +* Haar-like Object Detection functions * +\****************************************************************************************/ + +#define CV_HAAR_MAGIC_VAL 0x42500000 +#define CV_TYPE_NAME_HAAR "opencv-haar-classifier" + +#define CV_IS_HAAR_CLASSIFIER( haar ) \ + ((haar) != NULL && \ + (((const CvHaarClassifierCascade*)(haar))->flags & CV_MAGIC_MASK)==CV_HAAR_MAGIC_VAL) + +#define CV_HAAR_FEATURE_MAX 3 +#define CV_HAAR_STAGE_MAX 1000 + +typedef struct CvHaarFeature +{ + int tilted; + struct + { + CvRect r; + float weight; + } rect[CV_HAAR_FEATURE_MAX]; +} CvHaarFeature; + +typedef struct CvHaarClassifier +{ + int count; + CvHaarFeature* haar_feature; + float* threshold; + int* left; + int* right; + float* alpha; +} CvHaarClassifier; + +typedef struct CvHaarStageClassifier +{ + int count; + float threshold; + CvHaarClassifier* classifier; + + int next; + int child; + int parent; +} CvHaarStageClassifier; + +typedef struct CvHidHaarClassifierCascade CvHidHaarClassifierCascade; + +typedef struct CvHaarClassifierCascade +{ + int flags; + int count; + CvSize orig_window_size; + CvSize real_window_size; + double scale; + CvHaarStageClassifier* stage_classifier; + CvHidHaarClassifierCascade* hid_cascade; +} CvHaarClassifierCascade; + +typedef struct CvAvgComp +{ + CvRect rect; + int neighbors; +} CvAvgComp; + +/* Loads haar classifier cascade from a directory. + It is obsolete: convert your cascade to xml and use cvLoad instead */ +CVAPI(CvHaarClassifierCascade*) cvLoadHaarClassifierCascade( + const char* directory, CvSize orig_window_size); + +CVAPI(void) cvReleaseHaarClassifierCascade( CvHaarClassifierCascade** cascade ); + +#define CV_HAAR_DO_CANNY_PRUNING 1 +#define CV_HAAR_SCALE_IMAGE 2 +#define CV_HAAR_FIND_BIGGEST_OBJECT 4 +#define CV_HAAR_DO_ROUGH_SEARCH 8 + +CVAPI(CvSeq*) cvHaarDetectObjects( const CvArr* image, + CvHaarClassifierCascade* cascade, CvMemStorage* storage, + double scale_factor CV_DEFAULT(1.1), + int min_neighbors CV_DEFAULT(3), int flags CV_DEFAULT(0), + CvSize min_size CV_DEFAULT(cvSize(0,0)), CvSize max_size CV_DEFAULT(cvSize(0,0))); + +/* sets images for haar classifier cascade */ +CVAPI(void) cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* cascade, + const CvArr* sum, const CvArr* sqsum, + const CvArr* tilted_sum, double scale ); + +/* runs the cascade on the specified window */ +CVAPI(int) cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade, + CvPoint pt, int start_stage CV_DEFAULT(0)); + +/** @} objdetect_c */ + +#ifdef __cplusplus +} + +CV_EXPORTS CvSeq* cvHaarDetectObjectsForROC( const CvArr* image, + CvHaarClassifierCascade* cascade, CvMemStorage* storage, + std::vector& rejectLevels, std::vector& levelWeightds, + double scale_factor = 1.1, + int min_neighbors = 3, int flags = 0, + CvSize min_size = cvSize(0, 0), CvSize max_size = cvSize(0, 0), + bool outputRejectLevels = false ); + +#endif + +#endif /* OPENCV_OBJDETECT_C_H */ diff --git a/3rdparty/opencv/include/opencv2/opencv.hpp b/3rdparty/opencv/include/opencv2/opencv.hpp new file mode 100644 index 00000000..40481587 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/opencv.hpp @@ -0,0 +1,139 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2010, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_ALL_HPP +#define OPENCV_ALL_HPP + +// File that defines what modules where included during the build of OpenCV +// These are purely the defines of the correct HAVE_OPENCV_modulename values +#include "opencv2/opencv_modules.hpp" + +// Then the list of defines is checked to include the correct headers +// Core library is always included --> without no OpenCV functionality available +#include "opencv2/core.hpp" + +// Then the optional modules are checked +#ifdef HAVE_OPENCV_CALIB3D +#include "opencv2/calib3d.hpp" +#endif +#ifdef HAVE_OPENCV_FEATURES2D +#include "opencv2/features2d.hpp" +#endif +#ifdef HAVE_OPENCV_DNN +#include "opencv2/dnn.hpp" +#endif +#ifdef HAVE_OPENCV_FLANN +#include "opencv2/flann.hpp" +#endif +#ifdef HAVE_OPENCV_HIGHGUI +#include "opencv2/highgui.hpp" +#endif +#ifdef HAVE_OPENCV_IMGCODECS +#include "opencv2/imgcodecs.hpp" +#endif +#ifdef HAVE_OPENCV_IMGPROC +#include "opencv2/imgproc.hpp" +#endif +#ifdef HAVE_OPENCV_ML +#include "opencv2/ml.hpp" +#endif +#ifdef HAVE_OPENCV_OBJDETECT +#include "opencv2/objdetect.hpp" +#endif +#ifdef HAVE_OPENCV_PHOTO +#include "opencv2/photo.hpp" +#endif +#ifdef HAVE_OPENCV_SHAPE +#include "opencv2/shape.hpp" +#endif +#ifdef HAVE_OPENCV_STITCHING +#include "opencv2/stitching.hpp" +#endif +#ifdef HAVE_OPENCV_SUPERRES +#include "opencv2/superres.hpp" +#endif +#ifdef HAVE_OPENCV_VIDEO +#include "opencv2/video.hpp" +#endif +#ifdef HAVE_OPENCV_VIDEOIO +#include "opencv2/videoio.hpp" +#endif +#ifdef HAVE_OPENCV_VIDEOSTAB +#include "opencv2/videostab.hpp" +#endif +#ifdef HAVE_OPENCV_VIZ +#include "opencv2/viz.hpp" +#endif + +// Finally CUDA specific entries are checked and added +#ifdef HAVE_OPENCV_CUDAARITHM +#include "opencv2/cudaarithm.hpp" +#endif +#ifdef HAVE_OPENCV_CUDABGSEGM +#include "opencv2/cudabgsegm.hpp" +#endif +#ifdef HAVE_OPENCV_CUDACODEC +#include "opencv2/cudacodec.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAFEATURES2D +#include "opencv2/cudafeatures2d.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAFILTERS +#include "opencv2/cudafilters.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAIMGPROC +#include "opencv2/cudaimgproc.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAOBJDETECT +#include "opencv2/cudaobjdetect.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAOPTFLOW +#include "opencv2/cudaoptflow.hpp" +#endif +#ifdef HAVE_OPENCV_CUDASTEREO +#include "opencv2/cudastereo.hpp" +#endif +#ifdef HAVE_OPENCV_CUDAWARPING +#include "opencv2/cudawarping.hpp" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/opencv_modules.hpp b/3rdparty/opencv/include/opencv2/opencv_modules.hpp new file mode 100644 index 00000000..e14f3ec7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/opencv_modules.hpp @@ -0,0 +1,31 @@ +/* + * ** File generated automatically, do not modify ** + * + * This file defines the list of modules available in current build configuration + * + * +*/ + +// This definition means that OpenCV is built with enabled non-free code. +// For example, patented algorithms for non-profit/non-commercial use only. +/* #undef OPENCV_ENABLE_NONFREE */ + +#define HAVE_OPENCV_CALIB3D +#define HAVE_OPENCV_CORE +#define HAVE_OPENCV_DNN +#define HAVE_OPENCV_FEATURES2D +#define HAVE_OPENCV_FLANN +#define HAVE_OPENCV_HIGHGUI +#define HAVE_OPENCV_IMGCODECS +#define HAVE_OPENCV_IMGPROC +#define HAVE_OPENCV_ML +#define HAVE_OPENCV_OBJDETECT +#define HAVE_OPENCV_PHOTO +#define HAVE_OPENCV_SHAPE +#define HAVE_OPENCV_STITCHING +#define HAVE_OPENCV_SUPERRES +#define HAVE_OPENCV_VIDEO +#define HAVE_OPENCV_VIDEOIO +#define HAVE_OPENCV_VIDEOSTAB + + diff --git a/3rdparty/opencv/include/opencv2/photo.hpp b/3rdparty/opencv/include/opencv2/photo.hpp new file mode 100644 index 00000000..8b0652ad --- /dev/null +++ b/3rdparty/opencv/include/opencv2/photo.hpp @@ -0,0 +1,860 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_PHOTO_HPP +#define OPENCV_PHOTO_HPP + +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" + +/** +@defgroup photo Computational Photography + +This module includes photo processing algorithms +@{ + @defgroup photo_inpaint Inpainting + @defgroup photo_denoise Denoising + @defgroup photo_hdr HDR imaging + +This section describes high dynamic range imaging algorithms namely tonemapping, exposure alignment, +camera calibration with multiple exposures and exposure fusion. + + @defgroup photo_decolor Contrast Preserving Decolorization + +Useful links: + +http://www.cse.cuhk.edu.hk/leojia/projects/color2gray/index.html + + @defgroup photo_clone Seamless Cloning + +Useful links: + +https://www.learnopencv.com/seamless-cloning-using-opencv-python-cpp + + @defgroup photo_render Non-Photorealistic Rendering + +Useful links: + +http://www.inf.ufrgs.br/~eslgastal/DomainTransform + +https://www.learnopencv.com/non-photorealistic-rendering-using-opencv-python-c/ +@} + */ + +namespace cv +{ + +//! @addtogroup photo +//! @{ + +//! @addtogroup photo_inpaint +//! @{ +//! the inpainting algorithm +enum +{ + INPAINT_NS = 0, //!< Use Navier-Stokes based method + INPAINT_TELEA = 1 //!< Use the algorithm proposed by Alexandru Telea @cite Telea04 +}; + +/** @brief Restores the selected region in an image using the region neighborhood. + +@param src Input 8-bit, 16-bit unsigned or 32-bit float 1-channel or 8-bit 3-channel image. +@param inpaintMask Inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that +needs to be inpainted. +@param dst Output image with the same size and type as src . +@param inpaintRadius Radius of a circular neighborhood of each point inpainted that is considered +by the algorithm. +@param flags Inpainting method that could be cv::INPAINT_NS or cv::INPAINT_TELEA + +The function reconstructs the selected image area from the pixel near the area boundary. The +function may be used to remove dust and scratches from a scanned photo, or to remove undesirable +objects from still images or video. See for more details. + +@note + - An example using the inpainting technique can be found at + opencv_source_code/samples/cpp/inpaint.cpp + - (Python) An example using the inpainting technique can be found at + opencv_source_code/samples/python/inpaint.py + */ +CV_EXPORTS_W void inpaint( InputArray src, InputArray inpaintMask, + OutputArray dst, double inpaintRadius, int flags ); + +//! @} photo_inpaint + +//! @addtogroup photo_denoise +//! @{ + +/** @brief Perform image denoising using Non-local Means Denoising algorithm + with several computational +optimizations. Noise expected to be a gaussian white noise + +@param src Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image. +@param dst Output image with the same size and type as src . +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Parameter regulating filter strength. Big h value perfectly removes noise but also +removes image details, smaller h value preserves details but also preserves some noise + +This function expected to be applied to grayscale images. For colored images look at +fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored +image in different colorspaces. Such approach is used in fastNlMeansDenoisingColored by converting +image to CIELAB colorspace and then separately denoise L and AB components with different h +parameter. + */ +CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, float h = 3, + int templateWindowSize = 7, int searchWindowSize = 21); + +/** @brief Perform image denoising using Non-local Means Denoising algorithm + with several computational +optimizations. Noise expected to be a gaussian white noise + +@param src Input 8-bit or 16-bit (only with NORM_L1) 1-channel, +2-channel, 3-channel or 4-channel image. +@param dst Output image with the same size and type as src . +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Array of parameters regulating filter strength, either one +parameter applied to all channels or one per channel in dst. Big h value +perfectly removes noise but also removes image details, smaller h +value preserves details but also preserves some noise +@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1 + +This function expected to be applied to grayscale images. For colored images look at +fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored +image in different colorspaces. Such approach is used in fastNlMeansDenoisingColored by converting +image to CIELAB colorspace and then separately denoise L and AB components with different h +parameter. + */ +CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, + const std::vector& h, + int templateWindowSize = 7, int searchWindowSize = 21, + int normType = NORM_L2); + +/** @brief Modification of fastNlMeansDenoising function for colored images + +@param src Input 8-bit 3-channel image. +@param dst Output image with the same size and type as src . +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Parameter regulating filter strength for luminance component. Bigger h value perfectly +removes noise but also removes image details, smaller h value preserves details but also preserves +some noise +@param hColor The same as h but for color components. For most images value equals 10 +will be enough to remove colored noise and do not distort colors + +The function converts image to CIELAB colorspace and then separately denoise L and AB components +with given h parameters using fastNlMeansDenoising function. + */ +CV_EXPORTS_W void fastNlMeansDenoisingColored( InputArray src, OutputArray dst, + float h = 3, float hColor = 3, + int templateWindowSize = 7, int searchWindowSize = 21); + +/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been +captured in small period of time. For example video. This version of the function is for grayscale +images or for manual manipulation with colorspaces. For more details see + + +@param srcImgs Input 8-bit 1-channel, 2-channel, 3-channel or +4-channel images sequence. All images should have the same type and +size. +@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence +@param temporalWindowSize Number of surrounding images to use for target image denoising. Should +be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to +imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs will be used to denoise +srcImgs[imgToDenoiseIndex] image. +@param dst Output image with the same size and type as srcImgs images. +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Parameter regulating filter strength. Bigger h value +perfectly removes noise but also removes image details, smaller h +value preserves details but also preserves some noise + */ +CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst, + int imgToDenoiseIndex, int temporalWindowSize, + float h = 3, int templateWindowSize = 7, int searchWindowSize = 21); + +/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been +captured in small period of time. For example video. This version of the function is for grayscale +images or for manual manipulation with colorspaces. For more details see + + +@param srcImgs Input 8-bit or 16-bit (only with NORM_L1) 1-channel, +2-channel, 3-channel or 4-channel images sequence. All images should +have the same type and size. +@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence +@param temporalWindowSize Number of surrounding images to use for target image denoising. Should +be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to +imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs will be used to denoise +srcImgs[imgToDenoiseIndex] image. +@param dst Output image with the same size and type as srcImgs images. +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Array of parameters regulating filter strength, either one +parameter applied to all channels or one per channel in dst. Big h value +perfectly removes noise but also removes image details, smaller h +value preserves details but also preserves some noise +@param normType Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1 + */ +CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst, + int imgToDenoiseIndex, int temporalWindowSize, + const std::vector& h, + int templateWindowSize = 7, int searchWindowSize = 21, + int normType = NORM_L2); + +/** @brief Modification of fastNlMeansDenoisingMulti function for colored images sequences + +@param srcImgs Input 8-bit 3-channel images sequence. All images should have the same type and +size. +@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence +@param temporalWindowSize Number of surrounding images to use for target image denoising. Should +be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to +imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs will be used to denoise +srcImgs[imgToDenoiseIndex] image. +@param dst Output image with the same size and type as srcImgs images. +@param templateWindowSize Size in pixels of the template patch that is used to compute weights. +Should be odd. Recommended value 7 pixels +@param searchWindowSize Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater +denoising time. Recommended value 21 pixels +@param h Parameter regulating filter strength for luminance component. Bigger h value perfectly +removes noise but also removes image details, smaller h value preserves details but also preserves +some noise. +@param hColor The same as h but for color components. + +The function converts images to CIELAB colorspace and then separately denoise L and AB components +with given h parameters using fastNlMeansDenoisingMulti function. + */ +CV_EXPORTS_W void fastNlMeansDenoisingColoredMulti( InputArrayOfArrays srcImgs, OutputArray dst, + int imgToDenoiseIndex, int temporalWindowSize, + float h = 3, float hColor = 3, + int templateWindowSize = 7, int searchWindowSize = 21); + +/** @brief Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, +finding a function to minimize some functional). As the image denoising, in particular, may be seen +as the variational problem, primal-dual algorithm then can be used to perform denoising and this is +exactly what is implemented. + +It should be noted, that this implementation was taken from the July 2013 blog entry +@cite MA13 , which also contained (slightly more general) ready-to-use source code on Python. +Subsequently, that code was rewritten on C++ with the usage of openCV by Vadim Pisarevsky at the end +of July 2013 and finally it was slightly adapted by later authors. + +Although the thorough discussion and justification of the algorithm involved may be found in +@cite ChambolleEtAl, it might make sense to skim over it here, following @cite MA13 . To begin +with, we consider the 1-byte gray-level images as the functions from the rectangular domain of +pixels (it may be seen as set +\f$\left\{(x,y)\in\mathbb{N}\times\mathbb{N}\mid 1\leq x\leq n,\;1\leq y\leq m\right\}\f$ for some +\f$m,\;n\in\mathbb{N}\f$) into \f$\{0,1,\dots,255\}\f$. We shall denote the noised images as \f$f_i\f$ and with +this view, given some image \f$x\f$ of the same size, we may measure how bad it is by the formula + +\f[\left\|\left\|\nabla x\right\|\right\| + \lambda\sum_i\left\|\left\|x-f_i\right\|\right\|\f] + +\f$\|\|\cdot\|\|\f$ here denotes \f$L_2\f$-norm and as you see, the first addend states that we want our +image to be smooth (ideally, having zero gradient, thus being constant) and the second states that +we want our result to be close to the observations we've got. If we treat \f$x\f$ as a function, this is +exactly the functional what we seek to minimize and here the Primal-Dual algorithm comes into play. + +@param observations This array should contain one or more noised versions of the image that is to +be restored. +@param result Here the denoised image will be stored. There is no need to do pre-allocation of +storage space, as it will be automatically allocated, if necessary. +@param lambda Corresponds to \f$\lambda\f$ in the formulas above. As it is enlarged, the smooth +(blurred) images are treated more favorably than detailed (but maybe more noised) ones. Roughly +speaking, as it becomes smaller, the result will be more blur but more sever outliers will be +removed. +@param niters Number of iterations that the algorithm will run. Of course, as more iterations as +better, but it is hard to quantitatively refine this statement, so just use the default and +increase it if the results are poor. + */ +CV_EXPORTS_W void denoise_TVL1(const std::vector& observations,Mat& result, double lambda=1.0, int niters=30); + +//! @} photo_denoise + +//! @addtogroup photo_hdr +//! @{ + +enum { LDR_SIZE = 256 }; + +/** @brief Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range. + */ +class CV_EXPORTS_W Tonemap : public Algorithm +{ +public: + /** @brief Tonemaps image + + @param src source image - CV_32FC3 Mat (float 32 bits 3 channels) + @param dst destination image - CV_32FC3 Mat with values in [0, 1] range + */ + CV_WRAP virtual void process(InputArray src, OutputArray dst) = 0; + + CV_WRAP virtual float getGamma() const = 0; + CV_WRAP virtual void setGamma(float gamma) = 0; +}; + +/** @brief Creates simple linear mapper with gamma correction + +@param gamma positive value for gamma correction. Gamma value of 1.0 implies no correction, gamma +equal to 2.2f is suitable for most displays. +Generally gamma \> 1 brightens the image and gamma \< 1 darkens it. + */ +CV_EXPORTS_W Ptr createTonemap(float gamma = 1.0f); + +/** @brief Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in +logarithmic domain. + +Since it's a global operator the same function is applied to all the pixels, it is controlled by the +bias parameter. + +Optional saturation enhancement is possible as described in @cite FL02 . + +For more information see @cite DM03 . + */ +class CV_EXPORTS_W TonemapDrago : public Tonemap +{ +public: + + CV_WRAP virtual float getSaturation() const = 0; + CV_WRAP virtual void setSaturation(float saturation) = 0; + + CV_WRAP virtual float getBias() const = 0; + CV_WRAP virtual void setBias(float bias) = 0; +}; + +/** @brief Creates TonemapDrago object + +@param gamma gamma value for gamma correction. See createTonemap +@param saturation positive saturation enhancement value. 1.0 preserves saturation, values greater +than 1 increase saturation and values less than 1 decrease it. +@param bias value for bias function in [0, 1] range. Values from 0.7 to 0.9 usually give best +results, default value is 0.85. + */ +CV_EXPORTS_W Ptr createTonemapDrago(float gamma = 1.0f, float saturation = 1.0f, float bias = 0.85f); + + +/** @brief This is a global tonemapping operator that models human visual system. + +Mapping function is controlled by adaptation parameter, that is computed using light adaptation and +color adaptation. + +For more information see @cite RD05 . + */ +class CV_EXPORTS_W TonemapReinhard : public Tonemap +{ +public: + CV_WRAP virtual float getIntensity() const = 0; + CV_WRAP virtual void setIntensity(float intensity) = 0; + + CV_WRAP virtual float getLightAdaptation() const = 0; + CV_WRAP virtual void setLightAdaptation(float light_adapt) = 0; + + CV_WRAP virtual float getColorAdaptation() const = 0; + CV_WRAP virtual void setColorAdaptation(float color_adapt) = 0; +}; + +/** @brief Creates TonemapReinhard object + +@param gamma gamma value for gamma correction. See createTonemap +@param intensity result intensity in [-8, 8] range. Greater intensity produces brighter results. +@param light_adapt light adaptation in [0, 1] range. If 1 adaptation is based only on pixel +value, if 0 it's global, otherwise it's a weighted mean of this two cases. +@param color_adapt chromatic adaptation in [0, 1] range. If 1 channels are treated independently, +if 0 adaptation level is the same for each channel. + */ +CV_EXPORTS_W Ptr +createTonemapReinhard(float gamma = 1.0f, float intensity = 0.0f, float light_adapt = 1.0f, float color_adapt = 0.0f); + +/** @brief This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid, +transforms contrast values to HVS response and scales the response. After this the image is +reconstructed from new contrast values. + +For more information see @cite MM06 . + */ +class CV_EXPORTS_W TonemapMantiuk : public Tonemap +{ +public: + CV_WRAP virtual float getScale() const = 0; + CV_WRAP virtual void setScale(float scale) = 0; + + CV_WRAP virtual float getSaturation() const = 0; + CV_WRAP virtual void setSaturation(float saturation) = 0; +}; + +/** @brief Creates TonemapMantiuk object + +@param gamma gamma value for gamma correction. See createTonemap +@param scale contrast scale factor. HVS response is multiplied by this parameter, thus compressing +dynamic range. Values from 0.6 to 0.9 produce best results. +@param saturation saturation enhancement value. See createTonemapDrago + */ +CV_EXPORTS_W Ptr +createTonemapMantiuk(float gamma = 1.0f, float scale = 0.7f, float saturation = 1.0f); + +/** @brief The base class for algorithms that align images of the same scene with different exposures + */ +class CV_EXPORTS_W AlignExposures : public Algorithm +{ +public: + /** @brief Aligns images + + @param src vector of input images + @param dst vector of aligned images + @param times vector of exposure time values for each image + @param response 256x1 matrix with inverse camera response function for each pixel value, it should + have the same number of channels as images. + */ + CV_WRAP virtual void process(InputArrayOfArrays src, std::vector& dst, + InputArray times, InputArray response) = 0; +}; + +/** @brief This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median +luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations. + +It is invariant to exposure, so exposure values and camera response are not necessary. + +In this implementation new image regions are filled with zeros. + +For more information see @cite GW03 . + */ +class CV_EXPORTS_W AlignMTB : public AlignExposures +{ +public: + CV_WRAP virtual void process(InputArrayOfArrays src, std::vector& dst, + InputArray times, InputArray response) CV_OVERRIDE = 0; + + /** @brief Short version of process, that doesn't take extra arguments. + + @param src vector of input images + @param dst vector of aligned images + */ + CV_WRAP virtual void process(InputArrayOfArrays src, std::vector& dst) = 0; + + /** @brief Calculates shift between two images, i. e. how to shift the second image to correspond it with the + first. + + @param img0 first image + @param img1 second image + */ + CV_WRAP virtual Point calculateShift(InputArray img0, InputArray img1) = 0; + /** @brief Helper function, that shift Mat filling new regions with zeros. + + @param src input image + @param dst result image + @param shift shift value + */ + CV_WRAP virtual void shiftMat(InputArray src, OutputArray dst, const Point shift) = 0; + /** @brief Computes median threshold and exclude bitmaps of given image. + + @param img input image + @param tb median threshold bitmap + @param eb exclude bitmap + */ + CV_WRAP virtual void computeBitmaps(InputArray img, OutputArray tb, OutputArray eb) = 0; + + CV_WRAP virtual int getMaxBits() const = 0; + CV_WRAP virtual void setMaxBits(int max_bits) = 0; + + CV_WRAP virtual int getExcludeRange() const = 0; + CV_WRAP virtual void setExcludeRange(int exclude_range) = 0; + + CV_WRAP virtual bool getCut() const = 0; + CV_WRAP virtual void setCut(bool value) = 0; +}; + +/** @brief Creates AlignMTB object + +@param max_bits logarithm to the base 2 of maximal shift in each dimension. Values of 5 and 6 are +usually good enough (31 and 63 pixels shift respectively). +@param exclude_range range for exclusion bitmap that is constructed to suppress noise around the +median value. +@param cut if true cuts images, otherwise fills the new regions with zeros. + */ +CV_EXPORTS_W Ptr createAlignMTB(int max_bits = 6, int exclude_range = 4, bool cut = true); + +/** @brief The base class for camera response calibration algorithms. + */ +class CV_EXPORTS_W CalibrateCRF : public Algorithm +{ +public: + /** @brief Recovers inverse camera response. + + @param src vector of input images + @param dst 256x1 matrix with inverse camera response function + @param times vector of exposure time values for each image + */ + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, InputArray times) = 0; +}; + +/** @brief Inverse camera response function is extracted for each brightness value by minimizing an objective +function as linear system. Objective function is constructed using pixel values on the same position +in all images, extra term is added to make the result smoother. + +For more information see @cite DM97 . + */ +class CV_EXPORTS_W CalibrateDebevec : public CalibrateCRF +{ +public: + CV_WRAP virtual float getLambda() const = 0; + CV_WRAP virtual void setLambda(float lambda) = 0; + + CV_WRAP virtual int getSamples() const = 0; + CV_WRAP virtual void setSamples(int samples) = 0; + + CV_WRAP virtual bool getRandom() const = 0; + CV_WRAP virtual void setRandom(bool random) = 0; +}; + +/** @brief Creates CalibrateDebevec object + +@param samples number of pixel locations to use +@param lambda smoothness term weight. Greater values produce smoother results, but can alter the +response. +@param random if true sample pixel locations are chosen at random, otherwise they form a +rectangular grid. + */ +CV_EXPORTS_W Ptr createCalibrateDebevec(int samples = 70, float lambda = 10.0f, bool random = false); + +/** @brief Inverse camera response function is extracted for each brightness value by minimizing an objective +function as linear system. This algorithm uses all image pixels. + +For more information see @cite RB99 . + */ +class CV_EXPORTS_W CalibrateRobertson : public CalibrateCRF +{ +public: + CV_WRAP virtual int getMaxIter() const = 0; + CV_WRAP virtual void setMaxIter(int max_iter) = 0; + + CV_WRAP virtual float getThreshold() const = 0; + CV_WRAP virtual void setThreshold(float threshold) = 0; + + CV_WRAP virtual Mat getRadiance() const = 0; +}; + +/** @brief Creates CalibrateRobertson object + +@param max_iter maximal number of Gauss-Seidel solver iterations. +@param threshold target difference between results of two successive steps of the minimization. + */ +CV_EXPORTS_W Ptr createCalibrateRobertson(int max_iter = 30, float threshold = 0.01f); + +/** @brief The base class algorithms that can merge exposure sequence to a single image. + */ +class CV_EXPORTS_W MergeExposures : public Algorithm +{ +public: + /** @brief Merges images. + + @param src vector of input images + @param dst result image + @param times vector of exposure time values for each image + @param response 256x1 matrix with inverse camera response function for each pixel value, it should + have the same number of channels as images. + */ + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, + InputArray times, InputArray response) = 0; +}; + +/** @brief The resulting HDR image is calculated as weighted average of the exposures considering exposure +values and camera response. + +For more information see @cite DM97 . + */ +class CV_EXPORTS_W MergeDebevec : public MergeExposures +{ +public: + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, + InputArray times, InputArray response) CV_OVERRIDE = 0; + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, InputArray times) = 0; +}; + +/** @brief Creates MergeDebevec object + */ +CV_EXPORTS_W Ptr createMergeDebevec(); + +/** @brief Pixels are weighted using contrast, saturation and well-exposedness measures, than images are +combined using laplacian pyramids. + +The resulting image weight is constructed as weighted average of contrast, saturation and +well-exposedness measures. + +The resulting image doesn't require tonemapping and can be converted to 8-bit image by multiplying +by 255, but it's recommended to apply gamma correction and/or linear tonemapping. + +For more information see @cite MK07 . + */ +class CV_EXPORTS_W MergeMertens : public MergeExposures +{ +public: + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, + InputArray times, InputArray response) CV_OVERRIDE = 0; + /** @brief Short version of process, that doesn't take extra arguments. + + @param src vector of input images + @param dst result image + */ + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst) = 0; + + CV_WRAP virtual float getContrastWeight() const = 0; + CV_WRAP virtual void setContrastWeight(float contrast_weiht) = 0; + + CV_WRAP virtual float getSaturationWeight() const = 0; + CV_WRAP virtual void setSaturationWeight(float saturation_weight) = 0; + + CV_WRAP virtual float getExposureWeight() const = 0; + CV_WRAP virtual void setExposureWeight(float exposure_weight) = 0; +}; + +/** @brief Creates MergeMertens object + +@param contrast_weight contrast measure weight. See MergeMertens. +@param saturation_weight saturation measure weight +@param exposure_weight well-exposedness measure weight + */ +CV_EXPORTS_W Ptr +createMergeMertens(float contrast_weight = 1.0f, float saturation_weight = 1.0f, float exposure_weight = 0.0f); + +/** @brief The resulting HDR image is calculated as weighted average of the exposures considering exposure +values and camera response. + +For more information see @cite RB99 . + */ +class CV_EXPORTS_W MergeRobertson : public MergeExposures +{ +public: + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, + InputArray times, InputArray response) CV_OVERRIDE = 0; + CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, InputArray times) = 0; +}; + +/** @brief Creates MergeRobertson object + */ +CV_EXPORTS_W Ptr createMergeRobertson(); + +//! @} photo_hdr + +//! @addtogroup photo_decolor +//! @{ + +/** @brief Transforms a color image to a grayscale image. It is a basic tool in digital printing, stylized +black-and-white photograph rendering, and in many single channel image processing applications +@cite CL12 . + +@param src Input 8-bit 3-channel image. +@param grayscale Output 8-bit 1-channel image. +@param color_boost Output 8-bit 3-channel image. + +This function is to be applied on color images. + */ +CV_EXPORTS_W void decolor( InputArray src, OutputArray grayscale, OutputArray color_boost); + +//! @} photo_decolor + +//! @addtogroup photo_clone +//! @{ + + +//! seamlessClone algorithm flags +enum +{ + /** The power of the method is fully expressed when inserting objects with complex outlines into a new background*/ + NORMAL_CLONE = 1, + /** The classic method, color-based selection and alpha masking might be time consuming and often leaves an undesirable + halo. Seamless cloning, even averaged with the original image, is not effective. Mixed seamless cloning based on a loose selection proves effective.*/ + MIXED_CLONE = 2, + /** Monochrome transfer allows the user to easily replace certain features of one object by alternative features.*/ + MONOCHROME_TRANSFER = 3}; + + +/** @example samples/cpp/tutorial_code/photo/seamless_cloning/cloning_demo.cpp +An example using seamlessClone function +*/ +/** @brief Image editing tasks concern either global changes (color/intensity corrections, filters, +deformations) or local changes concerned to a selection. Here we are interested in achieving local +changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless +manner. The extent of the changes ranges from slight distortions to complete replacement by novel +content @cite PM03 . + +@param src Input 8-bit 3-channel image. +@param dst Input 8-bit 3-channel image. +@param mask Input 8-bit 1 or 3-channel image. +@param p Point in dst image where object is placed. +@param blend Output image with the same size and type as dst. +@param flags Cloning method that could be cv::NORMAL_CLONE, cv::MIXED_CLONE or cv::MONOCHROME_TRANSFER + */ +CV_EXPORTS_W void seamlessClone( InputArray src, InputArray dst, InputArray mask, Point p, + OutputArray blend, int flags); + +/** @brief Given an original color image, two differently colored versions of this image can be mixed +seamlessly. + +@param src Input 8-bit 3-channel image. +@param mask Input 8-bit 1 or 3-channel image. +@param dst Output image with the same size and type as src . +@param red_mul R-channel multiply factor. +@param green_mul G-channel multiply factor. +@param blue_mul B-channel multiply factor. + +Multiplication factor is between .5 to 2.5. + */ +CV_EXPORTS_W void colorChange(InputArray src, InputArray mask, OutputArray dst, float red_mul = 1.0f, + float green_mul = 1.0f, float blue_mul = 1.0f); + +/** @brief Applying an appropriate non-linear transformation to the gradient field inside the selection and +then integrating back with a Poisson solver, modifies locally the apparent illumination of an image. + +@param src Input 8-bit 3-channel image. +@param mask Input 8-bit 1 or 3-channel image. +@param dst Output image with the same size and type as src. +@param alpha Value ranges between 0-2. +@param beta Value ranges between 0-2. + +This is useful to highlight under-exposed foreground objects or to reduce specular reflections. + */ +CV_EXPORTS_W void illuminationChange(InputArray src, InputArray mask, OutputArray dst, + float alpha = 0.2f, float beta = 0.4f); + +/** @brief By retaining only the gradients at edge locations, before integrating with the Poisson solver, one +washes out the texture of the selected region, giving its contents a flat aspect. Here Canny Edge %Detector is used. + +@param src Input 8-bit 3-channel image. +@param mask Input 8-bit 1 or 3-channel image. +@param dst Output image with the same size and type as src. +@param low_threshold %Range from 0 to 100. +@param high_threshold Value \> 100. +@param kernel_size The size of the Sobel kernel to be used. + +@note +The algorithm assumes that the color of the source image is close to that of the destination. This +assumption means that when the colors don't match, the source image color gets tinted toward the +color of the destination image. + */ +CV_EXPORTS_W void textureFlattening(InputArray src, InputArray mask, OutputArray dst, + float low_threshold = 30, float high_threshold = 45, + int kernel_size = 3); + +//! @} photo_clone + +//! @addtogroup photo_render +//! @{ + +//! Edge preserving filters +enum +{ + RECURS_FILTER = 1, //!< Recursive Filtering + NORMCONV_FILTER = 2 //!< Normalized Convolution Filtering +}; + +/** @brief Filtering is the fundamental operation in image and video processing. Edge-preserving smoothing +filters are used in many different applications @cite EM11 . + +@param src Input 8-bit 3-channel image. +@param dst Output 8-bit 3-channel image. +@param flags Edge preserving filters: cv::RECURS_FILTER or cv::NORMCONV_FILTER +@param sigma_s %Range between 0 to 200. +@param sigma_r %Range between 0 to 1. + */ +CV_EXPORTS_W void edgePreservingFilter(InputArray src, OutputArray dst, int flags = 1, + float sigma_s = 60, float sigma_r = 0.4f); + +/** @brief This filter enhances the details of a particular image. + +@param src Input 8-bit 3-channel image. +@param dst Output image with the same size and type as src. +@param sigma_s %Range between 0 to 200. +@param sigma_r %Range between 0 to 1. + */ +CV_EXPORTS_W void detailEnhance(InputArray src, OutputArray dst, float sigma_s = 10, + float sigma_r = 0.15f); + +/** @example samples/cpp/tutorial_code/photo/non_photorealistic_rendering/npr_demo.cpp +An example using non-photorealistic line drawing functions +*/ +/** @brief Pencil-like non-photorealistic line drawing + +@param src Input 8-bit 3-channel image. +@param dst1 Output 8-bit 1-channel image. +@param dst2 Output image with the same size and type as src. +@param sigma_s %Range between 0 to 200. +@param sigma_r %Range between 0 to 1. +@param shade_factor %Range between 0 to 0.1. + */ +CV_EXPORTS_W void pencilSketch(InputArray src, OutputArray dst1, OutputArray dst2, + float sigma_s = 60, float sigma_r = 0.07f, float shade_factor = 0.02f); + +/** @brief Stylization aims to produce digital imagery with a wide variety of effects not focused on +photorealism. Edge-aware filters are ideal for stylization, as they can abstract regions of low +contrast while preserving, or enhancing, high-contrast features. + +@param src Input 8-bit 3-channel image. +@param dst Output image with the same size and type as src. +@param sigma_s %Range between 0 to 200. +@param sigma_r %Range between 0 to 1. + */ +CV_EXPORTS_W void stylization(InputArray src, OutputArray dst, float sigma_s = 60, + float sigma_r = 0.45f); + +//! @} photo_render + +//! @} photo + +} // cv + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/photo/photo_c.h" +#endif + +#endif diff --git a/3rdparty/opencv/include/opencv2/photo/cuda.hpp b/3rdparty/opencv/include/opencv2/photo/cuda.hpp new file mode 100644 index 00000000..a2f38167 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/photo/cuda.hpp @@ -0,0 +1,132 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_PHOTO_CUDA_HPP +#define OPENCV_PHOTO_CUDA_HPP + +#include "opencv2/core/cuda.hpp" + +namespace cv { namespace cuda { + +//! @addtogroup photo_denoise +//! @{ + +/** @brief Performs pure non local means denoising without any simplification, and thus it is not fast. + +@param src Source image. Supports only CV_8UC1, CV_8UC2 and CV_8UC3. +@param dst Destination image. +@param h Filter sigma regulating filter strength for color. +@param search_window Size of search window. +@param block_size Size of block used for computing weights. +@param borderMode Border type. See borderInterpolate for details. BORDER_REFLECT101 , +BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now. +@param stream Stream for the asynchronous version. + +@sa + fastNlMeansDenoising + */ +CV_EXPORTS void nonLocalMeans(InputArray src, OutputArray dst, + float h, + int search_window = 21, + int block_size = 7, + int borderMode = BORDER_DEFAULT, + Stream& stream = Stream::Null()); + +/** @brief Perform image denoising using Non-local Means Denoising algorithm + with several computational +optimizations. Noise expected to be a gaussian white noise + +@param src Input 8-bit 1-channel, 2-channel or 3-channel image. +@param dst Output image with the same size and type as src . +@param h Parameter regulating filter strength. Big h value perfectly removes noise but also +removes image details, smaller h value preserves details but also preserves some noise +@param search_window Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater search_window - greater +denoising time. Recommended value 21 pixels +@param block_size Size in pixels of the template patch that is used to compute weights. Should be +odd. Recommended value 7 pixels +@param stream Stream for the asynchronous invocations. + +This function expected to be applied to grayscale images. For colored images look at +FastNonLocalMeansDenoising::labMethod. + +@sa + fastNlMeansDenoising + */ +CV_EXPORTS void fastNlMeansDenoising(InputArray src, OutputArray dst, + float h, + int search_window = 21, + int block_size = 7, + Stream& stream = Stream::Null()); + +/** @brief Modification of fastNlMeansDenoising function for colored images + +@param src Input 8-bit 3-channel image. +@param dst Output image with the same size and type as src . +@param h_luminance Parameter regulating filter strength. Big h value perfectly removes noise but +also removes image details, smaller h value preserves details but also preserves some noise +@param photo_render float The same as h but for color components. For most images value equals 10 will be +enough to remove colored noise and do not distort colors +@param search_window Size in pixels of the window that is used to compute weighted average for +given pixel. Should be odd. Affect performance linearly: greater search_window - greater +denoising time. Recommended value 21 pixels +@param block_size Size in pixels of the template patch that is used to compute weights. Should be +odd. Recommended value 7 pixels +@param stream Stream for the asynchronous invocations. + +The function converts image to CIELAB colorspace and then separately denoise L and AB components +with given h parameters using FastNonLocalMeansDenoising::simpleMethod function. + +@sa + fastNlMeansDenoisingColored + */ +CV_EXPORTS void fastNlMeansDenoisingColored(InputArray src, OutputArray dst, + float h_luminance, float photo_render, + int search_window = 21, + int block_size = 7, + Stream& stream = Stream::Null()); + +//! @} photo + +}} // namespace cv { namespace cuda { + +#endif /* OPENCV_PHOTO_CUDA_HPP */ diff --git a/3rdparty/opencv/include/opencv2/photo/photo.hpp b/3rdparty/opencv/include/opencv2/photo/photo.hpp new file mode 100644 index 00000000..8af5e9f0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/photo/photo.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/photo.hpp" diff --git a/3rdparty/opencv/include/opencv2/photo/photo_c.h b/3rdparty/opencv/include/opencv2/photo/photo_c.h new file mode 100644 index 00000000..cd623c19 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/photo/photo_c.h @@ -0,0 +1,74 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_PHOTO_C_H +#define OPENCV_PHOTO_C_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup photo_c + @{ + */ + +/* Inpainting algorithms */ +enum InpaintingModes +{ + CV_INPAINT_NS =0, + CV_INPAINT_TELEA =1 +}; + + +/* Inpaints the selected region in the image */ +CVAPI(void) cvInpaint( const CvArr* src, const CvArr* inpaint_mask, + CvArr* dst, double inpaintRange, int flags ); + +/** @} */ + +#ifdef __cplusplus +} //extern "C" +#endif + +#endif //OPENCV_PHOTO_C_H diff --git a/3rdparty/opencv/include/opencv2/shape.hpp b/3rdparty/opencv/include/opencv2/shape.hpp new file mode 100644 index 00000000..f302b6bb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape.hpp @@ -0,0 +1,57 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2012, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_SHAPE_HPP +#define OPENCV_SHAPE_HPP + +#include "opencv2/shape/emdL1.hpp" +#include "opencv2/shape/shape_transformer.hpp" +#include "opencv2/shape/hist_cost.hpp" +#include "opencv2/shape/shape_distance.hpp" + +/** + @defgroup shape Shape Distance and Matching + */ + +#endif + +/* End of file. */ diff --git a/3rdparty/opencv/include/opencv2/shape/emdL1.hpp b/3rdparty/opencv/include/opencv2/shape/emdL1.hpp new file mode 100644 index 00000000..a15d68c2 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape/emdL1.hpp @@ -0,0 +1,72 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2012, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_EMD_L1_HPP +#define OPENCV_EMD_L1_HPP + +#include "opencv2/core.hpp" + +namespace cv +{ +/****************************************************************************************\ +* EMDL1 Function * +\****************************************************************************************/ + +//! @addtogroup shape +//! @{ + +/** @brief Computes the "minimal work" distance between two weighted point configurations base on the papers +"EMD-L1: An efficient and Robust Algorithm for comparing histogram-based descriptors", by Haibin +Ling and Kazunori Okuda; and "The Earth Mover's Distance is the Mallows Distance: Some Insights from +Statistics", by Elizaveta Levina and Peter Bickel. + +@param signature1 First signature, a single column floating-point matrix. Each row is the value of +the histogram in each bin. +@param signature2 Second signature of the same format and size as signature1. + */ +CV_EXPORTS float EMDL1(InputArray signature1, InputArray signature2); + +//! @} + +}//namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/shape/hist_cost.hpp b/3rdparty/opencv/include/opencv2/shape/hist_cost.hpp new file mode 100644 index 00000000..21d0d680 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape/hist_cost.hpp @@ -0,0 +1,111 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_HIST_COST_HPP +#define OPENCV_HIST_COST_HPP + +#include "opencv2/imgproc.hpp" + +namespace cv +{ + +//! @addtogroup shape +//! @{ + +/** @brief Abstract base class for histogram cost algorithms. + */ +class CV_EXPORTS_W HistogramCostExtractor : public Algorithm +{ +public: + CV_WRAP virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) = 0; + + CV_WRAP virtual void setNDummies(int nDummies) = 0; + CV_WRAP virtual int getNDummies() const = 0; + + CV_WRAP virtual void setDefaultCost(float defaultCost) = 0; + CV_WRAP virtual float getDefaultCost() const = 0; +}; + +/** @brief A norm based cost extraction. : + */ +class CV_EXPORTS_W NormHistogramCostExtractor : public HistogramCostExtractor +{ +public: + CV_WRAP virtual void setNormFlag(int flag) = 0; + CV_WRAP virtual int getNormFlag() const = 0; +}; + +CV_EXPORTS_W Ptr + createNormHistogramCostExtractor(int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f); + +/** @brief An EMD based cost extraction. : + */ +class CV_EXPORTS_W EMDHistogramCostExtractor : public HistogramCostExtractor +{ +public: + CV_WRAP virtual void setNormFlag(int flag) = 0; + CV_WRAP virtual int getNormFlag() const = 0; +}; + +CV_EXPORTS_W Ptr + createEMDHistogramCostExtractor(int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f); + +/** @brief An Chi based cost extraction. : + */ +class CV_EXPORTS_W ChiHistogramCostExtractor : public HistogramCostExtractor +{}; + +CV_EXPORTS_W Ptr createChiHistogramCostExtractor(int nDummies=25, float defaultCost=0.2f); + +/** @brief An EMD-L1 based cost extraction. : + */ +class CV_EXPORTS_W EMDL1HistogramCostExtractor : public HistogramCostExtractor +{}; + +CV_EXPORTS_W Ptr + createEMDL1HistogramCostExtractor(int nDummies=25, float defaultCost=0.2f); + +//! @} + +} // cv +#endif diff --git a/3rdparty/opencv/include/opencv2/shape/shape.hpp b/3rdparty/opencv/include/opencv2/shape/shape.hpp new file mode 100644 index 00000000..5c4da3ce --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape/shape.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/shape.hpp" diff --git a/3rdparty/opencv/include/opencv2/shape/shape_distance.hpp b/3rdparty/opencv/include/opencv2/shape/shape_distance.hpp new file mode 100644 index 00000000..725b56ac --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape/shape_distance.hpp @@ -0,0 +1,227 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_SHAPE_SHAPE_DISTANCE_HPP +#define OPENCV_SHAPE_SHAPE_DISTANCE_HPP +#include "opencv2/core.hpp" +#include "opencv2/shape/hist_cost.hpp" +#include "opencv2/shape/shape_transformer.hpp" + +namespace cv +{ + +//! @addtogroup shape +//! @{ + +/** @example samples/cpp/shape_example.cpp +An example using shape distance algorithm +*/ +/** @brief Abstract base class for shape distance algorithms. + */ +class CV_EXPORTS_W ShapeDistanceExtractor : public Algorithm +{ +public: + /** @brief Compute the shape distance between two shapes defined by its contours. + + @param contour1 Contour defining first shape. + @param contour2 Contour defining second shape. + */ + CV_WRAP virtual float computeDistance(InputArray contour1, InputArray contour2) = 0; +}; + +/***********************************************************************************/ +/***********************************************************************************/ +/***********************************************************************************/ +/** @brief Implementation of the Shape Context descriptor and matching algorithm + +proposed by Belongie et al. in "Shape Matching and Object Recognition Using Shape Contexts" (PAMI +2002). This implementation is packaged in a generic scheme, in order to allow you the +implementation of the common variations of the original pipeline. +*/ +class CV_EXPORTS_W ShapeContextDistanceExtractor : public ShapeDistanceExtractor +{ +public: + /** @brief Establish the number of angular bins for the Shape Context Descriptor used in the shape matching + pipeline. + + @param nAngularBins The number of angular bins in the shape context descriptor. + */ + CV_WRAP virtual void setAngularBins(int nAngularBins) = 0; + CV_WRAP virtual int getAngularBins() const = 0; + + /** @brief Establish the number of radial bins for the Shape Context Descriptor used in the shape matching + pipeline. + + @param nRadialBins The number of radial bins in the shape context descriptor. + */ + CV_WRAP virtual void setRadialBins(int nRadialBins) = 0; + CV_WRAP virtual int getRadialBins() const = 0; + + /** @brief Set the inner radius of the shape context descriptor. + + @param innerRadius The value of the inner radius. + */ + CV_WRAP virtual void setInnerRadius(float innerRadius) = 0; + CV_WRAP virtual float getInnerRadius() const = 0; + + /** @brief Set the outer radius of the shape context descriptor. + + @param outerRadius The value of the outer radius. + */ + CV_WRAP virtual void setOuterRadius(float outerRadius) = 0; + CV_WRAP virtual float getOuterRadius() const = 0; + + CV_WRAP virtual void setRotationInvariant(bool rotationInvariant) = 0; + CV_WRAP virtual bool getRotationInvariant() const = 0; + + /** @brief Set the weight of the shape context distance in the final value of the shape distance. The shape + context distance between two shapes is defined as the symmetric sum of shape context matching costs + over best matching points. The final value of the shape distance is a user-defined linear + combination of the shape context distance, an image appearance distance, and a bending energy. + + @param shapeContextWeight The weight of the shape context distance in the final distance value. + */ + CV_WRAP virtual void setShapeContextWeight(float shapeContextWeight) = 0; + CV_WRAP virtual float getShapeContextWeight() const = 0; + + /** @brief Set the weight of the Image Appearance cost in the final value of the shape distance. The image + appearance cost is defined as the sum of squared brightness differences in Gaussian windows around + corresponding image points. The final value of the shape distance is a user-defined linear + combination of the shape context distance, an image appearance distance, and a bending energy. If + this value is set to a number different from 0, is mandatory to set the images that correspond to + each shape. + + @param imageAppearanceWeight The weight of the appearance cost in the final distance value. + */ + CV_WRAP virtual void setImageAppearanceWeight(float imageAppearanceWeight) = 0; + CV_WRAP virtual float getImageAppearanceWeight() const = 0; + + /** @brief Set the weight of the Bending Energy in the final value of the shape distance. The bending energy + definition depends on what transformation is being used to align the shapes. The final value of the + shape distance is a user-defined linear combination of the shape context distance, an image + appearance distance, and a bending energy. + + @param bendingEnergyWeight The weight of the Bending Energy in the final distance value. + */ + CV_WRAP virtual void setBendingEnergyWeight(float bendingEnergyWeight) = 0; + CV_WRAP virtual float getBendingEnergyWeight() const = 0; + + /** @brief Set the images that correspond to each shape. This images are used in the calculation of the Image + Appearance cost. + + @param image1 Image corresponding to the shape defined by contours1. + @param image2 Image corresponding to the shape defined by contours2. + */ + CV_WRAP virtual void setImages(InputArray image1, InputArray image2) = 0; + CV_WRAP virtual void getImages(OutputArray image1, OutputArray image2) const = 0; + + CV_WRAP virtual void setIterations(int iterations) = 0; + CV_WRAP virtual int getIterations() const = 0; + + /** @brief Set the algorithm used for building the shape context descriptor cost matrix. + + @param comparer Smart pointer to a HistogramCostExtractor, an algorithm that defines the cost + matrix between descriptors. + */ + CV_WRAP virtual void setCostExtractor(Ptr comparer) = 0; + CV_WRAP virtual Ptr getCostExtractor() const = 0; + + /** @brief Set the value of the standard deviation for the Gaussian window for the image appearance cost. + + @param sigma Standard Deviation. + */ + CV_WRAP virtual void setStdDev(float sigma) = 0; + CV_WRAP virtual float getStdDev() const = 0; + + /** @brief Set the algorithm used for aligning the shapes. + + @param transformer Smart pointer to a ShapeTransformer, an algorithm that defines the aligning + transformation. + */ + CV_WRAP virtual void setTransformAlgorithm(Ptr transformer) = 0; + CV_WRAP virtual Ptr getTransformAlgorithm() const = 0; +}; + +/* Complete constructor */ +CV_EXPORTS_W Ptr + createShapeContextDistanceExtractor(int nAngularBins=12, int nRadialBins=4, + float innerRadius=0.2f, float outerRadius=2, int iterations=3, + const Ptr &comparer = createChiHistogramCostExtractor(), + const Ptr &transformer = createThinPlateSplineShapeTransformer()); + +/***********************************************************************************/ +/***********************************************************************************/ +/***********************************************************************************/ +/** @brief A simple Hausdorff distance measure between shapes defined by contours + +according to the paper "Comparing Images using the Hausdorff distance." by D.P. Huttenlocher, G.A. +Klanderman, and W.J. Rucklidge. (PAMI 1993). : + */ +class CV_EXPORTS_W HausdorffDistanceExtractor : public ShapeDistanceExtractor +{ +public: + /** @brief Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm. + + @param distanceFlag Flag indicating which norm is used to compute the Hausdorff distance + (NORM_L1, NORM_L2). + */ + CV_WRAP virtual void setDistanceFlag(int distanceFlag) = 0; + CV_WRAP virtual int getDistanceFlag() const = 0; + + /** @brief This method sets the rank proportion (or fractional value) that establish the Kth ranked value of + the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare + shapes. + + @param rankProportion fractional value (between 0 and 1). + */ + CV_WRAP virtual void setRankProportion(float rankProportion) = 0; + CV_WRAP virtual float getRankProportion() const = 0; +}; + +/* Constructor */ +CV_EXPORTS_W Ptr createHausdorffDistanceExtractor(int distanceFlag=cv::NORM_L2, float rankProp=0.6f); + +//! @} + +} // cv +#endif diff --git a/3rdparty/opencv/include/opencv2/shape/shape_transformer.hpp b/3rdparty/opencv/include/opencv2/shape/shape_transformer.hpp new file mode 100644 index 00000000..3c3ce20c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/shape/shape_transformer.hpp @@ -0,0 +1,132 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_SHAPE_SHAPE_TRANSFORM_HPP +#define OPENCV_SHAPE_SHAPE_TRANSFORM_HPP +#include +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" + +namespace cv +{ + +//! @addtogroup shape +//! @{ + +/** @brief Abstract base class for shape transformation algorithms. + */ +class CV_EXPORTS_W ShapeTransformer : public Algorithm +{ +public: + /** @brief Estimate the transformation parameters of the current transformer algorithm, based on point matches. + + @param transformingShape Contour defining first shape. + @param targetShape Contour defining second shape (Target). + @param matches Standard vector of Matches between points. + */ + CV_WRAP virtual void estimateTransformation(InputArray transformingShape, InputArray targetShape, + std::vector& matches) = 0; + + /** @brief Apply a transformation, given a pre-estimated transformation parameters. + + @param input Contour (set of points) to apply the transformation. + @param output Output contour. + */ + CV_WRAP virtual float applyTransformation(InputArray input, OutputArray output=noArray()) = 0; + + /** @brief Apply a transformation, given a pre-estimated transformation parameters, to an Image. + + @param transformingImage Input image. + @param output Output image. + @param flags Image interpolation method. + @param borderMode border style. + @param borderValue border value. + */ + CV_WRAP virtual void warpImage(InputArray transformingImage, OutputArray output, + int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, + const Scalar& borderValue=Scalar()) const = 0; +}; + +/***********************************************************************************/ +/***********************************************************************************/ + +/** @brief Definition of the transformation + +occupied in the paper "Principal Warps: Thin-Plate Splines and Decomposition of Deformations", by +F.L. Bookstein (PAMI 1989). : + */ +class CV_EXPORTS_W ThinPlateSplineShapeTransformer : public ShapeTransformer +{ +public: + /** @brief Set the regularization parameter for relaxing the exact interpolation requirements of the TPS + algorithm. + + @param beta value of the regularization parameter. + */ + CV_WRAP virtual void setRegularizationParameter(double beta) = 0; + CV_WRAP virtual double getRegularizationParameter() const = 0; +}; + +/** Complete constructor */ +CV_EXPORTS_W Ptr + createThinPlateSplineShapeTransformer(double regularizationParameter=0); + +/***********************************************************************************/ +/***********************************************************************************/ + +/** @brief Wrapper class for the OpenCV Affine Transformation algorithm. : + */ +class CV_EXPORTS_W AffineTransformer : public ShapeTransformer +{ +public: + CV_WRAP virtual void setFullAffine(bool fullAffine) = 0; + CV_WRAP virtual bool getFullAffine() const = 0; +}; + +/** Complete constructor */ +CV_EXPORTS_W Ptr createAffineTransformer(bool fullAffine); + +//! @} + +} // cv +#endif diff --git a/3rdparty/opencv/include/opencv2/stitching.hpp b/3rdparty/opencv/include/opencv2/stitching.hpp new file mode 100644 index 00000000..07e1b5f7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching.hpp @@ -0,0 +1,329 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_STITCHER_HPP +#define OPENCV_STITCHING_STITCHER_HPP + +#include "opencv2/core.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/stitching/warpers.hpp" +#include "opencv2/stitching/detail/matchers.hpp" +#include "opencv2/stitching/detail/motion_estimators.hpp" +#include "opencv2/stitching/detail/exposure_compensate.hpp" +#include "opencv2/stitching/detail/seam_finders.hpp" +#include "opencv2/stitching/detail/blenders.hpp" +#include "opencv2/stitching/detail/camera.hpp" + + +#if defined(Status) +# warning Detected X11 'Status' macro definition, it can cause build conflicts. Please, include this header before any X11 headers. +#endif + + +/** +@defgroup stitching Images stitching + +This figure illustrates the stitching module pipeline implemented in the Stitcher class. Using that +class it's possible to configure/remove some steps, i.e. adjust the stitching pipeline according to +the particular needs. All building blocks from the pipeline are available in the detail namespace, +one can combine and use them separately. + +The implemented stitching pipeline is very similar to the one proposed in @cite BL07 . + +![stitching pipeline](StitchingPipeline.jpg) + +Camera models +------------- + +There are currently 2 camera models implemented in stitching pipeline. + +- _Homography model_ expecting perspective transformations between images + implemented in @ref cv::detail::BestOf2NearestMatcher cv::detail::HomographyBasedEstimator + cv::detail::BundleAdjusterReproj cv::detail::BundleAdjusterRay +- _Affine model_ expecting affine transformation with 6 DOF or 4 DOF implemented in + @ref cv::detail::AffineBestOf2NearestMatcher cv::detail::AffineBasedEstimator + cv::detail::BundleAdjusterAffine cv::detail::BundleAdjusterAffinePartial cv::AffineWarper + +Homography model is useful for creating photo panoramas captured by camera, +while affine-based model can be used to stitch scans and object captured by +specialized devices. Use @ref cv::Stitcher::create to get preconfigured pipeline for one +of those models. + +@note +Certain detailed settings of @ref cv::Stitcher might not make sense. Especially +you should not mix classes implementing affine model and classes implementing +Homography model, as they work with different transformations. + +@{ + @defgroup stitching_match Features Finding and Images Matching + @defgroup stitching_rotation Rotation Estimation + @defgroup stitching_autocalib Autocalibration + @defgroup stitching_warp Images Warping + @defgroup stitching_seam Seam Estimation + @defgroup stitching_exposure Exposure Compensation + @defgroup stitching_blend Image Blenders +@} + */ + +namespace cv { + +//! @addtogroup stitching +//! @{ + +/** @example samples/cpp/stitching.cpp +A basic example on image stitching +*/ + +/** @example samples/cpp/stitching_detailed.cpp +A detailed example on image stitching +*/ + +/** @brief High level image stitcher. + +It's possible to use this class without being aware of the entire stitching pipeline. However, to +be able to achieve higher stitching stability and quality of the final images at least being +familiar with the theory is recommended. + +@note + - A basic example on image stitching can be found at + opencv_source_code/samples/cpp/stitching.cpp + - A detailed example on image stitching can be found at + opencv_source_code/samples/cpp/stitching_detailed.cpp + */ +class CV_EXPORTS_W Stitcher +{ +public: + enum { ORIG_RESOL = -1 }; + enum Status + { + OK = 0, + ERR_NEED_MORE_IMGS = 1, + ERR_HOMOGRAPHY_EST_FAIL = 2, + ERR_CAMERA_PARAMS_ADJUST_FAIL = 3 + }; + enum Mode + { + /** Mode for creating photo panoramas. Expects images under perspective + transformation and projects resulting pano to sphere. + + @sa detail::BestOf2NearestMatcher SphericalWarper + */ + PANORAMA = 0, + /** Mode for composing scans. Expects images under affine transformation does + not compensate exposure by default. + + @sa detail::AffineBestOf2NearestMatcher AffineWarper + */ + SCANS = 1, + + }; + + // Stitcher() {} + /** @brief Creates a stitcher with the default parameters. + + @param try_use_gpu Flag indicating whether GPU should be used whenever it's possible. + @return Stitcher class instance. + */ + static Stitcher createDefault(bool try_use_gpu = false); + /** @brief Creates a Stitcher configured in one of the stitching modes. + + @param mode Scenario for stitcher operation. This is usually determined by source of images + to stitch and their transformation. Default parameters will be chosen for operation in given + scenario. + @param try_use_gpu Flag indicating whether GPU should be used whenever it's possible. + @return Stitcher class instance. + */ + static Ptr create(Mode mode = PANORAMA, bool try_use_gpu = false); + + CV_WRAP double registrationResol() const { return registr_resol_; } + CV_WRAP void setRegistrationResol(double resol_mpx) { registr_resol_ = resol_mpx; } + + CV_WRAP double seamEstimationResol() const { return seam_est_resol_; } + CV_WRAP void setSeamEstimationResol(double resol_mpx) { seam_est_resol_ = resol_mpx; } + + CV_WRAP double compositingResol() const { return compose_resol_; } + CV_WRAP void setCompositingResol(double resol_mpx) { compose_resol_ = resol_mpx; } + + CV_WRAP double panoConfidenceThresh() const { return conf_thresh_; } + CV_WRAP void setPanoConfidenceThresh(double conf_thresh) { conf_thresh_ = conf_thresh; } + + CV_WRAP bool waveCorrection() const { return do_wave_correct_; } + CV_WRAP void setWaveCorrection(bool flag) { do_wave_correct_ = flag; } + + detail::WaveCorrectKind waveCorrectKind() const { return wave_correct_kind_; } + void setWaveCorrectKind(detail::WaveCorrectKind kind) { wave_correct_kind_ = kind; } + + Ptr featuresFinder() { return features_finder_; } + const Ptr featuresFinder() const { return features_finder_; } + void setFeaturesFinder(Ptr features_finder) + { features_finder_ = features_finder; } + + Ptr featuresMatcher() { return features_matcher_; } + const Ptr featuresMatcher() const { return features_matcher_; } + void setFeaturesMatcher(Ptr features_matcher) + { features_matcher_ = features_matcher; } + + const cv::UMat& matchingMask() const { return matching_mask_; } + void setMatchingMask(const cv::UMat &mask) + { + CV_Assert(mask.type() == CV_8U && mask.cols == mask.rows); + matching_mask_ = mask.clone(); + } + + Ptr bundleAdjuster() { return bundle_adjuster_; } + const Ptr bundleAdjuster() const { return bundle_adjuster_; } + void setBundleAdjuster(Ptr bundle_adjuster) + { bundle_adjuster_ = bundle_adjuster; } + + /* TODO OpenCV ABI 4.x + Ptr estimator() { return estimator_; } + const Ptr estimator() const { return estimator_; } + void setEstimator(Ptr estimator) + { estimator_ = estimator; } + */ + + Ptr warper() { return warper_; } + const Ptr warper() const { return warper_; } + void setWarper(Ptr creator) { warper_ = creator; } + + Ptr exposureCompensator() { return exposure_comp_; } + const Ptr exposureCompensator() const { return exposure_comp_; } + void setExposureCompensator(Ptr exposure_comp) + { exposure_comp_ = exposure_comp; } + + Ptr seamFinder() { return seam_finder_; } + const Ptr seamFinder() const { return seam_finder_; } + void setSeamFinder(Ptr seam_finder) { seam_finder_ = seam_finder; } + + Ptr blender() { return blender_; } + const Ptr blender() const { return blender_; } + void setBlender(Ptr b) { blender_ = b; } + + /** @overload */ + CV_WRAP Status estimateTransform(InputArrayOfArrays images); + /** @brief These functions try to match the given images and to estimate rotations of each camera. + + @note Use the functions only if you're aware of the stitching pipeline, otherwise use + Stitcher::stitch. + + @param images Input images. + @param rois Region of interest rectangles. + @return Status code. + */ + Status estimateTransform(InputArrayOfArrays images, const std::vector > &rois); + + /** @overload */ + CV_WRAP Status composePanorama(OutputArray pano); + /** @brief These functions try to compose the given images (or images stored internally from the other function + calls) into the final pano under the assumption that the image transformations were estimated + before. + + @note Use the functions only if you're aware of the stitching pipeline, otherwise use + Stitcher::stitch. + + @param images Input images. + @param pano Final pano. + @return Status code. + */ + Status composePanorama(InputArrayOfArrays images, OutputArray pano); + + /** @overload */ + CV_WRAP Status stitch(InputArrayOfArrays images, OutputArray pano); + /** @brief These functions try to stitch the given images. + + @param images Input images. + @param rois Region of interest rectangles. + @param pano Final pano. + @return Status code. + */ + Status stitch(InputArrayOfArrays images, const std::vector > &rois, OutputArray pano); + + std::vector component() const { return indices_; } + std::vector cameras() const { return cameras_; } + CV_WRAP double workScale() const { return work_scale_; } + +private: + //Stitcher() {} + + Status matchImages(); + Status estimateCameraParams(); + + double registr_resol_; + double seam_est_resol_; + double compose_resol_; + double conf_thresh_; + Ptr features_finder_; + Ptr features_matcher_; + cv::UMat matching_mask_; + Ptr bundle_adjuster_; + /* TODO OpenCV ABI 4.x + Ptr estimator_; + */ + bool do_wave_correct_; + detail::WaveCorrectKind wave_correct_kind_; + Ptr warper_; + Ptr exposure_comp_; + Ptr seam_finder_; + Ptr blender_; + + std::vector imgs_; + std::vector > rois_; + std::vector full_img_sizes_; + std::vector features_; + std::vector pairwise_matches_; + std::vector seam_est_imgs_; + std::vector indices_; + std::vector cameras_; + double work_scale_; + double seam_scale_; + double seam_work_aspect_; + double warped_image_scale_; +}; + +CV_EXPORTS_W Ptr createStitcher(bool try_use_gpu = false); +CV_EXPORTS_W Ptr createStitcherScans(bool try_use_gpu = false); + +//! @} stitching + +} // namespace cv + +#endif // OPENCV_STITCHING_STITCHER_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/autocalib.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/autocalib.hpp new file mode 100644 index 00000000..19705e27 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/autocalib.hpp @@ -0,0 +1,86 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_AUTOCALIB_HPP +#define OPENCV_STITCHING_AUTOCALIB_HPP + +#include "opencv2/core.hpp" +#include "matchers.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_autocalib +//! @{ + +/** @brief Tries to estimate focal lengths from the given homography under the assumption that the camera +undergoes rotations around its centre only. + +@param H Homography. +@param f0 Estimated focal length along X axis. +@param f1 Estimated focal length along Y axis. +@param f0_ok True, if f0 was estimated successfully, false otherwise. +@param f1_ok True, if f1 was estimated successfully, false otherwise. + +See "Construction of Panoramic Image Mosaics with Global and Local Alignment" +by Heung-Yeung Shum and Richard Szeliski. + */ +void CV_EXPORTS focalsFromHomography(const Mat &H, double &f0, double &f1, bool &f0_ok, bool &f1_ok); + +/** @brief Estimates focal lengths for each given camera. + +@param features Features of images. +@param pairwise_matches Matches between all image pairs. +@param focals Estimated focal lengths for each camera. + */ +void CV_EXPORTS estimateFocal(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &focals); + +bool CV_EXPORTS calibrateRotatingCamera(const std::vector &Hs, Mat &K); + +//! @} stitching_autocalib + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_AUTOCALIB_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/blenders.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/blenders.hpp new file mode 100644 index 00000000..542f1e42 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/blenders.hpp @@ -0,0 +1,184 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_BLENDERS_HPP +#define OPENCV_STITCHING_BLENDERS_HPP + +#if defined(NO) +# warning Detected Apple 'NO' macro definition, it can cause build conflicts. Please, include this header before any Apple headers. +#endif + +#include "opencv2/core.hpp" +#include "opencv2/core/cuda.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_blend +//! @{ + +/** @brief Base class for all blenders. + +Simple blender which puts one image over another +*/ +class CV_EXPORTS Blender +{ +public: + virtual ~Blender() {} + + enum { NO, FEATHER, MULTI_BAND }; + static Ptr createDefault(int type, bool try_gpu = false); + + /** @brief Prepares the blender for blending. + + @param corners Source images top-left corners + @param sizes Source image sizes + */ + void prepare(const std::vector &corners, const std::vector &sizes); + /** @overload */ + virtual void prepare(Rect dst_roi); + /** @brief Processes the image. + + @param img Source image + @param mask Source image mask + @param tl Source image top-left corners + */ + virtual void feed(InputArray img, InputArray mask, Point tl); + /** @brief Blends and returns the final pano. + + @param dst Final pano + @param dst_mask Final pano mask + */ + virtual void blend(InputOutputArray dst, InputOutputArray dst_mask); + +protected: + UMat dst_, dst_mask_; + Rect dst_roi_; +}; + +/** @brief Simple blender which mixes images at its borders. + */ +class CV_EXPORTS FeatherBlender : public Blender +{ +public: + FeatherBlender(float sharpness = 0.02f); + + float sharpness() const { return sharpness_; } + void setSharpness(float val) { sharpness_ = val; } + + void prepare(Rect dst_roi) CV_OVERRIDE; + void feed(InputArray img, InputArray mask, Point tl) CV_OVERRIDE; + void blend(InputOutputArray dst, InputOutputArray dst_mask) CV_OVERRIDE; + + //! Creates weight maps for fixed set of source images by their masks and top-left corners. + //! Final image can be obtained by simple weighting of the source images. + Rect createWeightMaps(const std::vector &masks, const std::vector &corners, + std::vector &weight_maps); + +private: + float sharpness_; + UMat weight_map_; + UMat dst_weight_map_; +}; + +inline FeatherBlender::FeatherBlender(float _sharpness) { setSharpness(_sharpness); } + +/** @brief Blender which uses multi-band blending algorithm (see @cite BA83). + */ +class CV_EXPORTS MultiBandBlender : public Blender +{ +public: + MultiBandBlender(int try_gpu = false, int num_bands = 5, int weight_type = CV_32F); + + int numBands() const { return actual_num_bands_; } + void setNumBands(int val) { actual_num_bands_ = val; } + + void prepare(Rect dst_roi) CV_OVERRIDE; + void feed(InputArray img, InputArray mask, Point tl) CV_OVERRIDE; + void blend(InputOutputArray dst, InputOutputArray dst_mask) CV_OVERRIDE; + +private: + int actual_num_bands_, num_bands_; + std::vector dst_pyr_laplace_; + std::vector dst_band_weights_; + Rect dst_roi_final_; + bool can_use_gpu_; + int weight_type_; //CV_32F or CV_16S +#if defined(HAVE_OPENCV_CUDAARITHM) && defined(HAVE_OPENCV_CUDAWARPING) + std::vector gpu_dst_pyr_laplace_; + std::vector gpu_dst_band_weights_; + std::vector gpu_tl_points_; + std::vector gpu_imgs_with_border_; + std::vector > gpu_weight_pyr_gauss_vec_; + std::vector > gpu_src_pyr_laplace_vec_; + std::vector > gpu_ups_; + cuda::GpuMat gpu_dst_mask_; + cuda::GpuMat gpu_mask_; + cuda::GpuMat gpu_img_; + cuda::GpuMat gpu_weight_map_; + cuda::GpuMat gpu_add_mask_; + int gpu_feed_idx_; + bool gpu_initialized_; +#endif +}; + + +////////////////////////////////////////////////////////////////////////////// +// Auxiliary functions + +void CV_EXPORTS normalizeUsingWeightMap(InputArray weight, InputOutputArray src); + +void CV_EXPORTS createWeightMap(InputArray mask, float sharpness, InputOutputArray weight); + +void CV_EXPORTS createLaplacePyr(InputArray img, int num_levels, std::vector& pyr); +void CV_EXPORTS createLaplacePyrGpu(InputArray img, int num_levels, std::vector& pyr); + +// Restores source image +void CV_EXPORTS restoreImageFromLaplacePyr(std::vector& pyr); +void CV_EXPORTS restoreImageFromLaplacePyrGpu(std::vector& pyr); + +//! @} + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_BLENDERS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/camera.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/camera.hpp new file mode 100644 index 00000000..07c6b5b0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/camera.hpp @@ -0,0 +1,78 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_CAMERA_HPP +#define OPENCV_STITCHING_CAMERA_HPP + +#include "opencv2/core.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching +//! @{ + +/** @brief Describes camera parameters. + +@note Translation is assumed to be zero during the whole stitching pipeline. : + */ +struct CV_EXPORTS CameraParams +{ + CameraParams(); + CameraParams(const CameraParams& other); + CameraParams& operator =(const CameraParams& other); + Mat K() const; + + double focal; // Focal length + double aspect; // Aspect ratio + double ppx; // Principal point X + double ppy; // Principal point Y + Mat R; // Rotation + Mat t; // Translation +}; + +//! @} + +} // namespace detail +} // namespace cv + +#endif // #ifndef OPENCV_STITCHING_CAMERA_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/exposure_compensate.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/exposure_compensate.hpp new file mode 100644 index 00000000..6c99407c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/exposure_compensate.hpp @@ -0,0 +1,136 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP +#define OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP + +#if defined(NO) +# warning Detected Apple 'NO' macro definition, it can cause build conflicts. Please, include this header before any Apple headers. +#endif + +#include "opencv2/core.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_exposure +//! @{ + +/** @brief Base class for all exposure compensators. + */ +class CV_EXPORTS ExposureCompensator +{ +public: + virtual ~ExposureCompensator() {} + + enum { NO, GAIN, GAIN_BLOCKS }; + static Ptr createDefault(int type); + + /** + @param corners Source image top-left corners + @param images Source images + @param masks Image masks to update (second value in pair specifies the value which should be used + to detect where image is) + */ + void feed(const std::vector &corners, const std::vector &images, + const std::vector &masks); + /** @overload */ + virtual void feed(const std::vector &corners, const std::vector &images, + const std::vector > &masks) = 0; + /** @brief Compensate exposure in the specified image. + + @param index Image index + @param corner Image top-left corner + @param image Image to process + @param mask Image mask + */ + virtual void apply(int index, Point corner, InputOutputArray image, InputArray mask) = 0; +}; + +/** @brief Stub exposure compensator which does nothing. + */ +class CV_EXPORTS NoExposureCompensator : public ExposureCompensator +{ +public: + void feed(const std::vector &/*corners*/, const std::vector &/*images*/, + const std::vector > &/*masks*/) CV_OVERRIDE { } + void apply(int /*index*/, Point /*corner*/, InputOutputArray /*image*/, InputArray /*mask*/) CV_OVERRIDE { } +}; + +/** @brief Exposure compensator which tries to remove exposure related artifacts by adjusting image +intensities, see @cite BL07 and @cite WJ10 for details. + */ +class CV_EXPORTS GainCompensator : public ExposureCompensator +{ +public: + void feed(const std::vector &corners, const std::vector &images, + const std::vector > &masks) CV_OVERRIDE; + void apply(int index, Point corner, InputOutputArray image, InputArray mask) CV_OVERRIDE; + std::vector gains() const; + +private: + Mat_ gains_; +}; + +/** @brief Exposure compensator which tries to remove exposure related artifacts by adjusting image block +intensities, see @cite UES01 for details. + */ +class CV_EXPORTS BlocksGainCompensator : public ExposureCompensator +{ +public: + BlocksGainCompensator(int bl_width = 32, int bl_height = 32) + : bl_width_(bl_width), bl_height_(bl_height) {} + void feed(const std::vector &corners, const std::vector &images, + const std::vector > &masks) CV_OVERRIDE; + void apply(int index, Point corner, InputOutputArray image, InputArray mask) CV_OVERRIDE; + +private: + int bl_width_, bl_height_; + std::vector gain_maps_; +}; + +//! @} + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/matchers.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/matchers.hpp new file mode 100644 index 00000000..25c0f2ab --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/matchers.hpp @@ -0,0 +1,370 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_MATCHERS_HPP +#define OPENCV_STITCHING_MATCHERS_HPP + +#include "opencv2/core.hpp" +#include "opencv2/features2d.hpp" + +#include "opencv2/opencv_modules.hpp" + +#ifdef HAVE_OPENCV_XFEATURES2D +# include "opencv2/xfeatures2d/cuda.hpp" +#endif + +namespace cv { +namespace detail { + +//! @addtogroup stitching_match +//! @{ + +/** @brief Structure containing image keypoints and descriptors. */ +struct CV_EXPORTS ImageFeatures +{ + int img_idx; + Size img_size; + std::vector keypoints; + UMat descriptors; +}; + +/** @brief Feature finders base class */ +class CV_EXPORTS FeaturesFinder +{ +public: + virtual ~FeaturesFinder() {} + /** @overload */ + void operator ()(InputArray image, ImageFeatures &features); + /** @brief Finds features in the given image. + + @param image Source image + @param features Found features + @param rois Regions of interest + + @sa detail::ImageFeatures, Rect_ + */ + void operator ()(InputArray image, ImageFeatures &features, const std::vector &rois); + /** @brief Finds features in the given images in parallel. + + @param images Source images + @param features Found features for each image + @param rois Regions of interest for each image + + @sa detail::ImageFeatures, Rect_ + */ + void operator ()(InputArrayOfArrays images, std::vector &features, + const std::vector > &rois); + /** @overload */ + void operator ()(InputArrayOfArrays images, std::vector &features); + /** @brief Frees unused memory allocated before if there is any. */ + virtual void collectGarbage() {} + + /* TODO OpenCV ABI 4.x + reimplement this as public method similar to FeaturesMatcher and remove private function hack + @return True, if it's possible to use the same finder instance in parallel, false otherwise + bool isThreadSafe() const { return is_thread_safe_; } + */ + +protected: + /** @brief This method must implement features finding logic in order to make the wrappers + detail::FeaturesFinder::operator()_ work. + + @param image Source image + @param features Found features + + @sa detail::ImageFeatures */ + virtual void find(InputArray image, ImageFeatures &features) = 0; + /** @brief uses dynamic_cast to determine thread-safety + @return True, if it's possible to use the same finder instance in parallel, false otherwise + */ + bool isThreadSafe() const; +}; + +/** @brief SURF features finder. + +@sa detail::FeaturesFinder, SURF +*/ +class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder +{ +public: + SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4, + int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4); + +private: + void find(InputArray image, ImageFeatures &features) CV_OVERRIDE; + + Ptr detector_; + Ptr extractor_; + Ptr surf; +}; + + +/** @brief SIFT features finder. + +@sa detail::FeaturesFinder, SIFT +*/ +class CV_EXPORTS SiftFeaturesFinder : public FeaturesFinder +{ +public: + SiftFeaturesFinder(); + +private: + void find(InputArray image, ImageFeatures &features) CV_OVERRIDE; + Ptr sift; +}; + +/** @brief ORB features finder. : + +@sa detail::FeaturesFinder, ORB +*/ +class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder +{ +public: + OrbFeaturesFinder(Size _grid_size = Size(3,1), int nfeatures=1500, float scaleFactor=1.3f, int nlevels=5); + +private: + void find(InputArray image, ImageFeatures &features) CV_OVERRIDE; + + Ptr orb; + Size grid_size; +}; + +/** @brief AKAZE features finder. : + +@sa detail::FeaturesFinder, AKAZE +*/ +class CV_EXPORTS AKAZEFeaturesFinder : public detail::FeaturesFinder +{ +public: + AKAZEFeaturesFinder(int descriptor_type = AKAZE::DESCRIPTOR_MLDB, + int descriptor_size = 0, + int descriptor_channels = 3, + float threshold = 0.001f, + int nOctaves = 4, + int nOctaveLayers = 4, + int diffusivity = KAZE::DIFF_PM_G2); + +private: + void find(InputArray image, ImageFeatures &features) CV_OVERRIDE; + + Ptr akaze; +}; + +#ifdef HAVE_OPENCV_XFEATURES2D +class CV_EXPORTS SurfFeaturesFinderGpu : public FeaturesFinder +{ +public: + SurfFeaturesFinderGpu(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4, + int num_octaves_descr = 4, int num_layers_descr = 2); + + void collectGarbage() CV_OVERRIDE; + +private: + void find(InputArray image, ImageFeatures &features) CV_OVERRIDE; + + cuda::GpuMat image_; + cuda::GpuMat gray_image_; + cuda::SURF_CUDA surf_; + cuda::GpuMat keypoints_; + cuda::GpuMat descriptors_; + int num_octaves_, num_layers_; + int num_octaves_descr_, num_layers_descr_; +}; +#endif + +/** @brief Structure containing information about matches between two images. + +It's assumed that there is a transformation between those images. Transformation may be +homography or affine transformation based on selected matcher. + +@sa detail::FeaturesMatcher +*/ +struct CV_EXPORTS MatchesInfo +{ + MatchesInfo(); + MatchesInfo(const MatchesInfo &other); + MatchesInfo& operator =(const MatchesInfo &other); + + int src_img_idx, dst_img_idx; //!< Images indices (optional) + std::vector matches; + std::vector inliers_mask; //!< Geometrically consistent matches mask + int num_inliers; //!< Number of geometrically consistent matches + Mat H; //!< Estimated transformation + double confidence; //!< Confidence two images are from the same panorama +}; + +/** @brief Feature matchers base class. */ +class CV_EXPORTS FeaturesMatcher +{ +public: + virtual ~FeaturesMatcher() {} + + /** @overload + @param features1 First image features + @param features2 Second image features + @param matches_info Found matches + */ + void operator ()(const ImageFeatures &features1, const ImageFeatures &features2, + MatchesInfo& matches_info) { match(features1, features2, matches_info); } + + /** @brief Performs images matching. + + @param features Features of the source images + @param pairwise_matches Found pairwise matches + @param mask Mask indicating which image pairs must be matched + + The function is parallelized with the TBB library. + + @sa detail::MatchesInfo + */ + void operator ()(const std::vector &features, std::vector &pairwise_matches, + const cv::UMat &mask = cv::UMat()); + + /** @return True, if it's possible to use the same matcher instance in parallel, false otherwise + */ + bool isThreadSafe() const { return is_thread_safe_; } + + /** @brief Frees unused memory allocated before if there is any. + */ + virtual void collectGarbage() {} + +protected: + FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {} + + /** @brief This method must implement matching logic in order to make the wrappers + detail::FeaturesMatcher::operator()_ work. + + @param features1 first image features + @param features2 second image features + @param matches_info found matches + */ + virtual void match(const ImageFeatures &features1, const ImageFeatures &features2, + MatchesInfo& matches_info) = 0; + + bool is_thread_safe_; +}; + +/** @brief Features matcher which finds two best matches for each feature and leaves the best one only if the +ratio between descriptor distances is greater than the threshold match_conf + +@sa detail::FeaturesMatcher + */ +class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher +{ +public: + /** @brief Constructs a "best of 2 nearest" matcher. + + @param try_use_gpu Should try to use GPU or not + @param match_conf Match distances ration threshold + @param num_matches_thresh1 Minimum number of matches required for the 2D projective transform + estimation used in the inliers classification step + @param num_matches_thresh2 Minimum number of matches required for the 2D projective transform + re-estimation on inliers + */ + BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.3f, int num_matches_thresh1 = 6, + int num_matches_thresh2 = 6); + + void collectGarbage() CV_OVERRIDE; + +protected: + void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info) CV_OVERRIDE; + + int num_matches_thresh1_; + int num_matches_thresh2_; + Ptr impl_; +}; + +class CV_EXPORTS BestOf2NearestRangeMatcher : public BestOf2NearestMatcher +{ +public: + BestOf2NearestRangeMatcher(int range_width = 5, bool try_use_gpu = false, float match_conf = 0.3f, + int num_matches_thresh1 = 6, int num_matches_thresh2 = 6); + + void operator ()(const std::vector &features, std::vector &pairwise_matches, + const cv::UMat &mask = cv::UMat()); + + +protected: + int range_width_; +}; + +/** @brief Features matcher similar to cv::detail::BestOf2NearestMatcher which +finds two best matches for each feature and leaves the best one only if the +ratio between descriptor distances is greater than the threshold match_conf. + +Unlike cv::detail::BestOf2NearestMatcher this matcher uses affine +transformation (affine trasformation estimate will be placed in matches_info). + +@sa cv::detail::FeaturesMatcher cv::detail::BestOf2NearestMatcher + */ +class CV_EXPORTS AffineBestOf2NearestMatcher : public BestOf2NearestMatcher +{ +public: + /** @brief Constructs a "best of 2 nearest" matcher that expects affine trasformation + between images + + @param full_affine whether to use full affine transformation with 6 degress of freedom or reduced + transformation with 4 degrees of freedom using only rotation, translation and uniform scaling + @param try_use_gpu Should try to use GPU or not + @param match_conf Match distances ration threshold + @param num_matches_thresh1 Minimum number of matches required for the 2D affine transform + estimation used in the inliers classification step + + @sa cv::estimateAffine2D cv::estimateAffinePartial2D + */ + AffineBestOf2NearestMatcher(bool full_affine = false, bool try_use_gpu = false, + float match_conf = 0.3f, int num_matches_thresh1 = 6) : + BestOf2NearestMatcher(try_use_gpu, match_conf, num_matches_thresh1, num_matches_thresh1), + full_affine_(full_affine) {} + +protected: + void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info) CV_OVERRIDE; + + bool full_affine_; +}; + +//! @} stitching_match + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_MATCHERS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/motion_estimators.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/motion_estimators.hpp new file mode 100644 index 00000000..40f12c32 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/motion_estimators.hpp @@ -0,0 +1,359 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_MOTION_ESTIMATORS_HPP +#define OPENCV_STITCHING_MOTION_ESTIMATORS_HPP + +#include "opencv2/core.hpp" +#include "matchers.hpp" +#include "util.hpp" +#include "camera.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_rotation +//! @{ + +/** @brief Rotation estimator base class. + +It takes features of all images, pairwise matches between all images and estimates rotations of all +cameras. + +@note The coordinate system origin is implementation-dependent, but you can always normalize the +rotations in respect to the first camera, for instance. : + */ +class CV_EXPORTS Estimator +{ +public: + virtual ~Estimator() {} + + /** @brief Estimates camera parameters. + + @param features Features of images + @param pairwise_matches Pairwise matches of images + @param cameras Estimated camera parameters + @return True in case of success, false otherwise + */ + bool operator ()(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &cameras) + { return estimate(features, pairwise_matches, cameras); } + +protected: + /** @brief This method must implement camera parameters estimation logic in order to make the wrapper + detail::Estimator::operator()_ work. + + @param features Features of images + @param pairwise_matches Pairwise matches of images + @param cameras Estimated camera parameters + @return True in case of success, false otherwise + */ + virtual bool estimate(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &cameras) = 0; +}; + +/** @brief Homography based rotation estimator. + */ +class CV_EXPORTS HomographyBasedEstimator : public Estimator +{ +public: + HomographyBasedEstimator(bool is_focals_estimated = false) + : is_focals_estimated_(is_focals_estimated) {} + +private: + virtual bool estimate(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &cameras) CV_OVERRIDE; + + bool is_focals_estimated_; +}; + +/** @brief Affine transformation based estimator. + +This estimator uses pairwise transformations estimated by matcher to estimate +final transformation for each camera. + +@sa cv::detail::HomographyBasedEstimator + */ +class CV_EXPORTS AffineBasedEstimator : public Estimator +{ +private: + virtual bool estimate(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &cameras) CV_OVERRIDE; +}; + +/** @brief Base class for all camera parameters refinement methods. + */ +class CV_EXPORTS BundleAdjusterBase : public Estimator +{ +public: + const Mat refinementMask() const { return refinement_mask_.clone(); } + void setRefinementMask(const Mat &mask) + { + CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3)); + refinement_mask_ = mask.clone(); + } + + double confThresh() const { return conf_thresh_; } + void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; } + + TermCriteria termCriteria() { return term_criteria_; } + void setTermCriteria(const TermCriteria& term_criteria) { term_criteria_ = term_criteria; } + +protected: + /** @brief Construct a bundle adjuster base instance. + + @param num_params_per_cam Number of parameters per camera + @param num_errs_per_measurement Number of error terms (components) per match + */ + BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement) + : num_images_(0), total_num_matches_(0), + num_params_per_cam_(num_params_per_cam), + num_errs_per_measurement_(num_errs_per_measurement), + features_(0), pairwise_matches_(0), conf_thresh_(0) + { + setRefinementMask(Mat::ones(3, 3, CV_8U)); + setConfThresh(1.); + setTermCriteria(TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 1000, DBL_EPSILON)); + } + + // Runs bundle adjustment + virtual bool estimate(const std::vector &features, + const std::vector &pairwise_matches, + std::vector &cameras) CV_OVERRIDE; + + /** @brief Sets initial camera parameter to refine. + + @param cameras Camera parameters + */ + virtual void setUpInitialCameraParams(const std::vector &cameras) = 0; + /** @brief Gets the refined camera parameters. + + @param cameras Refined camera parameters + */ + virtual void obtainRefinedCameraParams(std::vector &cameras) const = 0; + /** @brief Calculates error vector. + + @param err Error column-vector of length total_num_matches \* num_errs_per_measurement + */ + virtual void calcError(Mat &err) = 0; + /** @brief Calculates the cost function jacobian. + + @param jac Jacobian matrix of dimensions + (total_num_matches \* num_errs_per_measurement) x (num_images \* num_params_per_cam) + */ + virtual void calcJacobian(Mat &jac) = 0; + + // 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine + Mat refinement_mask_; + + int num_images_; + int total_num_matches_; + + int num_params_per_cam_; + int num_errs_per_measurement_; + + const ImageFeatures *features_; + const MatchesInfo *pairwise_matches_; + + // Threshold to filter out poorly matched image pairs + double conf_thresh_; + + //Levenberg-Marquardt algorithm termination criteria + TermCriteria term_criteria_; + + // Camera parameters matrix (CV_64F) + Mat cam_params_; + + // Connected images pairs + std::vector > edges_; +}; + + +/** @brief Stub bundle adjuster that does nothing. + */ +class CV_EXPORTS NoBundleAdjuster : public BundleAdjusterBase +{ +public: + NoBundleAdjuster() : BundleAdjusterBase(0, 0) {} + +private: + bool estimate(const std::vector &, const std::vector &, + std::vector &) CV_OVERRIDE + { + return true; + } + void setUpInitialCameraParams(const std::vector &) CV_OVERRIDE {} + void obtainRefinedCameraParams(std::vector &) const CV_OVERRIDE {} + void calcError(Mat &) CV_OVERRIDE {} + void calcJacobian(Mat &) CV_OVERRIDE {} +}; + + +/** @brief Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection +error squares + +It can estimate focal length, aspect ratio, principal point. +You can affect only on them via the refinement mask. + */ +class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase +{ +public: + BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {} + +private: + void setUpInitialCameraParams(const std::vector &cameras) CV_OVERRIDE; + void obtainRefinedCameraParams(std::vector &cameras) const CV_OVERRIDE; + void calcError(Mat &err) CV_OVERRIDE; + void calcJacobian(Mat &jac) CV_OVERRIDE; + + Mat err1_, err2_; +}; + + +/** @brief Implementation of the camera parameters refinement algorithm which minimizes sum of the distances +between the rays passing through the camera center and a feature. : + +It can estimate focal length. It ignores the refinement mask for now. + */ +class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase +{ +public: + BundleAdjusterRay() : BundleAdjusterBase(4, 3) {} + +private: + void setUpInitialCameraParams(const std::vector &cameras) CV_OVERRIDE; + void obtainRefinedCameraParams(std::vector &cameras) const CV_OVERRIDE; + void calcError(Mat &err) CV_OVERRIDE; + void calcJacobian(Mat &jac) CV_OVERRIDE; + + Mat err1_, err2_; +}; + + +/** @brief Bundle adjuster that expects affine transformation +represented in homogeneous coordinates in R for each camera param. Implements +camera parameters refinement algorithm which minimizes sum of the reprojection +error squares + +It estimates all transformation parameters. Refinement mask is ignored. + +@sa AffineBasedEstimator AffineBestOf2NearestMatcher BundleAdjusterAffinePartial + */ +class CV_EXPORTS BundleAdjusterAffine : public BundleAdjusterBase +{ +public: + BundleAdjusterAffine() : BundleAdjusterBase(6, 2) {} + +private: + void setUpInitialCameraParams(const std::vector &cameras) CV_OVERRIDE; + void obtainRefinedCameraParams(std::vector &cameras) const CV_OVERRIDE; + void calcError(Mat &err) CV_OVERRIDE; + void calcJacobian(Mat &jac) CV_OVERRIDE; + + Mat err1_, err2_; +}; + + +/** @brief Bundle adjuster that expects affine transformation with 4 DOF +represented in homogeneous coordinates in R for each camera param. Implements +camera parameters refinement algorithm which minimizes sum of the reprojection +error squares + +It estimates all transformation parameters. Refinement mask is ignored. + +@sa AffineBasedEstimator AffineBestOf2NearestMatcher BundleAdjusterAffine + */ +class CV_EXPORTS BundleAdjusterAffinePartial : public BundleAdjusterBase +{ +public: + BundleAdjusterAffinePartial() : BundleAdjusterBase(4, 2) {} + +private: + void setUpInitialCameraParams(const std::vector &cameras) CV_OVERRIDE; + void obtainRefinedCameraParams(std::vector &cameras) const CV_OVERRIDE; + void calcError(Mat &err) CV_OVERRIDE; + void calcJacobian(Mat &jac) CV_OVERRIDE; + + Mat err1_, err2_; +}; + + +enum WaveCorrectKind +{ + WAVE_CORRECT_HORIZ, + WAVE_CORRECT_VERT +}; + +/** @brief Tries to make panorama more horizontal (or vertical). + +@param rmats Camera rotation matrices. +@param kind Correction kind, see detail::WaveCorrectKind. + */ +void CV_EXPORTS waveCorrect(std::vector &rmats, WaveCorrectKind kind); + + +////////////////////////////////////////////////////////////////////////////// +// Auxiliary functions + +// Returns matches graph representation in DOT language +String CV_EXPORTS matchesGraphAsString(std::vector &pathes, std::vector &pairwise_matches, + float conf_threshold); + +std::vector CV_EXPORTS leaveBiggestComponent( + std::vector &features, + std::vector &pairwise_matches, + float conf_threshold); + +void CV_EXPORTS findMaxSpanningTree( + int num_images, const std::vector &pairwise_matches, + Graph &span_tree, std::vector ¢ers); + +//! @} stitching_rotation + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_MOTION_ESTIMATORS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/seam_finders.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/seam_finders.hpp new file mode 100644 index 00000000..904f0ecb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/seam_finders.hpp @@ -0,0 +1,285 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_SEAM_FINDERS_HPP +#define OPENCV_STITCHING_SEAM_FINDERS_HPP + +#include +#include "opencv2/core.hpp" +#include "opencv2/opencv_modules.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_seam +//! @{ + +/** @brief Base class for a seam estimator. + */ +class CV_EXPORTS SeamFinder +{ +public: + virtual ~SeamFinder() {} + /** @brief Estimates seams. + + @param src Source images + @param corners Source image top-left corners + @param masks Source image masks to update + */ + virtual void find(const std::vector &src, const std::vector &corners, + std::vector &masks) = 0; +}; + +/** @brief Stub seam estimator which does nothing. + */ +class CV_EXPORTS NoSeamFinder : public SeamFinder +{ +public: + void find(const std::vector&, const std::vector&, std::vector&) CV_OVERRIDE {} +}; + +/** @brief Base class for all pairwise seam estimators. + */ +class CV_EXPORTS PairwiseSeamFinder : public SeamFinder +{ +public: + virtual void find(const std::vector &src, const std::vector &corners, + std::vector &masks) CV_OVERRIDE; + +protected: + void run(); + /** @brief Resolves masks intersection of two specified images in the given ROI. + + @param first First image index + @param second Second image index + @param roi Region of interest + */ + virtual void findInPair(size_t first, size_t second, Rect roi) = 0; + + std::vector images_; + std::vector sizes_; + std::vector corners_; + std::vector masks_; +}; + +/** @brief Voronoi diagram-based seam estimator. + */ +class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder +{ +public: + virtual void find(const std::vector &src, const std::vector &corners, + std::vector &masks) CV_OVERRIDE; + virtual void find(const std::vector &size, const std::vector &corners, + std::vector &masks); +private: + void findInPair(size_t first, size_t second, Rect roi) CV_OVERRIDE; +}; + + +class CV_EXPORTS DpSeamFinder : public SeamFinder +{ +public: + enum CostFunction { COLOR, COLOR_GRAD }; + + DpSeamFinder(CostFunction costFunc = COLOR); + + CostFunction costFunction() const { return costFunc_; } + void setCostFunction(CostFunction val) { costFunc_ = val; } + + virtual void find(const std::vector &src, const std::vector &corners, + std::vector &masks) CV_OVERRIDE; + +private: + enum ComponentState + { + FIRST = 1, SECOND = 2, INTERS = 4, + INTERS_FIRST = INTERS | FIRST, + INTERS_SECOND = INTERS | SECOND + }; + + class ImagePairLess + { + public: + ImagePairLess(const std::vector &images, const std::vector &corners) + : src_(&images[0]), corners_(&corners[0]) {} + + bool operator() (const std::pair &l, const std::pair &r) const + { + Point c1 = corners_[l.first] + Point(src_[l.first].cols / 2, src_[l.first].rows / 2); + Point c2 = corners_[l.second] + Point(src_[l.second].cols / 2, src_[l.second].rows / 2); + int d1 = (c1 - c2).dot(c1 - c2); + + c1 = corners_[r.first] + Point(src_[r.first].cols / 2, src_[r.first].rows / 2); + c2 = corners_[r.second] + Point(src_[r.second].cols / 2, src_[r.second].rows / 2); + int d2 = (c1 - c2).dot(c1 - c2); + + return d1 < d2; + } + + private: + const Mat *src_; + const Point *corners_; + }; + + class ClosePoints + { + public: + ClosePoints(int minDist) : minDist_(minDist) {} + + bool operator() (const Point &p1, const Point &p2) const + { + int dist2 = (p1.x-p2.x) * (p1.x-p2.x) + (p1.y-p2.y) * (p1.y-p2.y); + return dist2 < minDist_ * minDist_; + } + + private: + int minDist_; + }; + + void process( + const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2); + + void findComponents(); + + void findEdges(); + + void resolveConflicts( + const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2); + + void computeGradients(const Mat &image1, const Mat &image2); + + bool hasOnlyOneNeighbor(int comp); + + bool closeToContour(int y, int x, const Mat_ &contourMask); + + bool getSeamTips(int comp1, int comp2, Point &p1, Point &p2); + + void computeCosts( + const Mat &image1, const Mat &image2, Point tl1, Point tl2, + int comp, Mat_ &costV, Mat_ &costH); + + bool estimateSeam( + const Mat &image1, const Mat &image2, Point tl1, Point tl2, int comp, + Point p1, Point p2, std::vector &seam, bool &isHorizontal); + + void updateLabelsUsingSeam( + int comp1, int comp2, const std::vector &seam, bool isHorizontalSeam); + + CostFunction costFunc_; + + // processing images pair data + Point unionTl_, unionBr_; + Size unionSize_; + Mat_ mask1_, mask2_; + Mat_ contour1mask_, contour2mask_; + Mat_ gradx1_, grady1_; + Mat_ gradx2_, grady2_; + + // components data + int ncomps_; + Mat_ labels_; + std::vector states_; + std::vector tls_, brs_; + std::vector > contours_; + std::set > edges_; +}; + +/** @brief Base class for all minimum graph-cut-based seam estimators. + */ +class CV_EXPORTS GraphCutSeamFinderBase +{ +public: + enum CostType { COST_COLOR, COST_COLOR_GRAD }; +}; + +/** @brief Minimum graph cut-based seam estimator. See details in @cite V03 . + */ +class CV_EXPORTS GraphCutSeamFinder : public GraphCutSeamFinderBase, public SeamFinder +{ +public: + GraphCutSeamFinder(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f, + float bad_region_penalty = 1000.f); + + ~GraphCutSeamFinder(); + + void find(const std::vector &src, const std::vector &corners, + std::vector &masks) CV_OVERRIDE; + +private: + // To avoid GCGraph dependency + class Impl; + Ptr impl_; +}; + + +#ifdef HAVE_OPENCV_CUDALEGACY +class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder +{ +public: + GraphCutSeamFinderGpu(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f, + float bad_region_penalty = 1000.f) + : cost_type_(cost_type), terminal_cost_(terminal_cost), + bad_region_penalty_(bad_region_penalty) {} + + void find(const std::vector &src, const std::vector &corners, + std::vector &masks) CV_OVERRIDE; + void findInPair(size_t first, size_t second, Rect roi) CV_OVERRIDE; + +private: + void setGraphWeightsColor(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &mask1, const cv::Mat &mask2, + cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom); + void setGraphWeightsColorGrad(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &dx1, const cv::Mat &dx2, + const cv::Mat &dy1, const cv::Mat &dy2, const cv::Mat &mask1, const cv::Mat &mask2, + cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom); + std::vector dx_, dy_; + int cost_type_; + float terminal_cost_; + float bad_region_penalty_; +}; +#endif + +//! @} + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_SEAM_FINDERS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/timelapsers.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/timelapsers.hpp new file mode 100644 index 00000000..74d797ed --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/timelapsers.hpp @@ -0,0 +1,91 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + + +#ifndef OPENCV_STITCHING_TIMELAPSERS_HPP +#define OPENCV_STITCHING_TIMELAPSERS_HPP + +#include "opencv2/core.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching +//! @{ + +// Base Timelapser class, takes a sequence of images, applies appropriate shift, stores result in dst_. + +class CV_EXPORTS Timelapser +{ +public: + + enum {AS_IS, CROP}; + + virtual ~Timelapser() {} + + static Ptr createDefault(int type); + + virtual void initialize(const std::vector &corners, const std::vector &sizes); + virtual void process(InputArray img, InputArray mask, Point tl); + virtual const UMat& getDst() {return dst_;} + +protected: + + virtual bool test_point(Point pt); + + UMat dst_; + Rect dst_roi_; +}; + + +class CV_EXPORTS TimelapserCrop : public Timelapser +{ +public: + virtual void initialize(const std::vector &corners, const std::vector &sizes) CV_OVERRIDE; +}; + +//! @} + +} // namespace detail +} // namespace cv + +#endif // OPENCV_STITCHING_TIMELAPSERS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/util.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/util.hpp new file mode 100644 index 00000000..78301b85 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/util.hpp @@ -0,0 +1,121 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_UTIL_HPP +#define OPENCV_STITCHING_UTIL_HPP + +#include +#include "opencv2/core.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching +//! @{ + +class CV_EXPORTS DisjointSets +{ +public: + DisjointSets(int elem_count = 0) { createOneElemSets(elem_count); } + + void createOneElemSets(int elem_count); + int findSetByElem(int elem); + int mergeSets(int set1, int set2); + + std::vector parent; + std::vector size; + +private: + std::vector rank_; +}; + + +struct CV_EXPORTS GraphEdge +{ + GraphEdge(int from, int to, float weight); + bool operator <(const GraphEdge& other) const { return weight < other.weight; } + bool operator >(const GraphEdge& other) const { return weight > other.weight; } + + int from, to; + float weight; +}; + +inline GraphEdge::GraphEdge(int _from, int _to, float _weight) : from(_from), to(_to), weight(_weight) {} + + +class CV_EXPORTS Graph +{ +public: + Graph(int num_vertices = 0) { create(num_vertices); } + void create(int num_vertices) { edges_.assign(num_vertices, std::list()); } + int numVertices() const { return static_cast(edges_.size()); } + void addEdge(int from, int to, float weight); + template B forEach(B body) const; + template B walkBreadthFirst(int from, B body) const; + +private: + std::vector< std::list > edges_; +}; + + +////////////////////////////////////////////////////////////////////////////// +// Auxiliary functions + +CV_EXPORTS bool overlapRoi(Point tl1, Point tl2, Size sz1, Size sz2, Rect &roi); +CV_EXPORTS Rect resultRoi(const std::vector &corners, const std::vector &images); +CV_EXPORTS Rect resultRoi(const std::vector &corners, const std::vector &sizes); +CV_EXPORTS Rect resultRoiIntersection(const std::vector &corners, const std::vector &sizes); +CV_EXPORTS Point resultTl(const std::vector &corners); + +// Returns random 'count' element subset of the {0,1,...,size-1} set +CV_EXPORTS void selectRandomSubset(int count, int size, std::vector &subset); + +CV_EXPORTS int& stitchingLogLevel(); + +//! @} + +} // namespace detail +} // namespace cv + +#include "util_inl.hpp" + +#endif // OPENCV_STITCHING_UTIL_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/util_inl.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/util_inl.hpp new file mode 100644 index 00000000..dafab8b8 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/util_inl.hpp @@ -0,0 +1,131 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_UTIL_INL_HPP +#define OPENCV_STITCHING_UTIL_INL_HPP + +#include +#include "opencv2/core.hpp" +#include "util.hpp" // Make your IDE see declarations + +//! @cond IGNORED + +namespace cv { +namespace detail { + +template +B Graph::forEach(B body) const +{ + for (int i = 0; i < numVertices(); ++i) + { + std::list::const_iterator edge = edges_[i].begin(); + for (; edge != edges_[i].end(); ++edge) + body(*edge); + } + return body; +} + + +template +B Graph::walkBreadthFirst(int from, B body) const +{ + std::vector was(numVertices(), false); + std::queue vertices; + + was[from] = true; + vertices.push(from); + + while (!vertices.empty()) + { + int vertex = vertices.front(); + vertices.pop(); + + std::list::const_iterator edge = edges_[vertex].begin(); + for (; edge != edges_[vertex].end(); ++edge) + { + if (!was[edge->to]) + { + body(*edge); + was[edge->to] = true; + vertices.push(edge->to); + } + } + } + + return body; +} + + +////////////////////////////////////////////////////////////////////////////// +// Some auxiliary math functions + +static inline +float normL2(const Point3f& a) +{ + return a.x * a.x + a.y * a.y + a.z * a.z; +} + + +static inline +float normL2(const Point3f& a, const Point3f& b) +{ + return normL2(a - b); +} + + +static inline +double normL2sq(const Mat &r) +{ + return r.dot(r); +} + + +static inline int sqr(int x) { return x * x; } +static inline float sqr(float x) { return x * x; } +static inline double sqr(double x) { return x * x; } + +} // namespace detail +} // namespace cv + +//! @endcond + +#endif // OPENCV_STITCHING_UTIL_INL_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/warpers.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/warpers.hpp new file mode 100644 index 00000000..1b05651f --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/warpers.hpp @@ -0,0 +1,616 @@ + /*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_WARPERS_HPP +#define OPENCV_STITCHING_WARPERS_HPP + +#include "opencv2/core.hpp" +#include "opencv2/core/cuda.hpp" +#include "opencv2/imgproc.hpp" +#include "opencv2/opencv_modules.hpp" + +namespace cv { +namespace detail { + +//! @addtogroup stitching_warp +//! @{ + +/** @brief Rotation-only model image warper interface. + */ +class CV_EXPORTS RotationWarper +{ +public: + virtual ~RotationWarper() {} + + /** @brief Projects the image point. + + @param pt Source point + @param K Camera intrinsic parameters + @param R Camera rotation matrix + @return Projected point + */ + virtual Point2f warpPoint(const Point2f &pt, InputArray K, InputArray R) = 0; + + /** @brief Builds the projection maps according to the given camera data. + + @param src_size Source image size + @param K Camera intrinsic parameters + @param R Camera rotation matrix + @param xmap Projection map for the x axis + @param ymap Projection map for the y axis + @return Projected image minimum bounding box + */ + virtual Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) = 0; + + /** @brief Projects the image. + + @param src Source image + @param K Camera intrinsic parameters + @param R Camera rotation matrix + @param interp_mode Interpolation mode + @param border_mode Border extrapolation mode + @param dst Projected image + @return Project image top-left corner + */ + virtual Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) = 0; + + /** @brief Projects the image backward. + + @param src Projected image + @param K Camera intrinsic parameters + @param R Camera rotation matrix + @param interp_mode Interpolation mode + @param border_mode Border extrapolation mode + @param dst_size Backward-projected image size + @param dst Backward-projected image + */ + virtual void warpBackward(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + Size dst_size, OutputArray dst) = 0; + + /** + @param src_size Source image bounding box + @param K Camera intrinsic parameters + @param R Camera rotation matrix + @return Projected image minimum bounding box + */ + virtual Rect warpRoi(Size src_size, InputArray K, InputArray R) = 0; + + virtual float getScale() const { return 1.f; } + virtual void setScale(float) {} +}; + +/** @brief Base class for warping logic implementation. + */ +struct CV_EXPORTS ProjectorBase +{ + void setCameraParams(InputArray K = Mat::eye(3, 3, CV_32F), + InputArray R = Mat::eye(3, 3, CV_32F), + InputArray T = Mat::zeros(3, 1, CV_32F)); + + float scale; + float k[9]; + float rinv[9]; + float r_kinv[9]; + float k_rinv[9]; + float t[3]; +}; + +/** @brief Base class for rotation-based warper using a detail::ProjectorBase_ derived class. + */ +template +class CV_EXPORTS_TEMPLATE RotationWarperBase : public RotationWarper +{ +public: + Point2f warpPoint(const Point2f &pt, InputArray K, InputArray R) CV_OVERRIDE; + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE; + + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) CV_OVERRIDE; + + void warpBackward(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + Size dst_size, OutputArray dst) CV_OVERRIDE; + + Rect warpRoi(Size src_size, InputArray K, InputArray R) CV_OVERRIDE; + + float getScale() const CV_OVERRIDE{ return projector_.scale; } + void setScale(float val) CV_OVERRIDE { projector_.scale = val; } + +protected: + + // Detects ROI of the destination image. It's correct for any projection. + virtual void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br); + + // Detects ROI of the destination image by walking over image border. + // Correctness for any projection isn't guaranteed. + void detectResultRoiByBorder(Size src_size, Point &dst_tl, Point &dst_br); + + P projector_; +}; + + +struct CV_EXPORTS PlaneProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + +/** @brief Warper that maps an image onto the z = 1 plane. + */ +class CV_EXPORTS PlaneWarper : public RotationWarperBase +{ +public: + /** @brief Construct an instance of the plane warper class. + + @param scale Projected image scale multiplier + */ + PlaneWarper(float scale = 1.f) { projector_.scale = scale; } + + Point2f warpPoint(const Point2f &pt, InputArray K, InputArray R) CV_OVERRIDE; + Point2f warpPoint(const Point2f &pt, InputArray K, InputArray R, InputArray T); + + virtual Rect buildMaps(Size src_size, InputArray K, InputArray R, InputArray T, OutputArray xmap, OutputArray ymap); + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE; + + Point warp(InputArray src, InputArray K, InputArray R, + int interp_mode, int border_mode, OutputArray dst) CV_OVERRIDE; + virtual Point warp(InputArray src, InputArray K, InputArray R, InputArray T, int interp_mode, int border_mode, + OutputArray dst); + + Rect warpRoi(Size src_size, InputArray K, InputArray R) CV_OVERRIDE; + Rect warpRoi(Size src_size, InputArray K, InputArray R, InputArray T); + +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE; +}; + + +/** @brief Affine warper that uses rotations and translations + + Uses affine transformation in homogeneous coordinates to represent both rotation and + translation in camera rotation matrix. + */ +class CV_EXPORTS AffineWarper : public PlaneWarper +{ +public: + /** @brief Construct an instance of the affine warper class. + + @param scale Projected image scale multiplier + */ + AffineWarper(float scale = 1.f) : PlaneWarper(scale) {} + + Point2f warpPoint(const Point2f &pt, InputArray K, InputArray R) CV_OVERRIDE; + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE; + Point warp(InputArray src, InputArray K, InputArray R, + int interp_mode, int border_mode, OutputArray dst) CV_OVERRIDE; + Rect warpRoi(Size src_size, InputArray K, InputArray R) CV_OVERRIDE; + +protected: + /** @brief Extracts rotation and translation matrices from matrix H representing + affine transformation in homogeneous coordinates + */ + void getRTfromHomogeneous(InputArray H, Mat &R, Mat &T); +}; + + +struct CV_EXPORTS SphericalProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +/** @brief Warper that maps an image onto the unit sphere located at the origin. + + Projects image onto unit sphere with origin at (0, 0, 0) and radius scale, measured in pixels. + A 360 panorama would therefore have a resulting width of 2 * scale * PI pixels. + Poles are located at (0, -1, 0) and (0, 1, 0) points. +*/ +class CV_EXPORTS SphericalWarper : public RotationWarperBase +{ +public: + /** @brief Construct an instance of the spherical warper class. + + @param scale Radius of the projected sphere, in pixels. An image spanning the + whole sphere will have a width of 2 * scale * PI pixels. + */ + SphericalWarper(float scale) { projector_.scale = scale; } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE; + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, OutputArray dst) CV_OVERRIDE; +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE; +}; + + +struct CV_EXPORTS CylindricalProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +/** @brief Warper that maps an image onto the x\*x + z\*z = 1 cylinder. + */ +class CV_EXPORTS CylindricalWarper : public RotationWarperBase +{ +public: + /** @brief Construct an instance of the cylindrical warper class. + + @param scale Projected image scale multiplier + */ + CylindricalWarper(float scale) { projector_.scale = scale; } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE; + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, OutputArray dst) CV_OVERRIDE; +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE + { + RotationWarperBase::detectResultRoiByBorder(src_size, dst_tl, dst_br); + } +}; + + +struct CV_EXPORTS FisheyeProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS FisheyeWarper : public RotationWarperBase +{ +public: + FisheyeWarper(float scale) { projector_.scale = scale; } +}; + + +struct CV_EXPORTS StereographicProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS StereographicWarper : public RotationWarperBase +{ +public: + StereographicWarper(float scale) { projector_.scale = scale; } +}; + + +struct CV_EXPORTS CompressedRectilinearProjector : ProjectorBase +{ + float a, b; + + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS CompressedRectilinearWarper : public RotationWarperBase +{ +public: + CompressedRectilinearWarper(float scale, float A = 1, float B = 1) + { + projector_.a = A; + projector_.b = B; + projector_.scale = scale; + } +}; + + +struct CV_EXPORTS CompressedRectilinearPortraitProjector : ProjectorBase +{ + float a, b; + + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS CompressedRectilinearPortraitWarper : public RotationWarperBase +{ +public: + CompressedRectilinearPortraitWarper(float scale, float A = 1, float B = 1) + { + projector_.a = A; + projector_.b = B; + projector_.scale = scale; + } +}; + + +struct CV_EXPORTS PaniniProjector : ProjectorBase +{ + float a, b; + + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS PaniniWarper : public RotationWarperBase +{ +public: + PaniniWarper(float scale, float A = 1, float B = 1) + { + projector_.a = A; + projector_.b = B; + projector_.scale = scale; + } +}; + + +struct CV_EXPORTS PaniniPortraitProjector : ProjectorBase +{ + float a, b; + + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS PaniniPortraitWarper : public RotationWarperBase +{ +public: + PaniniPortraitWarper(float scale, float A = 1, float B = 1) + { + projector_.a = A; + projector_.b = B; + projector_.scale = scale; + } + +}; + + +struct CV_EXPORTS MercatorProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS MercatorWarper : public RotationWarperBase +{ +public: + MercatorWarper(float scale) { projector_.scale = scale; } +}; + + +struct CV_EXPORTS TransverseMercatorProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS TransverseMercatorWarper : public RotationWarperBase +{ +public: + TransverseMercatorWarper(float scale) { projector_.scale = scale; } +}; + + +class CV_EXPORTS PlaneWarperGpu : public PlaneWarper +{ +public: + PlaneWarperGpu(float scale = 1.f) : PlaneWarper(scale) {} + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE + { + Rect result = buildMaps(src_size, K, R, d_xmap_, d_ymap_); + d_xmap_.download(xmap); + d_ymap_.download(ymap); + return result; + } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, InputArray T, OutputArray xmap, OutputArray ymap) CV_OVERRIDE + { + Rect result = buildMaps(src_size, K, R, T, d_xmap_, d_ymap_); + d_xmap_.download(xmap); + d_ymap_.download(ymap); + return result; + } + + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) CV_OVERRIDE + { + d_src_.upload(src); + Point result = warp(d_src_, K, R, interp_mode, border_mode, d_dst_); + d_dst_.download(dst); + return result; + } + + Point warp(InputArray src, InputArray K, InputArray R, InputArray T, int interp_mode, int border_mode, + OutputArray dst) CV_OVERRIDE + { + d_src_.upload(src); + Point result = warp(d_src_, K, R, T, interp_mode, border_mode, d_dst_); + d_dst_.download(dst); + return result; + } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, cuda::GpuMat & xmap, cuda::GpuMat & ymap); + + Rect buildMaps(Size src_size, InputArray K, InputArray R, InputArray T, cuda::GpuMat & xmap, cuda::GpuMat & ymap); + + Point warp(const cuda::GpuMat & src, InputArray K, InputArray R, int interp_mode, int border_mode, + cuda::GpuMat & dst); + + Point warp(const cuda::GpuMat & src, InputArray K, InputArray R, InputArray T, int interp_mode, int border_mode, + cuda::GpuMat & dst); + +private: + cuda::GpuMat d_xmap_, d_ymap_, d_src_, d_dst_; +}; + + +class CV_EXPORTS SphericalWarperGpu : public SphericalWarper +{ +public: + SphericalWarperGpu(float scale) : SphericalWarper(scale) {} + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE + { + Rect result = buildMaps(src_size, K, R, d_xmap_, d_ymap_); + d_xmap_.download(xmap); + d_ymap_.download(ymap); + return result; + } + + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) CV_OVERRIDE + { + d_src_.upload(src); + Point result = warp(d_src_, K, R, interp_mode, border_mode, d_dst_); + d_dst_.download(dst); + return result; + } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, cuda::GpuMat & xmap, cuda::GpuMat & ymap); + + Point warp(const cuda::GpuMat & src, InputArray K, InputArray R, int interp_mode, int border_mode, + cuda::GpuMat & dst); + +private: + cuda::GpuMat d_xmap_, d_ymap_, d_src_, d_dst_; +}; + + +class CV_EXPORTS CylindricalWarperGpu : public CylindricalWarper +{ +public: + CylindricalWarperGpu(float scale) : CylindricalWarper(scale) {} + + Rect buildMaps(Size src_size, InputArray K, InputArray R, OutputArray xmap, OutputArray ymap) CV_OVERRIDE + { + Rect result = buildMaps(src_size, K, R, d_xmap_, d_ymap_); + d_xmap_.download(xmap); + d_ymap_.download(ymap); + return result; + } + + Point warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) CV_OVERRIDE + { + d_src_.upload(src); + Point result = warp(d_src_, K, R, interp_mode, border_mode, d_dst_); + d_dst_.download(dst); + return result; + } + + Rect buildMaps(Size src_size, InputArray K, InputArray R, cuda::GpuMat & xmap, cuda::GpuMat & ymap); + + Point warp(const cuda::GpuMat & src, InputArray K, InputArray R, int interp_mode, int border_mode, + cuda::GpuMat & dst); + +private: + cuda::GpuMat d_xmap_, d_ymap_, d_src_, d_dst_; +}; + + +struct CV_EXPORTS SphericalPortraitProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +// Projects image onto unit sphere with origin at (0, 0, 0). +// Poles are located NOT at (0, -1, 0) and (0, 1, 0) points, BUT at (1, 0, 0) and (-1, 0, 0) points. +class CV_EXPORTS SphericalPortraitWarper : public RotationWarperBase +{ +public: + SphericalPortraitWarper(float scale) { projector_.scale = scale; } + +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE; +}; + +struct CV_EXPORTS CylindricalPortraitProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS CylindricalPortraitWarper : public RotationWarperBase +{ +public: + CylindricalPortraitWarper(float scale) { projector_.scale = scale; } + +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE + { + RotationWarperBase::detectResultRoiByBorder(src_size, dst_tl, dst_br); + } +}; + +struct CV_EXPORTS PlanePortraitProjector : ProjectorBase +{ + void mapForward(float x, float y, float &u, float &v); + void mapBackward(float u, float v, float &x, float &y); +}; + + +class CV_EXPORTS PlanePortraitWarper : public RotationWarperBase +{ +public: + PlanePortraitWarper(float scale) { projector_.scale = scale; } + +protected: + void detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) CV_OVERRIDE + { + RotationWarperBase::detectResultRoiByBorder(src_size, dst_tl, dst_br); + } +}; + +//! @} stitching_warp + +} // namespace detail +} // namespace cv + +#include "warpers_inl.hpp" + +#endif // OPENCV_STITCHING_WARPERS_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/detail/warpers_inl.hpp b/3rdparty/opencv/include/opencv2/stitching/detail/warpers_inl.hpp new file mode 100644 index 00000000..f4a19d9c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/detail/warpers_inl.hpp @@ -0,0 +1,774 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_WARPERS_INL_HPP +#define OPENCV_STITCHING_WARPERS_INL_HPP + +#include "opencv2/core.hpp" +#include "warpers.hpp" // Make your IDE see declarations +#include + +//! @cond IGNORED + +namespace cv { +namespace detail { + +template +Point2f RotationWarperBase

::warpPoint(const Point2f &pt, InputArray K, InputArray R) +{ + projector_.setCameraParams(K, R); + Point2f uv; + projector_.mapForward(pt.x, pt.y, uv.x, uv.y); + return uv; +} + + +template +Rect RotationWarperBase

::buildMaps(Size src_size, InputArray K, InputArray R, OutputArray _xmap, OutputArray _ymap) +{ + projector_.setCameraParams(K, R); + + Point dst_tl, dst_br; + detectResultRoi(src_size, dst_tl, dst_br); + + _xmap.create(dst_br.y - dst_tl.y + 1, dst_br.x - dst_tl.x + 1, CV_32F); + _ymap.create(dst_br.y - dst_tl.y + 1, dst_br.x - dst_tl.x + 1, CV_32F); + + Mat xmap = _xmap.getMat(), ymap = _ymap.getMat(); + + float x, y; + for (int v = dst_tl.y; v <= dst_br.y; ++v) + { + for (int u = dst_tl.x; u <= dst_br.x; ++u) + { + projector_.mapBackward(static_cast(u), static_cast(v), x, y); + xmap.at(v - dst_tl.y, u - dst_tl.x) = x; + ymap.at(v - dst_tl.y, u - dst_tl.x) = y; + } + } + + return Rect(dst_tl, dst_br); +} + + +template +Point RotationWarperBase

::warp(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + OutputArray dst) +{ + UMat xmap, ymap; + Rect dst_roi = buildMaps(src.size(), K, R, xmap, ymap); + + dst.create(dst_roi.height + 1, dst_roi.width + 1, src.type()); + remap(src, dst, xmap, ymap, interp_mode, border_mode); + + return dst_roi.tl(); +} + + +template +void RotationWarperBase

::warpBackward(InputArray src, InputArray K, InputArray R, int interp_mode, int border_mode, + Size dst_size, OutputArray dst) +{ + projector_.setCameraParams(K, R); + + Point src_tl, src_br; + detectResultRoi(dst_size, src_tl, src_br); + + Size size = src.size(); + CV_Assert(src_br.x - src_tl.x + 1 == size.width && src_br.y - src_tl.y + 1 == size.height); + + Mat xmap(dst_size, CV_32F); + Mat ymap(dst_size, CV_32F); + + float u, v; + for (int y = 0; y < dst_size.height; ++y) + { + for (int x = 0; x < dst_size.width; ++x) + { + projector_.mapForward(static_cast(x), static_cast(y), u, v); + xmap.at(y, x) = u - src_tl.x; + ymap.at(y, x) = v - src_tl.y; + } + } + + dst.create(dst_size, src.type()); + remap(src, dst, xmap, ymap, interp_mode, border_mode); +} + + +template +Rect RotationWarperBase

::warpRoi(Size src_size, InputArray K, InputArray R) +{ + projector_.setCameraParams(K, R); + + Point dst_tl, dst_br; + detectResultRoi(src_size, dst_tl, dst_br); + + return Rect(dst_tl, Point(dst_br.x + 1, dst_br.y + 1)); +} + + +template +void RotationWarperBase

::detectResultRoi(Size src_size, Point &dst_tl, Point &dst_br) +{ + float tl_uf = (std::numeric_limits::max)(); + float tl_vf = (std::numeric_limits::max)(); + float br_uf = -(std::numeric_limits::max)(); + float br_vf = -(std::numeric_limits::max)(); + + float u, v; + for (int y = 0; y < src_size.height; ++y) + { + for (int x = 0; x < src_size.width; ++x) + { + projector_.mapForward(static_cast(x), static_cast(y), u, v); + tl_uf = (std::min)(tl_uf, u); tl_vf = (std::min)(tl_vf, v); + br_uf = (std::max)(br_uf, u); br_vf = (std::max)(br_vf, v); + } + } + + dst_tl.x = static_cast(tl_uf); + dst_tl.y = static_cast(tl_vf); + dst_br.x = static_cast(br_uf); + dst_br.y = static_cast(br_vf); +} + + +template +void RotationWarperBase

::detectResultRoiByBorder(Size src_size, Point &dst_tl, Point &dst_br) +{ + float tl_uf = (std::numeric_limits::max)(); + float tl_vf = (std::numeric_limits::max)(); + float br_uf = -(std::numeric_limits::max)(); + float br_vf = -(std::numeric_limits::max)(); + + float u, v; + for (float x = 0; x < src_size.width; ++x) + { + projector_.mapForward(static_cast(x), 0, u, v); + tl_uf = (std::min)(tl_uf, u); tl_vf = (std::min)(tl_vf, v); + br_uf = (std::max)(br_uf, u); br_vf = (std::max)(br_vf, v); + + projector_.mapForward(static_cast(x), static_cast(src_size.height - 1), u, v); + tl_uf = (std::min)(tl_uf, u); tl_vf = (std::min)(tl_vf, v); + br_uf = (std::max)(br_uf, u); br_vf = (std::max)(br_vf, v); + } + for (int y = 0; y < src_size.height; ++y) + { + projector_.mapForward(0, static_cast(y), u, v); + tl_uf = (std::min)(tl_uf, u); tl_vf = (std::min)(tl_vf, v); + br_uf = (std::max)(br_uf, u); br_vf = (std::max)(br_vf, v); + + projector_.mapForward(static_cast(src_size.width - 1), static_cast(y), u, v); + tl_uf = (std::min)(tl_uf, u); tl_vf = (std::min)(tl_vf, v); + br_uf = (std::max)(br_uf, u); br_vf = (std::max)(br_vf, v); + } + + dst_tl.x = static_cast(tl_uf); + dst_tl.y = static_cast(tl_vf); + dst_br.x = static_cast(br_uf); + dst_br.y = static_cast(br_vf); +} + + +inline +void PlaneProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + x_ = t[0] + x_ / z_ * (1 - t[2]); + y_ = t[1] + y_ / z_ * (1 - t[2]); + + u = scale * x_; + v = scale * y_; +} + + +inline +void PlaneProjector::mapBackward(float u, float v, float &x, float &y) +{ + u = u / scale - t[0]; + v = v / scale - t[1]; + + float z; + x = k_rinv[0] * u + k_rinv[1] * v + k_rinv[2] * (1 - t[2]); + y = k_rinv[3] * u + k_rinv[4] * v + k_rinv[5] * (1 - t[2]); + z = k_rinv[6] * u + k_rinv[7] * v + k_rinv[8] * (1 - t[2]); + + x /= z; + y /= z; +} + + +inline +void SphericalProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + u = scale * atan2f(x_, z_); + float w = y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_); + v = scale * (static_cast(CV_PI) - acosf(w == w ? w : 0)); +} + + +inline +void SphericalProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float sinv = sinf(static_cast(CV_PI) - v); + float x_ = sinv * sinf(u); + float y_ = cosf(static_cast(CV_PI) - v); + float z_ = sinv * cosf(u); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + + +inline +void CylindricalProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + u = scale * atan2f(x_, z_); + v = scale * y_ / sqrtf(x_ * x_ + z_ * z_); +} + + +inline +void CylindricalProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float x_ = sinf(u); + float y_ = v; + float z_ = cosf(u); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void FisheyeProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = (float)CV_PI - acosf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + u = scale * v_ * cosf(u_); + v = scale * v_ * sinf(u_); +} + +inline +void FisheyeProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float u_ = atan2f(v, u); + float v_ = sqrtf(u*u + v*v); + + float sinv = sinf((float)CV_PI - v_); + float x_ = sinv * sinf(u_); + float y_ = cosf((float)CV_PI - v_); + float z_ = sinv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void StereographicProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = (float)CV_PI - acosf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + float r = sinf(v_) / (1 - cosf(v_)); + + u = scale * r * cos(u_); + v = scale * r * sin(u_); +} + +inline +void StereographicProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float u_ = atan2f(v, u); + float r = sqrtf(u*u + v*v); + float v_ = 2 * atanf(1.f / r); + + float sinv = sinf((float)CV_PI - v_); + float x_ = sinv * sinf(u_); + float y_ = cosf((float)CV_PI - v_); + float z_ = sinv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void CompressedRectilinearProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + u = scale * a * tanf(u_ / a); + v = scale * b * tanf(v_) / cosf(u_); +} + +inline +void CompressedRectilinearProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float aatg = a * atanf(u / a); + float u_ = aatg; + float v_ = atanf(v * cosf(aatg) / b); + + float cosv = cosf(v_); + float x_ = cosv * sinf(u_); + float y_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void CompressedRectilinearPortraitProjector::mapForward(float x, float y, float &u, float &v) +{ + float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float x_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + u = - scale * a * tanf(u_ / a); + v = scale * b * tanf(v_) / cosf(u_); +} + +inline +void CompressedRectilinearPortraitProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= - scale; + v /= scale; + + float aatg = a * atanf(u / a); + float u_ = aatg; + float v_ = atanf(v * cosf( aatg ) / b); + + float cosv = cosf(v_); + float y_ = cosv * sinf(u_); + float x_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void PaniniProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + float tg = a * tanf(u_ / a); + u = scale * tg; + + float sinu = sinf(u_); + if ( fabs(sinu) < 1E-7 ) + v = scale * b * tanf(v_); + else + v = scale * b * tg * tanf(v_) / sinu; +} + +inline +void PaniniProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float lamda = a * atanf(u / a); + float u_ = lamda; + + float v_; + if ( fabs(lamda) > 1E-7) + v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda / a))); + else + v_ = atanf(v / b); + + float cosv = cosf(v_); + float x_ = cosv * sinf(u_); + float y_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void PaniniPortraitProjector::mapForward(float x, float y, float &u, float &v) +{ + float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float x_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + float tg = a * tanf(u_ / a); + u = - scale * tg; + + float sinu = sinf( u_ ); + if ( fabs(sinu) < 1E-7 ) + v = scale * b * tanf(v_); + else + v = scale * b * tg * tanf(v_) / sinu; +} + +inline +void PaniniPortraitProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= - scale; + v /= scale; + + float lamda = a * atanf(u / a); + float u_ = lamda; + + float v_; + if ( fabs(lamda) > 1E-7) + v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda/a))); + else + v_ = atanf(v / b); + + float cosv = cosf(v_); + float y_ = cosv * sinf(u_); + float x_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void MercatorProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + u = scale * u_; + v = scale * logf( tanf( (float)(CV_PI/4) + v_/2 ) ); +} + +inline +void MercatorProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float v_ = atanf( sinhf(v) ); + float u_ = u; + + float cosv = cosf(v_); + float x_ = cosv * sinf(u_); + float y_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void TransverseMercatorProjector::mapForward(float x, float y, float &u, float &v) +{ + float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float u_ = atan2f(x_, z_); + float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_)); + + float B = cosf(v_) * sinf(u_); + + u = scale / 2 * logf( (1+B) / (1-B) ); + v = scale * atan2f(tanf(v_), cosf(u_)); +} + +inline +void TransverseMercatorProjector::mapBackward(float u, float v, float &x, float &y) +{ + u /= scale; + v /= scale; + + float v_ = asinf( sinf(v) / coshf(u) ); + float u_ = atan2f( sinhf(u), cos(v) ); + + float cosv = cosf(v_); + float x_ = cosv * sinf(u_); + float y_ = sinf(v_); + float z_ = cosv * cosf(u_); + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void SphericalPortraitProjector::mapForward(float x, float y, float &u0, float &v0) +{ + float x0_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y0_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float x_ = y0_; + float y_ = x0_; + float u, v; + + u = scale * atan2f(x_, z_); + v = scale * (static_cast(CV_PI) - acosf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_))); + + u0 = -u;//v; + v0 = v;//u; +} + + +inline +void SphericalPortraitProjector::mapBackward(float u0, float v0, float &x, float &y) +{ + float u, v; + u = -u0;//v0; + v = v0;//u0; + + u /= scale; + v /= scale; + + float sinv = sinf(static_cast(CV_PI) - v); + float x0_ = sinv * sinf(u); + float y0_ = cosf(static_cast(CV_PI) - v); + float z_ = sinv * cosf(u); + + float x_ = y0_; + float y_ = x0_; + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void CylindricalPortraitProjector::mapForward(float x, float y, float &u0, float &v0) +{ + float x0_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y0_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float x_ = y0_; + float y_ = x0_; + float u, v; + + u = scale * atan2f(x_, z_); + v = scale * y_ / sqrtf(x_ * x_ + z_ * z_); + + u0 = -u;//v; + v0 = v;//u; +} + + +inline +void CylindricalPortraitProjector::mapBackward(float u0, float v0, float &x, float &y) +{ + float u, v; + u = -u0;//v0; + v = v0;//u0; + + u /= scale; + v /= scale; + + float x0_ = sinf(u); + float y0_ = v; + float z_ = cosf(u); + + float x_ = y0_; + float y_ = x0_; + + float z; + x = k_rinv[0] * x_ + k_rinv[1] * y_ + k_rinv[2] * z_; + y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_; + z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_; + + if (z > 0) { x /= z; y /= z; } + else x = y = -1; +} + +inline +void PlanePortraitProjector::mapForward(float x, float y, float &u0, float &v0) +{ + float x0_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2]; + float y0_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5]; + float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8]; + + float x_ = y0_; + float y_ = x0_; + + x_ = t[0] + x_ / z_ * (1 - t[2]); + y_ = t[1] + y_ / z_ * (1 - t[2]); + + float u,v; + u = scale * x_; + v = scale * y_; + + u0 = -u; + v0 = v; +} + + +inline +void PlanePortraitProjector::mapBackward(float u0, float v0, float &x, float &y) +{ + float u, v; + u = -u0; + v = v0; + + u = u / scale - t[0]; + v = v / scale - t[1]; + + float z; + x = k_rinv[0] * v + k_rinv[1] * u + k_rinv[2] * (1 - t[2]); + y = k_rinv[3] * v + k_rinv[4] * u + k_rinv[5] * (1 - t[2]); + z = k_rinv[6] * v + k_rinv[7] * u + k_rinv[8] * (1 - t[2]); + + x /= z; + y /= z; +} + + +} // namespace detail +} // namespace cv + +//! @endcond + +#endif // OPENCV_STITCHING_WARPERS_INL_HPP diff --git a/3rdparty/opencv/include/opencv2/stitching/warpers.hpp b/3rdparty/opencv/include/opencv2/stitching/warpers.hpp new file mode 100644 index 00000000..cf7699c0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/stitching/warpers.hpp @@ -0,0 +1,192 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_STITCHING_WARPER_CREATORS_HPP +#define OPENCV_STITCHING_WARPER_CREATORS_HPP + +#include "opencv2/stitching/detail/warpers.hpp" + +namespace cv { + +//! @addtogroup stitching_warp +//! @{ + +/** @brief Image warper factories base class. + */ +class WarperCreator +{ +public: + virtual ~WarperCreator() {} + virtual Ptr create(float scale) const = 0; +}; + +/** @brief Plane warper factory class. + @sa detail::PlaneWarper + */ +class PlaneWarper : public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +/** @brief Affine warper factory class. + @sa detail::AffineWarper + */ +class AffineWarper : public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +/** @brief Cylindrical warper factory class. +@sa detail::CylindricalWarper +*/ +class CylindricalWarper: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +/** @brief Spherical warper factory class */ +class SphericalWarper: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +class FisheyeWarper : public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +class StereographicWarper: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +class CompressedRectilinearWarper: public WarperCreator +{ + float a, b; +public: + CompressedRectilinearWarper(float A = 1, float B = 1) + { + a = A; b = B; + } + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale, a, b); } +}; + +class CompressedRectilinearPortraitWarper: public WarperCreator +{ + float a, b; +public: + CompressedRectilinearPortraitWarper(float A = 1, float B = 1) + { + a = A; b = B; + } + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale, a, b); } +}; + +class PaniniWarper: public WarperCreator +{ + float a, b; +public: + PaniniWarper(float A = 1, float B = 1) + { + a = A; b = B; + } + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale, a, b); } +}; + +class PaniniPortraitWarper: public WarperCreator +{ + float a, b; +public: + PaniniPortraitWarper(float A = 1, float B = 1) + { + a = A; b = B; + } + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale, a, b); } +}; + +class MercatorWarper: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + +class TransverseMercatorWarper: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + + + +#ifdef HAVE_OPENCV_CUDAWARPING +class PlaneWarperGpu: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + + +class CylindricalWarperGpu: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; + + +class SphericalWarperGpu: public WarperCreator +{ +public: + Ptr create(float scale) const CV_OVERRIDE { return makePtr(scale); } +}; +#endif + +//! @} stitching_warp + +} // namespace cv + +#endif // OPENCV_STITCHING_WARPER_CREATORS_HPP diff --git a/3rdparty/opencv/include/opencv2/superres.hpp b/3rdparty/opencv/include/opencv2/superres.hpp new file mode 100644 index 00000000..16c11acd --- /dev/null +++ b/3rdparty/opencv/include/opencv2/superres.hpp @@ -0,0 +1,207 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_SUPERRES_HPP +#define OPENCV_SUPERRES_HPP + +#include "opencv2/core.hpp" +#include "opencv2/superres/optical_flow.hpp" + +/** + @defgroup superres Super Resolution + +The Super Resolution module contains a set of functions and classes that can be used to solve the +problem of resolution enhancement. There are a few methods implemented, most of them are described in +the papers @cite Farsiu03 and @cite Mitzel09 . + + */ + +namespace cv +{ + namespace superres + { + +//! @addtogroup superres +//! @{ + + class CV_EXPORTS FrameSource + { + public: + virtual ~FrameSource(); + + virtual void nextFrame(OutputArray frame) = 0; + virtual void reset() = 0; + }; + + CV_EXPORTS Ptr createFrameSource_Empty(); + + CV_EXPORTS Ptr createFrameSource_Video(const String& fileName); + CV_EXPORTS Ptr createFrameSource_Video_CUDA(const String& fileName); + + CV_EXPORTS Ptr createFrameSource_Camera(int deviceId = 0); + + /** @brief Base class for Super Resolution algorithms. + + The class is only used to define the common interface for the whole family of Super Resolution + algorithms. + */ + class CV_EXPORTS SuperResolution : public cv::Algorithm, public FrameSource + { + public: + /** @brief Set input frame source for Super Resolution algorithm. + + @param frameSource Input frame source + */ + void setInput(const Ptr& frameSource); + + /** @brief Process next frame from input and return output result. + + @param frame Output result + */ + void nextFrame(OutputArray frame) CV_OVERRIDE; + void reset() CV_OVERRIDE; + + /** @brief Clear all inner buffers. + */ + virtual void collectGarbage(); + + //! @brief Scale factor + /** @see setScale */ + virtual int getScale() const = 0; + /** @copybrief getScale @see getScale */ + virtual void setScale(int val) = 0; + + //! @brief Iterations count + /** @see setIterations */ + virtual int getIterations() const = 0; + /** @copybrief getIterations @see getIterations */ + virtual void setIterations(int val) = 0; + + //! @brief Asymptotic value of steepest descent method + /** @see setTau */ + virtual double getTau() const = 0; + /** @copybrief getTau @see getTau */ + virtual void setTau(double val) = 0; + + //! @brief Weight parameter to balance data term and smoothness term + /** @see setLabmda */ + virtual double getLabmda() const = 0; + /** @copybrief getLabmda @see getLabmda */ + virtual void setLabmda(double val) = 0; + + //! @brief Parameter of spacial distribution in Bilateral-TV + /** @see setAlpha */ + virtual double getAlpha() const = 0; + /** @copybrief getAlpha @see getAlpha */ + virtual void setAlpha(double val) = 0; + + //! @brief Kernel size of Bilateral-TV filter + /** @see setKernelSize */ + virtual int getKernelSize() const = 0; + /** @copybrief getKernelSize @see getKernelSize */ + virtual void setKernelSize(int val) = 0; + + //! @brief Gaussian blur kernel size + /** @see setBlurKernelSize */ + virtual int getBlurKernelSize() const = 0; + /** @copybrief getBlurKernelSize @see getBlurKernelSize */ + virtual void setBlurKernelSize(int val) = 0; + + //! @brief Gaussian blur sigma + /** @see setBlurSigma */ + virtual double getBlurSigma() const = 0; + /** @copybrief getBlurSigma @see getBlurSigma */ + virtual void setBlurSigma(double val) = 0; + + //! @brief Radius of the temporal search area + /** @see setTemporalAreaRadius */ + virtual int getTemporalAreaRadius() const = 0; + /** @copybrief getTemporalAreaRadius @see getTemporalAreaRadius */ + virtual void setTemporalAreaRadius(int val) = 0; + + //! @brief Dense optical flow algorithm + /** @see setOpticalFlow */ + virtual Ptr getOpticalFlow() const = 0; + /** @copybrief getOpticalFlow @see getOpticalFlow */ + virtual void setOpticalFlow(const Ptr &val) = 0; + + protected: + SuperResolution(); + + virtual void initImpl(Ptr& frameSource) = 0; + virtual void processImpl(Ptr& frameSource, OutputArray output) = 0; + + bool isUmat_; + + private: + Ptr frameSource_; + bool firstCall_; + }; + + /** @brief Create Bilateral TV-L1 Super Resolution. + + This class implements Super Resolution algorithm described in the papers @cite Farsiu03 and + @cite Mitzel09 . + + Here are important members of the class that control the algorithm, which you can set after + constructing the class instance: + + - **int scale** Scale factor. + - **int iterations** Iteration count. + - **double tau** Asymptotic value of steepest descent method. + - **double lambda** Weight parameter to balance data term and smoothness term. + - **double alpha** Parameter of spacial distribution in Bilateral-TV. + - **int btvKernelSize** Kernel size of Bilateral-TV filter. + - **int blurKernelSize** Gaussian blur kernel size. + - **double blurSigma** Gaussian blur sigma. + - **int temporalAreaRadius** Radius of the temporal search area. + - **Ptr\ opticalFlow** Dense optical flow algorithm. + */ + CV_EXPORTS Ptr createSuperResolution_BTVL1(); + CV_EXPORTS Ptr createSuperResolution_BTVL1_CUDA(); + +//! @} superres + + } +} + +#endif // OPENCV_SUPERRES_HPP diff --git a/3rdparty/opencv/include/opencv2/superres/optical_flow.hpp b/3rdparty/opencv/include/opencv2/superres/optical_flow.hpp new file mode 100644 index 00000000..07e7ca9c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/superres/optical_flow.hpp @@ -0,0 +1,203 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_SUPERRES_OPTICAL_FLOW_HPP +#define OPENCV_SUPERRES_OPTICAL_FLOW_HPP + +#include "opencv2/core.hpp" + +namespace cv +{ + namespace superres + { + +//! @addtogroup superres +//! @{ + + class CV_EXPORTS DenseOpticalFlowExt : public cv::Algorithm + { + public: + virtual void calc(InputArray frame0, InputArray frame1, OutputArray flow1, OutputArray flow2 = noArray()) = 0; + virtual void collectGarbage() = 0; + }; + + + class CV_EXPORTS FarnebackOpticalFlow : public virtual DenseOpticalFlowExt + { + public: + /** @see setPyrScale */ + virtual double getPyrScale() const = 0; + /** @copybrief getPyrScale @see getPyrScale */ + virtual void setPyrScale(double val) = 0; + /** @see setLevelsNumber */ + virtual int getLevelsNumber() const = 0; + /** @copybrief getLevelsNumber @see getLevelsNumber */ + virtual void setLevelsNumber(int val) = 0; + /** @see setWindowSize */ + virtual int getWindowSize() const = 0; + /** @copybrief getWindowSize @see getWindowSize */ + virtual void setWindowSize(int val) = 0; + /** @see setIterations */ + virtual int getIterations() const = 0; + /** @copybrief getIterations @see getIterations */ + virtual void setIterations(int val) = 0; + /** @see setPolyN */ + virtual int getPolyN() const = 0; + /** @copybrief getPolyN @see getPolyN */ + virtual void setPolyN(int val) = 0; + /** @see setPolySigma */ + virtual double getPolySigma() const = 0; + /** @copybrief getPolySigma @see getPolySigma */ + virtual void setPolySigma(double val) = 0; + /** @see setFlags */ + virtual int getFlags() const = 0; + /** @copybrief getFlags @see getFlags */ + virtual void setFlags(int val) = 0; + }; + CV_EXPORTS Ptr createOptFlow_Farneback(); + CV_EXPORTS Ptr createOptFlow_Farneback_CUDA(); + + +// CV_EXPORTS Ptr createOptFlow_Simple(); + + + class CV_EXPORTS DualTVL1OpticalFlow : public virtual DenseOpticalFlowExt + { + public: + /** @see setTau */ + virtual double getTau() const = 0; + /** @copybrief getTau @see getTau */ + virtual void setTau(double val) = 0; + /** @see setLambda */ + virtual double getLambda() const = 0; + /** @copybrief getLambda @see getLambda */ + virtual void setLambda(double val) = 0; + /** @see setTheta */ + virtual double getTheta() const = 0; + /** @copybrief getTheta @see getTheta */ + virtual void setTheta(double val) = 0; + /** @see setScalesNumber */ + virtual int getScalesNumber() const = 0; + /** @copybrief getScalesNumber @see getScalesNumber */ + virtual void setScalesNumber(int val) = 0; + /** @see setWarpingsNumber */ + virtual int getWarpingsNumber() const = 0; + /** @copybrief getWarpingsNumber @see getWarpingsNumber */ + virtual void setWarpingsNumber(int val) = 0; + /** @see setEpsilon */ + virtual double getEpsilon() const = 0; + /** @copybrief getEpsilon @see getEpsilon */ + virtual void setEpsilon(double val) = 0; + /** @see setIterations */ + virtual int getIterations() const = 0; + /** @copybrief getIterations @see getIterations */ + virtual void setIterations(int val) = 0; + /** @see setUseInitialFlow */ + virtual bool getUseInitialFlow() const = 0; + /** @copybrief getUseInitialFlow @see getUseInitialFlow */ + virtual void setUseInitialFlow(bool val) = 0; + }; + CV_EXPORTS Ptr createOptFlow_DualTVL1(); + CV_EXPORTS Ptr createOptFlow_DualTVL1_CUDA(); + + + class CV_EXPORTS BroxOpticalFlow : public virtual DenseOpticalFlowExt + { + public: + //! @brief Flow smoothness + /** @see setAlpha */ + virtual double getAlpha() const = 0; + /** @copybrief getAlpha @see getAlpha */ + virtual void setAlpha(double val) = 0; + //! @brief Gradient constancy importance + /** @see setGamma */ + virtual double getGamma() const = 0; + /** @copybrief getGamma @see getGamma */ + virtual void setGamma(double val) = 0; + //! @brief Pyramid scale factor + /** @see setScaleFactor */ + virtual double getScaleFactor() const = 0; + /** @copybrief getScaleFactor @see getScaleFactor */ + virtual void setScaleFactor(double val) = 0; + //! @brief Number of lagged non-linearity iterations (inner loop) + /** @see setInnerIterations */ + virtual int getInnerIterations() const = 0; + /** @copybrief getInnerIterations @see getInnerIterations */ + virtual void setInnerIterations(int val) = 0; + //! @brief Number of warping iterations (number of pyramid levels) + /** @see setOuterIterations */ + virtual int getOuterIterations() const = 0; + /** @copybrief getOuterIterations @see getOuterIterations */ + virtual void setOuterIterations(int val) = 0; + //! @brief Number of linear system solver iterations + /** @see setSolverIterations */ + virtual int getSolverIterations() const = 0; + /** @copybrief getSolverIterations @see getSolverIterations */ + virtual void setSolverIterations(int val) = 0; + }; + CV_EXPORTS Ptr createOptFlow_Brox_CUDA(); + + + class PyrLKOpticalFlow : public virtual DenseOpticalFlowExt + { + public: + /** @see setWindowSize */ + virtual int getWindowSize() const = 0; + /** @copybrief getWindowSize @see getWindowSize */ + virtual void setWindowSize(int val) = 0; + /** @see setMaxLevel */ + virtual int getMaxLevel() const = 0; + /** @copybrief getMaxLevel @see getMaxLevel */ + virtual void setMaxLevel(int val) = 0; + /** @see setIterations */ + virtual int getIterations() const = 0; + /** @copybrief getIterations @see getIterations */ + virtual void setIterations(int val) = 0; + }; + CV_EXPORTS Ptr createOptFlow_PyrLK_CUDA(); + +//! @} + + } +} + +#endif // OPENCV_SUPERRES_OPTICAL_FLOW_HPP diff --git a/3rdparty/opencv/include/opencv2/video.hpp b/3rdparty/opencv/include/opencv2/video.hpp new file mode 100644 index 00000000..aa644a93 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/video.hpp @@ -0,0 +1,63 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEO_HPP +#define OPENCV_VIDEO_HPP + +/** + @defgroup video Video Analysis + @{ + @defgroup video_motion Motion Analysis + @defgroup video_track Object Tracking + @defgroup video_c C API + @} +*/ + +#include "opencv2/video/tracking.hpp" +#include "opencv2/video/background_segm.hpp" + +#ifndef DISABLE_OPENCV_24_COMPATIBILITY +#include "opencv2/video/tracking_c.h" +#endif + +#endif //OPENCV_VIDEO_HPP diff --git a/3rdparty/opencv/include/opencv2/video/background_segm.hpp b/3rdparty/opencv/include/opencv2/video/background_segm.hpp new file mode 100644 index 00000000..e1dfa15a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/video/background_segm.hpp @@ -0,0 +1,317 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_BACKGROUND_SEGM_HPP +#define OPENCV_BACKGROUND_SEGM_HPP + +#include "opencv2/core.hpp" + +namespace cv +{ + +//! @addtogroup video_motion +//! @{ + +/** @brief Base class for background/foreground segmentation. : + +The class is only used to define the common interface for the whole family of background/foreground +segmentation algorithms. + */ +class CV_EXPORTS_W BackgroundSubtractor : public Algorithm +{ +public: + /** @brief Computes a foreground mask. + + @param image Next video frame. + @param fgmask The output foreground mask as an 8-bit binary image. + @param learningRate The value between 0 and 1 that indicates how fast the background model is + learnt. Negative parameter value makes the algorithm to use some automatically chosen learning + rate. 0 means that the background model is not updated at all, 1 means that the background model + is completely reinitialized from the last frame. + */ + CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) = 0; + + /** @brief Computes a background image. + + @param backgroundImage The output background image. + + @note Sometimes the background image can be very blurry, as it contain the average background + statistics. + */ + CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const = 0; +}; + + +/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm. + +The class implements the Gaussian mixture model background subtraction described in @cite Zivkovic2004 +and @cite Zivkovic2006 . + */ +class CV_EXPORTS_W BackgroundSubtractorMOG2 : public BackgroundSubtractor +{ +public: + /** @brief Returns the number of last frames that affect the background model + */ + CV_WRAP virtual int getHistory() const = 0; + /** @brief Sets the number of last frames that affect the background model + */ + CV_WRAP virtual void setHistory(int history) = 0; + + /** @brief Returns the number of gaussian components in the background model + */ + CV_WRAP virtual int getNMixtures() const = 0; + /** @brief Sets the number of gaussian components in the background model. + + The model needs to be reinitalized to reserve memory. + */ + CV_WRAP virtual void setNMixtures(int nmixtures) = 0;//needs reinitialization! + + /** @brief Returns the "background ratio" parameter of the algorithm + + If a foreground pixel keeps semi-constant value for about backgroundRatio\*history frames, it's + considered background and added to the model as a center of a new component. It corresponds to TB + parameter in the paper. + */ + CV_WRAP virtual double getBackgroundRatio() const = 0; + /** @brief Sets the "background ratio" parameter of the algorithm + */ + CV_WRAP virtual void setBackgroundRatio(double ratio) = 0; + + /** @brief Returns the variance threshold for the pixel-model match + + The main threshold on the squared Mahalanobis distance to decide if the sample is well described by + the background model or not. Related to Cthr from the paper. + */ + CV_WRAP virtual double getVarThreshold() const = 0; + /** @brief Sets the variance threshold for the pixel-model match + */ + CV_WRAP virtual void setVarThreshold(double varThreshold) = 0; + + /** @brief Returns the variance threshold for the pixel-model match used for new mixture component generation + + Threshold for the squared Mahalanobis distance that helps decide when a sample is close to the + existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it + is considered foreground or added as a new component. 3 sigma =\> Tg=3\*3=9 is default. A smaller Tg + value generates more components. A higher Tg value may result in a small number of components but + they can grow too large. + */ + CV_WRAP virtual double getVarThresholdGen() const = 0; + /** @brief Sets the variance threshold for the pixel-model match used for new mixture component generation + */ + CV_WRAP virtual void setVarThresholdGen(double varThresholdGen) = 0; + + /** @brief Returns the initial variance of each gaussian component + */ + CV_WRAP virtual double getVarInit() const = 0; + /** @brief Sets the initial variance of each gaussian component + */ + CV_WRAP virtual void setVarInit(double varInit) = 0; + + CV_WRAP virtual double getVarMin() const = 0; + CV_WRAP virtual void setVarMin(double varMin) = 0; + + CV_WRAP virtual double getVarMax() const = 0; + CV_WRAP virtual void setVarMax(double varMax) = 0; + + /** @brief Returns the complexity reduction threshold + + This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05 + is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the + standard Stauffer&Grimson algorithm. + */ + CV_WRAP virtual double getComplexityReductionThreshold() const = 0; + /** @brief Sets the complexity reduction threshold + */ + CV_WRAP virtual void setComplexityReductionThreshold(double ct) = 0; + + /** @brief Returns the shadow detection flag + + If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for + details. + */ + CV_WRAP virtual bool getDetectShadows() const = 0; + /** @brief Enables or disables shadow detection + */ + CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0; + + /** @brief Returns the shadow value + + Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0 + in the mask always means background, 255 means foreground. + */ + CV_WRAP virtual int getShadowValue() const = 0; + /** @brief Sets the shadow value + */ + CV_WRAP virtual void setShadowValue(int value) = 0; + + /** @brief Returns the shadow threshold + + A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in + the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel + is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara, + *Detecting Moving Shadows...*, IEEE PAMI,2003. + */ + CV_WRAP virtual double getShadowThreshold() const = 0; + /** @brief Sets the shadow threshold + */ + CV_WRAP virtual void setShadowThreshold(double threshold) = 0; + + /** @brief Computes a foreground mask. + + @param image Next video frame. Floating point frame will be used without scaling and should be in range \f$[0,255]\f$. + @param fgmask The output foreground mask as an 8-bit binary image. + @param learningRate The value between 0 and 1 that indicates how fast the background model is + learnt. Negative parameter value makes the algorithm to use some automatically chosen learning + rate. 0 means that the background model is not updated at all, 1 means that the background model + is completely reinitialized from the last frame. + */ + CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0; +}; + +/** @brief Creates MOG2 Background Subtractor + +@param history Length of the history. +@param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model +to decide whether a pixel is well described by the background model. This parameter does not +affect the background update. +@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the +speed a bit, so if you do not need this feature, set the parameter to false. + */ +CV_EXPORTS_W Ptr + createBackgroundSubtractorMOG2(int history=500, double varThreshold=16, + bool detectShadows=true); + +/** @brief K-nearest neighbours - based Background/Foreground Segmentation Algorithm. + +The class implements the K-nearest neighbours background subtraction described in @cite Zivkovic2006 . +Very efficient if number of foreground pixels is low. + */ +class CV_EXPORTS_W BackgroundSubtractorKNN : public BackgroundSubtractor +{ +public: + /** @brief Returns the number of last frames that affect the background model + */ + CV_WRAP virtual int getHistory() const = 0; + /** @brief Sets the number of last frames that affect the background model + */ + CV_WRAP virtual void setHistory(int history) = 0; + + /** @brief Returns the number of data samples in the background model + */ + CV_WRAP virtual int getNSamples() const = 0; + /** @brief Sets the number of data samples in the background model. + + The model needs to be reinitalized to reserve memory. + */ + CV_WRAP virtual void setNSamples(int _nN) = 0;//needs reinitialization! + + /** @brief Returns the threshold on the squared distance between the pixel and the sample + + The threshold on the squared distance between the pixel and the sample to decide whether a pixel is + close to a data sample. + */ + CV_WRAP virtual double getDist2Threshold() const = 0; + /** @brief Sets the threshold on the squared distance + */ + CV_WRAP virtual void setDist2Threshold(double _dist2Threshold) = 0; + + /** @brief Returns the number of neighbours, the k in the kNN. + + K is the number of samples that need to be within dist2Threshold in order to decide that that + pixel is matching the kNN background model. + */ + CV_WRAP virtual int getkNNSamples() const = 0; + /** @brief Sets the k in the kNN. How many nearest neighbours need to match. + */ + CV_WRAP virtual void setkNNSamples(int _nkNN) = 0; + + /** @brief Returns the shadow detection flag + + If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for + details. + */ + CV_WRAP virtual bool getDetectShadows() const = 0; + /** @brief Enables or disables shadow detection + */ + CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0; + + /** @brief Returns the shadow value + + Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0 + in the mask always means background, 255 means foreground. + */ + CV_WRAP virtual int getShadowValue() const = 0; + /** @brief Sets the shadow value + */ + CV_WRAP virtual void setShadowValue(int value) = 0; + + /** @brief Returns the shadow threshold + + A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in + the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel + is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara, + *Detecting Moving Shadows...*, IEEE PAMI,2003. + */ + CV_WRAP virtual double getShadowThreshold() const = 0; + /** @brief Sets the shadow threshold + */ + CV_WRAP virtual void setShadowThreshold(double threshold) = 0; +}; + +/** @brief Creates KNN Background Subtractor + +@param history Length of the history. +@param dist2Threshold Threshold on the squared distance between the pixel and the sample to decide +whether a pixel is close to that sample. This parameter does not affect the background update. +@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the +speed a bit, so if you do not need this feature, set the parameter to false. + */ +CV_EXPORTS_W Ptr + createBackgroundSubtractorKNN(int history=500, double dist2Threshold=400.0, + bool detectShadows=true); + +//! @} video_motion + +} // cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/video/tracking.hpp b/3rdparty/opencv/include/opencv2/video/tracking.hpp new file mode 100644 index 00000000..e8566faa --- /dev/null +++ b/3rdparty/opencv/include/opencv2/video/tracking.hpp @@ -0,0 +1,654 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_TRACKING_HPP +#define OPENCV_TRACKING_HPP + +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" + +namespace cv +{ + +//! @addtogroup video_track +//! @{ + +enum { OPTFLOW_USE_INITIAL_FLOW = 4, + OPTFLOW_LK_GET_MIN_EIGENVALS = 8, + OPTFLOW_FARNEBACK_GAUSSIAN = 256 + }; + +/** @brief Finds an object center, size, and orientation. + +@param probImage Back projection of the object histogram. See calcBackProject. +@param window Initial search window. +@param criteria Stop criteria for the underlying meanShift. +returns +(in old interfaces) Number of iterations CAMSHIFT took to converge +The function implements the CAMSHIFT object tracking algorithm @cite Bradski98 . First, it finds an +object center using meanShift and then adjusts the window size and finds the optimal rotation. The +function returns the rotated rectangle structure that includes the object position, size, and +orientation. The next position of the search window can be obtained with RotatedRect::boundingRect() + +See the OpenCV sample camshiftdemo.c that tracks colored objects. + +@note +- (Python) A sample explaining the camshift tracking algorithm can be found at + opencv_source_code/samples/python/camshift.py + */ +CV_EXPORTS_W RotatedRect CamShift( InputArray probImage, CV_IN_OUT Rect& window, + TermCriteria criteria ); +/** @example samples/cpp/camshiftdemo.cpp +An example using the mean-shift tracking algorithm +*/ + +/** @brief Finds an object on a back projection image. + +@param probImage Back projection of the object histogram. See calcBackProject for details. +@param window Initial search window. +@param criteria Stop criteria for the iterative search algorithm. +returns +: Number of iterations CAMSHIFT took to converge. +The function implements the iterative object search algorithm. It takes the input back projection of +an object and the initial position. The mass center in window of the back projection image is +computed and the search window center shifts to the mass center. The procedure is repeated until the +specified number of iterations criteria.maxCount is done or until the window center shifts by less +than criteria.epsilon. The algorithm is used inside CamShift and, unlike CamShift , the search +window size or orientation do not change during the search. You can simply pass the output of +calcBackProject to this function. But better results can be obtained if you pre-filter the back +projection and remove the noise. For example, you can do this by retrieving connected components +with findContours , throwing away contours with small area ( contourArea ), and rendering the +remaining contours with drawContours. + + */ +CV_EXPORTS_W int meanShift( InputArray probImage, CV_IN_OUT Rect& window, TermCriteria criteria ); + +/** @brief Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK. + +@param img 8-bit input image. +@param pyramid output pyramid. +@param winSize window size of optical flow algorithm. Must be not less than winSize argument of +calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels. +@param maxLevel 0-based maximal pyramid level number. +@param withDerivatives set to precompute gradients for the every pyramid level. If pyramid is +constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally. +@param pyrBorder the border mode for pyramid layers. +@param derivBorder the border mode for gradients. +@param tryReuseInputImage put ROI of input image into the pyramid if possible. You can pass false +to force data copying. +@return number of levels in constructed pyramid. Can be less than maxLevel. + */ +CV_EXPORTS_W int buildOpticalFlowPyramid( InputArray img, OutputArrayOfArrays pyramid, + Size winSize, int maxLevel, bool withDerivatives = true, + int pyrBorder = BORDER_REFLECT_101, + int derivBorder = BORDER_CONSTANT, + bool tryReuseInputImage = true ); + +/** @example samples/cpp/lkdemo.cpp +An example using the Lucas-Kanade optical flow algorithm +*/ + +/** @brief Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with +pyramids. + +@param prevImg first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid. +@param nextImg second input image or pyramid of the same size and the same type as prevImg. +@param prevPts vector of 2D points for which the flow needs to be found; point coordinates must be +single-precision floating-point numbers. +@param nextPts output vector of 2D points (with single-precision floating-point coordinates) +containing the calculated new positions of input features in the second image; when +OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input. +@param status output status vector (of unsigned chars); each element of the vector is set to 1 if +the flow for the corresponding features has been found, otherwise, it is set to 0. +@param err output vector of errors; each element of the vector is set to an error for the +corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't +found then the error is not defined (use the status parameter to find such cases). +@param winSize size of the search window at each pyramid level. +@param maxLevel 0-based maximal pyramid level number; if set to 0, pyramids are not used (single +level), if set to 1, two levels are used, and so on; if pyramids are passed to input then +algorithm will use as many levels as pyramids have but no more than maxLevel. +@param criteria parameter, specifying the termination criteria of the iterative search algorithm +(after the specified maximum number of iterations criteria.maxCount or when the search window +moves by less than criteria.epsilon. +@param flags operation flags: + - **OPTFLOW_USE_INITIAL_FLOW** uses initial estimations, stored in nextPts; if the flag is + not set, then prevPts is copied to nextPts and is considered the initial estimate. + - **OPTFLOW_LK_GET_MIN_EIGENVALS** use minimum eigen values as an error measure (see + minEigThreshold description); if the flag is not set, then L1 distance between patches + around the original and a moved point, divided by number of pixels in a window, is used as a + error measure. +@param minEigThreshold the algorithm calculates the minimum eigen value of a 2x2 normal matrix of +optical flow equations (this matrix is called a spatial gradient matrix in @cite Bouguet00), divided +by number of pixels in a window; if this value is less than minEigThreshold, then a corresponding +feature is filtered out and its flow is not processed, so it allows to remove bad points and get a +performance boost. + +The function implements a sparse iterative version of the Lucas-Kanade optical flow in pyramids. See +@cite Bouguet00 . The function is parallelized with the TBB library. + +@note + +- An example using the Lucas-Kanade optical flow algorithm can be found at + opencv_source_code/samples/cpp/lkdemo.cpp +- (Python) An example using the Lucas-Kanade optical flow algorithm can be found at + opencv_source_code/samples/python/lk_track.py +- (Python) An example using the Lucas-Kanade tracker for homography matching can be found at + opencv_source_code/samples/python/lk_homography.py + */ +CV_EXPORTS_W void calcOpticalFlowPyrLK( InputArray prevImg, InputArray nextImg, + InputArray prevPts, InputOutputArray nextPts, + OutputArray status, OutputArray err, + Size winSize = Size(21,21), int maxLevel = 3, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), + int flags = 0, double minEigThreshold = 1e-4 ); + +/** @brief Computes a dense optical flow using the Gunnar Farneback's algorithm. + +@param prev first 8-bit single-channel input image. +@param next second input image of the same size and the same type as prev. +@param flow computed flow image that has the same size as prev and type CV_32FC2. +@param pyr_scale parameter, specifying the image scale (\<1) to build pyramids for each image; +pyr_scale=0.5 means a classical pyramid, where each next layer is twice smaller than the previous +one. +@param levels number of pyramid layers including the initial image; levels=1 means that no extra +layers are created and only the original images are used. +@param winsize averaging window size; larger values increase the algorithm robustness to image +noise and give more chances for fast motion detection, but yield more blurred motion field. +@param iterations number of iterations the algorithm does at each pyramid level. +@param poly_n size of the pixel neighborhood used to find polynomial expansion in each pixel; +larger values mean that the image will be approximated with smoother surfaces, yielding more +robust algorithm and more blurred motion field, typically poly_n =5 or 7. +@param poly_sigma standard deviation of the Gaussian that is used to smooth derivatives used as a +basis for the polynomial expansion; for poly_n=5, you can set poly_sigma=1.1, for poly_n=7, a +good value would be poly_sigma=1.5. +@param flags operation flags that can be a combination of the following: + - **OPTFLOW_USE_INITIAL_FLOW** uses the input flow as an initial flow approximation. + - **OPTFLOW_FARNEBACK_GAUSSIAN** uses the Gaussian \f$\texttt{winsize}\times\texttt{winsize}\f$ + filter instead of a box filter of the same size for optical flow estimation; usually, this + option gives z more accurate flow than with a box filter, at the cost of lower speed; + normally, winsize for a Gaussian window should be set to a larger value to achieve the same + level of robustness. + +The function finds an optical flow for each prev pixel using the @cite Farneback2003 algorithm so that + +\f[\texttt{prev} (y,x) \sim \texttt{next} ( y + \texttt{flow} (y,x)[1], x + \texttt{flow} (y,x)[0])\f] + +@note + +- An example using the optical flow algorithm described by Gunnar Farneback can be found at + opencv_source_code/samples/cpp/fback.cpp +- (Python) An example using the optical flow algorithm described by Gunnar Farneback can be + found at opencv_source_code/samples/python/opt_flow.py + */ +CV_EXPORTS_W void calcOpticalFlowFarneback( InputArray prev, InputArray next, InputOutputArray flow, + double pyr_scale, int levels, int winsize, + int iterations, int poly_n, double poly_sigma, + int flags ); + +/** @brief Computes an optimal affine transformation between two 2D point sets. + +@param src First input 2D point set stored in std::vector or Mat, or an image stored in Mat. +@param dst Second input 2D point set of the same size and the same type as A, or another image. +@param fullAffine If true, the function finds an optimal affine transformation with no additional +restrictions (6 degrees of freedom). Otherwise, the class of transformations to choose from is +limited to combinations of translation, rotation, and uniform scaling (4 degrees of freedom). + +The function finds an optimal affine transform *[A|b]* (a 2 x 3 floating-point matrix) that +approximates best the affine transformation between: + +* Two point sets +* Two raster images. In this case, the function first finds some features in the src image and + finds the corresponding features in dst image. After that, the problem is reduced to the first + case. +In case of point sets, the problem is formulated as follows: you need to find a 2x2 matrix *A* and +2x1 vector *b* so that: + +\f[[A^*|b^*] = arg \min _{[A|b]} \sum _i \| \texttt{dst}[i] - A { \texttt{src}[i]}^T - b \| ^2\f] +where src[i] and dst[i] are the i-th points in src and dst, respectively +\f$[A|b]\f$ can be either arbitrary (when fullAffine=true ) or have a form of +\f[\begin{bmatrix} a_{11} & a_{12} & b_1 \\ -a_{12} & a_{11} & b_2 \end{bmatrix}\f] +when fullAffine=false. + +@sa +estimateAffine2D, estimateAffinePartial2D, getAffineTransform, getPerspectiveTransform, findHomography + */ +CV_EXPORTS_W Mat estimateRigidTransform( InputArray src, InputArray dst, bool fullAffine); +CV_EXPORTS_W Mat estimateRigidTransform( InputArray src, InputArray dst, bool fullAffine, int ransacMaxIters, double ransacGoodRatio, + int ransacSize0); + + +enum +{ + MOTION_TRANSLATION = 0, + MOTION_EUCLIDEAN = 1, + MOTION_AFFINE = 2, + MOTION_HOMOGRAPHY = 3 +}; + +/** @brief Computes the Enhanced Correlation Coefficient value between two images @cite EP08 . + +@param templateImage single-channel template image; CV_8U or CV_32F array. +@param inputImage single-channel input image to be warped to provide an image similar to + templateImage, same type as templateImage. +@param inputMask An optional mask to indicate valid values of inputImage. + +@sa +findTransformECC + */ + +CV_EXPORTS_W double computeECC(InputArray templateImage, InputArray inputImage, InputArray inputMask = noArray()); + +/** @example samples/cpp/image_alignment.cpp +An example using the image alignment ECC algorithm +*/ + +/** @brief Finds the geometric transform (warp) between two images in terms of the ECC criterion @cite EP08 . + +@param templateImage single-channel template image; CV_8U or CV_32F array. +@param inputImage single-channel input image which should be warped with the final warpMatrix in +order to provide an image similar to templateImage, same type as templateImage. +@param warpMatrix floating-point \f$2\times 3\f$ or \f$3\times 3\f$ mapping matrix (warp). +@param motionType parameter, specifying the type of motion: + - **MOTION_TRANSLATION** sets a translational motion model; warpMatrix is \f$2\times 3\f$ with + the first \f$2\times 2\f$ part being the unity matrix and the rest two parameters being + estimated. + - **MOTION_EUCLIDEAN** sets a Euclidean (rigid) transformation as motion model; three + parameters are estimated; warpMatrix is \f$2\times 3\f$. + - **MOTION_AFFINE** sets an affine motion model (DEFAULT); six parameters are estimated; + warpMatrix is \f$2\times 3\f$. + - **MOTION_HOMOGRAPHY** sets a homography as a motion model; eight parameters are + estimated;\`warpMatrix\` is \f$3\times 3\f$. +@param criteria parameter, specifying the termination criteria of the ECC algorithm; +criteria.epsilon defines the threshold of the increment in the correlation coefficient between two +iterations (a negative criteria.epsilon makes criteria.maxcount the only termination criterion). +Default values are shown in the declaration above. +@param inputMask An optional mask to indicate valid values of inputImage. +@param gaussFiltSize An optional value indicating size of gaussian blur filter; (DEFAULT: 5) + +The function estimates the optimum transformation (warpMatrix) with respect to ECC criterion +(@cite EP08), that is + +\f[\texttt{warpMatrix} = \texttt{warpMatrix} = \arg\max_{W} \texttt{ECC}(\texttt{templateImage}(x,y),\texttt{inputImage}(x',y'))\f] + +where + +\f[\begin{bmatrix} x' \\ y' \end{bmatrix} = W \cdot \begin{bmatrix} x \\ y \\ 1 \end{bmatrix}\f] + +(the equation holds with homogeneous coordinates for homography). It returns the final enhanced +correlation coefficient, that is the correlation coefficient between the template image and the +final warped input image. When a \f$3\times 3\f$ matrix is given with motionType =0, 1 or 2, the third +row is ignored. + +Unlike findHomography and estimateRigidTransform, the function findTransformECC implements an +area-based alignment that builds on intensity similarities. In essence, the function updates the +initial transformation that roughly aligns the images. If this information is missing, the identity +warp (unity matrix) is used as an initialization. Note that if images undergo strong +displacements/rotations, an initial transformation that roughly aligns the images is necessary +(e.g., a simple euclidean/similarity transform that allows for the images showing the same image +content approximately). Use inverse warping in the second image to take an image close to the first +one, i.e. use the flag WARP_INVERSE_MAP with warpAffine or warpPerspective. See also the OpenCV +sample image_alignment.cpp that demonstrates the use of the function. Note that the function throws +an exception if algorithm does not converges. + +@sa +computeECC, estimateAffine2D, estimateAffinePartial2D, findHomography + */ +CV_EXPORTS_W double findTransformECC( InputArray templateImage, InputArray inputImage, + InputOutputArray warpMatrix, int motionType, + TermCriteria criteria, + InputArray inputMask, int gaussFiltSize); + +/** @overload */ +CV_EXPORTS +double findTransformECC(InputArray templateImage, InputArray inputImage, + InputOutputArray warpMatrix, int motionType = MOTION_AFFINE, + TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001), + InputArray inputMask = noArray()); + +/** @example samples/cpp/kalman.cpp +An example using the standard Kalman filter +*/ + +/** @brief Kalman filter class. + +The class implements a standard Kalman filter , +@cite Welch95 . However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get +an extended Kalman filter functionality. +@note In C API when CvKalman\* kalmanFilter structure is not needed anymore, it should be released +with cvReleaseKalman(&kalmanFilter) + */ +class CV_EXPORTS_W KalmanFilter +{ +public: + CV_WRAP KalmanFilter(); + /** @overload + @param dynamParams Dimensionality of the state. + @param measureParams Dimensionality of the measurement. + @param controlParams Dimensionality of the control vector. + @param type Type of the created matrices that should be CV_32F or CV_64F. + */ + CV_WRAP KalmanFilter( int dynamParams, int measureParams, int controlParams = 0, int type = CV_32F ); + + /** @brief Re-initializes Kalman filter. The previous content is destroyed. + + @param dynamParams Dimensionality of the state. + @param measureParams Dimensionality of the measurement. + @param controlParams Dimensionality of the control vector. + @param type Type of the created matrices that should be CV_32F or CV_64F. + */ + void init( int dynamParams, int measureParams, int controlParams = 0, int type = CV_32F ); + + /** @brief Computes a predicted state. + + @param control The optional input control + */ + CV_WRAP const Mat& predict( const Mat& control = Mat() ); + + /** @brief Updates the predicted state from the measurement. + + @param measurement The measured system parameters + */ + CV_WRAP const Mat& correct( const Mat& measurement ); + + CV_PROP_RW Mat statePre; //!< predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k) + CV_PROP_RW Mat statePost; //!< corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) + CV_PROP_RW Mat transitionMatrix; //!< state transition matrix (A) + CV_PROP_RW Mat controlMatrix; //!< control matrix (B) (not used if there is no control) + CV_PROP_RW Mat measurementMatrix; //!< measurement matrix (H) + CV_PROP_RW Mat processNoiseCov; //!< process noise covariance matrix (Q) + CV_PROP_RW Mat measurementNoiseCov;//!< measurement noise covariance matrix (R) + CV_PROP_RW Mat errorCovPre; //!< priori error estimate covariance matrix (P'(k)): P'(k)=A*P(k-1)*At + Q)*/ + CV_PROP_RW Mat gain; //!< Kalman gain matrix (K(k)): K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R) + CV_PROP_RW Mat errorCovPost; //!< posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P'(k) + + // temporary matrices + Mat temp1; + Mat temp2; + Mat temp3; + Mat temp4; + Mat temp5; +}; + + +class CV_EXPORTS_W DenseOpticalFlow : public Algorithm +{ +public: + /** @brief Calculates an optical flow. + + @param I0 first 8-bit single-channel input image. + @param I1 second input image of the same size and the same type as prev. + @param flow computed flow image that has the same size as prev and type CV_32FC2. + */ + CV_WRAP virtual void calc( InputArray I0, InputArray I1, InputOutputArray flow ) = 0; + /** @brief Releases all inner buffers. + */ + CV_WRAP virtual void collectGarbage() = 0; +}; + +/** @brief Base interface for sparse optical flow algorithms. + */ +class CV_EXPORTS_W SparseOpticalFlow : public Algorithm +{ +public: + /** @brief Calculates a sparse optical flow. + + @param prevImg First input image. + @param nextImg Second input image of the same size and the same type as prevImg. + @param prevPts Vector of 2D points for which the flow needs to be found. + @param nextPts Output vector of 2D points containing the calculated new positions of input features in the second image. + @param status Output status vector. Each element of the vector is set to 1 if the + flow for the corresponding features has been found. Otherwise, it is set to 0. + @param err Optional output vector that contains error response for each point (inverse confidence). + */ + CV_WRAP virtual void calc(InputArray prevImg, InputArray nextImg, + InputArray prevPts, InputOutputArray nextPts, + OutputArray status, + OutputArray err = cv::noArray()) = 0; +}; + +/** @brief "Dual TV L1" Optical Flow Algorithm. + +The class implements the "Dual TV L1" optical flow algorithm described in @cite Zach2007 and +@cite Javier2012 . +Here are important members of the class that control the algorithm, which you can set after +constructing the class instance: + +- member double tau + Time step of the numerical scheme. + +- member double lambda + Weight parameter for the data term, attachment parameter. This is the most relevant + parameter, which determines the smoothness of the output. The smaller this parameter is, + the smoother the solutions we obtain. It depends on the range of motions of the images, so + its value should be adapted to each image sequence. + +- member double theta + Weight parameter for (u - v)\^2, tightness parameter. It serves as a link between the + attachment and the regularization terms. In theory, it should have a small value in order + to maintain both parts in correspondence. The method is stable for a large range of values + of this parameter. + +- member int nscales + Number of scales used to create the pyramid of images. + +- member int warps + Number of warpings per scale. Represents the number of times that I1(x+u0) and grad( + I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the + method. It also affects the running time, so it is a compromise between speed and + accuracy. + +- member double epsilon + Stopping criterion threshold used in the numerical scheme, which is a trade-off between + precision and running time. A small value will yield more accurate solutions at the + expense of a slower convergence. + +- member int iterations + Stopping criterion iterations number used in the numerical scheme. + +C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow". +Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation". +*/ +class CV_EXPORTS_W DualTVL1OpticalFlow : public DenseOpticalFlow +{ +public: + //! @brief Time step of the numerical scheme + /** @see setTau */ + CV_WRAP virtual double getTau() const = 0; + /** @copybrief getTau @see getTau */ + CV_WRAP virtual void setTau(double val) = 0; + //! @brief Weight parameter for the data term, attachment parameter + /** @see setLambda */ + CV_WRAP virtual double getLambda() const = 0; + /** @copybrief getLambda @see getLambda */ + CV_WRAP virtual void setLambda(double val) = 0; + //! @brief Weight parameter for (u - v)^2, tightness parameter + /** @see setTheta */ + CV_WRAP virtual double getTheta() const = 0; + /** @copybrief getTheta @see getTheta */ + CV_WRAP virtual void setTheta(double val) = 0; + //! @brief coefficient for additional illumination variation term + /** @see setGamma */ + CV_WRAP virtual double getGamma() const = 0; + /** @copybrief getGamma @see getGamma */ + CV_WRAP virtual void setGamma(double val) = 0; + //! @brief Number of scales used to create the pyramid of images + /** @see setScalesNumber */ + CV_WRAP virtual int getScalesNumber() const = 0; + /** @copybrief getScalesNumber @see getScalesNumber */ + CV_WRAP virtual void setScalesNumber(int val) = 0; + //! @brief Number of warpings per scale + /** @see setWarpingsNumber */ + CV_WRAP virtual int getWarpingsNumber() const = 0; + /** @copybrief getWarpingsNumber @see getWarpingsNumber */ + CV_WRAP virtual void setWarpingsNumber(int val) = 0; + //! @brief Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time + /** @see setEpsilon */ + CV_WRAP virtual double getEpsilon() const = 0; + /** @copybrief getEpsilon @see getEpsilon */ + CV_WRAP virtual void setEpsilon(double val) = 0; + //! @brief Inner iterations (between outlier filtering) used in the numerical scheme + /** @see setInnerIterations */ + CV_WRAP virtual int getInnerIterations() const = 0; + /** @copybrief getInnerIterations @see getInnerIterations */ + CV_WRAP virtual void setInnerIterations(int val) = 0; + //! @brief Outer iterations (number of inner loops) used in the numerical scheme + /** @see setOuterIterations */ + CV_WRAP virtual int getOuterIterations() const = 0; + /** @copybrief getOuterIterations @see getOuterIterations */ + CV_WRAP virtual void setOuterIterations(int val) = 0; + //! @brief Use initial flow + /** @see setUseInitialFlow */ + CV_WRAP virtual bool getUseInitialFlow() const = 0; + /** @copybrief getUseInitialFlow @see getUseInitialFlow */ + CV_WRAP virtual void setUseInitialFlow(bool val) = 0; + //! @brief Step between scales (<1) + /** @see setScaleStep */ + CV_WRAP virtual double getScaleStep() const = 0; + /** @copybrief getScaleStep @see getScaleStep */ + CV_WRAP virtual void setScaleStep(double val) = 0; + //! @brief Median filter kernel size (1 = no filter) (3 or 5) + /** @see setMedianFiltering */ + CV_WRAP virtual int getMedianFiltering() const = 0; + /** @copybrief getMedianFiltering @see getMedianFiltering */ + CV_WRAP virtual void setMedianFiltering(int val) = 0; + + /** @brief Creates instance of cv::DualTVL1OpticalFlow*/ + CV_WRAP static Ptr create( + double tau = 0.25, + double lambda = 0.15, + double theta = 0.3, + int nscales = 5, + int warps = 5, + double epsilon = 0.01, + int innnerIterations = 30, + int outerIterations = 10, + double scaleStep = 0.8, + double gamma = 0.0, + int medianFiltering = 5, + bool useInitialFlow = false); +}; + +/** @brief Creates instance of cv::DenseOpticalFlow +*/ +CV_EXPORTS_W Ptr createOptFlow_DualTVL1(); + +/** @brief Class computing a dense optical flow using the Gunnar Farneback's algorithm. + */ +class CV_EXPORTS_W FarnebackOpticalFlow : public DenseOpticalFlow +{ +public: + CV_WRAP virtual int getNumLevels() const = 0; + CV_WRAP virtual void setNumLevels(int numLevels) = 0; + + CV_WRAP virtual double getPyrScale() const = 0; + CV_WRAP virtual void setPyrScale(double pyrScale) = 0; + + CV_WRAP virtual bool getFastPyramids() const = 0; + CV_WRAP virtual void setFastPyramids(bool fastPyramids) = 0; + + CV_WRAP virtual int getWinSize() const = 0; + CV_WRAP virtual void setWinSize(int winSize) = 0; + + CV_WRAP virtual int getNumIters() const = 0; + CV_WRAP virtual void setNumIters(int numIters) = 0; + + CV_WRAP virtual int getPolyN() const = 0; + CV_WRAP virtual void setPolyN(int polyN) = 0; + + CV_WRAP virtual double getPolySigma() const = 0; + CV_WRAP virtual void setPolySigma(double polySigma) = 0; + + CV_WRAP virtual int getFlags() const = 0; + CV_WRAP virtual void setFlags(int flags) = 0; + + CV_WRAP static Ptr create( + int numLevels = 5, + double pyrScale = 0.5, + bool fastPyramids = false, + int winSize = 13, + int numIters = 10, + int polyN = 5, + double polySigma = 1.1, + int flags = 0); +}; + + +/** @brief Class used for calculating a sparse optical flow. + +The class can calculate an optical flow for a sparse feature set using the +iterative Lucas-Kanade method with pyramids. + +@sa calcOpticalFlowPyrLK + +*/ +class CV_EXPORTS_W SparsePyrLKOpticalFlow : public SparseOpticalFlow +{ +public: + CV_WRAP virtual Size getWinSize() const = 0; + CV_WRAP virtual void setWinSize(Size winSize) = 0; + + CV_WRAP virtual int getMaxLevel() const = 0; + CV_WRAP virtual void setMaxLevel(int maxLevel) = 0; + + CV_WRAP virtual TermCriteria getTermCriteria() const = 0; + CV_WRAP virtual void setTermCriteria(TermCriteria& crit) = 0; + + CV_WRAP virtual int getFlags() const = 0; + CV_WRAP virtual void setFlags(int flags) = 0; + + CV_WRAP virtual double getMinEigThreshold() const = 0; + CV_WRAP virtual void setMinEigThreshold(double minEigThreshold) = 0; + + CV_WRAP static Ptr create( + Size winSize = Size(21, 21), + int maxLevel = 3, TermCriteria crit = + TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), + int flags = 0, + double minEigThreshold = 1e-4); +}; + +//! @} video_track + +} // cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/video/tracking_c.h b/3rdparty/opencv/include/opencv2/video/tracking_c.h new file mode 100644 index 00000000..3e32fbd0 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/video/tracking_c.h @@ -0,0 +1,232 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_TRACKING_C_H +#define OPENCV_TRACKING_C_H + +#include "opencv2/imgproc/types_c.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/** @addtogroup video_c + @{ +*/ + +/****************************************************************************************\ +* Motion Analysis * +\****************************************************************************************/ + +/************************************ optical flow ***************************************/ + +#define CV_LKFLOW_PYR_A_READY 1 +#define CV_LKFLOW_PYR_B_READY 2 +#define CV_LKFLOW_INITIAL_GUESSES 4 +#define CV_LKFLOW_GET_MIN_EIGENVALS 8 + +/* It is Lucas & Kanade method, modified to use pyramids. + Also it does several iterations to get optical flow for + every point at every pyramid level. + Calculates optical flow between two images for certain set of points (i.e. + it is a "sparse" optical flow, which is opposite to the previous 3 methods) */ +CVAPI(void) cvCalcOpticalFlowPyrLK( const CvArr* prev, const CvArr* curr, + CvArr* prev_pyr, CvArr* curr_pyr, + const CvPoint2D32f* prev_features, + CvPoint2D32f* curr_features, + int count, + CvSize win_size, + int level, + char* status, + float* track_error, + CvTermCriteria criteria, + int flags ); + + +/* Modification of a previous sparse optical flow algorithm to calculate + affine flow */ +CVAPI(void) cvCalcAffineFlowPyrLK( const CvArr* prev, const CvArr* curr, + CvArr* prev_pyr, CvArr* curr_pyr, + const CvPoint2D32f* prev_features, + CvPoint2D32f* curr_features, + float* matrices, int count, + CvSize win_size, int level, + char* status, float* track_error, + CvTermCriteria criteria, int flags ); + +/* Estimate rigid transformation between 2 images or 2 point sets */ +CVAPI(int) cvEstimateRigidTransform( const CvArr* A, const CvArr* B, + CvMat* M, int full_affine ); + +/* Estimate optical flow for each pixel using the two-frame G. Farneback algorithm */ +CVAPI(void) cvCalcOpticalFlowFarneback( const CvArr* prev, const CvArr* next, + CvArr* flow, double pyr_scale, int levels, + int winsize, int iterations, int poly_n, + double poly_sigma, int flags ); + +/********************************* motion templates *************************************/ + +/****************************************************************************************\ +* All the motion template functions work only with single channel images. * +* Silhouette image must have depth IPL_DEPTH_8U or IPL_DEPTH_8S * +* Motion history image must have depth IPL_DEPTH_32F, * +* Gradient mask - IPL_DEPTH_8U or IPL_DEPTH_8S, * +* Motion orientation image - IPL_DEPTH_32F * +* Segmentation mask - IPL_DEPTH_32F * +* All the angles are in degrees, all the times are in milliseconds * +\****************************************************************************************/ + +/* Updates motion history image given motion silhouette */ +CVAPI(void) cvUpdateMotionHistory( const CvArr* silhouette, CvArr* mhi, + double timestamp, double duration ); + +/* Calculates gradient of the motion history image and fills + a mask indicating where the gradient is valid */ +CVAPI(void) cvCalcMotionGradient( const CvArr* mhi, CvArr* mask, CvArr* orientation, + double delta1, double delta2, + int aperture_size CV_DEFAULT(3)); + +/* Calculates average motion direction within a selected motion region + (region can be selected by setting ROIs and/or by composing a valid gradient mask + with the region mask) */ +CVAPI(double) cvCalcGlobalOrientation( const CvArr* orientation, const CvArr* mask, + const CvArr* mhi, double timestamp, + double duration ); + +/* Splits a motion history image into a few parts corresponding to separate independent motions + (e.g. left hand, right hand) */ +CVAPI(CvSeq*) cvSegmentMotion( const CvArr* mhi, CvArr* seg_mask, + CvMemStorage* storage, + double timestamp, double seg_thresh ); + +/****************************************************************************************\ +* Tracking * +\****************************************************************************************/ + +/* Implements CAMSHIFT algorithm - determines object position, size and orientation + from the object histogram back project (extension of meanshift) */ +CVAPI(int) cvCamShift( const CvArr* prob_image, CvRect window, + CvTermCriteria criteria, CvConnectedComp* comp, + CvBox2D* box CV_DEFAULT(NULL) ); + +/* Implements MeanShift algorithm - determines object position + from the object histogram back project */ +CVAPI(int) cvMeanShift( const CvArr* prob_image, CvRect window, + CvTermCriteria criteria, CvConnectedComp* comp ); + +/* +standard Kalman filter (in G. Welch' and G. Bishop's notation): + + x(k)=A*x(k-1)+B*u(k)+w(k) p(w)~N(0,Q) + z(k)=H*x(k)+v(k), p(v)~N(0,R) +*/ +typedef struct CvKalman +{ + int MP; /* number of measurement vector dimensions */ + int DP; /* number of state vector dimensions */ + int CP; /* number of control vector dimensions */ + + /* backward compatibility fields */ +#if 1 + float* PosterState; /* =state_pre->data.fl */ + float* PriorState; /* =state_post->data.fl */ + float* DynamMatr; /* =transition_matrix->data.fl */ + float* MeasurementMatr; /* =measurement_matrix->data.fl */ + float* MNCovariance; /* =measurement_noise_cov->data.fl */ + float* PNCovariance; /* =process_noise_cov->data.fl */ + float* KalmGainMatr; /* =gain->data.fl */ + float* PriorErrorCovariance;/* =error_cov_pre->data.fl */ + float* PosterErrorCovariance;/* =error_cov_post->data.fl */ + float* Temp1; /* temp1->data.fl */ + float* Temp2; /* temp2->data.fl */ +#endif + + CvMat* state_pre; /* predicted state (x'(k)): + x(k)=A*x(k-1)+B*u(k) */ + CvMat* state_post; /* corrected state (x(k)): + x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) */ + CvMat* transition_matrix; /* state transition matrix (A) */ + CvMat* control_matrix; /* control matrix (B) + (it is not used if there is no control)*/ + CvMat* measurement_matrix; /* measurement matrix (H) */ + CvMat* process_noise_cov; /* process noise covariance matrix (Q) */ + CvMat* measurement_noise_cov; /* measurement noise covariance matrix (R) */ + CvMat* error_cov_pre; /* priori error estimate covariance matrix (P'(k)): + P'(k)=A*P(k-1)*At + Q)*/ + CvMat* gain; /* Kalman gain matrix (K(k)): + K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R)*/ + CvMat* error_cov_post; /* posteriori error estimate covariance matrix (P(k)): + P(k)=(I-K(k)*H)*P'(k) */ + CvMat* temp1; /* temporary matrices */ + CvMat* temp2; + CvMat* temp3; + CvMat* temp4; + CvMat* temp5; +} CvKalman; + +/* Creates Kalman filter and sets A, B, Q, R and state to some initial values */ +CVAPI(CvKalman*) cvCreateKalman( int dynam_params, int measure_params, + int control_params CV_DEFAULT(0)); + +/* Releases Kalman filter state */ +CVAPI(void) cvReleaseKalman( CvKalman** kalman); + +/* Updates Kalman filter by time (predicts future state of the system) */ +CVAPI(const CvMat*) cvKalmanPredict( CvKalman* kalman, + const CvMat* control CV_DEFAULT(NULL)); + +/* Updates Kalman filter by measurement + (corrects state of the system and internal matrices) */ +CVAPI(const CvMat*) cvKalmanCorrect( CvKalman* kalman, const CvMat* measurement ); + +#define cvKalmanUpdateByTime cvKalmanPredict +#define cvKalmanUpdateByMeasurement cvKalmanCorrect + +/** @} video_c */ + +#ifdef __cplusplus +} // extern "C" +#endif + + +#endif // OPENCV_TRACKING_C_H diff --git a/3rdparty/opencv/include/opencv2/video/video.hpp b/3rdparty/opencv/include/opencv2/video/video.hpp new file mode 100644 index 00000000..8267b85d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/video/video.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/video.hpp" diff --git a/3rdparty/opencv/include/opencv2/videoio.hpp b/3rdparty/opencv/include/opencv2/videoio.hpp new file mode 100644 index 00000000..cc639d60 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videoio.hpp @@ -0,0 +1,992 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOIO_HPP +#define OPENCV_VIDEOIO_HPP + +#include "opencv2/core.hpp" + +/** + @defgroup videoio Video I/O + + @brief Read and write video or images sequence with OpenCV + + ### See also: + - @ref videoio_overview + - Tutorials: @ref tutorial_table_of_content_videoio + @{ + @defgroup videoio_flags_base Flags for video I/O + @defgroup videoio_flags_others Additional flags for video I/O API backends + @defgroup videoio_c C API for video I/O + @defgroup videoio_ios iOS glue for video I/O + @defgroup videoio_winrt WinRT glue for video I/O + @defgroup videoio_registry Query I/O API backends registry + @} +*/ + +////////////////////////////////// video io ///////////////////////////////// + +typedef struct CvCapture CvCapture; +typedef struct CvVideoWriter CvVideoWriter; + +namespace cv +{ + +//! @addtogroup videoio +//! @{ + +//! @addtogroup videoio_flags_base +//! @{ + + +/** @brief %VideoCapture API backends identifier. + +Select preferred API for a capture object. +To be used in the VideoCapture::VideoCapture() constructor or VideoCapture::open() + +@note Backends are available only if they have been built with your OpenCV binaries. +See @ref videoio_overview for more information. +*/ +enum VideoCaptureAPIs { + CAP_ANY = 0, //!< Auto detect == 0 + CAP_VFW = 200, //!< Video For Windows (platform native) + CAP_V4L = 200, //!< V4L/V4L2 capturing support via libv4l + CAP_V4L2 = CAP_V4L, //!< Same as CAP_V4L + CAP_FIREWIRE = 300, //!< IEEE 1394 drivers + CAP_FIREWARE = CAP_FIREWIRE, //!< Same as CAP_FIREWIRE + CAP_IEEE1394 = CAP_FIREWIRE, //!< Same as CAP_FIREWIRE + CAP_DC1394 = CAP_FIREWIRE, //!< Same as CAP_FIREWIRE + CAP_CMU1394 = CAP_FIREWIRE, //!< Same as CAP_FIREWIRE + CAP_QT = 500, //!< QuickTime + CAP_UNICAP = 600, //!< Unicap drivers + CAP_DSHOW = 700, //!< DirectShow (via videoInput) + CAP_PVAPI = 800, //!< PvAPI, Prosilica GigE SDK + CAP_OPENNI = 900, //!< OpenNI (for Kinect) + CAP_OPENNI_ASUS = 910, //!< OpenNI (for Asus Xtion) + CAP_ANDROID = 1000, //!< Android - not used + CAP_XIAPI = 1100, //!< XIMEA Camera API + CAP_AVFOUNDATION = 1200, //!< AVFoundation framework for iOS (OS X Lion will have the same API) + CAP_GIGANETIX = 1300, //!< Smartek Giganetix GigEVisionSDK + CAP_MSMF = 1400, //!< Microsoft Media Foundation (via videoInput) + CAP_WINRT = 1410, //!< Microsoft Windows Runtime using Media Foundation + CAP_INTELPERC = 1500, //!< Intel Perceptual Computing SDK + CAP_OPENNI2 = 1600, //!< OpenNI2 (for Kinect) + CAP_OPENNI2_ASUS = 1610, //!< OpenNI2 (for Asus Xtion and Occipital Structure sensors) + CAP_GPHOTO2 = 1700, //!< gPhoto2 connection + CAP_GSTREAMER = 1800, //!< GStreamer + CAP_FFMPEG = 1900, //!< Open and record video file or stream using the FFMPEG library + CAP_IMAGES = 2000, //!< OpenCV Image Sequence (e.g. img_%02d.jpg) + CAP_ARAVIS = 2100, //!< Aravis SDK + CAP_OPENCV_MJPEG = 2200, //!< Built-in OpenCV MotionJPEG codec + CAP_INTEL_MFX = 2300, //!< Intel MediaSDK + CAP_XINE = 2400, //!< XINE engine (Linux) + }; + +/** @brief %VideoCapture generic properties identifier. + + Reading / writing properties involves many layers. Some unexpected result might happens along this chain. + Effective behaviour depends from device hardware, driver and API Backend. + @sa videoio_flags_others, VideoCapture::get(), VideoCapture::set() +*/ +enum VideoCaptureProperties { + CAP_PROP_POS_MSEC =0, //!< Current position of the video file in milliseconds. + CAP_PROP_POS_FRAMES =1, //!< 0-based index of the frame to be decoded/captured next. + CAP_PROP_POS_AVI_RATIO =2, //!< Relative position of the video file: 0=start of the film, 1=end of the film. + CAP_PROP_FRAME_WIDTH =3, //!< Width of the frames in the video stream. + CAP_PROP_FRAME_HEIGHT =4, //!< Height of the frames in the video stream. + CAP_PROP_FPS =5, //!< Frame rate. + CAP_PROP_FOURCC =6, //!< 4-character code of codec. see VideoWriter::fourcc . + CAP_PROP_FRAME_COUNT =7, //!< Number of frames in the video file. + CAP_PROP_FORMAT =8, //!< Format of the %Mat objects returned by VideoCapture::retrieve(). + CAP_PROP_MODE =9, //!< Backend-specific value indicating the current capture mode. + CAP_PROP_BRIGHTNESS =10, //!< Brightness of the image (only for those cameras that support). + CAP_PROP_CONTRAST =11, //!< Contrast of the image (only for cameras). + CAP_PROP_SATURATION =12, //!< Saturation of the image (only for cameras). + CAP_PROP_HUE =13, //!< Hue of the image (only for cameras). + CAP_PROP_GAIN =14, //!< Gain of the image (only for those cameras that support). + CAP_PROP_EXPOSURE =15, //!< Exposure (only for those cameras that support). + CAP_PROP_CONVERT_RGB =16, //!< Boolean flags indicating whether images should be converted to RGB. + CAP_PROP_WHITE_BALANCE_BLUE_U =17, //!< Currently unsupported. + CAP_PROP_RECTIFICATION =18, //!< Rectification flag for stereo cameras (note: only supported by DC1394 v 2.x backend currently). + CAP_PROP_MONOCHROME =19, + CAP_PROP_SHARPNESS =20, + CAP_PROP_AUTO_EXPOSURE =21, //!< DC1394: exposure control done by camera, user can adjust reference level using this feature. + CAP_PROP_GAMMA =22, + CAP_PROP_TEMPERATURE =23, + CAP_PROP_TRIGGER =24, + CAP_PROP_TRIGGER_DELAY =25, + CAP_PROP_WHITE_BALANCE_RED_V =26, + CAP_PROP_ZOOM =27, + CAP_PROP_FOCUS =28, + CAP_PROP_GUID =29, + CAP_PROP_ISO_SPEED =30, + CAP_PROP_BACKLIGHT =32, + CAP_PROP_PAN =33, + CAP_PROP_TILT =34, + CAP_PROP_ROLL =35, + CAP_PROP_IRIS =36, + CAP_PROP_SETTINGS =37, //!< Pop up video/camera filter dialog (note: only supported by DSHOW backend currently. The property value is ignored) + CAP_PROP_BUFFERSIZE =38, + CAP_PROP_AUTOFOCUS =39, + CAP_PROP_SAR_NUM =40, //!< Sample aspect ratio: num/den (num) + CAP_PROP_SAR_DEN =41, //!< Sample aspect ratio: num/den (den) + CAP_PROP_BACKEND =42, //!< Current backend (enum VideoCaptureAPIs). Read-only property + CAP_PROP_CHANNEL =43, //!< Video input or Channel Number (only for those cameras that support) + CAP_PROP_AUTO_WB =44, //!< enable/ disable auto white-balance + CAP_PROP_WB_TEMPERATURE=45, //!< white-balance color temperature +#ifndef CV_DOXYGEN + CV__CAP_PROP_LATEST +#endif + }; + + +/** @brief Generic camera output modes identifier. +@note Currently, these are supported through the libv4l backend only. +*/ +enum VideoCaptureModes { + CAP_MODE_BGR = 0, //!< BGR24 (default) + CAP_MODE_RGB = 1, //!< RGB24 + CAP_MODE_GRAY = 2, //!< Y8 + CAP_MODE_YUYV = 3 //!< YUYV + }; + +/** @brief %VideoWriter generic properties identifier. + @sa VideoWriter::get(), VideoWriter::set() +*/ +enum VideoWriterProperties { + VIDEOWRITER_PROP_QUALITY = 1, //!< Current quality (0..100%) of the encoded videostream. Can be adjusted dynamically in some codecs. + VIDEOWRITER_PROP_FRAMEBYTES = 2, //!< (Read-only): Size of just encoded video frame. Note that the encoding order may be different from representation order. + VIDEOWRITER_PROP_NSTRIPES = 3 //!< Number of stripes for parallel encoding. -1 for auto detection. +}; + +//! @} videoio_flags_base + +//! @addtogroup videoio_flags_others +//! @{ + +/** @name IEEE 1394 drivers + @{ +*/ + +/** @brief Modes of the IEEE 1394 controlling registers +(can be: auto, manual, auto single push, absolute Latter allowed with any other mode) +every feature can have only one mode turned on at a time +*/ +enum { CAP_PROP_DC1394_OFF = -4, //!< turn the feature off (not controlled manually nor automatically). + CAP_PROP_DC1394_MODE_MANUAL = -3, //!< set automatically when a value of the feature is set by the user. + CAP_PROP_DC1394_MODE_AUTO = -2, + CAP_PROP_DC1394_MODE_ONE_PUSH_AUTO = -1, + CAP_PROP_DC1394_MAX = 31 + }; + +//! @} IEEE 1394 drivers + +/** @name OpenNI (for Kinect) + @{ +*/ + +//! OpenNI map generators +enum { CAP_OPENNI_DEPTH_GENERATOR = 1 << 31, + CAP_OPENNI_IMAGE_GENERATOR = 1 << 30, + CAP_OPENNI_IR_GENERATOR = 1 << 29, + CAP_OPENNI_GENERATORS_MASK = CAP_OPENNI_DEPTH_GENERATOR + CAP_OPENNI_IMAGE_GENERATOR + CAP_OPENNI_IR_GENERATOR + }; + +//! Properties of cameras available through OpenNI backend +enum { CAP_PROP_OPENNI_OUTPUT_MODE = 100, + CAP_PROP_OPENNI_FRAME_MAX_DEPTH = 101, //!< In mm + CAP_PROP_OPENNI_BASELINE = 102, //!< In mm + CAP_PROP_OPENNI_FOCAL_LENGTH = 103, //!< In pixels + CAP_PROP_OPENNI_REGISTRATION = 104, //!< Flag that synchronizes the remapping depth map to image map + //!< by changing depth generator's view point (if the flag is "on") or + //!< sets this view point to its normal one (if the flag is "off"). + CAP_PROP_OPENNI_REGISTRATION_ON = CAP_PROP_OPENNI_REGISTRATION, + CAP_PROP_OPENNI_APPROX_FRAME_SYNC = 105, + CAP_PROP_OPENNI_MAX_BUFFER_SIZE = 106, + CAP_PROP_OPENNI_CIRCLE_BUFFER = 107, + CAP_PROP_OPENNI_MAX_TIME_DURATION = 108, + CAP_PROP_OPENNI_GENERATOR_PRESENT = 109, + CAP_PROP_OPENNI2_SYNC = 110, + CAP_PROP_OPENNI2_MIRROR = 111 + }; + +//! OpenNI shortcuts +enum { CAP_OPENNI_IMAGE_GENERATOR_PRESENT = CAP_OPENNI_IMAGE_GENERATOR + CAP_PROP_OPENNI_GENERATOR_PRESENT, + CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE = CAP_OPENNI_IMAGE_GENERATOR + CAP_PROP_OPENNI_OUTPUT_MODE, + CAP_OPENNI_DEPTH_GENERATOR_PRESENT = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_GENERATOR_PRESENT, + CAP_OPENNI_DEPTH_GENERATOR_BASELINE = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_BASELINE, + CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_FOCAL_LENGTH, + CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_REGISTRATION, + CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION_ON = CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION, + CAP_OPENNI_IR_GENERATOR_PRESENT = CAP_OPENNI_IR_GENERATOR + CAP_PROP_OPENNI_GENERATOR_PRESENT, + }; + +//! OpenNI data given from depth generator +enum { CAP_OPENNI_DEPTH_MAP = 0, //!< Depth values in mm (CV_16UC1) + CAP_OPENNI_POINT_CLOUD_MAP = 1, //!< XYZ in meters (CV_32FC3) + CAP_OPENNI_DISPARITY_MAP = 2, //!< Disparity in pixels (CV_8UC1) + CAP_OPENNI_DISPARITY_MAP_32F = 3, //!< Disparity in pixels (CV_32FC1) + CAP_OPENNI_VALID_DEPTH_MASK = 4, //!< CV_8UC1 + + CAP_OPENNI_BGR_IMAGE = 5, //!< Data given from RGB image generator + CAP_OPENNI_GRAY_IMAGE = 6, //!< Data given from RGB image generator + + CAP_OPENNI_IR_IMAGE = 7 //!< Data given from IR image generator + }; + +//! Supported output modes of OpenNI image generator +enum { CAP_OPENNI_VGA_30HZ = 0, + CAP_OPENNI_SXGA_15HZ = 1, + CAP_OPENNI_SXGA_30HZ = 2, + CAP_OPENNI_QVGA_30HZ = 3, + CAP_OPENNI_QVGA_60HZ = 4 + }; + +//! @} OpenNI + +/** @name GStreamer + @{ +*/ + +enum { CAP_PROP_GSTREAMER_QUEUE_LENGTH = 200 //!< Default is 1 + }; + +//! @} GStreamer + +/** @name PvAPI, Prosilica GigE SDK + @{ +*/ + +//! PVAPI +enum { CAP_PROP_PVAPI_MULTICASTIP = 300, //!< IP for enable multicast master mode. 0 for disable multicast. + CAP_PROP_PVAPI_FRAMESTARTTRIGGERMODE = 301, //!< FrameStartTriggerMode: Determines how a frame is initiated. + CAP_PROP_PVAPI_DECIMATIONHORIZONTAL = 302, //!< Horizontal sub-sampling of the image. + CAP_PROP_PVAPI_DECIMATIONVERTICAL = 303, //!< Vertical sub-sampling of the image. + CAP_PROP_PVAPI_BINNINGX = 304, //!< Horizontal binning factor. + CAP_PROP_PVAPI_BINNINGY = 305, //!< Vertical binning factor. + CAP_PROP_PVAPI_PIXELFORMAT = 306 //!< Pixel format. + }; + +//! PVAPI: FrameStartTriggerMode +enum { CAP_PVAPI_FSTRIGMODE_FREERUN = 0, //!< Freerun + CAP_PVAPI_FSTRIGMODE_SYNCIN1 = 1, //!< SyncIn1 + CAP_PVAPI_FSTRIGMODE_SYNCIN2 = 2, //!< SyncIn2 + CAP_PVAPI_FSTRIGMODE_FIXEDRATE = 3, //!< FixedRate + CAP_PVAPI_FSTRIGMODE_SOFTWARE = 4 //!< Software + }; + +//! PVAPI: DecimationHorizontal, DecimationVertical +enum { CAP_PVAPI_DECIMATION_OFF = 1, //!< Off + CAP_PVAPI_DECIMATION_2OUTOF4 = 2, //!< 2 out of 4 decimation + CAP_PVAPI_DECIMATION_2OUTOF8 = 4, //!< 2 out of 8 decimation + CAP_PVAPI_DECIMATION_2OUTOF16 = 8 //!< 2 out of 16 decimation + }; + +//! PVAPI: PixelFormat +enum { CAP_PVAPI_PIXELFORMAT_MONO8 = 1, //!< Mono8 + CAP_PVAPI_PIXELFORMAT_MONO16 = 2, //!< Mono16 + CAP_PVAPI_PIXELFORMAT_BAYER8 = 3, //!< Bayer8 + CAP_PVAPI_PIXELFORMAT_BAYER16 = 4, //!< Bayer16 + CAP_PVAPI_PIXELFORMAT_RGB24 = 5, //!< Rgb24 + CAP_PVAPI_PIXELFORMAT_BGR24 = 6, //!< Bgr24 + CAP_PVAPI_PIXELFORMAT_RGBA32 = 7, //!< Rgba32 + CAP_PVAPI_PIXELFORMAT_BGRA32 = 8, //!< Bgra32 + }; + +//! @} PvAPI + +/** @name XIMEA Camera API + @{ +*/ + +//! Properties of cameras available through XIMEA SDK backend +enum { CAP_PROP_XI_DOWNSAMPLING = 400, //!< Change image resolution by binning or skipping. + CAP_PROP_XI_DATA_FORMAT = 401, //!< Output data format. + CAP_PROP_XI_OFFSET_X = 402, //!< Horizontal offset from the origin to the area of interest (in pixels). + CAP_PROP_XI_OFFSET_Y = 403, //!< Vertical offset from the origin to the area of interest (in pixels). + CAP_PROP_XI_TRG_SOURCE = 404, //!< Defines source of trigger. + CAP_PROP_XI_TRG_SOFTWARE = 405, //!< Generates an internal trigger. PRM_TRG_SOURCE must be set to TRG_SOFTWARE. + CAP_PROP_XI_GPI_SELECTOR = 406, //!< Selects general purpose input. + CAP_PROP_XI_GPI_MODE = 407, //!< Set general purpose input mode. + CAP_PROP_XI_GPI_LEVEL = 408, //!< Get general purpose level. + CAP_PROP_XI_GPO_SELECTOR = 409, //!< Selects general purpose output. + CAP_PROP_XI_GPO_MODE = 410, //!< Set general purpose output mode. + CAP_PROP_XI_LED_SELECTOR = 411, //!< Selects camera signalling LED. + CAP_PROP_XI_LED_MODE = 412, //!< Define camera signalling LED functionality. + CAP_PROP_XI_MANUAL_WB = 413, //!< Calculates White Balance(must be called during acquisition). + CAP_PROP_XI_AUTO_WB = 414, //!< Automatic white balance. + CAP_PROP_XI_AEAG = 415, //!< Automatic exposure/gain. + CAP_PROP_XI_EXP_PRIORITY = 416, //!< Exposure priority (0.5 - exposure 50%, gain 50%). + CAP_PROP_XI_AE_MAX_LIMIT = 417, //!< Maximum limit of exposure in AEAG procedure. + CAP_PROP_XI_AG_MAX_LIMIT = 418, //!< Maximum limit of gain in AEAG procedure. + CAP_PROP_XI_AEAG_LEVEL = 419, //!< Average intensity of output signal AEAG should achieve(in %). + CAP_PROP_XI_TIMEOUT = 420, //!< Image capture timeout in milliseconds. + CAP_PROP_XI_EXPOSURE = 421, //!< Exposure time in microseconds. + CAP_PROP_XI_EXPOSURE_BURST_COUNT = 422, //!< Sets the number of times of exposure in one frame. + CAP_PROP_XI_GAIN_SELECTOR = 423, //!< Gain selector for parameter Gain allows to select different type of gains. + CAP_PROP_XI_GAIN = 424, //!< Gain in dB. + CAP_PROP_XI_DOWNSAMPLING_TYPE = 426, //!< Change image downsampling type. + CAP_PROP_XI_BINNING_SELECTOR = 427, //!< Binning engine selector. + CAP_PROP_XI_BINNING_VERTICAL = 428, //!< Vertical Binning - number of vertical photo-sensitive cells to combine together. + CAP_PROP_XI_BINNING_HORIZONTAL = 429, //!< Horizontal Binning - number of horizontal photo-sensitive cells to combine together. + CAP_PROP_XI_BINNING_PATTERN = 430, //!< Binning pattern type. + CAP_PROP_XI_DECIMATION_SELECTOR = 431, //!< Decimation engine selector. + CAP_PROP_XI_DECIMATION_VERTICAL = 432, //!< Vertical Decimation - vertical sub-sampling of the image - reduces the vertical resolution of the image by the specified vertical decimation factor. + CAP_PROP_XI_DECIMATION_HORIZONTAL = 433, //!< Horizontal Decimation - horizontal sub-sampling of the image - reduces the horizontal resolution of the image by the specified vertical decimation factor. + CAP_PROP_XI_DECIMATION_PATTERN = 434, //!< Decimation pattern type. + CAP_PROP_XI_TEST_PATTERN_GENERATOR_SELECTOR = 587, //!< Selects which test pattern generator is controlled by the TestPattern feature. + CAP_PROP_XI_TEST_PATTERN = 588, //!< Selects which test pattern type is generated by the selected generator. + CAP_PROP_XI_IMAGE_DATA_FORMAT = 435, //!< Output data format. + CAP_PROP_XI_SHUTTER_TYPE = 436, //!< Change sensor shutter type(CMOS sensor). + CAP_PROP_XI_SENSOR_TAPS = 437, //!< Number of taps. + CAP_PROP_XI_AEAG_ROI_OFFSET_X = 439, //!< Automatic exposure/gain ROI offset X. + CAP_PROP_XI_AEAG_ROI_OFFSET_Y = 440, //!< Automatic exposure/gain ROI offset Y. + CAP_PROP_XI_AEAG_ROI_WIDTH = 441, //!< Automatic exposure/gain ROI Width. + CAP_PROP_XI_AEAG_ROI_HEIGHT = 442, //!< Automatic exposure/gain ROI Height. + CAP_PROP_XI_BPC = 445, //!< Correction of bad pixels. + CAP_PROP_XI_WB_KR = 448, //!< White balance red coefficient. + CAP_PROP_XI_WB_KG = 449, //!< White balance green coefficient. + CAP_PROP_XI_WB_KB = 450, //!< White balance blue coefficient. + CAP_PROP_XI_WIDTH = 451, //!< Width of the Image provided by the device (in pixels). + CAP_PROP_XI_HEIGHT = 452, //!< Height of the Image provided by the device (in pixels). + CAP_PROP_XI_REGION_SELECTOR = 589, //!< Selects Region in Multiple ROI which parameters are set by width, height, ... ,region mode. + CAP_PROP_XI_REGION_MODE = 595, //!< Activates/deactivates Region selected by Region Selector. + CAP_PROP_XI_LIMIT_BANDWIDTH = 459, //!< Set/get bandwidth(datarate)(in Megabits). + CAP_PROP_XI_SENSOR_DATA_BIT_DEPTH = 460, //!< Sensor output data bit depth. + CAP_PROP_XI_OUTPUT_DATA_BIT_DEPTH = 461, //!< Device output data bit depth. + CAP_PROP_XI_IMAGE_DATA_BIT_DEPTH = 462, //!< bitdepth of data returned by function xiGetImage. + CAP_PROP_XI_OUTPUT_DATA_PACKING = 463, //!< Device output data packing (or grouping) enabled. Packing could be enabled if output_data_bit_depth > 8 and packing capability is available. + CAP_PROP_XI_OUTPUT_DATA_PACKING_TYPE = 464, //!< Data packing type. Some cameras supports only specific packing type. + CAP_PROP_XI_IS_COOLED = 465, //!< Returns 1 for cameras that support cooling. + CAP_PROP_XI_COOLING = 466, //!< Start camera cooling. + CAP_PROP_XI_TARGET_TEMP = 467, //!< Set sensor target temperature for cooling. + CAP_PROP_XI_CHIP_TEMP = 468, //!< Camera sensor temperature. + CAP_PROP_XI_HOUS_TEMP = 469, //!< Camera housing temperature. + CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, //!< Camera housing back side temperature. + CAP_PROP_XI_SENSOR_BOARD_TEMP = 596, //!< Camera sensor board temperature. + CAP_PROP_XI_CMS = 470, //!< Mode of color management system. + CAP_PROP_XI_APPLY_CMS = 471, //!< Enable applying of CMS profiles to xiGetImage (see XI_PRM_INPUT_CMS_PROFILE, XI_PRM_OUTPUT_CMS_PROFILE). + CAP_PROP_XI_IMAGE_IS_COLOR = 474, //!< Returns 1 for color cameras. + CAP_PROP_XI_COLOR_FILTER_ARRAY = 475, //!< Returns color filter array type of RAW data. + CAP_PROP_XI_GAMMAY = 476, //!< Luminosity gamma. + CAP_PROP_XI_GAMMAC = 477, //!< Chromaticity gamma. + CAP_PROP_XI_SHARPNESS = 478, //!< Sharpness Strength. + CAP_PROP_XI_CC_MATRIX_00 = 479, //!< Color Correction Matrix element [0][0]. + CAP_PROP_XI_CC_MATRIX_01 = 480, //!< Color Correction Matrix element [0][1]. + CAP_PROP_XI_CC_MATRIX_02 = 481, //!< Color Correction Matrix element [0][2]. + CAP_PROP_XI_CC_MATRIX_03 = 482, //!< Color Correction Matrix element [0][3]. + CAP_PROP_XI_CC_MATRIX_10 = 483, //!< Color Correction Matrix element [1][0]. + CAP_PROP_XI_CC_MATRIX_11 = 484, //!< Color Correction Matrix element [1][1]. + CAP_PROP_XI_CC_MATRIX_12 = 485, //!< Color Correction Matrix element [1][2]. + CAP_PROP_XI_CC_MATRIX_13 = 486, //!< Color Correction Matrix element [1][3]. + CAP_PROP_XI_CC_MATRIX_20 = 487, //!< Color Correction Matrix element [2][0]. + CAP_PROP_XI_CC_MATRIX_21 = 488, //!< Color Correction Matrix element [2][1]. + CAP_PROP_XI_CC_MATRIX_22 = 489, //!< Color Correction Matrix element [2][2]. + CAP_PROP_XI_CC_MATRIX_23 = 490, //!< Color Correction Matrix element [2][3]. + CAP_PROP_XI_CC_MATRIX_30 = 491, //!< Color Correction Matrix element [3][0]. + CAP_PROP_XI_CC_MATRIX_31 = 492, //!< Color Correction Matrix element [3][1]. + CAP_PROP_XI_CC_MATRIX_32 = 493, //!< Color Correction Matrix element [3][2]. + CAP_PROP_XI_CC_MATRIX_33 = 494, //!< Color Correction Matrix element [3][3]. + CAP_PROP_XI_DEFAULT_CC_MATRIX = 495, //!< Set default Color Correction Matrix. + CAP_PROP_XI_TRG_SELECTOR = 498, //!< Selects the type of trigger. + CAP_PROP_XI_ACQ_FRAME_BURST_COUNT = 499, //!< Sets number of frames acquired by burst. This burst is used only if trigger is set to FrameBurstStart. + CAP_PROP_XI_DEBOUNCE_EN = 507, //!< Enable/Disable debounce to selected GPI. + CAP_PROP_XI_DEBOUNCE_T0 = 508, //!< Debounce time (x * 10us). + CAP_PROP_XI_DEBOUNCE_T1 = 509, //!< Debounce time (x * 10us). + CAP_PROP_XI_DEBOUNCE_POL = 510, //!< Debounce polarity (pol = 1 t0 - falling edge, t1 - rising edge). + CAP_PROP_XI_LENS_MODE = 511, //!< Status of lens control interface. This shall be set to XI_ON before any Lens operations. + CAP_PROP_XI_LENS_APERTURE_VALUE = 512, //!< Current lens aperture value in stops. Examples: 2.8, 4, 5.6, 8, 11. + CAP_PROP_XI_LENS_FOCUS_MOVEMENT_VALUE = 513, //!< Lens current focus movement value to be used by XI_PRM_LENS_FOCUS_MOVE in motor steps. + CAP_PROP_XI_LENS_FOCUS_MOVE = 514, //!< Moves lens focus motor by steps set in XI_PRM_LENS_FOCUS_MOVEMENT_VALUE. + CAP_PROP_XI_LENS_FOCUS_DISTANCE = 515, //!< Lens focus distance in cm. + CAP_PROP_XI_LENS_FOCAL_LENGTH = 516, //!< Lens focal distance in mm. + CAP_PROP_XI_LENS_FEATURE_SELECTOR = 517, //!< Selects the current feature which is accessible by XI_PRM_LENS_FEATURE. + CAP_PROP_XI_LENS_FEATURE = 518, //!< Allows access to lens feature value currently selected by XI_PRM_LENS_FEATURE_SELECTOR. + CAP_PROP_XI_DEVICE_MODEL_ID = 521, //!< Returns device model id. + CAP_PROP_XI_DEVICE_SN = 522, //!< Returns device serial number. + CAP_PROP_XI_IMAGE_DATA_FORMAT_RGB32_ALPHA = 529, //!< The alpha channel of RGB32 output image format. + CAP_PROP_XI_IMAGE_PAYLOAD_SIZE = 530, //!< Buffer size in bytes sufficient for output image returned by xiGetImage. + CAP_PROP_XI_TRANSPORT_PIXEL_FORMAT = 531, //!< Current format of pixels on transport layer. + CAP_PROP_XI_SENSOR_CLOCK_FREQ_HZ = 532, //!< Sensor clock frequency in Hz. + CAP_PROP_XI_SENSOR_CLOCK_FREQ_INDEX = 533, //!< Sensor clock frequency index. Sensor with selected frequencies have possibility to set the frequency only by this index. + CAP_PROP_XI_SENSOR_OUTPUT_CHANNEL_COUNT = 534, //!< Number of output channels from sensor used for data transfer. + CAP_PROP_XI_FRAMERATE = 535, //!< Define framerate in Hz. + CAP_PROP_XI_COUNTER_SELECTOR = 536, //!< Select counter. + CAP_PROP_XI_COUNTER_VALUE = 537, //!< Counter status. + CAP_PROP_XI_ACQ_TIMING_MODE = 538, //!< Type of sensor frames timing. + CAP_PROP_XI_AVAILABLE_BANDWIDTH = 539, //!< Calculate and returns available interface bandwidth(int Megabits). + CAP_PROP_XI_BUFFER_POLICY = 540, //!< Data move policy. + CAP_PROP_XI_LUT_EN = 541, //!< Activates LUT. + CAP_PROP_XI_LUT_INDEX = 542, //!< Control the index (offset) of the coefficient to access in the LUT. + CAP_PROP_XI_LUT_VALUE = 543, //!< Value at entry LUTIndex of the LUT. + CAP_PROP_XI_TRG_DELAY = 544, //!< Specifies the delay in microseconds (us) to apply after the trigger reception before activating it. + CAP_PROP_XI_TS_RST_MODE = 545, //!< Defines how time stamp reset engine will be armed. + CAP_PROP_XI_TS_RST_SOURCE = 546, //!< Defines which source will be used for timestamp reset. Writing this parameter will trigger settings of engine (arming). + CAP_PROP_XI_IS_DEVICE_EXIST = 547, //!< Returns 1 if camera connected and works properly. + CAP_PROP_XI_ACQ_BUFFER_SIZE = 548, //!< Acquisition buffer size in buffer_size_unit. Default bytes. + CAP_PROP_XI_ACQ_BUFFER_SIZE_UNIT = 549, //!< Acquisition buffer size unit in bytes. Default 1. E.g. Value 1024 means that buffer_size is in KiBytes. + CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_SIZE = 550, //!< Acquisition transport buffer size in bytes. + CAP_PROP_XI_BUFFERS_QUEUE_SIZE = 551, //!< Queue of field/frame buffers. + CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_COMMIT = 552, //!< Number of buffers to commit to low level. + CAP_PROP_XI_RECENT_FRAME = 553, //!< GetImage returns most recent frame. + CAP_PROP_XI_DEVICE_RESET = 554, //!< Resets the camera to default state. + CAP_PROP_XI_COLUMN_FPN_CORRECTION = 555, //!< Correction of column FPN. + CAP_PROP_XI_ROW_FPN_CORRECTION = 591, //!< Correction of row FPN. + CAP_PROP_XI_SENSOR_MODE = 558, //!< Current sensor mode. Allows to select sensor mode by one integer. Setting of this parameter affects: image dimensions and downsampling. + CAP_PROP_XI_HDR = 559, //!< Enable High Dynamic Range feature. + CAP_PROP_XI_HDR_KNEEPOINT_COUNT = 560, //!< The number of kneepoints in the PWLR. + CAP_PROP_XI_HDR_T1 = 561, //!< Position of first kneepoint(in % of XI_PRM_EXPOSURE). + CAP_PROP_XI_HDR_T2 = 562, //!< Position of second kneepoint (in % of XI_PRM_EXPOSURE). + CAP_PROP_XI_KNEEPOINT1 = 563, //!< Value of first kneepoint (% of sensor saturation). + CAP_PROP_XI_KNEEPOINT2 = 564, //!< Value of second kneepoint (% of sensor saturation). + CAP_PROP_XI_IMAGE_BLACK_LEVEL = 565, //!< Last image black level counts. Can be used for Offline processing to recall it. + CAP_PROP_XI_HW_REVISION = 571, //!< Returns hardware revision number. + CAP_PROP_XI_DEBUG_LEVEL = 572, //!< Set debug level. + CAP_PROP_XI_AUTO_BANDWIDTH_CALCULATION = 573, //!< Automatic bandwidth calculation. + CAP_PROP_XI_FFS_FILE_ID = 594, //!< File number. + CAP_PROP_XI_FFS_FILE_SIZE = 580, //!< Size of file. + CAP_PROP_XI_FREE_FFS_SIZE = 581, //!< Size of free camera FFS. + CAP_PROP_XI_USED_FFS_SIZE = 582, //!< Size of used camera FFS. + CAP_PROP_XI_FFS_ACCESS_KEY = 583, //!< Setting of key enables file operations on some cameras. + CAP_PROP_XI_SENSOR_FEATURE_SELECTOR = 585, //!< Selects the current feature which is accessible by XI_PRM_SENSOR_FEATURE_VALUE. + CAP_PROP_XI_SENSOR_FEATURE_VALUE = 586, //!< Allows access to sensor feature value currently selected by XI_PRM_SENSOR_FEATURE_SELECTOR. + }; + +//! @} XIMEA + +/** @name AVFoundation framework for iOS + OS X Lion will have the same API + @{ +*/ + +//! Properties of cameras available through AVFOUNDATION backend +enum { CAP_PROP_IOS_DEVICE_FOCUS = 9001, + CAP_PROP_IOS_DEVICE_EXPOSURE = 9002, + CAP_PROP_IOS_DEVICE_FLASH = 9003, + CAP_PROP_IOS_DEVICE_WHITEBALANCE = 9004, + CAP_PROP_IOS_DEVICE_TORCH = 9005 + }; + +/** @name Smartek Giganetix GigEVisionSDK + @{ +*/ + +//! Properties of cameras available through Smartek Giganetix Ethernet Vision backend +/* --- Vladimir Litvinenko (litvinenko.vladimir@gmail.com) --- */ +enum { CAP_PROP_GIGA_FRAME_OFFSET_X = 10001, + CAP_PROP_GIGA_FRAME_OFFSET_Y = 10002, + CAP_PROP_GIGA_FRAME_WIDTH_MAX = 10003, + CAP_PROP_GIGA_FRAME_HEIGH_MAX = 10004, + CAP_PROP_GIGA_FRAME_SENS_WIDTH = 10005, + CAP_PROP_GIGA_FRAME_SENS_HEIGH = 10006 + }; + +//! @} Smartek + +/** @name Intel Perceptual Computing SDK + @{ +*/ +enum { CAP_PROP_INTELPERC_PROFILE_COUNT = 11001, + CAP_PROP_INTELPERC_PROFILE_IDX = 11002, + CAP_PROP_INTELPERC_DEPTH_LOW_CONFIDENCE_VALUE = 11003, + CAP_PROP_INTELPERC_DEPTH_SATURATION_VALUE = 11004, + CAP_PROP_INTELPERC_DEPTH_CONFIDENCE_THRESHOLD = 11005, + CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_HORZ = 11006, + CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_VERT = 11007 + }; + +//! Intel Perceptual Streams +enum { CAP_INTELPERC_DEPTH_GENERATOR = 1 << 29, + CAP_INTELPERC_IMAGE_GENERATOR = 1 << 28, + CAP_INTELPERC_GENERATORS_MASK = CAP_INTELPERC_DEPTH_GENERATOR + CAP_INTELPERC_IMAGE_GENERATOR + }; + +enum { CAP_INTELPERC_DEPTH_MAP = 0, //!< Each pixel is a 16-bit integer. The value indicates the distance from an object to the camera's XY plane or the Cartesian depth. + CAP_INTELPERC_UVDEPTH_MAP = 1, //!< Each pixel contains two 32-bit floating point values in the range of 0-1, representing the mapping of depth coordinates to the color coordinates. + CAP_INTELPERC_IR_MAP = 2, //!< Each pixel is a 16-bit integer. The value indicates the intensity of the reflected laser beam. + CAP_INTELPERC_IMAGE = 3 + }; + +//! @} Intel Perceptual + +/** @name gPhoto2 connection + @{ +*/ + +/** @brief gPhoto2 properties + +If `propertyId` is less than 0 then work on widget with that __additive inversed__ camera setting ID +Get IDs by using CAP_PROP_GPHOTO2_WIDGET_ENUMERATE. +@see CvCaptureCAM_GPHOTO2 for more info +*/ +enum { CAP_PROP_GPHOTO2_PREVIEW = 17001, //!< Capture only preview from liveview mode. + CAP_PROP_GPHOTO2_WIDGET_ENUMERATE = 17002, //!< Readonly, returns (const char *). + CAP_PROP_GPHOTO2_RELOAD_CONFIG = 17003, //!< Trigger, only by set. Reload camera settings. + CAP_PROP_GPHOTO2_RELOAD_ON_CHANGE = 17004, //!< Reload all settings on set. + CAP_PROP_GPHOTO2_COLLECT_MSGS = 17005, //!< Collect messages with details. + CAP_PROP_GPHOTO2_FLUSH_MSGS = 17006, //!< Readonly, returns (const char *). + CAP_PROP_SPEED = 17007, //!< Exposure speed. Can be readonly, depends on camera program. + CAP_PROP_APERTURE = 17008, //!< Aperture. Can be readonly, depends on camera program. + CAP_PROP_EXPOSUREPROGRAM = 17009, //!< Camera exposure program. + CAP_PROP_VIEWFINDER = 17010 //!< Enter liveview mode. + }; + +//! @} gPhoto2 + + +/** @name Images backend + @{ +*/ + +/** @brief Images backend properties + +*/ +enum { CAP_PROP_IMAGES_BASE = 18000, + CAP_PROP_IMAGES_LAST = 19000 // excluding + }; + +//! @} Images + +//! @} videoio_flags_others + + +class IVideoCapture; + +/** @brief Class for video capturing from video files, image sequences or cameras. + +The class provides C++ API for capturing video from cameras or for reading video files and image sequences. + +Here is how the class can be used: +@include samples/cpp/videocapture_basic.cpp + +@note In @ref videoio_c "C API" the black-box structure `CvCapture` is used instead of %VideoCapture. +@note +- (C++) A basic sample on using the %VideoCapture interface can be found at + `OPENCV_SOURCE_CODE/samples/cpp/videocapture_starter.cpp` +- (Python) A basic sample on using the %VideoCapture interface can be found at + `OPENCV_SOURCE_CODE/samples/python/video.py` +- (Python) A multi threaded video processing sample can be found at + `OPENCV_SOURCE_CODE/samples/python/video_threaded.py` +- (Python) %VideoCapture sample showcasing some features of the Video4Linux2 backend + `OPENCV_SOURCE_CODE/samples/python/video_v4l2.py` + */ +class CV_EXPORTS_W VideoCapture +{ +public: + /** @brief Default constructor + @note In @ref videoio_c "C API", when you finished working with video, release CvCapture structure with + cvReleaseCapture(), or use Ptr\ that calls cvReleaseCapture() automatically in the + destructor. + */ + CV_WRAP VideoCapture(); + + /** @overload + @brief Open video file or a capturing device or a IP video stream for video capturing + + Same as VideoCapture(const String& filename, int apiPreference) but using default Capture API backends + */ + CV_WRAP VideoCapture(const String& filename); + + /** @overload + @brief Open video file or a capturing device or a IP video stream for video capturing with API Preference + + @param filename it can be: + - name of video file (eg. `video.avi`) + - or image sequence (eg. `img_%02d.jpg`, which will read samples like `img_00.jpg, img_01.jpg, img_02.jpg, ...`) + - or URL of video stream (eg. `protocol://host:port/script_name?script_params|auth`). + Note that each video stream or IP camera feed has its own URL scheme. Please refer to the + documentation of source stream to know the right URL. + @param apiPreference preferred Capture API backends to use. Can be used to enforce a specific reader + implementation if multiple are available: e.g. cv::CAP_FFMPEG or cv::CAP_IMAGES or cv::CAP_DSHOW. + @sa The list of supported API backends cv::VideoCaptureAPIs + */ + CV_WRAP VideoCapture(const String& filename, int apiPreference); + + /** @overload + @brief Open a camera for video capturing + + @param index camera_id + domain_offset (CAP_*) id of the video capturing device to open. To open default camera using default backend just pass 0. + Use a `domain_offset` to enforce a specific reader implementation if multiple are available like cv::CAP_FFMPEG or cv::CAP_IMAGES or cv::CAP_DSHOW. + e.g. to open Camera 1 using the MS Media Foundation API use `index = 1 + cv::CAP_MSMF` + + @sa The list of supported API backends cv::VideoCaptureAPIs + */ + CV_WRAP VideoCapture(int index); + + /** @overload + @brief Opens a camera for video capturing + + @param index id of the video capturing device to open. To open default camera using default backend just pass 0. + (to backward compatibility usage of camera_id + domain_offset (CAP_*) is valid when apiPreference is CAP_ANY) + @param apiPreference preferred Capture API backends to use. Can be used to enforce a specific reader + implementation if multiple are available: e.g. cv::CAP_DSHOW or cv::CAP_MSMF or cv::CAP_V4L2. + + @sa The list of supported API backends cv::VideoCaptureAPIs + */ + CV_WRAP VideoCapture(int index, int apiPreference); + + /** @brief Default destructor + + The method first calls VideoCapture::release to close the already opened file or camera. + */ + virtual ~VideoCapture(); + + /** @brief Open video file or a capturing device or a IP video stream for video capturing + + @overload + + Parameters are same as the constructor VideoCapture(const String& filename) + @return `true` if the file has been successfully opened + + The method first calls VideoCapture::release to close the already opened file or camera. + */ + CV_WRAP virtual bool open(const String& filename); + + /** @brief Open a camera for video capturing + + @overload + + Parameters are same as the constructor VideoCapture(int index) + @return `true` if the camera has been successfully opened. + + The method first calls VideoCapture::release to close the already opened file or camera. + */ + CV_WRAP virtual bool open(int index); + + /** @brief Open a camera for video capturing + + @overload + + Parameters are similar as the constructor VideoCapture(int index),except it takes an additional argument apiPreference. + Definitely, is same as open(int index) where `index=cameraNum + apiPreference` + @return `true` if the camera has been successfully opened. + */ + CV_WRAP bool open(int cameraNum, int apiPreference); + + /** @brief Returns true if video capturing has been initialized already. + + If the previous call to VideoCapture constructor or VideoCapture::open() succeeded, the method returns + true. + */ + CV_WRAP virtual bool isOpened() const; + + /** @brief Closes video file or capturing device. + + The method is automatically called by subsequent VideoCapture::open and by VideoCapture + destructor. + + The C function also deallocates memory and clears \*capture pointer. + */ + CV_WRAP virtual void release(); + + /** @brief Grabs the next frame from video file or capturing device. + + @return `true` (non-zero) in the case of success. + + The method/function grabs the next frame from video file or camera and returns true (non-zero) in + the case of success. + + The primary use of the function is in multi-camera environments, especially when the cameras do not + have hardware synchronization. That is, you call VideoCapture::grab() for each camera and after that + call the slower method VideoCapture::retrieve() to decode and get frame from each camera. This way + the overhead on demosaicing or motion jpeg decompression etc. is eliminated and the retrieved frames + from different cameras will be closer in time. + + Also, when a connected camera is multi-head (for example, a stereo camera or a Kinect device), the + correct way of retrieving data from it is to call VideoCapture::grab() first and then call + VideoCapture::retrieve() one or more times with different values of the channel parameter. + + @ref tutorial_kinect_openni + */ + CV_WRAP virtual bool grab(); + + /** @brief Decodes and returns the grabbed video frame. + + @param [out] image the video frame is returned here. If no frames has been grabbed the image will be empty. + @param flag it could be a frame index or a driver specific flag + @return `false` if no frames has been grabbed + + The method decodes and returns the just grabbed frame. If no frames has been grabbed + (camera has been disconnected, or there are no more frames in video file), the method returns false + and the function returns an empty image (with %cv::Mat, test it with Mat::empty()). + + @sa read() + + @note In @ref videoio_c "C API", functions cvRetrieveFrame() and cv.RetrieveFrame() return image stored inside the video + capturing structure. It is not allowed to modify or release the image! You can copy the frame using + cvCloneImage and then do whatever you want with the copy. + */ + CV_WRAP virtual bool retrieve(OutputArray image, int flag = 0); + + /** @brief Stream operator to read the next video frame. + @sa read() + */ + virtual VideoCapture& operator >> (CV_OUT Mat& image); + + /** @overload + @sa read() + */ + virtual VideoCapture& operator >> (CV_OUT UMat& image); + + /** @brief Grabs, decodes and returns the next video frame. + + @param [out] image the video frame is returned here. If no frames has been grabbed the image will be empty. + @return `false` if no frames has been grabbed + + The method/function combines VideoCapture::grab() and VideoCapture::retrieve() in one call. This is the + most convenient method for reading video files or capturing data from decode and returns the just + grabbed frame. If no frames has been grabbed (camera has been disconnected, or there are no more + frames in video file), the method returns false and the function returns empty image (with %cv::Mat, test it with Mat::empty()). + + @note In @ref videoio_c "C API", functions cvRetrieveFrame() and cv.RetrieveFrame() return image stored inside the video + capturing structure. It is not allowed to modify or release the image! You can copy the frame using + cvCloneImage and then do whatever you want with the copy. + */ + CV_WRAP virtual bool read(OutputArray image); + + /** @brief Sets a property in the VideoCapture. + + @param propId Property identifier from cv::VideoCaptureProperties (eg. cv::CAP_PROP_POS_MSEC, cv::CAP_PROP_POS_FRAMES, ...) + or one from @ref videoio_flags_others + @param value Value of the property. + @return `true` if the property is supported by backend used by the VideoCapture instance. + @note Even if it returns `true` this doesn't ensure that the property + value has been accepted by the capture device. See note in VideoCapture::get() + */ + CV_WRAP virtual bool set(int propId, double value); + + /** @brief Returns the specified VideoCapture property + + @param propId Property identifier from cv::VideoCaptureProperties (eg. cv::CAP_PROP_POS_MSEC, cv::CAP_PROP_POS_FRAMES, ...) + or one from @ref videoio_flags_others + @return Value for the specified property. Value 0 is returned when querying a property that is + not supported by the backend used by the VideoCapture instance. + + @note Reading / writing properties involves many layers. Some unexpected result might happens + along this chain. + @code {.txt} + `VideoCapture -> API Backend -> Operating System -> Device Driver -> Device Hardware` + @endcode + The returned value might be different from what really used by the device or it could be encoded + using device dependent rules (eg. steps or percentage). Effective behaviour depends from device + driver and API Backend + + */ + CV_WRAP virtual double get(int propId) const; + + /** @brief Open video file or a capturing device or a IP video stream for video capturing with API Preference + + @overload + + Parameters are same as the constructor VideoCapture(const String& filename, int apiPreference) + @return `true` if the file has been successfully opened + + The method first calls VideoCapture::release to close the already opened file or camera. + */ + CV_WRAP virtual bool open(const String& filename, int apiPreference); + + /** @brief Returns used backend API name + + @note Stream should be opened. + */ + CV_WRAP String getBackendName() const; + +protected: + Ptr cap; + Ptr icap; +}; + +class IVideoWriter; + +/** @example samples/cpp/tutorial_code/videoio/video-write/video-write.cpp +Check @ref tutorial_video_write "the corresponding tutorial" for more details +*/ + +/** @example samples/cpp/videowriter_basic.cpp +An example using VideoCapture and VideoWriter class +*/ + +/** @brief Video writer class. + +The class provides C++ API for writing video files or image sequences. +*/ +class CV_EXPORTS_W VideoWriter +{ +public: + /** @brief Default constructors + + The constructors/functions initialize video writers. + - On Linux FFMPEG is used to write videos; + - On Windows FFMPEG or VFW is used; + - On MacOSX QTKit is used. + */ + CV_WRAP VideoWriter(); + + /** @overload + @param filename Name of the output video file. + @param fourcc 4-character code of codec used to compress the frames. For example, + VideoWriter::fourcc('P','I','M','1') is a MPEG-1 codec, VideoWriter::fourcc('M','J','P','G') is a + motion-jpeg codec etc. List of codes can be obtained at [Video Codecs by + FOURCC](http://www.fourcc.org/codecs.php) page. FFMPEG backend with MP4 container natively uses + other values as fourcc code: see [ObjectType](http://www.mp4ra.org/codecs.html), + so you may receive a warning message from OpenCV about fourcc code conversion. + @param fps Framerate of the created video stream. + @param frameSize Size of the video frames. + @param isColor If it is not zero, the encoder will expect and encode color frames, otherwise it + will work with grayscale frames (the flag is currently supported on Windows only). + + @b Tips: + - With some backends `fourcc=-1` pops up the codec selection dialog from the system. + - To save image sequence use a proper filename (eg. `img_%02d.jpg`) and `fourcc=0` + OR `fps=0`. Use uncompressed image format (eg. `img_%02d.BMP`) to save raw frames. + - Most codecs are lossy. If you want lossless video file you need to use a lossless codecs + (eg. FFMPEG FFV1, Huffman HFYU, Lagarith LAGS, etc...) + - If FFMPEG is enabled, using `codec=0; fps=0;` you can create an uncompressed (raw) video file. + */ + CV_WRAP VideoWriter(const String& filename, int fourcc, double fps, + Size frameSize, bool isColor = true); + + /** @overload + The `apiPreference` parameter allows to specify API backends to use. Can be used to enforce a specific reader implementation + if multiple are available: e.g. cv::CAP_FFMPEG or cv::CAP_GSTREAMER. + */ + CV_WRAP VideoWriter(const String& filename, int apiPreference, int fourcc, double fps, + Size frameSize, bool isColor = true); + + /** @brief Default destructor + + The method first calls VideoWriter::release to close the already opened file. + */ + virtual ~VideoWriter(); + + /** @brief Initializes or reinitializes video writer. + + The method opens video writer. Parameters are the same as in the constructor + VideoWriter::VideoWriter. + @return `true` if video writer has been successfully initialized + + The method first calls VideoWriter::release to close the already opened file. + */ + CV_WRAP virtual bool open(const String& filename, int fourcc, double fps, + Size frameSize, bool isColor = true); + + /** @overload + */ + CV_WRAP bool open(const String& filename, int apiPreference, int fourcc, double fps, + Size frameSize, bool isColor = true); + + /** @brief Returns true if video writer has been successfully initialized. + */ + CV_WRAP virtual bool isOpened() const; + + /** @brief Closes the video writer. + + The method is automatically called by subsequent VideoWriter::open and by the VideoWriter + destructor. + */ + CV_WRAP virtual void release(); + + /** @brief Stream operator to write the next video frame. + @sa write + */ + virtual VideoWriter& operator << (const Mat& image); + + /** @brief Writes the next video frame + + @param image The written frame. In general, color images are expected in BGR format. + + The function/method writes the specified image to video file. It must have the same size as has + been specified when opening the video writer. + */ + CV_WRAP virtual void write(const Mat& image); + + /** @brief Sets a property in the VideoWriter. + + @param propId Property identifier from cv::VideoWriterProperties (eg. cv::VIDEOWRITER_PROP_QUALITY) + or one of @ref videoio_flags_others + + @param value Value of the property. + @return `true` if the property is supported by the backend used by the VideoWriter instance. + */ + CV_WRAP virtual bool set(int propId, double value); + + /** @brief Returns the specified VideoWriter property + + @param propId Property identifier from cv::VideoWriterProperties (eg. cv::VIDEOWRITER_PROP_QUALITY) + or one of @ref videoio_flags_others + + @return Value for the specified property. Value 0 is returned when querying a property that is + not supported by the backend used by the VideoWriter instance. + */ + CV_WRAP virtual double get(int propId) const; + + /** @brief Concatenates 4 chars to a fourcc code + + @return a fourcc code + + This static method constructs the fourcc code of the codec to be used in the constructor + VideoWriter::VideoWriter or VideoWriter::open. + */ + CV_WRAP static int fourcc(char c1, char c2, char c3, char c4); + + /** @brief Returns used backend API name + + @note Stream should be opened. + */ + CV_WRAP String getBackendName() const; + +protected: + Ptr writer; + Ptr iwriter; + + static Ptr create(const String& filename, int fourcc, double fps, + Size frameSize, bool isColor = true); +}; + +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvCapture* obj) const; +template<> CV_EXPORTS void DefaultDeleter::operator ()(CvVideoWriter* obj) const; + +//! @} videoio + +} // cv + +#endif //OPENCV_VIDEOIO_HPP diff --git a/3rdparty/opencv/include/opencv2/videoio/cap_ios.h b/3rdparty/opencv/include/opencv2/videoio/cap_ios.h new file mode 100644 index 00000000..207ad46c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videoio/cap_ios.h @@ -0,0 +1,150 @@ +/* For iOS video I/O + * by Eduard Feicho on 29/07/12 + * Copyright 2012. All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions are met: + * + * 1. Redistributions of source code must retain the above copyright notice, + * this list of conditions and the following disclaimer. + * 2. Redistributions in binary form must reproduce the above copyright notice, + * this list of conditions and the following disclaimer in the documentation + * and/or other materials provided with the distribution. + * 3. The name of the author may not be used to endorse or promote products + * derived from this software without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR IMPLIED + * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF + * MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO + * EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; + * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, + * WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR + * OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF + * ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + * + */ + +#import +#import +#import +#import +#include "opencv2/core.hpp" + +//! @addtogroup videoio_ios +//! @{ + +/////////////////////////////////////// CvAbstractCamera ///////////////////////////////////// + +@class CvAbstractCamera; + +CV_EXPORTS @interface CvAbstractCamera : NSObject +{ + UIDeviceOrientation currentDeviceOrientation; + + BOOL cameraAvailable; +} + +@property (nonatomic, strong) AVCaptureSession* captureSession; +@property (nonatomic, strong) AVCaptureConnection* videoCaptureConnection; + +@property (nonatomic, readonly) BOOL running; +@property (nonatomic, readonly) BOOL captureSessionLoaded; + +@property (nonatomic, assign) int defaultFPS; +@property (nonatomic, readonly) AVCaptureVideoPreviewLayer *captureVideoPreviewLayer; +@property (nonatomic, assign) AVCaptureDevicePosition defaultAVCaptureDevicePosition; +@property (nonatomic, assign) AVCaptureVideoOrientation defaultAVCaptureVideoOrientation; +@property (nonatomic, assign) BOOL useAVCaptureVideoPreviewLayer; +@property (nonatomic, strong) NSString *const defaultAVCaptureSessionPreset; + +@property (nonatomic, assign) int imageWidth; +@property (nonatomic, assign) int imageHeight; + +@property (nonatomic, strong) UIView* parentView; + +- CV_UNUSED(start); +- CV_UNUSED(stop); +- CV_UNUSED(switchCameras); + +- (id)initWithParentView:(UIView*)parent; + +- CV_UNUSED(createCaptureOutput); +- CV_UNUSED(createVideoPreviewLayer); +- CV_UNUSED(updateOrientation); + +- CV_UNUSED(lockFocus); +- CV_UNUSED(unlockFocus); +- CV_UNUSED(lockExposure); +- CV_UNUSED(unlockExposure); +- CV_UNUSED(lockBalance); +- CV_UNUSED(unlockBalance); + +@end + +///////////////////////////////// CvVideoCamera /////////////////////////////////////////// + +@class CvVideoCamera; + +CV_EXPORTS @protocol CvVideoCameraDelegate + +#ifdef __cplusplus +// delegate method for processing image frames +- (void)processImage:(cv::Mat&)image; +#endif + +@end + +CV_EXPORTS @interface CvVideoCamera : CvAbstractCamera +{ + AVCaptureVideoDataOutput *videoDataOutput; + + dispatch_queue_t videoDataOutputQueue; + CALayer *customPreviewLayer; + + CMTime lastSampleTime; + +} + +@property (nonatomic, weak) id delegate; +@property (nonatomic, assign) BOOL grayscaleMode; + +@property (nonatomic, assign) BOOL recordVideo; +@property (nonatomic, assign) BOOL rotateVideo; +@property (nonatomic, strong) AVAssetWriterInput* recordAssetWriterInput; +@property (nonatomic, strong) AVAssetWriterInputPixelBufferAdaptor* recordPixelBufferAdaptor; +@property (nonatomic, strong) AVAssetWriter* recordAssetWriter; + +- (void)adjustLayoutToInterfaceOrientation:(UIInterfaceOrientation)interfaceOrientation; +- CV_UNUSED(layoutPreviewLayer); +- CV_UNUSED(saveVideo); +- (NSURL *)videoFileURL; +- (NSString *)videoFileString; + + +@end + +///////////////////////////////// CvPhotoCamera /////////////////////////////////////////// + +@class CvPhotoCamera; + +CV_EXPORTS @protocol CvPhotoCameraDelegate + +- (void)photoCamera:(CvPhotoCamera*)photoCamera capturedImage:(UIImage *)image; +- (void)photoCameraCancel:(CvPhotoCamera*)photoCamera; + +@end + +CV_EXPORTS @interface CvPhotoCamera : CvAbstractCamera +{ + AVCaptureStillImageOutput *stillImageOutput; +} + +@property (nonatomic, weak) id delegate; + +- CV_UNUSED(takePicture); + +@end + +//! @} videoio_ios diff --git a/3rdparty/opencv/include/opencv2/videoio/registry.hpp b/3rdparty/opencv/include/opencv2/videoio/registry.hpp new file mode 100644 index 00000000..7404c681 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videoio/registry.hpp @@ -0,0 +1,44 @@ +// This file is part of OpenCV project. +// It is subject to the license terms in the LICENSE file found in the top-level directory +// of this distribution and at http://opencv.org/license.html. + +#ifndef OPENCV_VIDEOIO_REGISTRY_HPP +#define OPENCV_VIDEOIO_REGISTRY_HPP + +#include + +namespace cv { namespace videoio_registry { +/** @addtogroup videoio_registry +This section contains API description how to query/configure available Video I/O backends. + +Runtime configuration options: +- enable debug mode: `OPENCV_VIDEOIO_DEBUG=1` +- change backend priority: `OPENCV_VIDEOIO_PRIORITY_=9999` +- disable backend: `OPENCV_VIDEOIO_PRIORITY_=0` +- specify list of backends with high priority (>100000): `OPENCV_VIDEOIO_PRIORITY_LIST=FFMPEG,GSTREAMER` + +@{ + */ + + +/** @brief Returns backend API name or "unknown" +@param api backend ID (#VideoCaptureAPIs) +*/ +CV_EXPORTS_W cv::String getBackendName(VideoCaptureAPIs api); + +/** @brief Returns list of all builtin backends */ +CV_EXPORTS_W std::vector getBackends(); + +/** @brief Returns list of available backends which works via `cv::VideoCapture(int index)` */ +CV_EXPORTS_W std::vector getCameraBackends(); + +/** @brief Returns list of available backends which works via `cv::VideoCapture(filename)` */ +CV_EXPORTS_W std::vector getStreamBackends(); + +/** @brief Returns list of available backends which works via `cv::VideoWriter()` */ +CV_EXPORTS_W std::vector getWriterBackends(); + +//! @} +}} // namespace + +#endif // OPENCV_VIDEOIO_REGISTRY_HPP diff --git a/3rdparty/opencv/include/opencv2/videoio/videoio.hpp b/3rdparty/opencv/include/opencv2/videoio/videoio.hpp new file mode 100644 index 00000000..ec84cf7a --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videoio/videoio.hpp @@ -0,0 +1,48 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., all rights reserved. +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifdef __OPENCV_BUILD +#error this is a compatibility header which should not be used inside the OpenCV library +#endif + +#include "opencv2/videoio.hpp" diff --git a/3rdparty/opencv/include/opencv2/videoio/videoio_c.h b/3rdparty/opencv/include/opencv2/videoio/videoio_c.h new file mode 100644 index 00000000..32f6ec7e --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videoio/videoio_c.h @@ -0,0 +1,587 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// Intel License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000, Intel Corporation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of Intel Corporation may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOIO_H +#define OPENCV_VIDEOIO_H + +#include "opencv2/core/core_c.h" + +#ifdef __cplusplus +extern "C" { +#endif /* __cplusplus */ + +/** + @addtogroup videoio_c + @{ +*/ + +/****************************************************************************************\ +* Working with Video Files and Cameras * +\****************************************************************************************/ + +/** @brief "black box" capture structure + +In C++ use cv::VideoCapture +*/ +typedef struct CvCapture CvCapture; + +/** @brief start capturing frames from video file +*/ +CVAPI(CvCapture*) cvCreateFileCapture( const char* filename ); + +/** @brief start capturing frames from video file. allows specifying a preferred API to use +*/ +CVAPI(CvCapture*) cvCreateFileCaptureWithPreference( const char* filename , int apiPreference); + +enum +{ + CV_CAP_ANY =0, // autodetect + + CV_CAP_MIL =100, // MIL proprietary drivers + + CV_CAP_VFW =200, // platform native + CV_CAP_V4L =200, + CV_CAP_V4L2 =200, + + CV_CAP_FIREWARE =300, // IEEE 1394 drivers + CV_CAP_FIREWIRE =300, + CV_CAP_IEEE1394 =300, + CV_CAP_DC1394 =300, + CV_CAP_CMU1394 =300, + + CV_CAP_STEREO =400, // TYZX proprietary drivers + CV_CAP_TYZX =400, + CV_TYZX_LEFT =400, + CV_TYZX_RIGHT =401, + CV_TYZX_COLOR =402, + CV_TYZX_Z =403, + + CV_CAP_QT =500, // QuickTime + + CV_CAP_UNICAP =600, // Unicap drivers + + CV_CAP_DSHOW =700, // DirectShow (via videoInput) + CV_CAP_MSMF =1400, // Microsoft Media Foundation (via videoInput) + + CV_CAP_PVAPI =800, // PvAPI, Prosilica GigE SDK + + CV_CAP_OPENNI =900, // OpenNI (for Kinect) + CV_CAP_OPENNI_ASUS =910, // OpenNI (for Asus Xtion) + + CV_CAP_ANDROID =1000, // Android - not used + CV_CAP_ANDROID_BACK =CV_CAP_ANDROID+99, // Android back camera - not used + CV_CAP_ANDROID_FRONT =CV_CAP_ANDROID+98, // Android front camera - not used + + CV_CAP_XIAPI =1100, // XIMEA Camera API + + CV_CAP_AVFOUNDATION = 1200, // AVFoundation framework for iOS (OS X Lion will have the same API) + + CV_CAP_GIGANETIX = 1300, // Smartek Giganetix GigEVisionSDK + + CV_CAP_INTELPERC = 1500, // Intel Perceptual Computing + + CV_CAP_OPENNI2 = 1600, // OpenNI2 (for Kinect) + CV_CAP_GPHOTO2 = 1700, + CV_CAP_GSTREAMER = 1800, // GStreamer + CV_CAP_FFMPEG = 1900, // FFMPEG + CV_CAP_IMAGES = 2000, // OpenCV Image Sequence (e.g. img_%02d.jpg) + + CV_CAP_ARAVIS = 2100 // Aravis GigE SDK +}; + +/** @brief start capturing frames from camera: index = camera_index + domain_offset (CV_CAP_*) +*/ +CVAPI(CvCapture*) cvCreateCameraCapture( int index ); + +/** @brief grab a frame, return 1 on success, 0 on fail. + + this function is thought to be fast +*/ +CVAPI(int) cvGrabFrame( CvCapture* capture ); + +/** @brief get the frame grabbed with cvGrabFrame(..) + + This function may apply some frame processing like + frame decompression, flipping etc. + @warning !!!DO NOT RELEASE or MODIFY the retrieved frame!!! +*/ +CVAPI(IplImage*) cvRetrieveFrame( CvCapture* capture, int streamIdx CV_DEFAULT(0) ); + +/** @brief Just a combination of cvGrabFrame and cvRetrieveFrame + + @warning !!!DO NOT RELEASE or MODIFY the retrieved frame!!! +*/ +CVAPI(IplImage*) cvQueryFrame( CvCapture* capture ); + +/** @brief stop capturing/reading and free resources +*/ +CVAPI(void) cvReleaseCapture( CvCapture** capture ); + +enum +{ + // modes of the controlling registers (can be: auto, manual, auto single push, absolute Latter allowed with any other mode) + // every feature can have only one mode turned on at a time + CV_CAP_PROP_DC1394_OFF = -4, //turn the feature off (not controlled manually nor automatically) + CV_CAP_PROP_DC1394_MODE_MANUAL = -3, //set automatically when a value of the feature is set by the user + CV_CAP_PROP_DC1394_MODE_AUTO = -2, + CV_CAP_PROP_DC1394_MODE_ONE_PUSH_AUTO = -1, + CV_CAP_PROP_POS_MSEC =0, + CV_CAP_PROP_POS_FRAMES =1, + CV_CAP_PROP_POS_AVI_RATIO =2, + CV_CAP_PROP_FRAME_WIDTH =3, + CV_CAP_PROP_FRAME_HEIGHT =4, + CV_CAP_PROP_FPS =5, + CV_CAP_PROP_FOURCC =6, + CV_CAP_PROP_FRAME_COUNT =7, + CV_CAP_PROP_FORMAT =8, + CV_CAP_PROP_MODE =9, + CV_CAP_PROP_BRIGHTNESS =10, + CV_CAP_PROP_CONTRAST =11, + CV_CAP_PROP_SATURATION =12, + CV_CAP_PROP_HUE =13, + CV_CAP_PROP_GAIN =14, + CV_CAP_PROP_EXPOSURE =15, + CV_CAP_PROP_CONVERT_RGB =16, + CV_CAP_PROP_WHITE_BALANCE_BLUE_U =17, + CV_CAP_PROP_RECTIFICATION =18, + CV_CAP_PROP_MONOCHROME =19, + CV_CAP_PROP_SHARPNESS =20, + CV_CAP_PROP_AUTO_EXPOSURE =21, // exposure control done by camera, + // user can adjust reference level + // using this feature + CV_CAP_PROP_GAMMA =22, + CV_CAP_PROP_TEMPERATURE =23, + CV_CAP_PROP_TRIGGER =24, + CV_CAP_PROP_TRIGGER_DELAY =25, + CV_CAP_PROP_WHITE_BALANCE_RED_V =26, + CV_CAP_PROP_ZOOM =27, + CV_CAP_PROP_FOCUS =28, + CV_CAP_PROP_GUID =29, + CV_CAP_PROP_ISO_SPEED =30, + CV_CAP_PROP_MAX_DC1394 =31, + CV_CAP_PROP_BACKLIGHT =32, + CV_CAP_PROP_PAN =33, + CV_CAP_PROP_TILT =34, + CV_CAP_PROP_ROLL =35, + CV_CAP_PROP_IRIS =36, + CV_CAP_PROP_SETTINGS =37, + CV_CAP_PROP_BUFFERSIZE =38, + CV_CAP_PROP_AUTOFOCUS =39, + CV_CAP_PROP_SAR_NUM =40, + CV_CAP_PROP_SAR_DEN =41, + + CV_CAP_PROP_AUTOGRAB =1024, // property for videoio class CvCapture_Android only + CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING=1025, // readonly, tricky property, returns cpnst char* indeed + CV_CAP_PROP_PREVIEW_FORMAT=1026, // readonly, tricky property, returns cpnst char* indeed + + // OpenNI map generators + CV_CAP_OPENNI_DEPTH_GENERATOR = 1 << 31, + CV_CAP_OPENNI_IMAGE_GENERATOR = 1 << 30, + CV_CAP_OPENNI_IR_GENERATOR = 1 << 29, + CV_CAP_OPENNI_GENERATORS_MASK = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_OPENNI_IMAGE_GENERATOR + CV_CAP_OPENNI_IR_GENERATOR, + + // Properties of cameras available through OpenNI interfaces + CV_CAP_PROP_OPENNI_OUTPUT_MODE = 100, + CV_CAP_PROP_OPENNI_FRAME_MAX_DEPTH = 101, // in mm + CV_CAP_PROP_OPENNI_BASELINE = 102, // in mm + CV_CAP_PROP_OPENNI_FOCAL_LENGTH = 103, // in pixels + CV_CAP_PROP_OPENNI_REGISTRATION = 104, // flag + CV_CAP_PROP_OPENNI_REGISTRATION_ON = CV_CAP_PROP_OPENNI_REGISTRATION, // flag that synchronizes the remapping depth map to image map + // by changing depth generator's view point (if the flag is "on") or + // sets this view point to its normal one (if the flag is "off"). + CV_CAP_PROP_OPENNI_APPROX_FRAME_SYNC = 105, + CV_CAP_PROP_OPENNI_MAX_BUFFER_SIZE = 106, + CV_CAP_PROP_OPENNI_CIRCLE_BUFFER = 107, + CV_CAP_PROP_OPENNI_MAX_TIME_DURATION = 108, + + CV_CAP_PROP_OPENNI_GENERATOR_PRESENT = 109, + CV_CAP_PROP_OPENNI2_SYNC = 110, + CV_CAP_PROP_OPENNI2_MIRROR = 111, + + CV_CAP_OPENNI_IMAGE_GENERATOR_PRESENT = CV_CAP_OPENNI_IMAGE_GENERATOR + CV_CAP_PROP_OPENNI_GENERATOR_PRESENT, + CV_CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE = CV_CAP_OPENNI_IMAGE_GENERATOR + CV_CAP_PROP_OPENNI_OUTPUT_MODE, + CV_CAP_OPENNI_DEPTH_GENERATOR_PRESENT = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_GENERATOR_PRESENT, + CV_CAP_OPENNI_DEPTH_GENERATOR_BASELINE = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_BASELINE, + CV_CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_FOCAL_LENGTH, + CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CV_CAP_OPENNI_DEPTH_GENERATOR + CV_CAP_PROP_OPENNI_REGISTRATION, + CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION_ON = CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION, + CV_CAP_OPENNI_IR_GENERATOR_PRESENT = CV_CAP_OPENNI_IR_GENERATOR + CV_CAP_PROP_OPENNI_GENERATOR_PRESENT, + + // Properties of cameras available through GStreamer interface + CV_CAP_GSTREAMER_QUEUE_LENGTH = 200, // default is 1 + + // PVAPI + CV_CAP_PROP_PVAPI_MULTICASTIP = 300, // ip for anable multicast master mode. 0 for disable multicast + CV_CAP_PROP_PVAPI_FRAMESTARTTRIGGERMODE = 301, // FrameStartTriggerMode: Determines how a frame is initiated + CV_CAP_PROP_PVAPI_DECIMATIONHORIZONTAL = 302, // Horizontal sub-sampling of the image + CV_CAP_PROP_PVAPI_DECIMATIONVERTICAL = 303, // Vertical sub-sampling of the image + CV_CAP_PROP_PVAPI_BINNINGX = 304, // Horizontal binning factor + CV_CAP_PROP_PVAPI_BINNINGY = 305, // Vertical binning factor + CV_CAP_PROP_PVAPI_PIXELFORMAT = 306, // Pixel format + + // Properties of cameras available through XIMEA SDK interface + CV_CAP_PROP_XI_DOWNSAMPLING = 400, // Change image resolution by binning or skipping. + CV_CAP_PROP_XI_DATA_FORMAT = 401, // Output data format. + CV_CAP_PROP_XI_OFFSET_X = 402, // Horizontal offset from the origin to the area of interest (in pixels). + CV_CAP_PROP_XI_OFFSET_Y = 403, // Vertical offset from the origin to the area of interest (in pixels). + CV_CAP_PROP_XI_TRG_SOURCE = 404, // Defines source of trigger. + CV_CAP_PROP_XI_TRG_SOFTWARE = 405, // Generates an internal trigger. PRM_TRG_SOURCE must be set to TRG_SOFTWARE. + CV_CAP_PROP_XI_GPI_SELECTOR = 406, // Selects general purpose input + CV_CAP_PROP_XI_GPI_MODE = 407, // Set general purpose input mode + CV_CAP_PROP_XI_GPI_LEVEL = 408, // Get general purpose level + CV_CAP_PROP_XI_GPO_SELECTOR = 409, // Selects general purpose output + CV_CAP_PROP_XI_GPO_MODE = 410, // Set general purpose output mode + CV_CAP_PROP_XI_LED_SELECTOR = 411, // Selects camera signalling LED + CV_CAP_PROP_XI_LED_MODE = 412, // Define camera signalling LED functionality + CV_CAP_PROP_XI_MANUAL_WB = 413, // Calculates White Balance(must be called during acquisition) + CV_CAP_PROP_XI_AUTO_WB = 414, // Automatic white balance + CV_CAP_PROP_XI_AEAG = 415, // Automatic exposure/gain + CV_CAP_PROP_XI_EXP_PRIORITY = 416, // Exposure priority (0.5 - exposure 50%, gain 50%). + CV_CAP_PROP_XI_AE_MAX_LIMIT = 417, // Maximum limit of exposure in AEAG procedure + CV_CAP_PROP_XI_AG_MAX_LIMIT = 418, // Maximum limit of gain in AEAG procedure + CV_CAP_PROP_XI_AEAG_LEVEL = 419, // Average intensity of output signal AEAG should achieve(in %) + CV_CAP_PROP_XI_TIMEOUT = 420, // Image capture timeout in milliseconds + CV_CAP_PROP_XI_EXPOSURE = 421, // Exposure time in microseconds + CV_CAP_PROP_XI_EXPOSURE_BURST_COUNT = 422, // Sets the number of times of exposure in one frame. + CV_CAP_PROP_XI_GAIN_SELECTOR = 423, // Gain selector for parameter Gain allows to select different type of gains. + CV_CAP_PROP_XI_GAIN = 424, // Gain in dB + CV_CAP_PROP_XI_DOWNSAMPLING_TYPE = 426, // Change image downsampling type. + CV_CAP_PROP_XI_BINNING_SELECTOR = 427, // Binning engine selector. + CV_CAP_PROP_XI_BINNING_VERTICAL = 428, // Vertical Binning - number of vertical photo-sensitive cells to combine together. + CV_CAP_PROP_XI_BINNING_HORIZONTAL = 429, // Horizontal Binning - number of horizontal photo-sensitive cells to combine together. + CV_CAP_PROP_XI_BINNING_PATTERN = 430, // Binning pattern type. + CV_CAP_PROP_XI_DECIMATION_SELECTOR = 431, // Decimation engine selector. + CV_CAP_PROP_XI_DECIMATION_VERTICAL = 432, // Vertical Decimation - vertical sub-sampling of the image - reduces the vertical resolution of the image by the specified vertical decimation factor. + CV_CAP_PROP_XI_DECIMATION_HORIZONTAL = 433, // Horizontal Decimation - horizontal sub-sampling of the image - reduces the horizontal resolution of the image by the specified vertical decimation factor. + CV_CAP_PROP_XI_DECIMATION_PATTERN = 434, // Decimation pattern type. + CV_CAP_PROP_XI_TEST_PATTERN_GENERATOR_SELECTOR = 587, // Selects which test pattern generator is controlled by the TestPattern feature. + CV_CAP_PROP_XI_TEST_PATTERN = 588, // Selects which test pattern type is generated by the selected generator. + CV_CAP_PROP_XI_IMAGE_DATA_FORMAT = 435, // Output data format. + CV_CAP_PROP_XI_SHUTTER_TYPE = 436, // Change sensor shutter type(CMOS sensor). + CV_CAP_PROP_XI_SENSOR_TAPS = 437, // Number of taps + CV_CAP_PROP_XI_AEAG_ROI_OFFSET_X = 439, // Automatic exposure/gain ROI offset X + CV_CAP_PROP_XI_AEAG_ROI_OFFSET_Y = 440, // Automatic exposure/gain ROI offset Y + CV_CAP_PROP_XI_AEAG_ROI_WIDTH = 441, // Automatic exposure/gain ROI Width + CV_CAP_PROP_XI_AEAG_ROI_HEIGHT = 442, // Automatic exposure/gain ROI Height + CV_CAP_PROP_XI_BPC = 445, // Correction of bad pixels + CV_CAP_PROP_XI_WB_KR = 448, // White balance red coefficient + CV_CAP_PROP_XI_WB_KG = 449, // White balance green coefficient + CV_CAP_PROP_XI_WB_KB = 450, // White balance blue coefficient + CV_CAP_PROP_XI_WIDTH = 451, // Width of the Image provided by the device (in pixels). + CV_CAP_PROP_XI_HEIGHT = 452, // Height of the Image provided by the device (in pixels). + CV_CAP_PROP_XI_REGION_SELECTOR = 589, // Selects Region in Multiple ROI which parameters are set by width, height, ... ,region mode + CV_CAP_PROP_XI_REGION_MODE = 595, // Activates/deactivates Region selected by Region Selector + CV_CAP_PROP_XI_LIMIT_BANDWIDTH = 459, // Set/get bandwidth(datarate)(in Megabits) + CV_CAP_PROP_XI_SENSOR_DATA_BIT_DEPTH = 460, // Sensor output data bit depth. + CV_CAP_PROP_XI_OUTPUT_DATA_BIT_DEPTH = 461, // Device output data bit depth. + CV_CAP_PROP_XI_IMAGE_DATA_BIT_DEPTH = 462, // bitdepth of data returned by function xiGetImage + CV_CAP_PROP_XI_OUTPUT_DATA_PACKING = 463, // Device output data packing (or grouping) enabled. Packing could be enabled if output_data_bit_depth > 8 and packing capability is available. + CV_CAP_PROP_XI_OUTPUT_DATA_PACKING_TYPE = 464, // Data packing type. Some cameras supports only specific packing type. + CV_CAP_PROP_XI_IS_COOLED = 465, // Returns 1 for cameras that support cooling. + CV_CAP_PROP_XI_COOLING = 466, // Start camera cooling. + CV_CAP_PROP_XI_TARGET_TEMP = 467, // Set sensor target temperature for cooling. + CV_CAP_PROP_XI_CHIP_TEMP = 468, // Camera sensor temperature + CV_CAP_PROP_XI_HOUS_TEMP = 469, // Camera housing tepmerature + CV_CAP_PROP_XI_HOUS_BACK_SIDE_TEMP = 590, // Camera housing back side tepmerature + CV_CAP_PROP_XI_SENSOR_BOARD_TEMP = 596, // Camera sensor board temperature + CV_CAP_PROP_XI_CMS = 470, // Mode of color management system. + CV_CAP_PROP_XI_APPLY_CMS = 471, // Enable applying of CMS profiles to xiGetImage (see XI_PRM_INPUT_CMS_PROFILE, XI_PRM_OUTPUT_CMS_PROFILE). + CV_CAP_PROP_XI_IMAGE_IS_COLOR = 474, // Returns 1 for color cameras. + CV_CAP_PROP_XI_COLOR_FILTER_ARRAY = 475, // Returns color filter array type of RAW data. + CV_CAP_PROP_XI_GAMMAY = 476, // Luminosity gamma + CV_CAP_PROP_XI_GAMMAC = 477, // Chromaticity gamma + CV_CAP_PROP_XI_SHARPNESS = 478, // Sharpness Strength + CV_CAP_PROP_XI_CC_MATRIX_00 = 479, // Color Correction Matrix element [0][0] + CV_CAP_PROP_XI_CC_MATRIX_01 = 480, // Color Correction Matrix element [0][1] + CV_CAP_PROP_XI_CC_MATRIX_02 = 481, // Color Correction Matrix element [0][2] + CV_CAP_PROP_XI_CC_MATRIX_03 = 482, // Color Correction Matrix element [0][3] + CV_CAP_PROP_XI_CC_MATRIX_10 = 483, // Color Correction Matrix element [1][0] + CV_CAP_PROP_XI_CC_MATRIX_11 = 484, // Color Correction Matrix element [1][1] + CV_CAP_PROP_XI_CC_MATRIX_12 = 485, // Color Correction Matrix element [1][2] + CV_CAP_PROP_XI_CC_MATRIX_13 = 486, // Color Correction Matrix element [1][3] + CV_CAP_PROP_XI_CC_MATRIX_20 = 487, // Color Correction Matrix element [2][0] + CV_CAP_PROP_XI_CC_MATRIX_21 = 488, // Color Correction Matrix element [2][1] + CV_CAP_PROP_XI_CC_MATRIX_22 = 489, // Color Correction Matrix element [2][2] + CV_CAP_PROP_XI_CC_MATRIX_23 = 490, // Color Correction Matrix element [2][3] + CV_CAP_PROP_XI_CC_MATRIX_30 = 491, // Color Correction Matrix element [3][0] + CV_CAP_PROP_XI_CC_MATRIX_31 = 492, // Color Correction Matrix element [3][1] + CV_CAP_PROP_XI_CC_MATRIX_32 = 493, // Color Correction Matrix element [3][2] + CV_CAP_PROP_XI_CC_MATRIX_33 = 494, // Color Correction Matrix element [3][3] + CV_CAP_PROP_XI_DEFAULT_CC_MATRIX = 495, // Set default Color Correction Matrix + CV_CAP_PROP_XI_TRG_SELECTOR = 498, // Selects the type of trigger. + CV_CAP_PROP_XI_ACQ_FRAME_BURST_COUNT = 499, // Sets number of frames acquired by burst. This burst is used only if trigger is set to FrameBurstStart + CV_CAP_PROP_XI_DEBOUNCE_EN = 507, // Enable/Disable debounce to selected GPI + CV_CAP_PROP_XI_DEBOUNCE_T0 = 508, // Debounce time (x * 10us) + CV_CAP_PROP_XI_DEBOUNCE_T1 = 509, // Debounce time (x * 10us) + CV_CAP_PROP_XI_DEBOUNCE_POL = 510, // Debounce polarity (pol = 1 t0 - falling edge, t1 - rising edge) + CV_CAP_PROP_XI_LENS_MODE = 511, // Status of lens control interface. This shall be set to XI_ON before any Lens operations. + CV_CAP_PROP_XI_LENS_APERTURE_VALUE = 512, // Current lens aperture value in stops. Examples: 2.8, 4, 5.6, 8, 11 + CV_CAP_PROP_XI_LENS_FOCUS_MOVEMENT_VALUE = 513, // Lens current focus movement value to be used by XI_PRM_LENS_FOCUS_MOVE in motor steps. + CV_CAP_PROP_XI_LENS_FOCUS_MOVE = 514, // Moves lens focus motor by steps set in XI_PRM_LENS_FOCUS_MOVEMENT_VALUE. + CV_CAP_PROP_XI_LENS_FOCUS_DISTANCE = 515, // Lens focus distance in cm. + CV_CAP_PROP_XI_LENS_FOCAL_LENGTH = 516, // Lens focal distance in mm. + CV_CAP_PROP_XI_LENS_FEATURE_SELECTOR = 517, // Selects the current feature which is accessible by XI_PRM_LENS_FEATURE. + CV_CAP_PROP_XI_LENS_FEATURE = 518, // Allows access to lens feature value currently selected by XI_PRM_LENS_FEATURE_SELECTOR. + CV_CAP_PROP_XI_DEVICE_MODEL_ID = 521, // Return device model id + CV_CAP_PROP_XI_DEVICE_SN = 522, // Return device serial number + CV_CAP_PROP_XI_IMAGE_DATA_FORMAT_RGB32_ALPHA = 529, // The alpha channel of RGB32 output image format. + CV_CAP_PROP_XI_IMAGE_PAYLOAD_SIZE = 530, // Buffer size in bytes sufficient for output image returned by xiGetImage + CV_CAP_PROP_XI_TRANSPORT_PIXEL_FORMAT = 531, // Current format of pixels on transport layer. + CV_CAP_PROP_XI_SENSOR_CLOCK_FREQ_HZ = 532, // Sensor clock frequency in Hz. + CV_CAP_PROP_XI_SENSOR_CLOCK_FREQ_INDEX = 533, // Sensor clock frequency index. Sensor with selected frequencies have possibility to set the frequency only by this index. + CV_CAP_PROP_XI_SENSOR_OUTPUT_CHANNEL_COUNT = 534, // Number of output channels from sensor used for data transfer. + CV_CAP_PROP_XI_FRAMERATE = 535, // Define framerate in Hz + CV_CAP_PROP_XI_COUNTER_SELECTOR = 536, // Select counter + CV_CAP_PROP_XI_COUNTER_VALUE = 537, // Counter status + CV_CAP_PROP_XI_ACQ_TIMING_MODE = 538, // Type of sensor frames timing. + CV_CAP_PROP_XI_AVAILABLE_BANDWIDTH = 539, // Calculate and return available interface bandwidth(int Megabits) + CV_CAP_PROP_XI_BUFFER_POLICY = 540, // Data move policy + CV_CAP_PROP_XI_LUT_EN = 541, // Activates LUT. + CV_CAP_PROP_XI_LUT_INDEX = 542, // Control the index (offset) of the coefficient to access in the LUT. + CV_CAP_PROP_XI_LUT_VALUE = 543, // Value at entry LUTIndex of the LUT + CV_CAP_PROP_XI_TRG_DELAY = 544, // Specifies the delay in microseconds (us) to apply after the trigger reception before activating it. + CV_CAP_PROP_XI_TS_RST_MODE = 545, // Defines how time stamp reset engine will be armed + CV_CAP_PROP_XI_TS_RST_SOURCE = 546, // Defines which source will be used for timestamp reset. Writing this parameter will trigger settings of engine (arming) + CV_CAP_PROP_XI_IS_DEVICE_EXIST = 547, // Returns 1 if camera connected and works properly. + CV_CAP_PROP_XI_ACQ_BUFFER_SIZE = 548, // Acquisition buffer size in buffer_size_unit. Default bytes. + CV_CAP_PROP_XI_ACQ_BUFFER_SIZE_UNIT = 549, // Acquisition buffer size unit in bytes. Default 1. E.g. Value 1024 means that buffer_size is in KiBytes + CV_CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_SIZE = 550, // Acquisition transport buffer size in bytes + CV_CAP_PROP_XI_BUFFERS_QUEUE_SIZE = 551, // Queue of field/frame buffers + CV_CAP_PROP_XI_ACQ_TRANSPORT_BUFFER_COMMIT = 552, // Number of buffers to commit to low level + CV_CAP_PROP_XI_RECENT_FRAME = 553, // GetImage returns most recent frame + CV_CAP_PROP_XI_DEVICE_RESET = 554, // Resets the camera to default state. + CV_CAP_PROP_XI_COLUMN_FPN_CORRECTION = 555, // Correction of column FPN + CV_CAP_PROP_XI_ROW_FPN_CORRECTION = 591, // Correction of row FPN + CV_CAP_PROP_XI_SENSOR_MODE = 558, // Current sensor mode. Allows to select sensor mode by one integer. Setting of this parameter affects: image dimensions and downsampling. + CV_CAP_PROP_XI_HDR = 559, // Enable High Dynamic Range feature. + CV_CAP_PROP_XI_HDR_KNEEPOINT_COUNT = 560, // The number of kneepoints in the PWLR. + CV_CAP_PROP_XI_HDR_T1 = 561, // position of first kneepoint(in % of XI_PRM_EXPOSURE) + CV_CAP_PROP_XI_HDR_T2 = 562, // position of second kneepoint (in % of XI_PRM_EXPOSURE) + CV_CAP_PROP_XI_KNEEPOINT1 = 563, // value of first kneepoint (% of sensor saturation) + CV_CAP_PROP_XI_KNEEPOINT2 = 564, // value of second kneepoint (% of sensor saturation) + CV_CAP_PROP_XI_IMAGE_BLACK_LEVEL = 565, // Last image black level counts. Can be used for Offline processing to recall it. + CV_CAP_PROP_XI_HW_REVISION = 571, // Returns hardware revision number. + CV_CAP_PROP_XI_DEBUG_LEVEL = 572, // Set debug level + CV_CAP_PROP_XI_AUTO_BANDWIDTH_CALCULATION = 573, // Automatic bandwidth calculation, + CV_CAP_PROP_XI_FFS_FILE_ID = 594, // File number. + CV_CAP_PROP_XI_FFS_FILE_SIZE = 580, // Size of file. + CV_CAP_PROP_XI_FREE_FFS_SIZE = 581, // Size of free camera FFS. + CV_CAP_PROP_XI_USED_FFS_SIZE = 582, // Size of used camera FFS. + CV_CAP_PROP_XI_FFS_ACCESS_KEY = 583, // Setting of key enables file operations on some cameras. + CV_CAP_PROP_XI_SENSOR_FEATURE_SELECTOR = 585, // Selects the current feature which is accessible by XI_PRM_SENSOR_FEATURE_VALUE. + CV_CAP_PROP_XI_SENSOR_FEATURE_VALUE = 586, // Allows access to sensor feature value currently selected by XI_PRM_SENSOR_FEATURE_SELECTOR. + + + // Properties for Android cameras + CV_CAP_PROP_ANDROID_FLASH_MODE = 8001, + CV_CAP_PROP_ANDROID_FOCUS_MODE = 8002, + CV_CAP_PROP_ANDROID_WHITE_BALANCE = 8003, + CV_CAP_PROP_ANDROID_ANTIBANDING = 8004, + CV_CAP_PROP_ANDROID_FOCAL_LENGTH = 8005, + CV_CAP_PROP_ANDROID_FOCUS_DISTANCE_NEAR = 8006, + CV_CAP_PROP_ANDROID_FOCUS_DISTANCE_OPTIMAL = 8007, + CV_CAP_PROP_ANDROID_FOCUS_DISTANCE_FAR = 8008, + CV_CAP_PROP_ANDROID_EXPOSE_LOCK = 8009, + CV_CAP_PROP_ANDROID_WHITEBALANCE_LOCK = 8010, + + // Properties of cameras available through AVFOUNDATION interface + CV_CAP_PROP_IOS_DEVICE_FOCUS = 9001, + CV_CAP_PROP_IOS_DEVICE_EXPOSURE = 9002, + CV_CAP_PROP_IOS_DEVICE_FLASH = 9003, + CV_CAP_PROP_IOS_DEVICE_WHITEBALANCE = 9004, + CV_CAP_PROP_IOS_DEVICE_TORCH = 9005, + + // Properties of cameras available through Smartek Giganetix Ethernet Vision interface + /* --- Vladimir Litvinenko (litvinenko.vladimir@gmail.com) --- */ + CV_CAP_PROP_GIGA_FRAME_OFFSET_X = 10001, + CV_CAP_PROP_GIGA_FRAME_OFFSET_Y = 10002, + CV_CAP_PROP_GIGA_FRAME_WIDTH_MAX = 10003, + CV_CAP_PROP_GIGA_FRAME_HEIGH_MAX = 10004, + CV_CAP_PROP_GIGA_FRAME_SENS_WIDTH = 10005, + CV_CAP_PROP_GIGA_FRAME_SENS_HEIGH = 10006, + + CV_CAP_PROP_INTELPERC_PROFILE_COUNT = 11001, + CV_CAP_PROP_INTELPERC_PROFILE_IDX = 11002, + CV_CAP_PROP_INTELPERC_DEPTH_LOW_CONFIDENCE_VALUE = 11003, + CV_CAP_PROP_INTELPERC_DEPTH_SATURATION_VALUE = 11004, + CV_CAP_PROP_INTELPERC_DEPTH_CONFIDENCE_THRESHOLD = 11005, + CV_CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_HORZ = 11006, + CV_CAP_PROP_INTELPERC_DEPTH_FOCAL_LENGTH_VERT = 11007, + + // Intel PerC streams + CV_CAP_INTELPERC_DEPTH_GENERATOR = 1 << 29, + CV_CAP_INTELPERC_IMAGE_GENERATOR = 1 << 28, + CV_CAP_INTELPERC_GENERATORS_MASK = CV_CAP_INTELPERC_DEPTH_GENERATOR + CV_CAP_INTELPERC_IMAGE_GENERATOR +}; + +// Generic camera output modes. +// Currently, these are supported through the libv4l interface only. +enum +{ + CV_CAP_MODE_BGR = 0, // BGR24 (default) + CV_CAP_MODE_RGB = 1, // RGB24 + CV_CAP_MODE_GRAY = 2, // Y8 + CV_CAP_MODE_YUYV = 3 // YUYV +}; + +enum +{ + // Data given from depth generator. + CV_CAP_OPENNI_DEPTH_MAP = 0, // Depth values in mm (CV_16UC1) + CV_CAP_OPENNI_POINT_CLOUD_MAP = 1, // XYZ in meters (CV_32FC3) + CV_CAP_OPENNI_DISPARITY_MAP = 2, // Disparity in pixels (CV_8UC1) + CV_CAP_OPENNI_DISPARITY_MAP_32F = 3, // Disparity in pixels (CV_32FC1) + CV_CAP_OPENNI_VALID_DEPTH_MASK = 4, // CV_8UC1 + + // Data given from RGB image generator. + CV_CAP_OPENNI_BGR_IMAGE = 5, + CV_CAP_OPENNI_GRAY_IMAGE = 6, + + // Data given from IR image generator. + CV_CAP_OPENNI_IR_IMAGE = 7 +}; + +// Supported output modes of OpenNI image generator +enum +{ + CV_CAP_OPENNI_VGA_30HZ = 0, + CV_CAP_OPENNI_SXGA_15HZ = 1, + CV_CAP_OPENNI_SXGA_30HZ = 2, + CV_CAP_OPENNI_QVGA_30HZ = 3, + CV_CAP_OPENNI_QVGA_60HZ = 4 +}; + +enum +{ + CV_CAP_INTELPERC_DEPTH_MAP = 0, // Each pixel is a 16-bit integer. The value indicates the distance from an object to the camera's XY plane or the Cartesian depth. + CV_CAP_INTELPERC_UVDEPTH_MAP = 1, // Each pixel contains two 32-bit floating point values in the range of 0-1, representing the mapping of depth coordinates to the color coordinates. + CV_CAP_INTELPERC_IR_MAP = 2, // Each pixel is a 16-bit integer. The value indicates the intensity of the reflected laser beam. + CV_CAP_INTELPERC_IMAGE = 3 +}; + +// gPhoto2 properties, if propertyId is less than 0 then work on widget with that __additive inversed__ camera setting ID +// Get IDs by using CAP_PROP_GPHOTO2_WIDGET_ENUMERATE. +// @see CvCaptureCAM_GPHOTO2 for more info +enum +{ + CV_CAP_PROP_GPHOTO2_PREVIEW = 17001, // Capture only preview from liveview mode. + CV_CAP_PROP_GPHOTO2_WIDGET_ENUMERATE = 17002, // Readonly, returns (const char *). + CV_CAP_PROP_GPHOTO2_RELOAD_CONFIG = 17003, // Trigger, only by set. Reload camera settings. + CV_CAP_PROP_GPHOTO2_RELOAD_ON_CHANGE = 17004, // Reload all settings on set. + CV_CAP_PROP_GPHOTO2_COLLECT_MSGS = 17005, // Collect messages with details. + CV_CAP_PROP_GPHOTO2_FLUSH_MSGS = 17006, // Readonly, returns (const char *). + CV_CAP_PROP_SPEED = 17007, // Exposure speed. Can be readonly, depends on camera program. + CV_CAP_PROP_APERTURE = 17008, // Aperture. Can be readonly, depends on camera program. + CV_CAP_PROP_EXPOSUREPROGRAM = 17009, // Camera exposure program. + CV_CAP_PROP_VIEWFINDER = 17010 // Enter liveview mode. +}; + +/** @brief retrieve capture properties +*/ +CVAPI(double) cvGetCaptureProperty( CvCapture* capture, int property_id ); +/** @brief set capture properties +*/ +CVAPI(int) cvSetCaptureProperty( CvCapture* capture, int property_id, double value ); + +/** @brief Return the type of the capturer (eg, ::CV_CAP_VFW, ::CV_CAP_UNICAP) + +It is unknown if created with ::CV_CAP_ANY +*/ +CVAPI(int) cvGetCaptureDomain( CvCapture* capture); + +/** @brief "black box" video file writer structure + +In C++ use cv::VideoWriter +*/ +typedef struct CvVideoWriter CvVideoWriter; + +//! Macro to construct the fourcc code of the codec. Same as CV_FOURCC() +#define CV_FOURCC_MACRO(c1, c2, c3, c4) (((c1) & 255) + (((c2) & 255) << 8) + (((c3) & 255) << 16) + (((c4) & 255) << 24)) + +/** @brief Constructs the fourcc code of the codec function + +Simply call it with 4 chars fourcc code like `CV_FOURCC('I', 'Y', 'U', 'V')` + +List of codes can be obtained at [Video Codecs by FOURCC](http://www.fourcc.org/codecs.php) page. +FFMPEG backend with MP4 container natively uses other values as fourcc code: +see [ObjectType](http://www.mp4ra.org/codecs.html). +*/ +CV_INLINE int CV_FOURCC(char c1, char c2, char c3, char c4) +{ + return CV_FOURCC_MACRO(c1, c2, c3, c4); +} + +//! (Windows only) Open Codec Selection Dialog +#define CV_FOURCC_PROMPT -1 +//! (Linux only) Use default codec for specified filename +#define CV_FOURCC_DEFAULT CV_FOURCC('I', 'Y', 'U', 'V') + +/** @brief initialize video file writer +*/ +CVAPI(CvVideoWriter*) cvCreateVideoWriter( const char* filename, int fourcc, + double fps, CvSize frame_size, + int is_color CV_DEFAULT(1)); + +/** @brief write frame to video file +*/ +CVAPI(int) cvWriteFrame( CvVideoWriter* writer, const IplImage* image ); + +/** @brief close video file writer +*/ +CVAPI(void) cvReleaseVideoWriter( CvVideoWriter** writer ); + +// *************************************************************************************** +//! @name Obsolete functions/synonyms +//! @{ +#define cvCaptureFromCAM cvCreateCameraCapture //!< @deprecated use cvCreateCameraCapture() instead +#define cvCaptureFromFile cvCreateFileCapture //!< @deprecated use cvCreateFileCapture() instead +#define cvCaptureFromAVI cvCaptureFromFile //!< @deprecated use cvCreateFileCapture() instead +#define cvCreateAVIWriter cvCreateVideoWriter //!< @deprecated use cvCreateVideoWriter() instead +#define cvWriteToAVI cvWriteFrame //!< @deprecated use cvWriteFrame() instead +//! @} Obsolete... + +//! @} videoio_c + +#ifdef __cplusplus +} +#endif + +#endif //OPENCV_VIDEOIO_H diff --git a/3rdparty/opencv/include/opencv2/videostab.hpp b/3rdparty/opencv/include/opencv2/videostab.hpp new file mode 100644 index 00000000..ca3f5ade --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab.hpp @@ -0,0 +1,81 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_HPP +#define OPENCV_VIDEOSTAB_HPP + +/** + @defgroup videostab Video Stabilization + +The video stabilization module contains a set of functions and classes that can be used to solve the +problem of video stabilization. There are a few methods implemented, most of them are described in +the papers @cite OF06 and @cite G11 . However, there are some extensions and deviations from the original +paper methods. + +### References + + 1. "Full-Frame Video Stabilization with Motion Inpainting" + Yasuyuki Matsushita, Eyal Ofek, Weina Ge, Xiaoou Tang, Senior Member, and Heung-Yeung Shum + 2. "Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths" + Matthias Grundmann, Vivek Kwatra, Irfan Essa + + @{ + @defgroup videostab_motion Global Motion Estimation + +The video stabilization module contains a set of functions and classes for global motion estimation +between point clouds or between images. In the last case features are extracted and matched +internally. For the sake of convenience the motion estimation functions are wrapped into classes. +Both the functions and the classes are available. + + @defgroup videostab_marching Fast Marching Method + +The Fast Marching Method @cite Telea04 is used in of the video stabilization routines to do motion and +color inpainting. The method is implemented is a flexible way and it's made public for other users. + + @} + +*/ + +#include "opencv2/videostab/stabilizer.hpp" +#include "opencv2/videostab/ring_buffer.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/deblurring.hpp b/3rdparty/opencv/include/opencv2/videostab/deblurring.hpp new file mode 100644 index 00000000..c6656401 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/deblurring.hpp @@ -0,0 +1,116 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_DEBLURRING_HPP +#define OPENCV_VIDEOSTAB_DEBLURRING_HPP + +#include +#include "opencv2/core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +CV_EXPORTS float calcBlurriness(const Mat &frame); + +class CV_EXPORTS DeblurerBase +{ +public: + DeblurerBase() : radius_(0), frames_(0), motions_(0), blurrinessRates_(0) {} + + virtual ~DeblurerBase() {} + + virtual void setRadius(int val) { radius_ = val; } + virtual int radius() const { return radius_; } + + virtual void deblur(int idx, Mat &frame) = 0; + + + // data from stabilizer + + virtual void setFrames(const std::vector &val) { frames_ = &val; } + virtual const std::vector& frames() const { return *frames_; } + + virtual void setMotions(const std::vector &val) { motions_ = &val; } + virtual const std::vector& motions() const { return *motions_; } + + virtual void setBlurrinessRates(const std::vector &val) { blurrinessRates_ = &val; } + virtual const std::vector& blurrinessRates() const { return *blurrinessRates_; } + +protected: + int radius_; + const std::vector *frames_; + const std::vector *motions_; + const std::vector *blurrinessRates_; +}; + +class CV_EXPORTS NullDeblurer : public DeblurerBase +{ +public: + virtual void deblur(int /*idx*/, Mat &/*frame*/) CV_OVERRIDE {} +}; + +class CV_EXPORTS WeightingDeblurer : public DeblurerBase +{ +public: + WeightingDeblurer(); + + void setSensitivity(float val) { sensitivity_ = val; } + float sensitivity() const { return sensitivity_; } + + virtual void deblur(int idx, Mat &frame) CV_OVERRIDE; + +private: + float sensitivity_; + Mat_ bSum_, gSum_, rSum_, wSum_; +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/fast_marching.hpp b/3rdparty/opencv/include/opencv2/videostab/fast_marching.hpp new file mode 100644 index 00000000..43f8e4a7 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/fast_marching.hpp @@ -0,0 +1,121 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_FAST_MARCHING_HPP +#define OPENCV_VIDEOSTAB_FAST_MARCHING_HPP + +#include +#include +#include +#include "opencv2/core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab_marching +//! @{ + +/** @brief Describes the Fast Marching Method implementation. + + See http://iwi.eldoc.ub.rug.nl/FILES/root/2004/JGraphToolsTelea/2004JGraphToolsTelea.pdf + */ +class CV_EXPORTS FastMarchingMethod +{ +public: + FastMarchingMethod() : inf_(1e6f), size_(0) {} + + /** @brief Template method that runs the Fast Marching Method. + + @param mask Image mask. 0 value indicates that the pixel value must be inpainted, 255 indicates + that the pixel value is known, other values aren't acceptable. + @param inpaint Inpainting functor that overloads void operator ()(int x, int y). + @return Inpainting functor. + */ + template + Inpaint run(const Mat &mask, Inpaint inpaint); + + /** + @return Distance map that's created during working of the method. + */ + Mat distanceMap() const { return dist_; } + +private: + enum { INSIDE = 0, BAND = 1, KNOWN = 255 }; + + struct DXY + { + float dist; + int x, y; + + DXY() : dist(0), x(0), y(0) {} + DXY(float _dist, int _x, int _y) : dist(_dist), x(_x), y(_y) {} + bool operator <(const DXY &dxy) const { return dist < dxy.dist; } + }; + + float solve(int x1, int y1, int x2, int y2) const; + int& indexOf(const DXY &dxy) { return index_(dxy.y, dxy.x); } + + void heapUp(int idx); + void heapDown(int idx); + void heapAdd(const DXY &dxy); + void heapRemoveMin(); + + float inf_; + + cv::Mat_ flag_; // flag map + cv::Mat_ dist_; // distance map + + cv::Mat_ index_; // index of point in the narrow band + std::vector narrowBand_; // narrow band heap + int size_; // narrow band size +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#include "fast_marching_inl.hpp" + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/fast_marching_inl.hpp b/3rdparty/opencv/include/opencv2/videostab/fast_marching_inl.hpp new file mode 100644 index 00000000..fdd488aa --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/fast_marching_inl.hpp @@ -0,0 +1,165 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_FAST_MARCHING_INL_HPP +#define OPENCV_VIDEOSTAB_FAST_MARCHING_INL_HPP + +#include "opencv2/videostab/fast_marching.hpp" + +namespace cv +{ +namespace videostab +{ + +template +Inpaint FastMarchingMethod::run(const cv::Mat &mask, Inpaint inpaint) +{ + using namespace cv; + + CV_Assert(mask.type() == CV_8U); + + static const int lut[4][2] = {{-1,0}, {0,-1}, {1,0}, {0,1}}; + + mask.copyTo(flag_); + flag_.create(mask.size()); + dist_.create(mask.size()); + index_.create(mask.size()); + narrowBand_.clear(); + size_ = 0; + + // init + for (int y = 0; y < flag_.rows; ++y) + { + for (int x = 0; x < flag_.cols; ++x) + { + if (flag_(y,x) == KNOWN) + dist_(y,x) = 0.f; + else + { + int n = 0; + int nunknown = 0; + + for (int i = 0; i < 4; ++i) + { + int xn = x + lut[i][0]; + int yn = y + lut[i][1]; + + if (xn >= 0 && xn < flag_.cols && yn >= 0 && yn < flag_.rows) + { + n++; + if (flag_(yn,xn) != KNOWN) + nunknown++; + } + } + + if (n>0 && nunknown == n) + { + dist_(y,x) = inf_; + flag_(y,x) = INSIDE; + } + else + { + dist_(y,x) = 0.f; + flag_(y,x) = BAND; + inpaint(x, y); + + narrowBand_.push_back(DXY(0.f,x,y)); + index_(y,x) = size_++; + } + } + } + } + + // make heap + for (int i = size_/2-1; i >= 0; --i) + heapDown(i); + + // main cycle + while (size_ > 0) + { + int x = narrowBand_[0].x; + int y = narrowBand_[0].y; + heapRemoveMin(); + + flag_(y,x) = KNOWN; + for (int n = 0; n < 4; ++n) + { + int xn = x + lut[n][0]; + int yn = y + lut[n][1]; + + if (xn >= 0 && xn < flag_.cols && yn >= 0 && yn < flag_.rows && flag_(yn,xn) != KNOWN) + { + dist_(yn,xn) = std::min(std::min(solve(xn-1, yn, xn, yn-1), solve(xn+1, yn, xn, yn-1)), + std::min(solve(xn-1, yn, xn, yn+1), solve(xn+1, yn, xn, yn+1))); + + if (flag_(yn,xn) == INSIDE) + { + flag_(yn,xn) = BAND; + inpaint(xn, yn); + heapAdd(DXY(dist_(yn,xn),xn,yn)); + } + else + { + int i = index_(yn,xn); + if (dist_(yn,xn) < narrowBand_[i].dist) + { + narrowBand_[i].dist = dist_(yn,xn); + heapUp(i); + } + // works better if it's commented out + /*else if (dist(yn,xn) > narrowBand[i].dist) + { + narrowBand[i].dist = dist(yn,xn); + heapDown(i); + }*/ + } + } + } + } + + return inpaint; +} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/frame_source.hpp b/3rdparty/opencv/include/opencv2/videostab/frame_source.hpp new file mode 100644 index 00000000..171c637c --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/frame_source.hpp @@ -0,0 +1,94 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_FRAME_SOURCE_HPP +#define OPENCV_VIDEOSTAB_FRAME_SOURCE_HPP + +#include +#include "opencv2/core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS IFrameSource +{ +public: + virtual ~IFrameSource() {} + virtual void reset() = 0; + virtual Mat nextFrame() = 0; +}; + +class CV_EXPORTS NullFrameSource : public IFrameSource +{ +public: + virtual void reset() CV_OVERRIDE {} + virtual Mat nextFrame() CV_OVERRIDE { return Mat(); } +}; + +class CV_EXPORTS VideoFileSource : public IFrameSource +{ +public: + VideoFileSource(const String &path, bool volatileFrame = false); + + virtual void reset() CV_OVERRIDE; + virtual Mat nextFrame() CV_OVERRIDE; + + int width(); + int height(); + int count(); + double fps(); + +private: + Ptr impl; +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/global_motion.hpp b/3rdparty/opencv/include/opencv2/videostab/global_motion.hpp new file mode 100644 index 00000000..fedca2cf --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/global_motion.hpp @@ -0,0 +1,300 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_GLOBAL_MOTION_HPP +#define OPENCV_VIDEOSTAB_GLOBAL_MOTION_HPP + +#include +#include +#include "opencv2/core.hpp" +#include "opencv2/features2d.hpp" +#include "opencv2/opencv_modules.hpp" +#include "opencv2/videostab/optical_flow.hpp" +#include "opencv2/videostab/motion_core.hpp" +#include "opencv2/videostab/outlier_rejection.hpp" + +#ifdef HAVE_OPENCV_CUDAIMGPROC +# include "opencv2/cudaimgproc.hpp" +#endif + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab_motion +//! @{ + +/** @brief Estimates best global motion between two 2D point clouds in the least-squares sense. + +@note Works in-place and changes input point arrays. + +@param points0 Source set of 2D points (32F). +@param points1 Destination set of 2D points (32F). +@param model Motion model (up to MM_AFFINE). +@param rmse Final root-mean-square error. +@return 3x3 2D transformation matrix (32F). + */ +CV_EXPORTS Mat estimateGlobalMotionLeastSquares( + InputOutputArray points0, InputOutputArray points1, int model = MM_AFFINE, + float *rmse = 0); + +/** @brief Estimates best global motion between two 2D point clouds robustly (using RANSAC method). + +@param points0 Source set of 2D points (32F). +@param points1 Destination set of 2D points (32F). +@param model Motion model. See cv::videostab::MotionModel. +@param params RANSAC method parameters. See videostab::RansacParams. +@param rmse Final root-mean-square error. +@param ninliers Final number of inliers. + */ +CV_EXPORTS Mat estimateGlobalMotionRansac( + InputArray points0, InputArray points1, int model = MM_AFFINE, + const RansacParams ¶ms = RansacParams::default2dMotion(MM_AFFINE), + float *rmse = 0, int *ninliers = 0); + +/** @brief Base class for all global motion estimation methods. + */ +class CV_EXPORTS MotionEstimatorBase +{ +public: + virtual ~MotionEstimatorBase() {} + + /** @brief Sets motion model. + + @param val Motion model. See cv::videostab::MotionModel. + */ + virtual void setMotionModel(MotionModel val) { motionModel_ = val; } + + /** + @return Motion model. See cv::videostab::MotionModel. + */ + virtual MotionModel motionModel() const { return motionModel_; } + + /** @brief Estimates global motion between two 2D point clouds. + + @param points0 Source set of 2D points (32F). + @param points1 Destination set of 2D points (32F). + @param ok Indicates whether motion was estimated successfully. + @return 3x3 2D transformation matrix (32F). + */ + virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0) = 0; + +protected: + MotionEstimatorBase(MotionModel model) { setMotionModel(model); } + +private: + MotionModel motionModel_; +}; + +/** @brief Describes a robust RANSAC-based global 2D motion estimation method which minimizes L2 error. + */ +class CV_EXPORTS MotionEstimatorRansacL2 : public MotionEstimatorBase +{ +public: + MotionEstimatorRansacL2(MotionModel model = MM_AFFINE); + + void setRansacParams(const RansacParams &val) { ransacParams_ = val; } + RansacParams ransacParams() const { return ransacParams_; } + + void setMinInlierRatio(float val) { minInlierRatio_ = val; } + float minInlierRatio() const { return minInlierRatio_; } + + virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0) CV_OVERRIDE; + +private: + RansacParams ransacParams_; + float minInlierRatio_; +}; + +/** @brief Describes a global 2D motion estimation method which minimizes L1 error. + +@note To be able to use this method you must build OpenCV with CLP library support. : + */ +class CV_EXPORTS MotionEstimatorL1 : public MotionEstimatorBase +{ +public: + MotionEstimatorL1(MotionModel model = MM_AFFINE); + + virtual Mat estimate(InputArray points0, InputArray points1, bool *ok = 0) CV_OVERRIDE; + +private: + std::vector obj_, collb_, colub_; + std::vector elems_, rowlb_, rowub_; + std::vector rows_, cols_; + + void set(int row, int col, double coef) + { + rows_.push_back(row); + cols_.push_back(col); + elems_.push_back(coef); + } +}; + +/** @brief Base class for global 2D motion estimation methods which take frames as input. + */ +class CV_EXPORTS ImageMotionEstimatorBase +{ +public: + virtual ~ImageMotionEstimatorBase() {} + + virtual void setMotionModel(MotionModel val) { motionModel_ = val; } + virtual MotionModel motionModel() const { return motionModel_; } + + virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) = 0; + +protected: + ImageMotionEstimatorBase(MotionModel model) { setMotionModel(model); } + +private: + MotionModel motionModel_; +}; + +class CV_EXPORTS FromFileMotionReader : public ImageMotionEstimatorBase +{ +public: + FromFileMotionReader(const String &path); + + virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) CV_OVERRIDE; + +private: + std::ifstream file_; +}; + +class CV_EXPORTS ToFileMotionWriter : public ImageMotionEstimatorBase +{ +public: + ToFileMotionWriter(const String &path, Ptr estimator); + + virtual void setMotionModel(MotionModel val) CV_OVERRIDE { motionEstimator_->setMotionModel(val); } + virtual MotionModel motionModel() const CV_OVERRIDE { return motionEstimator_->motionModel(); } + + virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) CV_OVERRIDE; + +private: + std::ofstream file_; + Ptr motionEstimator_; +}; + +/** @brief Describes a global 2D motion estimation method which uses keypoints detection and optical flow for +matching. + */ +class CV_EXPORTS KeypointBasedMotionEstimator : public ImageMotionEstimatorBase +{ +public: + KeypointBasedMotionEstimator(Ptr estimator); + + virtual void setMotionModel(MotionModel val) CV_OVERRIDE { motionEstimator_->setMotionModel(val); } + virtual MotionModel motionModel() const CV_OVERRIDE { return motionEstimator_->motionModel(); } + + void setDetector(Ptr val) { detector_ = val; } + Ptr detector() const { return detector_; } + + void setOpticalFlowEstimator(Ptr val) { optFlowEstimator_ = val; } + Ptr opticalFlowEstimator() const { return optFlowEstimator_; } + + void setOutlierRejector(Ptr val) { outlierRejector_ = val; } + Ptr outlierRejector() const { return outlierRejector_; } + + virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) CV_OVERRIDE; + Mat estimate(InputArray frame0, InputArray frame1, bool *ok = 0); + +private: + Ptr motionEstimator_; + Ptr detector_; + Ptr optFlowEstimator_; + Ptr outlierRejector_; + + std::vector status_; + std::vector keypointsPrev_; + std::vector pointsPrev_, points_; + std::vector pointsPrevGood_, pointsGood_; +}; + +#if defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDAOPTFLOW) + +class CV_EXPORTS KeypointBasedMotionEstimatorGpu : public ImageMotionEstimatorBase +{ +public: + KeypointBasedMotionEstimatorGpu(Ptr estimator); + + virtual void setMotionModel(MotionModel val) CV_OVERRIDE { motionEstimator_->setMotionModel(val); } + virtual MotionModel motionModel() const CV_OVERRIDE { return motionEstimator_->motionModel(); } + + void setOutlierRejector(Ptr val) { outlierRejector_ = val; } + Ptr outlierRejector() const { return outlierRejector_; } + + virtual Mat estimate(const Mat &frame0, const Mat &frame1, bool *ok = 0) CV_OVERRIDE; + Mat estimate(const cuda::GpuMat &frame0, const cuda::GpuMat &frame1, bool *ok = 0); + +private: + Ptr motionEstimator_; + Ptr detector_; + SparsePyrLkOptFlowEstimatorGpu optFlowEstimator_; + Ptr outlierRejector_; + + cuda::GpuMat frame0_, grayFrame0_, frame1_; + cuda::GpuMat pointsPrev_, points_; + cuda::GpuMat status_; + + Mat hostPointsPrev_, hostPoints_; + std::vector hostPointsPrevTmp_, hostPointsTmp_; + std::vector rejectionStatus_; +}; + +#endif // defined(HAVE_OPENCV_CUDAIMGPROC) && defined(HAVE_OPENCV_CUDAOPTFLOW) + +/** @brief Computes motion between two frames assuming that all the intermediate motions are known. + +@param from Source frame index. +@param to Destination frame index. +@param motions Pair-wise motions. motions[i] denotes motion from the frame i to the frame i+1 +@return Motion from the Source frame to the Destination frame. + */ +CV_EXPORTS Mat getMotion(int from, int to, const std::vector &motions); + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/inpainting.hpp b/3rdparty/opencv/include/opencv2/videostab/inpainting.hpp new file mode 100644 index 00000000..9c123f02 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/inpainting.hpp @@ -0,0 +1,212 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_INPAINTINT_HPP +#define OPENCV_VIDEOSTAB_INPAINTINT_HPP + +#include +#include "opencv2/core.hpp" +#include "opencv2/videostab/optical_flow.hpp" +#include "opencv2/videostab/fast_marching.hpp" +#include "opencv2/videostab/global_motion.hpp" +#include "opencv2/photo.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS InpainterBase +{ +public: + InpainterBase() + : radius_(0), motionModel_(MM_UNKNOWN), frames_(0), motions_(0), + stabilizedFrames_(0), stabilizationMotions_(0) {} + + virtual ~InpainterBase() {} + + virtual void setRadius(int val) { radius_ = val; } + virtual int radius() const { return radius_; } + + virtual void setMotionModel(MotionModel val) { motionModel_ = val; } + virtual MotionModel motionModel() const { return motionModel_; } + + virtual void inpaint(int idx, Mat &frame, Mat &mask) = 0; + + + // data from stabilizer + + virtual void setFrames(const std::vector &val) { frames_ = &val; } + virtual const std::vector& frames() const { return *frames_; } + + virtual void setMotions(const std::vector &val) { motions_ = &val; } + virtual const std::vector& motions() const { return *motions_; } + + virtual void setStabilizedFrames(const std::vector &val) { stabilizedFrames_ = &val; } + virtual const std::vector& stabilizedFrames() const { return *stabilizedFrames_; } + + virtual void setStabilizationMotions(const std::vector &val) { stabilizationMotions_ = &val; } + virtual const std::vector& stabilizationMotions() const { return *stabilizationMotions_; } + +protected: + int radius_; + MotionModel motionModel_; + const std::vector *frames_; + const std::vector *motions_; + const std::vector *stabilizedFrames_; + const std::vector *stabilizationMotions_; +}; + +class CV_EXPORTS NullInpainter : public InpainterBase +{ +public: + virtual void inpaint(int /*idx*/, Mat &/*frame*/, Mat &/*mask*/) CV_OVERRIDE {} +}; + +class CV_EXPORTS InpaintingPipeline : public InpainterBase +{ +public: + void pushBack(Ptr inpainter) { inpainters_.push_back(inpainter); } + bool empty() const { return inpainters_.empty(); } + + virtual void setRadius(int val) CV_OVERRIDE; + virtual void setMotionModel(MotionModel val) CV_OVERRIDE; + virtual void setFrames(const std::vector &val) CV_OVERRIDE; + virtual void setMotions(const std::vector &val) CV_OVERRIDE; + virtual void setStabilizedFrames(const std::vector &val) CV_OVERRIDE; + virtual void setStabilizationMotions(const std::vector &val) CV_OVERRIDE; + + virtual void inpaint(int idx, Mat &frame, Mat &mask) CV_OVERRIDE; + +private: + std::vector > inpainters_; +}; + +class CV_EXPORTS ConsistentMosaicInpainter : public InpainterBase +{ +public: + ConsistentMosaicInpainter(); + + void setStdevThresh(float val) { stdevThresh_ = val; } + float stdevThresh() const { return stdevThresh_; } + + virtual void inpaint(int idx, Mat &frame, Mat &mask) CV_OVERRIDE; + +private: + float stdevThresh_; +}; + +class CV_EXPORTS MotionInpainter : public InpainterBase +{ +public: + MotionInpainter(); + + void setOptFlowEstimator(Ptr val) { optFlowEstimator_ = val; } + Ptr optFlowEstimator() const { return optFlowEstimator_; } + + void setFlowErrorThreshold(float val) { flowErrorThreshold_ = val; } + float flowErrorThreshold() const { return flowErrorThreshold_; } + + void setDistThreshold(float val) { distThresh_ = val; } + float distThresh() const { return distThresh_; } + + void setBorderMode(int val) { borderMode_ = val; } + int borderMode() const { return borderMode_; } + + virtual void inpaint(int idx, Mat &frame, Mat &mask) CV_OVERRIDE; + +private: + FastMarchingMethod fmm_; + Ptr optFlowEstimator_; + float flowErrorThreshold_; + float distThresh_; + int borderMode_; + + Mat frame1_, transformedFrame1_; + Mat_ grayFrame_, transformedGrayFrame1_; + Mat_ mask1_, transformedMask1_; + Mat_ flowX_, flowY_, flowErrors_; + Mat_ flowMask_; +}; + +class CV_EXPORTS ColorAverageInpainter : public InpainterBase +{ +public: + virtual void inpaint(int idx, Mat &frame, Mat &mask) CV_OVERRIDE; + +private: + FastMarchingMethod fmm_; +}; + +class CV_EXPORTS ColorInpainter : public InpainterBase +{ +public: + ColorInpainter(int method = INPAINT_TELEA, double radius = 2.); + + virtual void inpaint(int idx, Mat &frame, Mat &mask) CV_OVERRIDE; + +private: + int method_; + double radius_; + Mat invMask_; +}; + +inline ColorInpainter::ColorInpainter(int _method, double _radius) + : method_(_method), radius_(_radius) {} + +CV_EXPORTS void calcFlowMask( + const Mat &flowX, const Mat &flowY, const Mat &errors, float maxError, + const Mat &mask0, const Mat &mask1, Mat &flowMask); + +CV_EXPORTS void completeFrameAccordingToFlow( + const Mat &flowMask, const Mat &flowX, const Mat &flowY, const Mat &frame1, const Mat &mask1, + float distThresh, Mat& frame0, Mat &mask0); + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/log.hpp b/3rdparty/opencv/include/opencv2/videostab/log.hpp new file mode 100644 index 00000000..73e70499 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/log.hpp @@ -0,0 +1,80 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_LOG_HPP +#define OPENCV_VIDEOSTAB_LOG_HPP + +#include "opencv2/core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS ILog +{ +public: + virtual ~ILog() {} + virtual void print(const char *format, ...) = 0; +}; + +class CV_EXPORTS NullLog : public ILog +{ +public: + virtual void print(const char * /*format*/, ...) CV_OVERRIDE {} +}; + +class CV_EXPORTS LogToStdout : public ILog +{ +public: + virtual void print(const char *format, ...) CV_OVERRIDE; +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/motion_core.hpp b/3rdparty/opencv/include/opencv2/videostab/motion_core.hpp new file mode 100644 index 00000000..4525cc7b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/motion_core.hpp @@ -0,0 +1,129 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_MOTION_CORE_HPP +#define OPENCV_VIDEOSTAB_MOTION_CORE_HPP + +#include +#include "opencv2/core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab_motion +//! @{ + +/** @brief Describes motion model between two point clouds. + */ +enum MotionModel +{ + MM_TRANSLATION = 0, + MM_TRANSLATION_AND_SCALE = 1, + MM_ROTATION = 2, + MM_RIGID = 3, + MM_SIMILARITY = 4, + MM_AFFINE = 5, + MM_HOMOGRAPHY = 6, + MM_UNKNOWN = 7 +}; + +/** @brief Describes RANSAC method parameters. + */ +struct CV_EXPORTS RansacParams +{ + int size; //!< subset size + float thresh; //!< max error to classify as inlier + float eps; //!< max outliers ratio + float prob; //!< probability of success + + RansacParams() : size(0), thresh(0), eps(0), prob(0) {} + /** @brief Constructor + @param size Subset size. + @param thresh Maximum re-projection error value to classify as inlier. + @param eps Maximum ratio of incorrect correspondences. + @param prob Required success probability. + */ + RansacParams(int size, float thresh, float eps, float prob); + + /** + @return Number of iterations that'll be performed by RANSAC method. + */ + int niters() const + { + return static_cast( + std::ceil(std::log(1 - prob) / std::log(1 - std::pow(1 - eps, size)))); + } + + /** + @param model Motion model. See cv::videostab::MotionModel. + @return Default RANSAC method parameters for the given motion model. + */ + static RansacParams default2dMotion(MotionModel model) + { + CV_Assert(model < MM_UNKNOWN); + if (model == MM_TRANSLATION) + return RansacParams(1, 0.5f, 0.5f, 0.99f); + if (model == MM_TRANSLATION_AND_SCALE) + return RansacParams(2, 0.5f, 0.5f, 0.99f); + if (model == MM_ROTATION) + return RansacParams(1, 0.5f, 0.5f, 0.99f); + if (model == MM_RIGID) + return RansacParams(2, 0.5f, 0.5f, 0.99f); + if (model == MM_SIMILARITY) + return RansacParams(2, 0.5f, 0.5f, 0.99f); + if (model == MM_AFFINE) + return RansacParams(3, 0.5f, 0.5f, 0.99f); + return RansacParams(4, 0.5f, 0.5f, 0.99f); + } +}; + +inline RansacParams::RansacParams(int _size, float _thresh, float _eps, float _prob) + : size(_size), thresh(_thresh), eps(_eps), prob(_prob) {} + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/motion_stabilizing.hpp b/3rdparty/opencv/include/opencv2/videostab/motion_stabilizing.hpp new file mode 100644 index 00000000..c50095bb --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/motion_stabilizing.hpp @@ -0,0 +1,174 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_MOTION_STABILIZING_HPP +#define OPENCV_VIDEOSTAB_MOTION_STABILIZING_HPP + +#include +#include +#include "opencv2/core.hpp" +#include "opencv2/videostab/global_motion.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab_motion +//! @{ + +class CV_EXPORTS IMotionStabilizer +{ +public: + virtual ~IMotionStabilizer() {} + + //! assumes that [0, size-1) is in or equals to [range.first, range.second) + virtual void stabilize( + int size, const std::vector &motions, std::pair range, + Mat *stabilizationMotions) = 0; +}; + +class CV_EXPORTS MotionStabilizationPipeline : public IMotionStabilizer +{ +public: + void pushBack(Ptr stabilizer) { stabilizers_.push_back(stabilizer); } + bool empty() const { return stabilizers_.empty(); } + + virtual void stabilize( + int size, const std::vector &motions, std::pair range, + Mat *stabilizationMotions) CV_OVERRIDE; + +private: + std::vector > stabilizers_; +}; + +class CV_EXPORTS MotionFilterBase : public IMotionStabilizer +{ +public: + virtual ~MotionFilterBase() {} + + virtual Mat stabilize( + int idx, const std::vector &motions, std::pair range) = 0; + + virtual void stabilize( + int size, const std::vector &motions, std::pair range, + Mat *stabilizationMotions) CV_OVERRIDE; +}; + +class CV_EXPORTS GaussianMotionFilter : public MotionFilterBase +{ +public: + GaussianMotionFilter(int radius = 15, float stdev = -1.f); + + void setParams(int radius, float stdev = -1.f); + int radius() const { return radius_; } + float stdev() const { return stdev_; } + + virtual Mat stabilize( + int idx, const std::vector &motions, std::pair range) CV_OVERRIDE; + +private: + int radius_; + float stdev_; + std::vector weight_; +}; + +inline GaussianMotionFilter::GaussianMotionFilter(int _radius, float _stdev) { setParams(_radius, _stdev); } + +class CV_EXPORTS LpMotionStabilizer : public IMotionStabilizer +{ +public: + LpMotionStabilizer(MotionModel model = MM_SIMILARITY); + + void setMotionModel(MotionModel val) { model_ = val; } + MotionModel motionModel() const { return model_; } + + void setFrameSize(Size val) { frameSize_ = val; } + Size frameSize() const { return frameSize_; } + + void setTrimRatio(float val) { trimRatio_ = val; } + float trimRatio() const { return trimRatio_; } + + void setWeight1(float val) { w1_ = val; } + float weight1() const { return w1_; } + + void setWeight2(float val) { w2_ = val; } + float weight2() const { return w2_; } + + void setWeight3(float val) { w3_ = val; } + float weight3() const { return w3_; } + + void setWeight4(float val) { w4_ = val; } + float weight4() const { return w4_; } + + virtual void stabilize( + int size, const std::vector &motions, std::pair range, + Mat *stabilizationMotions) CV_OVERRIDE; + +private: + MotionModel model_; + Size frameSize_; + float trimRatio_; + float w1_, w2_, w3_, w4_; + + std::vector obj_, collb_, colub_; + std::vector rows_, cols_; + std::vector elems_, rowlb_, rowub_; + + void set(int row, int col, double coef) + { + rows_.push_back(row); + cols_.push_back(col); + elems_.push_back(coef); + } +}; + +CV_EXPORTS Mat ensureInclusionConstraint(const Mat &M, Size size, float trimRatio); + +CV_EXPORTS float estimateOptimalTrimRatio(const Mat &M, Size size); + +//! @} + +} // namespace videostab +} // namespace + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/optical_flow.hpp b/3rdparty/opencv/include/opencv2/videostab/optical_flow.hpp new file mode 100644 index 00000000..5e06941d --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/optical_flow.hpp @@ -0,0 +1,150 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_OPTICAL_FLOW_HPP +#define OPENCV_VIDEOSTAB_OPTICAL_FLOW_HPP + +#include "opencv2/core.hpp" +#include "opencv2/opencv_modules.hpp" + +#ifdef HAVE_OPENCV_CUDAOPTFLOW + #include "opencv2/cudaoptflow.hpp" +#endif + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS ISparseOptFlowEstimator +{ +public: + virtual ~ISparseOptFlowEstimator() {} + virtual void run( + InputArray frame0, InputArray frame1, InputArray points0, InputOutputArray points1, + OutputArray status, OutputArray errors) = 0; +}; + +class CV_EXPORTS IDenseOptFlowEstimator +{ +public: + virtual ~IDenseOptFlowEstimator() {} + virtual void run( + InputArray frame0, InputArray frame1, InputOutputArray flowX, InputOutputArray flowY, + OutputArray errors) = 0; +}; + +class CV_EXPORTS PyrLkOptFlowEstimatorBase +{ +public: + PyrLkOptFlowEstimatorBase() { setWinSize(Size(21, 21)); setMaxLevel(3); } + + virtual void setWinSize(Size val) { winSize_ = val; } + virtual Size winSize() const { return winSize_; } + + virtual void setMaxLevel(int val) { maxLevel_ = val; } + virtual int maxLevel() const { return maxLevel_; } + virtual ~PyrLkOptFlowEstimatorBase() {} + +protected: + Size winSize_; + int maxLevel_; +}; + +class CV_EXPORTS SparsePyrLkOptFlowEstimator + : public PyrLkOptFlowEstimatorBase, public ISparseOptFlowEstimator +{ +public: + virtual void run( + InputArray frame0, InputArray frame1, InputArray points0, InputOutputArray points1, + OutputArray status, OutputArray errors) CV_OVERRIDE; +}; + +#ifdef HAVE_OPENCV_CUDAOPTFLOW + +class CV_EXPORTS SparsePyrLkOptFlowEstimatorGpu + : public PyrLkOptFlowEstimatorBase, public ISparseOptFlowEstimator +{ +public: + SparsePyrLkOptFlowEstimatorGpu(); + + virtual void run( + InputArray frame0, InputArray frame1, InputArray points0, InputOutputArray points1, + OutputArray status, OutputArray errors) CV_OVERRIDE; + + void run(const cuda::GpuMat &frame0, const cuda::GpuMat &frame1, const cuda::GpuMat &points0, cuda::GpuMat &points1, + cuda::GpuMat &status, cuda::GpuMat &errors); + + void run(const cuda::GpuMat &frame0, const cuda::GpuMat &frame1, const cuda::GpuMat &points0, cuda::GpuMat &points1, + cuda::GpuMat &status); + +private: + Ptr optFlowEstimator_; + cuda::GpuMat frame0_, frame1_, points0_, points1_, status_, errors_; +}; + +class CV_EXPORTS DensePyrLkOptFlowEstimatorGpu + : public PyrLkOptFlowEstimatorBase, public IDenseOptFlowEstimator +{ +public: + DensePyrLkOptFlowEstimatorGpu(); + + virtual void run( + InputArray frame0, InputArray frame1, InputOutputArray flowX, InputOutputArray flowY, + OutputArray errors) CV_OVERRIDE; + +private: + Ptr optFlowEstimator_; + cuda::GpuMat frame0_, frame1_, flowX_, flowY_, errors_; +}; + +#endif + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/outlier_rejection.hpp b/3rdparty/opencv/include/opencv2/videostab/outlier_rejection.hpp new file mode 100644 index 00000000..1d29896b --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/outlier_rejection.hpp @@ -0,0 +1,101 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_OUTLIER_REJECTION_HPP +#define OPENCV_VIDEOSTAB_OUTLIER_REJECTION_HPP + +#include +#include "opencv2/core.hpp" +#include "opencv2/videostab/motion_core.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS IOutlierRejector +{ +public: + virtual ~IOutlierRejector() {} + + virtual void process( + Size frameSize, InputArray points0, InputArray points1, OutputArray mask) = 0; +}; + +class CV_EXPORTS NullOutlierRejector : public IOutlierRejector +{ +public: + virtual void process( + Size frameSize, InputArray points0, InputArray points1, OutputArray mask) CV_OVERRIDE; +}; + +class CV_EXPORTS TranslationBasedLocalOutlierRejector : public IOutlierRejector +{ +public: + TranslationBasedLocalOutlierRejector(); + + void setCellSize(Size val) { cellSize_ = val; } + Size cellSize() const { return cellSize_; } + + void setRansacParams(RansacParams val) { ransacParams_ = val; } + RansacParams ransacParams() const { return ransacParams_; } + + virtual void process( + Size frameSize, InputArray points0, InputArray points1, OutputArray mask) CV_OVERRIDE; + +private: + Size cellSize_; + RansacParams ransacParams_; + + typedef std::vector Cell; + std::vector grid_; +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/ring_buffer.hpp b/3rdparty/opencv/include/opencv2/videostab/ring_buffer.hpp new file mode 100644 index 00000000..55d52444 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/ring_buffer.hpp @@ -0,0 +1,72 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_RING_BUFFER_HPP +#define OPENCV_VIDEOSTAB_RING_BUFFER_HPP + +#include +#include "opencv2/imgproc.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +template inline T& at(int idx, std::vector &items) +{ + return items[cv::borderInterpolate(idx, static_cast(items.size()), cv::BORDER_WRAP)]; +} + +template inline const T& at(int idx, const std::vector &items) +{ + return items[cv::borderInterpolate(idx, static_cast(items.size()), cv::BORDER_WRAP)]; +} + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/stabilizer.hpp b/3rdparty/opencv/include/opencv2/videostab/stabilizer.hpp new file mode 100644 index 00000000..634a0aa9 --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/stabilizer.hpp @@ -0,0 +1,200 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_STABILIZER_HPP +#define OPENCV_VIDEOSTAB_STABILIZER_HPP + +#include +#include +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" +#include "opencv2/videostab/global_motion.hpp" +#include "opencv2/videostab/motion_stabilizing.hpp" +#include "opencv2/videostab/frame_source.hpp" +#include "opencv2/videostab/log.hpp" +#include "opencv2/videostab/inpainting.hpp" +#include "opencv2/videostab/deblurring.hpp" +#include "opencv2/videostab/wobble_suppression.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS StabilizerBase +{ +public: + virtual ~StabilizerBase() {} + + void setLog(Ptr ilog) { log_ = ilog; } + Ptr log() const { return log_; } + + void setRadius(int val) { radius_ = val; } + int radius() const { return radius_; } + + void setFrameSource(Ptr val) { frameSource_ = val; } + Ptr frameSource() const { return frameSource_; } + + void setMotionEstimator(Ptr val) { motionEstimator_ = val; } + Ptr motionEstimator() const { return motionEstimator_; } + + void setDeblurer(Ptr val) { deblurer_ = val; } + Ptr deblurrer() const { return deblurer_; } + + void setTrimRatio(float val) { trimRatio_ = val; } + float trimRatio() const { return trimRatio_; } + + void setCorrectionForInclusion(bool val) { doCorrectionForInclusion_ = val; } + bool doCorrectionForInclusion() const { return doCorrectionForInclusion_; } + + void setBorderMode(int val) { borderMode_ = val; } + int borderMode() const { return borderMode_; } + + void setInpainter(Ptr val) { inpainter_ = val; } + Ptr inpainter() const { return inpainter_; } + +protected: + StabilizerBase(); + + void reset(); + Mat nextStabilizedFrame(); + bool doOneIteration(); + virtual void setUp(const Mat &firstFrame); + virtual Mat estimateMotion() = 0; + virtual Mat estimateStabilizationMotion() = 0; + void stabilizeFrame(); + virtual Mat postProcessFrame(const Mat &frame); + void logProcessingTime(); + + Ptr log_; + Ptr frameSource_; + Ptr motionEstimator_; + Ptr deblurer_; + Ptr inpainter_; + int radius_; + float trimRatio_; + bool doCorrectionForInclusion_; + int borderMode_; + + Size frameSize_; + Mat frameMask_; + int curPos_; + int curStabilizedPos_; + bool doDeblurring_; + Mat preProcessedFrame_; + bool doInpainting_; + Mat inpaintingMask_; + Mat finalFrame_; + std::vector frames_; + std::vector motions_; // motions_[i] is the motion from i-th to i+1-th frame + std::vector blurrinessRates_; + std::vector stabilizedFrames_; + std::vector stabilizedMasks_; + std::vector stabilizationMotions_; + clock_t processingStartTime_; +}; + +class CV_EXPORTS OnePassStabilizer : public StabilizerBase, public IFrameSource +{ +public: + OnePassStabilizer(); + + void setMotionFilter(Ptr val) { motionFilter_ = val; } + Ptr motionFilter() const { return motionFilter_; } + + virtual void reset() CV_OVERRIDE; + virtual Mat nextFrame() CV_OVERRIDE { return nextStabilizedFrame(); } + +protected: + virtual void setUp(const Mat &firstFrame) CV_OVERRIDE; + virtual Mat estimateMotion() CV_OVERRIDE; + virtual Mat estimateStabilizationMotion() CV_OVERRIDE; + virtual Mat postProcessFrame(const Mat &frame) CV_OVERRIDE; + + Ptr motionFilter_; +}; + +class CV_EXPORTS TwoPassStabilizer : public StabilizerBase, public IFrameSource +{ +public: + TwoPassStabilizer(); + + void setMotionStabilizer(Ptr val) { motionStabilizer_ = val; } + Ptr motionStabilizer() const { return motionStabilizer_; } + + void setWobbleSuppressor(Ptr val) { wobbleSuppressor_ = val; } + Ptr wobbleSuppressor() const { return wobbleSuppressor_; } + + void setEstimateTrimRatio(bool val) { mustEstTrimRatio_ = val; } + bool mustEstimateTrimaRatio() const { return mustEstTrimRatio_; } + + virtual void reset() CV_OVERRIDE; + virtual Mat nextFrame() CV_OVERRIDE; + +protected: + void runPrePassIfNecessary(); + + virtual void setUp(const Mat &firstFrame) CV_OVERRIDE; + virtual Mat estimateMotion() CV_OVERRIDE; + virtual Mat estimateStabilizationMotion() CV_OVERRIDE; + virtual Mat postProcessFrame(const Mat &frame) CV_OVERRIDE; + + Ptr motionStabilizer_; + Ptr wobbleSuppressor_; + bool mustEstTrimRatio_; + + int frameCount_; + bool isPrePassDone_; + bool doWobbleSuppression_; + std::vector motions2_; + Mat suppressedFrame_; +}; + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/include/opencv2/videostab/wobble_suppression.hpp b/3rdparty/opencv/include/opencv2/videostab/wobble_suppression.hpp new file mode 100644 index 00000000..d60ae6dd --- /dev/null +++ b/3rdparty/opencv/include/opencv2/videostab/wobble_suppression.hpp @@ -0,0 +1,140 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef OPENCV_VIDEOSTAB_WOBBLE_SUPPRESSION_HPP +#define OPENCV_VIDEOSTAB_WOBBLE_SUPPRESSION_HPP + +#include +#include "opencv2/core.hpp" +#include "opencv2/core/cuda.hpp" +#include "opencv2/videostab/global_motion.hpp" +#include "opencv2/videostab/log.hpp" + +namespace cv +{ +namespace videostab +{ + +//! @addtogroup videostab +//! @{ + +class CV_EXPORTS WobbleSuppressorBase +{ +public: + WobbleSuppressorBase(); + + virtual ~WobbleSuppressorBase() {} + + void setMotionEstimator(Ptr val) { motionEstimator_ = val; } + Ptr motionEstimator() const { return motionEstimator_; } + + virtual void suppress(int idx, const Mat &frame, Mat &result) = 0; + + + // data from stabilizer + + virtual void setFrameCount(int val) { frameCount_ = val; } + virtual int frameCount() const { return frameCount_; } + + virtual void setMotions(const std::vector &val) { motions_ = &val; } + virtual const std::vector& motions() const { return *motions_; } + + virtual void setMotions2(const std::vector &val) { motions2_ = &val; } + virtual const std::vector& motions2() const { return *motions2_; } + + virtual void setStabilizationMotions(const std::vector &val) { stabilizationMotions_ = &val; } + virtual const std::vector& stabilizationMotions() const { return *stabilizationMotions_; } + +protected: + Ptr motionEstimator_; + int frameCount_; + const std::vector *motions_; + const std::vector *motions2_; + const std::vector *stabilizationMotions_; +}; + +class CV_EXPORTS NullWobbleSuppressor : public WobbleSuppressorBase +{ +public: + virtual void suppress(int idx, const Mat &frame, Mat &result) CV_OVERRIDE; +}; + +class CV_EXPORTS MoreAccurateMotionWobbleSuppressorBase : public WobbleSuppressorBase +{ +public: + virtual void setPeriod(int val) { period_ = val; } + virtual int period() const { return period_; } + +protected: + MoreAccurateMotionWobbleSuppressorBase() { setPeriod(30); } + + int period_; +}; + +class CV_EXPORTS MoreAccurateMotionWobbleSuppressor : public MoreAccurateMotionWobbleSuppressorBase +{ +public: + virtual void suppress(int idx, const Mat &frame, Mat &result) CV_OVERRIDE; + +private: + Mat_ mapx_, mapy_; +}; + +#if defined(HAVE_OPENCV_CUDAWARPING) +class CV_EXPORTS MoreAccurateMotionWobbleSuppressorGpu : public MoreAccurateMotionWobbleSuppressorBase +{ +public: + void suppress(int idx, const cuda::GpuMat &frame, cuda::GpuMat &result); + virtual void suppress(int idx, const Mat &frame, Mat &result) CV_OVERRIDE; + +private: + cuda::GpuMat frameDevice_, resultDevice_; + cuda::GpuMat mapx_, mapy_; +}; +#endif + +//! @} + +} // namespace videostab +} // namespace cv + +#endif diff --git a/3rdparty/opencv/x64/bin/opencv_world346.dll b/3rdparty/opencv/x64/bin/opencv_world346.dll new file mode 100644 index 00000000..140a8926 Binary files /dev/null and b/3rdparty/opencv/x64/bin/opencv_world346.dll differ diff --git a/3rdparty/opencv/x64/bin/opencv_world346d.dll b/3rdparty/opencv/x64/bin/opencv_world346d.dll new file mode 100644 index 00000000..8b0ad74a Binary files /dev/null and b/3rdparty/opencv/x64/bin/opencv_world346d.dll differ diff --git a/3rdparty/opencv/x64/lib/opencv_world346.lib b/3rdparty/opencv/x64/lib/opencv_world346.lib new file mode 100644 index 00000000..6457e944 Binary files /dev/null and b/3rdparty/opencv/x64/lib/opencv_world346.lib differ diff --git a/3rdparty/opencv/x64/lib/opencv_world346d.lib b/3rdparty/opencv/x64/lib/opencv_world346d.lib new file mode 100644 index 00000000..9eb4deaa Binary files /dev/null and b/3rdparty/opencv/x64/lib/opencv_world346d.lib differ diff --git a/3rdparty/opencv/x86/bin/opencv_world346.dll b/3rdparty/opencv/x86/bin/opencv_world346.dll new file mode 100644 index 00000000..2b0a2c6c Binary files /dev/null and b/3rdparty/opencv/x86/bin/opencv_world346.dll differ diff --git a/3rdparty/opencv/x86/bin/opencv_world346d.dll b/3rdparty/opencv/x86/bin/opencv_world346d.dll new file mode 100644 index 00000000..a6d6fe5f Binary files /dev/null and b/3rdparty/opencv/x86/bin/opencv_world346d.dll differ diff --git a/3rdparty/opencv/x86/lib/opencv_world346.lib b/3rdparty/opencv/x86/lib/opencv_world346.lib new file mode 100644 index 00000000..fe644040 Binary files /dev/null and b/3rdparty/opencv/x86/lib/opencv_world346.lib differ diff --git a/3rdparty/opencv/x86/lib/opencv_world346d.lib b/3rdparty/opencv/x86/lib/opencv_world346d.lib new file mode 100644 index 00000000..c6828e4c Binary files /dev/null and b/3rdparty/opencv/x86/lib/opencv_world346d.lib differ diff --git a/3rdparty/turbojpeg/include/turbojpeg.h b/3rdparty/turbojpeg/include/turbojpeg.h new file mode 100644 index 00000000..9c0a3713 --- /dev/null +++ b/3rdparty/turbojpeg/include/turbojpeg.h @@ -0,0 +1,1744 @@ +/* + * Copyright (C)2009-2015, 2017 D. R. Commander. All Rights Reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions are met: + * + * - Redistributions of source code must retain the above copyright notice, + * this list of conditions and the following disclaimer. + * - Redistributions in binary form must reproduce the above copyright notice, + * this list of conditions and the following disclaimer in the documentation + * and/or other materials provided with the distribution. + * - Neither the name of the libjpeg-turbo Project nor the names of its + * contributors may be used to endorse or promote products derived from this + * software without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS", + * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE + * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE + * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS + * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN + * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) + * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + * POSSIBILITY OF SUCH DAMAGE. + */ + +#ifndef __TURBOJPEG_H__ +#define __TURBOJPEG_H__ + +#if defined(_WIN32) && defined(DLLDEFINE) +#define DLLEXPORT __declspec(dllexport) +#else +#define DLLEXPORT +#endif +#define DLLCALL + + +/** + * @addtogroup TurboJPEG + * TurboJPEG API. This API provides an interface for generating, decoding, and + * transforming planar YUV and JPEG images in memory. + * + * @anchor YUVnotes + * YUV Image Format Notes + * ---------------------- + * Technically, the JPEG format uses the YCbCr colorspace (which is technically + * not a colorspace but a color transform), but per the convention of the + * digital video community, the TurboJPEG API uses "YUV" to refer to an image + * format consisting of Y, Cb, and Cr image planes. + * + * Each plane is simply a 2D array of bytes, each byte representing the value + * of one of the components (Y, Cb, or Cr) at a particular location in the + * image. The width and height of each plane are determined by the image + * width, height, and level of chrominance subsampling. The luminance plane + * width is the image width padded to the nearest multiple of the horizontal + * subsampling factor (2 in the case of 4:2:0 and 4:2:2, 4 in the case of + * 4:1:1, 1 in the case of 4:4:4 or grayscale.) Similarly, the luminance plane + * height is the image height padded to the nearest multiple of the vertical + * subsampling factor (2 in the case of 4:2:0 or 4:4:0, 1 in the case of 4:4:4 + * or grayscale.) This is irrespective of any additional padding that may be + * specified as an argument to the various YUV functions. The chrominance + * plane width is equal to the luminance plane width divided by the horizontal + * subsampling factor, and the chrominance plane height is equal to the + * luminance plane height divided by the vertical subsampling factor. + * + * For example, if the source image is 35 x 35 pixels and 4:2:2 subsampling is + * used, then the luminance plane would be 36 x 35 bytes, and each of the + * chrominance planes would be 18 x 35 bytes. If you specify a line padding of + * 4 bytes on top of this, then the luminance plane would be 36 x 35 bytes, and + * each of the chrominance planes would be 20 x 35 bytes. + * + * @{ + */ + + +/** + * The number of chrominance subsampling options + */ +#define TJ_NUMSAMP 6 + +/** + * Chrominance subsampling options. + * When pixels are converted from RGB to YCbCr (see #TJCS_YCbCr) or from CMYK + * to YCCK (see #TJCS_YCCK) as part of the JPEG compression process, some of + * the Cb and Cr (chrominance) components can be discarded or averaged together + * to produce a smaller image with little perceptible loss of image clarity + * (the human eye is more sensitive to small changes in brightness than to + * small changes in color.) This is called "chrominance subsampling". + */ +enum TJSAMP { + /** + * 4:4:4 chrominance subsampling (no chrominance subsampling). The JPEG or + * YUV image will contain one chrominance component for every pixel in the + * source image. + */ + TJSAMP_444 = 0, + /** + * 4:2:2 chrominance subsampling. The JPEG or YUV image will contain one + * chrominance component for every 2x1 block of pixels in the source image. + */ + TJSAMP_422, + /** + * 4:2:0 chrominance subsampling. The JPEG or YUV image will contain one + * chrominance component for every 2x2 block of pixels in the source image. + */ + TJSAMP_420, + /** + * Grayscale. The JPEG or YUV image will contain no chrominance components. + */ + TJSAMP_GRAY, + /** + * 4:4:0 chrominance subsampling. The JPEG or YUV image will contain one + * chrominance component for every 1x2 block of pixels in the source image. + * + * @note 4:4:0 subsampling is not fully accelerated in libjpeg-turbo. + */ + TJSAMP_440, + /** + * 4:1:1 chrominance subsampling. The JPEG or YUV image will contain one + * chrominance component for every 4x1 block of pixels in the source image. + * JPEG images compressed with 4:1:1 subsampling will be almost exactly the + * same size as those compressed with 4:2:0 subsampling, and in the + * aggregate, both subsampling methods produce approximately the same + * perceptual quality. However, 4:1:1 is better able to reproduce sharp + * horizontal features. + * + * @note 4:1:1 subsampling is not fully accelerated in libjpeg-turbo. + */ + TJSAMP_411 +}; + +/** + * MCU block width (in pixels) for a given level of chrominance subsampling. + * MCU block sizes: + * - 8x8 for no subsampling or grayscale + * - 16x8 for 4:2:2 + * - 8x16 for 4:4:0 + * - 16x16 for 4:2:0 + * - 32x8 for 4:1:1 + */ +static const int tjMCUWidth[TJ_NUMSAMP] = { 8, 16, 16, 8, 8, 32 }; + +/** + * MCU block height (in pixels) for a given level of chrominance subsampling. + * MCU block sizes: + * - 8x8 for no subsampling or grayscale + * - 16x8 for 4:2:2 + * - 8x16 for 4:4:0 + * - 16x16 for 4:2:0 + * - 32x8 for 4:1:1 + */ +static const int tjMCUHeight[TJ_NUMSAMP] = { 8, 8, 16, 8, 16, 8 }; + + +/** + * The number of pixel formats + */ +#define TJ_NUMPF 12 + +/** + * Pixel formats + */ +enum TJPF { + /** + * RGB pixel format. The red, green, and blue components in the image are + * stored in 3-byte pixels in the order R, G, B from lowest to highest byte + * address within each pixel. + */ + TJPF_RGB = 0, + /** + * BGR pixel format. The red, green, and blue components in the image are + * stored in 3-byte pixels in the order B, G, R from lowest to highest byte + * address within each pixel. + */ + TJPF_BGR, + /** + * RGBX pixel format. The red, green, and blue components in the image are + * stored in 4-byte pixels in the order R, G, B from lowest to highest byte + * address within each pixel. The X component is ignored when compressing + * and undefined when decompressing. + */ + TJPF_RGBX, + /** + * BGRX pixel format. The red, green, and blue components in the image are + * stored in 4-byte pixels in the order B, G, R from lowest to highest byte + * address within each pixel. The X component is ignored when compressing + * and undefined when decompressing. + */ + TJPF_BGRX, + /** + * XBGR pixel format. The red, green, and blue components in the image are + * stored in 4-byte pixels in the order R, G, B from highest to lowest byte + * address within each pixel. The X component is ignored when compressing + * and undefined when decompressing. + */ + TJPF_XBGR, + /** + * XRGB pixel format. The red, green, and blue components in the image are + * stored in 4-byte pixels in the order B, G, R from highest to lowest byte + * address within each pixel. The X component is ignored when compressing + * and undefined when decompressing. + */ + TJPF_XRGB, + /** + * Grayscale pixel format. Each 1-byte pixel represents a luminance + * (brightness) level from 0 to 255. + */ + TJPF_GRAY, + /** + * RGBA pixel format. This is the same as @ref TJPF_RGBX, except that when + * decompressing, the X component is guaranteed to be 0xFF, which can be + * interpreted as an opaque alpha channel. + */ + TJPF_RGBA, + /** + * BGRA pixel format. This is the same as @ref TJPF_BGRX, except that when + * decompressing, the X component is guaranteed to be 0xFF, which can be + * interpreted as an opaque alpha channel. + */ + TJPF_BGRA, + /** + * ABGR pixel format. This is the same as @ref TJPF_XBGR, except that when + * decompressing, the X component is guaranteed to be 0xFF, which can be + * interpreted as an opaque alpha channel. + */ + TJPF_ABGR, + /** + * ARGB pixel format. This is the same as @ref TJPF_XRGB, except that when + * decompressing, the X component is guaranteed to be 0xFF, which can be + * interpreted as an opaque alpha channel. + */ + TJPF_ARGB, + /** + * CMYK pixel format. Unlike RGB, which is an additive color model used + * primarily for display, CMYK (Cyan/Magenta/Yellow/Key) is a subtractive + * color model used primarily for printing. In the CMYK color model, the + * value of each color component typically corresponds to an amount of cyan, + * magenta, yellow, or black ink that is applied to a white background. In + * order to convert between CMYK and RGB, it is necessary to use a color + * management system (CMS.) A CMS will attempt to map colors within the + * printer's gamut to perceptually similar colors in the display's gamut and + * vice versa, but the mapping is typically not 1:1 or reversible, nor can it + * be defined with a simple formula. Thus, such a conversion is out of scope + * for a codec library. However, the TurboJPEG API allows for compressing + * CMYK pixels into a YCCK JPEG image (see #TJCS_YCCK) and decompressing YCCK + * JPEG images into CMYK pixels. + */ + TJPF_CMYK, + /** + * Unknown pixel format. Currently this is only used by #tjLoadImage(). + */ + TJPF_UNKNOWN = -1 +}; + +/** + * Red offset (in bytes) for a given pixel format. This specifies the number + * of bytes that the red component is offset from the start of the pixel. For + * instance, if a pixel of format TJ_BGRX is stored in char pixel[], + * then the red component will be pixel[tjRedOffset[TJ_BGRX]]. This + * will be -1 if the pixel format does not have a red component. + */ +static const int tjRedOffset[TJ_NUMPF] = { + 0, 2, 0, 2, 3, 1, -1, 0, 2, 3, 1, -1 +}; +/** + * Green offset (in bytes) for a given pixel format. This specifies the number + * of bytes that the green component is offset from the start of the pixel. + * For instance, if a pixel of format TJ_BGRX is stored in + * char pixel[], then the green component will be + * pixel[tjGreenOffset[TJ_BGRX]]. This will be -1 if the pixel format + * does not have a green component. + */ +static const int tjGreenOffset[TJ_NUMPF] = { + 1, 1, 1, 1, 2, 2, -1, 1, 1, 2, 2, -1 +}; +/** + * Blue offset (in bytes) for a given pixel format. This specifies the number + * of bytes that the Blue component is offset from the start of the pixel. For + * instance, if a pixel of format TJ_BGRX is stored in char pixel[], + * then the blue component will be pixel[tjBlueOffset[TJ_BGRX]]. This + * will be -1 if the pixel format does not have a blue component. + */ +static const int tjBlueOffset[TJ_NUMPF] = { + 2, 0, 2, 0, 1, 3, -1, 2, 0, 1, 3, -1 +}; +/** + * Alpha offset (in bytes) for a given pixel format. This specifies the number + * of bytes that the Alpha component is offset from the start of the pixel. + * For instance, if a pixel of format TJ_BGRA is stored in + * char pixel[], then the alpha component will be + * pixel[tjAlphaOffset[TJ_BGRA]]. This will be -1 if the pixel format + * does not have an alpha component. + */ +static const int tjAlphaOffset[TJ_NUMPF] = { + -1, -1, -1, -1, -1, -1, -1, 3, 3, 0, 0, -1 +}; +/** + * Pixel size (in bytes) for a given pixel format + */ +static const int tjPixelSize[TJ_NUMPF] = { + 3, 3, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4 +}; + + +/** + * The number of JPEG colorspaces + */ +#define TJ_NUMCS 5 + +/** + * JPEG colorspaces + */ +enum TJCS { + /** + * RGB colorspace. When compressing the JPEG image, the R, G, and B + * components in the source image are reordered into image planes, but no + * colorspace conversion or subsampling is performed. RGB JPEG images can be + * decompressed to any of the extended RGB pixel formats or grayscale, but + * they cannot be decompressed to YUV images. + */ + TJCS_RGB = 0, + /** + * YCbCr colorspace. YCbCr is not an absolute colorspace but rather a + * mathematical transformation of RGB designed solely for storage and + * transmission. YCbCr images must be converted to RGB before they can + * actually be displayed. In the YCbCr colorspace, the Y (luminance) + * component represents the black & white portion of the original image, and + * the Cb and Cr (chrominance) components represent the color portion of the + * original image. Originally, the analog equivalent of this transformation + * allowed the same signal to drive both black & white and color televisions, + * but JPEG images use YCbCr primarily because it allows the color data to be + * optionally subsampled for the purposes of reducing bandwidth or disk + * space. YCbCr is the most common JPEG colorspace, and YCbCr JPEG images + * can be compressed from and decompressed to any of the extended RGB pixel + * formats or grayscale, or they can be decompressed to YUV planar images. + */ + TJCS_YCbCr, + /** + * Grayscale colorspace. The JPEG image retains only the luminance data (Y + * component), and any color data from the source image is discarded. + * Grayscale JPEG images can be compressed from and decompressed to any of + * the extended RGB pixel formats or grayscale, or they can be decompressed + * to YUV planar images. + */ + TJCS_GRAY, + /** + * CMYK colorspace. When compressing the JPEG image, the C, M, Y, and K + * components in the source image are reordered into image planes, but no + * colorspace conversion or subsampling is performed. CMYK JPEG images can + * only be decompressed to CMYK pixels. + */ + TJCS_CMYK, + /** + * YCCK colorspace. YCCK (AKA "YCbCrK") is not an absolute colorspace but + * rather a mathematical transformation of CMYK designed solely for storage + * and transmission. It is to CMYK as YCbCr is to RGB. CMYK pixels can be + * reversibly transformed into YCCK, and as with YCbCr, the chrominance + * components in the YCCK pixels can be subsampled without incurring major + * perceptual loss. YCCK JPEG images can only be compressed from and + * decompressed to CMYK pixels. + */ + TJCS_YCCK +}; + + +/** + * The uncompressed source/destination image is stored in bottom-up (Windows, + * OpenGL) order, not top-down (X11) order. + */ +#define TJFLAG_BOTTOMUP 2 +/** + * When decompressing an image that was compressed using chrominance + * subsampling, use the fastest chrominance upsampling algorithm available in + * the underlying codec. The default is to use smooth upsampling, which + * creates a smooth transition between neighboring chrominance components in + * order to reduce upsampling artifacts in the decompressed image. + */ +#define TJFLAG_FASTUPSAMPLE 256 +/** + * Disable buffer (re)allocation. If passed to one of the JPEG compression or + * transform functions, this flag will cause those functions to generate an + * error if the JPEG image buffer is invalid or too small rather than + * attempting to allocate or reallocate that buffer. This reproduces the + * behavior of earlier versions of TurboJPEG. + */ +#define TJFLAG_NOREALLOC 1024 +/** + * Use the fastest DCT/IDCT algorithm available in the underlying codec. The + * default if this flag is not specified is implementation-specific. For + * example, the implementation of TurboJPEG for libjpeg[-turbo] uses the fast + * algorithm by default when compressing, because this has been shown to have + * only a very slight effect on accuracy, but it uses the accurate algorithm + * when decompressing, because this has been shown to have a larger effect. + */ +#define TJFLAG_FASTDCT 2048 +/** + * Use the most accurate DCT/IDCT algorithm available in the underlying codec. + * The default if this flag is not specified is implementation-specific. For + * example, the implementation of TurboJPEG for libjpeg[-turbo] uses the fast + * algorithm by default when compressing, because this has been shown to have + * only a very slight effect on accuracy, but it uses the accurate algorithm + * when decompressing, because this has been shown to have a larger effect. + */ +#define TJFLAG_ACCURATEDCT 4096 +/** + * Immediately discontinue the current compression/decompression/transform + * operation if the underlying codec throws a warning (non-fatal error). The + * default behavior is to allow the operation to complete unless a fatal error + * is encountered. + */ +#define TJFLAG_STOPONWARNING 8192 +/** + * Use progressive entropy coding in JPEG images generated by the compression + * and transform functions. Progressive entropy coding will generally improve + * compression relative to baseline entropy coding (the default), but it will + * reduce compression and decompression performance considerably. + */ +#define TJFLAG_PROGRESSIVE 16384 + + +/** + * The number of error codes + */ +#define TJ_NUMERR 2 + +/** + * Error codes + */ +enum TJERR { + /** + * The error was non-fatal and recoverable, but the image may still be + * corrupt. + */ + TJERR_WARNING = 0, + /** + * The error was fatal and non-recoverable. + */ + TJERR_FATAL +}; + + +/** + * The number of transform operations + */ +#define TJ_NUMXOP 8 + +/** + * Transform operations for #tjTransform() + */ +enum TJXOP { + /** + * Do not transform the position of the image pixels + */ + TJXOP_NONE = 0, + /** + * Flip (mirror) image horizontally. This transform is imperfect if there + * are any partial MCU blocks on the right edge (see #TJXOPT_PERFECT.) + */ + TJXOP_HFLIP, + /** + * Flip (mirror) image vertically. This transform is imperfect if there are + * any partial MCU blocks on the bottom edge (see #TJXOPT_PERFECT.) + */ + TJXOP_VFLIP, + /** + * Transpose image (flip/mirror along upper left to lower right axis.) This + * transform is always perfect. + */ + TJXOP_TRANSPOSE, + /** + * Transverse transpose image (flip/mirror along upper right to lower left + * axis.) This transform is imperfect if there are any partial MCU blocks in + * the image (see #TJXOPT_PERFECT.) + */ + TJXOP_TRANSVERSE, + /** + * Rotate image clockwise by 90 degrees. This transform is imperfect if + * there are any partial MCU blocks on the bottom edge (see + * #TJXOPT_PERFECT.) + */ + TJXOP_ROT90, + /** + * Rotate image 180 degrees. This transform is imperfect if there are any + * partial MCU blocks in the image (see #TJXOPT_PERFECT.) + */ + TJXOP_ROT180, + /** + * Rotate image counter-clockwise by 90 degrees. This transform is imperfect + * if there are any partial MCU blocks on the right edge (see + * #TJXOPT_PERFECT.) + */ + TJXOP_ROT270 +}; + + +/** + * This option will cause #tjTransform() to return an error if the transform is + * not perfect. Lossless transforms operate on MCU blocks, whose size depends + * on the level of chrominance subsampling used (see #tjMCUWidth + * and #tjMCUHeight.) If the image's width or height is not evenly divisible + * by the MCU block size, then there will be partial MCU blocks on the right + * and/or bottom edges. It is not possible to move these partial MCU blocks to + * the top or left of the image, so any transform that would require that is + * "imperfect." If this option is not specified, then any partial MCU blocks + * that cannot be transformed will be left in place, which will create + * odd-looking strips on the right or bottom edge of the image. + */ +#define TJXOPT_PERFECT 1 +/** + * This option will cause #tjTransform() to discard any partial MCU blocks that + * cannot be transformed. + */ +#define TJXOPT_TRIM 2 +/** + * This option will enable lossless cropping. See #tjTransform() for more + * information. + */ +#define TJXOPT_CROP 4 +/** + * This option will discard the color data in the input image and produce + * a grayscale output image. + */ +#define TJXOPT_GRAY 8 +/** + * This option will prevent #tjTransform() from outputting a JPEG image for + * this particular transform (this can be used in conjunction with a custom + * filter to capture the transformed DCT coefficients without transcoding + * them.) + */ +#define TJXOPT_NOOUTPUT 16 +/** + * This option will enable progressive entropy coding in the output image + * generated by this particular transform. Progressive entropy coding will + * generally improve compression relative to baseline entropy coding (the + * default), but it will reduce compression and decompression performance + * considerably. + */ +#define TJXOPT_PROGRESSIVE 32 +/** + * This option will prevent #tjTransform() from copying any extra markers + * (including EXIF and ICC profile data) from the source image to the output + * image. + */ +#define TJXOPT_COPYNONE 64 + + +/** + * Scaling factor + */ +typedef struct { + /** + * Numerator + */ + int num; + /** + * Denominator + */ + int denom; +} tjscalingfactor; + +/** + * Cropping region + */ +typedef struct { + /** + * The left boundary of the cropping region. This must be evenly divisible + * by the MCU block width (see #tjMCUWidth.) + */ + int x; + /** + * The upper boundary of the cropping region. This must be evenly divisible + * by the MCU block height (see #tjMCUHeight.) + */ + int y; + /** + * The width of the cropping region. Setting this to 0 is the equivalent of + * setting it to the width of the source JPEG image - x. + */ + int w; + /** + * The height of the cropping region. Setting this to 0 is the equivalent of + * setting it to the height of the source JPEG image - y. + */ + int h; +} tjregion; + +/** + * Lossless transform + */ +typedef struct tjtransform { + /** + * Cropping region + */ + tjregion r; + /** + * One of the @ref TJXOP "transform operations" + */ + int op; + /** + * The bitwise OR of one of more of the @ref TJXOPT_CROP "transform options" + */ + int options; + /** + * Arbitrary data that can be accessed within the body of the callback + * function + */ + void *data; + /** + * A callback function that can be used to modify the DCT coefficients + * after they are losslessly transformed but before they are transcoded to a + * new JPEG image. This allows for custom filters or other transformations + * to be applied in the frequency domain. + * + * @param coeffs pointer to an array of transformed DCT coefficients. (NOTE: + * this pointer is not guaranteed to be valid once the callback returns, so + * applications wishing to hand off the DCT coefficients to another function + * or library should make a copy of them within the body of the callback.) + * + * @param arrayRegion #tjregion structure containing the width and height of + * the array pointed to by coeffs as well as its offset relative to + * the component plane. TurboJPEG implementations may choose to split each + * component plane into multiple DCT coefficient arrays and call the callback + * function once for each array. + * + * @param planeRegion #tjregion structure containing the width and height of + * the component plane to which coeffs belongs + * + * @param componentID ID number of the component plane to which + * coeffs belongs (Y, Cb, and Cr have, respectively, ID's of 0, 1, + * and 2 in typical JPEG images.) + * + * @param transformID ID number of the transformed image to which + * coeffs belongs. This is the same as the index of the transform + * in the transforms array that was passed to #tjTransform(). + * + * @param transform a pointer to a #tjtransform structure that specifies the + * parameters and/or cropping region for this transform + * + * @return 0 if the callback was successful, or -1 if an error occurred. + */ + int (*customFilter) (short *coeffs, tjregion arrayRegion, + tjregion planeRegion, int componentIndex, + int transformIndex, struct tjtransform *transform); +} tjtransform; + +/** + * TurboJPEG instance handle + */ +typedef void *tjhandle; + + +/** + * Pad the given width to the nearest 32-bit boundary + */ +#define TJPAD(width) (((width) + 3) & (~3)) + +/** + * Compute the scaled value of dimension using the given scaling + * factor. This macro performs the integer equivalent of ceil(dimension * + * scalingFactor). + */ +#define TJSCALED(dimension, scalingFactor) \ + ((dimension * scalingFactor.num + scalingFactor.denom - 1) / \ + scalingFactor.denom) + + +#ifdef __cplusplus +extern "C" { +#endif + + +/** + * Create a TurboJPEG compressor instance. + * + * @return a handle to the newly-created instance, or NULL if an error + * occurred (see #tjGetErrorStr2().) + */ +DLLEXPORT tjhandle tjInitCompress(void); + + +/** + * Compress an RGB, grayscale, or CMYK image into a JPEG image. + * + * @param handle a handle to a TurboJPEG compressor or transformer instance + * + * @param srcBuf pointer to an image buffer containing RGB, grayscale, or + * CMYK pixels to be compressed + * + * @param width width (in pixels) of the source image + * + * @param pitch bytes per line in the source image. Normally, this should be + * width * #tjPixelSize[pixelFormat] if the image is unpadded, or + * #TJPAD(width * #tjPixelSize[pixelFormat]) if each line of the image + * is padded to the nearest 32-bit boundary, as is the case for Windows + * bitmaps. You can also be clever and use this parameter to skip lines, etc. + * Setting this parameter to 0 is the equivalent of setting it to + * width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the source image + * + * @param pixelFormat pixel format of the source image (see @ref TJPF + * "Pixel formats".) + * + * @param jpegBuf address of a pointer to an image buffer that will receive the + * JPEG image. TurboJPEG has the ability to reallocate the JPEG buffer + * to accommodate the size of the JPEG image. Thus, you can choose to: + * -# pre-allocate the JPEG buffer with an arbitrary size using #tjAlloc() and + * let TurboJPEG grow the buffer as needed, + * -# set *jpegBuf to NULL to tell TurboJPEG to allocate the buffer + * for you, or + * -# pre-allocate the buffer to a "worst case" size determined by calling + * #tjBufSize(). This should ensure that the buffer never has to be + * re-allocated (setting #TJFLAG_NOREALLOC guarantees that it won't be.) + * . + * If you choose option 1, *jpegSize should be set to the size of your + * pre-allocated buffer. In any case, unless you have set #TJFLAG_NOREALLOC, + * you should always check *jpegBuf upon return from this function, as + * it may have changed. + * + * @param jpegSize pointer to an unsigned long variable that holds the size of + * the JPEG image buffer. If *jpegBuf points to a pre-allocated + * buffer, then *jpegSize should be set to the size of the buffer. + * Upon return, *jpegSize will contain the size of the JPEG image (in + * bytes.) If *jpegBuf points to a JPEG image buffer that is being + * reused from a previous call to one of the JPEG compression functions, then + * *jpegSize is ignored. + * + * @param jpegSubsamp the level of chrominance subsampling to be used when + * generating the JPEG image (see @ref TJSAMP + * "Chrominance subsampling options".) + * + * @param jpegQual the image quality of the generated JPEG image (1 = worst, + * 100 = best) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjCompress2(tjhandle handle, const unsigned char *srcBuf, + int width, int pitch, int height, int pixelFormat, + unsigned char **jpegBuf, unsigned long *jpegSize, + int jpegSubsamp, int jpegQual, int flags); + + +/** + * Compress a YUV planar image into a JPEG image. + * + * @param handle a handle to a TurboJPEG compressor or transformer instance + * + * @param srcBuf pointer to an image buffer containing a YUV planar image to be + * compressed. The size of this buffer should match the value returned by + * #tjBufSizeYUV2() for the given image width, height, padding, and level of + * chrominance subsampling. The Y, U (Cb), and V (Cr) image planes should be + * stored sequentially in the source buffer (refer to @ref YUVnotes + * "YUV Image Format Notes".) + * + * @param width width (in pixels) of the source image. If the width is not an + * even multiple of the MCU block width (see #tjMCUWidth), then an intermediate + * buffer copy will be performed within TurboJPEG. + * + * @param pad the line padding used in the source image. For instance, if each + * line in each plane of the YUV image is padded to the nearest multiple of 4 + * bytes, then pad should be set to 4. + * + * @param height height (in pixels) of the source image. If the height is not + * an even multiple of the MCU block height (see #tjMCUHeight), then an + * intermediate buffer copy will be performed within TurboJPEG. + * + * @param subsamp the level of chrominance subsampling used in the source + * image (see @ref TJSAMP "Chrominance subsampling options".) + * + * @param jpegBuf address of a pointer to an image buffer that will receive the + * JPEG image. TurboJPEG has the ability to reallocate the JPEG buffer to + * accommodate the size of the JPEG image. Thus, you can choose to: + * -# pre-allocate the JPEG buffer with an arbitrary size using #tjAlloc() and + * let TurboJPEG grow the buffer as needed, + * -# set *jpegBuf to NULL to tell TurboJPEG to allocate the buffer + * for you, or + * -# pre-allocate the buffer to a "worst case" size determined by calling + * #tjBufSize(). This should ensure that the buffer never has to be + * re-allocated (setting #TJFLAG_NOREALLOC guarantees that it won't be.) + * . + * If you choose option 1, *jpegSize should be set to the size of your + * pre-allocated buffer. In any case, unless you have set #TJFLAG_NOREALLOC, + * you should always check *jpegBuf upon return from this function, as + * it may have changed. + * + * @param jpegSize pointer to an unsigned long variable that holds the size of + * the JPEG image buffer. If *jpegBuf points to a pre-allocated + * buffer, then *jpegSize should be set to the size of the buffer. + * Upon return, *jpegSize will contain the size of the JPEG image (in + * bytes.) If *jpegBuf points to a JPEG image buffer that is being + * reused from a previous call to one of the JPEG compression functions, then + * *jpegSize is ignored. + * + * @param jpegQual the image quality of the generated JPEG image (1 = worst, + * 100 = best) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjCompressFromYUV(tjhandle handle, const unsigned char *srcBuf, + int width, int pad, int height, int subsamp, + unsigned char **jpegBuf, + unsigned long *jpegSize, int jpegQual, + int flags); + + +/** + * Compress a set of Y, U (Cb), and V (Cr) image planes into a JPEG image. + * + * @param handle a handle to a TurboJPEG compressor or transformer instance + * + * @param srcPlanes an array of pointers to Y, U (Cb), and V (Cr) image planes + * (or just a Y plane, if compressing a grayscale image) that contain a YUV + * image to be compressed. These planes can be contiguous or non-contiguous in + * memory. The size of each plane should match the value returned by + * #tjPlaneSizeYUV() for the given image width, height, strides, and level of + * chrominance subsampling. Refer to @ref YUVnotes "YUV Image Format Notes" + * for more details. + * + * @param width width (in pixels) of the source image. If the width is not an + * even multiple of the MCU block width (see #tjMCUWidth), then an intermediate + * buffer copy will be performed within TurboJPEG. + * + * @param strides an array of integers, each specifying the number of bytes per + * line in the corresponding plane of the YUV source image. Setting the stride + * for any plane to 0 is the same as setting it to the plane width (see + * @ref YUVnotes "YUV Image Format Notes".) If strides is NULL, then + * the strides for all planes will be set to their respective plane widths. + * You can adjust the strides in order to specify an arbitrary amount of line + * padding in each plane or to create a JPEG image from a subregion of a larger + * YUV planar image. + * + * @param height height (in pixels) of the source image. If the height is not + * an even multiple of the MCU block height (see #tjMCUHeight), then an + * intermediate buffer copy will be performed within TurboJPEG. + * + * @param subsamp the level of chrominance subsampling used in the source + * image (see @ref TJSAMP "Chrominance subsampling options".) + * + * @param jpegBuf address of a pointer to an image buffer that will receive the + * JPEG image. TurboJPEG has the ability to reallocate the JPEG buffer to + * accommodate the size of the JPEG image. Thus, you can choose to: + * -# pre-allocate the JPEG buffer with an arbitrary size using #tjAlloc() and + * let TurboJPEG grow the buffer as needed, + * -# set *jpegBuf to NULL to tell TurboJPEG to allocate the buffer + * for you, or + * -# pre-allocate the buffer to a "worst case" size determined by calling + * #tjBufSize(). This should ensure that the buffer never has to be + * re-allocated (setting #TJFLAG_NOREALLOC guarantees that it won't be.) + * . + * If you choose option 1, *jpegSize should be set to the size of your + * pre-allocated buffer. In any case, unless you have set #TJFLAG_NOREALLOC, + * you should always check *jpegBuf upon return from this function, as + * it may have changed. + * + * @param jpegSize pointer to an unsigned long variable that holds the size of + * the JPEG image buffer. If *jpegBuf points to a pre-allocated + * buffer, then *jpegSize should be set to the size of the buffer. + * Upon return, *jpegSize will contain the size of the JPEG image (in + * bytes.) If *jpegBuf points to a JPEG image buffer that is being + * reused from a previous call to one of the JPEG compression functions, then + * *jpegSize is ignored. + * + * @param jpegQual the image quality of the generated JPEG image (1 = worst, + * 100 = best) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjCompressFromYUVPlanes(tjhandle handle, + const unsigned char **srcPlanes, + int width, const int *strides, + int height, int subsamp, + unsigned char **jpegBuf, + unsigned long *jpegSize, int jpegQual, + int flags); + + +/** + * The maximum size of the buffer (in bytes) required to hold a JPEG image with + * the given parameters. The number of bytes returned by this function is + * larger than the size of the uncompressed source image. The reason for this + * is that the JPEG format uses 16-bit coefficients, and it is thus possible + * for a very high-quality JPEG image with very high-frequency content to + * expand rather than compress when converted to the JPEG format. Such images + * represent a very rare corner case, but since there is no way to predict the + * size of a JPEG image prior to compression, the corner case has to be + * handled. + * + * @param width width (in pixels) of the image + * + * @param height height (in pixels) of the image + * + * @param jpegSubsamp the level of chrominance subsampling to be used when + * generating the JPEG image (see @ref TJSAMP + * "Chrominance subsampling options".) + * + * @return the maximum size of the buffer (in bytes) required to hold the + * image, or -1 if the arguments are out of bounds. + */ +DLLEXPORT unsigned long tjBufSize(int width, int height, int jpegSubsamp); + + +/** + * The size of the buffer (in bytes) required to hold a YUV planar image with + * the given parameters. + * + * @param width width (in pixels) of the image + * + * @param pad the width of each line in each plane of the image is padded to + * the nearest multiple of this number of bytes (must be a power of 2.) + * + * @param height height (in pixels) of the image + * + * @param subsamp level of chrominance subsampling in the image (see + * @ref TJSAMP "Chrominance subsampling options".) + * + * @return the size of the buffer (in bytes) required to hold the image, or + * -1 if the arguments are out of bounds. + */ +DLLEXPORT unsigned long tjBufSizeYUV2(int width, int pad, int height, + int subsamp); + + +/** + * The size of the buffer (in bytes) required to hold a YUV image plane with + * the given parameters. + * + * @param componentID ID number of the image plane (0 = Y, 1 = U/Cb, 2 = V/Cr) + * + * @param width width (in pixels) of the YUV image. NOTE: this is the width of + * the whole image, not the plane width. + * + * @param stride bytes per line in the image plane. Setting this to 0 is the + * equivalent of setting it to the plane width. + * + * @param height height (in pixels) of the YUV image. NOTE: this is the height + * of the whole image, not the plane height. + * + * @param subsamp level of chrominance subsampling in the image (see + * @ref TJSAMP "Chrominance subsampling options".) + * + * @return the size of the buffer (in bytes) required to hold the YUV image + * plane, or -1 if the arguments are out of bounds. + */ +DLLEXPORT unsigned long tjPlaneSizeYUV(int componentID, int width, int stride, + int height, int subsamp); + + +/** + * The plane width of a YUV image plane with the given parameters. Refer to + * @ref YUVnotes "YUV Image Format Notes" for a description of plane width. + * + * @param componentID ID number of the image plane (0 = Y, 1 = U/Cb, 2 = V/Cr) + * + * @param width width (in pixels) of the YUV image + * + * @param subsamp level of chrominance subsampling in the image (see + * @ref TJSAMP "Chrominance subsampling options".) + * + * @return the plane width of a YUV image plane with the given parameters, or + * -1 if the arguments are out of bounds. + */ +DLLEXPORT int tjPlaneWidth(int componentID, int width, int subsamp); + + +/** + * The plane height of a YUV image plane with the given parameters. Refer to + * @ref YUVnotes "YUV Image Format Notes" for a description of plane height. + * + * @param componentID ID number of the image plane (0 = Y, 1 = U/Cb, 2 = V/Cr) + * + * @param height height (in pixels) of the YUV image + * + * @param subsamp level of chrominance subsampling in the image (see + * @ref TJSAMP "Chrominance subsampling options".) + * + * @return the plane height of a YUV image plane with the given parameters, or + * -1 if the arguments are out of bounds. + */ +DLLEXPORT int tjPlaneHeight(int componentID, int height, int subsamp); + + +/** + * Encode an RGB or grayscale image into a YUV planar image. This function + * uses the accelerated color conversion routines in the underlying + * codec but does not execute any of the other steps in the JPEG compression + * process. + * + * @param handle a handle to a TurboJPEG compressor or transformer instance + * + * @param srcBuf pointer to an image buffer containing RGB or grayscale pixels + * to be encoded + * + * @param width width (in pixels) of the source image + * + * @param pitch bytes per line in the source image. Normally, this should be + * width * #tjPixelSize[pixelFormat] if the image is unpadded, or + * #TJPAD(width * #tjPixelSize[pixelFormat]) if each line of the image + * is padded to the nearest 32-bit boundary, as is the case for Windows + * bitmaps. You can also be clever and use this parameter to skip lines, etc. + * Setting this parameter to 0 is the equivalent of setting it to + * width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the source image + * + * @param pixelFormat pixel format of the source image (see @ref TJPF + * "Pixel formats".) + * + * @param dstBuf pointer to an image buffer that will receive the YUV image. + * Use #tjBufSizeYUV2() to determine the appropriate size for this buffer based + * on the image width, height, padding, and level of chrominance subsampling. + * The Y, U (Cb), and V (Cr) image planes will be stored sequentially in the + * buffer (refer to @ref YUVnotes "YUV Image Format Notes".) + * + * @param pad the width of each line in each plane of the YUV image will be + * padded to the nearest multiple of this number of bytes (must be a power of + * 2.) To generate images suitable for X Video, pad should be set to + * 4. + * + * @param subsamp the level of chrominance subsampling to be used when + * generating the YUV image (see @ref TJSAMP + * "Chrominance subsampling options".) To generate images suitable for X + * Video, subsamp should be set to @ref TJSAMP_420. This produces an + * image compatible with the I420 (AKA "YUV420P") format. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjEncodeYUV3(tjhandle handle, const unsigned char *srcBuf, + int width, int pitch, int height, int pixelFormat, + unsigned char *dstBuf, int pad, int subsamp, + int flags); + + +/** + * Encode an RGB or grayscale image into separate Y, U (Cb), and V (Cr) image + * planes. This function uses the accelerated color conversion routines in the + * underlying codec but does not execute any of the other steps in the JPEG + * compression process. + * + * @param handle a handle to a TurboJPEG compressor or transformer instance + * + * @param srcBuf pointer to an image buffer containing RGB or grayscale pixels + * to be encoded + * + * @param width width (in pixels) of the source image + * + * @param pitch bytes per line in the source image. Normally, this should be + * width * #tjPixelSize[pixelFormat] if the image is unpadded, or + * #TJPAD(width * #tjPixelSize[pixelFormat]) if each line of the image + * is padded to the nearest 32-bit boundary, as is the case for Windows + * bitmaps. You can also be clever and use this parameter to skip lines, etc. + * Setting this parameter to 0 is the equivalent of setting it to + * width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the source image + * + * @param pixelFormat pixel format of the source image (see @ref TJPF + * "Pixel formats".) + * + * @param dstPlanes an array of pointers to Y, U (Cb), and V (Cr) image planes + * (or just a Y plane, if generating a grayscale image) that will receive the + * encoded image. These planes can be contiguous or non-contiguous in memory. + * Use #tjPlaneSizeYUV() to determine the appropriate size for each plane based + * on the image width, height, strides, and level of chrominance subsampling. + * Refer to @ref YUVnotes "YUV Image Format Notes" for more details. + * + * @param strides an array of integers, each specifying the number of bytes per + * line in the corresponding plane of the output image. Setting the stride for + * any plane to 0 is the same as setting it to the plane width (see + * @ref YUVnotes "YUV Image Format Notes".) If strides is NULL, then + * the strides for all planes will be set to their respective plane widths. + * You can adjust the strides in order to add an arbitrary amount of line + * padding to each plane or to encode an RGB or grayscale image into a + * subregion of a larger YUV planar image. + * + * @param subsamp the level of chrominance subsampling to be used when + * generating the YUV image (see @ref TJSAMP + * "Chrominance subsampling options".) To generate images suitable for X + * Video, subsamp should be set to @ref TJSAMP_420. This produces an + * image compatible with the I420 (AKA "YUV420P") format. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjEncodeYUVPlanes(tjhandle handle, const unsigned char *srcBuf, + int width, int pitch, int height, + int pixelFormat, unsigned char **dstPlanes, + int *strides, int subsamp, int flags); + + +/** + * Create a TurboJPEG decompressor instance. + * + * @return a handle to the newly-created instance, or NULL if an error + * occurred (see #tjGetErrorStr2().) +*/ +DLLEXPORT tjhandle tjInitDecompress(void); + + +/** + * Retrieve information about a JPEG image without decompressing it. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param jpegBuf pointer to a buffer containing a JPEG image + * + * @param jpegSize size of the JPEG image (in bytes) + * + * @param width pointer to an integer variable that will receive the width (in + * pixels) of the JPEG image + * + * @param height pointer to an integer variable that will receive the height + * (in pixels) of the JPEG image + * + * @param jpegSubsamp pointer to an integer variable that will receive the + * level of chrominance subsampling used when the JPEG image was compressed + * (see @ref TJSAMP "Chrominance subsampling options".) + * + * @param jpegColorspace pointer to an integer variable that will receive one + * of the JPEG colorspace constants, indicating the colorspace of the JPEG + * image (see @ref TJCS "JPEG colorspaces".) + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) +*/ +DLLEXPORT int tjDecompressHeader3(tjhandle handle, + const unsigned char *jpegBuf, + unsigned long jpegSize, int *width, + int *height, int *jpegSubsamp, + int *jpegColorspace); + + +/** + * Returns a list of fractional scaling factors that the JPEG decompressor in + * this implementation of TurboJPEG supports. + * + * @param numscalingfactors pointer to an integer variable that will receive + * the number of elements in the list + * + * @return a pointer to a list of fractional scaling factors, or NULL if an + * error is encountered (see #tjGetErrorStr2().) +*/ +DLLEXPORT tjscalingfactor *tjGetScalingFactors(int *numscalingfactors); + + +/** + * Decompress a JPEG image to an RGB, grayscale, or CMYK image. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param jpegBuf pointer to a buffer containing the JPEG image to decompress + * + * @param jpegSize size of the JPEG image (in bytes) + * + * @param dstBuf pointer to an image buffer that will receive the decompressed + * image. This buffer should normally be pitch * scaledHeight bytes + * in size, where scaledHeight can be determined by calling + * #TJSCALED() with the JPEG image height and one of the scaling factors + * returned by #tjGetScalingFactors(). The dstBuf pointer may also be + * used to decompress into a specific region of a larger buffer. + * + * @param width desired width (in pixels) of the destination image. If this is + * different than the width of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired width. If width is + * set to 0, then only the height will be considered when determining the + * scaled image size. + * + * @param pitch bytes per line in the destination image. Normally, this is + * scaledWidth * #tjPixelSize[pixelFormat] if the decompressed image + * is unpadded, else #TJPAD(scaledWidth * #tjPixelSize[pixelFormat]) + * if each line of the decompressed image is padded to the nearest 32-bit + * boundary, as is the case for Windows bitmaps. (NOTE: scaledWidth + * can be determined by calling #TJSCALED() with the JPEG image width and one + * of the scaling factors returned by #tjGetScalingFactors().) You can also be + * clever and use the pitch parameter to skip lines, etc. Setting this + * parameter to 0 is the equivalent of setting it to + * scaledWidth * #tjPixelSize[pixelFormat]. + * + * @param height desired height (in pixels) of the destination image. If this + * is different than the height of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired height. If height + * is set to 0, then only the width will be considered when determining the + * scaled image size. + * + * @param pixelFormat pixel format of the destination image (see @ref + * TJPF "Pixel formats".) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjDecompress2(tjhandle handle, const unsigned char *jpegBuf, + unsigned long jpegSize, unsigned char *dstBuf, + int width, int pitch, int height, int pixelFormat, + int flags); + + +/** + * Decompress a JPEG image to a YUV planar image. This function performs JPEG + * decompression but leaves out the color conversion step, so a planar YUV + * image is generated instead of an RGB image. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param jpegBuf pointer to a buffer containing the JPEG image to decompress + * + * @param jpegSize size of the JPEG image (in bytes) + * + * @param dstBuf pointer to an image buffer that will receive the YUV image. + * Use #tjBufSizeYUV2() to determine the appropriate size for this buffer based + * on the image width, height, padding, and level of subsampling. The Y, + * U (Cb), and V (Cr) image planes will be stored sequentially in the buffer + * (refer to @ref YUVnotes "YUV Image Format Notes".) + * + * @param width desired width (in pixels) of the YUV image. If this is + * different than the width of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired width. If width is + * set to 0, then only the height will be considered when determining the + * scaled image size. If the scaled width is not an even multiple of the MCU + * block width (see #tjMCUWidth), then an intermediate buffer copy will be + * performed within TurboJPEG. + * + * @param pad the width of each line in each plane of the YUV image will be + * padded to the nearest multiple of this number of bytes (must be a power of + * 2.) To generate images suitable for X Video, pad should be set to + * 4. + * + * @param height desired height (in pixels) of the YUV image. If this is + * different than the height of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired height. If height + * is set to 0, then only the width will be considered when determining the + * scaled image size. If the scaled height is not an even multiple of the MCU + * block height (see #tjMCUHeight), then an intermediate buffer copy will be + * performed within TurboJPEG. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjDecompressToYUV2(tjhandle handle, const unsigned char *jpegBuf, + unsigned long jpegSize, unsigned char *dstBuf, + int width, int pad, int height, int flags); + + +/** + * Decompress a JPEG image into separate Y, U (Cb), and V (Cr) image + * planes. This function performs JPEG decompression but leaves out the color + * conversion step, so a planar YUV image is generated instead of an RGB image. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param jpegBuf pointer to a buffer containing the JPEG image to decompress + * + * @param jpegSize size of the JPEG image (in bytes) + * + * @param dstPlanes an array of pointers to Y, U (Cb), and V (Cr) image planes + * (or just a Y plane, if decompressing a grayscale image) that will receive + * the YUV image. These planes can be contiguous or non-contiguous in memory. + * Use #tjPlaneSizeYUV() to determine the appropriate size for each plane based + * on the scaled image width, scaled image height, strides, and level of + * chrominance subsampling. Refer to @ref YUVnotes "YUV Image Format Notes" + * for more details. + * + * @param width desired width (in pixels) of the YUV image. If this is + * different than the width of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired width. If width is + * set to 0, then only the height will be considered when determining the + * scaled image size. If the scaled width is not an even multiple of the MCU + * block width (see #tjMCUWidth), then an intermediate buffer copy will be + * performed within TurboJPEG. + * + * @param strides an array of integers, each specifying the number of bytes per + * line in the corresponding plane of the output image. Setting the stride for + * any plane to 0 is the same as setting it to the scaled plane width (see + * @ref YUVnotes "YUV Image Format Notes".) If strides is NULL, then + * the strides for all planes will be set to their respective scaled plane + * widths. You can adjust the strides in order to add an arbitrary amount of + * line padding to each plane or to decompress the JPEG image into a subregion + * of a larger YUV planar image. + * + * @param height desired height (in pixels) of the YUV image. If this is + * different than the height of the JPEG image being decompressed, then + * TurboJPEG will use scaling in the JPEG decompressor to generate the largest + * possible image that will fit within the desired height. If height + * is set to 0, then only the width will be considered when determining the + * scaled image size. If the scaled height is not an even multiple of the MCU + * block height (see #tjMCUHeight), then an intermediate buffer copy will be + * performed within TurboJPEG. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjDecompressToYUVPlanes(tjhandle handle, + const unsigned char *jpegBuf, + unsigned long jpegSize, + unsigned char **dstPlanes, int width, + int *strides, int height, int flags); + + +/** + * Decode a YUV planar image into an RGB or grayscale image. This function + * uses the accelerated color conversion routines in the underlying + * codec but does not execute any of the other steps in the JPEG decompression + * process. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param srcBuf pointer to an image buffer containing a YUV planar image to be + * decoded. The size of this buffer should match the value returned by + * #tjBufSizeYUV2() for the given image width, height, padding, and level of + * chrominance subsampling. The Y, U (Cb), and V (Cr) image planes should be + * stored sequentially in the source buffer (refer to @ref YUVnotes + * "YUV Image Format Notes".) + * + * @param pad Use this parameter to specify that the width of each line in each + * plane of the YUV source image is padded to the nearest multiple of this + * number of bytes (must be a power of 2.) + * + * @param subsamp the level of chrominance subsampling used in the YUV source + * image (see @ref TJSAMP "Chrominance subsampling options".) + * + * @param dstBuf pointer to an image buffer that will receive the decoded + * image. This buffer should normally be pitch * height bytes in + * size, but the dstBuf pointer can also be used to decode into a + * specific region of a larger buffer. + * + * @param width width (in pixels) of the source and destination images + * + * @param pitch bytes per line in the destination image. Normally, this should + * be width * #tjPixelSize[pixelFormat] if the destination image is + * unpadded, or #TJPAD(width * #tjPixelSize[pixelFormat]) if each line + * of the destination image should be padded to the nearest 32-bit boundary, as + * is the case for Windows bitmaps. You can also be clever and use the pitch + * parameter to skip lines, etc. Setting this parameter to 0 is the equivalent + * of setting it to width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the source and destination images + * + * @param pixelFormat pixel format of the destination image (see @ref TJPF + * "Pixel formats".) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjDecodeYUV(tjhandle handle, const unsigned char *srcBuf, + int pad, int subsamp, unsigned char *dstBuf, + int width, int pitch, int height, int pixelFormat, + int flags); + + +/** + * Decode a set of Y, U (Cb), and V (Cr) image planes into an RGB or grayscale + * image. This function uses the accelerated color conversion routines in the + * underlying codec but does not execute any of the other steps in the JPEG + * decompression process. + * + * @param handle a handle to a TurboJPEG decompressor or transformer instance + * + * @param srcPlanes an array of pointers to Y, U (Cb), and V (Cr) image planes + * (or just a Y plane, if decoding a grayscale image) that contain a YUV image + * to be decoded. These planes can be contiguous or non-contiguous in memory. + * The size of each plane should match the value returned by #tjPlaneSizeYUV() + * for the given image width, height, strides, and level of chrominance + * subsampling. Refer to @ref YUVnotes "YUV Image Format Notes" for more + * details. + * + * @param strides an array of integers, each specifying the number of bytes per + * line in the corresponding plane of the YUV source image. Setting the stride + * for any plane to 0 is the same as setting it to the plane width (see + * @ref YUVnotes "YUV Image Format Notes".) If strides is NULL, then + * the strides for all planes will be set to their respective plane widths. + * You can adjust the strides in order to specify an arbitrary amount of line + * padding in each plane or to decode a subregion of a larger YUV planar image. + * + * @param subsamp the level of chrominance subsampling used in the YUV source + * image (see @ref TJSAMP "Chrominance subsampling options".) + * + * @param dstBuf pointer to an image buffer that will receive the decoded + * image. This buffer should normally be pitch * height bytes in + * size, but the dstBuf pointer can also be used to decode into a + * specific region of a larger buffer. + * + * @param width width (in pixels) of the source and destination images + * + * @param pitch bytes per line in the destination image. Normally, this should + * be width * #tjPixelSize[pixelFormat] if the destination image is + * unpadded, or #TJPAD(width * #tjPixelSize[pixelFormat]) if each line + * of the destination image should be padded to the nearest 32-bit boundary, as + * is the case for Windows bitmaps. You can also be clever and use the pitch + * parameter to skip lines, etc. Setting this parameter to 0 is the equivalent + * of setting it to width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the source and destination images + * + * @param pixelFormat pixel format of the destination image (see @ref TJPF + * "Pixel formats".) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjDecodeYUVPlanes(tjhandle handle, + const unsigned char **srcPlanes, + const int *strides, int subsamp, + unsigned char *dstBuf, int width, int pitch, + int height, int pixelFormat, int flags); + + +/** + * Create a new TurboJPEG transformer instance. + * + * @return a handle to the newly-created instance, or NULL if an error + * occurred (see #tjGetErrorStr2().) + */ +DLLEXPORT tjhandle tjInitTransform(void); + + +/** + * Losslessly transform a JPEG image into another JPEG image. Lossless + * transforms work by moving the raw DCT coefficients from one JPEG image + * structure to another without altering the values of the coefficients. While + * this is typically faster than decompressing the image, transforming it, and + * re-compressing it, lossless transforms are not free. Each lossless + * transform requires reading and performing Huffman decoding on all of the + * coefficients in the source image, regardless of the size of the destination + * image. Thus, this function provides a means of generating multiple + * transformed images from the same source or applying multiple + * transformations simultaneously, in order to eliminate the need to read the + * source coefficients multiple times. + * + * @param handle a handle to a TurboJPEG transformer instance + * + * @param jpegBuf pointer to a buffer containing the JPEG source image to + * transform + * + * @param jpegSize size of the JPEG source image (in bytes) + * + * @param n the number of transformed JPEG images to generate + * + * @param dstBufs pointer to an array of n image buffers. dstBufs[i] + * will receive a JPEG image that has been transformed using the parameters in + * transforms[i]. TurboJPEG has the ability to reallocate the JPEG + * buffer to accommodate the size of the JPEG image. Thus, you can choose to: + * -# pre-allocate the JPEG buffer with an arbitrary size using #tjAlloc() and + * let TurboJPEG grow the buffer as needed, + * -# set dstBufs[i] to NULL to tell TurboJPEG to allocate the buffer + * for you, or + * -# pre-allocate the buffer to a "worst case" size determined by calling + * #tjBufSize() with the transformed or cropped width and height. Under normal + * circumstances, this should ensure that the buffer never has to be + * re-allocated (setting #TJFLAG_NOREALLOC guarantees that it won't be.) Note, + * however, that there are some rare cases (such as transforming images with a + * large amount of embedded EXIF or ICC profile data) in which the output image + * will be larger than the worst-case size, and #TJFLAG_NOREALLOC cannot be + * used in those cases. + * . + * If you choose option 1, dstSizes[i] should be set to the size of + * your pre-allocated buffer. In any case, unless you have set + * #TJFLAG_NOREALLOC, you should always check dstBufs[i] upon return + * from this function, as it may have changed. + * + * @param dstSizes pointer to an array of n unsigned long variables that will + * receive the actual sizes (in bytes) of each transformed JPEG image. If + * dstBufs[i] points to a pre-allocated buffer, then + * dstSizes[i] should be set to the size of the buffer. Upon return, + * dstSizes[i] will contain the size of the JPEG image (in bytes.) + * + * @param transforms pointer to an array of n #tjtransform structures, each of + * which specifies the transform parameters and/or cropping region for the + * corresponding transformed output image. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_ACCURATEDCT + * "flags" + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2() + * and #tjGetErrorCode().) + */ +DLLEXPORT int tjTransform(tjhandle handle, const unsigned char *jpegBuf, + unsigned long jpegSize, int n, + unsigned char **dstBufs, unsigned long *dstSizes, + tjtransform *transforms, int flags); + + +/** + * Destroy a TurboJPEG compressor, decompressor, or transformer instance. + * + * @param handle a handle to a TurboJPEG compressor, decompressor or + * transformer instance + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2().) + */ +DLLEXPORT int tjDestroy(tjhandle handle); + + +/** + * Allocate an image buffer for use with TurboJPEG. You should always use + * this function to allocate the JPEG destination buffer(s) for the compression + * and transform functions unless you are disabling automatic buffer + * (re)allocation (by setting #TJFLAG_NOREALLOC.) + * + * @param bytes the number of bytes to allocate + * + * @return a pointer to a newly-allocated buffer with the specified number of + * bytes. + * + * @sa tjFree() + */ +DLLEXPORT unsigned char *tjAlloc(int bytes); + + +/** + * Load an uncompressed image from disk into memory. + * + * @param filename name of a file containing an uncompressed image in Windows + * BMP or PBMPLUS (PPM/PGM) format + * + * @param width pointer to an integer variable that will receive the width (in + * pixels) of the uncompressed image + * + * @param align row alignment of the image buffer to be returned (must be a + * power of 2.) For instance, setting this parameter to 4 will cause all rows + * in the image buffer to be padded to the nearest 32-bit boundary, and setting + * this parameter to 1 will cause all rows in the image buffer to be unpadded. + * + * @param height pointer to an integer variable that will receive the height + * (in pixels) of the uncompressed image + * + * @param pixelFormat pointer to an integer variable that specifies or will + * receive the pixel format of the uncompressed image buffer. The behavior of + * #tjLoadImage() will vary depending on the value of *pixelFormat + * passed to the function: + * - @ref TJPF_UNKNOWN : The uncompressed image buffer returned by the function + * will use the most optimal pixel format for the file type, and + * *pixelFormat will contain the ID of this pixel format upon + * successful return from the function. + * - @ref TJPF_GRAY : Only PGM files and 8-bit BMP files with a grayscale + * colormap can be loaded. + * - @ref TJPF_CMYK : The RGB or grayscale pixels stored in the file will be + * converted using a quick & dirty algorithm that is suitable only for testing + * purposes (proper conversion between CMYK and other formats requires a color + * management system.) + * - Other @ref TJPF "pixel formats" : The uncompressed image buffer will use + * the specified pixel format, and pixel format conversion will be performed if + * necessary. + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_BOTTOMUP + * "flags". + * + * @return a pointer to a newly-allocated buffer containing the uncompressed + * image, converted to the chosen pixel format and with the chosen row + * alignment, or NULL if an error occurred (see #tjGetErrorStr2().) This + * buffer should be freed using #tjFree(). + */ +DLLEXPORT unsigned char *tjLoadImage(const char *filename, int *width, + int align, int *height, int *pixelFormat, + int flags); + + +/** + * Save an uncompressed image from memory to disk. + * + * @param filename name of a file to which to save the uncompressed image. + * The image will be stored in Windows BMP or PBMPLUS (PPM/PGM) format, + * depending on the file extension. + * + * @param buffer pointer to an image buffer containing RGB, grayscale, or + * CMYK pixels to be saved + * + * @param width width (in pixels) of the uncompressed image + * + * @param pitch bytes per line in the image buffer. Setting this parameter to + * 0 is the equivalent of setting it to + * width * #tjPixelSize[pixelFormat]. + * + * @param height height (in pixels) of the uncompressed image + * + * @param pixelFormat pixel format of the image buffer (see @ref TJPF + * "Pixel formats".) If this parameter is set to @ref TJPF_GRAY, then the + * image will be stored in PGM or 8-bit (indexed color) BMP format. Otherwise, + * the image will be stored in PPM or 24-bit BMP format. If this parameter + * is set to @ref TJPF_CMYK, then the CMYK pixels will be converted to RGB + * using a quick & dirty algorithm that is suitable only for testing (proper + * conversion between CMYK and other formats requires a color management + * system.) + * + * @param flags the bitwise OR of one or more of the @ref TJFLAG_BOTTOMUP + * "flags". + * + * @return 0 if successful, or -1 if an error occurred (see #tjGetErrorStr2().) + */ +DLLEXPORT int tjSaveImage(const char *filename, unsigned char *buffer, + int width, int pitch, int height, int pixelFormat, + int flags); + + +/** + * Free an image buffer previously allocated by TurboJPEG. You should always + * use this function to free JPEG destination buffer(s) that were automatically + * (re)allocated by the compression and transform functions or that were + * manually allocated using #tjAlloc(). + * + * @param buffer address of the buffer to free + * + * @sa tjAlloc() + */ +DLLEXPORT void tjFree(unsigned char *buffer); + + +/** + * Returns a descriptive error message explaining why the last command failed. + * + * @param handle a handle to a TurboJPEG compressor, decompressor, or + * transformer instance, or NULL if the error was generated by a global + * function (but note that retrieving the error message for a global function + * is not thread-safe.) + * + * @return a descriptive error message explaining why the last command failed. + */ +DLLEXPORT char *tjGetErrorStr2(tjhandle handle); + + +/** + * Returns a code indicating the severity of the last error. See + * @ref TJERR "Error codes". + * + * @param handle a handle to a TurboJPEG compressor, decompressor or + * transformer instance + * + * @return a code indicating the severity of the last error. See + * @ref TJERR "Error codes". + */ +DLLEXPORT int tjGetErrorCode(tjhandle handle); + + +/* Deprecated functions and macros */ +#define TJFLAG_FORCEMMX 8 +#define TJFLAG_FORCESSE 16 +#define TJFLAG_FORCESSE2 32 +#define TJFLAG_FORCESSE3 128 + + +/* Backward compatibility functions and macros (nothing to see here) */ +#define NUMSUBOPT TJ_NUMSAMP +#define TJ_444 TJSAMP_444 +#define TJ_422 TJSAMP_422 +#define TJ_420 TJSAMP_420 +#define TJ_411 TJSAMP_420 +#define TJ_GRAYSCALE TJSAMP_GRAY + +#define TJ_BGR 1 +#define TJ_BOTTOMUP TJFLAG_BOTTOMUP +#define TJ_FORCEMMX TJFLAG_FORCEMMX +#define TJ_FORCESSE TJFLAG_FORCESSE +#define TJ_FORCESSE2 TJFLAG_FORCESSE2 +#define TJ_ALPHAFIRST 64 +#define TJ_FORCESSE3 TJFLAG_FORCESSE3 +#define TJ_FASTUPSAMPLE TJFLAG_FASTUPSAMPLE +#define TJ_YUV 512 + +DLLEXPORT unsigned long TJBUFSIZE(int width, int height); + +DLLEXPORT unsigned long TJBUFSIZEYUV(int width, int height, int jpegSubsamp); + +DLLEXPORT unsigned long tjBufSizeYUV(int width, int height, int subsamp); + +DLLEXPORT int tjCompress(tjhandle handle, unsigned char *srcBuf, int width, + int pitch, int height, int pixelSize, + unsigned char *dstBuf, unsigned long *compressedSize, + int jpegSubsamp, int jpegQual, int flags); + +DLLEXPORT int tjEncodeYUV(tjhandle handle, unsigned char *srcBuf, int width, + int pitch, int height, int pixelSize, + unsigned char *dstBuf, int subsamp, int flags); + +DLLEXPORT int tjEncodeYUV2(tjhandle handle, unsigned char *srcBuf, int width, + int pitch, int height, int pixelFormat, + unsigned char *dstBuf, int subsamp, int flags); + +DLLEXPORT int tjDecompressHeader(tjhandle handle, unsigned char *jpegBuf, + unsigned long jpegSize, int *width, + int *height); + +DLLEXPORT int tjDecompressHeader2(tjhandle handle, unsigned char *jpegBuf, + unsigned long jpegSize, int *width, + int *height, int *jpegSubsamp); + +DLLEXPORT int tjDecompress(tjhandle handle, unsigned char *jpegBuf, + unsigned long jpegSize, unsigned char *dstBuf, + int width, int pitch, int height, int pixelSize, + int flags); + +DLLEXPORT int tjDecompressToYUV(tjhandle handle, unsigned char *jpegBuf, + unsigned long jpegSize, unsigned char *dstBuf, + int flags); + +DLLEXPORT char *tjGetErrorStr(void); + + +/** + * @} + */ + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/3rdparty/turbojpeg/x86/bin/turbojpeg.dll b/3rdparty/turbojpeg/x86/bin/turbojpeg.dll new file mode 100644 index 00000000..fe5a1c85 Binary files /dev/null and b/3rdparty/turbojpeg/x86/bin/turbojpeg.dll differ diff --git a/3rdparty/turbojpeg/x86/lib/turbojpeg.lib b/3rdparty/turbojpeg/x86/lib/turbojpeg.lib new file mode 100644 index 00000000..3eca189b Binary files /dev/null and b/3rdparty/turbojpeg/x86/lib/turbojpeg.lib differ diff --git a/huagao/CAboutDlg.cpp b/huagao/CAboutDlg.cpp new file mode 100644 index 00000000..d7bfd205 --- /dev/null +++ b/huagao/CAboutDlg.cpp @@ -0,0 +1,46 @@ +// CAboutDlg.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CAboutDlg.h" +#include "afxdialogex.h" +#include "resource.h" + + +// CAboutDlg 对话框 + +IMPLEMENT_DYNAMIC(CAboutDlg, CDialogEx) + +CAboutDlg::CAboutDlg(CWnd* pParent /*=nullptr*/) + : CDialogEx(IDD_ABOUT, pParent) +{ + +} + +CAboutDlg::~CAboutDlg() +{ +} + +void CAboutDlg::DoDataExchange(CDataExchange* pDX) +{ + CDialogEx::DoDataExchange(pDX); +} + + +BEGIN_MESSAGE_MAP(CAboutDlg, CDialogEx) +END_MESSAGE_MAP() + + +// CAboutDlg 消息处理程序 + + +BOOL CAboutDlg::OnInitDialog() +{ + CDialogEx::OnInitDialog(); + + // TODO: 在此添加额外的初始化 + + SetDlgItemText(IDC_LBDERIVERVERSON, HG_VERSION_INFO); + return TRUE; // return TRUE unless you set the focus to a control + // 异常: OCX 属性页应返回 FALSE +} diff --git a/huagao/CAboutDlg.h b/huagao/CAboutDlg.h new file mode 100644 index 00000000..31e65aea --- /dev/null +++ b/huagao/CAboutDlg.h @@ -0,0 +1,25 @@ +#pragma once + + +// CAboutDlg 对话框 + +class CAboutDlg : public CDialogEx +{ + DECLARE_DYNAMIC(CAboutDlg) + +public: + CAboutDlg(CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CAboutDlg(); + +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_ABOUT }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + + DECLARE_MESSAGE_MAP() +public: + virtual BOOL OnInitDialog(); +}; diff --git a/huagao/CBasicPage.cpp b/huagao/CBasicPage.cpp new file mode 100644 index 00000000..8aeffe78 --- /dev/null +++ b/huagao/CBasicPage.cpp @@ -0,0 +1,181 @@ +// CBasicPage.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CBasicPage.h" +#include "afxdialogex.h" +#include "resource.h" +#include "CAboutDlg.h" +#include "CDiscardBlankSetting.h" +#include "Device/JsonConfig.h" +#include + +static std::vector colorModes = { + _T("24位彩色"), + _T("256级灰度"), + _T("黑白") +}; + +static std::vector surportStyles = { + _T("A3"), + _T("A4"), + _T("A4横向"), + _T("A5"), + _T("A5横向"), + _T("A6"), + _T("A6横向"), + _T("B4"), + _T("B5"), + _T("B5横向"), + _T("B6"), + _T("B6横向"), + _T("Letter"), + _T("Letter横向"), + _T("Double Letter"), + _T("LEGAL"), + _T("匹配原始尺寸"), + _T("最大扫描尺寸自动裁切"), + _T("最大扫描尺寸"), +}; + +static std::vector reslutions{ + _T("100"), + _T("150"), + _T("200"), + _T("240"), + _T("300") +}; + +static std::vector duplexs +{ + _T("单面"), + _T("双面"), + _T("跳过空白页(通用)"), + _T("跳过空白页(发票纸)") +}; + + +// CBasicPage 对话框 + +IMPLEMENT_DYNAMIC(CBasicPage, CTabPageSSL) + +CBasicPage::CBasicPage(std::function dataChange, CWnd* pParent /*=nullptr*/) + : CTabPageSSL(IDD_PAGEBASIC, pParent) + , m_dataChange(dataChange) + , AreaNum(8) + , DevnMax(200) +{ + +} + +CBasicPage::~CBasicPage() +{ +} + +void CBasicPage::DoDataExchange(CDataExchange* pDX) +{ + CTabPageSSL::DoDataExchange(pDX); +} + +BOOL CBasicPage::OnInitDialog() +{ + CTabPageSSL::OnInitDialog(); + m_cmBoxColorMode = (CComboBox*)GetDlgItem(IDC_CMBCOLORTYPE); + m_cmBoxSS = (CComboBox*)GetDlgItem(IDC_CMBSS); + m_cmBoxResultion = (CComboBox*)GetDlgItem(IDC_CMBRESLUTION); + m_cmBoxDuplex = (CComboBox*)GetDlgItem(IDC_CMBDUPLEX); + + for (const CString& colorMode : colorModes) + m_cmBoxColorMode->AddString(colorMode); + + + for (int i = 0; i < surportStyles.size(); i++) + m_cmBoxSS->InsertString(i, surportStyles[i]); + + for (const CString& reslution : reslutions) + m_cmBoxResultion->AddString(reslution); + + for (int i = 0; i < duplexs.size(); i++) + m_cmBoxDuplex->InsertString(i,duplexs[i]); + + + m_cmBoxResultion->SetCurSel(0); + m_cmBoxSS->SetCurSel(0); + m_cmBoxColorMode->SetCurSel(0); + m_cmBoxDuplex->SetCurSel(0); + + return true; +} + + +BEGIN_MESSAGE_MAP(CBasicPage, CTabPageSSL) + ON_BN_CLICKED(IDC_BTNABOUT, &CBasicPage::OnBnClickedBtnabout) + ON_CBN_SELCHANGE(IDC_CMBCOLORTYPE, &CBasicPage::OnCbnSelchangeCmbcolortype) + ON_CBN_SELCHANGE(IDC_CMBSS, &CBasicPage::OnCbnSelchangeCmbss) + ON_CBN_SELCHANGE(IDC_CMBRESLUTION, &CBasicPage::OnCbnSelchangeCmbreslution) + ON_CBN_SELCHANGE(IDC_CMBDUPLEX, &CBasicPage::OnCbnSelchangeCmbduplex) + ON_BN_CLICKED(IDC_BTNDISCARDSETTING, &CBasicPage::OnClickedBtndiscardsetting) +END_MESSAGE_MAP() + + +// CBasicPage 消息处理程序 + + +void CBasicPage::OnBnClickedBtnabout() +{ + // TODO: 在此添加控件通知处理程序代码 + CAboutDlg dlg; + dlg.DoModal(); + +} + + +void CBasicPage::OnCbnSelchangeCmbcolortype() +{ + // TODO: 在此添加控件通知处理程序代码 + m_dataChange(); +} + + +void CBasicPage::OnCbnSelchangeCmbss() +{ + // TODO: 在此添加控件通知处理程序代码 + int sleIndex = m_cmBoxSS->GetCurSel(); + if (sleIndex == -1) + { + sleIndex = 0; + } + + m_dataChange(); +} + + +void CBasicPage::OnCbnSelchangeCmbreslution() +{ + // TODO: 在此添加控件通知处理程序代码 +} + + +void CBasicPage::OnCbnSelchangeCmbduplex() +{ + // TODO: 在此添加控件通知处理程序代码 + int index = m_cmBoxDuplex->GetCurSel(); + if (index > 1) { + //AreaNum = index == 2? 8 : 20 ; + //DevnMax = index == 2 ? 200 : 300; + m_dataChange(); + } +} + +//跳过空白页设置页面 +void CBasicPage::OnClickedBtndiscardsetting() +{ + // TODO: 在此添加控件通知处理程序代码 + //JsonConfig jc; + //CONFIGPARAMS params = jc.ReadDefaultConfig(); + //CDiscardBlankSetting dbs(this, params.DBlank_AreaNum, params.DBlank_DevnMax); + //int nRet = dbs.DoModal(); + //if (nRet == IDOK) { + // dbs.GetParams(AreaNum, DevnMax); + //} +} diff --git a/huagao/CBasicPage.h b/huagao/CBasicPage.h new file mode 100644 index 00000000..33f0c710 --- /dev/null +++ b/huagao/CBasicPage.h @@ -0,0 +1,45 @@ +#pragma once +#include "TabPageSSL.h" +#include "twglue.hpp" +#include + +// CBasicPage 对话框 + +class CBasicPage : public CTabPageSSL +{ + DECLARE_DYNAMIC(CBasicPage) + +public: + CBasicPage(std::function dataChange, CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CBasicPage(); + + CComboBox* m_cmBoxColorMode; + CComboBox* m_cmBoxSS; + CComboBox* m_cmBoxResultion; + CComboBox* m_cmBoxDuplex; + + afx_msg void OnBnClickedBtnabout(); + afx_msg void OnCbnSelchangeCmbcolortype(); + afx_msg void OnCbnSelchangeCmbss(); + afx_msg void OnCbnSelchangeCmbreslution(); + afx_msg void OnCbnSelchangeCmbduplex(); + +public: + int AreaNum; + int DevnMax; + +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_PAGEBASIC }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + + DECLARE_MESSAGE_MAP() + + std::function m_dataChange; +public: + afx_msg void OnClickedBtndiscardsetting(); +}; diff --git a/huagao/CBrightnessPage.cpp b/huagao/CBrightnessPage.cpp new file mode 100644 index 00000000..c1adabe9 --- /dev/null +++ b/huagao/CBrightnessPage.cpp @@ -0,0 +1,60 @@ +// CBrightnessPage.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CBrightnessPage.h" +#include "afxdialogex.h" +#include "resource.h" + + +// CBrightnessPage 对话框 + +IMPLEMENT_DYNAMIC(CBrightnessPage, CTabPageSSL) + +CBrightnessPage::CBrightnessPage(CWnd* pParent /*=nullptr*/) + : CTabPageSSL(IDD_PAGEBRIGHTNESS, pParent) + , m_cbAutoContrast(FALSE) +{ + +} + +CBrightnessPage::~CBrightnessPage() +{ +} + +void CBrightnessPage::DoDataExchange(CDataExchange* pDX) +{ + CTabPageSSL::DoDataExchange(pDX); + DDX_Control(pDX, IDC_EDIT_BRIGHTNESS, m_Edit_Brightness); + DDX_Control(pDX, IDC_EDIT_CONSTRAST, m_Edit_Contrast); + DDX_Control(pDX, IDC_EDIT_GAMMA, m_Edit_Gamma); + DDX_Control(pDX, IDC_SLIDER_BRIGTHNESS, m_Slider_Brightness); + DDX_Control(pDX, IDC_SLIDER_CONTRAST, m_Slider_Contrast); + DDX_Control(pDX, IDC_SLIDER_GAMMA, m_Slider_Gamma); + DDX_Check(pDX, IDC_CHKSELFCONTRAST, m_cbAutoContrast); +} + +BOOL CBrightnessPage::OnInitDialog() +{ + CTabPageSSL::OnInitDialog(); + m_Edit_Brightness.SetSlideLink(this, IDC_SLIDER_BRIGTHNESS); + m_Edit_Brightness.SetParams(1, 255, 15); + m_Edit_Brightness.SetValue(128); + + m_Edit_Contrast.SetSlideLink(this, IDC_SLIDER_CONTRAST); + m_Edit_Contrast.SetParams(1, 7, 6); + m_Edit_Contrast.SetValue(4); + + // setup third slider-edit box - floating point + m_Edit_Gamma.SetSlideLink(this, IDC_SLIDER_GAMMA); + m_Edit_Gamma.SetParams(0.01, 5.0, 10, _T("%0.2f")); + m_Edit_Gamma.SetValue(1.0); + return true; +} + + +BEGIN_MESSAGE_MAP(CBrightnessPage, CTabPageSSL) +END_MESSAGE_MAP() + + +// CBrightnessPage 消息处理程序 diff --git a/huagao/CBrightnessPage.h b/huagao/CBrightnessPage.h new file mode 100644 index 00000000..a0dcc58b --- /dev/null +++ b/huagao/CBrightnessPage.h @@ -0,0 +1,36 @@ +#pragma once +#include "TabPageSSL.h" +#include "Sliders.h" +#include "SmartEdit.h" + + +// CBrightnessPage 对话框 + +class CBrightnessPage : public CTabPageSSL +{ + DECLARE_DYNAMIC(CBrightnessPage) + +public: + CBrightnessPage(CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CBrightnessPage(); + + CSmartEdit m_Edit_Brightness; + CSmartEdit m_Edit_Contrast; + CSmartEdit m_Edit_Gamma; + CLinkSlider m_Slider_Brightness; + CLinkSlider m_Slider_Contrast; + CLinkSlider m_Slider_Gamma; + BOOL m_cbAutoContrast; + +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_PAGEBRIGHTNESS }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + + DECLARE_MESSAGE_MAP() + +}; diff --git a/huagao/CDiscardBlankSetting.cpp b/huagao/CDiscardBlankSetting.cpp new file mode 100644 index 00000000..60826b05 --- /dev/null +++ b/huagao/CDiscardBlankSetting.cpp @@ -0,0 +1,69 @@ +// CDiscardBlankSetting.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CDiscardBlankSetting.h" +#include "afxdialogex.h" + + +// CDiscardBlankSetting 对话框 + +IMPLEMENT_DYNAMIC(CDiscardBlankSetting, CDialogEx) + +CDiscardBlankSetting::CDiscardBlankSetting(CWnd* pParent /*=nullptr*/, int areanum, int devnmax) + : CDialogEx(IDD_DISCARDBLANKSETTING, pParent) +{ + areaNum = areanum; + devnMax = devnmax; +} + +CDiscardBlankSetting::~CDiscardBlankSetting() +{ +} + +void CDiscardBlankSetting::GetParams(int& areaNum, int& devnMax) +{ + areaNum =this->areaNum; + devnMax =this->devnMax; +} + +void CDiscardBlankSetting::DoDataExchange(CDataExchange* pDX) +{ + CDialogEx::DoDataExchange(pDX); + DDX_Control(pDX, IDC_SLD_AREANUM, m_Slider_AreaNum); + DDX_Control(pDX, IDC_SLD_DEVNMAX, m_Slider_DevnMax); + DDX_Control(pDX, IDC_DBLANK_AREANUM, m_Edit_AreaNum); + DDX_Control(pDX, IDC_DBLANK_DEVNMAX, m_Edit_DevnMax); +} + +BOOL CDiscardBlankSetting::OnInitDialog() +{ + CDialogEx::OnInitDialog(); + m_Edit_AreaNum.SetSlideLink(this, IDC_SLD_AREANUM); + m_Edit_AreaNum.SetParams(6, 39, 11); + m_Edit_AreaNum.SetValue(areaNum); + + m_Edit_DevnMax.SetSlideLink(this, IDC_SLD_DEVNMAX); + m_Edit_DevnMax.SetParams(150, 400, 25); + m_Edit_DevnMax.SetValue(devnMax); + return TRUE; +} + + +BEGIN_MESSAGE_MAP(CDiscardBlankSetting, CDialogEx) +END_MESSAGE_MAP() + + +// CDiscardBlankSetting 消息处理程序 + + +BOOL CDiscardBlankSetting::DestroyWindow() +{ + // TODO: 在此添加专用代码和/或调用基类 + CString strAreaNum, strDevnMax; + GetDlgItemText(IDC_DBLANK_AREANUM, strAreaNum); + areaNum = _ttoi(strAreaNum); + GetDlgItemText(IDC_DBLANK_DEVNMAX, strDevnMax); + devnMax = _ttoi(strDevnMax); + return CDialogEx::DestroyWindow(); +} diff --git a/huagao/CDiscardBlankSetting.h b/huagao/CDiscardBlankSetting.h new file mode 100644 index 00000000..8260986a --- /dev/null +++ b/huagao/CDiscardBlankSetting.h @@ -0,0 +1,34 @@ +#pragma once +#include "Resource.h" +#include "SmartEdit.h" +#include "Sliders.h" +// CDiscardBlankSetting 对话框 + +class CDiscardBlankSetting : public CDialogEx +{ + DECLARE_DYNAMIC(CDiscardBlankSetting) + +public: + CDiscardBlankSetting(CWnd* pParent = nullptr,int areanum=8,int devnmax=200); // 标准构造函数 + virtual ~CDiscardBlankSetting(); +public: + void GetParams(int& areaNum, int& devnMax); +private: + CSmartEdit m_Edit_AreaNum; + CSmartEdit m_Edit_DevnMax; + CLinkSlider m_Slider_AreaNum; + CLinkSlider m_Slider_DevnMax; + int areaNum; + int devnMax; +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_DISCARDBLANKSETTING }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + DECLARE_MESSAGE_MAP() +public: + virtual BOOL DestroyWindow(); +}; diff --git a/huagao/CFeedPaperPage.cpp b/huagao/CFeedPaperPage.cpp new file mode 100644 index 00000000..596f654f --- /dev/null +++ b/huagao/CFeedPaperPage.cpp @@ -0,0 +1,126 @@ +// CFeedPaperPage.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CFeedPaperPage.h" +#include "afxdialogex.h" +#include "resource.h" + + + +// CFeedPaperPage 对话框 + +IMPLEMENT_DYNAMIC(CFeedPaperPage, CTabPageSSL) + +CFeedPaperPage::CFeedPaperPage(CWnd* pParent /*=nullptr*/) + : CTabPageSSL(IDD_PAGEFEEDPAPER, pParent) + , m_radioGroupScanMode(0) + , m_cbDoublePaper(FALSE) + , m_cbStaple(FALSE) + , m_cbRotation(FALSE) + , m_cbSkew(FALSE) +{ + +} + +CFeedPaperPage::~CFeedPaperPage() +{ +} + +void CFeedPaperPage::DoDataExchange(CDataExchange* pDX) +{ + CTabPageSSL::DoDataExchange(pDX); + DDX_Radio(pDX, IDC_RDCONSISTSCAN, m_radioGroupScanMode); + DDX_Check(pDX, IDC_CKULTRSONICDETECT, m_cbDoublePaper); + DDX_Check(pDX, IDC_CKBINDINGDETECT, m_cbStaple); + DDX_Check(pDX, IDC_CKBACKROTATION, m_cbRotation); + DDX_Check(pDX, IDC_CKSKEWDETECT, m_cbSkew); + DDX_Control(pDX, IDC_CMBORENTATION, m_cmBoxOrentation); + DDX_Control(pDX, IDC_SLDDETECTLEVEL, m_sldSkrewDetecttion); + DDX_Control(pDX, IDC_EDSCANNUM, m_editNum); +} + +BOOL CFeedPaperPage::OnInitDialog() +{ + CTabPageSSL::OnInitDialog(); + + m_radioGroupScanMode = 0; + + OnInitcmBoxOrentation(0); + m_sldSkrewDetecttion.SetSlideRange(1, 5); + m_sldSkrewDetecttion.SetSlidePos(3); + return true; +} + + + +BEGIN_MESSAGE_MAP(CFeedPaperPage, CTabPageSSL) + ON_BN_CLICKED(IDC_RDCONSISTSCAN, &CFeedPaperPage::OnBnClickedScanMode) + ON_BN_CLICKED(IDC_RDSPECIFYSCANNUM, &CFeedPaperPage::OnBnClickedScanMode) + ON_BN_CLICKED(IDC_CKSKEWDETECT, &CFeedPaperPage::OnBnClickedCkskewdetect) +END_MESSAGE_MAP() + +BOOL CFeedPaperPage::PreTranslateMessage(MSG* pMsg) +{ + // TODO: 在此添加专用代码和/或调用基类 + if (pMsg->message == WM_CHAR) + { + CEdit* pEdit = (CEdit*)GetDlgItem(IDC_EDSCANNUM); + if (pMsg->hwnd == pEdit->m_hWnd) + { + CString strText; + pEdit->GetWindowText(strText); + int length = strText.GetLength(); + if ((pMsg->wParam >= '0' && pMsg->wParam <= '9' || pMsg->wParam == '\b')) + return CDialog::PreTranslateMessage(pMsg); + else + return true; + } + } + return CDialog::PreTranslateMessage(pMsg); +} + +// CFeedPaperPage 消息处理程序 +void CFeedPaperPage::OnBnClickedScanMode() +{ + UpdateData(TRUE); + CButton* m_tempBtn = ((CButton*)GetDlgItem(IDC_RDCONSISTSCAN)); + m_editNum.SetWindowText(m_tempBtn->GetCheck()==TRUE?_T("-1"):_T("1")); + m_editNum.EnableWindow(m_radioGroupScanMode); +} + +void CFeedPaperPage::FeedPaperPageUpdate(int val) +{ + CButton* m_tempBtn = (CButton*)(GetDlgItem(IDC_CKBACKROTATION)); + int ival = (val == 3 ? 2 : (val == 0 ? 0 : 1)); + m_tempBtn->SetCheck(0); + m_tempBtn->EnableWindow(ival != 0); +} + +void CFeedPaperPage::FeedAutoDescrewUpdate(int val) +{ + CComboBox* m_temp = (CComboBox*)(GetDlgItem(IDC_CMBORENTATION)); + if (16 == val) + { + m_temp->SetCurSel(4); + } +} + +void CFeedPaperPage::OnInitcmBoxOrentation(int selectIndex) +{ + m_cmBoxOrentation.InsertString(0, _T("0°")); + m_cmBoxOrentation.InsertString(1, _T("90°")); + m_cmBoxOrentation.InsertString(2, _T("180°")); + m_cmBoxOrentation.InsertString(3, _T("-90°")); + m_cmBoxOrentation.InsertString(4, _T("自动文本方向识别°")); + m_cmBoxOrentation.SetCurSel(selectIndex); +} + +void CFeedPaperPage::OnBnClickedCkskewdetect() +{ + // TODO: 在此添加控件通知处理程序代码 + UpdateData(TRUE); + if (m_cbSkew != 1) + m_sldSkrewDetecttion.SetPos(3); + m_sldSkrewDetecttion.EnableWindow(m_cbSkew); +} diff --git a/huagao/CFeedPaperPage.h b/huagao/CFeedPaperPage.h new file mode 100644 index 00000000..33b378da --- /dev/null +++ b/huagao/CFeedPaperPage.h @@ -0,0 +1,47 @@ +#pragma once +#include "TabPageSSL.h" +#include "Sliders.h" +#include "SmartEdit.h" + +// CFeedPaperPage 对话框 + +class CFeedPaperPage : public CTabPageSSL +{ + DECLARE_DYNAMIC(CFeedPaperPage) + +public: + CFeedPaperPage(CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CFeedPaperPage(); + + void FeedPaperPageUpdate(int val); + void FeedAutoDescrewUpdate(int val); + void OnInitcmBoxOrentation(int selectIndex); + + BOOL m_cbDoublePaper; + BOOL m_cbStaple; + BOOL m_cbRotation; + BOOL m_cbSkew; + CComboBox m_cmBoxOrentation; + CLinkSlider m_sldSkrewDetecttion; + int m_radioGroupScanMode; + CSmartEdit m_editNum; + + afx_msg void OnBnClickedCkskewdetect(); + afx_msg void OnBnClickedScanMode(); + +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_PAGEFEEDPAPER }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + + DECLARE_MESSAGE_MAP() + +private: + virtual BOOL PreTranslateMessage(MSG* pMsg); + + +}; diff --git a/huagao/CImageProcPage.cpp b/huagao/CImageProcPage.cpp new file mode 100644 index 00000000..b190a2f6 --- /dev/null +++ b/huagao/CImageProcPage.cpp @@ -0,0 +1,163 @@ +// CImageProcPage.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CImageProcPage.h" +#include "afxdialogex.h" +#include "resource.h" +#include + + + +static std::vector filters = { + _T("不除色"), + _T("除红色"), + _T("除绿色"), + _T("除蓝色"), + _T("红色增强"), + _T("绿色增强"), + _T("蓝色增强") +}; + +static std::vector sharpens = { + _T("无"), + _T("锐化"), + _T("进一步锐化"), + _T("模糊"), + _T("进一步模糊") +}; +// CImageProcPage 对话框 + +IMPLEMENT_DYNAMIC(CImageProcPage, CTabPageSSL) + +CImageProcPage::CImageProcPage(CWnd* pParent /*=nullptr*/) + : CTabPageSSL(IDD_PAGEIMGPROC, pParent) + , m_ckbFillBlack(FALSE) + , m_ckbAutoDeskrew(FALSE) + , m_ckbMultioutput(FALSE) + , m_ckbRemoveHole(FALSE) +{ + +} + +CImageProcPage::~CImageProcPage() +{ +} + +void CImageProcPage::ImageProcPageUpdate(int val) +{ + CComboBox* m_temp = (CComboBox*)(GetDlgItem(IDC_CMBFILTER)); + CButton* t_chMultiOutput = (CButton*)(GetDlgItem(IDC_CKMULTIOUTPUT)); + CComboBox* m_temp_sharpen = (CComboBox*)(GetDlgItem(IDC_CMBSHARPEN)); + + int ival = (val == 0 ? 0 : (val == 1 ? 1 : 2)); + + + if (0 == ival)//彩色 + { + m_temp->SetCurSel(0); + m_temp->EnableWindow(FALSE); + t_chMultiOutput->SetCheck(FALSE); + t_chMultiOutput->EnableWindow(TRUE); + } + else + { + m_temp->SetCurSel(0); + m_temp->EnableWindow(TRUE); + t_chMultiOutput->SetCheck(FALSE); + t_chMultiOutput->EnableWindow(FALSE); + } + + bool enabele = ival <= 1; + m_temp_sharpen->SetCurSel(enabele?0:0); + m_temp_sharpen->EnableWindow(enabele); +} + +void CImageProcPage::ImageAutoDescrewUpdate(int val) +{ + //CButton* t_chAutoDeskrew = (CButton*)(GetDlgItem(IDC_CKAUTODESKREW)); + + //if (16 == val) + //{ + // t_chAutoDeskrew->SetCheck(TRUE); + //} +} + +void CImageProcPage::DoDataExchange(CDataExchange* pDX) +{ + CTabPageSSL::DoDataExchange(pDX); + DDX_Control(pDX, IDC_SLDOUTHOLE, m_slider_hole); + DDX_Control(pDX, IDC_EDIT_HOLE, m_edit_hole); + DDX_Control(pDX, IDC_CMBFILTER, m_cmBoxFilter); + DDX_Control(pDX, IDC_CMBSHARPEN, m_cmBoxSharpen); + DDX_Check(pDX, IDC_CKFILLBLACKRECT, m_ckbFillBlack); + DDX_Check(pDX, IDC_CKAUTODESKREW, m_ckbAutoDeskrew); + DDX_Check(pDX, IDC_CKMULTIOUTPUT, m_ckbMultioutput); + DDX_Check(pDX, IDC_CKREMOVEHOLE, m_ckbRemoveHole); +} + +BOOL CImageProcPage::OnInitDialog() +{ + CTabPageSSL::OnInitDialog(); + m_edit_hole.SetSlideLink(this, IDC_SLDOUTHOLE); + m_edit_hole.SetParams(0.01, 0.50, 10, _T("%0.2f")); + m_edit_hole.SetValue(0.10); + + for (int i = 0; i < filters.size(); i++) + { + m_cmBoxFilter.InsertString(i, filters[i]); + } + + for (int i = 0; i < sharpens.size(); i++) + { + m_cmBoxSharpen.InsertString(i, sharpens[i]); + } + + return true; +} + + +BEGIN_MESSAGE_MAP(CImageProcPage, CTabPageSSL) + ON_BN_CLICKED(IDC_CKREMOVEHOLE, &CImageProcPage::OnCtrlChange) +END_MESSAGE_MAP() + +void CImageProcPage::EnableOutHoleCheckChanged(BOOL enable) +{ + UpdateData(); + ((CButton*)GetDlgItem(IDC_EDIT_HOLE))->SetCheck(enable); + GetDlgItem(IDC_EDIT_HOLE)->EnableWindow(enable); + GetDlgItem(IDC_SLDOUTHOLE)->EnableWindow(enable); + GetDlgItem(IDC_EDIT_HOLE)->EnableWindow(enable); +} + +void CImageProcPage::SetOutHoleValue(int value) +{ + m_edit_hole.SetValue(value); +} + +void CImageProcPage::SetMultiOutputEnable(int pixtype, bool enable) +{ + switch (pixtype) + { + case 2://彩色 + ((CButton*)GetDlgItem(IDC_CKMULTIOUTPUT))->SetCheck(enable); + ((CButton*)GetDlgItem(IDC_CKMULTIOUTPUT))->EnableWindow(TRUE); + break; + case 0://灰度 黑白 + case 1: + ((CButton*)GetDlgItem(IDC_CKMULTIOUTPUT))->SetCheck(FALSE); + ((CButton*)GetDlgItem(IDC_CKMULTIOUTPUT))->EnableWindow(FALSE); + break; + default: + break; + } +} + + +void CImageProcPage::OnCtrlChange() +{ + // TODO: 在此添加控件通知处理程序代码 + UpdateData(); + m_edit_hole.EnableWindow(m_ckbRemoveHole); + m_slider_hole.EnableWindow(m_ckbRemoveHole); +} diff --git a/huagao/CImageProcPage.h b/huagao/CImageProcPage.h new file mode 100644 index 00000000..b7621126 --- /dev/null +++ b/huagao/CImageProcPage.h @@ -0,0 +1,42 @@ +#pragma once +#include "TabPageSSL.h" +#include "Sliders.h" +#include "SmartEdit.h" + +// CImageProcPage 对话框 + +class CImageProcPage : public CTabPageSSL +{ + DECLARE_DYNAMIC(CImageProcPage) + +public: + CImageProcPage(CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CImageProcPage(); + + CLinkSlider m_slider_hole; + CSmartEdit m_edit_hole; + CComboBox m_cmBoxFilter; + CComboBox m_cmBoxSharpen; + BOOL m_ckbFillBlack; + BOOL m_ckbAutoDeskrew; + BOOL m_ckbMultioutput; + BOOL m_ckbRemoveHole; + + void ImageProcPageUpdate(int val); + void ImageAutoDescrewUpdate(int val); + void EnableOutHoleCheckChanged(BOOL enable); + void SetOutHoleValue(int value); + void SetMultiOutputEnable(int pixtype, bool enable); +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_PAGEIMGPROC }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + + DECLARE_MESSAGE_MAP() + + afx_msg void OnCtrlChange(); +}; diff --git a/huagao/CIndicatorDlg.cpp b/huagao/CIndicatorDlg.cpp new file mode 100644 index 00000000..7500d1a2 --- /dev/null +++ b/huagao/CIndicatorDlg.cpp @@ -0,0 +1,44 @@ +// CIndicatorDlg.cpp: 实现文件 +// + +#include "stdafx.h" +#include "CIndicatorDlg.h" +#include "afxdialogex.h" +#include "resource.h" + + +// CIndicatorDlg 对话框 + +IMPLEMENT_DYNAMIC(CIndicatorDlg, CDialogEx) + +CIndicatorDlg::CIndicatorDlg(std::function stop, CWnd* pParent /*=nullptr*/) + : CDialogEx(IDD_INDICATOR, pParent) + , m_stop(stop) +{ + +} + +CIndicatorDlg::~CIndicatorDlg() +{ +} + +void CIndicatorDlg::DoDataExchange(CDataExchange* pDX) +{ + CDialogEx::DoDataExchange(pDX); +} + + +BEGIN_MESSAGE_MAP(CIndicatorDlg, CDialogEx) + ON_BN_CLICKED(IDC_BTNSTOPSCAN, &CIndicatorDlg::OnBnClickedBtnstopscan) +END_MESSAGE_MAP() + + +// CIndicatorDlg 消息处理程序 + + +void CIndicatorDlg::OnBnClickedBtnstopscan() +{ + // TODO: 在此添加控件通知处理程序代码 + if (m_stop) + m_stop(); +} diff --git a/huagao/CIndicatorDlg.h b/huagao/CIndicatorDlg.h new file mode 100644 index 00000000..017d1cd9 --- /dev/null +++ b/huagao/CIndicatorDlg.h @@ -0,0 +1,28 @@ +#pragma once +#include + + +// CIndicatorDlg 对话框 + +class CIndicatorDlg : public CDialogEx +{ + DECLARE_DYNAMIC(CIndicatorDlg) + +public: + CIndicatorDlg(std::function stop = std::function(), CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CIndicatorDlg(); + +// 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_INDICATOR }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + + DECLARE_MESSAGE_MAP() + + afx_msg void OnBnClickedBtnstopscan(); + + std::function m_stop; +}; diff --git a/huagao/CSaveConfigDlg.cpp b/huagao/CSaveConfigDlg.cpp new file mode 100644 index 00000000..7ebf20cc --- /dev/null +++ b/huagao/CSaveConfigDlg.cpp @@ -0,0 +1,96 @@ +// CSaveConfigDlg.cpp : 实现文件 +// + +#include "stdafx.h" +#include "CSaveConfigDlg.h" +#include "CTwainUI.h" +#include + + +// CSaveConfigDlg 对话框 + +IMPLEMENT_DYNAMIC(CSaveConfigDlg, CDialog) + +CSaveConfigDlg::CSaveConfigDlg(CWnd* pParent /*=NULL*/) + : CDialog(IDD_SAVECONFIG, pParent) +{ + +} + +CSaveConfigDlg::~CSaveConfigDlg() +{ +} + +void CSaveConfigDlg::DoDataExchange(CDataExchange* pDX) +{ + CDialog::DoDataExchange(pDX); +} + + +BEGIN_MESSAGE_MAP(CSaveConfigDlg, CDialog) + ON_BN_CLICKED(IDOK, &CSaveConfigDlg::OnBnClickedOk) +END_MESSAGE_MAP() + + +// CSaveConfigDlg 消息处理程序 +std::string TCHAR2STRING2(TCHAR* STR) +{ + int iLen = WideCharToMultiByte(CP_ACP, 0, STR, -1, NULL, 0, NULL, NULL); + char* chRtn = new char[iLen * sizeof(char)]; + WideCharToMultiByte(CP_ACP, 0, STR, -1, chRtn, iLen, NULL, NULL); + std::string str(chRtn); + return str; +} + +void CSaveConfigDlg::OnBnClickedOk() +{ + CTwainUI* m_Parent=(CTwainUI*)GetParent(); + CONFIGPARAMS citem={0}; + m_Parent->UpDateScanParam(&citem,false); + CString m_sName; + GetDlgItemText(IDC_EDITSAVENAME,m_sName); + TCHAR szIniFile[MAX_PATH] = { 0 }; + INT length=m_sName.GetLength(); + //INT length=10; + if (length>0&&length<50) + { + char invalid_FileChars[8]={'/','\\',':','*',' ?','<', '>','|'}; + for(short j=0;j<8;j++) + { + m_sName.Remove(invalid_FileChars[j]); + } + if (m_sName.IsEmpty()) + { + MessageBox(_TEXT("请避免输入非法字符('/','\\',':','*',' ?','<', '>','|')!"),_TEXT("提示"),MB_OK|MB_ICONWARNING); + return; + } + SHGetSpecialFolderPath(NULL, szIniFile, CSIDL_LOCAL_APPDATA, TRUE); + _tcscat(szIniFile,HUAGAO_SCAN); + _tcscat(szIniFile, TWAIN_DATA_PATH); + _tcscat(szIniFile, _T("\\")); + std::string dirpath = TCHAR2STRING2(szIniFile); + bool is_exist = isFolderExist((char*)dirpath.c_str()); + if (!is_exist) { + createDirectory((char*)dirpath.c_str()); + } + citem.Caption = (CW2A)m_sName; + _tcscat(szIniFile,m_sName+_TEXT(".json")); + std::string s_savePath = TCHAR2STRING2(szIniFile); + citem.SavePath=s_savePath; + JsonConfig cfg; + cfg.WriteToJson(&citem,s_savePath,true); + m_Parent->UpdateListConfig(); + CDialog::OnOK(); + } + else + { + if (length==0) + { + MessageBox(_TEXT("请输入保存项名称"),_TEXT("提示")); + } + else + { + MessageBox(_TEXT("最多只允许输入50个字符,请重新输入"),_TEXT("提示")); + } + } +} diff --git a/huagao/CSaveConfigDlg.h b/huagao/CSaveConfigDlg.h new file mode 100644 index 00000000..d88cc03d --- /dev/null +++ b/huagao/CSaveConfigDlg.h @@ -0,0 +1,27 @@ +#pragma once +#include "Resource.h" +// SaveConfigDlg Ի + +class CSaveConfigDlg : public CDialog +{ + DECLARE_DYNAMIC(CSaveConfigDlg) + +public: + CSaveConfigDlg(CWnd* pParent = nullptr); // ׼캯 + virtual ~CSaveConfigDlg(); + +// Ի +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_SAVECONFIG }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV ֧ + + DECLARE_MESSAGE_MAP() +public: + afx_msg void OnBnClickedOk(); + +private: + CWnd* m_Parent; +}; diff --git a/huagao/CTiffWriter.cpp b/huagao/CTiffWriter.cpp new file mode 100644 index 00000000..cb7689bc --- /dev/null +++ b/huagao/CTiffWriter.cpp @@ -0,0 +1,288 @@ +/*************************************************************************** +* Copyright ?2007 TWAIN Working Group: +* Adobe Systems Incorporated, AnyDoc Software Inc., Eastman Kodak Company, +* Fujitsu Computer Products of America, JFL Peripheral Solutions Inc., +* Ricoh Corporation, and Xerox Corporation. +* All rights reserved. +* +* Redistribution and use in source and binary forms, with or without +* modification, are permitted provided that the following conditions are met: +* * Redistributions of source code must retain the above copyright +* notice, this list of conditions and the following disclaimer. +* * Redistributions in binary form must reproduce the above copyright +* notice, this list of conditions and the following disclaimer in the +* documentation and/or other materials provided with the distribution. +* * Neither the name of the TWAIN Working Group nor the +* names of its contributors may be used to endorse or promote products +* derived from this software without specific prior written permission. +* +* THIS SOFTWARE IS PROVIDED BY TWAIN Working Group ``AS IS'' AND ANY +* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +* DISCLAIMED. IN NO EVENT SHALL TWAIN Working Group BE LIABLE FOR ANY +* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +* +***************************************************************************/ + +/** + * @file CTiffWriter.cpp + * Write an image to disk as a tiff file. + * @author JFL Peripheral Solutions Inc. + * @date October 2007 + */ + +#include "stdafx.h" +#include "CTiffWriter.h" +#include + +CTiffWriter::CTiffWriter(const string& _filename, + const long int _width, + const long int _height, + const int _bitsPerPixel, + const unsigned long int _bytesPerRow) +{ + m_pImageStream = 0; + m_nOffset = 0; + m_filename = _filename; + + m_ImageWidth.TagID = kTIFF_TAG_IMGWIDTH; + m_ImageWidth.DataType = kTIFF_TY_LONG; + m_ImageWidth.DataCount = 1; + m_ImageWidth.DataOffset = _width; + + m_ImageLength.TagID = kTIFF_TAG_IMGLENGTH; + m_ImageLength.DataType = kTIFF_TY_LONG; + m_ImageLength.DataCount = 1; + m_ImageLength.DataOffset = _height; + + m_BitsPerSample.TagID = kTIFF_TAG_BITSPERSAMPLE; + m_BitsPerSample.DataType = kTIFF_TY_SHORT; + m_BitsPerSample.DataCount = 1; + + if(24 == _bitsPerPixel) + { + m_BitsPerSample.DataOffset = 8; + } + else + { + m_BitsPerSample.DataOffset = _bitsPerPixel; + } + + + m_Compression.TagID = kTIFF_TAG_COMPRESSION; + m_Compression.DataType = kTIFF_TY_SHORT; + m_Compression.DataCount = 1; + m_Compression.DataOffset = 1; + + m_PhotometricInterp.TagID = kTIFF_TAG_PHOTOMETRICINT; + m_PhotometricInterp.DataType = kTIFF_TY_SHORT; + m_PhotometricInterp.DataCount = 1; + + if(24 == _bitsPerPixel) + { + m_PhotometricInterp.DataOffset = 2; + } + else + { + m_PhotometricInterp.DataOffset = 1; + } + + // -there is only one strip that contains all the row data, and it starts right after the header. + // -There are always 12 tags being written for each tiff. + m_StripOffsets.TagID = kTIFF_TAG_STRIPOFFSETS; + m_StripOffsets.DataType = kTIFF_TY_SHORT; + m_StripOffsets.DataCount = 1; + m_StripOffsets.DataOffset = getSizeofHeader(); + + m_SamplesPerPixel.TagID = kTIFF_TAG_SAMPLESPERPIXEL; + m_SamplesPerPixel.DataType = kTIFF_TY_SHORT; + + if(24 == _bitsPerPixel) + { + m_SamplesPerPixel.DataCount = 1; + m_SamplesPerPixel.DataOffset = 3; + } + else + { + m_SamplesPerPixel.DataCount = 1; + m_SamplesPerPixel.DataOffset = 1; + } + + m_RowsPerStrip.TagID = kTIFF_TAG_ROWSPERSTRIP; + m_RowsPerStrip.DataType = kTIFF_TY_LONG; + m_RowsPerStrip.DataCount = 1; + m_RowsPerStrip.DataOffset = _height; + + m_StripByteCounts.TagID = kTIFF_TAG_STRIPBYTECOUNTS; + m_StripByteCounts.DataType = kTIFF_TY_LONG; + m_StripByteCounts.DataCount = 1; + m_StripByteCounts.DataOffset = _bytesPerRow * _height; + + m_XResolution.TagID = kTIFF_TAG_XRESOLUTION; + m_XResolution.DataType = kTIFF_TY_RATIONAL; + m_XResolution.DataCount = 1; + m_XResolution.DataOffset = m_StripOffsets.DataOffset - sizeof(DWORD)*4; // fixed offset from the end of the header + setXResolution(100, 1); + + m_YResolution.TagID = kTIFF_TAG_YRESOLUTION; + m_YResolution.DataType = kTIFF_TY_RATIONAL; + m_YResolution.DataCount = 1; + m_YResolution.DataOffset = m_StripOffsets.DataOffset - sizeof(DWORD)*2; // fixed offset from the end of the header + setYResolution(100, 1); + + m_ResolutionUnit.TagID = kTIFF_TAG_RESOLUTIONUNIT; + m_ResolutionUnit.DataType = kTIFF_TY_SHORT; + m_ResolutionUnit.DataCount = 1; + m_ResolutionUnit.DataOffset = 2; +} + +CTiffWriter::~CTiffWriter() +{ + if(0 != m_pImageStream) + { + if(m_pImageStream->is_open()) + { + m_pImageStream->close(); + } + delete m_pImageStream; + } +} + +void CTiffWriter::setImageWidth(const long int _v) +{ + m_ImageWidth.DataOffset = _v; +} + +void CTiffWriter::setImageHeight(const long int _v) +{ + m_ImageLength.DataOffset = _v; +} + +void CTiffWriter::setBitsPerSample(const int _v) +{ + m_BitsPerSample.DataOffset = _v; +} + +void CTiffWriter::setCompression(const int _v) +{ + m_Compression.DataOffset = _v; +} + +void CTiffWriter::setPhotometricInterp(const int _v) +{ + m_PhotometricInterp.DataOffset = _v; +} + +void CTiffWriter::setSamplesPerPixel(const int _v) +{ + m_SamplesPerPixel.DataOffset = _v; +} + +void CTiffWriter::setXResolution(const int _numerator, const int _denominator) +{ + m_xres[0] = _numerator; + m_xres[1] = _denominator; +} + +void CTiffWriter::setYResolution(const int _numerator, const int _denominator) +{ + m_yres[0] = _numerator; + m_yres[1] = _denominator; +} + +void CTiffWriter::setBytesPerRow(const int _v) +{ + m_StripByteCounts.DataOffset = _v * m_ImageLength.DataOffset; +} + +void CTiffWriter::GetImageHeader(stringstream &Header) +{ + // write the header + TIFFIFH hdr = {0x4949, 0x002a, sizeof(TIFFIFH)}; + Header.write(reinterpret_cast(&hdr), sizeof(TIFFIFH)); + + // write the Tags immediately after the header + WORD numTags = 12; + Header.write(reinterpret_cast(&numTags), sizeof(numTags)); + + const int nsize = sizeof(TIFFTag); + + Header.write(reinterpret_cast(&m_ImageWidth), nsize); + Header.write(reinterpret_cast(&m_ImageLength), nsize); + Header.write(reinterpret_cast(&m_BitsPerSample), nsize); + Header.write(reinterpret_cast(&m_Compression), nsize); + Header.write(reinterpret_cast(&m_PhotometricInterp), nsize); + Header.write(reinterpret_cast(&m_StripOffsets), nsize); + Header.write(reinterpret_cast(&m_SamplesPerPixel), nsize); + Header.write(reinterpret_cast(&m_RowsPerStrip), nsize); + Header.write(reinterpret_cast(&m_StripByteCounts), nsize); + Header.write(reinterpret_cast(&m_XResolution), nsize); + Header.write(reinterpret_cast(&m_YResolution), nsize); + Header.write(reinterpret_cast(&m_ResolutionUnit), nsize); + + // end the header by setting the next image offset to null + DWORD end = 0; + Header.write(reinterpret_cast(&end), sizeof(end)); + + // write the X and Y resolutions + Header.write(reinterpret_cast(&m_xres), sizeof(DWORD)*2); + + Header.write(reinterpret_cast(&m_yres), sizeof(DWORD)*2); +} + +bool CTiffWriter::writeImageHeader() +{ + // create the out stream if not done so already + if(0 == m_pImageStream) + { + m_pImageStream = new ofstream(); + } + + // open the stream. If already open, reset it + if(m_pImageStream->is_open()) + { + m_pImageStream->seekp(0); + } + else + { + m_pImageStream->open(m_filename.c_str(), ios_base::out|ios_base::binary|ios_base::trunc); + } + stringstream Header; + GetImageHeader(Header); + Header.seekp(0, ios_base::end); + m_nOffset =(int) Header.tellp(); + Header.seekg(0, ios_base::beg); + char *pData = new char[m_nOffset]; + Header.read(pData,m_nOffset); + m_pImageStream->write(pData,m_nOffset); + delete []pData; + return true; +} + +bool CTiffWriter::WriteTIFFData(char *_pData, DWORD _nCount) +{ + bool bret = false; + + if(0 != m_pImageStream && + m_pImageStream->good()) + { + m_pImageStream->seekp(m_nOffset); + m_pImageStream->write(_pData, _nCount); + m_nOffset += _nCount; + bret = true; + } + + return bret; +} + +unsigned int CTiffWriter::getSizeofHeader() +{ + // Header is as follows: + // TIFFIFH + Num. of Tags + each tag + Xres Data (2 dwords) + Yres Data (2 dwords) + Next Image offset (1 dword) + return sizeof(TIFFIFH)+sizeof(WORD)+sizeof(TIFFTag)*12+sizeof(DWORD)*5; +} diff --git a/huagao/CTiffWriter.h b/huagao/CTiffWriter.h new file mode 100644 index 00000000..9f73f148 --- /dev/null +++ b/huagao/CTiffWriter.h @@ -0,0 +1,240 @@ +/*************************************************************************** +* Copyright ?2007 TWAIN Working Group: +* Adobe Systems Incorporated, AnyDoc Software Inc., Eastman Kodak Company, +* Fujitsu Computer Products of America, JFL Peripheral Solutions Inc., +* Ricoh Corporation, and Xerox Corporation. +* All rights reserved. +* +* Redistribution and use in source and binary forms, with or without +* modification, are permitted provided that the following conditions are met: +* * Redistributions of source code must retain the above copyright +* notice, this list of conditions and the following disclaimer. +* * Redistributions in binary form must reproduce the above copyright +* notice, this list of conditions and the following disclaimer in the +* documentation and/or other materials provided with the distribution. +* * Neither the name of the TWAIN Working Group nor the +* names of its contributors may be used to endorse or promote products +* derived from this software without specific prior written permission. +* +* THIS SOFTWARE IS PROVIDED BY TWAIN Working Group ``AS IS'' AND ANY +* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +* DISCLAIMED. IN NO EVENT SHALL TWAIN Working Group BE LIABLE FOR ANY +* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +* +***************************************************************************/ + +/** +* @file CTiffWriter.h +* Write an image to disk as a tiff file. +* @author TWAIN Working Group +* @date October 2007 +*/ + +#ifndef __TIFFWRITER_H__ +#define __TIFFWRITER_H__ + +#include +#include + +using namespace std; + +#ifdef _MSC_VER + #include +#else + typedef uint16_t WORD; + typedef uint32_t DWORD; +#endif // _MSC_VER + +#define TIFF_UNCOMPRESSED 1 /**< TIFF compression types */ +#define TIFF_CCITTGROUP3 3 +#define TIFF_CCITTGROUP4 4 + +// TIFF types +#define kTIFF_TY_BYTE 1 /**< 8-bit unsigned int */ +#define kTIFF_TY_ASCII 2 /**< 8-bit byte that contains a 7-bit ASCII code; last byte must be binary 0 (NULL) */ +#define kTIFF_TY_SHORT 3 /**< 16-bit (2-byte) unsigned int */ +#define kTIFF_TY_LONG 4 /**< 32-bit (4-byte) unsigned int */ +#define kTIFF_TY_RATIONAL 5 /**< two LONGs; the first is the numerator of a fraction; the second, the denominator */ + +// these field types where introduced in TIFF 6.0 +#define kTIFF_TY_SBYTE 6 /**< 8-bit signed int */ +#define kTIFF_TY_UNDEFINED 7 /**< 8-bit byte that may contain anything, depending on the definition of the field */ +#define kTIFF_TY_SSHORT 8 /**< 16-bit (2-byte) signed int */ +#define kTIFF_TY_SLONG 9 /**< 32-bit (4-byte) signed int */ +#define kTIFF_TY_SRATIONAL 10 /**< two SLONG's; first is numerator of fraction, second is denominator */ +#define kTIFF_TY_FLOAT 11 /**< single precision (4-byte) IEEE format */ +#define kTIFF_TY_DOUBLE 12 /**< double precision (8-byte) IEEE format */ + +// TIFF Tags +#define kTIFF_TAG_IMGWIDTH 0x0100 /**< Image width, short or long */ +#define kTIFF_TAG_IMGLENGTH 0x0101 /**< Image length, short or long */ +#define kTIFF_TAG_BITSPERSAMPLE 0x0102 /**< BitsPerSample, short */ +#define kTIFF_TAG_COMPRESSION 0x0103 /**< Compression, short */ +#define kTIFF_TAG_PHOTOMETRICINT 0x0106 /**< PhotometricInterpretation, short */ +#define kTIFF_TAG_STRIPOFFSETS 0x0111 /**< StripOffsets, short or long */ +#define kTIFF_TAG_SAMPLESPERPIXEL 0x0115 /**< Samples per pixel, short */ +#define kTIFF_TAG_ROWSPERSTRIP 0x0116 /**< RowsPerStrip, short or long */ +#define kTIFF_TAG_STRIPBYTECOUNTS 0x0117 /**< StripByteCounts, short or long */ +#define kTIFF_TAG_XRESOLUTION 0x011A /**< X Resolution, rational */ +#define kTIFF_TAG_YRESOLUTION 0x011B /**< Y Resolution, rational */ +#define kTIFF_TAG_RESOLUTIONUNIT 0x0128 /**< Resolution unit, short */ +#define kTIFF_TAG_COLORMAP 0x0140 /**< ColorMap, short, RGB order, black = 0,0,0, TWAIN supports max 256 entry pallette */ + +/** +* TIFF Image File Header +*/ +struct TIFFIFH +{ + WORD Identifier; + WORD Version; + DWORD IFDOffset; +}; + +/** +* A TIFF Tag +* If the actual value of the tag is less then a DWORD, then offset will contain +* it, else offset is truly an offset to the value. +*/ +struct TIFFTag +{ + WORD TagID; + WORD DataType; + DWORD DataCount; + DWORD DataOffset; +}; + +/** +* This is a class that will progressively write a TIFF image to a file. +*/ +class CTiffWriter +{ +public: +/** +* Constructor for CTiffWriter. This is a class that will progressively +* write a TIFF image to a file. +* @param[in] _filename name of file to write to. +* @param[in] _width image width. +* @param[in] _height image height. +* @param[in] _bitsPerPixel number of bits per each pixel. +* @param[in] _bytesPerRow number of bytes per row of data. +*/ + CTiffWriter(const string& _filename, + const long int _width, + const long int _height, + const int _bitsPerPixel, + const unsigned long int _bytesPerRow); + +/** +* Deconstructor for CTiffWriter. +*/ + virtual ~CTiffWriter(); + +/** +* Set the width of the image. +* @param[in] _v the new image width +*/ + void setImageWidth(const long int _v); + +/** +* Set the height of the image. +* @param[in] _v the new image height +*/ + void setImageHeight(const long int _v); + +/** +* Set the bits per sample of the image. +* @param[in] _v the new bits per sample +*/ + void setBitsPerSample(const int _v); + +/** +* Set the compression method to use. +* @param[in] _v the new compression method +*/ + void setCompression(const int _v); + +/** +* Set the Photometric Interpretation. +* @param[in] _v the new Photometric Interpretation +*/ + void setPhotometricInterp(const int _v); + +/** +* Set the number of samples per pixel of the image. +* @param[in] _v the new samples per pixel +*/ + void setSamplesPerPixel(const int _v); + +/** +* Set the x resolution of the image. Using type kTIFF_TY_RATIONAL (fraction) +* @param[in] _numerator the numerator part of the fraction +* @param[in] _denominator the denominator part of the fraction +*/ + void setXResolution(const int _numerator, const int _denominator); + +/** +* Set the y resolution of the image. Using type kTIFF_TY_RATIONAL (fraction) +* @param[in] _numerator the numerator part of the fraction +* @param[in] _denominator the denominator part of the fraction +*/ + void setYResolution(const int _numerator, const int _denominator); + +/** +* Set the Bytes per row of the image. +* @param[in] _v the new bytes per row +*/ + void setBytesPerRow(const int _v); + + +/** +* Write the prepaired image header to the file. +* @return true for succes +*/ + bool writeImageHeader(); + +/** +* Write the data for the image to the file. +* @param[in] _pData pointer to the image data +* @param[in] _nCount number of bytes to write +* @return true for success +*/ + bool WriteTIFFData(char *_pData, DWORD _nCount); + +/** +* Return the size of the TIFF header for the image file. +* @return the size of the header +*/ + unsigned int getSizeofHeader(); + + void GetImageHeader(stringstream &Header); + +protected: + string m_filename; /**< Name and or path of file */ + int m_nOffset; /**< Current offset into file */ + + DWORD m_xres[2]; /**< The X resolution of the image */ + DWORD m_yres[2]; /**< The Y resolution of the image */ + + TIFFTag m_ImageWidth; /**< The image width in pixels */ + TIFFTag m_ImageLength; /**< The image height in pixels */ + TIFFTag m_BitsPerSample; /**< The number of Bits per sample */ + TIFFTag m_Compression; /**< The compression method to use */ + TIFFTag m_PhotometricInterp; /**< The Photometric Interpretation to use */ + TIFFTag m_StripOffsets; /**< The strip offset, where image data starts */ + TIFFTag m_SamplesPerPixel; /**< The number of channels (RGB, G, )*/ + TIFFTag m_RowsPerStrip; /**< The number of rows that make up each strip */ + TIFFTag m_StripByteCounts; /**< The size of each strip of image data */ + TIFFTag m_XResolution; /**< The offset to the X resolution */ + TIFFTag m_YResolution; /**< The offset to the Y resolution */ + TIFFTag m_ResolutionUnit; /**< The units of the Resolution */ + + ofstream* m_pImageStream; /**< The output stream to write the file to */ +}; + +#endif // __TIFFWRITER_H__ diff --git a/huagao/CTwainMutex.cpp b/huagao/CTwainMutex.cpp new file mode 100644 index 00000000..dce9b07c --- /dev/null +++ b/huagao/CTwainMutex.cpp @@ -0,0 +1,126 @@ +#include "stdafx.h" +#include "CTwainMutex.h" + +CTwainMutex::CTwainMutex(void) +{ + m_hTwainMutex=NULL; + m_bInited=FALSE; + memset(m_sTwainMutex,0,sizeof(m_sTwainMutex)); +} + +CTwainMutex::~CTwainMutex(void) +{ + + if (m_hTwainMutex!=NULL) + { + CloseHandle(m_hTwainMutex); + m_hTwainMutex=NULL; + } +} + +BOOL CTwainMutex::CreatTwainMutex(TCHAR *str_Mutex) +{ + TCHAR mutexName[MAX_PATH]={0}; + DWORD error_code=0; + HANDLE hMutex=NULL; + BOOL b_ret=FALSE; + if (m_hTwainMutex!=NULL) + { + return b_ret; + } + + _tcscpy(mutexName,str_Mutex); + + hMutex=CreateMutex(NULL,FALSE,mutexName); + if (hMutex!=NULL) + { + error_code=GetLastError(); + if (error_code==ERROR_ALREADY_EXISTS||error_code==ERROR_ACCESS_DENIED) + { + MessageBox(NULL, _T("豸ѱռãرռó֮ԣ"), _T("ʾ"),MB_OK|MB_ICONWARNING); + b_ret=CloseHandle(hMutex); + if (!b_ret) + { + MessageBox(NULL, TEXT("Դͷ쳣"), 0, MB_ICONWARNING); + } + hMutex=NULL; + return FALSE; + } + else + { + if (m_hTwainMutex!=NULL) + { + b_ret=CloseHandle(m_hTwainMutex); + if (!b_ret) + { + return FALSE; + } + m_hTwainMutex=NULL; + } + m_hTwainMutex=hMutex; + b_ret=TRUE; + } + return b_ret; + } + else + { + MessageBox(NULL, TEXT("ʼ"), 0, MB_ICONWARNING); + } + return b_ret; +} + +BOOL CTwainMutex::CheckExistTwainMutex(TCHAR* str_Mutex) +{ + TCHAR szMutexName[MAX_PATH] = {0}; + DWORD error_code = 0; + BOOL b_ret = FALSE; + HANDLE hMutex = NULL; + + if (m_hTwainMutex!=NULL) + { + return TRUE; + } + + _tcscpy(szMutexName,str_Mutex); + hMutex=CreateMutex(NULL,FALSE,szMutexName); + if (hMutex!=NULL) + { + error_code=GetLastError(); + if (error_code==ERROR_ALREADY_EXISTS||error_code==ERROR_ACCESS_DENIED) + { + b_ret=CloseHandle(hMutex); + hMutex=NULL; + b_ret=TRUE; + return b_ret; + } + else + { + CloseHandle(hMutex); + b_ret=FALSE; + return b_ret; + } + } + else + { + return TRUE; + } + return b_ret; +} + +BOOL CTwainMutex::CloseTwainMutex() +{ + BOOL b_ret=FALSE; + if (m_hTwainMutex!=NULL) + { + b_ret=CloseHandle(m_hTwainMutex); + + if (!b_ret) + { + MessageBox(NULL, TEXT("ͷԴʧ"), 0, MB_ICONWARNING); + } + m_hTwainMutex=NULL; + return b_ret; + } + return TRUE; +} + diff --git a/huagao/CTwainMutex.h b/huagao/CTwainMutex.h new file mode 100644 index 00000000..0581a661 --- /dev/null +++ b/huagao/CTwainMutex.h @@ -0,0 +1,16 @@ +#include "stdafx.h" + +class CTwainMutex +{ +public: + CTwainMutex(void); + ~CTwainMutex(void); +public: + BOOL CreatTwainMutex(TCHAR *str_Mutex); + BOOL CheckExistTwainMutex(TCHAR *str_Mutex); + BOOL CloseTwainMutex(); +private: + HANDLE m_hTwainMutex; + TCHAR m_sTwainMutex[MAX_PATH]; + BOOL m_bInited; +}; \ No newline at end of file diff --git a/huagao/CTwainUI.cpp b/huagao/CTwainUI.cpp new file mode 100644 index 00000000..38920195 --- /dev/null +++ b/huagao/CTwainUI.cpp @@ -0,0 +1,582 @@ +// CTwainUI.cpp: 实现文件 +// +#include "stdafx.h" +#include "CTwainUI.h" +#include "afxdialogex.h" +#include "resource.h" +#include "TabCtrlSSL.h" +#include "CBasicPage.h" +#include "CBrightnessPage.h" +#include "CFeedPaperPage.h" +#include "CImageProcPage.h" +#include "Device/PaperSize.h" +#include + +// CTwainUI 对话框 + +IMPLEMENT_DYNAMIC(CTwainUI, CDialogEx) + +CTwainUI::CTwainUI(TwGlue glue, CWnd* pParent /*=nullptr*/) + : CDialogEx(IDD_TWAINUI, pParent) + , m_tabCtrl(new CTabCtrlSSL()) + , m_pageBrightness(new CBrightnessPage) + , m_pageFeedPaper(new CFeedPaperPage) + , m_pageImageProc(new CImageProcPage) + , m_glue(glue) + , settings(new GScanCap) +{ + memset(settings.get(), 0, sizeof(GScanCap)); +} + +CTwainUI::~CTwainUI() +{ +} + +void CTwainUI::DoDataExchange(CDataExchange* pDX) +{ + CDialogEx::DoDataExchange(pDX); + DDX_Control(pDX, IDC_TAB, *m_tabCtrl); +} + +BOOL CTwainUI::OnInitDialog() +{ + CDialogEx::OnInitDialog(); + // Setup the tab control + int nPageID = 0; + + auto dataChangeFunction = [this]() { + m_pageImageProc->ImageProcPageUpdate(m_pageBasic->m_cmBoxColorMode->GetCurSel()); + m_pageFeedPaper->FeedPaperPageUpdate(m_pageBasic->m_cmBoxDuplex->GetCurSel()); + m_pageImageProc->ImageAutoDescrewUpdate(m_pageBasic->m_cmBoxSS->GetCurSel()); + //m_pageFeedPaper->FeedAutoDescrewUpdate(m_pageBasic->m_cmBoxSS->GetCurSel()); + UpdateUi(); + }; + + m_pageBasic.reset(new CBasicPage(dataChangeFunction)); + m_pageBasic->Create(IDD_PAGEBASIC, this); + m_tabCtrl->AddSSLPage(_T("基本"), nPageID++, m_pageBasic.get()); + m_pageBrightness->Create(IDD_PAGEBRIGHTNESS, this); + m_tabCtrl->AddSSLPage(_T("亮度"), nPageID++, m_pageBrightness.get()); + m_pageImageProc->Create(IDD_PAGEIMGPROC, this); + m_tabCtrl->AddSSLPage(_T("图像处理"), nPageID++, m_pageImageProc.get()); + m_pageFeedPaper->Create(IDD_PAGEFEEDPAPER, this); + m_tabCtrl->AddSSLPage(_T("送纸"), nPageID++, m_pageFeedPaper.get()); + + JsonConfig cfg; + CONFIGPARAMS configParams = cfg.ReadDefaultConfig(); + UpdateUI(configParams); + UpdateListConfig(); + UpdateUi(); + return true; +} + + +BEGIN_MESSAGE_MAP(CTwainUI, CDialogEx) + ON_BN_CLICKED(IDC_CONFIRM, &CTwainUI::OnBnClickedConfirm) + ON_BN_CLICKED(IDC_BTNDEFAULT, &CTwainUI::OnBnClickedBtndefault) + ON_BN_CLICKED(ID_CANCEL, &CTwainUI::OnBnClickedCancel) + ON_BN_CLICKED(IDC_BTNHELP, &CTwainUI::OnBnClickedBtnhelp) + ON_BN_CLICKED(IDC_BTNBACKUPCONFIG, &CTwainUI::OnBnClickedBtnbackupconfig) + ON_BN_CLICKED(IDC_BTNSAVECONFIG, &CTwainUI::OnBnClickedBtnsaveconfig) + ON_BN_CLICKED(IDC_BTNDELETCONFIG, &CTwainUI::OnBnClickedBtndeletconfig) + ON_BN_CLICKED(IDC_BTNRECOVERYCONFIG, &CTwainUI::OnBnClickedBtnrecoveryconfig) + ON_LBN_SELCHANGE(IDC_LSTCONFIG, &CTwainUI::OnLbnSelchangeLstconfig) +END_MESSAGE_MAP() + + +// CTwainUI 消息处理程序 +std::string TCHAR2STRING1(TCHAR* STR) +{ + int iLen = WideCharToMultiByte(CP_ACP, 0, STR, -1, NULL, 0, NULL, NULL); + char* chRtn = new char[iLen * sizeof(char)]; + WideCharToMultiByte(CP_ACP, 0, STR, -1, chRtn, iLen, NULL, NULL); + std::string str(chRtn); + return str; +} + +void CTwainUI::OnBnClickedConfirm() +{ + // TODO: 在此添加控件通知处理程序代码 + CString str_caption; + GetDlgItemText(IDC_CONFIRM, str_caption); + CONFIGPARAMS configItem = { 0 }; + UpDateScanParam(&configItem); + TCHAR szIniFile[MAX_PATH] = { 0 }; + SHGetSpecialFolderPath(NULL, szIniFile, CSIDL_LOCAL_APPDATA, TRUE); + _tcscat(szIniFile, HUAGAO_SCAN); + _tcscat(szIniFile, TWAIN_INIPATH); + _tcscat(szIniFile, TEXT("\\")); + _tcscat(szIniFile, TWAIN_JSON_NAME); + JsonConfig js; + vector vc; + vc.push_back(configItem); + std::string savepath = TCHAR2STRING1(szIniFile); + js.WriteJsonArrayToFile(vc, savepath); + if (str_caption.Compare(_T("扫描")) == 0)//内容为扫描时 + { + m_glue.m_scan(*settings); + } + else + { + m_glue.m_cancel(); + } +} + + +void CTwainUI::OnBnClickedBtndefault() +{ + // TODO: 在此添加控件通知处理程序代码 + JsonConfig js; + CONFIGPARAMS cf = js.GetDefaultConfigParams(); + UpdateUI(cf); +} + + +void CTwainUI::OnBnClickedCancel() +{ + // TODO: 在此添加控件通知处理程序代码 + m_glue.m_cancel(); +} + + +void CTwainUI::OnBnClickedBtnhelp() +{ + // TODO: 在此添加控件通知处理程序代码 + this->SetWindowPos(&wndNoTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); + TCHAR chmPath[MAX_PATH] = { 0 }; + SHGetSpecialFolderPath(NULL, chmPath, CSIDL_WINDOWS, TRUE); + _tcscat(chmPath, CHM_DEFAULT_PATH); + int ret = (int)ShellExecute(NULL, _T("Open"), chmPath, NULL, NULL, SW_SHOWMAXIMIZED); + if (ret < 32) + MessageBox(ret == ERROR_FILE_NOT_FOUND ? _T("未找到帮助文档！") : _T("打开帮助文档异常！"), + _T("提示"), MB_OK | MB_ICONINFORMATION); + + this->SetWindowPos(&wndTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); +} + +void CTwainUI::UpdateUI(CONFIGPARAMS configParams) +{ + //!< Page Basic + m_pageBasic->m_cmBoxColorMode->SetCurSel(configParams.Pixtype);//!< 颜色模式 + m_pageBasic->m_cmBoxResultion->SetCurSel(configParams.Resolution);//!< 分辨率 + m_pageBasic->m_cmBoxDuplex->SetCurSel(configParams.Duplex);//!< 单双面 + m_pageBasic->m_cmBoxSS->SetCurSel(configParams.PaperSize); //!< 纸张类型 + m_pageBasic->UpdateData(FALSE); + + //!< Page Breghtness + + m_pageBrightness->m_cbAutoContrast = configParams.EnAutoContrast; //!< 自动亮度对比度 + int brt = GetMappingBrightnessValue(configParams.Brightness); + m_pageBrightness->m_Edit_Brightness.SetValue(brt); //!< 亮度 + int crt = GetContrastLevel(configParams.Contrast); + m_pageBrightness->m_Edit_Contrast.SetValue(crt);//!<对比度 + m_pageBrightness->m_Edit_Gamma.SetValue(configParams.Gamma); //!< gamma + m_pageBrightness->UpdateData(FALSE); + + //!< Page Proc + m_pageImageProc->m_ckbFillBlack = configParams.EnFillBlack?TRUE:FALSE;//填充黑框 + m_pageImageProc->m_ckbAutoDeskrew =configParams.EnAutoDescrew? TRUE : FALSE;//自动纠偏 + m_pageImageProc->m_cmBoxFilter.SetCurSel(configParams.Filter);//除色 + m_pageImageProc->m_cmBoxSharpen.SetCurSel(configParams.Sharpen);//锐化 + m_pageImageProc->m_ckbRemoveHole = configParams.EnOutHole;//除穿孔可用性 + m_pageImageProc->m_edit_hole.SetValue(configParams.OutHoleRatio/100.0);//穿孔搜索范围比例系数 + m_pageImageProc->m_ckbMultioutput = configParams.EnMultiOutPutR;//多流除红 + m_pageImageProc->UpdateData(FALSE); + + //!< Page feed paper + m_pageFeedPaper->m_cbRotation = configParams.EnBackRotate180? TRUE : FALSE;//背面旋转180 + m_pageFeedPaper->m_cbStaple = configParams.EnBindingDetect? TRUE : FALSE;//装订检测 + m_pageFeedPaper->m_cbDoublePaper = configParams.EnUltrasonicDetect? TRUE : FALSE;//双张检测 + m_pageFeedPaper->m_cbSkew = configParams.EnScrewDetect? TRUE : FALSE;//歪斜检测 + m_pageFeedPaper->m_cmBoxOrentation.SetCurSel(configParams.Orentation);//旋转方向; + m_pageFeedPaper->m_sldSkrewDetecttion.SetPos(configParams.ScrewDetectLevel);//歪斜检测等级 + + if (configParams.ScanCount <= 0)//连续扫描 + { + m_pageFeedPaper->m_radioGroupScanMode = 0; + m_pageFeedPaper->GetDlgItem(IDC_EDSCANNUM)->SetWindowText(_T("1")); + m_pageFeedPaper->GetDlgItem(IDC_EDSCANNUM)->EnableWindow(FALSE); + } + else//指定数目 + { + m_pageFeedPaper->GetDlgItem(IDC_EDSCANNUM)->EnableWindow(TRUE); + m_pageFeedPaper->m_radioGroupScanMode = 1; + int tempcount = configParams.ScanCount; + //if (configParams.Duplex == 0) + //{ + // tempcount = configParams.ScanCount; + //} + //else + //{ + // tempcount = configParams.ScanCount / 2; + //} + CString csCount; + csCount.Format(_T("%d"), tempcount); + m_pageFeedPaper->GetDlgItem(IDC_EDSCANNUM)->SetWindowText(csCount); + } + + m_pageFeedPaper->UpdateData(FALSE); +} + +int CTwainUI::getResolutionIndex(int resolution) +{ + int result = 0; + for (size_t i = 0; i < SUPPORTRESNUMS; i++) + { + if (Resolutions[i] == resolution) + { + result = i; + break; + } + } + return result; +} + +int CTwainUI::getPaparSizeIndex(int papersize,int orentation) +{ + PaperStatus ps = { papersize,orentation }; + int result = 0; + for (std::map::iterator it = paperStatusMap.begin(); it != paperStatusMap.end(); it++) { + if (it->second.Paper == ps.Paper && it->second.Orentate == ps.Orentate) { + return it->first; + } + } + return 0; +} + +int CTwainUI::getColorModelIndex(int pixtype) +{ + return pixtype == 2 ? 0 : (pixtype == 1 ? 1 : 2); +} + +vector CTwainUI::getConfigFiles() +{ + vector vc_cfi; + CFileFind find; + TCHAR cfFilePath[MAX_PATH] = { 0 }; + SHGetSpecialFolderPath(NULL, cfFilePath, CSIDL_LOCAL_APPDATA, TRUE); + _tcscat(cfFilePath, HUAGAO_SCAN); + _tcscat(cfFilePath, TWAIN_DATA_PATH); + CString filePath(cfFilePath); + BOOL isFind = find.FindFile(filePath + _TEXT("/*.json")); + while (isFind) + { + isFind = find.FindNextFile(); + if (find.IsDots()) + { + continue; + } + else + { + CONFIGINFO cfi; + cfi.Caption = CW2A(find.GetFileTitle()); + cfi.SavePath = CW2A(find.GetFilePath()); + vc_cfi.push_back(cfi); + } + } + return vc_cfi; +} + +static int WndCtrl2i(const CWnd* wnd) +{ + CString valText; + wnd->GetWindowText(valText); + return _ttoi(valText); +} + +static float WndCtrl2f(const CWnd* wnd) +{ + CString valText; + wnd->GetWindowText(valText); + return (float)_ttof(valText); +} + +template +static T* GetCtrl(const CWnd* wnd, int nID) +{ + return wnd->GetDlgCtrlID(nID); +} + +////////////////////////////////////////////////////////////////////// +/*从UI获取参数*/ +void CTwainUI::UpDateScanParam(PCONFIGPARAMS configItem, bool updateDs) +{ + //!< Page Basic + m_pageBasic->UpdateData(); + configItem->Pixtype = m_pageBasic->m_cmBoxColorMode->GetCurSel();//!< 颜色模式 index + configItem->Resolution = m_pageBasic->m_cmBoxResultion->GetCurSel();//!< 分辨率 index + configItem->Duplex = m_pageBasic->m_cmBoxDuplex->GetCurSel();//!< 单双面 + configItem->PaperSize = m_pageBasic->m_cmBoxSS->GetCurSel();//!< 纸张类型 index + configItem->EnAutoCrop = configItem->PaperSize == 16; + configItem->EnDiscardBlank = configItem->Duplex == 2;//自动跳骨空白页通用 + configItem->EnDiscardBlankVince = configItem->Duplex == 3;//自动跳骨空白页发票 + //configItem->DBlank_AreaNum = m_pageBasic->AreaNum;//!< 分区数 + //configItem->DBlank_DevnMax = m_pageBasic->DevnMax;//!< 跳过阈值 + + //!< Page Breghtness + m_pageBrightness->UpdateData(); + configItem->EnAutoContrast = m_pageBrightness->m_cbAutoContrast; //!< 自动亮度对比度 + configItem->Brightness = (WndCtrl2i(&(m_pageBrightness->m_Edit_Brightness)) - 128)*(2000.0/254.0); //!< 亮度 + int crtvalue = WndCtrl2i(&(m_pageBrightness->m_Edit_Contrast)) - 4; + configItem->Contrast = GetContrast(crtvalue);//!<对比度 + configItem->Gamma = WndCtrl2f(&(m_pageBrightness->m_Edit_Gamma)); //!< gamma + + //!< Page Proc + m_pageImageProc->UpdateData(); + configItem->EnFillBlack = m_pageImageProc->m_ckbFillBlack;//填充黑框 + configItem->EnAutoDescrew = m_pageImageProc->m_ckbAutoDeskrew;//自动纠偏 + configItem->Filter = m_pageImageProc->m_cmBoxFilter.GetCurSel();//除色 + configItem->Sharpen = m_pageImageProc->m_cmBoxSharpen.GetCurSel();//锐化 + configItem->EnOutHole = m_pageImageProc->m_ckbRemoveHole;//除穿孔可用性 + configItem->OutHoleRatio = WndCtrl2f(&(m_pageImageProc->m_edit_hole))*100;//穿孔搜索范围比例系数 + configItem->EnMultiOutPutR = m_pageImageProc->m_ckbMultioutput;//多流除红 + + //!< Page feed paper + m_pageFeedPaper->UpdateData(); + configItem->EnBackRotate180 = m_pageFeedPaper->m_cbRotation;//背面旋转180 + configItem->EnBindingDetect = m_pageFeedPaper->m_cbStaple;//装订检测 + configItem->EnUltrasonicDetect = m_pageFeedPaper->m_cbDoublePaper;//双张检测 + configItem->EnScrewDetect = m_pageFeedPaper->m_cbSkew;//歪斜检测 + configItem->Orentation = m_pageFeedPaper->m_cmBoxOrentation.GetCurSel();//旋转方向 + + int count = WndCtrl2i(&(m_pageFeedPaper->m_editNum)); + if (count == 0) + { + m_pageFeedPaper->GetDlgItem(IDC_EDSCANNUM)->SetWindowText(_T("1")); + count = 1; + } + configItem->ScanCount = (m_pageFeedPaper->m_radioGroupScanMode == 0) ? -1 : count; + configItem->ScrewDetectLevel = m_pageFeedPaper->m_sldSkrewDetecttion.GetPos();//歪斜检测等级 + + if (!updateDs) + return; + + settings->pixtype =colorModes[configItem->Pixtype]; + settings->hardwarecaps.capturepixtype = settings->pixtype; + + PaperStatus paper= paperStatusMap[configItem->PaperSize]; + settings->papertype = paper.Paper; + settings->paperAlign = (PaperAlign)paper.Orentate; + + settings->resolution_dst = Resolutions[configItem->Resolution]; + settings->resolution_native = 200.0f; + + //float value_Contrast = GetContrast(configItem->Contrast); + settings->contrast = configItem->Contrast; + settings->brightness = (configItem->Brightness); + settings->gamma = (configItem->Gamma); + settings->is_autocrop = paper.Paper == TwSS::None; + settings->is_duplex = configItem->Duplex >= 1; + settings->is_autodiscradblank_normal = configItem->Duplex == 2; + settings->is_autodiscradblank_vince = configItem->Duplex == 3; + //settings->areanum = configItem->DBlank_AreaNum; + //settings->devnmax = configItem->DBlank_DevnMax; + + //填充黑框 + settings->fillbackground = configItem->EnFillBlack; + settings->autodescrew = configItem->EnAutoDescrew; + if (configItem->Orentation <= 3) { + settings->imageRotateDegree = rotateDegrees[configItem->Orentation]; + } + else { + settings->imageRotateDegree = 0.0f; + } + + settings->is_autotext = configItem->Orentation == 4; + settings->is_backrotate180 = configItem->EnBackRotate180; + settings->hardwarecaps.en_skrewdetect = configItem->EnScrewDetect; + settings->hardwarecaps.skrewdetectlevel = (float)configItem->ScrewDetectLevel; + settings->hardwarecaps.en_stapledetect = configItem->EnBindingDetect; + settings->hardwarecaps.en_doublefeed = configItem->EnUltrasonicDetect; + + bool bVal = settings->is_duplex; + //if (configItem->ScanCount == -1) + settings->scannum = configItem->ScanCount; + //else{ + // if (settings->multi_output_red) + // configItem->ScanCount /= 2; + // settings->scannum = bVal ? configItem->ScanCount / 2 : configItem->ScanCount; + //} + + if (configItem->Filter){ + if (configItem->Filter <= 3) { + settings->filter = (byte)filterMaps[configItem->Filter]; + settings->enhance_color =(byte)EnchaceColor::Enhance_None; + } + else { + settings->filter = 3;//不除色 + settings->enhance_color = (byte)filterMaps[configItem->Filter]; + } + } + else { + settings->filter = 3; + settings->enhance_color = (byte)EnchaceColor::Enhance_None; + } + + settings->sharpen = configItem->Sharpen; + if (configItem->Filter != 0||configItem->EnMultiOutPutR) + settings->hardwarecaps.capturepixtype = TWPT_RGB; + + settings->fillhole.is_fillhole = configItem->EnOutHole; + settings->fillhole.fillholeratio = configItem->OutHoleRatio; + settings->multi_output_red = configItem->EnMultiOutPutR; + + UpdateUi(); +} + +void CTwainUI::UpdateListConfig() +{ + ((CListBox*)(GetDlgItem(IDC_LSTCONFIG)))->ResetContent(); + if (cfi.size() > 0) + { + cfi.clear(); + } + cfi = getConfigFiles(); + for (int i = 0; i < cfi.size(); i++) + { + CString a; + a = cfi[i].Caption.c_str(); + ((CListBox*)(GetDlgItem(IDC_LSTCONFIG)))->AddString(a); + } + if (cfi.size() <= 0) + { + ((CButton*)(GetDlgItem(IDC_BTNDELETCONFIG)))->EnableWindow(FALSE); + ((CButton*)(GetDlgItem(IDC_BTNBACKUPCONFIG)))->EnableWindow(FALSE); + } + else + { + ((CButton*)(GetDlgItem(IDC_BTNDELETCONFIG)))->EnableWindow(TRUE); + ((CButton*)(GetDlgItem(IDC_BTNBACKUPCONFIG)))->EnableWindow(TRUE); + } +} + +void CTwainUI::UpdateUi() +{ + m_pageImageProc->m_cmBoxFilter.EnableWindow(m_pageBasic->m_cmBoxColorMode->GetCurSel() != 0); + m_pageFeedPaper->GetDlgItem(IDC_CKBACKROTATION)->EnableWindow(m_pageBasic->m_cmBoxDuplex->GetCurSel() != 0); + m_pageImageProc->GetDlgItem(IDC_SLDOUTHOLE)->EnableWindow(((CButton*)m_pageImageProc->GetDlgItem(IDC_CKREMOVEHOLE))->GetCheck()==TRUE); + m_pageFeedPaper->GetDlgItem(IDC_SLDDETECTLEVEL)->EnableWindow(((CButton*)m_pageFeedPaper->GetDlgItem(IDC_CKSKEWDETECT))->GetCheck()==TRUE); + m_pageImageProc->GetDlgItem(IDC_CKMULTIOUTPUT)->EnableWindow(m_pageBasic->m_cmBoxColorMode->GetCurSel() == 0); +} + +void CTwainUI::EnableID_OKorID_Cancel(bool enable) +{ + GetDlgItem(IDC_CONFIRM)->EnableWindow(enable); + GetDlgItem(ID_CANCEL)->EnableWindow(enable); + GetDlgItem(IDC_BTNHELP)->EnableWindow(enable); + GetDlgItem(IDC_BTNDEFAULT)->EnableWindow(enable); + GetDlgItem(IDC_TAB)->EnableWindow(enable); + GetDlgItem(IDC_GROUP)->EnableWindow(enable); +} + + +void CTwainUI::OnBnClickedBtnbackupconfig() +{ + // TODO: 在此添加控件通知处理程序代码 + CString csFilters = _T("Json file(*.json)\0"); + CFileDialog cfd(FALSE, _T("json"), _T("另存为")); + cfd.m_ofn.lpstrTitle = _T(""); + cfd.m_ofn.lpstrFilter = csFilters; + this->SetWindowPos(&wndNoTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); + JsonConfig js; + if (IDOK == cfd.DoModal()) + { + vector vc_tempOut; + std::vector temp_cfi = getConfigFiles(); + for (int i = 0; i < temp_cfi.size(); i++) + { + vector vc_item = js.ReadJsonArrayFromFile(temp_cfi[i].SavePath.c_str()); + if (vc_item.size() > 0) + { + vc_tempOut.push_back(vc_item[0]); + } + } + if (vc_tempOut.size() > 0) + { + std::string path = (CW2A)cfd.GetPathName(); + js.WriteJsonArrayToFile(vc_tempOut, path); + } + } + this->SetWindowPos(&wndTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); +} + + +void CTwainUI::OnBnClickedBtnsaveconfig() +{ + // TODO: 在此添加控件通知处理程序代码 + CSaveConfigDlg sfd(this); + sfd.DoModal(); +} + + +void CTwainUI::OnBnClickedBtndeletconfig() +{ + // TODO: 在此添加控件通知处理程序代码 + if (MessageBox(TEXT("确认要删除此用户首选项配置吗？"), TEXT("用户首选项"), MB_YESNO | MB_ICONQUESTION) == IDYES) + { + int cursel = -1; + cursel = ((CListBox*)(GetDlgItem(IDC_LSTCONFIG)))->GetCurSel(); + if (cursel != -1) + { + CFile file; + CString csFile; + csFile = cfi[cursel].SavePath.c_str(); + file.Remove(csFile); + UpdateListConfig(); + } + } +} + +void CTwainUI::OnBnClickedBtnrecoveryconfig() +{ + // TODO: 在此添加控件通知处理程序代码 + this->SetWindowPos(&wndNoTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); + if (MessageBox(TEXT("如果恢复,当前所有已保存配置将丢失。是否继续？"), TEXT("恢复"), MB_YESNO | MB_ICONQUESTION) == IDYES) + { + JsonConfig js; + CFileDialog ofd(TRUE, + _T(".json"), + NULL, + OFN_HIDEREADONLY | OFN_OVERWRITEPROMPT, + _TEXT("Json Files (*.json)|*.json||)"), + NULL); + for (int i = 0; i < cfi.size(); i++) + { + DeleteFile((LPCWSTR)cfi[i].SavePath.c_str()); + } + cfi.clear(); + if (IDOK == ofd.DoModal()) + { + std::string path = (CW2A)ofd.GetPathName(); + vector vc = js.ReadJsonArrayFromFile(path); + for (int i = 0; i < vc.size(); i++) + { + // js.WriteJsonArrayToFile(vc[i],vc[i].SavePath); + vector vc_item; + vc_item.push_back(vc[i]); + js.WriteJsonArrayToFile(vc_item, vc[i].SavePath); + } + UpdateListConfig(); + } + } + this->SetWindowPos(&wndTopMost, 0, 0, 0, 0, SWP_NOMOVE | SWP_NOSIZE); +} + + +void CTwainUI::OnLbnSelchangeLstconfig() +{ + // TODO: 在此添加控件通知处理程序代码 + int index = -1; + index = ((CListBox*)(GetDlgItem(IDC_LSTCONFIG)))->GetCurSel(); + if (index != -1) + { + JsonConfig js; + //std::string savepath= cfi[index].SavePath; + std::vector vc_temp; + vc_temp = js.ReadJsonArrayFromFile(cfi[index].SavePath); + if (vc_temp.size() > 0) + { + UpdateUI(vc_temp[0]); + } + } +} diff --git a/huagao/CTwainUI.h b/huagao/CTwainUI.h new file mode 100644 index 00000000..34c13929 --- /dev/null +++ b/huagao/CTwainUI.h @@ -0,0 +1,164 @@ +#pragma once +#include +#include "twglue.hpp" +#include "Device/JsonConfig.h" +#include "CSaveConfigDlg.h" +#include "Device/PublicFunc.h" +#include "Device/PaperSize.h" +#include + +class CTabCtrlSSL; +class CTabPageSSL; +class CImageProcPage; +class CBasicPage; +class CFeedPaperPage; +class CBrightnessPage; + +/*帮助文档存储路径*/ +#define DOCHELPPATH "C:/Windows/twain_32/HuagaoT/HuaGoScan TWAIN_Cs.chm" +/*配置文件默认索引号*/ +#define SUPPORTRESNUMS 5 +static int Resolutions[SUPPORTRESNUMS] = {100,150,200,240,300}; + +#define TWPT_BW 0 +#define TWPT_GRAY 1 +#define TWPT_RGB 2 + +static std::map paperStatusMap = { + {0,{TwSS::A3,PaperAlign::Rot0}}, + {1,{TwSS::A4,PaperAlign::Rot0}}, + {2,{TwSS::A4,PaperAlign::Rot270}}, + {3,{TwSS::A5,PaperAlign::Rot0}}, + {4,{TwSS::A5,PaperAlign::Rot270}}, + {5,{TwSS::A6,PaperAlign::Rot0}}, + {6,{TwSS::A6,PaperAlign::Rot270}}, + {7,{TwSS::B4,PaperAlign::Rot0}}, + {8,{TwSS::B5,PaperAlign::Rot0}}, + {9,{TwSS::B5,PaperAlign::Rot270}}, + {10,{TwSS::B6,PaperAlign::Rot0}}, + {11,{TwSS::B6,PaperAlign::Rot270}}, + {12,{TwSS::USLetter,PaperAlign::Rot0}}, + {13,{TwSS::USLetter,PaperAlign::Rot270}}, + {14,{TwSS::USLedger,PaperAlign::Rot0}}, + {15,{TwSS::USLegal,PaperAlign::Rot0}}, + {16,{TwSS::None,PaperAlign::Rot0}}, + {17,{TwSS::USStatement,PaperAlign::Rot0}}, + {18,{TwSS::MaxSize,PaperAlign::Rot0}} +}; + +static std::map filterMaps = { + {0,3},//不除色 None + {1,0},//除红 + {2,1},//除绿 + {3,2},//除蓝 + {4,Enchace_Color::Enhance_Red},//红色增强 + {5,Enchace_Color::Enhance_Green},//绿色增强 + {6,Enchace_Color::Enhance_Blue}//蓝色增强 +}; + +// +static std::map resolutions = { + {0,100.0f}, + {1,150.0f}, + {2,200.0f}, + {3,240.0f}, + {4,300.0f} +}; + +static std::map colorModes = { + {0,TWPT_RGB}, + {1,TWPT_GRAY}, + {2,TWPT_BW} +}; + +static std::map rotateDegrees = { + {0,0.0f}, + {1,90.0f}, + {2,180.0f}, + {3,270.0f} +}; +struct tagSCANCONFIGPARAM +{ + UINT32 ColorModal; + UINT32 PaperSize; + FLOAT Resoulation; + UINT32 DuplexType; + BOOL IsDoubleFeeded; + BOOL IsBingdingDetectable; + BOOL SkrewDetectable; + BOOL Is10BitTure; + BOOL Is11BitTure; + BOOL Is12BitTure; +}; + +typedef tagSCANCONFIGPARAM SCANCONFIGPARAM, PSCANCONFIGPARAM; + +struct tagIMAGEPROCESSPARAMS +{ + UINT32 PaperSize; + BOOL IsDiscardBlankPage; + BOOL IsFlodPages; + INT Brightness; + INT Contrast; + INT Gamma; + INT Filter; + BOOL IsFillBlack; + BOOL IsAutoCrop; + INT ScanCount; + INT Orentation; + BOOL IsBackImageFlip180; +}; + +typedef tagIMAGEPROCESSPARAMS IMAGEPROCESSPARAMS, PIMAGEPROCESSPARAMS; + +// CTwainUI 对话框 + +class CTwainUI : public CDialogEx +{ + DECLARE_DYNAMIC(CTwainUI) + +public: + CTwainUI(TwGlue glue, CWnd* pParent = nullptr); // 标准构造函数 + virtual ~CTwainUI(); + + void UpdateUI(CONFIGPARAMS configParams); + void UpDateScanParam(PCONFIGPARAMS pConfigItem, bool updateDs = true); + void UpdateListConfig(); + + void UpdateUi(); + + void EnableID_OKorID_Cancel(bool enable); + // 对话框数据 +#ifdef AFX_DESIGN_TIME + enum { IDD = IDD_TWAINUI }; +#endif + +protected: + virtual void DoDataExchange(CDataExchange* pDX); // DDX/DDV 支持 + virtual BOOL OnInitDialog(); + + DECLARE_MESSAGE_MAP() + afx_msg void OnBnClickedConfirm(); + afx_msg void OnBnClickedBtndefault(); + afx_msg void OnBnClickedCancel(); + afx_msg void OnBnClickedBtnhelp(); + afx_msg void OnBnClickedBtnbackupconfig(); + afx_msg void OnBnClickedBtnsaveconfig(); + afx_msg void OnBnClickedBtndeletconfig(); + afx_msg void OnBnClickedBtnrecoveryconfig(); + afx_msg void OnLbnSelchangeLstconfig(); + + std::unique_ptr m_tabCtrl; + std::unique_ptr m_pageBasic; + std::unique_ptr m_pageFeedPaper; + std::unique_ptr m_pageBrightness; + std::unique_ptr m_pageImageProc; + TwGlue m_glue; + + std::vector cfi; + int getResolutionIndex(int resolution); + int getPaparSizeIndex(int papersize,int orentation); + int getColorModelIndex(int pixtype); + std::vector getConfigFiles(); + std::unique_ptr settings; +}; diff --git a/huagao/Device/BlockingQueue.h b/huagao/Device/BlockingQueue.h new file mode 100644 index 00000000..a18fefa7 --- /dev/null +++ b/huagao/Device/BlockingQueue.h @@ -0,0 +1,80 @@ +#pragma once +#include +#include +#include + + +template +class BlockingQueue +{ +private: + BlockingQueue(const BlockingQueue& rhs); + BlockingQueue& operator =(const BlockingQueue& rhs); + mutable std::mutex _mutex; + std::condition_variable _condvar; + std::deque _queue; + volatile bool isShutDown = false; + T tRet; + +public: + BlockingQueue() + : _mutex() + , _condvar() + , _queue() + { + } + + ~BlockingQueue() + { + ShutDown(); + } + + void Clear() + { + std::lock_guard lock(_mutex); + _condvar.notify_all(); + _queue.clear(); + } + + void ShutDown() + { + isShutDown = true; + _condvar.notify_all(); + _queue.clear(); + } + + bool IsShutDown() + { + return isShutDown; + } + + void Put(const T task) + { + std::lock_guard lock(_mutex); + if (!isShutDown) { + _queue.push_back(task); + _condvar.notify_all(); + } + } + + T Take() + { + std::unique_lock lock(_mutex); + if (_queue.size() <= 0) + _condvar.wait(lock); + + if (isShutDown || _queue.empty()) + return tRet; + + T front(_queue.front()); + _queue.pop_front(); + + return front; + } + + size_t Size() const + { + std::lock_guard lock(_mutex); + return _queue.size(); + } +}; \ No newline at end of file diff --git a/huagao/Device/CJsonObject.cpp b/huagao/Device/CJsonObject.cpp new file mode 100644 index 00000000..55b3a451 --- /dev/null +++ b/huagao/Device/CJsonObject.cpp @@ -0,0 +1,2914 @@ +/******************************************************************************* + * Project: neb + * @file CJsonObject.cpp + * @brief + * @author bwarliao + * @date: 2014-7-16- + * @note + * Modify history: + ******************************************************************************/ +#include "stdafx.h" +#include "CJsonObject.hpp" +#include "cJSON.h" + + +namespace neb +{ + + CJsonObject::CJsonObject() + : m_pJsonData(NULL), m_pExternJsonDataRef(NULL) + { + // m_pJsonData = cJSON_CreateObject(); + } + + CJsonObject::CJsonObject(const std::string& strJson) + : m_pJsonData(NULL), m_pExternJsonDataRef(NULL) + { + Parse(strJson); + } + + CJsonObject::CJsonObject(const CJsonObject* pJsonObject) + : m_pJsonData(NULL), m_pExternJsonDataRef(NULL) + { + if (pJsonObject) + { + Parse(pJsonObject->ToString()); + } + } + + CJsonObject::CJsonObject(const CJsonObject& oJsonObject) + : m_pJsonData(NULL), m_pExternJsonDataRef(NULL) + { + Parse(oJsonObject.ToString()); + } + + CJsonObject::~CJsonObject() + { + Clear(); + } + + CJsonObject& CJsonObject::operator=(const CJsonObject& oJsonObject) + { + Parse(oJsonObject.ToString().c_str()); + return(*this); + } + + bool CJsonObject::operator==(const CJsonObject& oJsonObject) const + { + return(this->ToString() == oJsonObject.ToString()); + } + + bool CJsonObject::AddEmptySubObject(const std::string& strKey) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateObject(); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("create sub empty object error!"); + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + return(true); + } + + bool CJsonObject::AddEmptySubArray(const std::string& strKey) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateArray(); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("create sub empty array error!"); + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + return(true); + } + + CJsonObject& CJsonObject::operator[](const std::string& strKey) + { + std::map::iterator iter; + iter = m_mapJsonObjectRef.find(strKey); + if (iter == m_mapJsonObjectRef.end()) + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + CJsonObject* pJsonObject = new CJsonObject(); + m_mapJsonObjectRef.insert(std::pair(strKey, pJsonObject)); + return(*pJsonObject); + } + else + { + CJsonObject* pJsonObject = new CJsonObject(pJsonStruct); + m_mapJsonObjectRef.insert(std::pair(strKey, pJsonObject)); + return(*pJsonObject); + } + } + else + { + return(*(iter->second)); + } + } + + CJsonObject& CJsonObject::operator[](unsigned int uiWhich) + { + std::map::iterator iter; + iter = m_mapJsonArrayRef.find(uiWhich); + if (iter == m_mapJsonArrayRef.end()) + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, uiWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, uiWhich); + } + } + if (pJsonStruct == NULL) + { + CJsonObject* pJsonObject = new CJsonObject(); + m_mapJsonArrayRef.insert(std::pair(uiWhich, pJsonObject)); + return(*pJsonObject); + } + else + { + CJsonObject* pJsonObject = new CJsonObject(pJsonStruct); + m_mapJsonArrayRef.insert(std::pair(uiWhich, pJsonObject)); + return(*pJsonObject); + } + } + else + { + return(*(iter->second)); + } + } + + std::string CJsonObject::operator()(const std::string& strKey) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(std::string("")); + } + if (pJsonStruct->type == cJSON_String) + { + return(pJsonStruct->valuestring); + } + else if (pJsonStruct->type == cJSON_Int) + { + char szNumber[128] = { 0 }; + if (pJsonStruct->sign == -1) + { + if ((int64)pJsonStruct->valueint <= (int64)INT_MAX && (int64)pJsonStruct->valueint >= (int64)INT_MIN) + { + snprintf(szNumber, sizeof(szNumber), "%d", (int32)pJsonStruct->valueint); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%lld", (int64)pJsonStruct->valueint); + } + } + else + { + if (pJsonStruct->valueint <= (uint64)UINT_MAX) + { + snprintf(szNumber, sizeof(szNumber), "%u", (uint32)pJsonStruct->valueint); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%llu", pJsonStruct->valueint); + } + } + return(std::string(szNumber)); + } + else if (pJsonStruct->type == cJSON_Double) + { + char szNumber[128] = { 0 }; + if (fabs(pJsonStruct->valuedouble) < 1.0e-6 || fabs(pJsonStruct->valuedouble) > 1.0e9) + { + snprintf(szNumber, sizeof(szNumber), "%e", pJsonStruct->valuedouble); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%f", pJsonStruct->valuedouble); + } + } + else if (pJsonStruct->type == cJSON_False) + { + return(std::string("false")); + } + else if (pJsonStruct->type == cJSON_True) + { + return(std::string("true")); + } + return(std::string("")); + } + + std::string CJsonObject::operator()(unsigned int uiWhich) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, uiWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, uiWhich); + } + } + if (pJsonStruct == NULL) + { + return(std::string("")); + } + if (pJsonStruct->type == cJSON_String) + { + return(pJsonStruct->valuestring); + } + else if (pJsonStruct->type == cJSON_Int) + { + char szNumber[128] = { 0 }; + if (pJsonStruct->sign == -1) + { + if ((int64)pJsonStruct->valueint <= (int64)INT_MAX && (int64)pJsonStruct->valueint >= (int64)INT_MIN) + { + snprintf(szNumber, sizeof(szNumber), "%d", (int32)pJsonStruct->valueint); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%lld", (int64)pJsonStruct->valueint); + } + } + else + { + if (pJsonStruct->valueint <= (uint64)UINT_MAX) + { + snprintf(szNumber, sizeof(szNumber), "%u", (uint32)pJsonStruct->valueint); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%llu", pJsonStruct->valueint); + } + } + return(std::string(szNumber)); + } + else if (pJsonStruct->type == cJSON_Double) + { + char szNumber[128] = { 0 }; + if (fabs(pJsonStruct->valuedouble) < 1.0e-6 || fabs(pJsonStruct->valuedouble) > 1.0e9) + { + snprintf(szNumber, sizeof(szNumber), "%e", pJsonStruct->valuedouble); + } + else + { + snprintf(szNumber, sizeof(szNumber), "%f", pJsonStruct->valuedouble); + } + } + else if (pJsonStruct->type == cJSON_False) + { + return(std::string("false")); + } + else if (pJsonStruct->type == cJSON_True) + { + return(std::string("true")); + } + return(std::string("")); + } + + bool CJsonObject::Parse(const std::string& strJson) + { + Clear(); + m_pJsonData = cJSON_Parse(strJson.c_str()); + if (m_pJsonData == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + return(true); + } + + void CJsonObject::Clear() + { + m_pExternJsonDataRef = NULL; + if (m_pJsonData != NULL) + { + cJSON_Delete(m_pJsonData); + m_pJsonData = NULL; + } + for (std::map::iterator iter = m_mapJsonArrayRef.begin(); + iter != m_mapJsonArrayRef.end(); ++iter) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + } + m_mapJsonArrayRef.clear(); + for (std::map::iterator iter = m_mapJsonObjectRef.begin(); + iter != m_mapJsonObjectRef.end(); ++iter) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + } + m_mapJsonObjectRef.clear(); + } + + bool CJsonObject::IsEmpty() const + { + if (m_pJsonData != NULL) + { + return(false); + } + else if (m_pExternJsonDataRef != NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::IsArray() const + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + + if (pFocusData == NULL) + { + return(false); + } + + if (pFocusData->type == cJSON_Array) + { + return(true); + } + else + { + return(false); + } + } + + std::string CJsonObject::ToString() const + { + char* pJsonString = NULL; + std::string strJsonData = ""; + if (m_pJsonData != NULL) + { + pJsonString = cJSON_PrintUnformatted(m_pJsonData); + } + else if (m_pExternJsonDataRef != NULL) + { + pJsonString = cJSON_PrintUnformatted(m_pExternJsonDataRef); + } + if (pJsonString != NULL) + { + strJsonData = pJsonString; + free(pJsonString); + } + return(strJsonData); + } + + std::string CJsonObject::ToFormattedString() const + { + char* pJsonString = NULL; + std::string strJsonData = ""; + if (m_pJsonData != NULL) + { + pJsonString = cJSON_Print(m_pJsonData); + } + else if (m_pExternJsonDataRef != NULL) + { + pJsonString = cJSON_Print(m_pExternJsonDataRef); + } + if (pJsonString != NULL) + { + strJsonData = pJsonString; + free(pJsonString); + } + return(strJsonData); + } + + + bool CJsonObject::Get(const std::string& strKey, CJsonObject& oJsonObject) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + char* pJsonString = cJSON_Print(pJsonStruct); + std::string strJsonData = pJsonString; + free(pJsonString); + if (oJsonObject.Parse(strJsonData)) + { + return(true); + } + else + { + return(false); + } + } + + bool CJsonObject::Get(const std::string& strKey, std::string& strValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_String) + { + return(false); + } + strValue = pJsonStruct->valuestring; + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, int32& iValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + iValue = (int32)(pJsonStruct->valueint); + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, uint32& uiValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + uiValue = (uint32)(pJsonStruct->valueint); + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, int64& llValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + llValue = (int64)pJsonStruct->valueint; + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, uint64& ullValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + ullValue = (uint64)pJsonStruct->valueint; + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, bool& bValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type > cJSON_True) + { + return(false); + } + bValue = pJsonStruct->type; + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, float& fValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Double) + { + return(false); + } + fValue = (float)(pJsonStruct->valuedouble); + return(true); + } + + bool CJsonObject::Get(const std::string& strKey, double& dValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pJsonData, strKey.c_str()); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Object) + { + pJsonStruct = cJSON_GetObjectItem(m_pExternJsonDataRef, strKey.c_str()); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Double) + { + return(false); + } + dValue = pJsonStruct->valuedouble; + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, const CJsonObject& oJsonObject) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_Parse(oJsonObject.ToString().c_str()); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + std::map::iterator iter = m_mapJsonObjectRef.find(strKey); + if (iter != m_mapJsonObjectRef.end()) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonObjectRef.erase(iter); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, const std::string& strValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateString(strValue.c_str()); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, int32 iValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)iValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, uint32 uiValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)uiValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, int64 llValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)llValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, uint64 ullValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt(ullValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, bool bValue, bool bValueAgain) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateBool(bValue); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, float fValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)fValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(const std::string& strKey, double dValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateObject(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)dValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_AddItemToObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Delete(const std::string& strKey) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON_DeleteItemFromObject(pFocusData, strKey.c_str()); + std::map::iterator iter = m_mapJsonObjectRef.find(strKey); + if (iter != m_mapJsonObjectRef.end()) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonObjectRef.erase(iter); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, const CJsonObject& oJsonObject) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_Parse(oJsonObject.ToString().c_str()); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + std::map::iterator iter = m_mapJsonObjectRef.find(strKey); + if (iter != m_mapJsonObjectRef.end()) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonObjectRef.erase(iter); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, const std::string& strValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateString(strValue.c_str()); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, int32 iValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)iValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, uint32 uiValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)uiValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, int64 llValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)llValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, uint64 ullValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)ullValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, bool bValue, bool bValueAgain) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateBool(bValue); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, float fValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)fValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(const std::string& strKey, double dValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Object) + { + m_strErrMsg = "not a json object! json array?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)dValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInObject(pFocusData, strKey.c_str(), pJsonStruct); + if (cJSON_GetObjectItem(pFocusData, strKey.c_str()) == NULL) + { + return(false); + } + return(true); + } + + int CJsonObject::GetArraySize() + { + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + return(cJSON_GetArraySize(m_pJsonData)); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + return(cJSON_GetArraySize(m_pExternJsonDataRef)); + } + } + return(0); + } + + bool CJsonObject::Get(int iWhich, CJsonObject& oJsonObject) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + char* pJsonString = cJSON_Print(pJsonStruct); + std::string strJsonData = pJsonString; + free(pJsonString); + if (oJsonObject.Parse(strJsonData)) + { + return(true); + } + else + { + return(false); + } + } + + bool CJsonObject::Get(int iWhich, std::string& strValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_String) + { + return(false); + } + strValue = pJsonStruct->valuestring; + return(true); + } + + bool CJsonObject::Get(int iWhich, int32& iValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + iValue = (int32)(pJsonStruct->valueint); + return(true); + } + + bool CJsonObject::Get(int iWhich, uint32& uiValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + uiValue = (uint32)(pJsonStruct->valueint); + return(true); + } + + bool CJsonObject::Get(int iWhich, int64& llValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + llValue = (int64)pJsonStruct->valueint; + return(true); + } + + bool CJsonObject::Get(int iWhich, uint64& ullValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Int) + { + return(false); + } + ullValue = (uint64)pJsonStruct->valueint; + return(true); + } + + bool CJsonObject::Get(int iWhich, bool& bValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type > cJSON_True) + { + return(false); + } + bValue = pJsonStruct->type; + return(true); + } + + bool CJsonObject::Get(int iWhich, float& fValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Double) + { + return(false); + } + fValue = (float)(pJsonStruct->valuedouble); + return(true); + } + + bool CJsonObject::Get(int iWhich, double& dValue) const + { + cJSON* pJsonStruct = NULL; + if (m_pJsonData != NULL) + { + if (m_pJsonData->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pJsonData, iWhich); + } + } + else if (m_pExternJsonDataRef != NULL) + { + if (m_pExternJsonDataRef->type == cJSON_Array) + { + pJsonStruct = cJSON_GetArrayItem(m_pExternJsonDataRef, iWhich); + } + } + if (pJsonStruct == NULL) + { + return(false); + } + if (pJsonStruct->type != cJSON_Double) + { + return(false); + } + dValue = pJsonStruct->valuedouble; + return(true); + } + + bool CJsonObject::Add(const CJsonObject& oJsonObject) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_Parse(oJsonObject.ToString().c_str()); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + unsigned int uiLastIndex = (unsigned int)cJSON_GetArraySize(pFocusData) - 1; + for (std::map::iterator iter = m_mapJsonArrayRef.begin(); + iter != m_mapJsonArrayRef.end(); ) + { + if (iter->first >= uiLastIndex) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonArrayRef.erase(iter++); + } + else + { + iter++; + } + } + return(true); + } + + bool CJsonObject::Add(const std::string& strValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateString(strValue.c_str()); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(int32 iValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)iValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(uint32 uiValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)uiValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(int64 llValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)llValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(uint64 ullValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)ullValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(int iAnywhere, bool bValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateBool(bValue); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(float fValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)fValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Add(double dValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)dValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArray(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(const CJsonObject& oJsonObject) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_Parse(oJsonObject.ToString().c_str()); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + for (std::map::iterator iter = m_mapJsonArrayRef.begin(); + iter != m_mapJsonArrayRef.end(); ) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonArrayRef.erase(iter++); + } + return(true); + } + + bool CJsonObject::AddAsFirst(const std::string& strValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateString(strValue.c_str()); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(int32 iValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)iValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(uint32 uiValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)uiValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(int64 llValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)llValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(uint64 ullValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)ullValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(int iAnywhere, bool bValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateBool(bValue); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(float fValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)fValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::AddAsFirst(double dValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData != NULL) + { + pFocusData = m_pJsonData; + } + else if (m_pExternJsonDataRef != NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + m_pJsonData = cJSON_CreateArray(); + pFocusData = m_pJsonData; + } + + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)dValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + int iArraySizeBeforeAdd = cJSON_GetArraySize(pFocusData); + cJSON_AddItemToArrayHead(pFocusData, pJsonStruct); + int iArraySizeAfterAdd = cJSON_GetArraySize(pFocusData); + if (iArraySizeAfterAdd == iArraySizeBeforeAdd) + { + return(false); + } + return(true); + } + + bool CJsonObject::Delete(int iWhich) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON_DeleteItemFromArray(pFocusData, iWhich); + for (std::map::iterator iter = m_mapJsonArrayRef.begin(); + iter != m_mapJsonArrayRef.end(); ) + { + if (iter->first >= (unsigned int)iWhich) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonArrayRef.erase(iter++); + } + else + { + iter++; + } + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, const CJsonObject& oJsonObject) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_Parse(oJsonObject.ToString().c_str()); + if (pJsonStruct == NULL) + { + m_strErrMsg = std::string("prase json string error at ") + cJSON_GetErrorPtr(); + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + std::map::iterator iter = m_mapJsonArrayRef.find(iWhich); + if (iter != m_mapJsonArrayRef.end()) + { + if (iter->second != NULL) + { + delete (iter->second); + iter->second = NULL; + } + m_mapJsonArrayRef.erase(iter); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, const std::string& strValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateString(strValue.c_str()); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, int32 iValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)iValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, uint32 uiValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)uiValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, int64 llValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)((uint64)llValue), -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, uint64 ullValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateInt((uint64)ullValue, 1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, bool bValue, bool bValueAgain) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateBool(bValue); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, float fValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)fValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + bool CJsonObject::Replace(int iWhich, double dValue) + { + cJSON* pFocusData = NULL; + if (m_pJsonData == NULL) + { + pFocusData = m_pExternJsonDataRef; + } + else + { + pFocusData = m_pJsonData; + } + if (pFocusData == NULL) + { + m_strErrMsg = "json data is null!"; + return(false); + } + if (pFocusData->type != cJSON_Array) + { + m_strErrMsg = "not a json array! json object?"; + return(false); + } + cJSON* pJsonStruct = cJSON_CreateDouble((double)dValue, -1); + if (pJsonStruct == NULL) + { + return(false); + } + cJSON_ReplaceItemInArray(pFocusData, iWhich, pJsonStruct); + if (cJSON_GetArrayItem(pFocusData, iWhich) == NULL) + { + return(false); + } + return(true); + } + + CJsonObject::CJsonObject(cJSON* pJsonData) + : m_pJsonData(NULL), m_pExternJsonDataRef(pJsonData) + { + } + +} + + diff --git a/huagao/Device/CJsonObject.hpp b/huagao/Device/CJsonObject.hpp new file mode 100644 index 00000000..83d4deff --- /dev/null +++ b/huagao/Device/CJsonObject.hpp @@ -0,0 +1,153 @@ +/******************************************************************************* + * Project: neb + * @file CJsonObject.hpp + * @brief Json + * @author bwarliao + * @date: 2014-7-16 + * @note + * Modify history: + ******************************************************************************/ + +#ifndef CJSONOBJECT_HPP_ +#define CJSONOBJECT_HPP_ + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#ifdef __cplusplus +extern "C" +{ +#endif +typedef struct cJSON cJSON; + +#ifdef __cplusplus +} +#endif + + +namespace neb +{ +typedef int int32; +typedef unsigned int uint32; +typedef long long int64; +typedef unsigned long long uint64; + +class CJsonObject +{ +public: // method of ordinary json object or json array + CJsonObject(); + CJsonObject(const std::string& strJson); + CJsonObject(const CJsonObject* pJsonObject); + CJsonObject(const CJsonObject& oJsonObject); + virtual ~CJsonObject(); + + CJsonObject& operator=(const CJsonObject& oJsonObject); + bool operator==(const CJsonObject& oJsonObject) const; + bool Parse(const std::string& strJson); + void Clear(); + bool IsEmpty() const; + bool IsArray() const; + std::string ToString() const; + std::string ToFormattedString() const; + const std::string& GetErrMsg() const + { + return(m_strErrMsg); + } + +public: // method of ordinary json object + bool AddEmptySubObject(const std::string& strKey); + bool AddEmptySubArray(const std::string& strKey); + CJsonObject& operator[](const std::string& strKey); + std::string operator()(const std::string& strKey) const; + bool Get(const std::string& strKey, CJsonObject& oJsonObject) const; + bool Get(const std::string& strKey, std::string& strValue) const; + bool Get(const std::string& strKey, int32& iValue) const; + bool Get(const std::string& strKey, uint32& uiValue) const; + bool Get(const std::string& strKey, int64& llValue) const; + bool Get(const std::string& strKey, uint64& ullValue) const; + bool Get(const std::string& strKey, bool& bValue) const; + bool Get(const std::string& strKey, float& fValue) const; + bool Get(const std::string& strKey, double& dValue) const; + bool Add(const std::string& strKey, const CJsonObject& oJsonObject); + bool Add(const std::string& strKey, const std::string& strValue); + bool Add(const std::string& strKey, int32 iValue); + bool Add(const std::string& strKey, uint32 uiValue); + bool Add(const std::string& strKey, int64 llValue); + bool Add(const std::string& strKey, uint64 ullValue); + bool Add(const std::string& strKey, bool bValue, bool bValueAgain); + bool Add(const std::string& strKey, float fValue); + bool Add(const std::string& strKey, double dValue); + bool Delete(const std::string& strKey); + bool Replace(const std::string& strKey, const CJsonObject& oJsonObject); + bool Replace(const std::string& strKey, const std::string& strValue); + bool Replace(const std::string& strKey, int32 iValue); + bool Replace(const std::string& strKey, uint32 uiValue); + bool Replace(const std::string& strKey, int64 llValue); + bool Replace(const std::string& strKey, uint64 ullValue); + bool Replace(const std::string& strKey, bool bValue, bool bValueAgain); + bool Replace(const std::string& strKey, float fValue); + bool Replace(const std::string& strKey, double dValue); + +public: // method of json array + int GetArraySize(); + CJsonObject& operator[](unsigned int uiWhich); + std::string operator()(unsigned int uiWhich) const; + bool Get(int iWhich, CJsonObject& oJsonObject) const; + bool Get(int iWhich, std::string& strValue) const; + bool Get(int iWhich, int32& iValue) const; + bool Get(int iWhich, uint32& uiValue) const; + bool Get(int iWhich, int64& llValue) const; + bool Get(int iWhich, uint64& ullValue) const; + bool Get(int iWhich, bool& bValue) const; + bool Get(int iWhich, float& fValue) const; + bool Get(int iWhich, double& dValue) const; + bool Add(const CJsonObject& oJsonObject); + bool Add(const std::string& strValue); + bool Add(int32 iValue); + bool Add(uint32 uiValue); + bool Add(int64 llValue); + bool Add(uint64 ullValue); + bool Add(int iAnywhere, bool bValue); + bool Add(float fValue); + bool Add(double dValue); + bool AddAsFirst(const CJsonObject& oJsonObject); + bool AddAsFirst(const std::string& strValue); + bool AddAsFirst(int32 iValue); + bool AddAsFirst(uint32 uiValue); + bool AddAsFirst(int64 llValue); + bool AddAsFirst(uint64 ullValue); + bool AddAsFirst(int iAnywhere, bool bValue); + bool AddAsFirst(float fValue); + bool AddAsFirst(double dValue); + bool Delete(int iWhich); + bool Replace(int iWhich, const CJsonObject& oJsonObject); + bool Replace(int iWhich, const std::string& strValue); + bool Replace(int iWhich, int32 iValue); + bool Replace(int iWhich, uint32 uiValue); + bool Replace(int iWhich, int64 llValue); + bool Replace(int iWhich, uint64 ullValue); + bool Replace(int iWhich, bool bValue, bool bValueAgain); + bool Replace(int iWhich, float fValue); + bool Replace(int iWhich, double dValue); + +private: + CJsonObject(cJSON* pJsonData); + +private: + cJSON* m_pJsonData; + cJSON* m_pExternJsonDataRef; + std::string m_strErrMsg; + std::map m_mapJsonArrayRef; + std::map m_mapJsonObjectRef; +}; + +} + +#endif /* CJSONHELPER_HPP_ */ diff --git a/huagao/Device/GDevice.cpp b/huagao/Device/GDevice.cpp new file mode 100644 index 00000000..3f89f10f --- /dev/null +++ b/huagao/Device/GDevice.cpp @@ -0,0 +1,545 @@ +#include "stdafx.h" +#include "GDevice.h" +#include "IUsb.h" +#include +#include +#include +#include +#include +#include +#include +#include +#include "StopWatch.h" +#include "device_common.h" +#include "GScan200.h" + +#ifndef WIN32 + #include +#endif + +#include + +#define DSP_CODE_ADDR 0 +#define USER_ADDR 0x4000 + +using namespace std; +//class GScan200; + + +GDevice::GDevice(std::shared_ptr usb) +{ + m_bScan = false; + m_bListen = false; + m_usb = usb; + event_call = NULL; + image_call = NULL; + m_imagecall_userdata = NULL; + m_eventcall_userdata = NULL; + m_threadInt = NULL; + m_threadrecv = NULL; + m_run = false; +} + +GDevice::~GDevice() +{ + close(); +} + +bool GDevice::open() +{ + if (is_open()) + return true; + + if (m_usb && m_usb->open()) { + m_usb->set_timeout(1000); + init_cam(); + m_bListen = true; + m_bScan = true; + + if (m_threadInt) { + m_bListen = false; + m_threadInt->join(); + } + + if (m_threadrecv) { + m_bScan = false; + m_threadrecv->join(); + } + m_bListen = true; + m_bScan = true; + m_threadInt = std::shared_ptr(new std::thread(&GDevice::Int_main, this)); + m_threadrecv = std::shared_ptr(new std::thread(&GDevice::recv_main, this)); + return true; + } + return false; +} + +void GDevice::close() +{ + if (m_usb.get() && m_usb->is_open()) { + m_usb->set_timeout(100); + stop(); + + if (m_threadInt && m_threadInt->joinable()) { + m_bListen = false; + this_thread::sleep_for(std::chrono::milliseconds(100)); + m_threadInt->join(); + m_threadInt = NULL; + } + + if (m_threadrecv && m_threadrecv->joinable()) { + m_bScan = false; + image_indexs.ShutDown(); + m_threadrecv->join(); + m_threadrecv = NULL; + } + m_usb->close(); + } +} + +bool GDevice::is_open() +{ + if (m_usb.get()) + return m_usb->is_open(); + return false; +} + +bool GDevice::start(image_callback callfunc, void* userdata) +{ + if (is_run()) + return false; + + image_call = callfunc; + m_imagecall_userdata = userdata; + MotorSetting ms; + ms.value = read_reg(MOTOR_BOARD, 0x00); + ms.scan_enable = 0; + write_reg(MOTOR_BOARD, 0x00, ms.value); + ms.scan_enable = 1; + write_reg(MOTOR_BOARD, 0x00, ms.value); + m_run = true; + return true; +} + +void GDevice::set_event_call(event_callback callfunc, void* userdata) +{ + m_eventcall_userdata = userdata; + event_call = callfunc; +} + +void GDevice::stop() +{ + set_option(Cam_Options::scanner_stop_motor, 0); +} + +int GDevice::is_run() +{ + return m_run; +} + +void GDevice::reset() +{ + +} + +static std::string read_all_from(std::string path) +{ + int t; + FILE* file = fopen(path.c_str(), "rb"); + fseek(file, 0, SEEK_END); + t = ftell(file); + std::string buf(t, 0); + fseek(file, 0, SEEK_SET); + fread((void*)buf.c_str(), t, 1, file); + fclose(file); + return buf; +} + +void GDevice::write_dsp_fw(std::string path) +{ + std::string buf = read_all_from(path); + write_flash(DSP_CODE_ADDR, (void*)buf.c_str(), buf.size()); +} + +void GDevice::write_pid(unsigned short pid) +{ + write_flash(PID_ADDR, &pid, sizeof(pid)); +} + +unsigned short GDevice::read_pid() +{ + unsigned short pid; + read_flash(PID_ADDR, &pid, sizeof(pid)); + return pid; +} + + +void GDevice::write_devname(std::string name) +{ + if (name.size() > 64) + return; + + write_flash(DEVNAME_ADDR, (void*)name.c_str(), name.size()); +} + +std::string GDevice::read_devname() +{ + char devname[65] = {0}; + read_flash(DEVNAME_ADDR, devname, sizeof(devname) - 1); + return devname; +} + +bool GDevice::write_flash(unsigned int addr, void* data, int size) +{ + unsigned int writeAddr = addr; + int writed = 0; + int writing = 0; + while (writed < size) { + writing = min(crtlBufferSize, size - writed); + writeAddr = addr + writed; + { + std::lock_guard lck(m_mtxCtrl); + m_usb->control_msg(to_device, flash_access, ((Reg2Short*)&writeAddr)->short2, ((Reg2Short*)&writeAddr)->short1, writing, (unsigned char*)data + writed); + } + writed += writing; + } + return true; +} + +bool GDevice::read_flash(unsigned int addr, void* data, int size) +{ + unsigned int readAddr = addr; + int readed = 0; + int reading = 0; + while (readed < size) { + reading = min(crtlBufferSize, size - readed); + readAddr = addr + readed; + { + std::lock_guard lck(m_mtxCtrl); + m_usb->control_msg(from_device, flash_access, ((Reg2Short*)&readAddr)->short2, ((Reg2Short*)&readAddr)->short1, reading, (unsigned char*)data + readed); + } + readed += reading; + } + return true; +} + +const int int_buffer_size = 1024; +int index_count = 0; +static void write_log(std::string fullname, std::string log) +{ + std::string savepath; + savepath = fullname; + std::ofstream ofs(savepath, std::ios::app); + + SYSTEMTIME sys; + GetLocalTime(&sys); + ofs << sys.wYear << "/" << sys.wMonth << "/" << sys.wDay << " " << sys.wHour << ":" << sys.wMinute << ":" << sys.wSecond << ":" << sys.wMilliseconds << " " << log << std::endl; +} +int image_index_c = 0; +void GDevice::recv_main() +{ + const double timeout_ratio = (1000.0 / (15.0 * 1024 * 1024)); //!< s / Mbyte + int image_index = 0; + int buffer_size = 0; + int b_buffer_size = 0; + int f_buffer_size = 0; + unsigned char* bbuf = 0; + unsigned char* fbuf = 0; + unsigned char* buf; + int buffer_reading = 0; + int buffer_readed = 0; + const int read_timeout = 5000; + std::vector image_data; + StopWatch sw; + while (m_bScan) { + image_index = image_indexs.Take(); + if (!image_indexs.IsShutDown() && image_index >= 0) + { + buffer_reading = 0; + buffer_readed = 0; + buffer_size = frame_size(image_index); + image_data.resize(buffer_size * 2 + int_buffer_size); + buf = image_data.data() + int_buffer_size; + + sw.reset(); + while (sw.elapsed_ms() < read_timeout) { + while (DataOn() && sw.elapsed_ms() < read_timeout); + read_frame(image_index, buffer_readed); + buffer_reading = max(0, buffer_size - buffer_readed); + buffer_reading = read_data(buf + buffer_readed, buffer_reading, (int)(buffer_reading * timeout_ratio)); + if (buffer_reading > 0) + buffer_readed += buffer_reading; + + if (buffer_readed >= buffer_size) { + write_log("d:\\1.txt", std::to_string(image_index_c) + " time1 = " + std::to_string(sw.elapsed_ms())); + break; + } + } + + image_index_c++; + if (buffer_readed != buffer_size) + { + write_log("d:\\1.txt", std::to_string(image_index_c) + " error readed:" + std::to_string(buffer_readed) + " per read:" + std::to_string(buffer_size) + " time = " + std::to_string(sw.elapsed_ms())); + } + else { + write_log("d:\\1.txt", std::to_string(image_index_c) + " get" + " time = " + std::to_string(sw.elapsed_ms())); + } + + b_buffer_size = 0; + f_buffer_size = 0; + bbuf = buf - int_buffer_size; + fbuf = buf + buffer_size; + for (int i = 0; i < (buffer_size / int_buffer_size); i++) + { + if (buf[(i + 1) * int_buffer_size - 1] == 0) + { + memcpy(bbuf + b_buffer_size, buf + i * int_buffer_size, int_buffer_size - 1); + b_buffer_size += (int_buffer_size - 1); + } + else if (buf[(i + 1) * int_buffer_size - 1] == 255) + { + memcpy(fbuf + f_buffer_size, buf + i * int_buffer_size, int_buffer_size - 1); + f_buffer_size += (int_buffer_size - 1); + } + } + + if (image_call) + { + if ((bbuf != NULL && b_buffer_size > 0)&&(fbuf != NULL && f_buffer_size > 0)) + { + image_call(bbuf, b_buffer_size, fbuf, f_buffer_size, m_imagecall_userdata); + } + } + } + } +} + +void GDevice::Int_main() +{ + unsigned int int_buffer[4]; + int size = 0; + while (m_bListen) { + size = m_usb->read_int(int_buffer, sizeof(int_buffer)); + if (size >= 16) + { + if (int_buffer[2] != 0) + { + image_indexs.Put(int_buffer[1]); + } + MotorStatus* ms = (MotorStatus*)int_buffer; + + //int ret = get_option(Cam_Options::scanner_scan_status); + //XdPrint("scanner_scan_status %d \n",ret); + //if (!ret)//幤 + //{ + // XdPrint("scanner stoped 1\n"); + // ((GScan200*)m_eventcall_userdata)->set_scan_status(false);//ֹͣ쳣ֹͣʱ֪ͨͼ߳ɨֹͣ + // m_run = false; + // XdPrint("scanner stoped 2\n"); + //} + //else + //{ + // XdPrint("scanner is scanning \n"); + //} + //if (ms->value && 0x7fe) { + // if(m_eventcall_userdata){ + // + // } + + //} + if (event_call) + { + //0x3fe ==>b 1111 1111 10 쳣λЧʱ + if (ms->value & 0x3fe) { + ((GScan200*)m_eventcall_userdata)->set_scan_status(false); + event_call(ms->value, m_eventcall_userdata); + m_run = false; + } + } + } + int ret = get_option(Cam_Options::scanner_scan_status); + if (m_run&&!ret)//幤 + { + ((GScan200*)m_eventcall_userdata)->set_scan_status(false);//ֹͣ쳣ֹͣʱ֪ͨͼ߳ɨֹͣ + m_run = false; + } + } +} + +void GDevice::init_cam() +{ +} + +int GDevice::read_data(void* data, int length, int timeout) +{ + int readed = 0; + int reading = 0; + StopWatch sw; + while (readed < length && sw.elapsed_ms() < timeout) { + reading = max(0, min(length - readed, buffer_size)); + reading = m_usb->read_bulk((unsigned char*)data + readed, reading); + if (reading > 0) { + readed += reading; + } + } + return readed; +} + +void GDevice::read_frame(int index, int offset) +{ + write_reg(3, index, offset); +} + +int GDevice::frame_size(int index) +{ + return read_reg(3, index); +} + +int GDevice::read_reg(int type, int addr) +{ + int value; + std::lock_guard lck(m_mtxCtrl); + m_usb->control_msg(from_device, regs_access, type, addr, sizeof(value), &value); + return value; +} + + +void GDevice::write_reg(int type, int addr, int value) +{ + std::lock_guard lck(m_mtxCtrl); + m_usb->control_msg(to_device, regs_access, type, addr, sizeof(value), &value); +} + +void GDevice::set_option(Cam_Options option, unsigned int value) +{ + unsigned int val = 0; + switch (option) + { + case scanner_config: + write_reg(USERDEFINE, ModeParam, value); + break; + case scanner_scan_skrew: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->skew_enable = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_stample_enable: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->staple_enable = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_doublePape_enable: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->double_paper = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_stop_motor: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->scan_enable = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_error_clean: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->error_clean = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_Init_Status: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->status_init = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_IIC_Config: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->iic_config = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + case scanner_Speed_Config: + val = read_reg(MOTOR_BOARD, 0x00); + ((MotorSetting*)& val)->speed_set_enable = value; + write_reg(MOTOR_BOARD, 0x00, val); + break; + default: + break; + } +} + +int GDevice::get_option(Cam_Options option) +{ + int value = 0; + switch (option) + { + case scanner_cover_status: + value = read_reg(1, 0x01); + value = ((MotorStatus*)& value)->open_machine; + break; + case scanner_pick_paper_stauts: + value = read_reg(1, 0x01); + value = ((MotorStatus*)& value)->pick_failed; + break; + case scanner_jam_stauts: + value = read_reg(1, 0x01); + value = ((MotorStatus*)& value)->stop_jam; + break; + case scanner_paper_count: + value = read_reg(1, 0x02); + value = ((MotorMode*)& value)->scan_num; + break; + case scanner_double_paper: + value = read_reg(1, 0x01); + value= ((MotorStatus*)& value)->double_paper; + break; + case scanner_staple_state: + value = read_reg(1, 0x01); + value = ((MotorStatus*)& value)->staple; + break; + case scanner_skrew_state: + value = read_reg(1, 0x01); + value = ((MotorStatus*)& value)->papertilted; + break; + case scanner_paper_have: + value = read_reg(MOTOR_BOARD, 0x02); + value = ((Motor_Mode*)& value)->feeding_paper_ready; + break; + case scanner_scan_status: + value = read_reg(MOTOR_BOARD, 0x02); + value = ((Motor_Mode*)& value)->scan_status; + break; + default: + break; + } + return value; +} + +std::vector GDevice::support_options() +{ + std::set options; + options.insert(Cam_Options::scanner_exposure_blue); + options.insert(Cam_Options::scanner_exposure_gray); + options.insert(Cam_Options::scanner_exposure_red); + + return std::vector(options.begin(), options.end()); +} + +void GDevice::pick_paper(void) +{ + MotorSetting ms; + ms.value = read_reg(MOTOR_BOARD, 0x00); + ms.pick_paper = 0; + write_reg(MOTOR_BOARD, 0x00, ms.value); + ms.pick_paper = 1; + write_reg(MOTOR_BOARD, 0x00, ms.value); +} + +void GDevice::trigger_scan(void) +{ + ScanTriger st; + st.value = 0; + write_reg(MAIN_BOARD, 0x02, st.value); + st.triger = 1; + write_reg(MAIN_BOARD, 0x02, st.value); +} + +bool GDevice::DataOn() +{ + return read_reg(USERDEFINE, IMAGEREGS); +} diff --git a/huagao/Device/GDevice.h b/huagao/Device/GDevice.h new file mode 100644 index 00000000..723a0044 --- /dev/null +++ b/huagao/Device/GDevice.h @@ -0,0 +1,88 @@ +#pragma once +#include "IGDevice.h" +#include +#include +#include +#include "BlockingQueue.h" +#include + +class IUsb; +class GDevice : public IGDevice +{ +public: + GDevice(std::shared_ptr usb); + virtual ~GDevice(); + // ͨ IGDevice ̳ + virtual bool open() override; + virtual void close() override; + virtual bool is_open() override; + bool start(image_callback callfunc, void* userdata); + void set_event_call(event_callback event_callfunc, void* userdata); + virtual void stop() override; + virtual int is_run() override; + virtual void reset() override; + + void write_dsp_fw(std::string path); + + void write_devname(std::string name); + std::string read_devname(); + + void write_reg(int type, int addr, int value); + int read_reg(int type, int addr); + + bool write_flash(unsigned int addr, void* data, int size); + bool read_flash(unsigned int addr, void* data, int size); + + void trigger_scan(void); + + void write_pid(unsigned short pid); + unsigned short read_pid(); + +private: + void recv_main(); + void Int_main(); + + void init_cam(); + + int read_data(void* data, int lenght, int timeout); + void read_frame(int index, int offset); + int frame_size(int index); + + + + + void pick_paper(void); + + bool DataOn(); + + std::shared_ptr m_usb; + const int buffer_size = 1204 * 1024; + const int crtlBufferSize = 512; + volatile bool m_bScan; + volatile bool m_bListen; + + std::shared_ptr m_threadInt; + std::shared_ptr m_threadrecv; + std::mutex m_mtxInt; + std::mutex m_mtxCtrl; + image_callback image_call; + event_callback event_call; + const int to_device = 0x40; + const int from_device = 0xc0; + const int regs_access = 0x0c; + const int flash_access = 0x04; + + const int regs_req = 0x0c; + + BlockingQueue image_indexs; + + void* m_imagecall_userdata; + void* m_eventcall_userdata; + volatile bool m_run; + + + // ͨ IGDevice ̳ + virtual void set_option(Cam_Options option,unsigned int value) override; + virtual int get_option(Cam_Options option) override; + virtual std::vector support_options() override; +}; diff --git a/huagao/Device/GDeviceLists.cpp b/huagao/Device/GDeviceLists.cpp new file mode 100644 index 00000000..4e074576 --- /dev/null +++ b/huagao/Device/GDeviceLists.cpp @@ -0,0 +1,19 @@ +#include "stdafx.h" +#include "GDeviceLists.h" +#include "UsbScanEx.h" +#include "GDevice.h" + + + std::list> HGDeviceLists::FindAll() + { + std::list> cameraLists; + + // std::list> usbs = CyUsbList::find_vid_pid(0x04b4, 0x1004); + std::list> usbs = UsbScan_List::find_vid_pid(0x064b, 0x7823); + + + for (auto i = usbs.begin(); i != usbs.end(); i++) + cameraLists.push_back(std::shared_ptr(new GDevice(*i))); + + return cameraLists; + } diff --git a/huagao/Device/GDeviceLists.h b/huagao/Device/GDeviceLists.h new file mode 100644 index 00000000..8d19ad91 --- /dev/null +++ b/huagao/Device/GDeviceLists.h @@ -0,0 +1,12 @@ +#pragma once +#include +#include + + +class IGDevice; + +class HGDeviceLists +{ +public: + static std::list> FindAll(); +}; diff --git a/huagao/Device/GScan.cpp b/huagao/Device/GScan.cpp new file mode 100644 index 00000000..ecdc308a --- /dev/null +++ b/huagao/Device/GScan.cpp @@ -0,0 +1,41 @@ +#include "stdafx.h" +#include "GScan.h" +#include "stdio.h" +#include +#include "jpeglib.h" +#include "ImageProcess/ImageApplyHeaders.h" +#include "ImageMatQueue.h" + + +GScan::GScan() + :pixType(0) + , m_pImages(new ImageMatQueue()) +{ + devState = DEV_STOP; + Error_Code = 0; +} + +GScan::~GScan() +{ +} + +void DoEvents() +{ + MSG msg; + if (PeekMessage(&msg , NULL, 0, 0, PM_REMOVE)) { + DispatchMessage(&msg); + TranslateMessage(&msg); + } +} + +void GScan::trim(std::string &s) +{ + int index = 0; + if (!s.empty()) { + while ((index = s.find(' ', index)) != string::npos) + s.erase(index, 1); + } +} + + + diff --git a/huagao/Device/GScan.h b/huagao/Device/GScan.h new file mode 100644 index 00000000..e5400d26 --- /dev/null +++ b/huagao/Device/GScan.h @@ -0,0 +1,130 @@ +#pragma once +#include +#include +#include +#include +#include +#include +#include +#include +#include "PublicFunc.h" + + +enum tagDevState +{ + DEV_STOP = -1, + DEV_ISRUNNING, + DEV_WRONG +}; + +typedef enum tagDevState DevState, PDevState; + +enum tagEventIndex +{ + EVENT_IMAGE, + EVENT_NUM +}; + +class DiscardBlank; +class CImageApply; + +class IGScan +{ +public: + virtual ~IGScan()=0 {}; + + virtual void open(int vid, int pid) = 0;; + virtual int aquire_bmpdata(std::vector& bmpdata) = 0; + virtual BOOL IsConnected() = 0; + virtual std::string GetFWVersion() = 0; + virtual std::string GetSerialNum() = 0; + virtual bool is_scan() = 0; + virtual BOOL Get_Scanner_PaperOn() = 0; + virtual void config_params(GScanCap& params) = 0; + virtual void Scanner_StartScan(UINT16 count) = 0; + virtual void Stop_scan() = 0; + virtual void ResetScanner() =0; + virtual bool Get_IsImageQueueEmpty() = 0; + virtual void reset() = 0; + + virtual void setdecodepixtype(int twpixtype)= 0; + virtual UINT32 get_ErrorCode() = 0; + virtual void Set_ErrorCode(UINT32 value) = 0; + virtual int get_scanned_num() = 0; +}; + +class IUsb; +class ImageMatQueue; + +class GScan +{ +public: + GScan(); + virtual ~GScan(); + +protected: + volatile UINT32 Error_Code; + + + void trim(std::string &s); + volatile int devState; + std::shared_ptr m_pImages; + + std::mutex m_Locker; + std::mutex m_imgLocker; + std::string fwVersion; + std::string SerialNum; + int pixType; +}; + + + +//u32_Data +typedef enum tagUsbSupported { + //ֹͣɨ + SCAN_STOP = -2, + //쳣 + HAVE_ERROR = -1, + //״̬ + NORMAL = 0, + // + OPEN_COVER = 1, + // ֽ + NO_FEED = 2, + // ֽʧ + FEED_IN_ERROR = 4, + // ֽ + PAPER_JAM = 8, + // ⵽˫ + DETECT_DOUBLE_FEED = 16, + // ⵽鶤 + DETECT_STAPLE = 32, + // ֽб + PAPER_SKEW = 64, + // Զģʽ + AUTO_SCAN_MODE = 65, + // ֶģʽ + MANAUL_SCAN_MODE = 66, + // ģʽ + COUNT_MODE = 67, + // Ӳ + HARDWARE_ERROR = 68, + // FPGA + FPGA_ERROR = 68, + // ʼ + START_SCAN = 69, + //ֹͣ + STOP_SCAN = 70, + //ͼ + HAVE_IMAGE = 71, + // ɨ + UPDATE_SCAN_PARAMETER = 72, + // PCæ + PC_SCAN_BUSY_or_ERROR = 73, + //USB δ + USB_DISCONNECTED = 200 +} UsbSupported, * PUsbSupported; + + + +void DoEvents(); \ No newline at end of file diff --git a/huagao/Device/GScan200.cpp b/huagao/Device/GScan200.cpp new file mode 100644 index 00000000..632e7ac0 --- /dev/null +++ b/huagao/Device/GScan200.cpp @@ -0,0 +1,168 @@ +#include "stdafx.h" +#include "GScan200.h" +#include "GDeviceLists.h" +#include "IGDevice.h" +#include "opencv2/opencv.hpp" +#include "config_new.h" +#include "device_common.h" +#include "GDevice.h" +#include "ImageMatQueue.h" + +GScan200::GScan200() +{ +} + +GScan200::~GScan200() +{ + //if (!error_msg.IsShutDown()) + // error_msg.ShutDown(); +} + +void GScan200::open(int vid, int pid) +{ + auto devs = HGDeviceLists::FindAll(); + if(!devs.empty()){ + m_dev = *(devs.begin()); + m_dev->open(); + } +} + +int GScan200::aquire_bmpdata(std::vector& bmpdata) +{ + return 0; +} + +BOOL GScan200::IsConnected() +{ + return m_dev && m_dev->is_open(); +} + +std::string GScan200::GetFWVersion() +{ + if (fwVersion.empty()) { + fwVersion.resize(8); + ((GDevice*)(m_dev.get()))->read_flash(FWVERSION_ADDR, (void*)(fwVersion.data()), FLASH_FWVERSION_ADDR_SIZE); + } + return fwVersion; +} + +std::string GScan200::GetSerialNum() +{ + if (SerialNum.empty()) { + SerialNum.resize(12); + ((GDevice*)(m_dev.get()))->read_flash(SERIAL_ADDR, (void*)(SerialNum.data()), FLASH_SERIAL_ADDR_SIZE); + } + return SerialNum; +} + +bool GScan200::is_scan() +{ + return m_dev && m_dev->is_run(); +} + +BOOL GScan200::Get_Scanner_PaperOn() +{ + return m_dev->get_option(Cam_Options::scanner_paper_have); +} + +void GScan200::config_params(GScanCap& params) +{ + config_new cfn(params); + unsigned int cfg_value=cfn.GetData(); + m_dev->set_option(Cam_Options::scanner_config, cfg_value); + m_pImages->setparam(params); +} + +void GScan200::Scanner_StartScan(UINT16 count) +{ + m_dev->start(image_call_s, this); + m_dev->set_event_call(event_call_g200, this); +} + +void GScan200::Stop_scan() +{ + m_dev->stop(); +} + +void GScan200::ResetScanner() +{ + +} + +bool GScan200::Get_IsImageQueueEmpty() +{ + return m_pImages->empty(); +} + +void GScan200::reset() +{ + if (m_dev) { + m_dev->stop(); + this_thread::sleep_for(chrono::milliseconds(200)); + m_pImages->clear(); + } +} + +void GScan200::setdecodepixtype(int twpixtype) +{ + pixType = (twpixtype == 0) ? 1 : 0; +} + +UINT32 GScan200::get_ErrorCode() +{ + return UINT32(); +} + +void GScan200::Set_ErrorCode(UINT32 value) +{ + //error_msg.Clear(); +} + +int GScan200::get_scanned_num() +{ + int scanned_count = 0; + ((GDevice*)(m_dev.get()))->read_flash(CONT_ADDR, &scanned_count, FLASH_CONT_ADDR_SIZE); + return scanned_count; +} + +void GScan200::set_scan_status(bool isscan) +{ + +} + +void GScan200::image_call_s(void* fdata, int fsize, void* bdata, int bsize, void* userdata) +{ + GScan200* This = (GScan200*)userdata; + This->image_call(fdata, fsize, bdata, bsize); +} + +void GScan200::event_call_g200(int error_value, void* userdata) +{ + GScan200* This = (GScan200*)userdata; + //if (!This->error_msg.IsShutDown()) + //{ + // MotorStatus ms; + // ms.value = error_value; + // if (ms.double_paper == 1) { This->error_msg.Put(DETECT_DOUBLE_FEED); };//error_msg.Put(DETECT_DOUBLE_FEED); + // if (ms.open_machine == 1) { This->error_msg.Put(OPEN_COVER); };//error_msg.Put(OPEN_COVER); + // if (ms.m1_paper_sin == 1) { This->error_msg.Put(NO_FEED); };//error_msg.Put(NO_FEED); + // if (ms.pick_failed == 1) { This->error_msg.Put(FEED_IN_ERROR); };//error_msg.Put(FEED_IN_ERROR); + // if (ms.stop_jam == 1) { This->error_msg.Put(PAPER_JAM); };//error_msg.Put(PAPER_JAM); + // if (ms.staple == 1) { This->error_msg.Put(DETECT_STAPLE); };//error_msg.Put(DETECT_STAPLE); + // if (ms.scan_mode_change == 1) { This->error_msg.Put(DETECT_STAPLE); };//error_msg.Put(DETECT_STAPLE); + // if (ms.papertilted == 1) { This->error_msg.Put(PAPER_SKEW); };//error_msg.Put(PAPER_SKEW); + //} +} + +void GScan200::image_call(void* fdata, int fsize, void* bdata, int bsize) +{ + if (fdata && fsize && bdata && bsize) + { + cv::Mat fmat(1, fsize, CV_8UC1, fdata); + cv::Mat bmat(1, bsize, CV_8UC1, bdata); + std::vector mats; + mats.push_back(fmat.clone()); + mats.push_back(bmat.clone()); + // m_pImages.pushMat(JpegBuffer(mats, pixType, 0)); + } +} diff --git a/huagao/Device/GScan200.h b/huagao/Device/GScan200.h new file mode 100644 index 00000000..dd528bac --- /dev/null +++ b/huagao/Device/GScan200.h @@ -0,0 +1,37 @@ +#pragma once +#include "GScan.h" +#include +#include "BlockingQueue.h" + +class IGDevice; + +class GScan200 : public IGScan, GScan +{ +public: + GScan200(); + virtual ~GScan200(); + virtual void open(int vid, int pid) override; + virtual int aquire_bmpdata(std::vector& bmpdata) override; + virtual BOOL IsConnected() override; + virtual std::string GetFWVersion() override; + virtual std::string GetSerialNum() override; + virtual bool is_scan() override; + virtual BOOL Get_Scanner_PaperOn() override; + virtual void config_params(GScanCap¶ms) override; + virtual void Scanner_StartScan(UINT16 count) override; + virtual void Stop_scan() override; + virtual void ResetScanner() override; + virtual bool Get_IsImageQueueEmpty() override; + virtual void reset() override; + virtual void setdecodepixtype(int twpixtype) override; + virtual UINT32 get_ErrorCode() override; + virtual void Set_ErrorCode(UINT32 value) override; + virtual int get_scanned_num() override; + void set_scan_status(bool isscan); +private: + static void image_call_s(void *fdata, int fsize, void *bdata, int bsize, void *userdata); + static void event_call_g200(int error_value, void* userdata); + void image_call(void *fdata, int fsize, void *bdata, int bsize); + BlockingQueue error_msg; + std::shared_ptr m_dev; +}; diff --git a/huagao/Device/GScanO200.cpp b/huagao/Device/GScanO200.cpp new file mode 100644 index 00000000..d3cb5ad1 --- /dev/null +++ b/huagao/Device/GScanO200.cpp @@ -0,0 +1,394 @@ +#include "stdafx.h" +#include "GScanO200.h" +#include "UsbScanEx.h" +#include "UsbScanEx.h" +#include "StopWatch.h" +#include "scn_config.h" +#include "JpegBuffer.h" +#include "ImageMatQueue.h" +#include "filetools.h" + +//u32_CMD +typedef enum tagUsbKeyWords : UINT32 +{ + // + NO_COMMAND = 0, + //ȡdsp ״̬ + GET_DSP_STATUS = 1, + //ȡͼ + GET_IMAGE = 2, + //DSPפͼ + POP_IMAGE = 3, + //ʼɨ + START_COMMAND = 4, + //ֹͣɨ + STOP = 5, + //ȡɨɨģʽ + GET_SCAN_MODE = 6, + //ȡ̼汾 + GET_FW_VERSION = 7, + //PC˵״̬ + SEND_STATUS_PC = 8, + //·ɨò + CONFIGURED_DATA = 9, + //·̼Ϣ + SEND_FW = 10, + //ȡɨ + GET_CONFIG_DATA = 11, + //ȡɨ + GET_SCANN_NUM = 12, + //ȡֽ״̬ + GET_PAPERFEEDER_STATUS = 13, + //DSPʼ + INIT_HARDWARE_SYS = 14, + //ȡֽ״̬ + GET_PAPER_STATUS = 0x0d, + //·ԪòҶȣLED Rعʱ䣩 + SEND_COMPONENTS_GR = 15, + //·ԪòLED G/Bعʱ䣩 + SEND_COMPONENTS_GB = 16, + //·ɨģʽ + SEND_SCAN_MODE = 17, + //ʼƽ + START_FLAT = 18, + //ֹͣƽ + STOP_FLAT = 19, + //·200dpiɫƽ + SEND_200_COLOR_FLAT_DATA = 20, + //·300dpiɫƽ + SEND_300_COLOR_FLAT_DATA = 21, + //ȡ200dpiɫƽ + GET_200_COLOR_FLAT_DATA = 22, + //ȡ300dpiɫƽ + GET_300_COLOR_FLAT_DATA = 23, + //·200dpiҶƽУ + SEND_200_GRAY_FLAT_DATA = 24, + //·300dpiҶƽУ + SEND_300_GRAY_FLAT_DATA = 25, + //ȡ200DPIҶƽУ + GET_200_GRAY_FLAT_DATA = 26, + //ȡ300DPIҶƽУ + GET_300_GRAY_FLAT_DATA = 27, + //·к + SEND_SERIAL = 28, + //ȡк + GET_SERIAL = 29 +} UsbKeyWords, * PUsbKeyWords; + +GScanO200::GScanO200() +{ +} + +GScanO200::~GScanO200() +{ + if (m_threadUsb && m_threadUsb->joinable()) { + devState = DEV_STOP; + m_threadUsb->join(); + m_threadUsb.reset(); + } +} + +void GScanO200::open(int vid, int pid) +{ + auto usbs = UsbScan_List::find_vid_pid(vid, pid); + + if (!usbs.empty()) { + m_usb = *usbs.begin(); + bool ret= m_usb->open(); + if (ret) { + m_usb->set_usbhotplug_callback(usbhotplug_callback, this); + } + } +} +#ifdef LOG_NORMAL +fstream fsaquire; +static int aquiretimes = 1; +#endif // LOG +int GScanO200::aquire_bmpdata(std::vector& bmpdata) +{ + StopWatch sw; + while (true) + { + if (m_pImages->empty()) { + DoEvents(); + this_thread::sleep_for(chrono::milliseconds(1)); + if (sw.elapsed_s() > 20.00) + { + if (m_threadUsb && m_threadUsb->joinable()) { + devState = DEV_STOP; + m_threadUsb->join(); + m_threadUsb.reset(); + } + Stop_scan();//ֹͣɨ + ResetScanner(); + return HARDWARE_ERROR; + } + + if (!is_scan()) { + if (devState == DEV_WRONG) { + return get_ErrorCode(); + } + return -1; + } + } + else { + if (m_pImages->valid()) { + bmpdata = m_pImages->popBmpdata(); +#ifdef LOG_NORMAL + static int aquireindex = 0; + FileTools::write_log("out.txt", "aquire image index " + std::to_string(++aquireindex)); +#endif // LOG + return 0; + } + DoEvents(); + this_thread::sleep_for(chrono::milliseconds(2)); + } + } +} + +BOOL GScanO200::IsConnected() +{ + return m_usb.get() && m_usb->is_connected(); +} + +std::string GScanO200::GetFWVersion() +{ + if (m_usb.get() && m_usb->is_connected()) { + lock_guard< mutex> lock(m_imgLocker); + if (fwVersion.empty()) { + fwVersion = " "; + USBCB cmd= { GET_FW_VERSION,8,0,}; + m_usb->write_bulk(&cmd, sizeof(cmd)); + m_usb->read_bulk(&fwVersion[0], 8); + } + return fwVersion; + } + return ""; +} + +std::string GScanO200::GetSerialNum() +{ + if (m_usb.get() && m_usb->is_connected()) + { + std::lock_guard lck(m_imgLocker); + if (SerialNum.empty()) { + SerialNum = " "; + USBCB usbcb = { GET_SERIAL,12,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + m_usb->read_bulk(&SerialNum[0], 12); + } + return SerialNum; + } + return ""; +} + +bool GScanO200::is_scan() +{ + //std::lock_guard lck(m_imgLocker); + return devState == DEV_ISRUNNING; +} + +BOOL GScanO200::Get_Scanner_PaperOn() +{ + if (m_usb.get()&&!m_usb->is_open()) + return false; + + USBCB usbcb = { GET_PAPER_STATUS ,0,0 }; + std::lock_guard lck(m_imgLocker); + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + m_usb->read_bulk(&usbcb, sizeof(usbcb)); + return usbcb.u32_Data != 0; +} + +void GScanO200::config_params(GScanCap& params) +{ + if (m_usb.get()&&m_usb->is_connected()) { + IConfig cfg; + cfg = hgConfigClass(params); + UINT32 cfgdata = cfg.GetData(); + USBCB usbcb = { CONFIGURED_DATA,cfgdata,0 }; + m_usb->write_bulk(&usbcb, sizeof(USBCB)); + m_pImages->setparam(params); + } +} + +void GScanO200::Scanner_StartScan(UINT16 count) +{ + if (m_usb.get() && m_usb->is_connected()) { + std::lock_guard lck(m_imgLocker); + USBCB usbcb = { START_COMMAND,(UINT32)count ,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + if (m_threadUsb && m_threadUsb->joinable()) { + m_threadUsb->join(); + } + m_threadUsb.reset(new std::thread(&GScanO200::usbmain, this)); + m_pImages->run(); + m_pImages->setscanflags(true); + } +} + +void GScanO200::Stop_scan() +{ + if (m_usb.get() && !m_usb->is_connected()) { + return; + } + std::lock_guard lck(m_imgLocker); + USBCB usbcb = { STOP ,0,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); +} + +void GScanO200::ResetScanner() +{ + if (m_usb.get() && !m_usb->is_connected()) + return; + + std::lock_guard lck(m_imgLocker); + USBCB usbcb = { INIT_HARDWARE_SYS ,0,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); +} + +bool GScanO200::Get_IsImageQueueEmpty() +{ + return m_pImages->empty(); +} + +void GScanO200::reset() +{ + while (!m_pImages->empty()) + m_pImages->clear(); +} + +void GScanO200::setdecodepixtype(int twpixtype) +{ +} + +UINT32 GScanO200::get_ErrorCode() +{ + return Error_Code; +} + +void GScanO200::Set_ErrorCode(UINT32 value) +{ + Error_Code = value; +} + +int GScanO200::get_scanned_num() +{ + if (m_usb.get() && !m_usb->is_connected()) + return -1; + + std::lock_guard lck(m_imgLocker); + USBCB usbcb = { GET_SCANN_NUM ,0,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + return usbcb.u32_Count; +} + +void GScanO200::usbhotplug_callback(bool isconnect, void* userdata) +{ + GScanO200* This = (GScanO200*)userdata; + This->usbhotplug(isconnect); +} + +void GScanO200::usbhotplug(bool isleft) +{ + if (isleft) { + devState = DEV_WRONG; + Error_Code = USB_DISCONNECTED; + m_pImages->setscanflags(false); + } +} + +void GScanO200::usbmain() +{ + std::shared_ptr> imgData; + devState = DEV_ISRUNNING; + while (devState == DEV_ISRUNNING) { + if (m_usb.get() && !m_usb->is_connected()) { + this_thread::sleep_for(chrono::milliseconds(200)); + continue; + } + USBCB usbcb = Get_Scanner_Status(); + switch (usbcb.u32_Data) { + case HAVE_IMAGE: + { + int totalNum = usbcb.u32_Count; + imgData = Get_Img_Data(totalNum); + if (!imgData->size()) { + Stop_scan(); + } + + + m_pImages->pushMat(std::shared_ptr(new G200Decode(imgData))); +#ifdef LOG_NORMAL + static int rawdataindex = 0; + FileTools::write_log("out.txt", "Enquque rawbuffer index " + std::to_string(++rawdataindex)); +#endif // LOG + Pop_Image(); + break; + } + case STOP_SCAN: + m_pImages->setscanflags(false); + devState = DEV_STOP; + break; + case COUNT_MODE: + case NO_FEED: + case OPEN_COVER: + case FEED_IN_ERROR: + case PAPER_JAM: + case DETECT_DOUBLE_FEED: + case DETECT_STAPLE: + case PAPER_SKEW: + case HARDWARE_ERROR: + case PC_SCAN_BUSY_or_ERROR: + Set_ErrorCode(usbcb.u32_Data); + m_pImages->setscanflags(false); + devState = DEV_WRONG; + break; + case NORMAL: + break; + default: + break; + } + this_thread::sleep_for(chrono::milliseconds(20)); + } +} + +/////////////////////////////////////////////////////////////////////////// +USBCB GScanO200::Get_Scanner_Status() +{ + if (m_usb.get() && !m_usb->is_connected()) { + return { NO_COMMAND ,PC_SCAN_BUSY_or_ERROR ,0 }; + } + USBCB usbcb = { GET_DSP_STATUS ,0,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + m_usb->read_bulk(&usbcb, sizeof(usbcb)); + return usbcb; +} + +std::shared_ptr> GScanO200::Get_Img_Data(int bufferSize) +{ + std::shared_ptr> imData(new std::vector(bufferSize)); + StopWatch sw; + int readed = 0; + while (readed < bufferSize && sw.elapsed_ms() < 3000){ + USBCB usbcb = { GET_IMAGE,0,(UINT32)bufferSize }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); + readed = m_usb->read_bulk(imData->data(), bufferSize); + } + + if (sw.elapsed_ms() > 3000) { + writelog("Usb read data error\n"); + } + + return imData; +} + +/////////////////////////////////////////////////////////////////////////// +void GScanO200::Pop_Image() +{ + if (m_usb.get() && !m_usb->is_open()) + return; + + USBCB usbcb = { POP_IMAGE ,0,0 }; + m_usb->write_bulk(&usbcb, sizeof(usbcb)); +} diff --git a/huagao/Device/GScanO200.h b/huagao/Device/GScanO200.h new file mode 100644 index 00000000..f844b2b3 --- /dev/null +++ b/huagao/Device/GScanO200.h @@ -0,0 +1,46 @@ +#pragma once +#include "GScan.h" +#include + +typedef struct tag_USBCB { + UINT32 u32_CMD; + UINT32 u32_Data; + UINT32 u32_Count; +}USBCB, * PUSBCB; + + +class GScanO200 : public IGScan, GScan +{ +public: + GScanO200(); + virtual ~GScanO200(); + // ͨ IGScan ̳ + virtual void open(int vid, int pid) override; + virtual int aquire_bmpdata(std::vector& bmpdata) override; + virtual BOOL IsConnected() override; + virtual std::string GetFWVersion() override; + virtual std::string GetSerialNum() override; + virtual bool is_scan() override; + virtual BOOL Get_Scanner_PaperOn() override; + virtual void config_params(GScanCap& params) override; + virtual void Scanner_StartScan(UINT16 count) override; + virtual void Stop_scan() override; + virtual void ResetScanner() override; + virtual bool Get_IsImageQueueEmpty() override; + virtual void reset() override; + virtual void setdecodepixtype(int twpixtype) override; + virtual UINT32 get_ErrorCode() override; + virtual void Set_ErrorCode(UINT32 value) override; + virtual int get_scanned_num() override; +private: + static void usbhotplug_callback(bool isleft, void* userdata); + void usbhotplug(bool isleft); + void usbmain(); + USBCB Get_Scanner_Status(); + std::shared_ptr> Get_Img_Data(int buffersize); + void Pop_Image(); + + std::shared_ptr m_usb; + std::unique_ptr m_threadUsb; +}; + diff --git a/huagao/Device/GScanVirtual.cpp b/huagao/Device/GScanVirtual.cpp new file mode 100644 index 00000000..38f6fdc6 --- /dev/null +++ b/huagao/Device/GScanVirtual.cpp @@ -0,0 +1,202 @@ +#include "stdafx.h" +#include "GScanVirtual.h" +#include "UsbScanEx.h" +#include "opencv2/opencv.hpp" +#include "UsbScanEx.h" +#include "StopWatch.h" +#include "filetools.h" +#include "ImageMatQueue.h" + +GScanVirtual::GScanVirtual() +{ +} + +GScanVirtual::~GScanVirtual() +{ + if (m_threadUsb && m_threadUsb->joinable()) { + devState = DEV_STOP; + m_threadUsb->join(); + m_threadUsb.reset(); + } +} + +void GScanVirtual::open(int vid, int pid) +{ + fstream fs; + fs.open("D:\\1.txt",ios::out); + fs << 1; + fs.close(); +} + +int GScanVirtual::aquire_bmpdata(std::vector& bmpdata) +{ + StopWatch sw; + while (true) + { + if (Get_IsImageQueueEmpty() && is_scan()) { + DoEvents(); + this_thread::sleep_for(chrono::milliseconds(1)); + if (sw.elapsed_s() > 15.00) + { + if (m_threadUsb && m_threadUsb->joinable()) { + devState = DEV_STOP; + m_threadUsb->join(); + m_threadUsb.reset(); + } + Stop_scan();//ֹͣɨ + ResetScanner(); + return HARDWARE_ERROR; + } + + if (!is_scan()) { + if (devState == DEV_WRONG) { + return get_ErrorCode(); + } + return 0; + } + } + else { + if (m_pImages->valid()) { + bmpdata = m_pImages->popBmpdata(); + return 0; + } + } + } +} + +BOOL GScanVirtual::IsConnected() +{ + return true; +} + +std::string GScanVirtual::GetFWVersion() +{ + return "201901012020"; +} + +std::string GScanVirtual::GetSerialNum() +{ + return "208881100"; +} + +bool GScanVirtual::is_scan() +{ + std::lock_guard lck(m_imgLocker); + std::ifstream io("d:\\1.txt"); + int ret; + io >> ret; + return ret; +} + +BOOL GScanVirtual::Get_Scanner_PaperOn() +{ + std::ifstream io("d:\\1.txt"); + int ret; + io >> ret; + return ret; +} + +void GScanVirtual::config_params(GScanCap& params) +{ + m_pImages->setparam(params); +} + +void GScanVirtual::Scanner_StartScan(UINT16 count) +{ + if (m_threadUsb && m_threadUsb->joinable()) { + m_threadUsb->join(); + } + + m_threadUsb.reset(new std::thread(&GScanVirtual::usbmain, this)); + m_pImages->run(); + devState = DEV_ISRUNNING; +} + +void GScanVirtual::Stop_scan() +{ + std::lock_guard lck(m_imgLocker); + fstream fs("D:\\1.txt", ios::out); + fs << 0; + fs.close(); +} + +void GScanVirtual::ResetScanner() +{ + +} + +bool GScanVirtual::Get_IsImageQueueEmpty() +{ + std::lock_guard lck(m_imgLocker); + return m_pImages->empty(); +} + +void GScanVirtual::reset() +{ + std::lock_guard lck(m_imgLocker); + while (!m_pImages->empty()) + { + m_pImages->clear(); + } +} + +void GScanVirtual::setdecodepixtype(int twpixtype) +{ + pixType = twpixtype; +} + +UINT32 GScanVirtual::get_ErrorCode() +{ + std::lock_guard lck(m_imgLocker); + return Error_Code; +} + +void GScanVirtual::Set_ErrorCode(UINT32 value) +{ + std::lock_guard lck(m_imgLocker); + Error_Code = value; +} + +int GScanVirtual::get_scanned_num() +{ + if (!m_usb->is_connected()) + return -1; + + std::lock_guard lck(m_imgLocker); + return 1; +} + +DWORD GScanVirtual::usbmain() +{ + cv::Mat imgData; + cv::Mat bufferF; + cv::Mat bufferB; + devState = DEV_ISRUNNING; + + while (Get_Scanner_PaperOn()) { + std::vector files = FileTools::getFiles("D:\\bb"); + for (int i = 0; i < files.size(); i++) { + if (!Get_Scanner_PaperOn()) { break; } + std::vector mats; + FILE* file = fopen(files[i].c_str(), "rb"); + if (file) { + fseek(file, 0, SEEK_END); + int length = ftell(file); + fseek(file, 0, SEEK_SET); + std::shared_ptr> imgData(new std::vector(length)); + fread(imgData->data(), sizeof(unsigned char), length, file); + fclose(file); + m_pImages->pushMat(std::shared_ptr(new GRawDecode(imgData))); + this_thread::sleep_for(std::chrono::milliseconds(1000)); + } + } + } + devState = DEV_STOP; + return 0; +} + + +/////////////////////////////////////////////////////////////////////////// +void GScanVirtual::Pop_Image() +{ +} diff --git a/huagao/Device/GScanVirtual.h b/huagao/Device/GScanVirtual.h new file mode 100644 index 00000000..ccf27475 --- /dev/null +++ b/huagao/Device/GScanVirtual.h @@ -0,0 +1,35 @@ +#pragma once +#include "GScan.h" +#include + + +class GScanVirtual : public IGScan, GScan +{ +public: + GScanVirtual(); + virtual ~GScanVirtual(); + // ͨ IGScan ̳ + virtual void open(int vid, int pid) override; + virtual int aquire_bmpdata(std::vector& bmpdata) override; + virtual BOOL IsConnected() override; + virtual std::string GetFWVersion() override; + virtual std::string GetSerialNum() override; + virtual bool is_scan() override; + virtual BOOL Get_Scanner_PaperOn() override; + virtual void config_params(GScanCap& params) override; + virtual void Scanner_StartScan(UINT16 count) override; + virtual void Stop_scan() override; + virtual void ResetScanner() override; + virtual bool Get_IsImageQueueEmpty() override; + virtual void reset() override; + virtual void setdecodepixtype(int twpixtype) override; + virtual UINT32 get_ErrorCode() override; + virtual void Set_ErrorCode(UINT32 value) override; + virtual int get_scanned_num() override; +private: + DWORD usbmain(); + void Pop_Image(); + std::shared_ptr m_usb; + std::unique_ptr m_threadUsb; +}; + diff --git a/huagao/Device/IConfig.h b/huagao/Device/IConfig.h new file mode 100644 index 00000000..a5a51a41 --- /dev/null +++ b/huagao/Device/IConfig.h @@ -0,0 +1,75 @@ +#ifndef ICONFIG_H +#define ICONFIG_H + // !ICONFIG_H +#include +#include "PublicFunc.h" +#include "PaperSize.h" + +static std::map SupPaperTyps = { + {{TwSS::A3,PaperAlign::Rot0},0}, + {{TwSS::A4,PaperAlign::Rot0},1}, + {{TwSS::A4,PaperAlign::Rot270},2}, + {{TwSS::A5,PaperAlign::Rot0 },2}, + {{TwSS::A5,PaperAlign::Rot270},2}, + {{TwSS::A6,PaperAlign::Rot0},2}, + {{TwSS::A6,PaperAlign::Rot270},2}, + {{TwSS::B4,PaperAlign::Rot0},0}, + {{TwSS::B5,PaperAlign::Rot0},0}, + {{TwSS::B5,PaperAlign::Rot270},1}, + {{TwSS::B6,PaperAlign::Rot0},2}, + {{TwSS::B6,PaperAlign::Rot270},2}, + {{TwSS::USLetter,PaperAlign::Rot0},1}, + {{TwSS::USLetter,PaperAlign::Rot270},2}, + {{TwSS::USLedger,PaperAlign::Rot0},0}, + {{TwSS::USLegal,PaperAlign::Rot0},0}, + {{TwSS::None,PaperAlign::Rot0},0}, + {{TwSS::USStatement,PaperAlign::Rot0},16}, + {{TwSS::MaxSize,PaperAlign::Rot0},16} +}; + +static std::map SupPixelTypes = { + {0, 0},//bw + {1, 0},//gray + {2, 1}//color +}; + +static std::map SupResolutions = { + {300.0f, 0}, + {200.0f, 1}, + {600.0f, 2} +}; + + +static std::map secrewMaps = { + {1,0}, + {2,1}, + {3,2}, + {4,3}, + {5,4} +}; +typedef union Config_Param { + unsigned int value; + struct { + unsigned int paper : 5; + unsigned int color : 1; + unsigned int dpi : 2; + unsigned int double_feed_enbale : 1; + unsigned int stable_enbale : 1; + unsigned int screw_detect_enable : 1; + unsigned int screw_detect_level : 3; + unsigned int unused_one : 6; + unsigned int pc_correct : 1; + unsigned int unused_two : 11; + }; +} ConfigParam; + +class IConfig +{ +public: + IConfig(void) {}; + virtual ~IConfig(void) {}; + virtual unsigned int GetData() { return m_param.value; } +protected: + ConfigParam m_param; +}; +#endif diff --git a/huagao/Device/IGDevice.h b/huagao/Device/IGDevice.h new file mode 100644 index 00000000..f23ede98 --- /dev/null +++ b/huagao/Device/IGDevice.h @@ -0,0 +1,54 @@ +#pragma once +#include + + +typedef void(*image_callback)(void*, int, void*, int, void*); +typedef void(*event_callback)(int, void*); + +enum Cam_Options { + scanner_config, //!< color, gray + scanner_exposure_gray, + scanner_exposure_green, + scanner_exposure_blue, + scanner_exposure_red, + scanner_status, + scanner_ad_gain, + scanner_ad_offset, + scanner_cover_status, //Ƿرո + scanner_pick_paper_stauts, //Ƿֽʧ + scanner_jam_stauts, //Ƿֽ + scanner_paper_count, //ɨֵ + scanner_trigger_scan, //ɨ + scanner_staple_state, //޶鶤 + scanner_skrew_state, //б״̬ + scanner_paper_have, //ֽ + scanner_double_paper, //˫ż + scanner_scan_triger,//ɨ״̬1ֹͣɨ裬0ɨ + scanner_scan_skrew, //б⿪أ10 + scanner_stample_enable, //鶤ʹ,0:default1鶤ʹ + scanner_doublePape_enable,//˫żʹ + scanner_stop_motor, //ֹͣ + scanner_error_clean ,//쳣 + scanner_Init_Status, //״̬ʼʹ + scanner_IIC_Config, //IICʹ + scanner_Speed_Config, //ٶʹ + scanner_scan_status +}; + +class IGDevice +{ +public: + virtual ~IGDevice() {} + virtual bool open() = 0; + virtual void close() = 0; + virtual bool is_open() = 0; + virtual bool start(image_callback imagecall= NULL, void* userdata = NULL) = 0; + virtual void stop() = 0; + virtual int is_run() = 0; + virtual void reset() = 0; + virtual void set_event_call(event_callback event_callfunc, void* userdata) = 0; + virtual void set_option(Cam_Options option, unsigned int value) = 0; + virtual int get_option(Cam_Options option) = 0; + virtual std::vector support_options() = 0; +}; + diff --git a/huagao/Device/IUsb.h b/huagao/Device/IUsb.h new file mode 100644 index 00000000..a286b467 --- /dev/null +++ b/huagao/Device/IUsb.h @@ -0,0 +1,18 @@ +#pragma once +typedef void(*usbhotplug_callback)(bool isleft, void* userdata); + +class IUsb +{ +public: + virtual ~IUsb() {} + virtual bool open() = 0; + virtual void set_usbhotplug_callback(usbhotplug_callback callback=NULL,void* userdata=NULL)=0; + virtual bool close() = 0; + virtual bool is_open() = 0; + virtual bool is_connected() = 0; + virtual void set_timeout(int timeout) = 0; + virtual int read_bulk(void* data, int len) = 0; + virtual int write_bulk(void* data, int len) = 0; + virtual int read_int(void* data, int len) = 0; + virtual int control_msg(int rtype, int req, int value, int index, int len, void* data) = 0; +}; \ No newline at end of file diff --git a/huagao/Device/ImageMatQueue.cpp b/huagao/Device/ImageMatQueue.cpp new file mode 100644 index 00000000..661bad66 --- /dev/null +++ b/huagao/Device/ImageMatQueue.cpp @@ -0,0 +1,297 @@ +#include "StdAfx.h" +#include "ImageMatQueue.h" +#include "PublicFunc.h" +#include "ImageProcess/ImageApplyHeaders.h" +#include "ImageMultiOutput.h" +#include "jpeglib.h" +#include "filetools.h" +#include +using namespace cv; +using namespace std; + +#define DECODE_COLOR_BGR 1 +#define DECODE_GRAY 6 + +G200Decode::G200Decode(std::shared_ptr> buff) +{ + const int int_buffer_size = 1024; + int buffer_size = buff->size(); + int b_buffer_size = 0; + int f_buffer_size = 0; + std::shared_ptr> buffB(new std::vector(buff->size())); + std::shared_ptr> buffF(new std::vector(buff->size()));; + unsigned char* bbuf = (unsigned char*)(buffB->data()); + unsigned char* fbuf = (unsigned char*)(buffF->data()); + unsigned char* buf = (unsigned char*)(buff->data()); + for (int i = 0; i < (buffer_size / int_buffer_size); i++) { + if (buf[(i + 1) * int_buffer_size - 1] == 0) { + memcpy(bbuf + b_buffer_size, buf + i * int_buffer_size, int_buffer_size - 1); + b_buffer_size += (int_buffer_size - 1); + } + else if (buf[(i + 1) * int_buffer_size - 1] == 255) { + memcpy(fbuf + f_buffer_size, buf + i * int_buffer_size, int_buffer_size - 1); + f_buffer_size += (int_buffer_size - 1); + } + } + buffB->resize(b_buffer_size); + buffF->resize(f_buffer_size); + m_buffs.push_back(buffB); + m_buffs.push_back(buffF); +} + +ImageMatQueue::ImageMatQueue(void) + : bRun(false) + , is_scanning(false) +{ + atm_orgin_image_remains = 0; +} + +void ImageMatQueue::run() +{ + if (!m_threadProc) { + bRun = true; + m_threadProc.reset(new thread(&ImageMatQueue::proc, this)); + } +} + +int ImageMatQueue::orginimgcount() +{ + return atm_orgin_image_remains; +} + +ImageMatQueue::~ImageMatQueue(void) +{ + m_rawBuffs.Clear(); + m_imagedata.Clear(); + m_rawBuffs.ShutDown(); + m_imagedata.ShutDown(); + if (m_threadProc) { + bRun = false; + m_threadProc->join(); + m_threadProc.reset(); + } +} + +void ImageMatQueue::pushMat(std::shared_ptr data) +{ + std::lock_guard lock(m_mtxJB); + m_rawBuffs.Put(data); + atm_orgin_image_remains++; +} + +std::vector ImageMatQueue::popBmpdata() +{ + std::lock_guard lock(m_mtxJB); + std::vector retdata = m_imagedata.Take(); + return retdata; +} + +bool ImageMatQueue::valid() +{ + return m_imagedata.Size(); +} + +void ImageMatQueue::clear() +{ + m_rawBuffs.Clear(); + m_imagedata.Clear(); + atm_orgin_image_remains = 0; +} + +void ImageMatQueue::setparam(const GScanCap& param) +{ + scanParam = param; + m_iaList.clear(); + + if (scanParam.fillhole.is_fillhole) { + float ratio = scanParam.fillhole.fillholeratio/100.0; + m_iaList.push_back(shared_ptr(new CImageOutHole(200, ratio, 50))); + } //ȷܹȡͼ + + { + bool islongcustomcrop = false; + if (param.papertype == TwSS::USStatement) + islongcustomcrop = true; + CSize fixedSize = papersize.GetPaperSize(param.papertype, 200.0f, param.paperAlign); + m_iaList.push_back(shared_ptr(new CImageApplyAutoCrop(islongcustomcrop ? islongcustomcrop : param.is_autocrop, param.autodescrew, param.fillbackground, cv::Size(fixedSize.cx, fixedSize.cy), true))); + } + + if (param.is_autodiscradblank_normal || param.is_autodiscradblank_vince) { + m_iaList.push_back(shared_ptr(new CImageApplyDiscardBlank(param.is_autodiscradblank_normal ? true : false))); + //m_iaList.push_back(shared_ptr(new CImageApplyDiscardBlank(param.areanum,param.devnmax))); + } + //if (param.pixtype != 0) //sharpen + // m_iaList.push_back(shared_ptr(new CImageApplySharpen())); + + //filter 0 r 1 g 2 b 3 none enhance color 0 none 1 r 2 g 3 b + if (param.filter != 3 || param.enhance_color) { + int channel = 0; //filter none r g b enhance none r g b + if (param.filter != 3) { channel = param.filter; } + else { channel = param.enhance_color + 3; } + m_iaList.push_back(shared_ptr(new CImageApplyChannel(static_cast(channel)))); + } + + if (param.brightness != 0 || param.contrast != 0 || param.gamma != 1.0) { + double aa = (254.0 / 2000.0) * param.brightness + 0.5; + int bright = ceil(aa);//[-127,128] 0.128=256.0/2000.0 + int contrast = (int)(param.contrast * 0.036);//[-36,36] 0.036=72.0/2000.0; + m_iaList.push_back(shared_ptr(new CImageApplyAdjustColors(bright, contrast, param.gamma))); + } + + if (param.pixtype == 0) //threshold + m_iaList.push_back(shared_ptr(new CImageApplyBWBinaray(CImageApplyBWBinaray::ThresholdType::THRESH_BINARY))); + + if (param.sharpen) { + SharpenBlur sb = (SharpenBlur)param.sharpen; + m_iaList.push_back(shared_ptr(new CImageApplySharpen(sb))); + } + + + if (param.resolution_dst != 200.0) + { + CImageApplyResize* apply; + if (param.is_autocrop) { + double ratio = param.resolution_dst / 200.0; + apply = new CImageApplyResize(CImageApplyResize::ResizeType::RATIO, cv::Size(0, 0), ratio, ratio); + } + else { + CSize dSize = papersize.GetPaperSize(param.papertype, param.resolution_dst, param.paperAlign); + apply = new CImageApplyResize(CImageApplyResize::ResizeType::DSIZE, cv::Size(dSize.cx, dSize.cy), 1.0, 1.0); + } + m_iaList.push_back(shared_ptr< CImageApply>(apply)); + } + + if (param.imageRotateDegree != 0.0 || param.is_backrotate180 || param.is_autotext) + { + CImageApplyRotation::RotationType type; + if (param.imageRotateDegree > 89.0f && param.imageRotateDegree < 91.0f) + type = CImageApplyRotation::RotationType::Rotate_90_clockwise; + else if (param.imageRotateDegree > 269.0f && param.imageRotateDegree < 271.0f) + type = CImageApplyRotation::RotationType::Rotate_90_anti_clockwise; + else if (param.imageRotateDegree > 179.0f && param.imageRotateDegree < 181.0f) + type = CImageApplyRotation::RotationType::Rotate_180; + else + type = CImageApplyRotation::RotationType::Invalid; + + if (param.is_autotext) + type = CImageApplyRotation::RotationType::AutoTextOrientation; + + TCHAR szIniFile[MAX_PATH] = { 0 }; + SHGetSpecialFolderPath(NULL, szIniFile, CSIDL_WINDOWS, TRUE); + _tcscat(szIniFile, _T("\\twain_32\\HuaGoScan\\tessdata")); + int iLen = WideCharToMultiByte(CP_ACP, 0, szIniFile, -1, NULL, 0, NULL, NULL); + char* chRtn = new char[iLen * sizeof(char)]; + WideCharToMultiByte(CP_ACP, 0, szIniFile, -1, chRtn, iLen, NULL, NULL); + m_iaList.push_back(shared_ptr(new CImageApplyRotation(type, param.is_backrotate180, param.resolution_dst, chRtn))); + delete[] chRtn; + } +} + +void ImageMatQueue::EnqueueBmpBuffer(std::vector& bmpdata) +{ + //std::lock_guard lock(m_Locker); + m_imagedata.Put(bmpdata); +} + +void ImageMatQueue::PaniusCount() +{ + atm_orgin_image_remains--; +} + +double ImageMatQueue::round_to_n_digits(double x, int n) +{ + double scale = pow(10.0, ceil(log10(fabs(x))) + n); + + return round(x * scale) / scale; +} + + +bool ImageMatQueue::empty() +{ + return atm_orgin_image_remains == 0 && m_imagedata.Size() == 0 && !is_scanning; +} + +static int index = 0; +void ImageMatQueue::proc() +{ + while (bRun) { + while (m_imagedata.Size() > 0) { + this_thread::sleep_for(chrono::milliseconds(1)); + } + + if (m_rawBuffs.Size() == 0) + { + this_thread::sleep_for(chrono::milliseconds(1)); + continue; + } + + auto buffs = m_rawBuffs.Take()->getImageBuffs(); + if (!m_rawBuffs.IsShutDown() && !buffs.empty()) { + vector mats; + for (auto& buf : buffs) { + ImreadModes rm; + + if (scanParam.filter != 3 || scanParam.enhance_color) + rm = IMREAD_COLOR; + else + rm = scanParam.pixtype == 2 ? IMREAD_COLOR : IMREAD_GRAYSCALE; + + cv::Mat mat = cv::imdecode(*buf, rm); + if (mat.empty()) { + fstream fss; + fss.open("D:\\decodeerror.txt", std::ios::out); + fss << "decode image data error" << endl; + fss.close(); + } + mats.push_back(mat); + } + + for (int j = 0; j < m_iaList.size(); j++) { + m_iaList[j]->apply(mats, scanParam.is_duplex); + } + + + for (int i = 0; i < mats.size(); i++) { + if (!scanParam.is_duplex && i == 1) { + mats[i].release(); + break; + } + if (!mats[i].empty()) { + IMat2Bmp idata; + idata = scanParam.pixtype == 0 ? (IMat2Bmp)Mat2BmpBw(mats[i], scanParam.resolution_dst) : Mat2Bmp(mats[i]); + auto data = idata.getBmpDataBuffer(); + EnqueueBmpBuffer(data); + } + else + { + FileTools::write_log("emptyimage.txt", "enqueue image is empty " + std::to_string(index++)); + } + } + + if (scanParam.multi_output_red) { + for (int i = 0; i < mats.size(); i++) { + ImageMultiOutput m_mlt; + Mat m_filterMat = m_mlt.GetMultiFilterMat(mats[i], 2); + if (!m_filterMat.empty()) { + if (!scanParam.is_duplex && i == 1) { + mats[i].release(); + break; + } + + if (!m_filterMat.empty()) { + Mat2Bmp mb(m_filterMat); + auto data = mb.getBmpDataBuffer(); + EnqueueBmpBuffer(data); + } + } + } + } + PaniusCount(); + } + } +} + +GRawDecode::GRawDecode(std::shared_ptr> buff) +{ + m_buffs.push_back(buff); +} \ No newline at end of file diff --git a/huagao/Device/ImageMatQueue.h b/huagao/Device/ImageMatQueue.h new file mode 100644 index 00000000..f50f18f8 --- /dev/null +++ b/huagao/Device/ImageMatQueue.h @@ -0,0 +1,188 @@ +#pragma once +#include +#include +#include +#include "JpegBuffer.h" +#include "ImageProcess/ImageApplyHeaders.h" +#include "PublicFunc.h" +#include "BlockingQueue.h" +#include +#include "PaperSize.h" + + +class IMat2Bmp { +public: + virtual ~IMat2Bmp() {} + virtual std::vector getBmpDataBuffer() { + return m_data; + }; +protected: + std::vector m_data; +}; + +class Mat2Bmp:public IMat2Bmp { +public: + Mat2Bmp(const cv::Mat& mat) { + int headersize = mat.channels() == 3 ? 54 : 1078; + int bmpdatasize = mat.step1() * mat.rows; + m_data.resize(headersize + bmpdatasize); + cv::imencode(".bmp", mat, m_data); + } +}; + +class Mat2BmpBw :public IMat2Bmp { +public: + Mat2BmpBw(const cv::Mat& mat,float res) { + //cv::imwrite("bw.bmp", mat); + int headsize = 62; + int width = mat.cols; + int height = mat.rows; + int bmpdatasize = (width + 31) / 32 * 4*height; + m_data.resize(headsize + bmpdatasize); + unsigned char* binary = m_data.data()+62;//file header(14)+info header(40)+RGBQUAD(8) + setBmpFileHeader(mat,bmpdatasize); + setBmpInfoHeader(mat, bmpdatasize, res); + memcpy(m_data.data(), &m_fileHeader, sizeof(BITMAPFILEHEADER)); + memcpy(m_data.data() + sizeof(BITMAPFILEHEADER), &m_infoHeader, sizeof(BITMAPINFOHEADER)); + RGBQUAD* quad = (RGBQUAD*)(m_data.data() + sizeof(BITMAPFILEHEADER)+sizeof(BITMAPINFOHEADER)); + quad->rgbBlue = quad->rgbGreen = quad->rgbRed = quad->rgbReserved = 0; + quad++; + quad->rgbBlue = quad->rgbGreen = quad->rgbRed = 255; + quad->rgbReserved = 0; + + unsigned char* imageData = mat.data; + unsigned char temp; + int n_lineByte = (width + 7) >> 3; + int m_lineByte = ((n_lineByte * 8 + 31) >> 5) << 2; + for (int row = height - 1; row >= 0; row--) + { + for (int col = 0; col < width; col++) + { + int pos = col % 8; + int pix = *(imageData + row * mat.step1() + col); + temp = 1 << (7 - pos); + if (pix == 255) + { + *(binary + (height - row - 1) * m_lineByte + col / 8) |= temp ; + } + else + { + *(binary + (height - row - 1) * m_lineByte + col / 8) &= (~temp); + } + } + } + //FILE* fout = fopen("afterBW.bmp", "wb"); + //if (fout) { + // fwrite(m_data.data(), 1, m_data.size(), fout); + // fclose(fout); + //} + } +private: + void setBmpFileHeader(const cv::Mat& mat,const int bmpDataLen) { + memset(&m_fileHeader, 0, sizeof(BITMAPFILEHEADER)); + m_fileHeader.bfType = ((unsigned short)('M' << 8) | 'B'); + m_fileHeader.bfOffBits = sizeof(BITMAPFILEHEADER) + sizeof(BITMAPINFOHEADER) + (sizeof(RGBQUAD) * 1); + int nDIBSize = sizeof(BITMAPINFOHEADER) + (sizeof(RGBQUAD) * 2) + bmpDataLen; + m_fileHeader.bfSize = sizeof(BITMAPFILEHEADER) + nDIBSize; + } + + void setBmpInfoHeader(const cv::Mat& mat,const int bmpDataLen, const long res) { + memset(&m_infoHeader, 0, sizeof(BITMAPINFOHEADER)); + m_infoHeader.biSize = sizeof(BITMAPINFOHEADER); + m_infoHeader.biWidth = mat.cols; + m_infoHeader.biHeight = mat.rows; + m_infoHeader.biPlanes = 1; + m_infoHeader.biBitCount = 1; + m_infoHeader.biCompression = 0; + m_infoHeader.biSizeImage = bmpDataLen; + m_infoHeader.biXPelsPerMeter = res; + m_infoHeader.biYPelsPerMeter = res; + m_infoHeader.biClrUsed = 2; + m_infoHeader.biClrImportant = 2; + } + +private: + BITMAPFILEHEADER m_fileHeader; + BITMAPINFOHEADER m_infoHeader; +}; + +class IDecode { +public: + virtual ~IDecode() {} + virtual std::vector>> getImageBuffs() { + return m_buffs; + } +protected: + std::vector>> m_buffs; +}; + +class G200Decode : public IDecode{ +public: + G200Decode(std::shared_ptr> buff); +}; + +class GRawDecode : public IDecode { +public: + GRawDecode(std::shared_ptr> buff); +}; + +class ImageMatQueue +{ +public: + ImageMatQueue(void); + virtual ~ImageMatQueue(void); + + void pushMat(std::shared_ptr buf); + std::vector popBmpdata(); + bool empty(); + bool valid(); + void clear(); + void setparam(const GScanCap& param); + void run(); + int orginimgcount(); + void setscanflags(const bool flags) { is_scanning = flags; } + +private: + void proc(); + void EnqueueBmpBuffer(std::vector& bmpdata); + void PaniusCount(); + + double round_to_n_digits(double x, int n); + //template + //T round(T, int bits); + BlockingQueue> m_imagedata; + std::mutex m_Locker; + std::mutex m_mtxJB; + std::mutex m_mtxscan; + std::unique_ptr m_threadProc; + volatile bool bRun; + bool isduplex; + volatile int atm_orgin_image_remains; + volatile bool is_scanning; + GScanCap scanParam; + Device::PaperSize papersize; + std::vector> m_iaList; + BlockingQueue> m_rawBuffs; +}; +// +//template +//inline T ImageMatQueue::round(T src, int bits) +//{ +// if (0 > bits) +// return 0; +// T retVal = 0.0; +// int tmp = 0; +// +// if (0 > src) { +// src *= -1; +// tmp = (int)((src + 0.5 / pow(10.0, bits)) * pow(10.0, bits)); +// retVal = ((T)tmp) / pow(10.0, bits); +// src *= -1; +// } +// else +// { +// tmp = (int)((src + 0.5 / pow(10.0, bits)) * pow(10.0, bits)); +// retVal = ((T)tmp) / pow(10.0, bits); +// } +// return retVal; +//} diff --git a/huagao/Device/ImageMultiOutput.cpp b/huagao/Device/ImageMultiOutput.cpp new file mode 100644 index 00000000..44dc8cfa --- /dev/null +++ b/huagao/Device/ImageMultiOutput.cpp @@ -0,0 +1,60 @@ +#include "StdAfx.h" +#include "ImageMultiOutput.h" + + +ImageMultiOutput::ImageMultiOutput(void) +{ +} + + +ImageMultiOutput::~ImageMultiOutput(void) +{ +} + +//void ImageMultiOutput::apply(cv::Mat& pDib,int side) +//{ +// //throw std::logic_error("The method or operation is not implemented."); +//} + +cv::Mat ImageMultiOutput::GetMultiFilterMat(cv::Mat &src,int channel) +{ + return FilterColor(src,channel); +} + +cv::Mat ImageMultiOutput::FilterColor(cv::Mat image,short channel) +{ + cv::Mat dstImage(image.rows,image.cols,CV_8UC1); + + //int pixelSize = image.depth(); + int channels = image.channels(); + if(channel > channels -1){ + return dstImage; + } + if ( ( channel == 3 ) && ( channels != 4 ) && ( channels != 8 )) + { + return dstImage; + } + if ( channels <= 4 ) + { + int srcOffset = image.step - image.cols* channels ; + int dstOffset = dstImage.step - dstImage.cols; + unsigned char* src = image.data; + unsigned char* dst = dstImage.data; + src += channel; + + for ( int y = 0; y < image.rows; y++ ) + { + for ( int x = 0; x < image.cols; x++, src += channels , dst++ ) + { + unsigned short pix = *src; + if(pix >=130){ + pix = 255; + } + *dst = pix; + } + src += srcOffset; + dst += dstOffset; + } + } + return dstImage; +} diff --git a/huagao/Device/ImageMultiOutput.h b/huagao/Device/ImageMultiOutput.h new file mode 100644 index 00000000..f2725701 --- /dev/null +++ b/huagao/Device/ImageMultiOutput.h @@ -0,0 +1,15 @@ +#pragma once +#include "ImageProcess/ImageApply.h" + +class ImageMultiOutput +{ +public: + ImageMultiOutput(void); + ~ImageMultiOutput(void); + + cv::Mat GetMultiFilterMat(cv::Mat &src,int channel); +private: + cv::Mat FilterColor(cv::Mat image,short channel); + +}; + diff --git a/huagao/Device/JpegBuffer.cpp b/huagao/Device/JpegBuffer.cpp new file mode 100644 index 00000000..88d1daa2 --- /dev/null +++ b/huagao/Device/JpegBuffer.cpp @@ -0,0 +1,85 @@ +#include "StdAfx.h" +#include "JpegBuffer.h" +#include "jpeglib.h" + +using namespace std; + +JpegBuffer::JpegBuffer(cv::Mat buffer, int color_type,int side,int mFilter) +{ + this->m_buffer = buffer; + this->m_color_type=color_type; + this->m_side=side; + this->m_mFilter=mFilter; +} + +JpegBuffer::JpegBuffer(std::vector mats, int color_type, int mFilter) +{ + matdatas = mats; + this->m_color_type = color_type; + this->m_mFilter = mFilter; +} + +JpegBuffer::JpegBuffer() +{ + this->m_buffer = cv::Mat(); + this->m_color_type = 2; + this->m_side = 0; + this->m_mFilter = 0; +} + + +JpegBuffer::~JpegBuffer(void) +{ +} + + +unsigned char* JpegBuffer::getBuffer() +{ + return m_buffer.data; +} + +cv::Mat JpegBuffer::buffer() +{ + return m_buffer; +} + +int JpegBuffer::getSize() +{ + return m_buffer.cols; +} + + +cv::Mat JpegBuffer::getMat( int pixType) +{ + JpegLib jl; + cv::Mat image = jl.decode(m_buffer, pixType); + return image.clone(); +} + +std::vector JpegBuffer::getMats() +{ + std::vector retmats; + for (int i = 0; i < matdatas.size(); i++) + { + JpegLib jl; + cv::Mat image = jl.decode(matdatas[i], m_color_type); + retmats.push_back(image.clone()); + image.release(); + } + return retmats; +} + +int JpegBuffer::getMFilter() +{ + return m_mFilter; +} + +int JpegBuffer::getSide() +{ + return m_side; +} + +bool JpegBuffer::empty() +{ + return matdatas.empty(); +} diff --git a/huagao/Device/JpegBuffer.h b/huagao/Device/JpegBuffer.h new file mode 100644 index 00000000..d4d95645 --- /dev/null +++ b/huagao/Device/JpegBuffer.h @@ -0,0 +1,27 @@ +#pragma once +#include + +class JpegBuffer +{ +public: + JpegBuffer(cv::Mat buffer,int color_type=6,int side=0,int mFilter=0); + JpegBuffer(std::vector mats, int color_type = 6,int mFilter = 0); + JpegBuffer(); + virtual ~JpegBuffer(void); + + unsigned char* getBuffer(); + cv::Mat buffer(); + int getSize(); + cv::Mat getMat( int pixType); + std::vector getMats(); + int getMFilter(); + int getSide(); + bool empty(); + +private: + cv::Mat m_buffer; + std::vector matdatas; + int m_color_type; + int m_side; + int m_mFilter; +}; diff --git a/huagao/Device/JsonConfig.cpp b/huagao/Device/JsonConfig.cpp new file mode 100644 index 00000000..819de54d --- /dev/null +++ b/huagao/Device/JsonConfig.cpp @@ -0,0 +1,504 @@ +#include "StdAfx.h" +#include "JsonConfig.h" +#include +#include +#include +#include +#include "CJsonObject.hpp" + +JsonConfig::JsonConfig(void) +{ +} + + +JsonConfig::~JsonConfig(void) +{ +} + +/************************************************************************/ +/* ò */ +/************************************************************************/ +void JsonConfig::WriteToJson(PCONFIGPARAMS pConfigItem,const std::string fileNames,bool isConfigItem) +{ + + neb::CJsonObject outJson; + + outJson.AddEmptySubObject("Config");//header + outJson["Config"].Add(PIXTYPE,(int)(pConfigItem->Pixtype)); + outJson["Config"].Add(PAPARSIZE,(int)(pConfigItem->PaperSize)); + outJson["Config"].Add(AUTOCROP,(bool)(pConfigItem->EnAutoCrop),false); + outJson["Config"].Add(RESOLUTION,(int)(pConfigItem->Resolution)); + outJson["Config"].Add(DUPLEX,(int)(pConfigItem->Duplex)); + outJson["Config"].Add(DISCARBLANK,(bool)(pConfigItem->EnDiscardBlank),false); + outJson["Config"].Add(DISCARBLANKVINCE,(bool)(pConfigItem->EnDiscardBlankVince),false); + outJson["Config"].Add(DB_AREANUM, (int)(pConfigItem->DBlank_AreaNum)); + outJson["Config"].Add(DB_DEVNMAX, (int)(pConfigItem->DBlank_DevnMax)); + + outJson["Config"].Add(BRIGHTNESS,(float)(pConfigItem->Brightness)); + outJson["Config"].Add(AUTOCONTRAST,(bool)(pConfigItem->EnAutoContrast),false); + outJson["Config"].Add(CONTRAST,(float)(pConfigItem->Contrast)); + outJson["Config"].Add(GAMMA_,(int)(pConfigItem->Gamma)); + + outJson["Config"].Add(FILTERTYPE,(int)(pConfigItem->Filter)); + outJson["Config"].Add(SHARPENTYPE, (int)(pConfigItem->Sharpen)); + outJson["Config"].Add(AUTODESCREW,(bool)(pConfigItem->EnAutoDescrew),false); + outJson["Config"].Add(FILLBLACK,(bool)(pConfigItem->EnFillBlack),false); + outJson["Config"].Add(MULTIOUTPUT,(bool)(pConfigItem->EnMultiOutPutR),false); + outJson["Config"].Add(OUTHOLE,(bool)(pConfigItem->EnOutHole),false); + outJson["Config"].Add(OUTHOLERATIO,(int)(pConfigItem->OutHoleRatio)); + + outJson["Config"].Add(ULTRADETECT,(bool)(pConfigItem->EnUltrasonicDetect),false); + outJson["Config"].Add(BINDINGDETECT,(bool)(pConfigItem->EnBindingDetect),false); + outJson["Config"].Add(SCANCOUNT,(int)(pConfigItem->ScanCount)); + outJson["Config"].Add(DOCORIENTATION,(int)(pConfigItem->Orentation)); + outJson["Config"].Add(BACKROTATE180,(bool)(pConfigItem->EnBackRotate180),false); + outJson["Config"].Add(SCREWDETECT,(bool)(pConfigItem->EnScrewDetect),false); + outJson["Config"].Add(SCREWLEVEL,(int)(pConfigItem->ScrewDetectLevel)); + if (isConfigItem) + { + outJson["Config"].Add(ITEMCAPTION,(string)(pConfigItem->Caption)); + outJson["Config"].Add(SAVEPATH,(string)(pConfigItem->SavePath)); + } + std::ofstream os; + os.open(fileNames.c_str()); + os< cfgArray,const std::string filename) +{ + //Json::StyledWriter sw; + neb::CJsonObject root; + root.AddEmptySubObject("Config"); + root["Config"].AddEmptySubArray(PIXTYPE); + root["Config"].AddEmptySubArray(PAPARSIZE); + root["Config"].AddEmptySubArray(AUTOCROP); + root["Config"].AddEmptySubArray(RESOLUTION); + root["Config"].AddEmptySubArray(DUPLEX); + root["Config"].AddEmptySubArray(DISCARBLANK); + root["Config"].AddEmptySubArray(DISCARBLANKVINCE); + root["Config"].AddEmptySubArray(DB_AREANUM); + root["Config"].AddEmptySubArray(DB_DEVNMAX); + + root["Config"].AddEmptySubArray(BRIGHTNESS); + root["Config"].AddEmptySubArray(AUTOCONTRAST); + root["Config"].AddEmptySubArray(CONTRAST); + root["Config"].AddEmptySubArray(GAMMA_); + + root["Config"].AddEmptySubArray(FILTERTYPE); + root["Config"].AddEmptySubArray(SHARPENTYPE); + root["Config"].AddEmptySubArray(AUTODESCREW); + root["Config"].AddEmptySubArray(FILLBLACK); + root["Config"].AddEmptySubArray(MULTIOUTPUT); + root["Config"].AddEmptySubArray(OUTHOLE); + root["Config"].AddEmptySubArray(OUTHOLERATIO); + + root["Config"].AddEmptySubArray(ULTRADETECT); + root["Config"].AddEmptySubArray(BINDINGDETECT); + root["Config"].AddEmptySubArray(SCANCOUNT); + root["Config"].AddEmptySubArray(DOCORIENTATION); + root["Config"].AddEmptySubArray(BACKROTATE180); + root["Config"].AddEmptySubArray(SCREWDETECT); + root["Config"].AddEmptySubArray(SCREWLEVEL); + + root["Config"].AddEmptySubArray(ITEMCAPTION); + root["Config"].AddEmptySubArray(SAVEPATH); + for (int i = 0; i < cfgArray.size(); i++) + { + root["Config"][PIXTYPE].Add(cfgArray[i].Pixtype); + root["Config"][PAPARSIZE].Add(cfgArray[i].PaperSize); + root["Config"][AUTOCROP].Add(i, cfgArray[i].EnAutoCrop); + root["Config"][RESOLUTION].Add(cfgArray[i].Resolution); + root["Config"][DUPLEX].Add(cfgArray[i].Duplex); + root["Config"][DISCARBLANK].Add(i, cfgArray[i].EnDiscardBlank); + root["Config"][DISCARBLANKVINCE].Add(i, cfgArray[i].EnDiscardBlankVince); + root["Config"][DB_AREANUM].Add(cfgArray[i].DBlank_AreaNum); + root["Config"][DB_DEVNMAX].Add(cfgArray[i].DBlank_DevnMax); + + root["Config"][BRIGHTNESS].Add(cfgArray[i].Brightness); + root["Config"][AUTOCONTRAST].Add(i,cfgArray[i].EnAutoContrast); + root["Config"][CONTRAST].Add(cfgArray[i].Contrast); + root["Config"][GAMMA_].Add(cfgArray[i].Gamma); + + root["Config"][FILTERTYPE].Add(cfgArray[i].Filter); + root["Config"][SHARPENTYPE].Add(cfgArray[i].Sharpen); + root["Config"][AUTODESCREW].Add(i,cfgArray[i].EnAutoDescrew); + root["Config"][FILLBLACK].Add(i,cfgArray[i].EnFillBlack); + root["Config"][MULTIOUTPUT].Add(i,cfgArray[i].EnMultiOutPutR); + root["Config"][OUTHOLE].Add(i,cfgArray[i].EnOutHole); + root["Config"][OUTHOLERATIO].Add(cfgArray[i].OutHoleRatio); + + root["Config"][ULTRADETECT].Add(i,cfgArray[i].EnUltrasonicDetect); + root["Config"][BINDINGDETECT].Add(i,cfgArray[i].EnBindingDetect); + root["Config"][SCANCOUNT].Add(cfgArray[i].ScanCount); + root["Config"][DOCORIENTATION].Add(cfgArray[i].Orentation); + root["Config"][BACKROTATE180].Add(i,cfgArray[i].EnBackRotate180); + root["Config"][SCREWDETECT].Add(i,cfgArray[i].EnScrewDetect); + root["Config"][SCREWLEVEL].Add(cfgArray[i].ScrewDetectLevel); + + if (cfgArray[i].Caption.c_str()!=NULL) + { + root["Config"][ITEMCAPTION].Add(cfgArray[i].Caption); + } + if (cfgArray[i].SavePath.c_str()!=NULL) + { + root["Config"][SAVEPATH].Add(cfgArray[i].SavePath); + } + } + std::ofstream os; + os.open(filename.c_str()); + os< vc; + vc.push_back(GetDefaultConfigParams()); + WriteJsonArrayToFile(vc, dstpath); + return vc[0]; + } + _tcscat(szIniFile, TWAIN_JSON_NAME); + std::string s_default = TCHAR2STRING(szIniFile); + + vector vc; + vc=ReadJsonArrayFromFile(s_default.c_str()); + if (vc.size()!=0) + { + return vc[0]; + } + return GetDefaultConfigParams(); +} + +bool JsonConfig::DeleteJsonFile(std::string path) +{ + return (remove(path.c_str())); +} + +std::vector JsonConfig::ReadJsonArrayFromFile(const std::string filename) +{ + std::vector re; + FILE* file=fopen(filename.c_str(),"rb"); + if (!file) + { + return re; + } + fseek(file,0,SEEK_END); + long size=ftell(file); + fseek(file,0,SEEK_SET); + std::string text; + char* buffer=new char[size+1]; + buffer[size]=0; + if (!fread(buffer,1,size,file)==(unsigned long)size) + { + return re; + } + text=buffer; + fclose(file); + delete []buffer; + re=parseJsonFromString(text); + return re; +} + +CONFIGPARAMS JsonConfig::GetDefaultConfigParams() +{ + CONFIGPARAMS params; + params.Pixtype=1;//Ҷ + params.PaperSize=0;//A3 + params.EnAutoCrop=FALSE;//Զ + params.Resolution=2;//200dpi + params.Duplex=1;//˫ + params.EnDiscardBlank=FALSE;//Զհҳ + params.EnDiscardBlankVince=FALSE; + params.DBlank_AreaNum = 8; + params.DBlank_DevnMax = 200; + + params.Brightness=0.0f;// + params.EnAutoContrast=FALSE;//ԶԱȶ + params.Contrast=0;//Աȶ + params.Gamma=1.0f;//٤ֵ + + params.Filter=0;//ɫ + params.Sharpen = 0;// + params.EnFillBlack=FALSE;//ڿ + params.EnAutoDescrew=TRUE;//Զƫ + params.EnMultiOutPutR=FALSE;// + params.EnOutHole=FALSE;//ȥ׶ + params.OutHoleRatio=10;//Ĭֵ0.10 + + params.EnUltrasonicDetect=TRUE;//⿪ + params.EnBindingDetect=FALSE;//װ⿪ + params.ScanCount=-1;//ɨ + params.Orentation=0;//ת0 + params.EnBackRotate180=FALSE;//ת180 ת + params.EnScrewDetect=TRUE;//б + params.ScrewDetectLevel=3;//бȼ 3 + return params; +} + +std::vector JsonConfig::parseJsonFromString(const std::string str) +{ + + neb::CJsonObject root(str); + vector vcConfig; + + int size=0; + neb::CJsonObject itmPaparSize; + root["Config"].Get(PAPARSIZE,itmPaparSize); + size=itmPaparSize.GetArraySize(); + if (size>0) + { + neb::CJsonObject itmPixType; + root["Config"].Get(PIXTYPE,itmPixType); + neb::CJsonObject itmAutoCrop; + root["Config"].Get(AUTOCROP,itmAutoCrop); + neb::CJsonObject itmRes; + root["Config"].Get(RESOLUTION,itmRes); + neb::CJsonObject itmDulpex; + root["Config"].Get(DUPLEX,itmDulpex); + neb::CJsonObject itmDiscardBlk; + root["Config"].Get(DISCARBLANK,itmDiscardBlk); + neb::CJsonObject itmDiscardBlkVince; + root["Config"].Get(DISCARBLANKVINCE,itmDiscardBlkVince); + neb::CJsonObject itmDBAreaNum; + root["Config"].Get(DB_AREANUM, itmDBAreaNum); + neb::CJsonObject itmDBDevnMax; + root["Config"].Get(DB_DEVNMAX, itmDBDevnMax); + + neb::CJsonObject itmBrtnes; + root["Config"].Get(BRIGHTNESS,itmBrtnes); + neb::CJsonObject itmAutoCrnt; + root["Config"].Get(AUTOCONTRAST,itmAutoCrnt); + neb::CJsonObject itmContrast; + root["Config"].Get(CONTRAST,itmContrast); + neb::CJsonObject itmGamma; + root["Config"].Get(GAMMA_,itmGamma); + + neb::CJsonObject itmFilter; + root["Config"].Get(FILTERTYPE,itmFilter); + neb::CJsonObject itmSharpen; + root["Config"].Get(SHARPENTYPE, itmSharpen); + neb::CJsonObject itmAutoDescrew; + root["Config"].Get(AUTODESCREW,itmAutoDescrew); + neb::CJsonObject itmFillBlack; + root["Config"].Get(FILLBLACK,itmFillBlack); + neb::CJsonObject itmMultiOutput; + root["Config"].Get(MULTIOUTPUT,itmMultiOutput); + neb::CJsonObject itmOutHole; + root["Config"].Get(OUTHOLE,itmOutHole); + neb::CJsonObject itmOutHoleRatio; + root["Config"].Get(OUTHOLERATIO,itmOutHoleRatio); + + neb::CJsonObject itmUltDetect; + root["Config"].Get(ULTRADETECT,itmUltDetect); + neb::CJsonObject itmBingdingDetect; + root["Config"].Get(BINDINGDETECT,itmBingdingDetect); + neb::CJsonObject itmScanCount; + root["Config"].Get(SCANCOUNT,itmScanCount); + neb::CJsonObject itmDocOrientation; + root["Config"].Get(DOCORIENTATION,itmDocOrientation); + neb::CJsonObject itmBackRotate; + root["Config"].Get(BACKROTATE180,itmBackRotate); + neb::CJsonObject itmScrewDetct; + root["Config"].Get(SCREWDETECT,itmScrewDetct); + neb::CJsonObject itmScrewLevel; + root["Config"].Get(SCREWLEVEL,itmScrewLevel); + + neb::CJsonObject itmCaption; + if (!root["Config"][ITEMCAPTION].IsEmpty()) + { + root["Config"].Get(ITEMCAPTION,itmCaption); + } + neb::CJsonObject itmSavePtah; + if (!root["Config"][SAVEPATH].IsEmpty()) + { + root["Config"].Get(SAVEPATH,itmSavePtah); + } + for (int i=0;i + +using namespace std; + +class JsonConfig +{ +public: + JsonConfig(void); + ~JsonConfig(void); +public: + void WriteToJson(PCONFIGPARAMS pConfigItem,const std::string fileName,bool isConfigItem=true); + //PCONFIGPARAMS ReadJsonFromFile(const char* fileNames); + void WriteJsonData(const std::string fileName); + void WriteJsonArrayToFile(std::vector cfgArray,const std::string filename); + CONFIGPARAMS ReadDefaultConfig(); + bool DeleteJsonFile(std::string path); + std::vector ReadJsonArrayFromFile(const std::string filename); + CONFIGPARAMS GetDefaultConfigParams(); +private: + std::vector parseJsonFromString(const std::string str) ; +}; + diff --git a/huagao/Device/PaperSize.cpp b/huagao/Device/PaperSize.cpp new file mode 100644 index 00000000..fa5475a9 --- /dev/null +++ b/huagao/Device/PaperSize.cpp @@ -0,0 +1,174 @@ +#include "stdafx.h" +#include "PaperSize.h" + +using namespace std; + +namespace Device { + + PaperSize::PaperSize() + { + InitPaperMap(); + } + + + PaperSize::~PaperSize() + { + } + + void PaperSize::InitPaperMap() + { + //!< Ӧ + dpiDct[{None, 50.0f}] = CSize(594, 898); + dpiDct[{None, 75.0f}] = CSize(892, 1347); + dpiDct[{None, 100.0f}] = CSize(1189, 1795); + dpiDct[{None, 150.0f}] = CSize(1784, 2693); + dpiDct[{None, 200.0f}] = CSize(2338, 3307); + dpiDct[{None, 240.0f}] = CSize(2854, 4308); + dpiDct[{None, 300.0f}] = CSize(3567, 5385); + dpiDct[{None, 400.0f}] = CSize(4756, 7180); + dpiDct[{None, 600.0f}] = CSize(7134, 10770); + + //A3 + dpiDct[{A3, 50.0f}] = CSize(585, 827); + dpiDct[{A3, 75.0f}] = CSize(877, 1240); + dpiDct[{A3, 100.0f}] = CSize(1169, 1653); + dpiDct[{A3, 150.0f}] = CSize(1753, 2480); + dpiDct[{A3, 200.0f}] = CSize(2338, 3307); + dpiDct[{A3, 240.0f}] = CSize(2806, 3968); + dpiDct[{A3, 300.0f}] = CSize(3507, 4960); + dpiDct[{A3, 400.0f}] = CSize(4677, 6614); + dpiDct[{A3, 600.0f}] = CSize(7015, 9921); + //add lyc 2019 12 18 + //A4 + dpiDct[{A4, 50.0f}] = CSize(413, 585); + dpiDct[{A4, 75.0f}] = CSize(620, 877); + dpiDct[{A4, 100.0f}] = CSize(826, 1169); + dpiDct[{A4, 150.0f}] = CSize(1240, 1753); + dpiDct[{A4, 200.0f}] = CSize(1653, 2338); + dpiDct[{A4, 240.0f}] = CSize(1984, 2806); + dpiDct[{A4, 300.0f}] = CSize(2480, 3507); + dpiDct[{A4, 400.0f}] = CSize(3307, 4677); + dpiDct[{A4, 600.0f}] = CSize(4960, 7015); + //add lyc 2019 12 18 A5 + dpiDct[{A5, 50.0f}] = CSize(291, 413); + dpiDct[{A5, 75.0f}] = CSize(437, 620); + dpiDct[{A5, 100.0f}] = CSize(582, 826); + dpiDct[{A5, 150.0f}] = CSize(874, 1240); + dpiDct[{A5, 200.0f}] = CSize(1165, 1653); + dpiDct[{A5, 240.0f}] = CSize(1398, 1984); + dpiDct[{A5, 300.0f}] = CSize(1748, 2480); + dpiDct[{A5, 400.0f}] = CSize(2330, 3307); + dpiDct[{A5, 600.0f}] = CSize(3496, 4960); + + //add lyc 2019 12 18 A6 + dpiDct[{A6, 50.0f}] = CSize(207, 291); + dpiDct[{A6, 75.0f}] = CSize(310, 437); + dpiDct[{A6, 100.0f}] = CSize(413, 582); + dpiDct[{A6, 150.0f}] = CSize(620, 874); + dpiDct[{A6, 200.0f}] = CSize(826, 1165); + dpiDct[{A6, 240.0f}] = CSize(992, 1398); + dpiDct[{A6, 300.0f}] = CSize(1240, 1748); + dpiDct[{A6, 400.0f}] = CSize(1653, 2330); + dpiDct[{A6, 600.0f}] = CSize(2480, 3496); + + dpiDct[{USStatement, 50.0f}] = CSize(585, 827 * 1.5); + dpiDct[{USStatement, 75.0f}] = CSize(877, 1240 * 1.5); + dpiDct[{USStatement, 100.0f}] = CSize(1169, 1653 * 1.5); + dpiDct[{USStatement, 150.0f}] = CSize(1753, 2480 * 1.5); + dpiDct[{USStatement, 200.0f}] = CSize(2338, 3307 * 1.5); + dpiDct[{USStatement, 240.0f}] = CSize(2806, 3968 * 1.5); + dpiDct[{USStatement, 300.0f}] == CSize(3507, 4960 * 1.5); + dpiDct[{USStatement, 400.0f}] = CSize(4677, 6614 * 1.5); + dpiDct[{USStatement, 600.0f}] = CSize(7015, 9921 * 1.5); + //add lyc 2019 12 18 ĸ壬2A3 + dpiDct[{MaxSize, 50.0f}] = CSize(585, 1653); + dpiDct[{MaxSize, 75.0f}] = CSize(877, 2480); + dpiDct[{MaxSize, 100.0f}] = CSize(1169, 1653 * 2); + dpiDct[{MaxSize, 150.0f}] = CSize(1753, 2480 * 2); + dpiDct[{MaxSize, 200.0f}] = CSize(2338, 3307 * 2); + dpiDct[{MaxSize, 240.0f}] = CSize(2806, 3968 * 2); + dpiDct[{MaxSize, 300.0f}] = CSize(3507, 4960 * 2); + dpiDct[{MaxSize, 400.0f}] = CSize(4677, 6614 * 2); + dpiDct[{MaxSize, 600.0f}] = CSize(7015, 9921 * 2); + //add lyc 2019 12 18 B4 + dpiDct[{B4, 50.0f}] = CSize(506, 717); + dpiDct[{B4, 75.0f}] = CSize(759, 1075); + dpiDct[{B4, 100.0f}] = CSize(1011, 1433); + dpiDct[{B4, 150.0f}] = CSize(1517, 2149); + dpiDct[{B4, 200.0f}] = CSize(2023, 2866); + dpiDct[{B4, 240.0f}] = CSize(2428, 3439); + dpiDct[{B4, 300.0f}] = CSize(3035, 4299); + dpiDct[{B4, 400.0f}] = CSize(4047, 5732); + dpiDct[{B4, 600.0f}] = CSize(6070, 8598); + //add lyc 2019 12 18 B5 + dpiDct[{B5, 50.0f}] = CSize(358, 506); + dpiDct[{B5, 75.0f}] = CSize(537, 759); + dpiDct[{B5, 100.0f}] = CSize(716, 1011); + dpiDct[{B5, 150.0f}] = CSize(1074, 1517); + dpiDct[{B5, 200.0f}] = CSize(1433, 2023); + dpiDct[{B5, 240.0f}] = CSize(1719, 2428); + dpiDct[{B5, 300.0f}] = CSize(2149, 3035); + dpiDct[{B5, 400.0f}] = CSize(2866, 4047); + dpiDct[{B5, 600.0f}] = CSize(4299, 6070); + //add lyc 2019 12 18 B6 + dpiDct[{B6, 50.0f}] = CSize(252, 358); + dpiDct[{B6, 75.0f}] = CSize(378, 537); + dpiDct[{B6, 100.0f}] = CSize(503, 716); + dpiDct[{B6, 150.0f}] = CSize(755, 1074); + dpiDct[{B6, 200.0f}] = CSize(1007, 1433); + dpiDct[{B6, 240.0f}] = CSize(1209, 1719); + dpiDct[{B6, 300.0f}] = CSize(1511, 2149); + dpiDct[{B6, 400.0f}] = CSize(2015, 2866); + dpiDct[{B6, 600.0f}] = CSize(3023, 4299); + + //add lyc 2019 12 18 DOUBLE LETTER + dpiDct[{USLedger, 50.0f}] = CSize(550, 850); + dpiDct[{USLedger, 75.0f}] = CSize(825, 1275); + dpiDct[{USLedger, 100.0f}] = CSize(1100, 1700); + dpiDct[{USLedger, 150.0f}] = CSize(1650, 2550); + dpiDct[{USLedger, 200.0f}] = CSize(2200, 3400); + dpiDct[{USLedger, 240.0f}] = CSize(2640, 4080); + dpiDct[{USLedger, 300.0f}] = CSize(3300, 5100); + dpiDct[{USLedger, 400.0f}] = CSize(4400, 6800); + dpiDct[{USLedger, 600.0f}] = CSize(6600, 10200); + //add lyc 2019 12 18 LETTER + dpiDct[{USLetter, 50.0f}] = CSize(425, 550); + dpiDct[{USLetter, 75.0f}] = CSize(638, 825); + dpiDct[{USLetter, 100.0f}] = CSize(850, 1100); + dpiDct[{USLetter, 150.0f}] = CSize(1275, 1650); + dpiDct[{USLetter, 200.0f}] = CSize(1700, 2200); + dpiDct[{USLetter, 240.0f}] = CSize(2040, 2640); + dpiDct[{USLetter, 300.0f}] = CSize(2550, 3300); + dpiDct[{USLetter, 400.0f}] = CSize(3400, 4400); + dpiDct[{USLetter, 600.0f}] = CSize(5100, 6600); + + //add lyc 2019 12 18 LETTER + dpiDct[{USLegal, 50.0f}] = CSize(425, 700); + dpiDct[{USLegal, 75.0f}] = CSize(638, 1050); + dpiDct[{USLegal, 100.0f}] = CSize(850, 1400); + dpiDct[{USLegal, 150.0f}] = CSize(1275, 2100); + dpiDct[{USLegal, 200.0f}] = CSize(1700, 2800); + dpiDct[{USLegal, 240.0f}] = CSize(2040, 3360); + dpiDct[{USLegal, 300.0f}] = CSize(2550, 4200); + dpiDct[{USLegal, 400.0f}] = CSize(3400, 5600); + dpiDct[{USLegal, 600.0f}] = CSize(5100, 8400); + } + + CSize PaperSize::GetPaperSize(DWORD paperType, float dpi,int orentation) + { + auto iter = dpiDct.find({(TwSS)paperType, dpi}); + if (iter != dpiDct.end()) { + if (orentation == 0)//Ҫת + return iter->second; + else if(orentation == 3)//תʮ + { + CSize size; + size.cx = iter->second.cy; + size.cy = iter->second.cx; + return size; + } + } + return CSize(2338, 3307); + } + +} diff --git a/huagao/Device/PaperSize.h b/huagao/Device/PaperSize.h new file mode 100644 index 00000000..9884b0b9 --- /dev/null +++ b/huagao/Device/PaperSize.h @@ -0,0 +1,80 @@ +#pragma once +#include + +enum TwSS : unsigned short +{ + None = 0, + A4Letter = 1, + A4 = 1, + B5Letter = 2, + JISB5 = 2, + B5 = 2, + USLetter = 3, + USLegal = 4, + A5 = 5, + B4 = 6, + ISOB4 = 6, + B6 = 7, + ISOB6 = 7, + USLedger = 9, + USExecutive = 10, + A3 = 11, + B3 = 12, + ISOB3 = 12, + A6 = 13, + C4 = 14, + C5 = 15, + C6 = 16, + _4A0 = 17, + _2A0 = 18, + A0 = 19, + A1 = 20, + A2 = 21, + A7 = 22, + A8 = 23, + A9 = 24, + A10 = 25, + ISOB0 = 26, + ISOB1 = 27, + ISOB2 = 28, + ISOB5 = 29, + ISOB7 = 30, + ISOB8 = 31, + ISOB9 = 32, + ISOB10 = 33, + JISB0 = 34, + JISB1 = 35, + JISB2 = 36, + JISB3 = 37, + JISB4 = 38, + JISB6 = 39, + JISB7 = 40, + JISB8 = 41, + JISB9 = 42, + JISB10 = 43, + C0 = 44, + C1 = 45, + C2 = 46, + C3 = 47, + C7 = 48, + C8 = 49, + C9 = 50, + C10 = 51, + USStatement = 52, + BusinessCard = 53, + MaxSize = 54, +}; + +namespace Device { + class PaperSize + { + public: + PaperSize(); + ~PaperSize(); + private: + void InitPaperMap(); + std::map, CSize> dpiDct; + public: + CSize GetPaperSize(DWORD paperType, float dpi, int orentation); + }; +} diff --git a/huagao/Device/PublicFunc.cpp b/huagao/Device/PublicFunc.cpp new file mode 100644 index 00000000..d26473aa --- /dev/null +++ b/huagao/Device/PublicFunc.cpp @@ -0,0 +1,722 @@ +#include "stdafx.h" +#include "PublicFunc.h" +#include "CTwainMutex.h" +#include + +TCHAR* GetUserCustomFilePath(HWND hWin, TCHAR* lpFilePath, TCHAR* lp_head_text) +{ + if (lpFilePath == NULL) + { + return NULL; + } + + BROWSEINFO bi = { 0 }; + TCHAR szBuffer[MAX_PATH] = { 0 }; + + memset(&bi, 0, sizeof(BROWSEINFO)); + + + bi.hwndOwner = hWin; + bi.pszDisplayName = GetExistFileDir(lpFilePath); + bi.ulFlags = BIF_RETURNONLYFSDIRS | BIF_SHAREABLE | BIF_USENEWUI | BIF_RETURNFSANCESTORS; + + LPITEMIDLIST pIDList = NULL; + LPMALLOC lpMalloc = NULL; + //m_pUI_INI->GetMessageBoxStr(szBuffer, sizeof(szBuffer), 1041); + //bi.lpszTitle = szBuffer;//1041=ѡļ洢· + bi.lpszTitle = lp_head_text;//TEXT("ѡ½ļ"); + bi.lpfn = (BFFCALLBACK)BrowserCallbackProc; //ص + bi.lParam = (LPARAM)lpFilePath; //صʹõIJ趨Ĭ· + + pIDList = SHBrowseForFolder(&bi); + if (pIDList != NULL) + { + SHGetPathFromIDList(pIDList, lpFilePath); + } + if (SHGetMalloc(&lpMalloc)) + { + return NULL; //ͷڴ + } + if (pIDList == NULL) + { + return NULL; //ͷڴ + } + lpMalloc->Free(pIDList); + lpMalloc->Release(); + pIDList = NULL; + lpMalloc = NULL; + //_tcscpy(lpFilePath, szBuffer2); + return lpFilePath; +} + +TCHAR* GetCurExeFilePath(HINSTANCE hInstance, TCHAR* lpPath, DWORD dwSize) +{ + INT nRet = 0x0L; + TCHAR* p = NULL; + if (lpPath == NULL || dwSize == 0) + { + return NULL; + } + nRet = GetModuleFileName(hInstance, lpPath, dwSize); + if (nRet > 0) + { + p = _tcsrchr(lpPath, TEXT('\\')); + if (p != NULL) + { + *(p + 1) = TEXT('\0'); + } + else + { + return NULL; + } + } + else + { + return NULL; + } + return lpPath; +} + +TCHAR* GetExistFileDir(TCHAR* p_file_path) +{ + WIN32_FIND_DATA wfd = { 0 }; + LPSTR p_test = NULL; + HANDLE hFindFile = INVALID_HANDLE_VALUE; + + if (p_file_path == NULL) + return NULL; + + hFindFile = FindFirstFile(p_file_path, &wfd); + if (hFindFile != NULL) + { + FindClose(hFindFile); + hFindFile = INVALID_HANDLE_VALUE; + } + if (wfd.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY) + { + return p_file_path; + } + + p_test = (LPSTR)(_tcsrchr(p_file_path, '\\')); + if (p_test != NULL) + { + *p_test = 0; + return GetExistFileDir(p_file_path); + } + else + { + return NULL; + } +} + +DWORD CALLBACK BrowserCallbackProc(HWND hWnd, UINT uMsg, WPARAM wParam, LPARAM lParam) +{ + switch (uMsg) + { + case BFFM_INITIALIZED: //LPARAM(TEXT("D:\\test_adf_project")) + SendMessage(hWnd, BFFM_SETSELECTION, TRUE, lParam); //lpDataһ info.lParam ҲĬ· + break; + default: + break; + } + return 0; +} + +BOOL isFolderExist(char* folder) +{ + int ret = 0; + + ret = _access(folder, 0); + if (ret == 0) + ret = TRUE; + else + ret = FALSE; + + return ret; +} + +int32_t createDirectory(char* directoryPath) +{ + uint32_t dirPathLen = 0; + if (directoryPath != NULL) { + dirPathLen = strlen(directoryPath); + } + if (dirPathLen > FILENAME_MAX) + { + return -1; + } + char tmpDirPath[FILENAME_MAX] = { 0 }; + for (uint32_t i = 0; i < dirPathLen; ++i) + { + tmpDirPath[i] = directoryPath[i]; + if (tmpDirPath[i] == '\\' || tmpDirPath[i] == '/') + { + if (!isFolderExist(tmpDirPath)) + { + int ret = _mkdir(tmpDirPath); + if (ret != 0) + return -1; + } + } + } + return 0; +} + +float GetContrast(int level) +{ + float ret = 0.0; + switch (level) + { + case -3: + ret = -1000.0; + break; + case -2: + ret = -666.0; + break; + case -1: + ret = -333.0; + break; + case 1: + ret = 333.0; + break; + case 2: + ret = 666.0; + break; + case 3: + ret = 1000.0; + break; + } + return ret; +} + +char* THCAR2char(TCHAR* tchStr) +{ + int iLen = 2 * wcslen(tchStr);//CString,TCHARһַ˲ͨ㳤 + char* chRtn = new char[iLen + 1]; + wcstombs(chRtn, tchStr, iLen + 1);//תɹΪǸֵ + return chRtn; +} + +BOOL CheckAndCreateFileDir(TCHAR* p_file_path, BOOL flg) +{ + TCHAR szTmp[MAX_PATH] = { 0 }; + WIN32_FIND_DATA wfd = { 0 }; + INT len = 0; + INT pos = 0; + BOOL bFlg = FALSE; + HANDLE hFindFile = INVALID_HANDLE_VALUE; + + if (p_file_path == NULL) + return FALSE; + + if (*p_file_path >= 'a' && *p_file_path <= 'z' || *p_file_path >= 'A' && *p_file_path <= 'Z') + { + if (*(p_file_path + 1) != ':' && *(p_file_path + 2) != '\\') + { + return FALSE; + } + } + if (_access(THCAR2char(p_file_path), 0) == 0) + { + return TRUE; + } + + if (!flg) + return FALSE; + + if (CreateDirectory(p_file_path, NULL)) + return TRUE; + + _tcscpy(szTmp, p_file_path); + + len = (INT)_tcslen(szTmp); + + bFlg = FALSE; + while (len) + { + if (*(szTmp + len - 1) == '\\') + { + bFlg = TRUE; + break; + } + len--; + } + if (bFlg) + { + *(szTmp + len - 1) = 0; + CheckAndCreateFileDir(szTmp, flg); + return CreateDirectory(p_file_path, NULL); + } + else + return FALSE; +} + +BOOL CheckDiskFreeBitM(HWND hWin, TCHAR* p_disk_name, DWORD dw_min_bit_m) +{ + TCHAR* p = NULL; + TCHAR sz_root_path_name[MAX_PATH + 1] = { 0 }; + INT len = 0; + + DWORD dwTotalDiskSpace = 0; + DWORD dwFreeDiskSpace = 0; + DWORD dwUsedDiskSpace = 0; + + ULARGE_INTEGER uiFreeBytesAvailableToCaller; + ULARGE_INTEGER uiTotalNumberOfBytes; + ULARGE_INTEGER uiTotalNumberOfFreeBytes; + + UINT un_ret = 0; + if (p_disk_name == NULL) + return FALSE; + + len = _tcslen(p_disk_name); + if (len > MAX_PATH) + { + len = MAX_PATH; + } + + memcpy(sz_root_path_name, p_disk_name, (size_t)len); + + p = sz_root_path_name; + //p = _tcsstr(sz_root_path_name, "\\"); + if (p == NULL) + { + if (len == 2) + { + if (!((sz_root_path_name[0] >= 'A' && sz_root_path_name[0] <= 'Z' || sz_root_path_name[0] >= 'a' && sz_root_path_name[0] <= 'z') && sz_root_path_name[1] == ':')) + return FALSE; + } + else + return FALSE; + } + if (p != NULL) + *(p + 1) = 0; + un_ret = GetDriveType(sz_root_path_name); + if (un_ret == 0 || un_ret == 1) + { + return FALSE; + } + + if (GetDiskFreeSpaceEx(sz_root_path_name, &uiFreeBytesAvailableToCaller, &uiTotalNumberOfBytes, &uiTotalNumberOfFreeBytes)) + { + //dwTotalDiskSpace = (DWORD)(uiTotalNumberOfBytes.QuadPart / 1024 / 1024); + dwFreeDiskSpace = (DWORD)(uiFreeBytesAvailableToCaller.QuadPart >> 20); + //dwUsedDiskSpace = dwTotalDiskSpace - dwFreeDiskSpace; + if (dwFreeDiskSpace < dw_min_bit_m) + { + //ShowErrorStr(hWin, 1101);//1101=̿ռ䲻 + return FALSE; + } + } + else + { + //GetErrorMessage(NULL, 0, FALSE); + return FALSE; + } + //ShowErrorStr(hWin, 1101);//1101=̿ռ䲻 + //return FALSE; + return TRUE; +} + +HBITMAP SetButtonStaticBkBmp(HINSTANCE hInst, HWND hWin, UINT id, UINT iamge_id) +{ + + UINT ctr_msg = 0; + UINT str_iamge_type = 0; + HBITMAP hBitmap = NULL; + HBITMAP hOldBitmap = NULL; + //BS_ICON BS_BITMAP + //SS_BITMAP|SS_CENTERIMAGE SS_ICON + + LONG ctr_s = 0; + ctr_s = GetWindowLong(GetDlgItem(hWin, id), GWL_STYLE); + + ctr_msg = STM_SETIMAGE; + ctr_s |= SS_BITMAP | SS_CENTERIMAGE | SS_RIGHT; + + hBitmap = LoadBitmap(hInst, MAKEINTRESOURCE(iamge_id)); + + if (hBitmap == NULL) + { + return NULL; + } + + SetWindowLong(GetDlgItem(hWin, id), GWL_STYLE, ctr_s); + hOldBitmap = (HBITMAP)SendDlgItemMessage(hWin, id, ctr_msg, IMAGE_BITMAP, (LPARAM)hBitmap); + if (hOldBitmap != NULL) + { + DeleteObject(hOldBitmap); + hOldBitmap = NULL; + } + DeleteObject(hBitmap); + hBitmap = NULL; + return hBitmap; +} + +void writelog(std::string msg) +{ + TCHAR cfFilePath[MAX_PATH] = { 0 }; + SHGetSpecialFolderPath(NULL, cfFilePath, CSIDL_LOCAL_APPDATA, TRUE); + _tcscat(cfFilePath, HUAGAO_SCAN); + _tcscat(cfFilePath, TWAIN_ERROR_PATH); + std::string tmpstr = TCHAR2STRING(cfFilePath); + if (!isFolderExist((char*)tmpstr.c_str())) { + createDirectory((char*)tmpstr.c_str()); + } + CString filePath(cfFilePath); + filePath += TWAIN_ERROR_LOG_NAME; + std::string savepath = TCHAR2STRING(filePath.GetBuffer()); + + std::ofstream ofs(savepath, std::ios::app); + SYSTEMTIME sys; + GetLocalTime(&sys); + ofs << sys.wYear << "/" << sys.wMonth << "/" << sys.wDay << " " << sys.wHour << ":" << sys.wMinute << ":" << sys.wSecond << ":" << sys.wMilliseconds << " " << msg << std::endl; + ofs.close(); +} + +std::string TCHAR2STRING(TCHAR* STR) +{ + int iLen = WideCharToMultiByte(CP_ACP, 0, STR, -1, NULL, 0, NULL, NULL); + char* chRtn = new char[iLen * sizeof(char)]; + WideCharToMultiByte(CP_ACP, 0, STR, -1, chRtn, iLen, NULL, NULL); + std::string str(chRtn); + return str; +} + +std::string UtfToString(std::string strValue) +{ + int nwLen = ::MultiByteToWideChar(CP_ACP, 0, strValue.c_str(), -1, NULL, 0); + wchar_t* pwBuf = new wchar_t[nwLen + 1];//ĩβ'\0' + ZeroMemory(pwBuf, nwLen * 2 + 2); + ::MultiByteToWideChar(CP_ACP, 0, strValue.c_str(), strValue.length(), pwBuf, nwLen); + int nLen = ::WideCharToMultiByte(CP_UTF8, 0, pwBuf, -1, NULL, NULL, NULL, NULL); + char* pBuf = new char[nLen + 1]; + ZeroMemory(pBuf, nLen + 1); + ::WideCharToMultiByte(CP_UTF8, 0, pwBuf, nwLen, pBuf, nLen, NULL, NULL); + std::string retStr(pBuf); + delete[]pwBuf; + delete[]pBuf; + pwBuf = NULL; + pBuf = NULL; + return retStr; +} + + +std::string StringToUtf(std::string strValue) +{ + int nwLen = MultiByteToWideChar(CP_UTF8, 0, strValue.c_str(), -1, NULL, 0); + wchar_t* pwBuf = new wchar_t[nwLen + 1];//ĩβ'\0' + memset(pwBuf, 0, nwLen * 2 + 2); + MultiByteToWideChar(CP_UTF8, 0, strValue.c_str(), strValue.length(), pwBuf, nwLen); + int nLen = WideCharToMultiByte(CP_ACP, 0, pwBuf, -1, NULL, NULL, NULL, NULL); + char* pBuf = new char[nLen + 1]; + memset(pBuf, 0, nLen + 1); + WideCharToMultiByte(CP_ACP, 0, pwBuf, nwLen, pBuf, nLen, NULL, NULL); + std::string retStr = pBuf; + delete[]pBuf; + delete[]pwBuf; + return retStr; +} + +int GetContrastLevel(float contrast) { + int ret = 4; + if (contrast >= -1000.0f && contrast < -666.0f) { ret = 1; } + else if (contrast >= -666.0f && contrast < -333.0f) { ret = 2; } + else if (contrast >= -333.0f && contrast < 0.0f) { ret = 3; } + else if (contrast > 0.0f && contrast < 333.0f) { ret = 5; } + else if (contrast >= 333.0f && contrast < 666.0f) { ret = 6; } + else if (contrast >= 666.0f && contrast <= 1000.0f) { ret = 7; } + return ret; +} + +int GetMappingBrightnessValue(float in) +{ + float ratio = 254 / 2000.0f; + int ret = 0; + ret = (int)(ratio * in) + 128; + return ret; +} + +int GetMappingContrastValue(float in) { + int ret = 0; + float ratio = 72 / 2000.0f; + ret = (int)(in * ratio); + return ret; +} + +string getOSInfo() { + string iosinfo; + OSVERSIONINFOEX osver = { sizeof(OSVERSIONINFOEX) }; + osver.dwOSVersionInfoSize = sizeof(OSVERSIONINFOEX); + GetVersionEx((OSVERSIONINFO*)(&osver)); + if (osver.dwMajorVersion == 5 && osver.dwMinorVersion == 0) + iosinfo = "Windows 2000"; + else if (osver.dwMajorVersion == 5 && osver.dwMinorVersion == 1) + iosinfo = "Windows XP"; + else if (osver.dwMajorVersion == 5 && osver.dwMinorVersion == 2) { + if (GetSystemMetrics(SM_SERVERR2) != 0) { iosinfo = "Windows Server 2003 R2"; } + else { iosinfo = "Windows Server 2003"; } + } + else if (osver.dwMajorVersion == 6 && osver.dwMinorVersion == 0) { + if (osver.wProductType == VER_NT_WORKSTATION) { iosinfo = "Windows Vista"; } + else { iosinfo = "Windows Server 2008"; } + } + else if (osver.dwMajorVersion == 6 && osver.dwMinorVersion == 1) { + if (osver.wProductType == VER_NT_WORKSTATION) { iosinfo = "Windows 7"; } + else { iosinfo = "Windows Server 2008 R2"; } + } + else if (osver.dwMajorVersion == 6 && osver.dwMinorVersion == 2) { + if (osver.wProductType == VER_NT_WORKSTATION) { iosinfo = "Windows 8"; } + else { iosinfo = "Windows Server 2012"; } + } + else if (osver.dwMajorVersion == 6 && osver.dwMinorVersion == 3) { + if (osver.wProductType == VER_NT_WORKSTATION) { iosinfo = "Windows 8.1"; } + else { iosinfo = "Windows Server 2012 R2"; } + } + else if (osver.dwMajorVersion == 10 && osver.dwMinorVersion == 0) { + if (osver.wProductType == VER_NT_WORKSTATION) { iosinfo = "Windows 10"; } + else { iosinfo = "Windows Server 2016"; } + } + else + iosinfo = "unkown system"; + return iosinfo; +} + +#ifdef _WIN64 + +// method 2: usde winapi, works for x86 and x64 +#include +string getCpuInfo() +{ + string retinfo; + int cpuInfo[4] = { -1 }; + char cpu_manufacture[32] = { 0 }; + char cpu_type[32] = { 0 }; + char cpu_freq[32] = { 0 }; + + __cpuid(cpuInfo, 0x80000002); + memcpy(cpu_manufacture, cpuInfo, sizeof(cpuInfo)); + + __cpuid(cpuInfo, 0x80000003); + memcpy(cpu_type, cpuInfo, sizeof(cpuInfo)); + + __cpuid(cpuInfo, 0x80000004); + memcpy(cpu_freq, cpuInfo, sizeof(cpuInfo)); + + string mfc(cpu_manufacture); + string cputype(cpu_type); + string cpufreq(cpu_freq); + retinfo = mfc + cputype + cpufreq; + return retinfo; +} + +#else + +// mothed 1: this kind asm embedded in code only works in x86 build +// save 4 register variables +DWORD deax; +DWORD debx; +DWORD decx; +DWORD dedx; + +// init cpu in assembly language +void initCpu(DWORD veax) +{ + __asm + { + mov eax, veax + cpuid + mov deax, eax + mov debx, ebx + mov decx, ecx + mov dedx, edx + } +} + +long getCpuFreq() +{ + int start, over; + _asm + { + RDTSC + mov start, eax + } + Sleep(50); + _asm + { + RDTSC + mov over, eax + } + return (over - start) / 50000; +} + +std::string getManufactureID() +{ + char manuID[25]; + memset(manuID, 0, sizeof(manuID)); + + initCpu(0); + memcpy(manuID + 0, &debx, 4); // copy to array + memcpy(manuID + 4, &dedx, 4); + memcpy(manuID + 8, &decx, 4); + + return string(manuID); +} + +std::string getCpuType() +{ + const DWORD id = 0x80000002; // start 0x80000002 end to 0x80000004 + char cpuType[49]; + memset(cpuType, 0, sizeof(cpuType)); + + for (DWORD t = 0; t < 3; t++) + { + initCpu(id + t); + + memcpy(cpuType + 16 * t + 0, &deax, 4); + memcpy(cpuType + 16 * t + 4, &debx, 4); + memcpy(cpuType + 16 * t + 8, &decx, 4); + memcpy(cpuType + 16 * t + 12, &dedx, 4); + } + + return string(cpuType); +} + +#endif + + +// ---- get memory info ---- // +string getMemoryInfo() +{ + std::string memory_info; + MEMORYSTATUSEX statusex; + statusex.dwLength = sizeof(statusex); + if (GlobalMemoryStatusEx(&statusex)) + { + unsigned long long total = 0, remain_total = 0, avl = 0, remain_avl = 0; + double decimal_total = 0, decimal_avl = 0; + remain_total = statusex.ullTotalPhys % GBYTES; + total = statusex.ullTotalPhys / GBYTES; + avl = statusex.ullAvailPhys / GBYTES; + remain_avl = statusex.ullAvailPhys % GBYTES; + if (remain_total > 0) + decimal_total = (remain_total / MBYTES) / DKBYTES; + if (remain_avl > 0) + decimal_avl = (remain_avl / MBYTES) / DKBYTES; + + decimal_total += (double)total; + decimal_avl += (double)avl; + char buffer[kMaxInfoBuffer]; + sprintf_s(buffer, kMaxInfoBuffer, "total %.2f GB (%.2f GB available)", decimal_total, decimal_avl); + memory_info.append(buffer); + } + return memory_info; +} + +void GetDiskInfo(DWORD& dwNum, CString chDriveInfo[]) +{ + DWORD DiskCount = 0; + + //The number of logical drivers in the system can be obtained by using the GetLogicalDrives() function, which returns a 32-bit unsigned integer data. + DWORD DiskInfo = GetLogicalDrives(); + + //Cyclic operations are used to see if each bit of data is 1, if 1, the disk is true, and if 0, the disk does not exist. + while (DiskInfo) + { + //Through the logic and operation of bit operation, we can judge whether it is 1 or not. + Sleep(10); + if (DiskInfo & 1) + { + DiskCount++; + } + DiskInfo = DiskInfo >> 1;//The right-shift operation of bit operation ensures that the checked position moves one bit to the right once per cycle. * / + } + + if (dwNum < DiskCount) + { + return;//The actual number of disks is greater than dwNum + } + dwNum = DiskCount;//Save the number of disk partitions + + + //-------------------------------------------------------------------// + //Get the length of all drive string information through the GetLogicalDriveStrings() function + int DSLength = GetLogicalDriveStrings(0, NULL); + + WCHAR* DStr = new WCHAR[DSLength]; + memset(DStr, 0, DSLength); + + //The string information is copied into the heap area array by GetLogical Drive Strings, which stores the information of all drives. + GetLogicalDriveStrings(DSLength, DStr); + + int DType; + int si = 0; + BOOL fResult; + unsigned _int64 i64FreeBytesToCaller; + unsigned _int64 i64TotalBytes; + unsigned _int64 i64FreeBytes; + + //Read the driver information, because the DStr internal data format is A: NULLB: NULLC: NULL, so DSLength/4 can get specific large cycle range. + for (int i = 0; i < DSLength / 4; ++i) + { + Sleep(10); + CString strdriver = DStr + i * 4; + CString strTmp, strTotalBytes, strFreeBytes; + DType = GetDriveType(strdriver);//GetDriveType function, you can get the driver type, parameter is the root directory of the driver + switch (DType) + { + case DRIVE_FIXED: + { + strTmp.Format(_T("Local disk")); + } + break; + case DRIVE_CDROM: + { + strTmp.Format(_T("DVD Driver")); + } + break; + case DRIVE_REMOVABLE: + { + strTmp.Format(_T("Removable disk")); + } + break; + case DRIVE_REMOTE: + { + strTmp.Format(_T("Network disk")); + } + break; + case DRIVE_RAMDISK: + { + strTmp.Format(_T("fictitious RAM disk")); + } + break; + case DRIVE_UNKNOWN: + { + strTmp.Format(_T("fictitious RAM unknown device")); + } + break; + default: + strTmp.Format(_T("unknown device")); + break; + } + + //GetDiskFreeSpaceEx function, which can get the space state of the drive disk, returns a BOOL-type data + fResult = GetDiskFreeSpaceEx(strdriver, + (PULARGE_INTEGER)&i64FreeBytesToCaller, + (PULARGE_INTEGER)&i64TotalBytes, + (PULARGE_INTEGER)&i64FreeBytes); + + if (fResult) + { + strTotalBytes.Format(_T("Total disk capacity%fMB"), (float)i64TotalBytes / 1024 / 1024); + strFreeBytes.Format(_T("Disk Remaining Space%fMB"), (float)i64FreeBytesToCaller / 1024 / 1024); + } + else + { + strTotalBytes.Format(_T("")); + strFreeBytes.Format(_T("")); + } + chDriveInfo[i] = strTmp + _T("(") + strdriver + _T("):") + strTotalBytes + strFreeBytes; + si += 4; + } +} diff --git a/huagao/Device/PublicFunc.h b/huagao/Device/PublicFunc.h new file mode 100644 index 00000000..1168920f --- /dev/null +++ b/huagao/Device/PublicFunc.h @@ -0,0 +1,241 @@ +#ifndef PUBLICFUNC_H_ +#define PUBLICFUNC_H_ + +#include "stdafx.h" +#include +#include +#include +#include +#include + + + +#define BYTES_PERLINE_ALIGN4(width, bpp) (((((int)(width)*(bpp))+31)/32)*4) +#define BYTES_PERLINE(width, bpp) ((((int)(width)*(bpp))+7)/8) + +using namespace std; + +/************************************ +**ɨjsonʽ** +*************************************/ + +// +#include + +UsbScanEx::UsbScanEx(int index) +{ + m_h_dev = INVALID_HANDLE_VALUE; + timeout = 100; + m_h_index = index; + memset(ov, 0, sizeof(ov)); + CTRL_IN_OUT = 3; + for (int i = 0; i < (sizeof(ov) / sizeof(ov[0])); i++) + ov[i].hEvent = CreateEvent(NULL, FALSE, FALSE, NULL); +} + +UsbScanEx::~UsbScanEx() +{ + if (m_h_dev != INVALID_HANDLE_VALUE) + close(); + + for (int i = 0; i < (sizeof(ov) / sizeof(ov[0])); i++) + CloseHandle(ov[i].hEvent); +} + +bool UsbScanEx::open() +{ + BOOL b_ret = FALSE; + TCHAR szDevPath[MAX_PATH] = { 0 }; + DWORD cbRet = 0; + + USBSCAN_TIMEOUT ut; + ut.TimeoutEvent = 1; + ut.TimeoutRead = 1; + ut.TimeoutWrite = 1; + + _stprintf(szDevPath, TEXT("\\\\.\\Usbscan%d"), m_h_index); + m_h_dev = CreateFile(szDevPath, + GENERIC_READ | GENERIC_WRITE, + FILE_SHARE_READ | FILE_SHARE_WRITE, + NULL, + OPEN_EXISTING, + FILE_FLAG_OVERLAPPED, + NULL); + if (m_h_dev != INVALID_HANDLE_VALUE) { + m_b_is_connected = TRUE; + b_ret = DeviceIoControl(m_h_dev, (DWORD)IOCTL_GET_PIPE_CONFIGURATION, + NULL, 0, &m_usbscan_config, sizeof(USBSCAN_PIPE_CONFIGURATION), + &cbRet, NULL); + if (b_ret && m_usbscan_config.NumberOfPipes > 0) { + for (int by_i = 0x00; (ULONG)by_i < m_usbscan_config.NumberOfPipes; by_i++) { + TCHAR szPipePath[MAX_PATH] = { 0 }; + _stprintf(szPipePath, TEXT("\\\\.\\Usbscan%d\\%d"), m_h_index, by_i); + m_usb_pipes[by_i].pipe_info = m_usbscan_config.PipeInfo[by_i]; + m_usb_pipes[by_i].h_pipe = CreateFile(szPipePath, + GENERIC_READ | GENERIC_WRITE, + FILE_SHARE_READ | FILE_SHARE_WRITE, + NULL, + OPEN_EXISTING, + FILE_FLAG_OVERLAPPED, + NULL); + if (m_usbscan_config.PipeInfo[by_i].PipeType == USBSCAN_PIPE_INTERRUPT) { + INT_IN = by_i; + } + else { + if (m_usbscan_config.PipeInfo[by_i].EndpointAddress & 0x80) { + BULK_IN = by_i; + } + else { + BULK_OUT = by_i; + } + } + b_ret = DeviceIoControl(m_usb_pipes[by_i].h_pipe, IOCTL_SET_TIMEOUT, &ut, sizeof(ut), NULL, 0, &cbRet, NULL); + } + } + } + else { + CloseHandle(m_h_dev); + m_h_dev = INVALID_HANDLE_VALUE; + } + return m_h_dev; +} + +void UsbScanEx::set_usbhotplug_callback(usbhotplug_callback callback, void* userdata) +{ + hotplug_call = callback; + usrdata = userdata; +} + +bool UsbScanEx::close() +{ + BOOL b_ret = FALSE; + BYTE by_i = 0x00; + + if (m_h_dev != INVALID_HANDLE_VALUE) { + BOOL bState = FALSE; + DWORD cbRet = 0; + OVERLAPPED overlapped; + PIPE_TYPE pipeType = ALL_PIPE; + + memset(&overlapped, 0, sizeof(OVERLAPPED)); + overlapped.hEvent = + CreateEvent(NULL, // pointer to security attributes + FALSE, // automatic reset + FALSE, // initialize to nosignaled + NULL); // pointer to the event-object name + bState = + DeviceIoControl(m_h_dev, + (DWORD)IOCTL_CANCEL_IO, + (LPVOID)&pipeType, + sizeof(PIPE_TYPE), + NULL, + 0, + &cbRet, + &overlapped); + WaitForSingleObject(overlapped.hEvent, 1000); + CloseHandle(overlapped.hEvent); + + for (by_i = 0x00; by_i < m_usbscan_config.NumberOfPipes; by_i++) { + CancelIo(m_usb_pipes[by_i].h_pipe); + CloseHandle(m_usb_pipes[by_i].h_pipe); + m_usb_pipes[by_i].h_pipe = INVALID_HANDLE_VALUE; + } + + CancelIo(m_h_dev); + b_ret = CloseHandle(m_h_dev); + if (b_ret) { + m_h_dev = INVALID_HANDLE_VALUE; + b_ret = TRUE; + } + } + m_b_is_connected = FALSE; + return b_ret; +} + +void UsbScanEx::set_timeout(int timeout) +{ + this->timeout = timeout; +} + +int UsbScanEx::read_bulk(void* data, int len) +{ + BOOL b_ret = FALSE; + HANDLE h_pipe = m_usb_pipes[BULK_IN].h_pipe; + unsigned long pdw_ret = len; + LPOVERLAPPED lp_overlap = ov+BULK_IN; + lp_overlap->Internal = 0; + lp_overlap->InternalHigh = 0; + lp_overlap->Offset = 0; + lp_overlap->OffsetHigh = 0; + lp_overlap->Pointer = 0; + + if (m_h_dev != NULL) { + b_ret = ReadFile(h_pipe, data, len, &pdw_ret, lp_overlap); + + if (b_ret) { + return pdw_ret; + } + else { + int error_code = GetLastError(); + switch (error_code) + { + case ERROR_IO_PENDING: + GetOverlappedResult(h_pipe, lp_overlap, &pdw_ret, TRUE); + return pdw_ret; + + case ERROR_FILE_NOT_FOUND: + case ERROR_ACCESS_DENIED: + m_b_is_connected = false; + if (hotplug_call) { + hotplug_call(true, usrdata); + } + break; + default: + int a = 0; + break; + } + } + } + return 0; +} + +int UsbScanEx::write_bulk(void* data, int len) +{ + BOOL b_ret = FALSE; + HANDLE h_pipe = m_usb_pipes[BULK_OUT].h_pipe; + void* p_data = data; + unsigned long dw_size = len; + + LPOVERLAPPED lp_overlap = ov + BULK_OUT; + + if (m_h_dev == INVALID_HANDLE_VALUE) + return TRUE; + + b_ret = WriteFile(h_pipe, p_data, dw_size, &dw_size, lp_overlap); + if (b_ret) { + return dw_size; + } + else { + int errorcode = GetLastError(); + switch (errorcode) + { + case ERROR_IO_PENDING: + GetOverlappedResult(h_pipe, lp_overlap, &dw_size, TRUE); + return dw_size; + + case ERROR_FILE_NOT_FOUND: + case ERROR_ACCESS_DENIED: + m_b_is_connected = false; + if (hotplug_call) { + hotplug_call(true, usrdata); + } + break; + default: + int a = 0; + break; + } + } + return 0; +} + +int UsbScanEx::control_msg(int rtype, int req, int value, int index, int len, void* data) +{ + BOOL b_ret = FALSE; + _IO_BLOCK_EX irp; + DWORD dw_ret; + + if (m_h_dev == INVALID_HANDLE_VALUE) + return TRUE; + irp.uOffset = value; + irp.uLength = len; + irp.uIndex = index; + irp.pbyData = (LPBYTE)data; + irp.fTransferDirectionIn = (rtype >> 7); + irp.bRequest = req; + irp.bmRequestType = (rtype >> 5) & 0x03; + + LPOVERLAPPED lp_overlap = ov + CTRL_IN_OUT; + b_ret = DeviceIoControl(m_h_dev, IOCTL_SEND_USB_REQUEST, &irp, sizeof(irp), data, len, &dw_ret, lp_overlap); + + if (!b_ret) + b_ret = WaitForSingleObject(lp_overlap->hEvent, timeout) == WAIT_OBJECT_0; + + return b_ret; +} + +bool UsbScanEx::is_open() +{ + return m_h_dev != INVALID_HANDLE_VALUE; +} + +bool UsbScanEx::is_connected() +{ + return is_open();//m_b_is_connected; +} + +int UsbScanEx::read_int(void* data, int len) +{ + BOOL b_ret = FALSE; + DWORD dw_ret = 0L; + HANDLE h_pipe = m_usb_pipes[INT_IN].h_pipe; + LPOVERLAPPED lp_overlap = ov + INT_IN; + + if (m_h_dev == INVALID_HANDLE_VALUE) + return FALSE; + + b_ret = DeviceIoControl(h_pipe, (DWORD)IOCTL_WAIT_ON_DEVICE_EVENT, NULL, 0, + data, len, &dw_ret, lp_overlap); + + if (b_ret) { + return dw_ret; + } + else { + switch (GetLastError()) + { + case ERROR_IO_PENDING: + GetOverlappedResult(h_pipe, lp_overlap, &dw_ret, TRUE); + return dw_ret; + + case ERROR_FILE_NOT_FOUND: + m_b_is_connected = false; + if (hotplug_call) { + hotplug_call(true, usrdata); + } + break; + default: + break; + } + } + + return 0; +} + +UsbScan_List::~UsbScan_List() +{ +} + +std::list> UsbScan_List::find_all() +{ + auto devs = find_all_usb(); + std::list> usbs; + for (auto inter = devs.begin(); inter != devs.end(); inter++) { + usbs.push_back(std::shared_ptr(new UsbScanEx(inter->index))); + } + return usbs; +} + +std::list> UsbScan_List::find_vid_pid(int vid, int pid) +{ + auto devs = find_all_usb(); + std::list> usbs; + for (auto inter = devs.begin(); inter != devs.end(); inter++) { + if (inter->vid == vid && inter->pid == pid) + usbs.push_back(std::shared_ptr(new UsbScanEx(inter->index))); + } + return usbs; +} + +std::list UsbScan_List::find_all_usb() +{ + BOOL b_ret = FALSE; + DWORD cbRet = 0; + TCHAR szDevPath[MAX_PATH] = { 0 }; + DEVICE_DESCRIPTOR dev_desc; + HANDLE h_dev; + std::list usbs; + usb_scan_dev_info dev_info; + + for (int i = 0; i < 1024; i++) { + + _stprintf(szDevPath, TEXT("\\\\.\\Usbscan%d"), i); + h_dev = CreateFile(szDevPath, + GENERIC_READ | GENERIC_WRITE, + FILE_SHARE_READ | FILE_SHARE_WRITE, + NULL, + OPEN_EXISTING, + FILE_FLAG_OVERLAPPED, + NULL); + if (h_dev != INVALID_HANDLE_VALUE) { + b_ret = DeviceIoControl(h_dev, (DWORD)IOCTL_GET_DEVICE_DESCRIPTOR, + &dev_desc, sizeof(dev_desc), &dev_desc, sizeof(dev_desc), + &cbRet, NULL); + if (b_ret != 0) { + dev_info.index = i; + dev_info.vid = dev_desc.usVendorId; + dev_info.pid = dev_desc.usProductId; + usbs.push_back(dev_info); + } + CloseHandle(h_dev); + } + } + + return usbs; +} diff --git a/huagao/Device/UsbScanEx.h b/huagao/Device/UsbScanEx.h new file mode 100644 index 00000000..47020e02 --- /dev/null +++ b/huagao/Device/UsbScanEx.h @@ -0,0 +1,82 @@ +#pragma once +#ifdef WIN32 +#include +#include +#endif // WINDOWS + +#include +#include +#include "IUsb.h" + + +#pragma pack(1) +struct tag_usb_pipe +{ + HANDLE h_pipe; + USBSCAN_PIPE_INFORMATION pipe_info; + OVERLAPPED overlap; +}; +typedef struct tag_usb_pipe usb_pipe_t, * pusb_pipe_t; +#pragma pack() + +typedef struct tag_usb_scan_dev_info +{ + WORD vid; + WORD pid; + WORD index; +}usb_scan_dev_info, * pusb_scan_dev_info; + +typedef struct tag_usb_scan_dev +{ + USHORT _NumberOfDevs; + tag_usb_scan_dev_info dev_infos[1024]; +}usb_scan_dev, * pusb_scan_dev; + +class UsbScanEx : public IUsb +{ +public: + UsbScanEx(int index); + virtual ~UsbScanEx(); + // ͨ IUsb ̳ + virtual bool open() override; + virtual void set_usbhotplug_callback(usbhotplug_callback callback, void* userdata) override; + virtual bool close() override; + virtual void set_timeout(int timeout) override; + virtual int read_bulk(void *data, int len) override; + virtual int write_bulk(void *data, int len) override; + virtual int control_msg(int rtype, int req, int value, int index, int len, void* data) override; + virtual bool is_open() override; + virtual bool is_connected() override; + virtual int read_int(void* data, int len) override; + +private: + + int BULK_OUT; + int BULK_IN; + int INT_IN; + int CTRL_IN_OUT; + USBSCAN_PIPE_CONFIGURATION m_usbscan_config; + usb_pipe_t m_usb_pipes[MAX_NUM_PIPES]; + HANDLE m_h_dev; + bool m_b_is_connected; + int m_h_index; + int timeout; + OVERLAPPED ov[4]; + usbhotplug_callback hotplug_call; + void* usrdata; +}; + + +class UsbScan_List +{ +public: + ~UsbScan_List(); + + static std::list> find_all(); + static std::list> find_vid_pid(int vid, int pid); + +private: + static std::list find_all_usb(); + UsbScan_List(); + UsbScan_List(uint16_t vendor_id, uint16_t product_id); +}; diff --git a/huagao/Device/cJSON.cpp b/huagao/Device/cJSON.cpp new file mode 100644 index 00000000..866e37ca --- /dev/null +++ b/huagao/Device/cJSON.cpp @@ -0,0 +1,1088 @@ +/* + Copyright (c) 2009 Dave Gamble + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to deal + in the Software without restriction, including without limitation the rights + to use, copy, modify, merge, publish, distribute, sublicense, and/or sell + copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + The above copyright notice and this permission notice shall be included in + all copies or substantial portions of the Software. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN + THE SOFTWARE. + */ + +/* cJSON */ +/* JSON parser in C. */ +#include "stdafx.h" +#include +#include +#include +#include +#include +#include +#include +#include "cJSON.h" + + +static const char *ep; + +const char *cJSON_GetErrorPtr() +{ + return ep; +} + +static int cJSON_strcasecmp(const char *s1, const char *s2) +{ + if (!s1) + return (s1 == s2) ? 0 : 1; + if (!s2) + return 1; + for (; tolower(*s1) == tolower(*s2); ++s1, ++s2) + if (*s1 == 0) + return 0; + return tolower(*(const unsigned char *)s1) + - tolower(*(const unsigned char *)s2); +} + +static void *(*cJSON_malloc)(size_t sz) = malloc; +static void (*cJSON_free)(void *ptr) = free; + +static char* cJSON_strdup(const char* str) +{ + size_t len; + char* copy; + + len = strlen(str) + 1; + if (!(copy = (char*) cJSON_malloc(len))) + return 0; + memcpy(copy, str, len); + return copy; +} + +void cJSON_InitHooks(cJSON_Hooks* hooks) +{ + if (!hooks) + { /* Reset hooks */ + cJSON_malloc = malloc; + cJSON_free = free; + return; + } + + cJSON_malloc = (hooks->malloc_fn) ? hooks->malloc_fn : malloc; + cJSON_free = (hooks->free_fn) ? hooks->free_fn : free; +} + +/* Internal constructor. */ +static cJSON *cJSON_New_Item() +{ + cJSON* node = (cJSON*) cJSON_malloc(sizeof(cJSON)); + if (node) + memset(node, 0, sizeof(cJSON)); + return node; +} + +/* Delete a cJSON structure. */ +void cJSON_Delete(cJSON *c) +{ + cJSON *next; + while (c) + { + next = c->next; + if (!(c->type & cJSON_IsReference) && c->child) + cJSON_Delete(c->child); + if (!(c->type & cJSON_IsReference) && c->valuestring) + cJSON_free(c->valuestring); + if (c->string) + cJSON_free(c->string); + cJSON_free(c); + c = next; + } +} + +/* Parse the input text to generate a number, and populate the result into item. */ +static const char *parse_number(cJSON *item, const char *num) +{ + long double n = 0, scale = 0; + int subscale = 0, signsubscale = 1; + item->sign = 1; + + /* Could use sscanf for this? */ + if (*num == '-') + item->sign = -1, num++; /* Has sign? */ + if (*num == '0') + num++; /* is zero */ + if (*num >= '1' && *num <= '9') + do + n = (n * 10.0) + (*num++ - '0'); + while (*num >= '0' && *num <= '9'); /* Number? */ + if (*num == '.' && num[1] >= '0' && num[1] <= '9') + { + num++; + do + n = (n * 10.0) + (*num++ - '0'), scale--; + while (*num >= '0' && *num <= '9'); + } /* Fractional part? */ + if (*num == 'e' || *num == 'E') /* Exponent? */ + { + num++; + if (*num == '+') + num++; + else if (*num == '-') + signsubscale = -1, num++; /* With sign? */ + while (*num >= '0' && *num <= '9') + subscale = (subscale * 10) + (*num++ - '0'); /* Number? */ + } + + if (scale == 0 && subscale == 0) + { + item->valuedouble = (double)(item->sign * (uint64)n); + item->valueint = (uint64)(item->sign * (uint64)n); + item->type = cJSON_Int; + } + else + { + n = item->sign * n * pow(10.0, (scale + subscale * signsubscale)); /* number = +/- number.fraction * 10^+/- exponent */ + item->valuedouble = (double)n; + item->valueint = (uint64)n; + item->type = cJSON_Double; + } + return num; +} + +/* Render the number nicely from the given item into a string. */ +static char *print_double(cJSON *item) +{ + char *str; + double d = item->valuedouble; + str = (char*) cJSON_malloc(64); /* This is a nice tradeoff. */ + if (str) + { + if (fabs(floor(d) - d) <= DBL_EPSILON) + sprintf(str, "%.0f", d); + else if (fabs(d) < 1.0e-6 || fabs(d) > 1.0e9) + sprintf(str, "%lf", d); + else + sprintf(str, "%f", d); + } + return str; +} + +static char *print_int(cJSON *item) +{ + char *str; + str = (char*) cJSON_malloc(22); /* 2^64+1 can be represented in 21 chars. */ + if (str) + { + if (item->sign == -1) + { + if (item->valueint <= (int64)INT_MAX && item->valueint >= (int64)INT_MIN) + { + sprintf(str, "%d", (int32)item->valueint); + } + else + { + sprintf(str, "%lld", (int64)item->valueint); + } + } + else + { + if (item->valueint <= (uint64)UINT_MAX) + { + sprintf(str, "%u", (uint32)item->valueint); + } + else + { + sprintf(str, "%llu", item->valueint); + } + } + } + return str; +} + +/* Parse the input text into an unescaped cstring, and populate item. */ +static const unsigned char firstByteMark[7] = { 0x00, 0x00, 0xC0, 0xE0, 0xF0, + 0xF8, 0xFC }; +static const char *parse_string(cJSON *item, const char *str) +{ + const char *ptr = str + 1; + char *ptr2; + char *out; + int len = 0; + unsigned uc, uc2; + if (*str != '\"') + { + ep = str; + return 0; + } /* not a string! */ + + while (*ptr != '\"' && *ptr && ++len) + if (*ptr++ == '\\') + ptr++; /* Skip escaped quotes. */ + + out = (char*) cJSON_malloc(len + 1); /* This is how long we need for the string, roughly. */ + if (!out) + return 0; + + ptr = str + 1; + ptr2 = out; + while (*ptr != '\"' && *ptr) + { + if (*ptr != '\\') + *ptr2++ = *ptr++; + else + { + ptr++; + switch (*ptr) + { + case 'b': + *ptr2++ = '\b'; + break; + case 'f': + *ptr2++ = '\f'; + break; + case 'n': + *ptr2++ = '\n'; + break; + case 'r': + *ptr2++ = '\r'; + break; + case 't': + *ptr2++ = '\t'; + break; + case 'u': /* transcode utf16 to utf8. */ + sscanf(ptr + 1, "%4x", &uc); + ptr += 4; /* get the unicode char. */ + + if ((uc >= 0xDC00 && uc <= 0xDFFF) || uc == 0) + break; // check for invalid. + + if (uc >= 0xD800 && uc <= 0xDBFF) // UTF16 surrogate pairs. + { + if (ptr[1] != '\\' || ptr[2] != 'u') + break; // missing second-half of surrogate. + sscanf(ptr + 3, "%4x", &uc2); + ptr += 6; + if (uc2 < 0xDC00 || uc2 > 0xDFFF) + break; // invalid second-half of surrogate. + uc = 0x10000 | ((uc & 0x3FF) << 10) | (uc2 & 0x3FF); + } + + len = 4; + if (uc < 0x80) + len = 1; + else if (uc < 0x800) + len = 2; + else if (uc < 0x10000) + len = 3; + ptr2 += len; + + switch (len) + { + case 4: + *--ptr2 = ((uc | 0x80) & 0xBF); + uc >>= 6; + case 3: + *--ptr2 = ((uc | 0x80) & 0xBF); + uc >>= 6; + case 2: + *--ptr2 = ((uc | 0x80) & 0xBF); + uc >>= 6; + case 1: + *--ptr2 = (uc | firstByteMark[len]); + } + ptr2 += len; + break; + default: + *ptr2++ = *ptr; + break; + } + ptr++; + } + } + *ptr2 = 0; + if (*ptr == '\"') + ptr++; + item->valuestring = out; + item->type = cJSON_String; + return ptr; +} + +/* Render the cstring provided to an escaped version that can be printed. */ +static char *print_string_ptr(const char *str) +{ + const char *ptr; + char *ptr2, *out; + int len = 0; + unsigned char token; + + if (!str) + return cJSON_strdup(""); + ptr = str; + while ((token = *ptr) && ++len) + { + if (strchr("\"\\\b\f\n\r\t", token)) + len++; + else if (token < 32) + len += 5; + ptr++; + } + + out = (char*) cJSON_malloc(len + 3); + if (!out) + return 0; + + ptr2 = out; + ptr = str; + *ptr2++ = '\"'; + while (*ptr) + { + if ((unsigned char) *ptr > 31 && *ptr != '\"' && *ptr != '\\') + *ptr2++ = *ptr++; + else + { + *ptr2++ = '\\'; + switch (token = *ptr++) + { + case '\\': + *ptr2++ = '\\'; + break; + case '\"': + *ptr2++ = '\"'; + break; + case '\b': + *ptr2++ = 'b'; + break; + case '\f': + *ptr2++ = 'f'; + break; + case '\n': + *ptr2++ = 'n'; + break; + case '\r': + *ptr2++ = 'r'; + break; + case '\t': + *ptr2++ = 't'; + break; + default: + sprintf(ptr2, "u%04x", token); + ptr2 += 5; + break; /* escape and print */ + } + } + } + *ptr2++ = '\"'; + *ptr2++ = 0; + return out; +} +/* Invote print_string_ptr (which is useful) on an item. */ +static char *print_string(cJSON *item) +{ + return print_string_ptr(item->valuestring); +} + +/* Predeclare these prototypes. */ +static const char *parse_value(cJSON *item, const char *value); +static char *print_value(cJSON *item, int depth, int fmt); +static const char *parse_array(cJSON *item, const char *value); +static char *print_array(cJSON *item, int depth, int fmt); +static const char *parse_object(cJSON *item, const char *value); +static char *print_object(cJSON *item, int depth, int fmt); + +/* Utility to jump whitespace and cr/lf */ +static const char *skip(const char *in) +{ + while (in && *in && (unsigned char) *in <= 32) + in++; + return in; +} + +/* Parse an object - create a new root, and populate. */ +cJSON *cJSON_Parse(const char *value) +{ + cJSON *c = cJSON_New_Item(); + ep = 0; + if (!c) + return 0; /* memory fail */ + + if (!parse_value(c, skip(value))) + { + cJSON_Delete(c); + return 0; + } + return c; +} + +/* Render a cJSON item/entity/structure to text. */ +char *cJSON_Print(cJSON *item) +{ + return print_value(item, 0, 1); +} +char *cJSON_PrintUnformatted(cJSON *item) +{ + return print_value(item, 0, 0); +} + +/* Parser core - when encountering text, process appropriately. */ +static const char *parse_value(cJSON *item, const char *value) +{ + if (!value) + return 0; /* Fail on null. */ + if (!strncmp(value, "null", 4)) + { + item->type = cJSON_NULL; + return value + 4; + } + if (!strncmp(value, "false", 5)) + { + item->type = cJSON_False; + return value + 5; + } + if (!strncmp(value, "true", 4)) + { + item->type = cJSON_True; + item->valueint = 1; + return value + 4; + } + if (*value == '\"') + { + return parse_string(item, value); + } + if (*value == '-' || (*value >= '0' && *value <= '9')) + { + return parse_number(item, value); + } + if (*value == '[') + { + return parse_array(item, value); + } + if (*value == '{') + { + return parse_object(item, value); + } + + ep = value; + return 0; /* failure. */ +} + +/* Render a value to text. */ +static char *print_value(cJSON *item, int depth, int fmt) +{ + char *out = 0; + if (!item) + return 0; + switch ((item->type) & 255) + { + case cJSON_NULL: + out = cJSON_strdup("null"); + break; + case cJSON_False: + out = cJSON_strdup("false"); + break; + case cJSON_True: + out = cJSON_strdup("true"); + break; + case cJSON_Int: + out = print_int(item); + break; + case cJSON_Double: + out = print_double(item); + break; + case cJSON_String: + out = print_string(item); + break; + case cJSON_Array: + out = print_array(item, depth, fmt); + break; + case cJSON_Object: + out = print_object(item, depth, fmt); + break; + } + return out; +} + +/* Build an array from input text. */ +static const char *parse_array(cJSON *item, const char *value) +{ + cJSON *child; + if (*value != '[') + { + ep = value; + return 0; + } /* not an array! */ + + item->type = cJSON_Array; + value = skip(value + 1); + if (*value == ']') + return value + 1; /* empty array. */ + + item->child = child = cJSON_New_Item(); + if (!item->child) + return 0; /* memory fail */ + value = skip(parse_value(child, skip(value))); /* skip any spacing, get the value. */ + if (!value) + return 0; + + while (*value == ',') + { + cJSON *new_item; + if (!(new_item = cJSON_New_Item())) + return 0; /* memory fail */ + child->next = new_item; + new_item->prev = child; + child = new_item; + value = skip(parse_value(child, skip(value + 1))); + if (!value) + return 0; /* memory fail */ + } + + if (*value == ']') + return value + 1; /* end of array */ + ep = value; + return 0; /* malformed. */ +} + +/* Render an array to text */ +static char *print_array(cJSON *item, int depth, int fmt) +{ + char **entries; + char *out = 0, *ptr, *ret; + int len = 5; + cJSON *child = item->child; + int numentries = 0, i = 0, fail = 0; + + /* How many entries in the array? */ + while (child) + numentries++, child = child->next; + /* Allocate an array to hold the values for each */ + entries = (char**) cJSON_malloc(numentries * sizeof(char*)); + if (!entries) + return 0; + memset(entries, 0, numentries * sizeof(char*)); + /* Retrieve all the results: */ + child = item->child; + while (child && !fail) + { + ret = print_value(child, depth + 1, fmt); + entries[i++] = ret; + if (ret) + len += strlen(ret) + 2 + (fmt ? 1 : 0); + else + fail = 1; + child = child->next; + } + + /* If we didn't fail, try to malloc the output string */ + if (!fail) + out = (char*) cJSON_malloc(len); + /* If that fails, we fail. */ + if (!out) + fail = 1; + + /* Handle failure. */ + if (fail) + { + for (i = 0; i < numentries; i++) + if (entries[i]) + cJSON_free(entries[i]); + cJSON_free(entries); + return 0; + } + + /* Compose the output array. */ + *out = '['; + ptr = out + 1; + *ptr = 0; + for (i = 0; i < numentries; i++) + { + strcpy(ptr, entries[i]); + ptr += strlen(entries[i]); + if (i != numentries - 1) + { + *ptr++ = ','; + if (fmt) + *ptr++ = ' '; + *ptr = 0; + } + cJSON_free(entries[i]); + } + cJSON_free(entries); + *ptr++ = ']'; + *ptr++ = 0; + return out; +} + +/* Build an object from the text. */ +static const char *parse_object(cJSON *item, const char *value) +{ + cJSON *child; + if (*value != '{') + { + ep = value; + return 0; + } /* not an object! */ + + item->type = cJSON_Object; + value = skip(value + 1); + if (*value == '}') + return value + 1; /* empty array. */ + + item->child = child = cJSON_New_Item(); + if (!item->child) + return 0; + value = skip(parse_string(child, skip(value))); + if (!value) + return 0; + child->string = child->valuestring; + child->valuestring = 0; + if (*value != ':') + { + ep = value; + return 0; + } /* fail! */ + value = skip(parse_value(child, skip(value + 1))); /* skip any spacing, get the value. */ + if (!value) + return 0; + + while (*value == ',') + { + cJSON *new_item; + if (!(new_item = cJSON_New_Item())) + return 0; /* memory fail */ + child->next = new_item; + new_item->prev = child; + child = new_item; + value = skip(parse_string(child, skip(value + 1))); + if (!value) + return 0; + child->string = child->valuestring; + child->valuestring = 0; + if (*value != ':') + { + ep = value; + return 0; + } /* fail! */ + value = skip(parse_value(child, skip(value + 1))); /* skip any spacing, get the value. */ + if (!value) + return 0; + } + + if (*value == '}') + return value + 1; /* end of array */ + ep = value; + return 0; /* malformed. */ +} + +/* Render an object to text. */ +static char *print_object(cJSON *item, int depth, int fmt) +{ + char **entries = 0, **names = 0; + char *out = 0, *ptr, *ret, *str; + int len = 7, i = 0, j; + cJSON *child = item->child; + int numentries = 0, fail = 0; + /* Count the number of entries. */ + while (child) + numentries++, child = child->next; + /* Allocate space for the names and the objects */ + entries = (char**) cJSON_malloc(numentries * sizeof(char*)); + if (!entries) + return 0; + names = (char**) cJSON_malloc(numentries * sizeof(char*)); + if (!names) + { + cJSON_free(entries); + return 0; + } + memset(entries, 0, sizeof(char*) * numentries); + memset(names, 0, sizeof(char*) * numentries); + + /* Collect all the results into our arrays: */ + child = item->child; + depth++; + if (fmt) + len += depth; + while (child) + { + names[i] = str = print_string_ptr(child->string); + entries[i++] = ret = print_value(child, depth, fmt); + if (str && ret) + len += strlen(ret) + strlen(str) + 2 + (fmt ? 2 + depth : 0); + else + fail = 1; + child = child->next; + } + + /* Try to allocate the output string */ + if (!fail) + out = (char*) cJSON_malloc(len); + if (!out) + fail = 1; + + /* Handle failure */ + if (fail) + { + for (i = 0; i < numentries; i++) + { + if (names[i]) + cJSON_free(names[i]); + if (entries[i]) + cJSON_free(entries[i]); + } + cJSON_free(names); + cJSON_free(entries); + return 0; + } + + /* Compose the output: */ + *out = '{'; + ptr = out + 1; + if (fmt) + *ptr++ = '\n'; + *ptr = 0; + for (i = 0; i < numentries; i++) + { + if (fmt) + for (j = 0; j < depth; j++) + *ptr++ = '\t'; + strcpy(ptr, names[i]); + ptr += strlen(names[i]); + *ptr++ = ':'; + if (fmt) + *ptr++ = '\t'; + strcpy(ptr, entries[i]); + ptr += strlen(entries[i]); + if (i != numentries - 1) + *ptr++ = ','; + if (fmt) + *ptr++ = '\n'; + *ptr = 0; + cJSON_free(names[i]); + cJSON_free(entries[i]); + } + + cJSON_free(names); + cJSON_free(entries); + if (fmt) + for (i = 0; i < depth - 1; i++) + *ptr++ = '\t'; + *ptr++ = '}'; + *ptr++ = 0; + return out; +} + +/* Get Array size/item / object item. */ +int cJSON_GetArraySize(cJSON *array) +{ + cJSON *c = array->child; + int i = 0; + while (c) + i++, c = c->next; + return i; +} +cJSON *cJSON_GetArrayItem(cJSON *array, int item) +{ + cJSON *c = array->child; + while (c && item > 0) + item--, c = c->next; + return c; +} +cJSON *cJSON_GetObjectItem(cJSON *object, const char *string) +{ + cJSON *c = object->child; + while (c && cJSON_strcasecmp(c->string, string)) + c = c->next; + return c; +} + +/* Utility for array list handling. */ +static void suffix_object(cJSON *prev, cJSON *item) +{ + prev->next = item; + item->prev = prev; +} +/* Utility for handling references. */ +static cJSON *create_reference(cJSON *item) +{ + cJSON *ref = cJSON_New_Item(); + if (!ref) + return 0; + memcpy(ref, item, sizeof(cJSON)); + ref->string = 0; + ref->type |= cJSON_IsReference; + ref->next = ref->prev = 0; + return ref; +} + +/* Add item to array/object. */ +void cJSON_AddItemToArray(cJSON *array, cJSON *item) +{ + cJSON *c = array->child; + if (!item) + return; + if (!c) + { + array->child = item; + } + else + { + while (c && c->next) + c = c->next; + suffix_object(c, item); + } +} + +void cJSON_AddItemToArrayHead(cJSON *array, cJSON *item) +{ + cJSON *c = array->child; + if (!item) + return; + if (!c) + { + array->child = item; + } + else + { + item->prev = c->prev; + item->next = c; + c->prev = item; + array->child = item; + } +} + +void cJSON_AddItemToObject(cJSON *object, const char *string, cJSON *item) +{ + if (!item) + return; + if (item->string) + cJSON_free(item->string); + item->string = cJSON_strdup(string); + cJSON_AddItemToArray(object, item); +} +void cJSON_AddItemReferenceToArray(cJSON *array, cJSON *item) +{ + cJSON_AddItemToArray(array, create_reference(item)); +} +void cJSON_AddItemReferenceToObject(cJSON *object, const char *string, + cJSON *item) +{ + cJSON_AddItemToObject(object, string, create_reference(item)); +} + +cJSON *cJSON_DetachItemFromArray(cJSON *array, int which) +{ + cJSON *c = array->child; + while (c && which > 0) + c = c->next, which--; + if (!c) + return 0; + if (c->prev) + c->prev->next = c->next; + if (c->next) + c->next->prev = c->prev; + if (c == array->child) + array->child = c->next; + c->prev = c->next = 0; + return c; +} +void cJSON_DeleteItemFromArray(cJSON *array, int which) +{ + cJSON_Delete(cJSON_DetachItemFromArray(array, which)); +} +cJSON *cJSON_DetachItemFromObject(cJSON *object, const char *string) +{ + int i = 0; + cJSON *c = object->child; + while (c && cJSON_strcasecmp(c->string, string)) + i++, c = c->next; + if (c) + return cJSON_DetachItemFromArray(object, i); + return 0; +} +void cJSON_DeleteItemFromObject(cJSON *object, const char *string) +{ + cJSON_Delete(cJSON_DetachItemFromObject(object, string)); +} + +/* Replace array/object items with new ones. */ +void cJSON_ReplaceItemInArray(cJSON *array, int which, cJSON *newitem) +{ + cJSON *c = array->child; + while (c && which > 0) + c = c->next, which--; + if (!c) + return; + newitem->next = c->next; + newitem->prev = c->prev; + if (newitem->next) + newitem->next->prev = newitem; + if (c == array->child) + array->child = newitem; + else + newitem->prev->next = newitem; + c->next = c->prev = 0; + cJSON_Delete(c); +} +void cJSON_ReplaceItemInObject(cJSON *object, const char *string, + cJSON *newitem) +{ + int i = 0; + cJSON *c = object->child; + while (c && cJSON_strcasecmp(c->string, string)) + i++, c = c->next; + if (c) + { + newitem->string = cJSON_strdup(string); + cJSON_ReplaceItemInArray(object, i, newitem); + } +} + +/* Create basic types: */ +cJSON *cJSON_CreateNull() +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = cJSON_NULL; + return item; +} +cJSON *cJSON_CreateTrue() +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = cJSON_True; + return item; +} +cJSON *cJSON_CreateFalse() +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = cJSON_False; + return item; +} +cJSON *cJSON_CreateBool(int b) +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = b ? cJSON_True : cJSON_False; + return item; +} +cJSON *cJSON_CreateDouble(double num, int sign) +{ + cJSON *item = cJSON_New_Item(); + if (item) + { + item->type = cJSON_Double; + item->valuedouble = num; + item->valueint = (uint64)num; + item->sign = sign; + } + return item; +} +cJSON *cJSON_CreateInt(uint64 num, int sign) +{ + cJSON *item = cJSON_New_Item(); + if (item) + { + item->type = cJSON_Int; + item->valuedouble = (double)num; + item->valueint = (uint64)num; + item->sign = sign; + } + return item; +} +cJSON *cJSON_CreateString(const char *string) +{ + cJSON *item = cJSON_New_Item(); + if (item) + { + item->type = cJSON_String; + item->valuestring = cJSON_strdup(string); + } + return item; +} +cJSON *cJSON_CreateArray() +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = cJSON_Array; + return item; +} +cJSON *cJSON_CreateObject() +{ + cJSON *item = cJSON_New_Item(); + if (item) + item->type = cJSON_Object; + return item; +} + +/* Create Arrays: */ +cJSON *cJSON_CreateIntArray(int *numbers, int sign, int count) +{ + int i; + cJSON *n = 0, *p = 0, *a = cJSON_CreateArray(); + for (i = 0; a && i < count; i++) + { + n = cJSON_CreateDouble((long double)((unsigned int)numbers[i]), sign); + if (!i) + a->child = n; + else + suffix_object(p, n); + p = n; + } + return a; +} +cJSON *cJSON_CreateFloatArray(float *numbers, int count) +{ + int i; + cJSON *n = 0, *p = 0, *a = cJSON_CreateArray(); + for (i = 0; a && i < count; i++) + { + n = cJSON_CreateDouble((long double)numbers[i], -1); + if (!i) + a->child = n; + else + suffix_object(p, n); + p = n; + } + return a; +} +cJSON *cJSON_CreateDoubleArray(double *numbers, int count) +{ + int i; + cJSON *n = 0, *p = 0, *a = cJSON_CreateArray(); + for (i = 0; a && i < count; i++) + { + n = cJSON_CreateDouble((long double)numbers[i], -1); + if (!i) + a->child = n; + else + suffix_object(p, n); + p = n; + } + return a; +} +cJSON *cJSON_CreateStringArray(const char **strings, int count) +{ + int i; + cJSON *n = 0, *p = 0, *a = cJSON_CreateArray(); + for (i = 0; a && i < count; i++) + { + n = cJSON_CreateString(strings[i]); + if (!i) + a->child = n; + else + suffix_object(p, n); + p = n; + } + return a; +} + diff --git a/huagao/Device/cJSON.h b/huagao/Device/cJSON.h new file mode 100644 index 00000000..4084728b --- /dev/null +++ b/huagao/Device/cJSON.h @@ -0,0 +1,142 @@ +/* + Copyright (c) 2009 Dave Gamble + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to deal + in the Software without restriction, including without limitation the rights + to use, copy, modify, merge, publish, distribute, sublicense, and/or sell + copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + The above copyright notice and this permission notice shall be included in + all copies or substantial portions of the Software. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN + THE SOFTWARE. + */ + +#ifndef cJSON__h +#define cJSON__h + + +typedef int int32; +typedef unsigned int uint32; +typedef long long int64; +typedef unsigned long long uint64; + +#ifdef __cplusplus +extern "C" +{ +#endif + +/* cJSON Types: */ +#define cJSON_False 0 +#define cJSON_True 1 +#define cJSON_NULL 2 +#define cJSON_Int 3 +#define cJSON_Double 4 +#define cJSON_String 5 +#define cJSON_Array 6 +#define cJSON_Object 7 + +#define cJSON_IsReference 256 + +/* The cJSON structure: */ +typedef struct cJSON +{ + struct cJSON *next, *prev; /* next/prev allow you to walk array/object chains. Alternatively, use GetArraySize/GetArrayItem/GetObjectItem */ + struct cJSON *child; /* An array or object item will have a child pointer pointing to a chain of the items in the array/object. */ + + int type; /* The type of the item, as above. */ + + char *valuestring; /* The item's string, if type==cJSON_String */ + uint64 valueint; /* The item's number, if type==cJSON_Number */ + double valuedouble; /* The item's number, if type==cJSON_Number */ + int sign; /* sign of valueint, 1(unsigned), -1(signed) */ + + char *string; /* The item's name string, if this item is the child of, or is in the list of subitems of an object. */ +} cJSON; + +typedef struct cJSON_Hooks +{ + void *(*malloc_fn)(size_t sz); + void (*free_fn)(void *ptr); +} cJSON_Hooks; + +/* Supply malloc, realloc and free functions to cJSON */ +extern void cJSON_InitHooks(cJSON_Hooks* hooks); + +/* Supply a block of JSON, and this returns a cJSON object you can interrogate. Call cJSON_Delete when finished. */ +extern cJSON *cJSON_Parse(const char *value); +/* Render a cJSON entity to text for transfer/storage. Free the char* when finished. */ +extern char *cJSON_Print(cJSON *item); +/* Render a cJSON entity to text for transfer/storage without any formatting. Free the char* when finished. */ +extern char *cJSON_PrintUnformatted(cJSON *item); +/* Delete a cJSON entity and all subentities. */ +extern void cJSON_Delete(cJSON *c); + +/* Returns the number of items in an array (or object). */ +extern int cJSON_GetArraySize(cJSON *array); +/* Retrieve item number "item" from array "array". Returns NULL if unsuccessful. */ +extern cJSON *cJSON_GetArrayItem(cJSON *array, int item); +/* Get item "string" from object. Case insensitive. */ +extern cJSON *cJSON_GetObjectItem(cJSON *object, const char *string); + +/* For analysing failed parses. This returns a pointer to the parse error. You'll probably need to look a few chars back to make sense of it. Defined when cJSON_Parse() returns 0. 0 when cJSON_Parse() succeeds. */ +extern const char *cJSON_GetErrorPtr(); + +/* These calls create a cJSON item of the appropriate type. */ +extern cJSON *cJSON_CreateNull(); +extern cJSON *cJSON_CreateTrue(); +extern cJSON *cJSON_CreateFalse(); +extern cJSON *cJSON_CreateBool(int b); +extern cJSON *cJSON_CreateDouble(double num, int sign); +extern cJSON *cJSON_CreateInt(uint64 num, int sign); +extern cJSON *cJSON_CreateString(const char *string); +extern cJSON *cJSON_CreateArray(); +extern cJSON *cJSON_CreateObject(); + +/* These utilities create an Array of count items. */ +extern cJSON *cJSON_CreateIntArray(int *numbers, int sign, int count); +extern cJSON *cJSON_CreateFloatArray(float *numbers, int count); +extern cJSON *cJSON_CreateDoubleArray(double *numbers, int count); +extern cJSON *cJSON_CreateStringArray(const char **strings, int count); + +/* Append item to the specified array/object. */ +extern void cJSON_AddItemToArray(cJSON *array, cJSON *item); +extern void cJSON_AddItemToArrayHead(cJSON *array, cJSON *item); /* add by Bwar on 2015-01-28 */ +extern void cJSON_AddItemToObject(cJSON *object, const char *string, + cJSON *item); +/* Append reference to item to the specified array/object. Use this when you want to add an existing cJSON to a new cJSON, but don't want to corrupt your existing cJSON. */ +extern void cJSON_AddItemReferenceToArray(cJSON *array, cJSON *item); +extern void cJSON_AddItemReferenceToObject(cJSON *object, const char *string, + cJSON *item); + +/* Remove/Detatch items from Arrays/Objects. */ +extern cJSON *cJSON_DetachItemFromArray(cJSON *array, int which); +extern void cJSON_DeleteItemFromArray(cJSON *array, int which); +extern cJSON *cJSON_DetachItemFromObject(cJSON *object, const char *string); +extern void cJSON_DeleteItemFromObject(cJSON *object, const char *string); + +/* Update array items. */ +extern void cJSON_ReplaceItemInArray(cJSON *array, int which, cJSON *newitem); +extern void cJSON_ReplaceItemInObject(cJSON *object, const char *string, + cJSON *newitem); + +#define cJSON_AddNullToObject(object,name) cJSON_AddItemToObject(object, name, cJSON_CreateNull()) +#define cJSON_AddTrueToObject(object,name) cJSON_AddItemToObject(object, name, cJSON_CreateTrue()) +#define cJSON_AddFalseToObject(object,name) cJSON_AddItemToObject(object, name, cJSON_CreateFalse()) +#define cJSON_AddNumberToObject(object,name,n) cJSON_AddItemToObject(object, name, cJSON_CreateNumber(n)) +#define cJSON_AddStringToObject(object,name,s) cJSON_AddItemToObject(object, name, cJSON_CreateString(s)) + + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/huagao/Device/config_new.cpp b/huagao/Device/config_new.cpp new file mode 100644 index 00000000..2e4d2e00 --- /dev/null +++ b/huagao/Device/config_new.cpp @@ -0,0 +1,38 @@ +#include "stdafx.h" +#include "config_new.h" + +config_new::config_new(GScanCap param) +{ + ms.value = 0; + ms.double_paper = param.hardwarecaps.en_doublefeed; + ms.color_model = SupPixelTypes[param.hardwarecaps.capturepixtype]; + ms.dpi = SupResolutions[param.resolution_native]; + ms.papar_type = 0;//SupPaperTyps[param.papertype]; + ms.paper = ms.papar_type == 3; + ms.skew_enable = param.hardwarecaps.en_skrewdetect; + ms.skew_parameter = param.hardwarecaps.skrewdetectlevel; + ms.staple_enable = param.hardwarecaps.en_stapledetect; +} + +config_new::~config_new(void) +{ +} + +unsigned int config_new::GetData() +{ + return ms.value; +} + +void config_new::set_unused_default_value(void) +{ + ms.error_clean = 0; + ms.iic_config = 0; + ms.iic_config_addr = 0; + ms.pick_paper = 0; + ms.scan_enable = 0; + ms.status_init = 0; + ms.v_setting = 0; + ms.speed_set_enable = 0; + ms.key_staple_enable = 0; + ms.scan_busy_motor_stop = 1; +} diff --git a/huagao/Device/config_new.h b/huagao/Device/config_new.h new file mode 100644 index 00000000..00f5481e --- /dev/null +++ b/huagao/Device/config_new.h @@ -0,0 +1,22 @@ +#pragma once +#include "IConfig.h" +#include "PublicFunc.h" +#include "device_common.h" +#include + +class config_new : + public IConfig +{ +public : + config_new(GScanCap param); + virtual ~config_new(void); + virtual unsigned int GetData() override; +private: + void set_unused_default_value(void); +private: + std::map paperTypes; + std::map pixType; + std::map resolutions; + MotorSetting ms; +}; + diff --git a/huagao/Device/device_common.h b/huagao/Device/device_common.h new file mode 100644 index 00000000..d4553b69 --- /dev/null +++ b/huagao/Device/device_common.h @@ -0,0 +1,168 @@ +#pragma once +#define FLASH_ADDR_START (0x300000) //! +#include +#include +#include + +class FileTools +{ +public: + + + static std::vector getFiles(std::string path) + { + std::vector files; + getFiles(path, files); + return files; + } + + static void write_log(std::string filename, std::string log) + { + std::string savepath; + std::string str = "D:"; + savepath = str+"\\"+filename; + std::ofstream ofs(savepath, std::ios::app); + + time_t timp; + struct tm* p; + time(&timp); + p=localtime(&timp); + ofs << p->tm_year << "/" << p->tm_mon << "/" << p->tm_mday << " " << p->tm_hour << ":" << p->tm_min << ":" << p->tm_sec << " "<& files) + { + //ļ + long hFile = 0; + //ļϢ + struct _finddata_t fileinfo; + std::string p; + if ((hFile = _findfirst(p.assign(path).append("\\*").c_str(), &fileinfo))!=-1) + { + do + { + //Ŀ¼,֮ + //,б + if ((fileinfo.attrib & _A_SUBDIR)) + { + if (strcmp(fileinfo.name, ".") != 0 && strcmp(fileinfo.name, "..") != 0) + getFiles(p.assign(path).append("\\").append(fileinfo.name), files); + } + else + { + files.push_back(p.assign(path).append("\\").append(fileinfo.name)); + } + } while (_findnext(hFile, &fileinfo) == 0); + _findclose(hFile); + } + } + +}; diff --git a/huagao/Device/jpeglib.cpp b/huagao/Device/jpeglib.cpp new file mode 100644 index 00000000..75c5b13f --- /dev/null +++ b/huagao/Device/jpeglib.cpp @@ -0,0 +1,67 @@ +#include "stdafx.h" +#include "jpeglib.h" + +JpegLib::JpegLib() : +img_buffer(NULL), sizeBuffer(0) +{ + handle = std::shared_ptr (tjInitDecompress(),tjDestroy); +} + +JpegLib::~JpegLib() +{ + clear(); +} + +void JpegLib::clear() +{ + img_buffer.reset(); + sizeBuffer = 0; +} + +cv::Mat JpegLib::decode(cv::Mat buf, int pixelFormat) +{ + if(buf.rows != 1) + return cv::Mat(); + + decode(buf.data, buf.cols, pixelFormat); + + return cv::Mat(getHeight(), getWidth() , pixelFormat == TJPF_BGR ? CV_8UC3 : CV_8UC1, getData()); +} + +void JpegLib::decode(unsigned char* buff, unsigned long buff_size, int pixelFormat) +{ + tjDecompressHeader(handle.get(), buff, buff_size, &width, &height); + int size = width * height *tjPixelSize[pixelFormat]; + + if (sizeBuffer != size) + { + clear(); + img_buffer = std::shared_ptr(tjAlloc(size), tjFree); + sizeBuffer = size; + } + + if (img_buffer) + { + tjDecompress2(handle.get(), buff, buff_size, img_buffer.get(), width, 0, height, pixelFormat, 0); + } +} + +int JpegLib::getWidth() +{ + return width; +} + +int JpegLib::getHeight() +{ + return height; +} + +int JpegLib::getBufferSize() +{ + return sizeBuffer; +} + +unsigned char* JpegLib::getData() +{ + return img_buffer.get(); +} \ No newline at end of file diff --git a/huagao/Device/jpeglib.h b/huagao/Device/jpeglib.h new file mode 100644 index 00000000..c70a4d2d --- /dev/null +++ b/huagao/Device/jpeglib.h @@ -0,0 +1,26 @@ +#pragma once +#include "turbojpeg.h" +#include +#include + +class JpegLib +{ +public: + JpegLib(); + ~JpegLib(); + + void clear(); + cv::Mat decode(cv::Mat buf, int pixelFormat); + void decode(unsigned char* buff, unsigned long buff_size, int pixelFormat); + int getWidth(); + int getHeight(); + int getBufferSize(); + unsigned char* getData(); + +private: + std::shared_ptr handle; + std::shared_ptr img_buffer; + int sizeBuffer; + int width; + int height; +}; diff --git a/huagao/Device/scn_config.cpp b/huagao/Device/scn_config.cpp new file mode 100644 index 00000000..0a43fadf --- /dev/null +++ b/huagao/Device/scn_config.cpp @@ -0,0 +1,44 @@ +#include "stdafx.h" +#include "scn_config.h" +#include "math.h" + +hgConfigClass::hgConfigClass(GScanCap param) +{ + PaperStatus ps = { param.papertype,param.paperAlign }; + m_param.paper = ContainspaperTypesKey(ps) ? SupPaperTyps[ps] : 0; + m_param.color = ContainsPixTypeKey(param.hardwarecaps.capturepixtype) ? SupPixelTypes[param.hardwarecaps.capturepixtype] : 2; + m_param.dpi = 1;//Ĭ 200dpi ContainsResolutionKey(param.resolution_native) ? SupResolutions[param.resolution_native] : + m_param.double_feed_enbale = param.hardwarecaps.en_doublefeed; + m_param.stable_enbale = param.hardwarecaps.en_stapledetect; + m_param.screw_detect_enable = param.hardwarecaps.en_skrewdetect; + m_param.screw_detect_level = m_param.screw_detect_enable? secrewMaps[param.hardwarecaps.skrewdetectlevel]:0; + m_param.pc_correct = 0; + m_param.unused_one = m_param.unused_two = 0; +} + +bool hgConfigClass::ContainspaperTypesKey(PaperStatus key) +{ + if (SupPaperTyps.count(key) > 0) + { + return true; + } + return false; +} + +bool hgConfigClass::ContainsPixTypeKey(uint16_t key) +{ + if (SupPixelTypes.count(key)>0) + { + return true; + } + return false; +} + +bool hgConfigClass::ContainsResolutionKey(float key) +{ + if ( SupResolutions.count(key)>0) + { + return true; + } + return false; +} \ No newline at end of file diff --git a/huagao/Device/scn_config.h b/huagao/Device/scn_config.h new file mode 100644 index 00000000..bc8cdc5a --- /dev/null +++ b/huagao/Device/scn_config.h @@ -0,0 +1,29 @@ +#pragma once +#include +#include +#include +#include +#include +#include "PublicFunc.h" +#include "IConfig.h" + +typedef unsigned short uint16_t; + +class hgConfigClass:public IConfig +{ +public: + hgConfigClass(GScanCap param); +private: + enum Config_Scanner + { + cfStaple, + cfSkewDelection, + SkewLevel0, + SkewLevel1, + SkewLevel2 + }; + bool ContainspaperTypesKey(PaperStatus key); + bool ContainsPixTypeKey(uint16_t key); + bool ContainsResolutionKey(float key); +}; + diff --git a/huagao/HUAGO-LOGO-for UI.bmp b/huagao/HUAGO-LOGO-for UI.bmp new file mode 100644 index 00000000..090f5676 Binary files /dev/null and b/huagao/HUAGO-LOGO-for UI.bmp differ diff --git a/huagao/ImageProcess/ImageApply.cpp b/huagao/ImageProcess/ImageApply.cpp new file mode 100644 index 00000000..80f5fbf5 --- /dev/null +++ b/huagao/ImageProcess/ImageApply.cpp @@ -0,0 +1,9 @@ +#include "ImageApply.h" + +CImageApply::CImageApply(void) +{ +} + +CImageApply::~CImageApply(void) +{ +} diff --git a/huagao/ImageProcess/ImageApply.h b/huagao/ImageProcess/ImageApply.h new file mode 100644 index 00000000..3894eb29 --- /dev/null +++ b/huagao/ImageProcess/ImageApply.h @@ -0,0 +1,27 @@ +#ifndef IMAGE_APPLY_H +#define IMAGE_APPLY_H + +//#define LOG + +#include +#include +#include + +#if defined(LOG) +#include "Device/filetools.h" +#endif + +class CImageApply +{ +public: + CImageApply(void); + virtual ~CImageApply(void); + + virtual void apply(cv::Mat& pDib,int side) = 0; + + virtual void apply(std::vector& mats, bool isTwoSide) = 0; +}; + +typedef std::shared_ptr ImageApplyPtr; + +#endif //!IMAGE_APPLY_H diff --git a/huagao/ImageProcess/ImageApplyAdjustColors.cpp b/huagao/ImageProcess/ImageApplyAdjustColors.cpp new file mode 100644 index 00000000..d298e84e --- /dev/null +++ b/huagao/ImageProcess/ImageApplyAdjustColors.cpp @@ -0,0 +1,104 @@ +#include "ImageApplyAdjustColors.h" + +CImageApplyAdjustColors::CImageApplyAdjustColors(void) + : m_brightness(0) + , m_contrast(0) + , m_gamma(1.0f) + , lut(1, 256, CV_8UC1) +{ + update_lutData(); +} + +CImageApplyAdjustColors::CImageApplyAdjustColors(int brightness, int contrast, float gamma) + : lut(1, 256, CV_8UC1) +{ + setAdjustColors(brightness, contrast, gamma); +} + +CImageApplyAdjustColors::~CImageApplyAdjustColors(void) +{ + +} + +void CImageApplyAdjustColors::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyAdjustColors apply"); +#endif // LOG + if (pDib.empty()) + { + +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAdjustColors apply"); +#endif // LOG + return; + } + + if (m_brightness != 0 || m_contrast != 0 || m_gamma != 1.0) + cv::LUT(pDib, lut, pDib); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAdjustColors apply"); +#endif // LOG +} + +void CImageApplyAdjustColors::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} + +void CImageApplyAdjustColors::setAdjustColors(int brightness, int contrast, float gamma) +{ + setBrightness(brightness); + setContrast(contrast); + setGamma(gamma); + update_lutData(); +} + +void CImageApplyAdjustColors::setBrightness(int brightness) +{ + m_brightness = cv::max(-255, cv::min(brightness, 255)); + update_lutData(); +} + +void CImageApplyAdjustColors::setContrast(int contrast) +{ + m_contrast = cv::max(-127, cv::min(contrast, 127)); + update_lutData(); +} + +void CImageApplyAdjustColors::setGamma(float gamma) +{ + m_gamma = cv::max(0.1f, cv::min(gamma, 5.0f)); + update_lutData(); +} + +void CImageApplyAdjustColors::update_lutData() +{ + unsigned char* ptr = lut.data; + + if (m_gamma != 1.0f) + { + float g = 1.0f / m_gamma; + for (int i = 0; i < 256; i++) + ptr[i] = static_cast(cv::min(255, static_cast(cv::pow(i / 255.0f, g) * 255.0f + 0.5f))); + } + else + { + for (int i = 0; i < 256; i++) + { + //update contrast + if (i < 128) + ptr[i] = static_cast(cv::max(0, cv::min(i - m_contrast, 127))); + else + ptr[i] = static_cast(cv::max(127, cv::min(i + m_contrast, 255))); + + //update brightness + ptr[i] = static_cast(cv::max(0, cv::min(ptr[i] + m_brightness, 255))); + } + } +} diff --git a/huagao/ImageProcess/ImageApplyAdjustColors.h b/huagao/ImageProcess/ImageApplyAdjustColors.h new file mode 100644 index 00000000..f9dd77bb --- /dev/null +++ b/huagao/ImageProcess/ImageApplyAdjustColors.h @@ -0,0 +1,48 @@ +#ifndef IMAGE_APPLY_ADJUST_COLOR_H +#define IMAGE_APPLY_ADJUST_COLOR_H + +#include "ImageApply.h" + +class CImageApplyAdjustColors : public CImageApply +{ +public: + + CImageApplyAdjustColors(void); + + CImageApplyAdjustColors(int brightness, int contrast, float gamma); + + virtual ~CImageApplyAdjustColors(void); + + virtual void apply(cv::Mat& pDib, int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + + void setAdjustColors(int brightness, int contrast, float gamma); + + int getContrast() { return m_contrast; } + + int getBrightness() { return m_brightness; } + + double getGamma() { return m_gamma; } + + void setBrightness(int brightness); + + void setContrast(int contrast); + + void setGamma(float gamma); + +private: + + void update_lutData(); + +private: + + int m_brightness; + int m_contrast; + float m_gamma; + cv::Mat lut; +}; + +#endif // !IMAGE_APPLY_ADJUST_COLOR_H + + diff --git a/huagao/ImageProcess/ImageApplyAutoCrop.cpp b/huagao/ImageProcess/ImageApplyAutoCrop.cpp new file mode 100644 index 00000000..2dd22256 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyAutoCrop.cpp @@ -0,0 +1,183 @@ +#include "ImageApplyAutoCrop.h" +#include "ImageProcess_Public.h" + +#define RE 2 + +CImageApplyAutoCrop::CImageApplyAutoCrop() + : m_isCrop(false) + , m_isDesaskew(false) + , m_isFillBlank(false) + , m_isConvexHull(true) + , m_threshold(40) + , m_noise(2) + , m_indent(5) +{ +} + +CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex, double threshold, int noise, int indent) + : m_isCrop(isCrop) + , m_isDesaskew(isDesaskew) + , m_isFillBlank(isFillBlank) + , m_isConvexHull(isConvex) + , m_threshold(threshold) + , m_noise(noise) + , m_indent(indent) + , m_fixedSize(fixedSize) +{ +} + +CImageApplyAutoCrop::~CImageApplyAutoCrop() +{ +} + +void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyAutoCrop apply"); +#endif // LOG + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply"); +#endif // LOG + return; + } + + cv::Mat src = pDib; + cv::Mat dst; + cv::Mat src_resize; + cv::resize(src, src_resize, cv::Size(src.cols / RE, src.rows / RE)); + cv::Mat scale_mat; + cv::Mat thre(src_resize.size(), CV_8UC1); + hg::threshold_Mat(src_resize, thre, m_threshold); + + if (m_noise > RE) + { + cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(m_noise / RE, m_noise / RE)); + cv::morphologyEx(thre, thre, cv::MORPH_OPEN, element); + } + std::vector hierarchy; + std::vector> contours; + + hg::findContours(thre, contours, hierarchy, cv::RETR_EXTERNAL); + std::vector maxContour = hg::getMaxContour(contours, hierarchy); + + for (cv::Point& item : maxContour) + { + item.x = item.x * RE - RE / 2; + item.y = item.y * RE - RE / 2; + } + + if (maxContour.size() == 0) + { + thre.release(); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply"); +#endif // LOG + return; + } + thre.release(); + dst.release(); + + cv::RotatedRect rect = hg::getBoundingRect(maxContour); + + if (m_isDesaskew) + { + cv::Point2f srcTri[4]; + cv::Point2f dstTri[3]; + rect.points(srcTri); + + dstTri[0] = cv::Point2f(0, rect.size.height - 1); + dstTri[1] = cv::Point2f(0, 0); + dstTri[2] = cv::Point2f(rect.size.width - 1, 0); + + cv::Mat warp_mat; + warp_mat = cv::getAffineTransform(srcTri, dstTri); + cv::warpAffine(src, dst, warp_mat, rect.size); + } + else + dst = src(rect.boundingRect() & cv::Rect(0, 0, src.cols, src.rows)); + + if (m_isFillBlank) + { + cv::Mat thre_dst; + hg::threshold_Mat(dst, thre_dst, m_threshold); + cv::erode(thre_dst, thre_dst, cv::Mat(), cv::Point(-1, -1), m_indent); + hierarchy.clear(); + contours.clear(); + maxContour.clear(); + + hg::findContours(thre_dst, contours, hierarchy, cv::RETR_EXTERNAL); + maxContour = hg::getMaxContour(contours, hierarchy); + if (m_isConvexHull) + hg::convexHull(maxContour, maxContour); + + contours.clear(); + contours.resize(2); + contours[0] = maxContour; + contours[1].push_back(cv::Point(0, dst.rows - 1)); + contours[1].push_back(cv::Point(0, 0)); + contours[1].push_back(cv::Point(dst.cols - 1, 0)); + contours[1].push_back(cv::Point(dst.cols - 1, dst.rows - 1)); + + hg::fillPolys(dst, contours, cv::Scalar(255, 255, 255)); + } + + pDib.release(); + if ((m_isCrop && side == 0) || (side == 1 && m_fixedSize.width * m_fixedSize.height == 0)) + pDib = dst.clone(); + else + { + if (m_isCrop && side == 1 && !m_fixedSize.empty()) + if (std::abs(m_fixedSize.width - dst.cols) > 50 || std::abs(m_fixedSize.height - dst.rows) > 50) + { + pDib = dst.clone(); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply"); +#endif // LOG + return; + } + pDib = cv::Mat(m_fixedSize, dst.type(), m_isFillBlank ? cv::Scalar(255, 255, 255) : cv::Scalar(0, 0, 0)); + + cv::Rect roi; + roi.x = dst.cols > pDib.cols ? (dst.cols - pDib.cols) / 2 : 0; + roi.width = cv::min(pDib.cols, dst.cols); + roi.y = dst.rows > pDib.rows ? (dst.rows - pDib.rows) / 2 : 0; + roi.height = cv::min(pDib.rows, dst.rows); + cv::Rect rect((pDib.cols - roi.width) / 2, (pDib.rows - roi.height) / 2, roi.width, roi.height); +#if 0 + std::string outrectinfo ="copy to rect x: "+std::to_string(rect.x) + "y: "+std::to_string(rect.y) + "width: "+std::to_string(rect.width) + "height: "+std::to_string(rect.height); + std::string outroiinfo = "roi x: " + std::to_string(roi.x) + "y: " + std::to_string(roi.y) + "width: " + std::to_string(roi.width) + "height: " + std::to_string(roi.height); + std::string dstsize = "dst size: width:" + std::to_string(dst.cols) + "height: " + std::to_string(dst.rows); + std::string pDibszie= "pDib size: width: " + std::to_string(pDib.cols) + "height: " + std::to_string(pDib.rows); + FileTools::write_log("imgprc.txt", dstsize); + FileTools::write_log("imgprc.txt", pDibszie); + FileTools::write_log("imgprc.txt", outrectinfo); + FileTools::write_log("imgprc.txt", outroiinfo); +#endif // LOG + dst(roi).copyTo(pDib(rect)); + + } +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply8"); +#endif // LOG +} + +void CImageApplyAutoCrop::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + { + cv::Size dSize = m_fixedSize; + if (!mats[0].empty()) + m_fixedSize = mats[0].size(); + + apply(mats[1], 1); + + if (!mats[0].empty()) + m_fixedSize = dSize; + } +} \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyAutoCrop.h b/huagao/ImageProcess/ImageApplyAutoCrop.h new file mode 100644 index 00000000..23eefe84 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyAutoCrop.h @@ -0,0 +1,66 @@ +#ifndef IMAGE_APPLY_AUTO_CROP_H +#define IMAGE_APPLY_AUTO_CROP_H + +#include "ImageApply.h" + +class CImageApplyAutoCrop : public CImageApply +{ +public: + CImageApplyAutoCrop(); + + CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex = true, double threshold = 40, int noise = 40, int indent = 5); + + virtual ~CImageApplyAutoCrop(); + + virtual void apply(cv::Mat& pDib, int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + + bool isAutoCrop() { return m_isCrop; } + + bool isFillBlank() { return m_isFillBlank; } + + bool isDesaskew() { return m_isDesaskew; } + + bool isConvexHull() { return m_isConvexHull; } + + double threshold() { return m_threshold; } + + int noise() { return m_noise; } + + int indent() { return m_indent; } + + cv::Size fixedSize() { return m_fixedSize; } + + void setAutoCrop(bool enabled) { m_isCrop = enabled; } + + void setFillBlank(bool enabled) { m_isFillBlank = enabled; } + + void setDesaskew(bool enabled) { m_isDesaskew = enabled; } + + void setConvexHull(bool convex) { m_isConvexHull = convex; } + + void setThreshold(double value) { m_threshold = value; } + + void setNoise(int value) { m_noise = value; } + + void setIndent(int value) { m_indent = value; } + + void setFixedSize(cv::Size size) { m_fixedSize = size; } + +private: + bool m_isCrop; + bool m_isDesaskew; + bool m_isFillBlank; + bool m_isConvexHull; + + double m_threshold; + int m_noise; + int m_indent; + cv::Size m_fixedSize; + +}; + +#endif // !IMAGE_APPLY_AUTO_CROP_H + + diff --git a/huagao/ImageProcess/ImageApplyBWBinaray.cpp b/huagao/ImageProcess/ImageApplyBWBinaray.cpp new file mode 100644 index 00000000..2d1125b9 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyBWBinaray.cpp @@ -0,0 +1,143 @@ +#include "ImageApplyBWBinaray.h" + +CImageApplyBWBinaray::CImageApplyBWBinaray(ThresholdType type, int threshold, int blockSize, int constant) + : m_threshold(threshold) + , m_type(type) + , m_blockSize(blockSize) + , m_constant(constant) + , m_table(new uchar[256]) +{ + memset(m_table, 255, 256); + memset(m_table, 0, static_cast(m_threshold)); +} + +CImageApplyBWBinaray::CImageApplyBWBinaray() + : m_threshold(180) + , m_type(ThresholdType::THRESH_BINARY) + , m_blockSize(25) + , m_constant(5) + , m_table(new uchar[256]) +{ + memset(m_table, 255, 256); + memset(m_table, 0, static_cast(m_threshold)); +} + + +CImageApplyBWBinaray::~CImageApplyBWBinaray(void) +{ + delete[] m_table; +} + +void CImageApplyBWBinaray::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyBWBinaray apply"); +#endif // LOG + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyBWBinaray apply"); +#endif // LOG + return; + } + + if (pDib.channels() == 3) + cv::cvtColor(pDib, pDib, cv::COLOR_BGR2GRAY); + + switch (m_type) + { + case ThresholdType::THRESH_BINARY: + cv::threshold(pDib, pDib, m_threshold, 255, CV_THRESH_BINARY); + break; + case ThresholdType::THRESH_OTSU: + cv::threshold(pDib, pDib, m_threshold, 255, CV_THRESH_OTSU); + break; + case ThresholdType::ADAPTIVE_GAUSSIAN: + cv::adaptiveThreshold(pDib, pDib, 255, cv::ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, m_blockSize, m_constant); + break; + case ThresholdType::ADAPTIVE_MEAN: + cv::adaptiveThreshold(pDib, pDib, 255, cv::ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, m_blockSize, m_constant); + break; + case ThresholdType::ERROR_DIFFUSION: + errorDiffuse(pDib); + break; + default: + break; + } + +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyBWBinaray apply"); +#endif // LOG +} + +void CImageApplyBWBinaray::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} + +void CImageApplyBWBinaray::errorDiffuse(cv::Mat & image) +{ + if (image.rows < 3 || image.cols < 3) + { + cv::threshold(image, image, m_threshold, 255, CV_THRESH_BINARY); + return; + } + + cv::Mat dst; + image.convertTo(dst, CV_16S); + + size_t rows = static_cast(image.rows) - 1; + size_t cols = static_cast(image.cols) - 1; + + short** pixels_dst = new short*[static_cast(image.rows)]; + for (int i = 0; i < image.rows; i++) + pixels_dst[i] = reinterpret_cast(dst.data + i * static_cast(dst.step)); + + short error; + for (size_t y = 0; y < rows; y++) + for (size_t x = 1; x < cols; x++) + { + short dstPix = pixels_dst[y][x]; + if (dstPix >= m_threshold) + { + pixels_dst[y][x] = 255; + error = dstPix - 255; + } + else + { + pixels_dst[y][x] = 0; + error = dstPix; + } + + pixels_dst[y][x + 1] += error * 7 / 16; + pixels_dst[y + 1][x - 1] += error * 3 / 16; + pixels_dst[y + 1][x] += error * 5 / 16; + pixels_dst[y + 1][x + 1] += error * 1 / 16; + } + image.release(); + dst.convertTo(image, CV_8U); + + rows++; + uchar* ptr = image.data; + size_t step = image.step; + size_t offset; + for (size_t y = 0; y < rows; y++) + { + offset = y * step; + ptr[offset] = m_table[ptr[offset]]; + offset += cols; + ptr[offset] = m_table[ptr[offset]]; + } + + cols++; + ptr = image.data + step * (rows - 1); + for (size_t x = 0; x < cols; x++) + ptr[x] = m_table[ptr[x]]; + + delete[] pixels_dst; +} diff --git a/huagao/ImageProcess/ImageApplyBWBinaray.h b/huagao/ImageProcess/ImageApplyBWBinaray.h new file mode 100644 index 00000000..9f062f97 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyBWBinaray.h @@ -0,0 +1,64 @@ +#ifndef IMAGE_APPLY_BW_BINARAY_H +#define IMAGE_APPLY_BW_BINARAY_H + +#include "ImageApply.h" + +class CImageApplyBWBinaray:public CImageApply +{ +public: + + enum class ThresholdType + { + THRESH_BINARY = 0, + THRESH_OTSU, + + ADAPTIVE_GAUSSIAN, + ADAPTIVE_MEAN, + + ERROR_DIFFUSION + }; + + CImageApplyBWBinaray(ThresholdType type, int threshold = 180, int blockSize = 25, int constant = 5); + + CImageApplyBWBinaray(); + + virtual ~CImageApplyBWBinaray(void); + + virtual void apply(cv::Mat& pDib,int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + + double getThreshold() { return m_threshold; } + + ThresholdType getThresholdType() { return m_type; } + + int getBlockSize() { return m_blockSize; } + + double getConstant() { return m_constant; } + + void setThreshold(double value) { m_threshold = value; } + + void setThresholdType(ThresholdType type) { m_type = type; } + + void setBlockSize(int value) { m_blockSize = value; } + + void setConstant(double value) { m_constant = value; } + +private: + + void errorDiffuse(cv::Mat& image); + +private: + double m_threshold; + + ThresholdType m_type; + + int m_blockSize; + + double m_constant; + + uchar* m_table; +}; + +#endif //!IMAGE_APPLY_BW_BINARAY_H + diff --git a/huagao/ImageProcess/ImageApplyChannel.cpp b/huagao/ImageProcess/ImageApplyChannel.cpp new file mode 100644 index 00000000..ba96ca49 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyChannel.cpp @@ -0,0 +1,99 @@ +#include "ImageApplyChannel.h" + +CImageApplyChannel::CImageApplyChannel() + : m_channel(Invalid) +{ +} + +CImageApplyChannel::CImageApplyChannel(Channel channel) + : m_channel(channel) +{ +} + +CImageApplyChannel::~CImageApplyChannel(void) +{ +} + +void CImageApplyChannel::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyChannel apply"); +#endif // LOG + + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyChannel apply"); +#endif // LOG + return; + } + + cv::Mat dst(pDib.rows, pDib.cols, CV_8UC1); + switch (m_channel) + { + case Red: + cv::extractChannel(pDib, dst, 2); + break; + case Green: + cv::extractChannel(pDib, dst, 1); + break; + case Blue: + cv::extractChannel(pDib, dst, 0); + break; + case Except_Red: + except_channel(pDib, dst, 2); + break; + case Except_Green: + except_channel(pDib, dst, 1); + break; + case Except_Blue: + except_channel(pDib, dst, 0); + break; + default: + break; + } + pDib.release(); + pDib = dst; +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyChannel apply"); +#endif // LOG +} + +void CImageApplyChannel::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} + +void CImageApplyChannel::except_channel(const cv::Mat & src, cv::Mat & dst, int channel) +{ + int rows = src.total(); + cv::Mat src_temp(rows, 3, CV_8UC1, src.data); + cv::Mat dst_temp(rows, 1, CV_8UC1, dst.data); + + cv::Mat temp1, temp2; + switch (channel) + { + case 0: + temp1 = src_temp(cv::Rect(1, 0, 1, rows)); + temp2 = src_temp(cv::Rect(2, 0, 1, rows)); + cv::addWeighted(temp1, 0.84, temp2, 0.16, 0, dst_temp); + break; + case 1: + temp1 = src_temp(cv::Rect(0, 0, 1, rows)); + temp2 = src_temp(cv::Rect(2, 0, 1, rows)); + cv::addWeighted(temp1, 0.73, temp2, 0.27, 0, dst_temp); + break; + case 2: + temp1 = src_temp(cv::Rect(0, 0, 1, rows)); + temp2 = src_temp(cv::Rect(1, 0, 1, rows)); + cv::addWeighted(temp1, 0.33, temp2, 0.67, 0, dst_temp); + break; + default: + break; + } +} diff --git a/huagao/ImageProcess/ImageApplyChannel.h b/huagao/ImageProcess/ImageApplyChannel.h new file mode 100644 index 00000000..cb7d9017 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyChannel.h @@ -0,0 +1,42 @@ +#ifndef IMAGE_APPLY_CHANNEL_H +#define IMAGE_APPLY_CHANNEL_H + +#include "imageapply.h" + +class CImageApplyChannel : public CImageApply +{ +public: + + typedef enum channel + { + Red, + Green, + Blue, + Invalid, + Except_Red, + Except_Green, + Except_Blue + }Channel; + +public: + + CImageApplyChannel(); + + CImageApplyChannel(Channel channel); + + virtual ~CImageApplyChannel(void); + + virtual void apply(cv::Mat& pDib,int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + +private: + + void except_channel(const cv::Mat& src, cv::Mat& dst, int channel); + +private: + + Channel m_channel; +}; + +#endif // !IMAGE_APPLY_CHANNEL_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyCrop.cpp b/huagao/ImageProcess/ImageApplyCrop.cpp new file mode 100644 index 00000000..763da940 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyCrop.cpp @@ -0,0 +1,48 @@ +#include "ImageApplyCrop.h" + +CImageApplyCrop::CImageApplyCrop(void) +{ +} + + +CImageApplyCrop::~CImageApplyCrop(void) +{ +} + +void CImageApplyCrop::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyCrop apply"); +#endif // LOG + + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyCrop apply"); +#endif // LOG + return; + } + + if (m_roi.x < 0 || m_roi.y < 0 || m_roi.br().x >= pDib.cols || m_roi.br().y >= pDib.rows || m_roi.width == 0 || m_roi.height == 0) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyCrop apply"); +#endif // LOG + return; + } + + pDib = pDib(m_roi).clone(); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyCrop apply"); +#endif // LOG +} + +void CImageApplyCrop::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} diff --git a/huagao/ImageProcess/ImageApplyCrop.h b/huagao/ImageProcess/ImageApplyCrop.h new file mode 100644 index 00000000..3d178b5e --- /dev/null +++ b/huagao/ImageProcess/ImageApplyCrop.h @@ -0,0 +1,28 @@ +#ifndef IMAGE_APPLY_CROP_H +#define IMAGE_APPLY_CROP_H + +#include "imageapply.h" + +class CImageApplyCrop : public CImageApply +{ + +public: + + CImageApplyCrop(void); + + virtual ~CImageApplyCrop(void); + + virtual void apply(cv::Mat& pDib,int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + + cv::Rect getROI() { return m_roi; } + + void setROI(const cv::Rect& rect) { m_roi = rect; } + +private: + + cv::Rect m_roi; +}; + +#endif // !IMAGE_APPLY_CROP_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyDiscardBlank.cpp b/huagao/ImageProcess/ImageApplyDiscardBlank.cpp new file mode 100644 index 00000000..ff768b79 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyDiscardBlank.cpp @@ -0,0 +1,175 @@ +#include "ImageApplyDiscardBlank.h" +#include "ImageProcess_Public.h" + +CImageApplyDiscardBlank::CImageApplyDiscardBlank(bool isnormal) + : m_res(false) + , isNormalDiscard(isnormal) + , dSize(200) + , devTh(15, 15, 15, 15) +{ +} + +CImageApplyDiscardBlank::~CImageApplyDiscardBlank(void) +{ +} + +int CImageApplyDiscardBlank::processRectR(const cv::Mat& image, cv::RotatedRect& rotatedRect, std::vector& maxContour, + double scale, double thresh, int blobAreaSize) +{ + cv::Mat gray; + int blockCount = 0; + if (image.channels() == 3) + if (scale != 1.0f) + { + cv::Size ResImgSiz = cv::Size(image.cols * scale, image.rows * scale); + resize(image, gray, cv::Size(), scale, scale, 0); + cvtColor(gray, gray, CV_BGR2GRAY); + } + else + cvtColor(image, gray, CV_BGR2GRAY); + else + if (scale != 1.0f) + resize(image, gray, cv::Size(), scale, scale, 0); + else + gray = image; + + cv::Mat threshold_img; + threshold(gray, threshold_img, thresh, 255.0, CV_THRESH_BINARY); + std::vector> contours; + std::vector h1; + hg::findContours(threshold_img, contours, h1, CV_CHAIN_APPROX_SIMPLE); + threshold_img.release(); + + if (contours.size() == 0) + return blockCount; + + std::vector list_com; + for (int i = 0; i < contours.size(); i++) + { + double area = cv::contourArea(contours[i]); + if (area > blobAreaSize) + { + blockCount++; + for (int j = 0; j < contours[i].size(); j++) + list_com.push_back(contours[i][j]); + } + } + + if (list_com.size() == 0) + return blockCount; + + rotatedRect = cv::minAreaRect(list_com); + rotatedRect.center.x /= (float)scale; + rotatedRect.center.y /= (float)scale; + rotatedRect.size.width /= (float)scale; + rotatedRect.size.height /= (float)scale; + + if (rotatedRect.angle < -45.0f) + { + rotatedRect.angle += 90.0f; + float l_temp = rotatedRect.size.width; + rotatedRect.size.width = rotatedRect.size.height; + rotatedRect.size.height = l_temp; + } + + std::vector hull(list_com.size()); + cv::convexHull(list_com, hull); + + for (int i = 0; i < hull.size(); i++) + { + cv::Point temp = list_com[hull[i]]; + int x = (int)(temp.x / scale); + int y = (int)(temp.y / scale); + maxContour.push_back(cv::Point(x, y)); + } + + return blockCount; +} + + bool CImageApplyDiscardBlank::scalar_LE(const cv::Scalar& val1, const cv::Scalar& val2) +{ + for(int i = 0; i < 3; i++) + if(val1[i] > val2[i]) + return false; + return true; +} + +void CImageApplyDiscardBlank::setIntensity(int val) +{ + val = cv::max(cv::min(20, val), 2); + devTh = cv::Scalar(val, val, val, val); +} + +cv::Mat CImageApplyDiscardBlank::getRoiMat(const cv::Mat& image) +{ + int gap = 100; + cv::RotatedRect rect; + std::vector contour; + double scale = 0.25; + double thresh = 50; + int blobSize = 200; + int edgeWidth = 10; + processRectR(image, rect, contour, scale, thresh, blobSize); + cv::Rect rect2 = rect.boundingRect(); + cv::Rect inRect = rect2 & cv::Rect(0, 0, image.cols, image.rows); + gap = cv::max(inRect.width - rect.size.width, inRect.height - rect.size.height) + 100; + inRect = cv::Rect(inRect.x + gap, inRect.y + gap, inRect.width - gap * 2, inRect.height - gap * 2); + return image(inRect); +} + +void CImageApplyDiscardBlank::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyDiscardBlank apply"); +#endif // LOG + + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply"); +#endif // LOG + return; + } + + setIntensity(isNormalDiscard ? 8 : 20); + setMinArea(isNormalDiscard ? 200 : 300); + + cv::Scalar mean; + cv::Scalar dev; + cv::Mat image = getRoiMat(pDib); + cv::Rect rect; + cv::Rect imRect(0, 0, image.cols, image.rows); + for(int i = 0; i < image.cols; i+= dSize) + for(int j = 0; j < image.rows; j+= dSize) + { + rect = cv::Rect(i, j,dSize, dSize) & imRect; + if(rect != cv::Rect()) + { + cv::meanStdDev (image(rect) , mean, dev); + if(!scalar_LE(dev, devTh)) + { + m_res = false; +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply"); +#endif // LOG + return; + } + } + } + m_res = true; + if (m_res) + pDib.release(); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyDiscardBlank apply"); +#endif // LOG +} + +void CImageApplyDiscardBlank::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyDiscardBlank.h b/huagao/ImageProcess/ImageApplyDiscardBlank.h new file mode 100644 index 00000000..70394911 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyDiscardBlank.h @@ -0,0 +1,35 @@ +#ifndef IMAGE_APPLY_DISCARD_BLANK_H +#define IMAGE_APPLY_DISCARD_BLANK_H + +#include "ImageApply.h" + +class CImageApplyDiscardBlank : public CImageApply +{ +public: + CImageApplyDiscardBlank(bool isnormal = true); + + virtual ~CImageApplyDiscardBlank(void); + + virtual void apply(cv::Mat& pDib,int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + +private: + void setIntensity(int val); + + void setMinArea(int val) { dSize = val; } + + int processRectR(const cv::Mat& image, cv::RotatedRect& rotatedRect, std::vector& maxContour, + double scale, double thresh, int blobAreaSize); + + bool scalar_LE(const cv::Scalar& val1, const cv::Scalar& val2); + + cv::Mat getRoiMat(const cv::Mat& pDib); +private: + bool m_res; + bool isNormalDiscard; + int dSize; + cv::Scalar devTh; +}; + +#endif // !IMAGE_APPLY_DISCARD_BLANK_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyHeaders.h b/huagao/ImageProcess/ImageApplyHeaders.h new file mode 100644 index 00000000..3b3dee2c --- /dev/null +++ b/huagao/ImageProcess/ImageApplyHeaders.h @@ -0,0 +1,16 @@ +#ifndef IMAGE_APPLY_HEADER_H +#define IMAGE_APPLY_HEADER_H + +#include "ImageApply.h" +#include "ImageApplyAdjustColors.h" +#include "ImageApplyAutoCrop.h" +#include "ImageApplyBWBinaray.h" +#include "ImageApplyChannel.h" +#include "ImageApplyCrop.h" +#include "ImageApplyDiscardBlank.h" +#include "ImageApplyOutHole.h" +#include "ImageApplyResize.h" +#include "ImageApplyRotation.h" +#include "ImageApplySharpen.h" + +#endif diff --git a/huagao/ImageProcess/ImageApplyOutHole.cpp b/huagao/ImageProcess/ImageApplyOutHole.cpp new file mode 100644 index 00000000..3cde1b59 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyOutHole.cpp @@ -0,0 +1,251 @@ +#include "ImageApplyOutHole.h" +#include "ImageProcess_Public.h" + +#ifdef LOG +#include "Device/filetools.h" +#endif // LOG + +CImageOutHole::CImageOutHole(void) + : CImageApply() + , m_borderSize(200) + , m_edgeScale(0.1f) + , m_threshold(50) +{ +} + +CImageOutHole::CImageOutHole(float borderSize, float edgeScale, double threshold) + : CImageApply() + , m_borderSize(borderSize) + , m_edgeScale(edgeScale) + , m_threshold(threshold) +{ +} + +CImageOutHole::~CImageOutHole(void) +{ +} + +void CImageOutHole::apply(cv::Mat& pDib, int side) {} + +void CImageOutHole::apply(std::vector& mats, bool isTwoSide) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter ImageOutHole apply"); +#endif // LOG + + if (mats.size() < 2) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit ImageOutHole apply"); +#endif // LOG + return; + } + + if (mats[0].empty() || mats[1].empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit ImageOutHole apply"); +#endif // LOG + return; + } + + //ֵͼ + cv::Mat front = mats[0]; + cv::Mat back = mats[1]; + cv::Mat front_thre, back_thre; + hg::threshold_Mat(front, front_thre, m_threshold); + hg::threshold_Mat(back, back_thre, m_threshold); + + //ֵͼˮƽת + cv::flip(back_thre, back_thre, 1); //1:Horizontal + + //ͼѰ + std::vector> contours_front, contours_back; + std::vector b1_front, b1_back; + hg::findContours(front_thre.clone(), contours_front, b1_front, cv::RETR_EXTERNAL); + hg::findContours(back_thre.clone(), contours_back, b1_back, cv::RETR_EXTERNAL); + + //ȡͼ + std::vector maxContour_front = hg::getMaxContour(contours_front, b1_front); + std::vector maxContour_back = hg::getMaxContour(contours_back, b1_back); + + cv::RotatedRect rrect_front = hg::getBoundingRect(maxContour_front); //ȡСӾ + cv::RotatedRect rrect_back = hg::getBoundingRect(maxContour_back); //ȡСӾ + + //ȡͼص + cv::Rect roi_front, roi_back; + cv::RotatedRect mask_rotatedRect; + getRoi(rrect_front, rrect_back, cv::Size(front.cols, front.rows), roi_front, roi_back, mask_rotatedRect); + + cv::Mat roiMat_front(front_thre, roi_front); //ֵͼнȡص + cv::Mat roiMat_back(back_thre, roi_back); //ڷֵͼнȡص + + //ֵͼ㣬ο0طΪ255 + cv::Mat mask; + bitwise_or(roiMat_front, roiMat_back, mask); //㣬ֵͼص + + //ֵͼصͼɫȡͣȡ + std::vector> contours_mask; + std::vector b1_mask; + bitwise_not(mask, mask); //ɫ + + cv::Mat element = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(15, 15)); + dilate(mask, mask, element, cv::Point(-1, -1), 1, cv::BORDER_CONSTANT, cv::Scalar(255)); //㷨׶ͨ + + //Ϊ˱׶׹ᴩֽߣΪֽȷп׶ΪͼΣ뱳ճ + polylines(mask, hg::getVertices(mask_rotatedRect), true, cv::Scalar(0), 15); //ֽžαԵ + + hg::findContours(mask.clone(), contours_mask, b1_mask, cv::RETR_TREE); //ȡصͼ + + //˷ǿ׶ͨ + std::vector> hole_contours = filterPoly(contours_mask, b1_mask, mask_rotatedRect, m_edgeScale, m_borderSize); + for (int i = 0; i < hole_contours.size(); i++) + cv::drawContours(mask, hole_contours, i, cv::Scalar(127), 2); + + for (size_t i = 0; i < hole_contours.size(); i++) + { + cv::Scalar color = getBackGroudColor(front(roi_front), hole_contours[i]); + cv::Mat temp = front(roi_front); + std::vector> contourss_temp; + contourss_temp.push_back(hole_contours[i]); + hg::fillPolys(temp, contourss_temp, color); + } + + if (isTwoSide) + { + int width_ = roi_back.width; + roi_back.x = back.cols - roi_back.width - roi_back.x; //Ϊ֮ǰͼתROIҲҪӦת + for (size_t i = 0; i < hole_contours.size(); i++) + { + std::vector hole_contour; + for (size_t j = 0; j < hole_contours[i].size(); j++) + hole_contour.push_back(cv::Point(width_ - hole_contours[i][j].x - 1, hole_contours[i][j].y)); + + cv::Scalar color = getBackGroudColor(back(roi_back), hole_contour); + cv::Mat temp = back(roi_back); + + std::vector> contours_temp; + contours_temp.push_back(hole_contour); + hg::fillPolys(temp, contours_temp, color); + } + } +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit ImageOutHole apply"); +#endif // LOG +} + +void CImageOutHole::getRoi(cv::RotatedRect rrect_front, cv::RotatedRect rrect_back, cv::Size srcSize, + cv::Rect& roi_front, cv::Rect& roi_back, cv::RotatedRect& mask_rotatedRect) +{ + cv::Size size(static_cast(rrect_front.size.width + rrect_back.size.width) / 2, static_cast(rrect_front.size.height + rrect_back.size.height) / 2); + float angle = (rrect_front.angle + rrect_back.angle) / 2; + + rrect_front.size = rrect_back.size = size; + rrect_front.angle = rrect_back.angle = angle; + + roi_front = rrect_front.boundingRect(); + roi_back = rrect_back.boundingRect(); + + if (roi_front.width != roi_back.width || roi_front.height != roi_back.height) + { + roi_front.height = roi_back.height; + roi_front.width = roi_back.width; + } + + cv::Point offset(0, 0); + int top = std::min(roi_front.y, roi_back.y); + if (top < 0) + { + roi_front.y -= top; + roi_back.y -= top; + roi_front.height += top; + roi_back.height += top; + offset.y += top; + } + + int left = std::min(roi_front.x, roi_back.x); + if (left < 0) + { + roi_front.x -= left; + roi_back.x -= left; + roi_front.width += left; + roi_back.width += left; + offset.x += left; + } + + int right = std::max(roi_front.x + roi_front.width, roi_back.x + roi_back.width); + if (right >= srcSize.width) + { + roi_front.width -= (right - srcSize.width + 1); + roi_back.width -= (right - srcSize.width + 1); + } + + int bottom = std::max(roi_front.y + roi_front.height, roi_back.y + roi_back.height); + if (bottom >= srcSize.height) + { + roi_front.height -= (bottom - srcSize.height + 1); + roi_back.height -= (bottom - srcSize.height + 1); + } + + mask_rotatedRect.center = cv::Point((roi_front.width + offset.x) / 2, (roi_front.height + offset.y) / 2); + mask_rotatedRect.size = size; + mask_rotatedRect.angle = angle; +} + +std::vector> CImageOutHole::filterPoly(std::vector>& contours, const std::vector& m, + cv::RotatedRect roi, float edgeScale, float areaThreshold) +{ + edgeScale = std::min(0.49f, std::max(edgeScale, 0.0f)); + cv::RotatedRect roi2(roi.center, cv::Size(static_cast(roi.size.width * (1 - edgeScale * 2)), + static_cast(roi.size.height * (1 - edgeScale * 2))), roi.angle); + + std::vector vertices_roi1 = hg::getVertices(roi); + std::vector vertices_roi2 = hg::getVertices(roi2); + + std::vector> hole_contours; + for (size_t i = 0, length = contours.size(); i < length; i++) + { + if (m[i][2] != -1) continue; + + cv::RotatedRect rrect = hg::getBoundingRect(contours[i]); + if (rrect.size.width > areaThreshold || rrect.size.height > areaThreshold) continue; + + bool enabled = true; + for (size_t j = 0, count = contours[i].size(); j < count; j++) + { + cv::Point p(contours[i][j]); + double temp1 = pointPolygonTest(vertices_roi1, p, false); //жǷֽ 1ڣ0ϣ-1 + double temp2 = pointPolygonTest(vertices_roi2, p, false); //жǷڱԵ 1ڣ0ϣ-1 + //ֽ⣬߱ԵڣΪǿ׶ + if (temp1 < 0 || temp2 > 0) + { + enabled = false; + break; + } + } + + if (enabled) + hole_contours.push_back(contours[i]); + } + return hole_contours; +} + +cv::Scalar CImageOutHole::getBackGroudColor(const cv::Mat &image, const std::vector pixelPoints) +{ + if (pixelPoints.empty()) return cv::Scalar(255, 255, 255); + + int channels = image.channels(); + + int temp[3] = { 0 }; + for (size_t i = 0, length = pixelPoints.size(); i < length; ++i) + { + int x = cv::min(cv::max(0, pixelPoints[i].x), image.cols - 1); + int y = cv::min(cv::max(0, pixelPoints[i].y), image.rows - 1); + + const unsigned char* ptr = image.ptr(y, x); + for (int j = 0; j < channels; ++j) + temp[j] += ptr[j]; + } + + return cv::Scalar(temp[0] / pixelPoints.size(), temp[1] / pixelPoints.size(), temp[2] / pixelPoints.size()); +} diff --git a/huagao/ImageProcess/ImageApplyOutHole.h b/huagao/ImageProcess/ImageApplyOutHole.h new file mode 100644 index 00000000..20aebb4e --- /dev/null +++ b/huagao/ImageProcess/ImageApplyOutHole.h @@ -0,0 +1,49 @@ +#ifndef IMAGE_APPLY_OUT_HOLE_H +#define IMAGE_APPLY_OUT_HOLE_H + +#include "ImageApply.h" + +class CImageOutHole : public CImageApply +{ + +public: + + CImageOutHole(); + + CImageOutHole(float borderSize, float edgeScale, double threshold); + + ~CImageOutHole(void); + + virtual void apply(std::vector& mats, bool isTwoSide); + + float getBorderSize() { return m_borderSize; } + + float getEdgeScale() { return m_edgeScale; } + + double getThreshold() { return m_threshold; } + + void setBorderSize(float size) { m_borderSize = size; } + + void setEdgeScale(float scale) { m_edgeScale = scale; } + + void setThreshold(double threshold) { m_threshold = std::min(std::max(threshold, 1.0), 254.0); } + +private: + + virtual void apply(cv::Mat& pDib, int side); + + void getRoi(cv::RotatedRect rrect_front, cv::RotatedRect rrect_back, cv::Size srcSize, cv::Rect& roi_front, + cv::Rect& roi_back, cv::RotatedRect& mask_rotatedRect); + + std::vector > filterPoly(std::vector>& contours, const std::vector &m, cv::RotatedRect roi, + float edgeScale, float areaThreshold); + + cv::Scalar getBackGroudColor(const cv::Mat& image, const std::vector pixelPoints); + +private: + float m_borderSize; + float m_edgeScale; + double m_threshold; +}; + +#endif // !IMAGE_APPLY_OUT_HOLE_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyResize.cpp b/huagao/ImageProcess/ImageApplyResize.cpp new file mode 100644 index 00000000..ddf7e8f5 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyResize.cpp @@ -0,0 +1,55 @@ +#include "ImageApplyResize.h" + +CImageApplyResize::CImageApplyResize() + : m_fx(1.0) + , m_fy(1.0) + , m_type(ResizeType::RATIO) +{ +} + +CImageApplyResize::CImageApplyResize(ResizeType type, const cv::Size& size, double fx, double fy) + : m_type(type) + , m_dSize(size) + , m_fx(fx) + , m_fy(fy) +{ +} + + +CImageApplyResize::~CImageApplyResize(void) +{ +} + + +void CImageApplyResize::apply(cv::Mat& pDib,int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyResize apply"); +#endif // LOG + + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyResize apply"); +#endif // LOG + return; + } + + if (m_type == ResizeType::RATIO) + cv::resize(pDib, pDib, cv::Size(0, 0), m_fx, m_fy); + else + cv::resize(pDib, pDib, m_dSize); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyResize apply"); +#endif // LOG +} + +void CImageApplyResize::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} diff --git a/huagao/ImageProcess/ImageApplyResize.h b/huagao/ImageProcess/ImageApplyResize.h new file mode 100644 index 00000000..6b694bb6 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyResize.h @@ -0,0 +1,51 @@ +#ifndef IMAGE_APPLY_RESIZE_H +#define IMAGE_APPLY_RESIZE_H + +#include "imageapply.h" + +class CImageApplyResize : public CImageApply +{ +public: + + enum class ResizeType + { + RATIO, + DSIZE + }; + +public: + CImageApplyResize(); + + CImageApplyResize(ResizeType type, const cv::Size& size, double fx, double fy); + + virtual ~CImageApplyResize(void); + + virtual void apply(cv::Mat& pDib,int side); + + virtual void apply(std::vector& mats, bool isTwoSide); + + + double getFX() { return m_fx; } + + double getFY() { return m_fy; } + + cv::Size getDSize() { return m_dSize; } + + ResizeType getType() { return m_type; } + + void setFX(double value) { m_fx = value; } + + void setFY(double value) { m_fy = value; } + + void setDSize(const cv::Size& size) { m_dSize = size; } + + void setType(ResizeType type) { m_type = type; } + +private: + double m_fx; + double m_fy; + cv::Size m_dSize; + ResizeType m_type; +}; + +#endif // !IMAGE_APPLY_RESIZE_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplyRotation.cpp b/huagao/ImageProcess/ImageApplyRotation.cpp new file mode 100644 index 00000000..e82fe2d0 --- /dev/null +++ b/huagao/ImageProcess/ImageApplyRotation.cpp @@ -0,0 +1,128 @@ +#include "ImageApplyRotation.h" + +#define USE_TESSERCAT + +#ifdef USE_TESSERCAT +#define HG_OCR4_BUILD +#include "hg_ocr4.h" +#endif + +CImageApplyRotation::CImageApplyRotation(RotationType rotation, bool isBackTransposed, int dpi, const char* tessdataPath) + : m_rotation(rotation) + , m_backTranspose(isBackTransposed) + , m_dpi(dpi) + , osd(nullptr) +{ + if (rotation == RotationType::AutoTextOrientation) + { +#ifdef USE_TESSERCAT + osd = new HG_OCR4(); + reinterpret_cast(osd)->init(tessdataPath, HG_OCR4::Orientation); +#endif + } +} + +CImageApplyRotation::~CImageApplyRotation() +{ +#ifdef USE_TESSERCAT + if (osd) delete reinterpret_cast(osd); +#endif +} + +void CImageApplyRotation::apply(cv::Mat & pDib, int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplyRotation apply"); +#endif // LOG + if (pDib.empty()) + { +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyRotation apply"); +#endif // LOG + return; + } + + if (m_rotation == RotationType::AutoTextOrientation) //Զıʶ + { +#ifdef USE_TESSERCAT + if (osd) + { + cv::Mat temp; + if (m_dpi != 200) + { + double scale = 200 / static_cast(m_dpi); + cv::resize(pDib, temp, cv::Size(), scale, scale); + } + else + temp = pDib.clone(); + + if (temp.channels() == 3) + cv::cvtColor(temp, temp, cv::COLOR_BGR2GRAY); + cv::threshold(temp, temp, 180, 255, cv::THRESH_OTSU); + + HG_OCR4* ptr_osd = reinterpret_cast(osd); + int orientation = ptr_osd->getOrientation(temp.data, temp.cols, temp.rows, temp.channels(), temp.step); + + switch (orientation) + { + case 1: + transpose(pDib, pDib); + flip(pDib, pDib, 0); + break; + case 2: + flip(pDib, pDib, 0); + flip(pDib, pDib, 1); + break; + case 3: + transpose(pDib, pDib); + flip(pDib, pDib, 1); + break; + default: + break; + } + } +#endif + } + else if (m_backTranspose && side == 1) //ת180 + { + if (m_rotation != RotationType::Rotate_180) //ת180 + { + if (m_rotation == RotationType::Rotate_90_clockwise || m_rotation == RotationType::Rotate_90_anti_clockwise) //90 -90 + { + transpose(pDib, pDib); + flip(pDib, pDib, m_rotation == RotationType::Rotate_90_clockwise ? 0 : 1); + } + else + { + flip(pDib, pDib, 0); + flip(pDib, pDib, 1); + } + } + } + else //zh + { + if (m_rotation == RotationType::Rotate_90_clockwise || m_rotation == RotationType::Rotate_90_anti_clockwise) //90 -90 + { + transpose(pDib, pDib); + flip(pDib, pDib, m_rotation == RotationType::Rotate_90_clockwise ? 1 : 0); + } + else if (m_rotation == RotationType::Rotate_180) + { + flip(pDib, pDib, 0); + flip(pDib, pDib, 1); + } + } +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplyRotation apply"); +#endif // LOG +} + +void CImageApplyRotation::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} diff --git a/huagao/ImageProcess/ImageApplyRotation.h b/huagao/ImageProcess/ImageApplyRotation.h new file mode 100644 index 00000000..203c994e --- /dev/null +++ b/huagao/ImageProcess/ImageApplyRotation.h @@ -0,0 +1,49 @@ +#ifndef IMAGE_APPLY_ROTATION_H +#define IMAGE_APPLY_ROTATION_H + +#include "ImageApply.h" + +class CImageApplyRotation : public CImageApply +{ +public: + enum class RotationType + { + Invalid, + Rotate_90_clockwise, + Rotate_180, + Rotate_90_anti_clockwise, + + AutoTextOrientation + }; + +public: + + CImageApplyRotation(RotationType rotation, bool isBackTransposed = false, int dpi = 200, const char* tessdataPath = nullptr); + + virtual ~CImageApplyRotation(); + + virtual void apply(cv::Mat & pDib, int side) override; + + virtual void apply(std::vector& mats, bool isTwoSide); + + bool isBackTransposed() { return m_backTranspose; } + + int getDPI() { return m_dpi; } + + RotationType getRotationType() { return m_rotation; } + + void setBackTransposed(bool enabled) { m_backTranspose = enabled; } + + void setDPI(int dpi) { m_dpi = dpi; } + + void setRotationType(RotationType type) { m_rotation = type; } + +private: + RotationType m_rotation; + bool m_backTranspose; + int m_dpi; + + void* osd; +}; + +#endif // !IMAGE_APPLY_ROTATION_H \ No newline at end of file diff --git a/huagao/ImageProcess/ImageApplySharpen.cpp b/huagao/ImageProcess/ImageApplySharpen.cpp new file mode 100644 index 00000000..d847c34c --- /dev/null +++ b/huagao/ImageProcess/ImageApplySharpen.cpp @@ -0,0 +1,36 @@ +#include "ImageApplySharpen.h" + +CImageApplySharpen::CImageApplySharpen() + : kernel(5, 5, CV_32FC1) +{ + float kernel_data[] = { -0.1f, 0, 0, 0, -0.1f, 0, 0, 0, 0, 0, 0, 0, 1.5f, 0, 0, 0, 0, 0, 0, 0, -0.1f, 0, 0, 0, -0.1f }; + memcpy(kernel.data, kernel_data, sizeof(float) * 25); +} + +CImageApplySharpen::~CImageApplySharpen() +{ +} + +void CImageApplySharpen::apply(cv::Mat & pDib, int side) +{ +#ifdef LOG + FileTools::write_log("imgprc.txt", "enter CImageApplySharpen apply"); +#endif // LOG + + if (pDib.empty()) return; + + cv::filter2D(pDib, pDib, pDib.depth(), kernel); +#ifdef LOG + FileTools::write_log("imgprc.txt", "exit CImageApplySharpen apply"); +#endif // LOG +} + +void CImageApplySharpen::apply(std::vector& mats, bool isTwoSide) +{ + if (mats.empty()) return; + + apply(mats[0], 0); + + if (isTwoSide && mats.size() > 1) + apply(mats[1], 1); +} diff --git a/huagao/ImageProcess/ImageApplySharpen.h b/huagao/ImageProcess/ImageApplySharpen.h new file mode 100644 index 00000000..5a2de22c --- /dev/null +++ b/huagao/ImageProcess/ImageApplySharpen.h @@ -0,0 +1,20 @@ +#ifndef IMAGE_APPLY_SHARPEN_H +#define IMAGE_APPLY_SHARPEN_H + +#include "ImageApply.h" + +class CImageApplySharpen : public CImageApply +{ +public: + CImageApplySharpen(); + + virtual ~CImageApplySharpen(); + + virtual void apply(cv::Mat& pDib, int side); + + virtual void apply(std::vector& mats, bool isTwoSide); +private: + cv::Mat kernel; +}; + +#endif // !IMAGE_APPLY_SHARPEN_H diff --git a/huagao/ImageProcess/ImageProcess_Public.cpp b/huagao/ImageProcess/ImageProcess_Public.cpp new file mode 100644 index 00000000..9634693f --- /dev/null +++ b/huagao/ImageProcess/ImageProcess_Public.cpp @@ -0,0 +1,309 @@ +#include "ImageProcess_Public.h" + +namespace hg +{ + void convexHull(const std::vector& src, std::vector& dst, bool clockwise) + { + CvMemStorage* storage = cvCreateMemStorage(); // + CvSeq* ptseq = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2, sizeof(CvContour), sizeof(CvPoint), storage); //ptseqstorage + + // + for (const cv::Point& item : src) + { + CvPoint p; + p.x = item.x; + p.y = item.y; + cvSeqPush(ptseq, &p); + } + + //hullstorage + CvSeq* hull = cvConvexHull2(ptseq, nullptr, clockwise ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE, 0); + + //dst + dst.clear(); + int hullCount = hull->total; + for (int i = 0; i < hullCount; i++) + dst.push_back(**CV_GET_SEQ_ELEM(CvPoint*, hull, i)); + + //storage + cvReleaseMemStorage(&storage); + } + +#define R_COLOR 255 + void fillConvexHull(cv::Mat& image, const std::vector& points) + { + uint index_top = 0; + uint index_bottom = 0; + for (size_t i = 0, length = points.size(); i < length; i++) + { + if (points[i].y < points[index_top].y) + index_top = i; + if (points[i].y > points[index_bottom].y) + index_bottom = i; + } + + std::vector edge_left; + uint temp = index_top; + while (temp != index_bottom) + { + edge_left.push_back(points[temp]); + temp = (temp + points.size() - 1) % points.size(); + } + edge_left.push_back(points[index_bottom]); + + std::vector edge_right; + temp = index_top; + while (temp != index_bottom) + { + edge_right.push_back(points[temp]); + temp = (temp + points.size() + 1) % points.size(); + } + edge_right.push_back(points[index_bottom]); + + std::vector left_edge_x; + std::vector left_edge_y; + for (size_t i = 0, length = edge_left.size() - 1; i < length; i++) + { + int y_top = edge_left[i].y; + int x_top = edge_left[i].x; + int y_bottom = edge_left[i + 1].y; + int x_bottom = edge_left[i + 1].x; + for (int y = y_top; y < y_bottom; y++) + if (y >= 0 && y_top != y_bottom && y < image.rows) + { + left_edge_x.push_back(((x_bottom - x_top) * y + x_top * y_bottom - x_bottom * y_top) / (y_bottom - y_top)); + left_edge_y.push_back(y); + } + } + size_t step = image.step; + unsigned char* ptr; + ptr = image.data + static_cast(left_edge_y[0]) * step; + for (size_t i = 0, length = left_edge_x.size(); i < length; i++) + { + int pix = left_edge_x[i]; + if (pix < image.cols - 1 && pix > 0) + memset(ptr + i * step, R_COLOR, static_cast((pix + 1) * image.channels())); + } + + std::vector right_edge_x; + std::vector right_edge_y; + for (size_t i = 0, length = edge_right.size() - 1; i < length; i++) + { + int y_top = edge_right[i].y; + int x_top = edge_right[i].x; + int y_bottom = edge_right[i + 1].y; + int x_bottom = edge_right[i + 1].x; + for (int y = y_top; y < y_bottom; y++) + if (y_top != y_bottom && y < image.rows && y >= 0) + { + right_edge_x.push_back(((x_bottom - x_top) * y + x_top * y_bottom - x_bottom * y_top) / (y_bottom - y_top)); + right_edge_y.push_back(y); + } + } + + ptr = image.data + static_cast(right_edge_y[0]) * step; + for (size_t i = 0, length = right_edge_x.size(); i < length; i++) + { + int pix = right_edge_x[i]; + if (pix < image.cols - 1 && pix > 0) + memset(ptr + i * step + pix * image.channels(), R_COLOR, step - static_cast(pix * image.channels())); + } + + if (edge_left[0].y > 0) + memset(image.data, R_COLOR, static_cast(edge_left[0].y) * step); + + if (edge_left.back().y < image.rows - 1) + memset(image.data + static_cast(edge_left.back().y) * step, R_COLOR, + static_cast(image.rows - edge_left.back().y) * step); + } + + void fillPolys(cv::Mat& image, const std::vector>& contours, const cv::Scalar& color) + { + if (contours.empty()) return; + + size_t count = contours.size(); + cv::Point** pointss = new cv::Point*[count]; + int* npts = new int[count]; + + for (size_t i = 0; i < count; i++) + { + size_t length = contours[i].size(); + npts[i] = length; + pointss[i] = new cv::Point[length]; + for (size_t j = 0; j < length; j++) + pointss[i][j] = contours[i][j]; + } + cv::fillPoly(image, const_cast(pointss), npts, count, color); + + for (size_t i = 0; i < count; i++) + delete[] pointss[i]; + + delete[] pointss; + delete[] npts; + } + + void findContours(const cv::Mat& src, std::vector>& contours, std::vector& hierarchy, int retr, int method, cv::Point offset) + { + CvMat c_image = src; + cv::MemStorage storage(cvCreateMemStorage()); + CvSeq* _ccontours = nullptr; + cvFindContours(&c_image, storage, &_ccontours, sizeof(CvContour), retr, method, CvPoint(offset)); + + if (!_ccontours) + { + contours.clear(); + return; + } + cv::Seq all_contours(cvTreeToNodeSeq(_ccontours, sizeof(CvSeq), storage)); + size_t total = all_contours.size(); + contours.resize(total); + + cv::SeqIterator it = all_contours.begin(); + for (size_t i = 0; i < total; i++, ++it) + { + CvSeq* c = *it; + reinterpret_cast(c)->color = static_cast(i); + int count = c->total; + int* data = new int[static_cast(count * 2)]; + cvCvtSeqToArray(c, data); + for (int j = 0; j < count; j++) + { + contours[i].push_back(cv::Point(data[j * 2], data[j * 2 + 1])); + } + delete[] data; + } + + hierarchy.resize(total); + it = all_contours.begin(); + for (size_t i = 0; i < total; i++, ++it) + { + CvSeq* c = *it; + int h_next = c->h_next ? reinterpret_cast(c->h_next)->color : -1; + int h_prev = c->h_prev ? reinterpret_cast(c->h_prev)->color : -1; + int v_next = c->v_next ? reinterpret_cast(c->v_next)->color : -1; + int v_prev = c->v_prev ? reinterpret_cast(c->v_prev)->color : -1; + hierarchy[i] = cv::Vec4i(h_next, h_prev, v_next, v_prev); + } + + storage.release(); + } + + cv::RotatedRect getBoundingRect(const std::vector& contour) + { + if (contour.empty()) return {}; + + cv::RotatedRect rect = minAreaRect(contour); + if (rect.angle < -45) + { + rect.angle += 90; + float temp = rect.size.width; + rect.size.width = rect.size.height; + rect.size.height = temp; + } + + return rect; + } + + std::vector getMaxContour(const std::vector>& contours, const std::vector& hierarchy) + { + std::vector maxContour; + if (contours.size() < 1) return {}; + + for (size_t i = 0, length = hierarchy.size(); i < length; i++) + if (hierarchy[i][3] == -1) + for (const auto &item : contours[i]) + maxContour.push_back(item); + + return maxContour; + } + + std::vector getVertices(const cv::RotatedRect& rect) + { + cv::Point2f box[4]; + rect.points(box); + std::vector points; + for (int i = 0; i < 4; i++) + points.push_back(cv::Point(box[i])); + + return points; + } + + void polyIndent(std::vector& points, const cv::Point& center, int indent) + { + static cv::Point zero(0, 0); + for (cv::Point& item : points) + { +#if 0 + cv::Point vec = item - center; + if (vec != zero) + { + int length = vec.x * vec.x + vec.y * vec.y; + float x = cv::sqrt(static_cast(vec.x * vec.x / length)) * indent; + float y = cv::sqrt(static_cast(vec.y * vec.y / length)) * indent; + + if (vec.x < 0) x *= -1.0f; + if (vec.y < 0) y *= -1.0f; + + item.x -= static_cast(x); + item.y -= static_cast(y); + } +#else + if (item.x > center.x) + item.x -= indent; + else + item.x += indent; + + if (item.y > center.y) + item.y -= indent; + else + item.y += indent; +#endif + } + } + + cv::Mat transforColor(const cv::Mat& src) + { + if (src.channels() == 1) return src.clone(); + + std::vector channels(3); + cv::split(src, channels); + + cv::Mat temp, dst; + bitwise_or(channels[0], channels[1], temp); + bitwise_or(channels[2], temp, dst); + temp.release(); + + for (cv::Mat& index : channels) + index.release(); + return dst; + } + + void threshold_Mat(const cv::Mat& src, cv::Mat& dst, double thre) + { + if (src.channels() == 3) + { +#ifdef USE_ONENCL + if (cl_res.context) + transforColor_threshold_opencl(src, dst, static_cast(thre)); + else +#endif + { + cv::Mat gray = transforColor(src); + cv::threshold(gray, dst, thre, 255, cv::THRESH_BINARY); + gray.release(); + } + } + else + cv::threshold(src, dst, thre, 255, cv::THRESH_BINARY); + } + + cv::Point warpPoint(cv::Point p, const cv::Mat& warp_mat) + { + double src_data[3] = { static_cast(p.x), static_cast(p.y), 1 }; + cv::Mat src(3, 1, warp_mat.type(), src_data); //warp_mat.type() == CV_64FC1 + + cv::Mat dst = warp_mat * src; + double* ptr = reinterpret_cast(dst.data); + return cv::Point(static_cast(ptr[0]), static_cast(ptr[1])); + } +} \ No newline at end of file diff --git a/huagao/ImageProcess/ImageProcess_Public.h b/huagao/ImageProcess/ImageProcess_Public.h new file mode 100644 index 00000000..db792cfd --- /dev/null +++ b/huagao/ImageProcess/ImageProcess_Public.h @@ -0,0 +1,33 @@ +#ifndef IMAGE_PROCESS_PUBLIC_H +#define IMAGE_PROCESS_PUBLIC_H + +#include "opencv2/opencv.hpp" +#include + +namespace hg +{ + void convexHull(const std::vector& src, std::vector& dst, bool clockwise = false); + + void fillConvexHull(cv::Mat& image, const std::vector& points); + + void fillPolys(cv::Mat& image, const std::vector>& contours, const cv::Scalar& color); + + void findContours(const cv::Mat& src, std::vector>& contours, std::vector& hierarchy, + int retr = cv::RETR_LIST, int method = cv::CHAIN_APPROX_SIMPLE, cv::Point offset = cv::Point(0, 0)); + + cv::RotatedRect getBoundingRect(const std::vector& contour); + + std::vector getMaxContour(const std::vector>& contours, const std::vector& hierarchy); + + std::vector getVertices(const cv::RotatedRect& rect); + + void polyIndent(std::vector& points, const cv::Point& center, int indent); + + void threshold_Mat(const cv::Mat& src, cv::Mat& dst, double thre); + + cv::Mat transforColor(const cv::Mat& src); + + cv::Point warpPoint(cv::Point p, const cv::Mat& warp_mat); +} + +#endif // !IMAGE_PROCESS_C_H diff --git a/huagao/Scan2411.jpg b/huagao/Scan2411.jpg new file mode 100644 index 00000000..690eecc0 Binary files /dev/null and b/huagao/Scan2411.jpg differ diff --git a/huagao/Sliders.cpp b/huagao/Sliders.cpp new file mode 100644 index 00000000..76cff710 --- /dev/null +++ b/huagao/Sliders.cpp @@ -0,0 +1,123 @@ +// +// Sliders.cpp - the slider subclassing module +// +/////////////////////////////////////////////////////////////////// +// +// Copyright (C) 1998 Rick York - Feel free to use this as +// you wish provided that this notice remains intact and +// a small credit is given (like in an about box :). +// +// This class is used to link a slider with an edit box +// for coordinated updates. +// +/////////////////////////////////////////////////////////////////// +// +//@tabs=4 + +#include "Stdafx.h" +#include "Sliders.h" +#include "SmartEdit.h" + + +#ifdef _DEBUG +#define new DEBUG_NEW +#endif + + +AfxApi CLinkSlider * GetLinkSlider( CWnd *pcwnd, int id ) +{ + return (CLinkSlider *)pcwnd->GetDlgItem( id ); +} + + +/////////////////////////////////////////////////////////// + + +BEGIN_MESSAGE_MAP(CLinkSlider, CSliderCtrl) + //{{AFX_MSG_MAP(CLinkSlider) + ON_WM_HSCROLL_REFLECT() + ON_WM_VSCROLL_REFLECT() + //}}AFX_MSG_MAP +END_MESSAGE_MAP() + + +CLinkSlider::CLinkSlider() : CSliderCtrl() +{ + m_pEdit = NULL; + m_iPosition = INT_MAX; + m_bVertical = FALSE; +} + + +void CLinkSlider::SetEditLink( CSmartEdit *pedit ) +{ + m_pEdit = pedit; + DWORD style = GetStyle(); + if( style & TBS_VERT ) + m_bVertical = TRUE; +} + + +void CLinkSlider::SetSlidePos( const int pos ) +{ + if( m_bVertical ) + m_iPosition = m_iMax - ( pos - m_iMin ); + else + m_iPosition = pos; + + SetPos( m_iPosition ); +} + + +void CLinkSlider::SetSlideRange( const int imin, const int imax ) +{ + m_iMin = imin; + m_iMax = imax; + SetRange( m_iMin, m_iMax ); +} + + +void CLinkSlider::HScroll( UINT ncode, UINT pos ) +{ + CSliderCtrl::OnHScroll( ncode, pos, NULL ); + if( ! m_pEdit ) + return; + + switch( ncode ) + { + case TB_PAGEUP : + case TB_PAGEDOWN : + m_iPosition = GetPos(); + m_pEdit->UpdateEdit( m_iPosition ); + break; + + case TB_THUMBTRACK : + m_iPosition = pos; + m_pEdit->UpdateEdit( pos ); + break; + } +} + + +void CLinkSlider::VScroll( UINT ncode, UINT pos ) +{ + CSliderCtrl::OnVScroll( ncode, pos, NULL ); + if( ! m_pEdit ) + return; + + switch( ncode ) + { + // we have to play some games with vertical sliders - + // max position is on the bottom and min is on the top + + case TB_PAGEUP : + case TB_PAGEDOWN : + m_iPosition = m_iMax - ( GetPos() - m_iMin ); + m_pEdit->UpdateEdit( m_iPosition ); + break; + + case TB_THUMBTRACK : + m_iPosition = m_iMax - ( pos - m_iMin ); + m_pEdit->UpdateEdit( m_iPosition ); + } +} diff --git a/huagao/Sliders.h b/huagao/Sliders.h new file mode 100644 index 00000000..137c2da5 --- /dev/null +++ b/huagao/Sliders.h @@ -0,0 +1,75 @@ +// +// Sliders.h - header for slider subclassing module +// +/////////////////////////////////////////////////////////////////// +// +// Copyright (C) 1998 Rick York - Feel free to use this as +// you wish provided that this notice remains intact and +// a small credit is given (like in an about box :). +// +// This class is used to link a slider with an edit box +// for coordinated updates. +// +/////////////////////////////////////////////////////////////////// +// +//@tabs=4 + +//#ifdef _SLIDERS_H +//#error repeated include of this file +//#else // _SLIDERS_H +//#define _SLIDERS_H +//#endif // _SLIDERS_H +#pragma once + + +#ifndef __cplusplus +#error this is file may be used in C++ only +#endif + + +#ifndef AfxExt + +#ifdef EXTENSION_DLL // define this if controls are in a DLL +#define AfxExt AFX_EXT_CLASS +#define AfxApi AFX_EXT_API +#else // EXTENSION_DLL +#define AfxExt // controls are NOT in a DLL +#define AfxApi +#endif // EXTENSION_DLL + +#endif // AfxExt + + +class AfxExt CSmartEdit; + + +class AfxExt CLinkSlider : public CSliderCtrl +{ +public: + // Construction + CLinkSlider(); + + CSmartEdit * m_pEdit; + + int m_iMin; + int m_iMax; + int m_iPosition; + BOOL m_bVertical; + + void SetSlidePos( const int pos ); + void SetSlideRange( const int min, const int max ); + + void SetEditLink( CSmartEdit *pedit ); + + // Implementation +protected: + //{{AFX_MSG(CLinkSlider) + afx_msg void HScroll( UINT ncode, UINT pos ); + afx_msg void VScroll( UINT ncode, UINT pos ); + //}}AFX_MSG + + DECLARE_MESSAGE_MAP() +}; + + +AfxApi CLinkSlider * GetLinkSlider( CWnd *pcwnd, int id ); diff --git a/huagao/SmartEdit.cpp b/huagao/SmartEdit.cpp new file mode 100644 index 00000000..55a7698b --- /dev/null +++ b/huagao/SmartEdit.cpp @@ -0,0 +1,325 @@ +// +// SmartEdit.cpp - the smart edit control module +// +/////////////////////////////////////////////////////////////////// +// +// This is a part of the Microsoft Foundation Classes C++ library. +// Copyright (C) 1992-1997 Microsoft Corporation +// All rights reserved. +// +// This source code is only intended as a supplement to the +// Microsoft Foundation Classes Reference and related +// electronic documentation provided with the library. +// See these sources for detailed information regarding the +// Microsoft Foundation Classes product. +// +/////////////////////////////////////////////////////////////////// +// +// Copyright (C) 1998 Rick York - Feel free to use this as +// you wish provided that these notices remain intact and +// a small credit is given (like in an about box :). +// +// This began life as part of the CTRLTEST sample from the +// MSDN disks and was called CParsedEdit. I have changed +// its name to reflect its enhanced functionality which +// includes support for more input types : floating point, +// underscore, and negative sign; and linking with a slider +// for coordinated updates. +// +// NOTE : I have attempted to make this Unicode compatable +// but I have not tested on a MBCS so I can't make +// any guarantees. Please notify me of any problems +// (or any successes) at ry@proaxis.com +// +/////////////////////////////////////////////////////////////////// +// +//@tabs=4 + +#include "Stdafx.h" +#include "SmartEdit.h" +#include "Sliders.h" + + +#ifdef _DEBUG +#define new DEBUG_NEW +#endif + + +AfxApi CSmartEdit * GetSmartEdit( CWnd *pcwnd, int id ) +{ + return (CSmartEdit *)pcwnd->GetDlgItem( id ); +} + + +/////////////////////////////////////////////////////////// +// CSmartEdit implementation + +BEGIN_MESSAGE_MAP(CSmartEdit, CEdit) +//{{AFX_MSG_MAP(CSmartEdit) +ON_WM_CHAR() +ON_CONTROL_REFLECT(EN_UPDATE, OnUpdate) +//}}AFX_MSG_MAP +END_MESSAGE_MAP() + + +CSmartEdit::CSmartEdit() +{ + m_wParseType = SES_ALL; + m_pSlider = NULL; + m_iValue = INT_MIN; + m_bUseFp = FALSE; +} + + +CSmartEdit::~CSmartEdit() +{ +} + + +int CSmartEdit::SetParseType( WORD type ) +{ + m_wParseType = type; + return type; +} + + +// Aliasing on top of an existing Edit control + +BOOL CSmartEdit::SubclassEdit( UINT nID, CWnd* pParent, WORD wParseStyle ) +{ + SetParseType( wParseStyle ); + return SubclassDlgItem( nID, pParent ); +} + + +// Input character filter + +void CSmartEdit::OnChar( UINT nChar, UINT nRepCnt, UINT nFlags ) +{ + WORD type = SES_OTHERCHARS; // default + int alpha = IsCharAlpha( (TCHAR)nChar ); + int number = IsCharAlphaNumeric( (TCHAR)nChar ) && ! alpha; + + if( nChar < 0x20 ) + type = SES_ALL; // always allow control chars ??? + else if( number ) + type = SES_NUMBERS | SES_SIGNED | SES_FLOATINGPT | SES_HEXADECIMAL; + else if( alpha ) + { + type = SES_LETTERS; + int uprval = toupper( (TCHAR)nChar ); + if( uprval == 'E' ) + type |= ( SES_FLOATINGPT | SES_HEXADECIMAL ); + else if( uprval == 'X' ) + type |= SES_HEXADECIMAL; + else if( ( uprval >= 'A' ) && ( uprval <= 'F' ) ) + type |= SES_HEXADECIMAL; + } + else if( (TCHAR)nChar == '-' ) // dash + type = SES_SIGNED | SES_FLOATINGPT; + else if( (TCHAR)nChar == '.' ) // dot + type = SES_FLOATINGPT; + else if( (TCHAR)nChar == '_' ) // underscore + type = SES_UNDERSCORE | SES_OTHERCHARS; + + if( m_wParseType & type ) + { + CEdit::OnChar(nChar, nRepCnt, nFlags); // permitted + } + else + { + // illegal character - inform parent + OnBadInput(); + } +} + + + +// This is the default response to bad input. +// This is virtual so it may be overridden. + +void CSmartEdit::OnBadInput() +{ + MessageBeep((UINT)-1); +} + + +///////////////////////////////////////////////////////////// +// The following code is used when an edit box is linked +// with a slider for coordinated updates. If you do not +// want this functionality remove this code from here and +// in the header. + +void CSmartEdit::OnUpdate() +{ + if( ! m_pSlider ) + return; + + TCHAR buf[512]; + GetWindowText( buf, sizeof( buf ) / sizeof(TCHAR) ); + + int error = TRUE; + if( m_bUseFp ) + { + m_dValue = _tstof( buf ); + if( m_dValue < m_dMin ) + { + m_dValue = m_dMin; + OnBadInput(); + } + else if( m_dValue > m_dMax ) + { + m_dValue = m_dMax; + OnBadInput(); + } + else + error = FALSE; + + // scale to integer + + double dpos = ( m_dValue - m_dMin ) * (double)m_iRange / m_dRange; + m_iValue = (int)dpos; + } + else + { + m_iValue = _tstoi( buf ); + if( m_iValue < m_iMin ) + { + m_iValue = m_iMin; + OnBadInput(); + } + else if( m_iValue > m_iMax ) + { + m_iValue = m_iMax; + OnBadInput(); + } + else + error = FALSE; + } + + if( m_pSlider ) + m_pSlider->SetSlidePos( m_iValue ); + + if( error ) + { + int posn = m_iValue; + m_iValue = INT_MIN; + UpdateEdit( posn ); + } +} + + +int CSmartEdit::UpdateEdit( int position ) +{ + CString buffer; + + if( position == m_iValue ) + return FALSE; // been here already + + m_iValue = position; + if( m_bUseFp ) + { + // scale to double value + m_dValue = m_dMin + (double)m_iValue * m_dRange / 1000.0; + buffer.Format(m_pFormat, m_dValue); + } + else + buffer.Format(_T("%d"), m_iValue ); + + SetWindowText( buffer ); + return TRUE; +} + + +void CSmartEdit::SetSlideLink( CWnd *pParent, int sliderid ) +{ + m_pSlider = (CLinkSlider *)pParent->GetDlgItem( sliderid ); + ASSERT( m_pSlider ); + m_pSlider->SetEditLink( this ); +} + + +int CSmartEdit::InitSlider() +{ + if( ! m_pSlider ) + return FALSE; + m_pSlider->SetEditLink( this ); + + m_iRange = m_iMax - m_iMin; + m_pSlider->SetSlideRange(m_iMin, m_iMax); + int freq = m_iRange / m_iBands; + m_pSlider->SetTicFreq(freq); + + return TRUE; +} + + +void CSmartEdit::SetFormatString( CString fmtstring ) +{ + m_pFormat = fmtstring; +} + + +int CSmartEdit::SetParams( cint imin, cint imax, cint ticbands ) +{ + m_bUseFp = FALSE; + m_iBands = ticbands; + m_iMin = imin; + m_iMax = imax; + InitSlider(); + SetFormatString( _T("%d") ); + WORD type = SES_NUMBERS; + if( imin < 0 ) + type |= SES_SIGNED; + SetParseType( type ); + return TRUE; +} + + +int CSmartEdit::SetParams( cdbl dmin, cdbl dmax, + cint ticbands, CString fmtstring ) +{ + m_bUseFp = TRUE; + m_iBands = ticbands; + m_dRange = dmax - dmin; + m_dMin = dmin; + m_dMax = dmax; + m_iMin = 0; + m_iMax = 1000; + + InitSlider(); + SetFormatString( fmtstring ); + SetParseType( SES_FLOATINGPT ); + return TRUE; +} + + +int CSmartEdit::SetValue( cint ivalue ) +{ + if( m_bUseFp ) + return FALSE; + + if( ( ivalue < m_iMin ) || ( ivalue > m_iMax ) ) + return FALSE; + + CString buf; + buf.Format(m_pFormat, ivalue); + SetWindowText( buf ); + return TRUE; +} + + +int CSmartEdit::SetValue( cdbl dvalue ) +{ + if( ! m_bUseFp ) + return FALSE; + + if( ( dvalue < m_dMin ) || ( dvalue > m_dMax ) ) + return FALSE; + + CString buf; + buf.Format(m_pFormat, dvalue ); + SetWindowText( buf ); + return TRUE; +} + diff --git a/huagao/SmartEdit.h b/huagao/SmartEdit.h new file mode 100644 index 00000000..b542ae54 --- /dev/null +++ b/huagao/SmartEdit.h @@ -0,0 +1,144 @@ +// +// SmartEdit.h - CSmartEdit is a specialized CEdit control +// that only allows characters of a given type. +// Available types are defined below. +// +/////////////////////////////////////////////////////////////////// +// +// This is a part of the Microsoft Foundation Classes C++ library. +// Copyright (C) 1992-1997 Microsoft Corporation +// All rights reserved. +// +// This source code is only intended as a supplement to the +// Microsoft Foundation Classes Reference and related +// electronic documentation provided with the library. +// See these sources for detailed information regarding the +// Microsoft Foundation Classes product. +// +/////////////////////////////////////////////////////////////////// +// +// Copyright (C) 1998 Rick York - Feel free to use this as +// you wish provided that these notices remain intact and +// a small credit is given (like in an about box ;). +// +// This began life as part of the CTRLTEST sample from the +// MSDN disks and was called CParsedEdit. I have changed +// its name to reflect its enhanced functionality which +// includes support for more input types : floating point, +// underscore, and negative sign; and linking with a slider +// for coordinated updates. +// +/////////////////////////////////////////////////////////////////// +// +//@tabs=4 + +#pragma once +//#ifdef _SMARTEDIT_H +//#error repeated include of this file +//#else // _SMARTEDIT_H +//#define _SMARTEDIT_H +//#endif // _SMARTEDIT_H + + +#ifndef __cplusplus +#error this is file may be used in C++ only +#endif + + + // smart edit control sub-styles + +#define SES_NUMBERS 0x0001 // no negative sign allowed +#define SES_LETTERS 0x0002 // also upper and lower case +#define SES_FLOATINGPT 0x0004 // allows '-', '.', and 'E' +#define SES_OTHERCHARS 0x0008 // allows punctuation +#define SES_SIGNED 0x0010 // allows negative sign also +#define SES_UNDERSCORE 0x0020 // allows the underscore +#define SES_HEXADECIMAL 0x0040 // allows hex chars (0-9,A-F,X) +#define SES_ALL 0xFFFF // anything goes + + // define some constant data types + +typedef const int cint; +typedef const double cdbl; + + +#ifndef AfxExt + +#ifdef EXTENSION_DLL // define this if controls are in a DLL +#define AfxExt AFX_EXT_CLASS +#define AfxApi AFX_EXT_API +#else // EXTENSION_DLL +#define AfxExt // controls are NOT in a DLL +#define AfxApi +#endif // EXTENSION_DLL + +#endif // AfxExt + + +class AfxExt CLinkSlider; // a specialized slider control + + +class AfxExt CSmartEdit : public CEdit +{ +private: + WORD m_wParseType; + +protected: + // Overridables + virtual void OnBadInput(); + +public: + CSmartEdit(); + virtual ~CSmartEdit(); + + int SetParseType( WORD type ); + BOOL SubclassEdit( UINT nID, CWnd* pParent, + WORD wParseStyle ); + +///////////////////////////////////////////////////////////// +// code for linking with a slider + + // link the slider and edit control first + + void SetSlideLink( CWnd *pParent, int sliderid ); + + int SetParams( cint imin, cint imax, cint ticbands ); + int SetParams( cdbl dmin, cdbl dmax, + cint tbands, CString fmtstring ); + + int SetValue( cint ivalue ); + int SetValue( cdbl dvalue ); + int UpdateEdit( cint position ); + + void SetFormatString( CString fmtstring ); + +private : + int InitSlider(); + + // Implementation + +private: + CLinkSlider * m_pSlider; + + CString m_pFormat; + int m_iTextId; + int m_iSliderId; + int m_iBands; + BOOL m_bUseFp; + int m_iMin, m_iMax, m_iValue, m_iRange; + double m_dMin, m_dMax, m_dValue, m_dRange; + +// end of code for linking with a slider +///////////////////////////////////////////////////////////// + +protected: + //{{AFX_MSG(CSmartEdit) + afx_msg void OnChar(UINT, UINT, UINT); + afx_msg void OnUpdate(); // used with a linked slider + //}}AFX_MSG + + DECLARE_MESSAGE_MAP() +}; + + +AfxApi CSmartEdit * GetSmartEdit( CWnd *pcwnd, int id ); diff --git a/huagao/TabCtrlSSL.cpp b/huagao/TabCtrlSSL.cpp new file mode 100644 index 00000000..487423f0 --- /dev/null +++ b/huagao/TabCtrlSSL.cpp @@ -0,0 +1,496 @@ +// TabCtrlSSL.cpp : implementation file +// + +#include "stdafx.h" +#include "TabCtrlSSL.h" + +#ifdef _DEBUG +#define new DEBUG_NEW +#undef THIS_FILE +static char THIS_FILE[] = __FILE__; +#endif + +///////////////////////////////////////////////////////////////////////////// +// Construction + +CTabCtrlSSL::CTabCtrlSSL () { +#ifndef _AFX_NO_OCC_SUPPORT + AfxEnableControlContainer (); +#endif // !_AFX_NO_OCC_SUPPORT +} + +///////////////////////////////////////////////////////////////////////////// +// Destruction + +CTabCtrlSSL::~CTabCtrlSSL (void) { +} + +BEGIN_MESSAGE_MAP(CTabCtrlSSL, CTabCtrl) + //{{AFX_MSG_MAP(CTabCtrlSSL) + ON_WM_DESTROY () + ON_WM_SETFOCUS () + ON_WM_KILLFOCUS () + ON_NOTIFY_REFLECT (TCN_SELCHANGING, OnSelChanging) + ON_NOTIFY_REFLECT (TCN_SELCHANGE, OnSelChange) + //}}AFX_MSG_MAP +END_MESSAGE_MAP() + +///////////////////////////////////////////////////////////////////////////// +// Page Functions + +int CTabCtrlSSL::AddSSLPage (LPCTSTR pszTitle, int nPageID, CTabPageSSL* pTabPage) { + // Add a page to the tab control. + TabDelete tabDelete; + tabDelete.pTabPage = pTabPage; + tabDelete.bDelete = FALSE; + + return AddPage (pszTitle, nPageID, tabDelete); +} + +int CTabCtrlSSL::AddSSLPage (LPCTSTR pszTitle, int nPageID, LPCTSTR pszTemplateName) { + // Verify that the dialog template is compatible with CTabCtrlSSL + // (debug builds only). If your app asserts here, make sure the dialog + // resource you're adding to the view is a borderless child window and + // is not marked visible. +#ifdef _DEBUG + if (pszTemplateName != NULL) { + BOOL bResult = CheckDialogTemplate (pszTemplateName); + ASSERT (bResult); + } +#endif // _DEBUG + + // Add a page to the tab control. + // Create a modeless dialog box. + CTabPageSSL* pDialog = new CTabPageSSL; + + if (pDialog == NULL) { + return -1; + } + + if (!pDialog->Create (pszTemplateName, this)) { + pDialog->DestroyWindow (); + delete pDialog; + return -1; + } + + TabDelete tabDelete; + tabDelete.pTabPage = pDialog; + tabDelete.bDelete = TRUE; + + return AddPage (pszTitle, nPageID, tabDelete); +} + +int CTabCtrlSSL::AddSSLPage (LPCTSTR pszTitle, int nPageID, int nTemplateID) { + return AddSSLPage (pszTitle, nPageID, MAKEINTRESOURCE (nTemplateID)); +} + +BOOL CTabCtrlSSL::RemoveSSLPage (int nIndex) { + if (nIndex >= GetItemCount ()) + return FALSE; + + // Notify derived classes that the page is being destroyed. + OnDestroyPage (nIndex, m_nPageIDs[nIndex]); + + // Switch pages if the page being deleted is the current page and it's + // not the only remaining page. + int nCount = GetItemCount (); + if (nCount > 1 && nIndex == GetCurSel ()) { + int nPage = nIndex + 1; + if (nPage >= nCount) + nPage = nCount - 2; + ActivateSSLPage (nPage); + } + + // Remove the page from the tab control. + DeleteItem (nIndex); + + // Destroy the dialog (if any) that represents the page. + TabDelete tabDelete = m_tabs[nIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + if (pDialog != NULL) { + pDialog->DestroyWindow (); + delete pDialog; + } + + // Clean up, repaint, and return. + m_tabs.RemoveAt (nIndex); + m_hFocusWnd.RemoveAt (nIndex); + m_nPageIDs.RemoveAt (nIndex); + Invalidate (); + return TRUE; +} + +int CTabCtrlSSL::GetSSLPageCount (void) { + return GetItemCount (); +} + +BOOL CTabCtrlSSL::GetSSLPageTitle (int nIndex, CString &strTitle) { + if (nIndex >= GetItemCount ()) + return FALSE; + + TCHAR szTitle[1024]; + + TC_ITEM item; + item.mask = TCIF_TEXT; + item.pszText = szTitle; + item.cchTextMax = sizeof szTitle / sizeof (TCHAR); + + if (!GetItem (nIndex, &item)) + return FALSE; + + strTitle = item.pszText; + return TRUE; +} + +BOOL CTabCtrlSSL::SetSSLPageTitle (int nIndex, LPCTSTR pszTitle) { + if (nIndex >= GetItemCount ()) + return FALSE; + + TC_ITEM item; + item.mask = TCIF_TEXT; + item.pszText = (LPTSTR) pszTitle; + + BOOL bResult = SetItem (nIndex, &item); + if (bResult) + Invalidate (); + return bResult; +} + +int CTabCtrlSSL::GetSSLPageID (int nIndex) { + if (nIndex >= GetItemCount ()) + return -1; + + return m_nPageIDs[nIndex]; +} + +int CTabCtrlSSL::SetSSLPageID (int nIndex, int nPageID) { + if (nIndex >= GetItemCount ()) + return -1; + + int nOldPageID = m_nPageIDs[nIndex]; + m_nPageIDs[nIndex] = nPageID; + return nOldPageID; +} + +BOOL CTabCtrlSSL::ActivateSSLPage (int nIndex) { + if (nIndex >= GetItemCount ()) + return FALSE; + + // Do nothing if the specified page is already active. + if (nIndex == GetCurSel ()) + return TRUE; + + // Deactivate the current page. + int nOldIndex = GetCurSel (); + + if (nIndex != -1) { + TabDelete tabDelete = m_tabs[nOldIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + if (pDialog != NULL) { + m_hFocusWnd[nOldIndex] = ::GetFocus (); + pDialog->ShowWindow (SW_HIDE); + } + } + + // Activate the new one. + SetCurSel (nIndex); + TabDelete tabDelete = m_tabs[nIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + + if (pDialog != NULL) { + ::SetFocus (m_hFocusWnd[nIndex]); + CRect rect; + GetClientRect (&rect); + ResizeDialog (nIndex, rect.Width (), rect.Height ()); + pDialog->ShowWindow (SW_SHOW); + } + return TRUE; +} + +int CTabCtrlSSL::GetSSLActivePage (void) { + return GetCurSel (); +} + +CWnd* CTabCtrlSSL::GetSSLPage (int nIndex) { + if (nIndex >= GetItemCount ()) + return NULL; + + TabDelete tabDelete = m_tabs[nIndex]; + return (CWnd*) tabDelete.pTabPage; +} + +int CTabCtrlSSL::GetSSLPageIndex (int nPageID) { + int nCount = GetItemCount (); + if (nCount == 0) + return -1; + + for (int i=0; isignature == 0xFFFF) + dwStyle = pTemplate->style; + else + dwStyle = ((DLGTEMPLATE*) pTemplate)->style; + + UnlockResource (hTemplate); + FreeResource (hTemplate); + + // Verify that the dialog is an invisible child window. + if (dwStyle & WS_VISIBLE) + return FALSE; // WS_VISIBLE flag is set + + if (!(dwStyle & WS_CHILD)) + return FALSE; // WS_CHILD flag isn't set + + // Verify that the dialog has no border and no title bar. + if (dwStyle & (WS_BORDER | WS_THICKFRAME | DS_MODALFRAME)) + return FALSE; // One or more border flags are set + + if (dwStyle & WS_CAPTION) + return FALSE; // WS_CAPTION flag is set + + return TRUE; +} +#endif // _DEBUG + +void CTabCtrlSSL::ResizeDialog (int nIndex, int cx, int cy) { + if (nIndex != -1) { + TabDelete tabDelete = m_tabs[nIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + + if (pDialog != NULL) { + CRect rect; + GetItemRect (nIndex, &rect); + + int x, y, nWidth, nHeight; + DWORD dwStyle = GetStyle (); + + if (dwStyle & TCS_VERTICAL) { // Vertical tabs + int nTabWidth = + rect.Width () * GetRowCount (); + x = (dwStyle & TCS_RIGHT) ? 4 : nTabWidth + 4; + y = 4; + nWidth = cx - nTabWidth - 8; + nHeight = cy - 8; + } + else { // Horizontal tabs + int nTabHeight = + rect.Height () * GetRowCount (); + x = 4; + y = (dwStyle & TCS_BOTTOM) ? 4 : nTabHeight + 4; + nWidth = cx - 8; + nHeight = cy - nTabHeight - 8; + } + pDialog->SetWindowPos (NULL, x, y, nWidth, nHeight, SWP_NOZORDER); + } + } +} + +///////////////////////////////////////////////////////////////////////////// +// Overridables + +BOOL CTabCtrlSSL::OnInitPage (int nIndex, int nPageID) { + // TODO: Override in derived class to initialise pages. + return TRUE; +} + +void CTabCtrlSSL::OnActivatePage (int nIndex, int nPageID) { + // TODO: Override in derived class to respond to page activations. +} + +void CTabCtrlSSL::OnDeactivatePage (int nIndex, int nPageID) { + // TODO: Override in derived class to respond to page deactivations. +} + +void CTabCtrlSSL::OnDestroyPage (int nIndex, int nPageID) { + // TODO: Override in derived class to free resources. +} + +///////////////////////////////////////////////////////////////////////////// +// Message handlers + +void CTabCtrlSSL::OnSelChanging (NMHDR* pNMHDR, LRESULT* pResult) { + // Notify derived classes that the selection is changing. + int nIndex = GetCurSel (); + if (nIndex == -1) + return; + + OnDeactivatePage (nIndex, m_nPageIDs[nIndex]); + + // Save the input focus and hide the old page. + TabDelete tabDelete = m_tabs[nIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + + if (pDialog != NULL) { + m_hFocusWnd[nIndex] = ::GetFocus (); + pDialog->ShowWindow (SW_HIDE); + } + *pResult = 0; +} + +void CTabCtrlSSL::OnSelChange (NMHDR* pNMHDR, LRESULT* pResult) { + int nIndex = GetCurSel (); + if (nIndex == -1) + return; + + // Show the new page. + TabDelete tabDelete = m_tabs[nIndex]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + + if (pDialog != NULL) { + ::SetFocus (m_hFocusWnd[nIndex]); + CRect rect; + GetClientRect (&rect); + ResizeDialog (nIndex, rect.Width (), rect.Height ()); + pDialog->ShowWindow (SW_SHOW); + } + + // Notify derived classes that the selection has changed. + OnActivatePage (nIndex, m_nPageIDs[nIndex]); + *pResult = 0; +} + +void CTabCtrlSSL::OnSetFocus (CWnd* pOldWnd) { + CTabCtrl::OnSetFocus (pOldWnd); + + // Set the focus to a control on the current page. + int nIndex = GetCurSel (); + if (nIndex != -1) + ::SetFocus (m_hFocusWnd[nIndex]); +} + +void CTabCtrlSSL::OnKillFocus (CWnd* pNewWnd) { + CTabCtrl::OnKillFocus (pNewWnd); + + // Save the HWND of the control that holds the input focus. + int nIndex = GetCurSel (); + if (nIndex != -1) + m_hFocusWnd[nIndex] = ::GetFocus (); +} + +// My thanks to Tomasz Sowinski for all his help coming up with a workable +// solution to the stack versus heap object destruction +void CTabCtrlSSL::OnDestroy (void) { + int nCount = m_tabs.GetSize (); + + // Destroy dialogs and delete CTabCtrlSSL objects. + if (nCount > 0) { + for (int i=nCount - 1; i>=0; i--) { + OnDestroyPage (i, m_nPageIDs[i]); + TabDelete tabDelete = m_tabs[i]; + CTabPageSSL* pDialog = tabDelete.pTabPage; + if (pDialog != NULL) { + pDialog->DestroyWindow (); + if (TRUE == tabDelete.bDelete) { + delete pDialog; + } + } + } + } + + // Clean up the internal arrays. + m_tabs.RemoveAll (); + m_hFocusWnd.RemoveAll (); + m_nPageIDs.RemoveAll (); + + CTabCtrl::OnDestroy (); +} + +BOOL CTabCtrlSSL::OnCommand (WPARAM wParam, LPARAM lParam) { + // Forward WM_COMMAND messages to the dialog's parent. + return GetParent ()->SendMessage (WM_COMMAND, wParam, lParam); +} + +BOOL CTabCtrlSSL::OnNotify (WPARAM wParam, LPARAM lParam, LRESULT* pResult) { + // Forward WM_NOTIFY messages to the dialog's parent. + return GetParent ()->SendMessage (WM_NOTIFY, wParam, lParam); +} + +BOOL CTabCtrlSSL::OnCmdMsg (UINT nID, int nCode, void* pExtra, + AFX_CMDHANDLERINFO* pHandlerInfo) { + // Forward ActiveX control events to the dialog's parent. +#ifndef _AFX_NO_OCC_SUPPORT + if (nCode == CN_EVENT) + return GetParent ()->OnCmdMsg (nID, nCode, pExtra, pHandlerInfo); +#endif // !_AFX_NO_OCC_SUPPORT + + return CTabCtrl::OnCmdMsg (nID, nCode, pExtra, pHandlerInfo); +} + +int CTabCtrlSSL::AddPage (LPCTSTR pszTitle, int nPageID, TabDelete tabDelete) { + // Add a page to the tab control. + TC_ITEM item; + item.mask = TCIF_TEXT; + item.pszText = (LPTSTR) pszTitle; + int nIndex = GetItemCount (); + + if (InsertItem (nIndex, &item) == -1) + return -1; + + if (NULL == tabDelete.pTabPage) { + // Fail - no point calling the function with a NULL pointer! + DeleteItem (nIndex); + return -1; + } + else { + // Record the address of the dialog object and the page ID. + int nArrayIndex = m_tabs.Add (tabDelete); + ASSERT (nIndex == nArrayIndex); + + nArrayIndex = m_nPageIDs.Add (nPageID); + ASSERT (nIndex == nArrayIndex); + + // Size and position the dialog box within the view. + tabDelete.pTabPage->SetParent (this); // Just to be sure + + CRect rect; + GetClientRect (&rect); + + if (rect.Width () > 0 && rect.Height () > 0) + ResizeDialog (nIndex, rect.Width (), rect.Height ()); + + // Initialize the page. + if (OnInitPage (nIndex, nPageID)) { + // Make sure the first control in the dialog is the one that + // receives the input focus when the page is displayed. + HWND hwndFocus = tabDelete.pTabPage->GetTopWindow ()->m_hWnd; + nArrayIndex = m_hFocusWnd.Add (hwndFocus); + ASSERT (nIndex == nArrayIndex); + } + else { + // Make the control that currently has the input focus is the one + // that receives the input focus when the page is displayed. + m_hFocusWnd.Add (::GetFocus ()); + } + + // If this is the first page added to the view, make it visible. + if (nIndex == 0) + tabDelete.pTabPage->ShowWindow (SW_SHOW); + } + return nIndex; +} diff --git a/huagao/TabCtrlSSL.h b/huagao/TabCtrlSSL.h new file mode 100644 index 00000000..7424be65 --- /dev/null +++ b/huagao/TabCtrlSSL.h @@ -0,0 +1,98 @@ +#if !defined(AFX_TABCTRLSSL_H__75BE48A7_864C_11D5_9F04_000102FB9990__INCLUDED_) +#define AFX_TABCTRLSSL_H__75BE48A7_864C_11D5_9F04_000102FB9990__INCLUDED_ + +#if _MSC_VER > 1000 +#pragma once +#endif // _MSC_VER > 1000 +// TabCtrlEx.h : header file +// + +#include +#include "TabPageSSL.h" + +#ifdef _DEBUG +#pragma pack (push, 1) + +typedef struct { + WORD dlgVer; + WORD signature; + DWORD helpID; + DWORD exStyle; + DWORD style; + WORD cDlgItems; + short x; + short y; + short cx; + short cy; +} DLGTEMPLATEEX; + +#pragma pack (pop) +#endif // _DEBUG + +///////////////////////////////////////////////////////////////////////////// +// CTabCtrlSSL window + +class CTabCtrlSSL : public CTabCtrl { +public: +// Construction + CTabCtrlSSL (); +// Destruction + virtual ~CTabCtrlSSL (void); +// Page Functions + int AddSSLPage (LPCTSTR pszTitle, int nPageID, CTabPageSSL* pTabPage); + int AddSSLPage (LPCTSTR pszTitle, int nPageID, LPCTSTR pszTemplateName); + int AddSSLPage (LPCTSTR pszTitle, int nPageID, int nTemplateID); + BOOL RemoveSSLPage (int nIndex); + int GetSSLPageCount (void); + BOOL GetSSLPageTitle (int nIndex, CString& strTitle); + BOOL SetSSLPageTitle (int nIndex, LPCTSTR pszTitle); + int GetSSLPageID (int nIndex); + int SetSSLPageID (int nIndex, int nPageID); + BOOL ActivateSSLPage (int nIndex); + int GetSSLActivePage (void); + CWnd* GetSSLPage (int nIndex); + int GetSSLPageIndex (int nPageID); + +protected: + struct TabDelete { + CTabPageSSL* pTabPage; + BOOL bDelete; + }; + CArray m_tabs; + CArray m_hFocusWnd; + CArray m_nPageIDs; + + int AddPage (LPCTSTR pszTitle, int nPageID, TabDelete tabDelete); + + virtual BOOL OnInitPage (int nIndex, int nPageID); + virtual void OnActivatePage (int nIndex, int nPageID); + virtual void OnDeactivatePage (int nIndex, int nPageID); + virtual void OnDestroyPage (int nIndex, int nPageID); + virtual BOOL OnCommand (WPARAM wParam, LPARAM lParam); + virtual BOOL OnNotify (WPARAM wParam, LPARAM lParam, LRESULT* pResult); + virtual BOOL OnCmdMsg (UINT nID, int nCode, void* pExtra, + AFX_CMDHANDLERINFO* pHandlerInfo); + +#ifdef _DEBUG + BOOL CheckDialogTemplate (LPCTSTR pszTemplateName); +#endif // _DEBUG + void ResizeDialog (int nIndex, int cx, int cy); + // Generated message map functions +protected: + //{{AFX_MSG(CTabCtrlSSL) + afx_msg void OnDestroy (void); + afx_msg void OnSetFocus (CWnd* pOldWnd); + afx_msg void OnKillFocus (CWnd* pNewWnd); + afx_msg void OnSelChanging (NMHDR* pNMHDR, LRESULT* pResult); + afx_msg void OnSelChange (NMHDR* pNMHDR, LRESULT* pResult); + //}}AFX_MSG + + DECLARE_MESSAGE_MAP() +}; + +///////////////////////////////////////////////////////////////////////////// + +//{{AFX_INSERT_LOCATION}} +// Microsoft Visual C++ will insert additional declarations immediately before the previous line. + +#endif // !defined(AFX_TABCTRLSSL_H__75BE48A7_864C_11D5_9F04_000102FB9990__INCLUDED_) diff --git a/huagao/TabPageSSL.cpp b/huagao/TabPageSSL.cpp new file mode 100644 index 00000000..e64e21bc --- /dev/null +++ b/huagao/TabPageSSL.cpp @@ -0,0 +1,98 @@ +#include "stdafx.h" +#include "TabPageSSL.h" + +#ifdef _DEBUG +#define new DEBUG_NEW +#undef THIS_FILE +static char THIS_FILE[] = __FILE__; +#endif + +///////////////////////////////////////////////////////////////////////////// +// Construction + +CTabPageSSL::CTabPageSSL () { +#ifndef _AFX_NO_OCC_SUPPORT + AfxEnableControlContainer (); +#endif // !_AFX_NO_OCC_SUPPORT + m_bRouteCommand = false; + m_bRouteCmdMsg = false; + m_bRouteNotify = false; +} + +CTabPageSSL::CTabPageSSL (UINT nIDTemplate, CWnd* pParent /*=NULL*/) + : CDialog(nIDTemplate, pParent) { +#ifndef _AFX_NO_OCC_SUPPORT + AfxEnableControlContainer (); +#endif // !_AFX_NO_OCC_SUPPORT + m_bRouteCommand = false; + m_bRouteCmdMsg = false; + m_bRouteNotify = false; +} + +///////////////////////////////////////////////////////////////////////////// +// Destruction + +CTabPageSSL::~CTabPageSSL () { +} + +///////////////////////////////////////////////////////////////////////////// +// Message Handlers + +void CTabPageSSL::OnOK (void) { + // + // Prevent CDialog::OnOK from calling EndDialog. + // +} + +void CTabPageSSL::OnCancel (void) { + // + // Prevent CDialog::OnCancel from calling EndDialog. + // +} + +BOOL CTabPageSSL::OnCommand (WPARAM wParam, LPARAM lParam) { + // Call base class OnCommand to allow message map processing + BOOL bReturn = CDialog::OnCommand (wParam, lParam); + + if (true == m_bRouteCommand) + { + // + // Forward WM_COMMAND messages to the dialog's parent. + // + return GetParent ()->SendMessage (WM_COMMAND, wParam, lParam); + } + + return bReturn; +} + +BOOL CTabPageSSL::OnNotify (WPARAM wParam, LPARAM lParam, LRESULT* pResult) { + BOOL bReturn = CDialog::OnNotify(wParam, lParam, pResult); + + if (true == m_bRouteNotify) + { + // + // Forward WM_NOTIFY messages to the dialog's parent. + // + return GetParent ()->SendMessage (WM_NOTIFY, wParam, lParam); + } + + return bReturn; +} + +BOOL CTabPageSSL::OnCmdMsg (UINT nID, int nCode, void* pExtra, + AFX_CMDHANDLERINFO* pHandlerInfo) { + BOOL bReturn = CDialog::OnCmdMsg (nID, nCode, pExtra, pHandlerInfo); + +#ifndef _AFX_NO_OCC_SUPPORT + if (true == m_bRouteCmdMsg) + { + // + // Forward ActiveX control events to the dialog's parent. + // + if (nCode == CN_EVENT) + return GetParent ()->OnCmdMsg (nID, nCode, pExtra, pHandlerInfo); + } +#endif // !_AFX_NO_OCC_SUPPORT + + return bReturn; +} diff --git a/huagao/TabPageSSL.h b/huagao/TabPageSSL.h new file mode 100644 index 00000000..03101630 --- /dev/null +++ b/huagao/TabPageSSL.h @@ -0,0 +1,41 @@ +#if !defined(AFX_TABPAGESSL_H__619331B3_7DE7_4DB1_A039_2103E87E8E71__INCLUDED_) +#define AFX_TABPAGESSL_H__619331B3_7DE7_4DB1_A039_2103E87E8E71__INCLUDED_ + +///////////////////////////////////////////////////////////////////////////// +// CTabPageSSL declaration + +class CTabPageSSL : public CDialog +{ +public: +// Construction + CTabPageSSL (); // Default Constructor + CTabPageSSL (UINT nIDTemplate, CWnd* pParent = NULL); // Standard Constructor +// Destruction + ~CTabPageSSL (); + + // Enable/disable command routing to the parent. + void EnableRouteCommand(bool bRoute = true) { m_bRouteCommand = bRoute; }; + bool IsRouteCommand() { return m_bRouteCommand; }; + // Enable CmdMsg routing to the parent. + void EnableRouteCmdMsg(bool bRoute = true) { m_bRouteCmdMsg = bRoute; }; + bool IsRouteCmdMsg() { return m_bRouteCmdMsg; }; + // Enable/Disable Notify routing to the parent. + void EnableRouteNotify(bool bRoute = true) { m_bRouteNotify = bRoute; }; + bool IsRouteNotify() { return m_bRouteNotify; }; + +protected: +// Message Handlers + virtual BOOL OnCommand (WPARAM wParam, LPARAM lParam); + virtual BOOL OnNotify (WPARAM wParam, LPARAM lParam, LRESULT* pResult); + virtual void OnOK (void); + virtual void OnCancel (void); + virtual BOOL OnCmdMsg (UINT nID, int nCode, void* pExtra, + AFX_CMDHANDLERINFO* pHandlerInfo); + +// Routing flags + bool m_bRouteCommand; + bool m_bRouteCmdMsg; + bool m_bRouteNotify; +}; + +#endif // !defined(AFX_TABPAGE_H__619331B3_7DE7_4DB1_A039_2103E87E8E71__INCLUDED_) diff --git a/huagao/exports.def b/huagao/exports.def new file mode 100644 index 00000000..054bac6a --- /dev/null +++ b/huagao/exports.def @@ -0,0 +1,3 @@ +LIBRARY huagaoscands +EXPORTS + DS_Entry \ No newline at end of file diff --git a/huagao/huagaods.cpp b/huagao/huagaods.cpp new file mode 100644 index 00000000..f1d018bb --- /dev/null +++ b/huagao/huagaods.cpp @@ -0,0 +1,1876 @@ +#include "stdafx.h" +#ifdef max +#undef max +#endif +#ifdef min +#undef min +#endif + +#include + +#include "huagaods.hpp" +#include "twglue.hpp" + +#include "resource.h" +#include "CTwainUI.h" +#include "CIndicatorDlg.h" +#include "Device/PublicFunc.h" +#include "Device/GScanO200.h" +#include "Device/filetools.h" +#include "Device/GScanVirtual.h" +#include +#include +#include "Device/JsonConfig.h" + + +//custom define caps enum +enum class CapTypeEx : unsigned short { + Base = 0x8000,//custom caps enum value must bigger than CapTypeEx::Base value,otherwise might make conflict + TwEx_IMultiOutputRed = 0x8026, + TwEx_IFillHole = 0x8018, + TwEx_IFillHoleRatio = 0x8092, + TwEx_IFillBackground = 0x8004, + TwEx_IBackRotate180 = 0x8005, + TwEx_IAutoDiscardBlankVince = 0x8091, + TwEx_IEnhanceColor = 0x8007, + TwEx_HardwareVersion = 0x8025, + TwEx_ScrewDetectEnable = 0x8006, + TwEx_ScrewLevel = 0x8021, + TwEx_Sharpen = 0x8022, + TwEx_DBAreaNum =0x8027, + TwEx_DBDevnMax = 0x8028, + TwEx_StableDetectEnable = 0x8090 +}; + +using namespace Twpp; +using namespace std::placeholders; + +#define TWPP_ENTRY_MFC(SourceClass)\ + extern "C" TWPP_DETAIL_EXPORT Twpp::ReturnCode TWPP_DETAIL_CALLSTYLE \ + DS_Entry(Twpp::Identity* origin, Twpp::DataGroup dg, Twpp::Dat dat, Twpp::Msg msg, void* data){\ + AFX_MANAGE_STATE(AfxGetStaticModuleState()); \ + static_assert(\ + std::is_base_of, SourceClass>::value ||\ + std::is_base_of, SourceClass>::value,\ + "Class " #SourceClass " is not derived from SourceFromThis."\ + );\ + return SourceClass::entry(origin, dg, dat, msg, data);\ + } + +TWPP_ENTRY_MFC(HuagaoDs) + +static constexpr const Identity srcIdent( + Version(3, 3, Language::English, Country::CzechRepublic, "v3.3.1.3"), + DataGroup::Image, + "ϢƼ޹˾", + "G200 Series", + "HUAGOSCAN Twain" +#if defined(_MSC_VER) + "" +#elif defined(__GNUC__) + " GCC" +#elif defined(__clang__) + " CLang" +#endif + ); + +// lets just simulate uniform resolution for both axes +static constexpr UInt32 RESOLUTIONX = 85; + +static std::unique_ptr application(new CWinApp()); + +static list resList = { 100.0,150.0,200.0,240.0,300.0 }; + +static list paperSizeList = { (UInt16)PaperSize::A3,(UInt16)PaperSize::A4,(UInt16)PaperSize::A5,(UInt16)PaperSize::A6, + (UInt16)PaperSize::IsoB4,(UInt16)PaperSize::IsoB5,(UInt16)PaperSize::IsoB6, + (UInt16)PaperSize::UsLetter,(UInt16)PaperSize::UsLegal,(UInt16)PaperSize::UsLedger, + (UInt16)PaperSize::MaxSize,(UInt16)PaperSize::None,(UInt16)PaperSize::UsStatement }; + +static list imageRotateList = {0.0,90.0,180.0,270.0}; + +static map noticeMsgMap = { {OPEN_COVER,_T("ɨǿ")}, + {NO_FEED,_T("ֽ")}, + {FEED_IN_ERROR,_T("ֽʧܣ")}, + {PAPER_JAM,_T("ֽ")}, + {DETECT_DOUBLE_FEED,_T("˫ţ")}, + {DETECT_STAPLE,_T("룡")}, + {PAPER_SKEW,_T("ֽб")}, + {COUNT_MODE,_T("ģʽ˳ģʽ")}, + {HARDWARE_ERROR,_T("Ӳ")}, + {FPGA_ERROR,_T("FPGA 쳣")}, + {USB_DISCONNECTED,_T("USB쳣")} + }; + +static void DeleteWnd(CDialog* pWnd) { + if (pWnd && pWnd->GetSafeHwnd()) { + pWnd->DestroyWindow(); + delete pWnd; + } +} +static std::unique_ptr guiTwain(nullptr, DeleteWnd); + +#if TWPP_DETAIL_OS_WIN +static std::unique_ptr guiBridge(nullptr, DeleteWnd); +#endif +static std::unique_ptr guiIndicator(nullptr, DeleteWnd); + +#ifndef HG_VIRTUAL +static std::unique_ptr scanner(new GScanO200()); +#else +static std::unique_ptr scanner(new GScanVirtual()); +#endif + + + +HuagaoDs::HuagaoDs() + : m_scanparam(new GScanCap) +{ + /*string ss1= getOSInfo(); + string ss2=getManufactureID(); + string ss3=getCpuType(); + string ss4= getMemoryInfo(); + DWORD dwNum; + CString aas[10]; + GetDiskInfo(dwNum,aas);*/ + initGScanCap(); +} + +HuagaoDs::~HuagaoDs() +{ +} + +const Identity& HuagaoDs::defaultIdentity() noexcept{ + // remember, we return a reference, therefore the identity must not be placed on the stack of this method + return srcIdent; +} + +Result HuagaoDs::call(const Identity& origin, DataGroup dg, Dat dat, Msg msg, void* data){ + try { + // we can override almost anything from SourceFromThis, even the top-most source instance call + return Base::call(origin, dg, dat, msg, data); + } catch (const CapabilityException&){ + return badValue(); + } +} + +// some helper functions to handle capability stuff +template +static Result oneValGet(Msg msg, Capability& data, const T& value){ + switch (msg){ + case Msg::Get: + case Msg::GetCurrent: + case Msg::GetDefault: + data = Capability::createOneValue(data.type(), value); + return {}; + + default: + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } +} + +static Result oneValGetString(Msg msg, Capability& data, std::string value) { + Str255 str; + str.setData(value.c_str(), value.size()); + return oneValGet(msg, data, str); +} + +template +static Result enmGet(Msg msg, Capability& data, const T& value){ + switch (msg){ + case Msg::Get: + data = Capability::createEnumeration(data.type(), {value}); + return {}; + case Msg::GetCurrent: + case Msg::GetDefault: + data = Capability::createOneValue(data.type(), value); + return {}; + + default: + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } +} + +template +static Result oneValGetSet(Msg msg, Capability& data, T& value, const T& def){ + switch (msg){ + case Msg::Reset: + value = def; + // fallthrough + case Msg::Get: + case Msg::GetCurrent: + data = Capability::createOneValue(data.type(), value); + return {}; + + case Msg::GetDefault: + data = Capability::createOneValue(data.type(), def); + return {}; + + case Msg::Set: + value = data.currentItem(); + return {}; + + default: + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } +} + +template +static Result oneValGetSetConst(Msg msg, Capability& data, const T& def){ + switch (msg){ + case Msg::Get: + case Msg::GetCurrent: + case Msg::GetDefault: + case Msg::Reset: + data = Capability::createOneValue(data.type(), def); + return {}; + + case Msg::Set: + return data.currentItem() == def ? + Result() : Result(ReturnCode::Failure, ConditionCode::BadValue); + + default: + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } +} + +template +static Result enmGetSetConst(Msg msg, Capability& data, const T& def){ + switch (msg){ + case Msg::Get: + data = Capability::createEnumeration(data.type(), {def}); + return {}; + + case Msg::GetCurrent: + case Msg::GetDefault: + case Msg::Reset: + data = Capability::createOneValue(data.type(), def); + return {}; + + case Msg::Set: + return data.currentItem() == def ? + Result() : Result(ReturnCode::Failure, ConditionCode::BadValue); + + default: + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } +} + +/// Shortcut for Result(RC::Failure, CC::CheckDeviceOnline). +static constexpr Result checkDeviceOnline() noexcept { + return { ReturnCode::Failure,ConditionCode::CheckDeviceOnline }; +} + +//void HuagaoDs::updateScanParam() +//{ +// +//} + +Result HuagaoDs::capCommon(const Identity&, Msg msg, Capability& data){ + auto it = m_caps.find(data.type()); + if (it != m_caps.end()){ + return (it->second)(msg, data); + } + + return capUnsupported(); +} + +Result HuagaoDs::capabilityGet(const Identity& origin, Capability& data){ + return capCommon(origin, Msg::Get, data); +} + +Result HuagaoDs::capabilityGetCurrent(const Identity& origin, Capability& data){ + return capCommon(origin, Msg::GetCurrent, data); +} + +Result HuagaoDs::capabilityGetDefault(const Identity& origin, Capability& data){ + return capCommon(origin, Msg::GetDefault, data); +} + +Result HuagaoDs::capabilityQuerySupport(const Identity&, Capability& data){ + auto it = m_query.find(data.type()); + MsgSupport sup = it != m_query.end() ? it->second : msgSupportEmpty; + data = Capability::createOneValue(data.type(), sup); + return success(); +} + +Result HuagaoDs::capabilityReset(const Identity& origin, Capability& data){ + return capCommon(origin, Msg::Reset, data); +} + +Result HuagaoDs::capabilityResetAll(const Identity& origin){ + for (auto& pair : m_query){ + if ((pair.second & MsgSupport::Reset) != msgSupportEmpty){ + Capability dummyCap(pair.first); + capCommon(origin, Msg::Reset, dummyCap); + } + } + + return success(); +} + +Result HuagaoDs::capabilitySet(const Identity& origin, Capability& data){ + return capCommon(origin, Msg::Set, data); +} + +Result HuagaoDs::eventProcess(const Identity&, Event& event){ + // Qt needs to process its events, otherwise the GUI will appear frozen + // this is Windows-only method, Linux and macOS behave differently + if (guiTwain) { + // // QApplication::processEvents(); - TODO: needs more investigation; results in freeze when attempting to scan using old DSM + // QApplication::sendPostedEvents(); + guiTwain->SendMessage((UINT)(event.message())); + } + event.setMessage(Msg::Null); + return {ReturnCode::NotDsEvent, ConditionCode::Success}; +} + +Result HuagaoDs::identityOpenDs(const Identity&){ + bmpData.resize(sizeof(BITMAPFILEHEADER) + sizeof(BITMAPINFOHEADER)); + BITMAPINFOHEADER& bmInfo = *((BITMAPINFOHEADER*)header()); + bmInfo.biHeight = 2000; + bmInfo.biWidth = 2000; + bmInfo.biBitCount = 24; + updataGscanCap(); + scanner->open(0x064B, 0x7823); + if (!scanner->IsConnected()) { + MessageBox(NULL, _T("δҵɨ!ԴUSBǷͨ!"), _T("ʾ"), MB_SYSTEMMODAL | MB_OK | MB_ICONINFORMATION); + return checkDeviceOnline(); + } + + // init caps + // there are caps a minimal source must support + // query -> says which operations a cap supports + // caps -> has handler for each specific cap + m_query[CapType::SupportedCaps] = msgSupportGetAll; + m_caps[CapType::SupportedCaps] = [this](Msg msg, Capability& data){ + switch (msg){ + case Msg::Get: + case Msg::GetCurrent: + case Msg::GetDefault: { + data = Capability::createArray(m_caps.size()); + auto arr = data.array(); + UInt32 i = 0; + for (const auto& kv : m_caps){ + arr[i] = kv.first; + i++; + } + + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::UiControllable] = msgSupportGetAll; + m_caps[CapType::UiControllable] = std::bind(enmGet, _1, _2, Bool(true)); + + m_query[CapType::DeviceOnline] = msgSupportGetAll; + m_caps[CapType::DeviceOnline] = std::bind(enmGet, _1, _2, Bool(scanner->IsConnected())); + + m_query[CapType::XferCount] = msgSupportGetAllSetReset; + m_caps[CapType::XferCount] = [this](Msg msg, Capability& data) -> Result{ + if (msg == Msg::Set){ + auto item = data.currentItem(); + if (item > 65535 || item < -1){ + return badValue(); + } + m_capXferCount = item; + return success(); + } + + auto ret = oneValGetSet(msg, data, m_capXferCount, -1); + if (Twpp::success(ret) && m_capXferCount == 0){ + m_capXferCount = -1; + m_scanparam->scannum = m_capXferCount; + return {ReturnCode::CheckStatus, ConditionCode::BadValue}; + } + + return ret; + }; + + m_query[CapType::ICompression] = msgSupportGetAllSetReset; + m_caps[CapType::ICompression] = std::bind(enmGetSetConst, _1, _2, Compression::None); + + m_query[CapType::IBitDepth] = msgSupportGetAllSetReset; + m_caps[CapType::IBitDepth] = std::bind(enmGetSetConst, _1, _2, UInt16(header()->biBitCount)); + + m_query[CapType::IBitOrder] = msgSupportGetAllSetReset; + m_caps[CapType::IBitOrder] = std::bind(enmGetSetConst, _1, _2, BitOrder::MsbFirst); + + m_query[CapType::IPlanarChunky] = msgSupportGetAllSetReset; + m_caps[CapType::IPlanarChunky] = std::bind(enmGetSetConst, _1, _2, PlanarChunky::Chunky); + + m_query[CapType::IPhysicalWidth] = msgSupportGetAll; + m_caps[CapType::IPhysicalWidth] = std::bind(oneValGet, _1, _2, Fix32(static_cast(header()->biWidth) / RESOLUTIONX)); + + m_query[CapType::IPhysicalHeight] = msgSupportGetAll; + m_caps[CapType::IPhysicalHeight] = std::bind(oneValGet, _1, _2, Fix32(static_cast(header()->biHeight) / RESOLUTIONX)); + + m_query[CapType::IPixelFlavor] = msgSupportGetAllSetReset; + m_caps[CapType::IPixelFlavor] = std::bind(enmGetSetConst, _1, _2, PixelFlavor::Chocolate); + + m_query[CapType::IPixelType] = msgSupportGetAllSetReset; + m_caps[CapType::IPixelType] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { PixelType::BlackWhite, PixelType::Gray, PixelType::Rgb}, (int)(m_scanparam->pixtype), (int)PixelType::Gray); + return success(); + + case Msg::Reset: + m_scanparam->pixtype = (byte)PixelType::Gray; + case Msg::GetCurrent: + data = Capability::createOneValue((PixelType)(m_scanparam->pixtype)); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(PixelType::Gray); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->pixtype = (int)mech; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IUnits] = msgSupportGetAllSetReset; + m_caps[CapType::IUnits] = std::bind(enmGetSetConst, _1, _2, Unit::Inches); + + m_query[CapType::IXferMech] = msgSupportGetAllSetReset; + m_caps[CapType::IXferMech] = [this](Msg msg, Capability& data) -> Result{ + switch (msg){ + case Msg::Get: + data = Capability::createEnumeration( + {XferMech::Native, XferMech::Memory}, m_capXferMech == XferMech::Native ? 0 : 1, 0); + return success(); + + case Msg::Reset: + m_capXferMech = XferMech::Native; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_capXferMech); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(XferMech::Native); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + if (mech == XferMech::Native || mech == XferMech::Memory){ + m_capXferMech = mech; + return success(); + } else { + return badValue(); + } + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IXResolution] = msgSupportGetAllSetReset; + m_caps[CapType::IXResolution] = [this](Msg msg, Capability& data){ + switch (msg){ + case Msg::Get: { + int index = -1; + std::list::iterator it = resList.begin(); + int i = 0; + for (it,i; it != resList.end(); ++it, i++) { + if (*it == m_scanparam->resolution_dst) { + index = i; + break; + } + } + data = Capability::createEnumeration(data.type(), { Fix32(100.0),Fix32(150.0),Fix32(200.0),Fix32(240.0),Fix32(300.0) }, index==-1?2:index, 2); + return success(); + } + case Msg::GetCurrent: { + data = Capability::createOneValue(data.type(), Fix32(m_scanparam->resolution_dst)); + return success(); + } + case Msg::GetDefault: + case Msg::Reset:{ + data = Capability::createOneValue(data.type(), Fix32(200.0)); + return success(); + } + case Msg::Set:{ + auto res = data.currentItem(); + std::list::iterator resIter= resList.begin(); + bool contains = false; + for (resIter; resIter != resList.end(); resIter++) { + if (*resIter == res) { + contains = true; + break; + } + } + if (contains) { + m_scanparam->resolution_dst = (float)res; + return success(); + } + return badValue(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IYResolution] = msgSupportGetAllSetReset; + m_caps[CapType::IYResolution] = m_caps[CapType::IXResolution]; + + m_query[CapType::IXNativeResolution] = msgSupportGetAll; + m_caps[CapType::IXNativeResolution] = std::bind(enmGet, _1, _2, Fix32(200.0)); + + m_query[CapType::IYNativeResolution] = msgSupportGetAll; + m_caps[CapType::IYNativeResolution] = m_caps[CapType::IXNativeResolution]; + + m_query[CapType::FeederLoaded] = msgSupportGetAll; + m_caps[CapType::FeederLoaded] = std::bind(enmGet, _1, _2, Bool(scanner->Get_Scanner_PaperOn())); + + m_query[CapType::ISupportedSizes] = msgSupportGetAllSetReset; + m_caps[CapType::ISupportedSizes] = [this](Msg msg, Capability& data) { + switch (msg) { + case Msg::Get: { + int index = -1; + std::list::iterator it = paperSizeList.begin(); + int i = 0; + for (it, i; it != paperSizeList.end(); ++it, i++) { + if (*it == m_scanparam->papertype) { + index = i; + break; + } + } + data = Capability::createEnumeration(data.type(), { PaperSize::A3,PaperSize::A4,PaperSize::A5, + PaperSize::A6,PaperSize::IsoB4,PaperSize::IsoB5, + PaperSize::IsoB6,PaperSize::UsLetter,PaperSize::UsLegal, + PaperSize::UsLedger,PaperSize::MaxSize,PaperSize::None}, + index == -1 ? 0 : index, + 0); + return success(); + } + case Msg::GetCurrent: + data = Capability::createOneValue(data.type(), UInt16(m_scanparam->papertype)); + return success(); + case Msg::GetDefault: + case Msg::Reset: + data = Capability::createOneValue(data.type(), UInt16(PaperSize::A3)); + return success(); + + case Msg::Set: { + auto res = data.currentItem(); + std::list::iterator resIter = paperSizeList.begin(); + bool contains = false; + for (resIter; resIter != paperSizeList.end(); resIter++) { + if (*resIter == res) { + contains = true; + break; + } + } + if (contains) { + m_scanparam->papertype = (byte)res; + return success(); + } + return badValue(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IOrientation] = msgSupportGetAllSetReset; + m_caps[CapType::IOrientation] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Orientation::Portrait, Orientation::Landscape,Orientation::AutoText}, m_scanparam->paperAlign,0); + return success(); + + case Msg::Reset: + m_scanparam->paperAlign = PaperAlign::Rot0; + case Msg::GetCurrent: + data = Capability::createOneValue((Orientation)(m_scanparam->paperAlign)); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(Orientation::Portrait); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + if(mech== Orientation::Landscape|| mech == Orientation::Portrait|| mech== Orientation::AutoText){ + m_scanparam->paperAlign =(PaperAlign)mech; + return success(); + } + return badValue(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IRotation] = msgSupportGetAllSetReset; + m_caps[CapType::IRotation] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get:{ + int index = -1; + std::list::iterator it = imageRotateList.begin(); + int i = 0; + for (it, i; it != imageRotateList.end(); ++it, i++) { + if (*it == m_scanparam->imageRotateDegree) { + index = i; + break; + } + } + data = Capability::createEnumeration( + {Fix32(0.0),Fix32(90.0),Fix32(180.0),Fix32(270.0)}, + index==-1?0:index, + 0); + return success(); + } + case Msg::Reset: + m_scanparam->imageRotateDegree = 0.0; + case Msg::GetCurrent: + data = Capability::createOneValue(Fix32(m_scanparam->imageRotateDegree)); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(Fix32(0.0)); + return success(); + + case Msg::Set: { + auto res = data.currentItem(); + std::list::iterator resIter = imageRotateList.begin(); + bool contains = false; + for (resIter; resIter != imageRotateList.end(); resIter++) { + if (*resIter == res) { + contains = true; + break; + } + } + if (contains) { + m_scanparam->imageRotateDegree = (float)res; + return success(); + } + return badValue(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::SerialNumber] = msgSupportGetAll; + m_caps[CapType::SerialNumber] = std::bind(oneValGetString,_1,_2,scanner->GetSerialNum()); + + m_query[(CapType)(CapTypeEx::TwEx_HardwareVersion)] = msgSupportGetAll; + m_caps[(CapType)(CapTypeEx::TwEx_HardwareVersion)] = std::bind(oneValGetString, _1, _2, scanner->GetFWVersion()); + + m_query[CapType::Indicators] = msgSupportGetAllSetReset; + m_caps[CapType::Indicators] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true)}, Bool(m_bIndicator)); + return success(); + + case Msg::Reset: + m_bIndicator = true; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_bIndicator); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(false); + return success(); + + case Msg::Set: { + auto show = data.currentItem(); + m_bIndicator = show; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::EnableDsUiOnly] = msgSupportGetAll; + m_caps[CapType::EnableDsUiOnly] = std::bind(enmGet, _1, _2, Bool(true)); + + m_query[CapType::PaperDetectable] = msgSupportGetAll; + m_caps[CapType::PaperDetectable] = std::bind(enmGet, _1, _2, Bool(true)); + + m_query[CapType::FeederEnabled] = msgSupportGetAllSetReset; + m_caps[CapType::FeederEnabled] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_bFeederEnabled)); + return success(); + case Msg::GetCurrent: + data = Capability::createOneValue(m_bFeederEnabled); + return success(); + case Msg::Reset: + case Msg::GetDefault: + data = Capability::createOneValue(true); + m_bFeederEnabled = true; + return success(); + + case Msg::Set: { + auto feederen = data.currentItem(); + m_bFeederEnabled = feederen; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::Duplex] = msgSupportGetAll; + m_caps[CapType::Duplex] = std::bind(oneValGet, _1, _2, Duplex::OnePass); + + m_query[CapType::DuplexEnabled] = msgSupportGetAllSetReset; + m_caps[CapType::DuplexEnabled] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_scanparam->is_duplex)); + return success(); + + case Msg::Reset: + m_scanparam->is_duplex = true; + case Msg::GetCurrent: + data = Capability::createOneValue(m_scanparam->is_duplex); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(false); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->is_duplex=mech; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::AutoFeed] = msgSupportGetAllSetReset; + m_caps[CapType::AutoFeed] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_bAutoFeed)); + return success(); + + case Msg::Reset: + m_bAutoFeed = true; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_bAutoFeed); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(true); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + m_bAutoFeed = mech; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IImageFileFormat] = msgSupportGetAllSetReset; + m_caps[CapType::IImageFileFormat] = [this](Msg msg, Capability& data) -> Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { ImageFileFormat::Bmp, ImageFileFormat::Tiff}, m_capImageFileFormat == ImageFileFormat::Bmp? 0 : 1, 0); + return success(); + + case Msg::Reset: + m_capImageFileFormat =ImageFileFormat::Bmp; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_capImageFileFormat); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(ImageFileFormat::Bmp); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + if (mech == ImageFileFormat::Bmp || mech == ImageFileFormat::Tiff) { + m_capImageFileFormat =mech; + return success(); + } + else { + return badValue(); + } + } + + default: + return capBadOperation(); + } + }; + + //custom define + m_query[CapType::IAutomaticDeskew] = msgSupportGetAllSetReset; + m_caps[CapType::IAutomaticDeskew] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_scanparam->autodescrew)); + return success(); + case Msg::Reset: + m_scanparam->autodescrew = true; + case Msg::GetCurrent: + data = Capability::createOneValue(m_scanparam->autodescrew); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(true); + return success(); + + case Msg::Set: { + auto atuodsw = data.currentItem(); + m_scanparam->autodescrew = (bool)atuodsw; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IAutomaticRotate] = msgSupportGetAllSetReset; + m_caps[CapType::IAutomaticRotate] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_scanparam->is_autotext)); + case Msg::Reset: + m_scanparam->is_autotext = false; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_scanparam->is_autotext); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(false); + return success(); + + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->is_autotext = (bool)mech; + return success(); + } + + default: + return capBadOperation(); + } + }; + + m_query[CapType::IAutomaticCropUsesFrame] = msgSupportGetAllSetReset; + m_caps[CapType::IAutomaticCropUsesFrame] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration( + { Bool(), Bool(true) }, Bool(m_scanparam->is_autocrop)); + return success(); + case Msg::Reset: + m_scanparam->is_autocrop = false; + // fallthrough + case Msg::GetCurrent: + data = Capability::createOneValue(m_scanparam->is_autocrop); + return success(); + + case Msg::GetDefault: + data = Capability::createOneValue(false); + return success(); + + case Msg::Set: { + auto autocrop = data.currentItem(); + m_scanparam->is_autocrop = (bool)autocrop; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IAutoDiscardBlankPages] = msgSupportGetAllSetReset; + m_caps[CapType::IAutoDiscardBlankPages] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration({ DiscardBlankPages::Disabled,DiscardBlankPages::Auto}, + m_scanparam->is_autodiscradblank_normal?1:0, + 0); + return success(); + case Msg::Reset: + m_scanparam->is_autodiscradblank_normal = false; + case Msg::GetCurrent: + data = Capability::createOneValue(m_scanparam->is_autodiscradblank_normal? DiscardBlankPages::Auto: DiscardBlankPages::Disabled); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(DiscardBlankPages::Disabled); + return success(); + case Msg::Set:{ + auto mech = data.currentItem(); + m_scanparam->is_autodiscradblank_normal = mech == DiscardBlankPages::Auto; + return success(); + } + default: + return capBadOperation(); + } + }; + + /*costom caps*/ + //հҳƱ + m_query[(CapType)(CapTypeEx::TwEx_IAutoDiscardBlankVince)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IAutoDiscardBlankVince)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)((CapType)(CapTypeEx::TwEx_IAutoDiscardBlankVince)), { Bool(),Bool(true) }, Bool(m_scanparam->is_autodiscradblank_vince), 0); + return success(); + case Msg::Reset: + m_scanparam->is_autodiscradblank_vince = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)((CapType)(CapTypeEx::TwEx_IAutoDiscardBlankVince)), m_scanparam->is_autodiscradblank_vince); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)((CapType)(CapTypeEx::TwEx_IAutoDiscardBlankVince)), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->is_autodiscradblank_vince = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[(CapType)(CapTypeEx::TwEx_IBackRotate180)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IBackRotate180)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IBackRotate180), { Bool(),Bool(true) }, Bool(m_scanparam->is_backrotate180), 0); + return success(); + case Msg::Reset: + m_scanparam->is_backrotate180 = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IBackRotate180), m_scanparam->is_backrotate180); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IBackRotate180), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->is_backrotate180 = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + //ڿ + m_query[(CapType)(CapTypeEx::TwEx_IFillBackground)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IFillBackground)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IFillBackground), { Bool(),Bool(true) }, Bool(m_scanparam->fillbackground), 0); + return success(); + case Msg::Reset: + m_scanparam->fillbackground = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillBackground), m_scanparam->fillbackground); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillBackground), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->fillbackground = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + // + m_query[(CapType)(CapTypeEx::TwEx_IFillHole)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IFillHole)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IFillHole), { Bool(),Bool(true) }, Bool(m_scanparam->fillhole.is_fillhole), 0); + return success(); + case Msg::Reset: + m_scanparam->fillhole.is_fillhole = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillHole), m_scanparam->fillhole.is_fillhole); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillHole), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->fillhole.is_fillhole = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[(CapType)(CapTypeEx::TwEx_IFillHoleRatio)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IFillHoleRatio)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillHoleRatio), m_scanparam->fillhole.fillholeratio); + return success(); + case Msg::Reset: + m_scanparam->fillhole.fillholeratio = 10; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillHoleRatio), m_scanparam->fillhole.fillholeratio); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IFillHoleRatio), Int32(10)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if (mech > 0 && mech < 50) { + m_scanparam->fillhole.fillholeratio = (float)mech; + return success(); + } + return badValue(); + } + default: + return capBadOperation(); + } + }; + + // + m_query[(CapType)(CapTypeEx::TwEx_IMultiOutputRed)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IMultiOutputRed)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IMultiOutputRed), { Bool(),Bool(true) }, Bool(m_scanparam->multi_output_red), 0); + return success(); + case Msg::Reset: + m_scanparam->multi_output_red = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IMultiOutputRed), m_scanparam->multi_output_red); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IMultiOutputRed), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->multi_output_red = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IFilter] = msgSupportGetAllSetReset; + m_caps[CapType::IFilter] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration({Filter::Red,Filter::Green,Filter::Blue,Filter::None }, + m_scanparam->filter, + 0); + return success(); + case Msg::Reset: + m_scanparam->filter = (byte)Filter::None; + case Msg::GetCurrent: + data = Capability::createOneValue((Filter)m_scanparam->filter); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(Filter::None); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if(mech == Filter::None|| mech == Filter::Red||mech == Filter::Green ||mech ==Filter::Blue){ + m_scanparam->filter =(byte) mech; + return success(); + } + return badValue(); + } + default: + return capBadOperation(); + } + }; + + //ɫǿ + m_query[(CapType)(CapTypeEx::TwEx_IEnhanceColor)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_IEnhanceColor)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IEnhanceColor), { Enchace_Color::Enhance_None,Enchace_Color::Enhance_Red,Enchace_Color::Enhance_Green,Enchace_Color::Enhance_Blue},m_scanparam->enhance_color,0); + return success(); + case Msg::Reset: + m_scanparam->enhance_color = Enchace_Color::Enhance_None; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IEnhanceColor), (Enchace_Color)(m_scanparam->enhance_color)); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_IEnhanceColor), Enchace_Color::Enhance_None); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->enhance_color =(byte)mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[(CapType)(CapTypeEx::TwEx_Sharpen)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_Sharpen)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_IEnhanceColor), { SharpenBlur::Sharpen_None,SharpenBlur::Sharpen_Normal,SharpenBlur::Sharpen_More,SharpenBlur::Sharpen_Blur,SharpenBlur::Sharpen_Blur_More }, m_scanparam->sharpen, 0); + return success(); + case Msg::Reset: + m_scanparam->sharpen = SharpenBlur::Sharpen_None; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_Sharpen), (SharpenBlur)(m_scanparam->sharpen)); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_Sharpen), SharpenBlur::Sharpen_None); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->sharpen = (byte)mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + /* Աȶ gamma range Range */ + m_query[CapType::IBrightness] = msgSupportGetAllSetReset; + m_caps[CapType::IBrightness] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data=Capability::createRange(Fix32(-1000.0f), Fix32(1000.0f), Fix32(333.3f), Fix32(m_scanparam->brightness), Fix32(0.0)); + return success(); + case Msg::Reset: + m_scanparam->brightness =0.0f; + case Msg::GetCurrent: + data = Capability::createOneValue(Fix32(m_scanparam->brightness)); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(Fix32(0.0f)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if (mech > 1000.0f || mech < -1000.0f) + return badValue(); + m_scanparam->brightness = (float)mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IContrast] = msgSupportGetAllSetReset; + m_caps[CapType::IContrast] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createRange(Fix32(-1000.0f), Fix32(1000.0f), Fix32(333.3f), Fix32(m_scanparam->contrast), Fix32(0.0)); + return success(); + case Msg::Reset: + m_scanparam->contrast = 0.0f; + case Msg::GetCurrent: + data = Capability::createOneValue(Fix32(m_scanparam->contrast)); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(Fix32(0.0f)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if (mech > 1000.0f || mech < -1000.0f) + return badValue(); + m_scanparam->contrast = (float)mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[CapType::IGamma] = msgSupportGetAllSetReset; + m_caps[CapType::IGamma] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createRange(Fix32(0.0f), Fix32(5.0f), Fix32(1.0f), Fix32(m_scanparam->gamma), Fix32(1.0)); + return success(); + case Msg::Reset: + m_scanparam->gamma = 1.0f; + case Msg::GetCurrent: + data = Capability::createOneValue(Fix32(m_scanparam->gamma)); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(Fix32(0.0f)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if (mech > 5.0f || mech < 0.0f) + return badValue(); + m_scanparam->gamma = (float)mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + + //m_query[(CapType)(CapTypeEx::TwEx_DBAreaNum)] = msgSupportGetAllSetReset; + //m_caps[(CapType)(CapTypeEx::TwEx_DBAreaNum)] = [this](Msg msg, Capability& data)->Result { + // switch (msg) { + // case Msg::Get: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBAreaNum), m_scanparam->areanum); + // return success(); + // case Msg::Reset: + // m_scanparam->areanum = 8; + // case Msg::GetCurrent: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBAreaNum), m_scanparam->areanum); + // return success(); + // case Msg::GetDefault: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBAreaNum), UInt16(8)); + // return success(); + // case Msg::Set: { + // auto mech = data.currentItem(); + // if (mech >= 5 && mech <= 40) { + // m_scanparam->areanum = mech; + // return success(); + // } + // return badValue(); + // } + // default: + // return capBadOperation(); + // } + //}; + + //m_query[(CapType)(CapTypeEx::TwEx_DBDevnMax)] = msgSupportGetAllSetReset; + //m_caps[(CapType)(CapTypeEx::TwEx_DBDevnMax)] = [this](Msg msg, Capability& data)->Result { + // switch (msg) { + // case Msg::Get: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBDevnMax), m_scanparam->devnmax); + // return success(); + // case Msg::Reset: + // m_scanparam->devnmax = 200; + // case Msg::GetCurrent: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBDevnMax), m_scanparam->devnmax); + // return success(); + // case Msg::GetDefault: + // data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_DBDevnMax), UInt16(200)); + // return success(); + // case Msg::Set: { + // auto mech = data.currentItem(); + // if (mech >= 150 && mech <= 400) { + // m_scanparam->devnmax = mech; + // return success(); + // } + // return badValue(); + // } + // default: + // return capBadOperation(); + // } + //}; + + /*ΪӲЭ*/ + m_query[(CapType)(CapTypeEx::TwEx_ScrewDetectEnable)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_ScrewDetectEnable)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_ScrewDetectEnable), { Bool(),Bool(true) }, Bool(m_scanparam->hardwarecaps.en_skrewdetect), 0); + return success(); + case Msg::Reset: + m_scanparam->hardwarecaps.en_skrewdetect = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_ScrewDetectEnable), m_scanparam->hardwarecaps.en_skrewdetect); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_ScrewDetectEnable), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->hardwarecaps.en_skrewdetect = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + m_query[(CapType)(CapTypeEx::TwEx_ScrewLevel)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_ScrewLevel)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_ScrewLevel), m_scanparam->hardwarecaps.skrewdetectlevel); + return success(); + case Msg::Reset: + m_scanparam->hardwarecaps.skrewdetectlevel = 3; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_ScrewLevel), m_scanparam->hardwarecaps.skrewdetectlevel); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_ScrewLevel), UInt8(3)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + if (mech >= 1 && mech <= 5) { + m_scanparam->hardwarecaps.skrewdetectlevel = mech; + return success(); + } + return badValue(); + } + default: + return capBadOperation(); + } + }; + + //װ + m_query[(CapType)(CapTypeEx::TwEx_StableDetectEnable)] = msgSupportGetAllSetReset; + m_caps[(CapType)(CapTypeEx::TwEx_StableDetectEnable)] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration((CapType)(CapTypeEx::TwEx_StableDetectEnable), { Bool(),Bool(true) }, Bool(m_scanparam->hardwarecaps.en_stapledetect), 0); + return success(); + case Msg::Reset: + m_scanparam->hardwarecaps.en_stapledetect = false; + case Msg::GetCurrent: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_StableDetectEnable), m_scanparam->hardwarecaps.en_stapledetect); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue((CapType)(CapTypeEx::TwEx_StableDetectEnable), Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->hardwarecaps.en_stapledetect = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + + //˫ż ٷ׼ Э޸Ϊbool + m_query[CapType::DoubleFeedDetection] = msgSupportGetAllSetReset; + m_caps[CapType::DoubleFeedDetection] = [this](Msg msg, Capability& data)->Result { + switch (msg) { + case Msg::Get: + data = Capability::createEnumeration(CapType::DoubleFeedDetection, { Bool(),Bool(true) }, Bool(m_scanparam->hardwarecaps.en_doublefeed), 0); + return success(); + case Msg::Reset: + m_scanparam->hardwarecaps.en_doublefeed = false; + case Msg::GetCurrent: + data = Capability::createOneValue(CapType::DoubleFeedDetection, m_scanparam->hardwarecaps.en_doublefeed); + return success(); + case Msg::GetDefault: + data = Capability::createOneValue(CapType::DoubleFeedDetection, Bool(false)); + return success(); + case Msg::Set: { + auto mech = data.currentItem(); + m_scanparam->hardwarecaps.en_doublefeed = mech; + return success(); + } + default: + return capBadOperation(); + } + }; + return success(); +} + +Result HuagaoDs::identityCloseDs(const Identity&){ + // no need to explicitly release any resources if using RAII + // TWPP will free the whole source on its own after this method + guiIndicator.reset(); + guiTwain.reset(); + guiBridge.reset(); + scanner.reset(); + return success(); +} + +Result HuagaoDs::pendingXfersGet(const Identity&, PendingXfers& data){ + data.setCount(m_pendingXfers); + return success(); +} + +Result HuagaoDs::pendingXfersEnd(const Identity&, PendingXfers& data){ + //!< end xfer if set count 0 + int ret= scanner->aquire_bmpdata(bmpData); + if (ret !=0) { + scanner->Set_ErrorCode(0); + guiIndicator.reset(); + if (ret != -1) { + MessageBox(guiTwain ? guiTwain->m_hWnd : NULL, noticeMsgMap[ret], _T("ʾ"), MB_SYSTEMMODAL | MB_OK | MB_ICONINFORMATION); + } + m_pendingXfers = 0; + if (guiTwain.get()) { + ((CTwainUI*)(guiTwain.get()))->EnableID_OKorID_Cancel(true); + } + + } + else { + m_pendingXfers = 1; + } +#ifdef LOG_NORMAL + FileTools::write_log("out.txt", "m_pendingXfers " + std::to_string(m_pendingXfers)); +#endif // LOG_NORMAL + + data.setCount(m_pendingXfers); + return success(); +} + +Result HuagaoDs::pendingXfersReset(const Identity&, PendingXfers& data){ + data.setCount(0); + return success(); +} + +Result HuagaoDs::setupMemXferGet(const Identity&, SetupMemXfer& data){ + auto bpl = bytesPerLine(); + auto max = bpl * static_cast(header()->biHeight); + + data.setMinSize(bpl); + data.setPreferredSize(max); + data.setMaxSize(max); + return success(); +} + +Result HuagaoDs::userInterfaceDisable(const Identity&, UserInterface& ui){ + guiTwain.reset(); + +#if TWPP_DETAIL_OS_WIN + guiBridge.reset(); +#endif + return success(); +} +Result HuagaoDs::userInterfaceEnable(const Identity&, UserInterface& ui){ + m_pendingXfers = 1; + m_memXferYOff = 0; + + if (!ui.showUi()){ + // this is an exception when we want to set state explicitly, notifyXferReady can be called only in enabled state + // with hidden UI, the usual workflow DsState::Enabled -> notifyXferReady() -> DsState::XferReady is a single step + setState(DsState::Enabled); + if(startScan() == success()){ + m_pendingXfers = 1; + auto notified = notifyXferReady(); + return success(); + } + else { + m_pendingXfers = 0; + setState(DsState::Open); + return seqError(); + } + } + + return showTwainUI(ui); +} + +Result HuagaoDs::userInterfaceEnableUiOnly(const Identity&, UserInterface& ui){ + // as a minimal source, we do not support GUI that just saves settings + return showTwainUI(ui, true); +} + +Result HuagaoDs::imageInfoGet(const Identity&, ImageInfo& data){ + // our image does not change + auto dib = header(); + data.setBitsPerPixel(static_cast(dib->biBitCount)); + data.setHeight(dib->biHeight); + //dib->biClrUseddib->biClrUsed==2?T + data.setPixelType(dib->biClrUsed == 2 ? PixelType::BlackWhite : (dib->biClrUsed == 256 ? PixelType::Gray : PixelType::Rgb)); + data.setPlanar(false); + data.setWidth(dib->biWidth); + data.setXResolution(m_scanparam->resolution_dst); + data.setYResolution(m_scanparam->resolution_dst); + + switch (dib->biClrUsed) + { + case 2: + case 256: + data.setSamplesPerPixel(1); + data.bitsPerSample()[0] = 8; + break; + case 0: + data.setSamplesPerPixel(3); + data.bitsPerSample()[0] = 8; + data.bitsPerSample()[1] = 8; + data.bitsPerSample()[2] = 8; + default: + break; + } + return success(); +} + +Result HuagaoDs::imageLayoutGet(const Identity&, ImageLayout& data){ + // our image does not change + auto dib = header(); + + data.setDocumentNumber(1); + data.setFrameNumber(1); + data.setPageNumber(1); + data.setFrame(Frame(0, 0, static_cast(dib->biWidth) / RESOLUTIONX, static_cast(dib->biHeight) / RESOLUTIONX)); + return success(); +} + +Result HuagaoDs::imageLayoutGetDefault(const Identity& origin, ImageLayout& data){ + return imageLayoutGet(origin, data); +} + +Result HuagaoDs::imageLayoutSet(const Identity& origin, ImageLayout& lay){ + // we dont support setting image frame + + ImageLayout def; + imageLayoutGetDefault(origin, def); + + return lay.frame() == def.frame() ? success() : badValue(); +} + +Result HuagaoDs::imageLayoutReset(const Identity& origin, ImageLayout& data){ + return imageLayoutGet(origin, data); +} + +Result HuagaoDs::imageMemXferGet(const Identity& origin, ImageMemXfer& data){ + if (!m_pendingXfers){ + return seqError(); + } + + // we can call our TWPP methods, but be careful about states + SetupMemXfer setup; + setupMemXferGet(origin, setup); + + // just a simple stored BMP image + auto dib = header(); + auto bpl = bytesPerLine(); + auto memSize = data.memory().size(); + if (memSize > setup.maxSize() || memSize < setup.minSize()){ + return badValue(); + } + + auto maxRows = memSize / bpl; + auto rows = std::min(maxRows, static_cast(dib->biHeight) - m_memXferYOff); + if (rows == 0){ + return seqError(); // image already transfered in this session + } + + data.setBytesPerRow(bpl); + data.setColumns(static_cast(dib->biWidth)); + data.setRows(rows); + data.setBytesWritten(rows * bpl); + data.setXOffset(0); + data.setYOffset(m_memXferYOff); + data.setCompression(Compression::None); + + auto lock = data.memory().data(); + char* out = lock.data(); + + // bottom-up BMP -> top-down memory transfer + auto begin = bmpEnd() - (bpl * (m_memXferYOff + 1)); + for (UInt32 i = 0; i < rows; i++){ + // copy bytes + std::copy(begin, begin + bpl, out); + + char* line = out; + out += bpl; + begin -= bpl; + + // BGR BMP -> RGB memory transfer + for ( ; line + 3 < out; line += 3){ + std::swap(line[0], line[2]); + } + } + + m_memXferYOff += rows; + + if (m_memXferYOff >= static_cast(std::abs(dib->biHeight))){ + m_pendingXfers = 0; + return {ReturnCode::XferDone, ConditionCode::Success}; + } + + return success(); +} +#ifdef LOG_NORMAL +static int xtfer = 0; +#endif + +Result HuagaoDs::imageNativeXferGet(const Identity&, ImageNativeXfer& data){ + if (!m_pendingXfers){ + return seqError(); + } + if (data) + data.release(); + // it does not get easier than that if we already have BMP + data = ImageNativeXfer(bmpSize()); + std::copy(bmpBegin(), bmpEnd(), data.data().data()); +#ifdef LOG_NORMAL + FileTools::write_log("out.txt", "imageNativeXferGet "+ std::to_string(++xtfer)); +#endif // LOG + + return {ReturnCode::XferDone, ConditionCode::Success}; +} + +Twpp::Result HuagaoDs::pendingXfersStopFeeder(const Identity& origin, PendingXfers& data) +{ + if (!scanner.get()) + return seqError(); + if (scanner->IsConnected()) { + scanner->Stop_scan(); + } + data.setCount(scanner->Get_IsImageQueueEmpty() ? 0 : 1); + return success(); +} + +Twpp::Result HuagaoDs::showTwainUI(Twpp::UserInterface& ui, bool bUiOnly) +{ + // as a minimal source, we do not support GUI that just saves settings + if (ui.parent()) { + guiBridge.reset(new CDialog()); + HWND appWindow = static_cast(ui.parent().raw()); + guiBridge->Create(IDD_BACK, CWnd::FromHandle(appWindow)); + HWND bridgeWindow = guiBridge->GetSafeHwnd(); + long bridgeFlags = GetWindowLong(bridgeWindow, GWL_STYLE); + SetWindowLong(bridgeWindow, GWL_STYLE, bridgeFlags | WS_CHILD); + SetParent(bridgeWindow, appWindow); + + //if (ui.modalUi()) { + // long appFlags = GetWindowLong(appWindow, GWL_STYLE); + // SetWindowLong(appWindow, GWL_STYLE, appFlags | WS_DISABLED); + //} + } + + //!< show ui to scan button push + auto scanFunction = [this](const GScanCap& caps) { + m_pendingXfers = 1; + m_scanparam.reset(new GScanCap(caps)); + //scanner->config_params(*m_scanparam); + if (startScan() == success()) { + notifyXferReady(); + } + else { + m_pendingXfers = 0; + } + }; + + //!< ui only to confirm button push + auto confirmFunction = [this](const GScanCap& caps) { + m_scanparam.reset(new GScanCap(caps)); + notifyCloseOk(); + }; + + //!< cancel button push + auto cancelFunction = [this]() { + notifyCloseCancel(); + }; + + CWnd* parent = guiBridge.get(); + + TwGlue glue = {scanFunction, cancelFunction }; + TwGlue glueUiOnly = {confirmFunction, cancelFunction }; + guiTwain.reset(new CTwainUI(bUiOnly ? glueUiOnly : glue)); + guiTwain->Create(IDD_TWAINUI, parent); + guiTwain->SetDlgItemText(IDC_CONFIRM, bUiOnly ? _T("ȷ") : _T("ɨ")); + guiTwain->ShowWindow(SW_SHOWNORMAL); + return success(); +} + +const BITMAPINFOHEADER* HuagaoDs::header() const noexcept{ + return reinterpret_cast(bmpData.data() + sizeof(BITMAPFILEHEADER)); +} + +UInt32 HuagaoDs::bytesPerLine() const noexcept{ + auto dib = header(); + return static_cast(dib->biWidth * dib->biBitCount + 31) / 32 * 4; +} + +UInt32 HuagaoDs::bmpSize() const noexcept{ + return static_cast(bmpData.size()) - sizeof(BITMAPFILEHEADER); +} + +const char* HuagaoDs::bmpBegin() const noexcept{ + return (const char*)bmpData.cbegin()._Ptr + sizeof(BITMAPFILEHEADER); +} + +const char* HuagaoDs::bmpEnd() const noexcept{ + return (const char*)bmpData.cend()._Ptr; +} + +void HuagaoDs::initGScanCap() +{ + m_scanparam->autodescrew = 1; + m_scanparam->brightness = 0.0f; + m_scanparam->contrast = 0.0f; + m_scanparam->fillbackground = 1; + m_scanparam->fillhole.is_fillhole = 1; + m_scanparam->fillhole.fillholeratio = 0.1f; + m_scanparam->filter = (byte)Filter::None; + m_scanparam->sharpen = (byte)SharpenBlur::Sharpen_None; + m_scanparam->gamma = 1.0; + m_scanparam->hardwarecaps.capturepixtype = (int)(PixelType::Gray); + m_scanparam->hardwarecaps.en_doublefeed = 1; + m_scanparam->hardwarecaps.en_skrewdetect = 0; + m_scanparam->hardwarecaps.en_stapledetect = 0; + m_scanparam->hardwarecaps.skrewdetectlevel = 3; + m_scanparam->is_autocontrast = 0; + m_scanparam->is_autocrop = 0; + m_scanparam->is_autodiscradblank_normal = 0; + m_scanparam->is_autodiscradblank_vince = 0; + //m_scanparam->areanum = 8; + //m_scanparam->devnmax = 200; + m_scanparam->is_backrotate180 = 0; + m_scanparam->is_duplex = 1; + m_scanparam->multi_output_red = 0; + m_scanparam->papertype = 11;//A3 + m_scanparam->paperAlign = PaperAlign::Rot0; + m_scanparam->resolution_native = 200.0f; + m_scanparam->resolution_dst = 200.0f; + m_scanparam->scannum = -1; + m_scanparam->is_autotext = 0; + m_scanparam->enhance_color = 0; + m_scanparam->pixtype= (int)(PixelType::Gray); + ScanRect rect = { 0 };//to be define + m_scanparam->scanrect = rect; + m_scanparam->threshold = 128.0f; +} + +void HuagaoDs::updataGscanCap() +{ + JsonConfig js; + CONFIGPARAMS cfs=js.ReadDefaultConfig(); + m_scanparam->autodescrew = cfs.EnAutoDescrew?1:0; + m_scanparam->brightness = cfs.Brightness; + m_scanparam->contrast = cfs.Contrast; + m_scanparam->fillbackground = cfs.EnFillBlack?1:0; + m_scanparam->fillhole.is_fillhole = cfs.EnOutHole?1:0; + m_scanparam->fillhole.fillholeratio = cfs.OutHoleRatio; + m_scanparam->sharpen = (SharpenBlur)cfs.Sharpen; + if (cfs.Filter) { + if (cfs.Filter <= 3) { + m_scanparam->filter = filterMaps[cfs.Filter]; + m_scanparam->enhance_color = 0;//ɫǿ none + } + else { + m_scanparam->filter = (byte)Filter::None;//ɫ + m_scanparam->enhance_color = filterMaps[cfs.Filter]; + } + } + else { + m_scanparam->filter = (byte)Filter::None; + m_scanparam->enhance_color = EnchaceColor::Enhance_None; + } + + m_scanparam->gamma =cfs.Gamma; + m_scanparam->hardwarecaps.en_doublefeed = cfs.EnUltrasonicDetect?1:0; + m_scanparam->hardwarecaps.en_skrewdetect = cfs.EnScrewDetect?1:0; + m_scanparam->hardwarecaps.en_stapledetect = cfs.EnBindingDetect?1:0; + m_scanparam->hardwarecaps.skrewdetectlevel = cfs.ScrewDetectLevel; + m_scanparam->is_autocontrast = cfs.EnAutoContrast?1:0; + m_scanparam->is_autocrop = cfs.EnAutoCrop?1:0; + m_scanparam->is_autodiscradblank_normal = cfs.EnDiscardBlank?1:0; + m_scanparam->is_autodiscradblank_vince = cfs.EnDiscardBlankVince?1:0; + m_scanparam->is_backrotate180 = cfs.EnBackRotate180?1:0; + m_scanparam->is_duplex = cfs.Duplex>=1?1:0; + m_scanparam->multi_output_red = cfs.EnMultiOutPutR?1:0; + PaperStatus ps = paperStatusMap[cfs.PaperSize]; + m_scanparam->papertype = ps.Paper;//A3 + m_scanparam->paperAlign =(PaperAlign)ps.Orentate; + m_scanparam->resolution_native =200.0f ; + m_scanparam->resolution_dst = resolutions[cfs.Resolution]; + m_scanparam->scannum = cfs.ScanCount; + m_scanparam->is_autotext = cfs.Orentation==4?1:0; + if (cfs.Orentation != 4) { + m_scanparam->imageRotateDegree = rotateDegrees[cfs.Orentation]; + } + m_scanparam->pixtype = colorModes[cfs.Pixtype]; + if (cfs.Filter || cfs.EnMultiOutPutR) { + m_scanparam->hardwarecaps.capturepixtype = (byte)(PixelType::Rgb); + } + else { + m_scanparam->hardwarecaps.capturepixtype = m_scanparam->pixtype; + } + ScanRect rect = { 0 };//to be define + m_scanparam->scanrect = rect; + m_scanparam->threshold = 128.0f; +} + +Twpp::Result HuagaoDs::startScan() +{ + if (!scanner->IsConnected()) + return checkDeviceOnline(); + + scanner->ResetScanner(); + scanner->config_params(*m_scanparam); + if (m_bIndicator) { + //!< cancel button push + auto stopFunc = [this]() { + scanner->Stop_scan(); + guiIndicator.reset();//ȡɨ رսָʾ + }; + guiIndicator.reset(new CIndicatorDlg(stopFunc)); + guiIndicator->Create(IDD_INDICATOR, guiTwain ? guiTwain.get() : guiBridge.get()); + guiIndicator->ShowWindow(SW_SHOWNORMAL); + } + scanner->Scanner_StartScan(m_scanparam->scannum); + if (bmpData.size() > 0) + bmpData.clear(); + + if(guiTwain.get()){ + ((CTwainUI*)(guiTwain.get()))->EnableID_OKorID_Cancel(false); + } + + int retCode = scanner->aquire_bmpdata(bmpData); + if (retCode!=0) { + scanner->Set_ErrorCode(0); + guiIndicator.reset(); + if(retCode!=-1) + MessageBox(guiTwain? guiTwain->m_hWnd:NULL, noticeMsgMap[retCode], _T("ʾ"), MB_SYSTEMMODAL | MB_OK | MB_ICONINFORMATION); + + if (guiTwain.get()) { + ((CTwainUI*)(guiTwain.get()))->EnableID_OKorID_Cancel(true); + } + return seqError(); + } + + if (bmpData.size()>0) { + return success(); + } + else { + guiIndicator.reset(); + if (guiTwain.get()) { + ((CTwainUI*)(guiTwain.get()))->EnableID_OKorID_Cancel(true); + } + return seqError(); + } +} diff --git a/huagao/huagaods.hpp b/huagao/huagaods.hpp new file mode 100644 index 00000000..04c54057 --- /dev/null +++ b/huagao/huagaods.hpp @@ -0,0 +1,93 @@ +#ifndef SIMPLEDS_HPP +#define SIMPLEDS_HPP + +#include +#include +#include +#include + +namespace std { + +template<> +struct hash { + size_t operator()(Twpp::CapType cap) const{ + return hash()(static_cast(cap)); + } +}; + +} + +typedef struct GScanCap GScanCap; + +class HuagaoDs : public Twpp::SourceFromThis { + +public: + HuagaoDs(); + virtual ~HuagaoDs(); + static const Twpp::Identity& defaultIdentity() noexcept; + + // SourceFromThis interface +protected: + typedef Twpp::SourceFromThis Base; + + virtual Twpp::Result capabilityGet(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result capabilityGetCurrent(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result capabilityGetDefault(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result capabilityQuerySupport(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result capabilityReset(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result capabilityResetAll(const Twpp::Identity& origin) override; + virtual Twpp::Result capabilitySet(const Twpp::Identity& origin, Twpp::Capability& data) override; + virtual Twpp::Result eventProcess(const Twpp::Identity& origin, Twpp::Event& data) override; + virtual Twpp::Result identityOpenDs(const Twpp::Identity& origin) override; + virtual Twpp::Result identityCloseDs(const Twpp::Identity& origin) override; + virtual Twpp::Result pendingXfersGet(const Twpp::Identity& origin, Twpp::PendingXfers& data) override; + virtual Twpp::Result pendingXfersEnd(const Twpp::Identity& origin, Twpp::PendingXfers& data) override; + virtual Twpp::Result pendingXfersReset(const Twpp::Identity& origin, Twpp::PendingXfers& data) override; + virtual Twpp::Result setupMemXferGet(const Twpp::Identity& origin, Twpp::SetupMemXfer& data) override; + virtual Twpp::Result userInterfaceDisable(const Twpp::Identity& origin, Twpp::UserInterface& data) override; + virtual Twpp::Result userInterfaceEnable(const Twpp::Identity& origin, Twpp::UserInterface& data) override; + virtual Twpp::Result userInterfaceEnableUiOnly(const Twpp::Identity& origin, Twpp::UserInterface& data) override; + virtual Twpp::Result imageInfoGet(const Twpp::Identity& origin, Twpp::ImageInfo& data) override; + virtual Twpp::Result imageLayoutGet(const Twpp::Identity& origin, Twpp::ImageLayout& data) override; + virtual Twpp::Result imageLayoutGetDefault(const Twpp::Identity& origin, Twpp::ImageLayout& data) override; + virtual Twpp::Result imageLayoutSet(const Twpp::Identity& origin, Twpp::ImageLayout& data) override; + virtual Twpp::Result imageLayoutReset(const Twpp::Identity& origin, Twpp::ImageLayout& data) override; + virtual Twpp::Result imageMemXferGet(const Twpp::Identity& origin, Twpp::ImageMemXfer& data) override; + virtual Twpp::Result imageNativeXferGet(const Twpp::Identity& origin, Twpp::ImageNativeXfer& data) override; + virtual Twpp::Result pendingXfersStopFeeder(const Twpp::Identity& origin, Twpp::PendingXfers& data) override; + virtual Twpp::Result call(const Twpp::Identity& origin, Twpp::DataGroup dg, Twpp::Dat dat, Twpp::Msg msg, void* data) override; + +private: + Twpp::Result showTwainUI(Twpp::UserInterface& data, bool bUiOnly = false); + Twpp::Result startScan(); + const BITMAPINFOHEADER* header() const noexcept; + Twpp::UInt32 bytesPerLine() const noexcept; + Twpp::UInt32 bmpSize() const noexcept; + const char* bmpBegin() const noexcept; + const char* bmpEnd() const noexcept; + void initGScanCap(); + void updataGscanCap(); + Twpp::Result capCommon(const Twpp::Identity& origin, Twpp::Msg msg, Twpp::Capability& data); + + std::unordered_map> m_caps; + std::unordered_map m_query; + + Twpp::UInt32 m_memXferYOff = 0; + Twpp::UInt16 m_pendingXfers = 0; + + Twpp::Int16 m_capXferCount = -1; + Twpp::Fix32 m_brightness = 0.0f; + Twpp::XferMech m_capXferMech = Twpp::XferMech::Native; + Twpp::PixelType m_capPixelType = Twpp::PixelType::Rgb; + bool m_bIndicator = true; + bool m_bFeederEnabled = true; + bool m_bAutoFeed = true; + Twpp::ImageFileFormat m_capImageFileFormat = Twpp::ImageFileFormat::Bmp; + + std::vector bmpData; + std::unique_ptr m_scanparam; + + +}; + +#endif // SIMPLEDS_HPP diff --git a/huagao/huagaotwds.pro b/huagao/huagaotwds.pro new file mode 100644 index 00000000..e11c4fa0 --- /dev/null +++ b/huagao/huagaotwds.pro @@ -0,0 +1,127 @@ +# compile with 32bit compiler +# place the resulting file "simpleds.ds" into \Windows\twain_32 +# do not forget to have all dependencies present in the PATH + +QT -= core gui + +TARGET = huagaoscands +TARGET_EXT = .ds +TEMPLATE = lib + +CONFIG += c++11 +DEFINES += TWPP_IS_DS _AFXDLL +INCLUDEPATH += $$PWD/../ $$PWD/../twpp $$PWD/../3rdparty/opencv/include $$PWD/../3rdparty/nick $$PWD/../3rdparty/turbojpeg/include $$PWD/../3rdparty/hgOCR/include +LIBS += -L$$PWD/../3rdparty/opencv/x86/lib -L$$PWD/../3rdparty/turbojpeg/x86/lib -L$$PWD/../3rdparty/hgOCR/x86/lib + +CONFIG(release, debug|release){ + LIBS += -lopencv_world346 -lturbojpeg -lHG_OCR4 +} +CONFIG(debug, debug|release){ + LIBS += -lopencv_world346d -lturbojpeg -lHG_OCR4 +} + +DEF_FILE = exports.def + +SOURCES += huagaods.cpp \ + CAboutDlg.cpp \ + CBasicPage.cpp \ + CBrightnessPage.cpp \ + CFeedPaperPage.cpp \ + CImageProcPage.cpp \ + CIndicatorDlg.cpp \ + CSaveConfigDlg.cpp \ + CTwainMutex.cpp \ + CTwainUI.cpp \ + Device/GDevice.cpp \ + Device/GDeviceLists.cpp \ + Device/GScan200.cpp \ + Device/GScanO200.cpp \ + Device/GScanVirtual.cpp \ + Device/ImageMatQueue.cpp \ + Device/ImageMultiOutput.cpp \ + Device/JpegBuffer.cpp \ + Device/PaperSize.cpp \ + Device/PublicFunc.cpp \ + Device/UsbScanEx.cpp \ + Device/config_new.cpp \ + Device/GScan.cpp \ + Device/jpeglib.cpp \ + Device/scn_config.cpp \ + Device/cJSON.cpp \ + Device/CJsonObject.cpp \ + Device/JsonConfig.cpp \ + ImageProcess/ImageApply.cpp \ + ImageProcess/ImageApplyAdjustColors.cpp \ + ImageProcess/ImageApplyAutoCrop.cpp \ + ImageProcess/ImageApplyBWBinaray.cpp \ + ImageProcess/ImageApplyChannel.cpp \ + ImageProcess/ImageApplyCrop.cpp \ + ImageProcess/ImageApplyDiscardBlank.cpp \ + ImageProcess/ImageApplyOutHole.cpp \ + ImageProcess/ImageApplyResize.cpp \ + ImageProcess/ImageApplyRotation.cpp \ + ImageProcess/ImageApplySharpen.cpp \ + ImageProcess/ImageProcess_Public.cpp \ + Sliders.cpp \ + SmartEdit.cpp \ + TabCtrlSSL.cpp \ + TabPageSSL.cpp \ + stdafx.cpp + +HEADERS += huagaods.hpp \ + CAboutDlg.h \ + CBasicPage.h \ + CBrightnessPage.h \ + CFeedPaperPage.h \ + CImageProcPage.h \ + CIndicatorDlg.h \ + CSaveConfigDlg.h \ + CTwainMutex.h \ + CTwainUI.h \ + Device/BlockingQueue.h \ + Device/GDevice.h \ + Device/GDeviceLists.h \ + Device/GScan200.h \ + Device/GScanO200.h \ + Device/GScanVirtual.h \ + Device/IConfig.h \ + Device/IGDevice.h \ + Device/IUsb.h \ + Device/ImageMatQueue.h \ + Device/ImageMultiOutput.h \ + Device/JpegBuffer.h \ + Device/PaperSize.h \ + Device/PublicFunc.h \ + Device/UsbScanEx.h \ + Device/config_new.h \ + Device/device_common.h \ + Device/GScan.h \ + Device/jpeglib.h \ + Device/scn_config.h \ + Device/filetools.h \ + Device/cJSON.h \ + Device/JsonConfig.h \ + Device/CJsonObject.hpp \ + ImageProcess/ImageApply.h \ + ImageProcess/ImageApplyAdjustColors.h \ + ImageProcess/ImageApplyAutoCrop.h \ + ImageProcess/ImageApplyBWBinaray.h \ + ImageProcess/ImageApplyChannel.h \ + ImageProcess/ImageApplyCrop.h \ + ImageProcess/ImageApplyDiscardBlank.h \ + ImageProcess/ImageApplyHeaders.h \ + ImageProcess/ImageApplyOutHole.h \ + ImageProcess/ImageApplyResize.h \ + ImageProcess/ImageApplyRotation.h \ + ImageProcess/ImageApplySharpen.h \ + ImageProcess/ImageProcess_Public.h \ + Sliders.h \ + SmartEdit.h \ + TabCtrlSSL.h \ + TabPageSSL.h \ + resource.h \ + stdafx.h \ + targetver.h \ + twglue.hpp + +RC_FILE += huagaotwds.rc diff --git a/huagao/huagaotwds.rc b/huagao/huagaotwds.rc new file mode 100644 index 00000000..a014c1cc Binary files /dev/null and b/huagao/huagaotwds.rc differ diff --git a/huagao/resource.h b/huagao/resource.h new file mode 100644 index 00000000..6b33a7a6 Binary files /dev/null and b/huagao/resource.h differ diff --git a/huagao/stdafx.cpp b/huagao/stdafx.cpp new file mode 100644 index 00000000..cc3e78f7 Binary files /dev/null and b/huagao/stdafx.cpp differ diff --git a/huagao/stdafx.h b/huagao/stdafx.h new file mode 100644 index 00000000..a82a5180 Binary files /dev/null and b/huagao/stdafx.h differ diff --git a/huagao/targetver.h b/huagao/targetver.h new file mode 100644 index 00000000..e2da66c0 Binary files /dev/null and b/huagao/targetver.h differ diff --git a/huagao/twglue.hpp b/huagao/twglue.hpp new file mode 100644 index 00000000..693002ef --- /dev/null +++ b/huagao/twglue.hpp @@ -0,0 +1,17 @@ +#ifndef TWGLUE_HPP +#define TWGLUE_HPP + +#include +#include "Device/PublicFunc.h" + +struct TwGlue { + + TwGlue(const std::function& scan, const std::function& cancel) : + m_scan(scan), m_cancel(cancel){} + + std::function m_scan; + std::function m_cancel; + +}; + +#endif // TWGLUE_HPP diff --git a/twpp.hpp b/twpp.hpp new file mode 100644 index 00000000..a3d95a12 --- /dev/null +++ b/twpp.hpp @@ -0,0 +1,114 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_TWPP_HPP +#define TWPP_DETAIL_FILE_TWPP_HPP + +#include "twpp/env.hpp" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include "twpp/utils.hpp" + +#include "twpp/types.hpp" +#include "twpp/strings.hpp" +#include "twpp/fix32.hpp" +#include "twpp/frame.hpp" +#include "twpp/exception.hpp" +#include "twpp/typesops.hpp" + +#include "twpp/memoryops.hpp" +#include "twpp/memory.hpp" + +#include "twpp/enums.hpp" +#include "twpp/status.hpp" +#include "twpp/identity.hpp" +#include "twpp/imageinfo.hpp" +#include "twpp/imagelayout.hpp" +#include "twpp/deviceevent.hpp" +#include "twpp/element8.hpp" + +#include "twpp/audio.hpp" +#include "twpp/capability.hpp" +#include "twpp/customdata.hpp" +#include "twpp/cie.hpp" +#include "twpp/curveresponse.hpp" +#include "twpp/event.hpp" +#include "twpp/extimageinfo.hpp" +#include "twpp/filesystem.hpp" +#include "twpp/imagememxfer.hpp" +#include "twpp/imagenativexfer.hpp" +#include "twpp/internal.hpp" +#include "twpp/jpegcompression.hpp" +#include "twpp/palette8.hpp" +#include "twpp/passthrough.hpp" +#include "twpp/pendingxfers.hpp" +#include "twpp/setupfilexfer.hpp" +#include "twpp/setupmemxfer.hpp" +#include "twpp/userinterface.hpp" + +#if !defined(TWPP_IS_DS) +# include "twpp/application.hpp" +#else +# include "twpp/datasource.hpp" +#endif + + +#if !defined(TWPP_NO_NOTES) +# if !defined(TWPP_IS_DS) +# pragma message ("note: using APPLICATION version of TWPP library, define TWPP_IS_DS before including twpp.hpp if you want DATA SOURCE version") +# if defined(TWPP_DETAIL_OS_WIN32) +# pragma message ("note: place the following into your module-definition (.def) file: EXPORTS DS_Entry @1") +# endif +# else +# pragma message ("note: using DATA SOURCE version of TWPP library, undefine TWPP_IS_DS if you want APPLICATION version") +# pragma message ("note: make sure to place TWPP_ENTRY() macro in exactly one source file") +# endif +# if defined(TWPP_DETAIL_OS_MAC) +# pragma message "warning: Str32, Str64, Str128 and Str255 are not null-terminated" +# endif +# pragma message ("note: to disable notes and warnings, define TWPP_NO_NOTES before including TWPP header") +#endif + + +#endif // TWPP_DETAIL_FILE_TWPP_HPP diff --git a/twpp/application.hpp b/twpp/application.hpp new file mode 100644 index 00000000..7ad02c7d --- /dev/null +++ b/twpp/application.hpp @@ -0,0 +1,1153 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_APPLICATION_HPP +#define TWPP_DETAIL_FILE_APPLICATION_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +struct ManagerData { + + ManagerData(const Identity& appId) noexcept : + m_appId(appId){} + + Identity m_appId; + DsmState m_state = DsmState::PreSession; + Detail::DsmLib m_lib; + Detail::DsmEntry m_entry = nullptr; + +#if defined(TWPP_DETAIL_OS_WIN) + Handle m_rootWindow; + bool m_ownRootWindow; +#elif defined(TWPP_DETAIL_OS_MAC) + Detail::NSAutoreleasePool m_autoreleasePool; +#elif !defined(TWPP_DETAIL_OS_LINUX) +# error "ManagerData for your platform here" +#endif + +}; + +struct SourceData { + + SourceData(ManagerData* mgr, const Identity& srcIdent) noexcept : + m_mgr(mgr), m_srcId(srcIdent){} + + ManagerData* m_mgr; + std::function m_devEvent; + Handle m_uiHandle; + Identity m_srcId; + DsState m_state = DsState::Closed; + Msg m_readyMsg = Msg::Null; + +#if defined(TWPP_DETAIL_OS_LINUX) + std::mutex m_cbMutex; + std::condition_variable m_cbCond; +#elif !defined(TWPP_DETAIL_OS_WIN) && !defined(TWPP_DETAIL_OS_MAC) +# error "SourceData for your platform here" +#endif + +}; + +} + +class Manager; + +/// A single TWAIN source. +/// Source must belong to a manager in order to perform operations on it. +/// Any valid source instance must be destroyed or at least cleaned by `cleanup` +/// before parent manager is itself destroyed. +/// +/// `call` vs +/// They are ultimately the same: +/// `call` is more suitable for cases that need fixed number of arguments. +/// is better for user-defined calls. +class Source { + + friend class Manager; + +public: + typedef std::function EventCallBack; + + /// Creates an invalid source. + /// Calling any method on such source results in + /// undefined behaviour, and possibly segfault. + /// Only isValid() and operator bool() may be called. + Source() noexcept{} + + ~Source(){ + if (isValid()){ + cleanup(); + } + } + + Source(Source&&) = default; + Source& operator=(Source&& o) noexcept{ + if (&o != this){ + if (isValid()){ + cleanup(); + } + + m_data = std::move(o.m_data); + } + + return *this; + } + + /// Performs explicit cleanup. + /// Ultimately closes the source. + void cleanup() noexcept{ + assert(isValid()); + + PendingXfers xfers; + + switch (d()->m_state){ + case DsState::Xferring: + pendingXfers(Msg::EndXfer, xfers); + // fallthrough + case DsState::XferReady: + if (d()->m_state == DsState::XferReady){ // EndXfer might have moved to DsState::Enabled + pendingXfers(Msg::Reset, xfers); + } + + // fallthrough + case DsState::Enabled: + disable(); + // fallthrough + case DsState::Open: + close(); + // reset the ref even if close() fails somehow + Static::g_openSource = nullptr; + // fallthrough + case DsState::Closed: + break; + } + } + + /// TWAIN state of the source. + DsState state() const noexcept{ + assert(isValid()); + + return d()->m_state; + } + + /// Whether the source is valid. + /// Valid source was created by manager. + /// Invalid source was created using default constructor. + bool isValid() const noexcept{ + return static_cast(m_data); + } + + operator bool() const noexcept{ + return isValid(); + } + + /// Identity of the source. + const Identity& identity() const noexcept{ + assert(isValid()); + + return d()->m_srcId; + } + + /// Sets function (object) to receive device event notifications. + /// + /// {In state 5 (enabled), the function should only set a flag and return immediately. + /// `waitReady()` then returns CheckStatus, and the device event may be processed in + /// the main thread. Call `waitReady()` again once you are done.} + void setEventCallBack(EventCallBack devEvent){ + assert(isValid()); + + d()->m_devEvent = std::move(devEvent); + } + + + // Control -> + + /// Opens the source. + /// Only up to 1 source may be opened at the same time. + /// \throw std::bad_alloc + ReturnCode open(){ + assert(Static::g_openSource == nullptr); + + auto rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::OpenDs, d()->m_srcId); + if (success(rc)){ + d()->m_state = DsState::Open; + + // TWAIN manual is rather confusing on this topic. + // Their example sends the registration to DSM, operation tripet documentation mentions DS as destination. + // Looking at some other applications, Windows seems to send this to DS, MacOS to DSM. + Detail::CallBack cb1(callBack, static_cast(0), Msg::Null); + +#if defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + Detail::CallBack2 cb2(callBack, 0, Msg::Null); + + bool usesCb = success(dsm(DataGroup::Control, Dat::Callback2, Msg::RegisterCallback, cb2)) || + success(dsm(DataGroup::Control, Dat::Callback, Msg::RegisterCallback, cb1)); +#elif defined(TWPP_DETAIL_OS_MAC) + bool usesCb = success(dsm(nullptr, DataGroup::Control, Dat::Callback, Msg::RegisterCallback, cb1)); +#else +# error "callback setup for your platform here" +#endif + +#if defined(TWPP_DETAIL_OS_WIN) + Detail::unused(usesCb); +#elif defined(TWPP_DETAIL_OS_MAC) || defined(TWPP_DETAIL_OS_LINUX) + if (!usesCb){ + close(); + return ReturnCode::Failure; + } +#else +# error "source open setup for your platform here" +#endif + Static::g_openSource = d(); + } + + return rc; + } + + /// Closes the source. + ReturnCode close(){ + ReturnCode rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::CloseDs, d()->m_srcId); + if (success(rc)){ + Static::g_openSource = nullptr; + d()->m_state = DsState::Closed; + } + + return rc; + } + + /// Enables the source, showing its GUI if requested. + /// A call to `waitReady` must follow, advanced users may look at `processEvent` on Windows. + /// \param ui GUI settings. + /// \param uiOnly Whether the GUI should only be used to change values, not scan. + ReturnCode enable(const UserInterface& ui, bool uiOnly = false) noexcept{ + auto uiTmp = ui; // allow ui to be const, dsm doesnt take const + ReturnCode rc = dsm(DataGroup::Control, Dat::UserInterface, uiOnly ? Msg::EnableDsUiOnly : Msg::EnableDs, uiTmp); + if (success(rc) || (!uiOnly && rc == ReturnCode::CheckStatus)){ + d()->m_readyMsg = Msg::Null; + d()->m_uiHandle = ui.parent(); + d()->m_state = DsState::Enabled; + } + + return rc; + } + + /// Disables this source. + ReturnCode disable(){ + assert(isValid()); + + UserInterface ui(false, false, d()->m_uiHandle); + auto rc = dsm(DataGroup::Control, Dat::UserInterface, Msg::DisableDs, ui); + if (success(rc)){ + d()->m_state = DsState::Open; + } + + return rc; + } + + /// Waits on source GUI, blocking. + /// This method is meant for CMD applications, see `processEvent()` for GUI-friendly version. + /// The state is moved to XferReady, when Success is returned, and the source is enabled with full UI (uiOnly = false). + /// On Windows and Mac OS, call this method from the main thread, GUI events are processed here. + /// On Linux, this method may be called from any thread, GUI events are NOT processed. + /// Call this again after processing device event. + /// \return {Failure on error, Cancel on CANCEL button, Success on SAVE or SCAN button, + /// CheckStatus on device event.} + ReturnCode waitReady(){ + assert(isValid()); + + if (d()->m_state != DsState::Enabled){ + return ReturnCode::Failure; + } + +#if defined(TWPP_DETAIL_OS_WIN) + MSG msg; + memset(&msg, 0, sizeof(msg)); + + Event event(&msg, Msg::Null); + while (d()->m_readyMsg == Msg::Null){ + auto val = GetMessage(&msg, nullptr, 0, 0); + if (val == 0 || val == -1){ // 0 ... WM_QUIT; -1 ... error; otherwise ... success + return ReturnCode::Failure; + } + + auto rc = dsm(DataGroup::Control, Dat::Event, Msg::ProcessEvent, event); + switch (rc){ + case ReturnCode::NotDsEvent: + TranslateMessage(&msg); + DispatchMessage(&msg); + // fallthrough + case ReturnCode::DsEvent: + if (d()->m_readyMsg == Msg::Null){ + d()->m_readyMsg = event.message(); + } + + break; + + default: + return rc; + } + } +#elif defined(TWPP_DETAIL_OS_MAC) + Detail::NSAutoreleasePool pool; + + while(d()->m_readyMsg == Msg::Null) { + Detail::NSLoop::processEvent(); + } + + pool.release(); + +#elif defined(TWPP_DETAIL_OS_LINUX) + std::unique_lock lock(d()->m_cbMutex); + while (d()->m_readyMsg == Msg::Null){ + d()->m_cbCond.wait(lock); + } +#else +# error "waitReady for your platform here" +#endif + + switch (d()->m_readyMsg){ + case Msg::XferReady: // ok/scan button <=> Msg::EnableDs + d()->m_state = DsState::XferReady; + case Msg::CloseDsOk: // ok/scan button <=> Msg::EnableDsUiOnly + return ReturnCode::Success; + + case Msg::CloseDsReq: // cancel button + return ReturnCode::Cancel; + + case Msg::DeviceEvent: + d()->m_readyMsg = Msg::Null; + return ReturnCode::CheckStatus; + + default: + return ReturnCode::Failure; + } + } + + /// Processes a single GUI event without blocking. + /// Can be used instead of `waitReady()` to process a single event. + /// Windows users must pass events from GUI loop to this method to be sent to DS. + /// \return {Failure on error, Cancel on CANCEL button, Success on SAVE or SCAN button, + /// CheckStatus on device event. NotDsEvent OR DsEvent when not ready yet.} +#if defined (TWPP_DETAIL_OS_WIN) + ReturnCode processEvent(MSG* event){ + Event twEvent(event, Msg::Null); + auto rc = dsm(DataGroup::Control, Dat::Event, Msg::ProcessEvent, twEvent); + switch (rc){ + case ReturnCode::DsEvent: + case ReturnCode::NotDsEvent: + if (d()->m_readyMsg == Msg::Null){ + d()->m_readyMsg = twEvent.message(); + } + + break; + + default: + return rc; + } + + auto msg = d()->m_readyMsg; + +#elif defined(TWPP_DETAIL_OS_LINUX) || defined(TWPP_DETAIL_OS_MAC) + ReturnCode processEvent(){ + assert(isValid()); + auto rc = ReturnCode::NotDsEvent; + +# if defined(TWPP_DETAIL_OS_MAC) + auto msg = d()->m_readyMsg; +# else + std::unique_lock lock(d()->m_cbMutex); + auto msg = d()->m_readyMsg; + lock.unlock(); +# endif + +#else +# error "processEvent for your platform here" +#endif + switch (msg){ + case Msg::XferReady: // ok/scan button <=> Msg::EnableDs + d()->m_state = DsState::XferReady; + // fallthrough + case Msg::CloseDsOk: // ok/scan button <=> Msg::EnableDsUiOnly + return ReturnCode::Success; + + case Msg::CloseDsReq: // cancel button + return ReturnCode::Cancel; + + case Msg::DeviceEvent: + d()->m_readyMsg = Msg::Null; + return ReturnCode::CheckStatus; + + case Msg::Null: + return rc; + + default: + return ReturnCode::Failure; + } + } + + /// Sends custom, user-defined data to the source. + /// This operation is unsafe, there is no way to discover + /// possible connection state changes. + /// \tparam T Data type. + /// \param dg Data group. + /// \param dat Custom data type identifier. Dat::CustomBase and greater. + /// \param msg Message, action to perform. + /// \param data Custom data. + template + ReturnCode customBase(DataGroup dg, Dat dat, Msg msg, T& data){ + return dsm(dg, dat, msg, data); + } + + /// Sends custom, user-defined data to the source. + /// This operation is unsafe, there is no way to discover + /// possible connection state changes. + /// \param dg Data group. + /// \param dat Custom data type identifier. Dat::CustomBase and greater. + /// \param msg Message, action to perform. + /// \param data Custom data. + ReturnCode customBase(DataGroup dg, Dat dat, Msg msg, void* data){ + return dsmPtr(dg, dat, msg, data); + } + + ReturnCode capability(Msg msg, Capability& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + /// \throw CapTypeException When input capability type does not match the + /// capability type of this template class. + /// \throw CapItemTypeException When input capability item type does not match + /// the expected item type of the capability. + template + ReturnCode capability(Msg msg, Cap& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode customData(Msg msg, CustomData& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode deviceEvent(DeviceEvent& out){ + return call(DataGroup::Control, Msg::Get, out); + } + + ReturnCode fileSystem(Msg msg, FileSystem& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode passThrough(PassThrough& inOut){ + return call(DataGroup::Control, Msg::PassThrough, inOut); + } + + ReturnCode pendingXfers(Msg msg, PendingXfers& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode setupFileXfer(Msg msg, SetupFileXfer& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode setupMemXfer(SetupMemXfer& out){ + return call(DataGroup::Control, Msg::Get, out); + } + + ReturnCode xferGroup(Msg msg, DataGroup& inOut){ + return call(DataGroup::Control, msg, inOut); + } + + ReturnCode status(Status& out){ + return call(DataGroup::Control, Msg::Get, out); + } + + ReturnCode statusUtf8(StatusUtf8& inOut){ + return call(DataGroup::Control, Msg::Get, inOut); + } + // <- Control + + + // Image -> + // TODO CieColor + /* + ReturnCode cieColor(CieColor& out){ + return call(DataGroup::Image, Msg::Get, out); + }*/ + + ReturnCode extImageInfo(ExtImageInfo& inOut){ + return call(DataGroup::Image, Msg::Get, inOut); + } + + ReturnCode grayResponse(Msg msg, GrayResponse& inOut){ + return call(DataGroup::Image, msg, inOut); + } + + ReturnCode iccProfile(IccProfileMemory& out){ + return call(DataGroup::Image, Msg::Get, out); + } + + ReturnCode imageFileXfer(){ + return call(DataGroup::Image, Msg::Get, ImageFileXfer()); + } + + ReturnCode imageInfo(ImageInfo& out){ + return call(DataGroup::Image, Msg::Get, out); + } + + ReturnCode imageLayout(Msg msg, ImageLayout& inOut){ + return call(DataGroup::Image, msg, inOut); + } + + ReturnCode imageMemFileXfer(ImageMemFileXfer& inOut){ + return call(DataGroup::Image, Msg::Get, inOut); + } + + ReturnCode imageMemXfer(ImageMemXfer& inOut){ + return call(DataGroup::Image, Msg::Get, inOut); + } + + ReturnCode imageNativeXfer(ImageNativeXfer& out){ + return call(DataGroup::Image, Msg::Get, out); + } + + ReturnCode jpegCompression(Msg msg, JpegCompression& inOut){ + return call(DataGroup::Image, msg, inOut); + } + + ReturnCode palette8(Msg msg, Palette8& inOut){ + return call(DataGroup::Image, msg, inOut); + } + + ReturnCode rgbResponse(Msg msg, RgbResponse& inOut){ + return call(DataGroup::Image, msg, inOut); + } + // <- Image + + + // Audio -> + ReturnCode audioFileXfer(){ + return call(DataGroup::Audio, Msg::Get, AudioFileXfer()); + } + + ReturnCode audioInfo(AudioInfo& out){ + return call(DataGroup::Audio, Msg::Get, out); + } + + ReturnCode audioNativeXfer(AudioNativeXfer& out){ + return call(DataGroup::Audio, Msg::Get, out); + } + // <- Audio + + + // Raw -> + + // dg:: control follows + ReturnCode call(DataGroup dg, Msg msg, Capability& data){ + return dsm(dg, Dat::Capability, msg, data); + } + + /// \throw CapTypeException When input capability type does not match the + /// capability type of this template class. + /// \throw CapItemTypeException When input capability item type does not match + /// the expected item type of the capability. + template + ReturnCode call(DataGroup dg, Msg msg, Cap& data){ + auto rc = call(dg, msg, data.m_cap); + data.checkTypes(); + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, CustomData& data){ + return dsm(dg, Dat::CustomData, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, DeviceEvent& data){ + return dsm(dg, Dat::DeviceEvent, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, FileSystem& data){ + return dsm(dg, Dat::FileSystem, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, PassThrough& data){ + return dsm(dg, Dat::PassThrough, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, PendingXfers& data){ + auto rc = dsm(dg, Dat::PendingXfers, msg, data); + if (success(rc)){ + // FIXME: unsure about audio state transitions + DataGroup xg = DataGroup::Image; + switch (msg){ + case Msg::EndXfer: + xferGroup(Msg::Get, xg); + if (xg == DataGroup::Image && data.count() == 0){ + d()->m_state = DsState::Enabled; + } else { + d()->m_state = DsState::XferReady; + } + + break; + + case Msg::Reset: + xferGroup(Msg::Get, xg); + if (xg == DataGroup::Image){ + d()->m_state = DsState::Enabled; + } + + break; + + default: + break; + } + + + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, SetupFileXfer& data){ + return dsm(dg, Dat::SetupFileXfer, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, SetupMemXfer& data){ + return dsm(dg, Dat::SetupMemXfer, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, DataGroup& data){ + return dsm(dg, Dat::XferGroup, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, Status& data){ + return dsm(dg, Dat::Status, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, StatusUtf8& data){ + return dsm(dg, Dat::StatusUtf8, msg, data); + } + + // dg::image follows + // TODO CieColor + /* + ReturnCode call(DataGroup dg, Msg msg, CieColor& data){ + return dsm(dg, Dat::CieColor, msg, data); + }*/ + + ReturnCode call(DataGroup dg, Msg msg, ExtImageInfo& data){ + char* raw = *Detail::alias_cast(&data); // ExtImageInfo is just an envelope; raw ~ ExtImageInfo.m_data + return dsmPtr(dg, Dat::ExtImageInfo, msg, raw); + } + + ReturnCode call(DataGroup dg, Msg msg, GrayResponse& data){ + return dsmPtr(dg, Dat::GrayResponse, msg, data.data()); + } + + ReturnCode call(DataGroup dg, Msg msg, IccProfileMemory& data){ + Memory mem; // DS allocates and owns the memory + ReturnCode rc = dsm(dg, Dat::IccProfile, msg, mem); + if (success(rc)){ + data = std::move(mem); + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, const ImageFileXfer&){ + ReturnCode rc = dsmPtr(dg, Dat::ImageFileXfer, msg, nullptr); + if (success(rc)){ + d()->m_state = DsState::Xferring; + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, ImageInfo& data){ + return dsm(dg, Dat::ImageInfo, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, ImageLayout& data){ + return dsm(dg, Dat::ImageLayout, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, ImageMemFileXfer& data){ + ReturnCode rc = dsm(dg, Dat::ImageMemFileXfer, msg, data); + if (success(rc) || rc == ReturnCode::XferDone){ + d()->m_state = DsState::Xferring; + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, ImageMemXfer& data){ + ReturnCode rc = dsm(dg, Dat::ImageMemXfer, msg, data); + if (success(rc) || rc == ReturnCode::XferDone){ + d()->m_state = DsState::Xferring; + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, ImageNativeXfer& data){ + Handle h; + ReturnCode rc = dsm(dg, Dat::ImageNativeXfer, msg, h); + if (rc == ReturnCode::XferDone){ + d()->m_state = DsState::Xferring; + } + + if (h){ + data = ImageNativeXfer(h); + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, JpegCompression& data){ + return dsm(dg, Dat::JpegCompression, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, Palette8& data){ + return dsm(dg, Dat::Palette8, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, RgbResponse& data){ + return dsmPtr(dg, Dat::RgbResponse, msg, data.data()); + } + + // dg::audio follows + ReturnCode call(DataGroup dg, Msg msg, const AudioFileXfer&){ + // FIXME: unsure about state transitions + ReturnCode rc = dsmPtr(dg, Dat::AudioFileXfer, msg, nullptr); + if (rc == ReturnCode::XferDone){ + d()->m_state = DsState::Xferring; + } + + return rc; + } + + ReturnCode call(DataGroup dg, Msg msg, AudioInfo& data){ + return dsm(dg, Dat::AudioInfo, msg, data); + } + + ReturnCode call(DataGroup dg, Msg msg, AudioNativeXfer& data){ + Handle h; + ReturnCode rc = dsm(dg, Dat::AudioNativeXfer, msg, h); + if (success(rc)){ + d()->m_state = DsState::Xferring; + } + + if (h){ + data = AudioNativeXfer(h); + } + + return rc; + } + // <- Raw + +private: + Source(Detail::ManagerData* mgr, const Identity& srcId) : + m_data(new Detail::SourceData(mgr, srcId)){} + + Detail::SourceData* d() noexcept{ + return m_data.get(); + } + + const Detail::SourceData* d() const noexcept{ + return m_data.get(); + } + + template + ReturnCode dsm(Identity* dest, DataGroup dg, Dat dat, Msg msg, T& data) noexcept{ + return dsmPtr(dest, dg, dat, msg, &data); + } + + ReturnCode dsmPtr(Identity* dest, DataGroup dg, Dat dat, Msg msg, void* data) noexcept{ + assert(isValid()); + + auto mgr = d()->m_mgr; + return mgr->m_entry(&mgr->m_appId, dest, dg, dat, msg, data); + } + + template + ReturnCode dsm(DataGroup dg, Dat dat, Msg msg, T& data) noexcept{ + return dsm(&d()->m_srcId, dg, dat, msg, data); + } + + ReturnCode dsmPtr(DataGroup dg, Dat dat, Msg msg, void* data) noexcept{ + return dsmPtr(&d()->m_srcId, dg, dat, msg, data); + } + + // header-only, yet we need static variables + // templates behave as if defined in at most one source file + template + struct Static { + static Detail::SourceData* g_openSource; + }; + + template + static ReturnCode TWPP_DETAIL_CALLSTYLE callBack( + Identity*, + Identity*, + DataGroup, + Dat, + Msg msg, + void* + ) noexcept{ + Detail::SourceData* src = Static::g_openSource; + if (src == nullptr){ + return ReturnCode::Failure; + } + +#if defined(TWPP_DETAIL_OS_LINUX) + std::unique_lock lock(src->m_cbMutex); + if (src->m_state != DsState::Enabled){ + lock.unlock(); + } +#elif !defined(TWPP_DETAIL_OS_WIN) && !defined(TWPP_DETAIL_OS_MAC) +# error "callBack preparation for your platform here" +#endif + if (msg == Msg::DeviceEvent){ + if (!src->m_devEvent){ + return ReturnCode::Failure; + } + + src->m_devEvent(); + } + + if (src->m_state == DsState::Enabled){ + src->m_readyMsg = msg; + +#if defined(TWPP_DETAIL_OS_WIN) + PostMessageA(static_cast(src->m_mgr->m_rootWindow.raw()), WM_NULL, 0, 0); +#elif defined(TWPP_DETAIL_OS_LINUX) + src->m_cbCond.notify_one(); +#elif defined(TWPP_DETAIL_OS_MAC) + Detail::NSLoop::postDummy(); +#else +# error "callBack for your platform here" +#endif + } + + + return ReturnCode::Success; + } + + std::unique_ptr m_data; + +}; + +template +Detail::SourceData* Source::Static::g_openSource = nullptr; + +/// TWAIN data source manager. +/// At most one valid instance may exist at all times. +/// All corresponding valid sources must be destroyed or cleaned up +/// BEFORE their parent valid manager is closed (destroyed/cleaned up). +class Manager { + +public: + /// Creates an invalid manager. + Manager() noexcept{} + + /// Creates a valid, unloaded manager. + /// \param appIdentity Application identity. + explicit Manager(const Identity& appIdentity) : + m_data(new Detail::ManagerData(appIdentity)){} + + ~Manager(){ + if (isValid()){ + cleanup(); + } + } + + Manager(Manager&&) = default; + Manager& operator=(Manager&& o) noexcept{ + if (&o != this){ + if (isValid()){ + cleanup(); + } + + m_data = std::move(o.m_data); + } + + return *this; + } + + /// Explicitly cleanes the manager, ultimately closing it. + void cleanup() noexcept{ + assert(isValid()); + + switch (d()->m_state){ + case DsmState::Open: + close(); + // fallthrough + case DsmState::Loaded: + unload(); + // fallthrough + case DsmState::PreSession: + // nothing to do now + break; + } + } + + /// Loads the manager library. + /// Not a TWAIN call. + /// \param preferOld {Whether to prefer old DSM (TWAIN_32) instead + /// of the new one (TWAINDSM) on 32bit Windows. + /// Has no effect anywhere else.} + /// \return Whether this call loaded the library. + bool load(bool preferOld = false) noexcept{ + assert(isValid()); + + if (d()->m_state != DsmState::PreSession){ + return false; + } + + if (!d()->m_lib.load(preferOld)){ + return false; + } + + d()->m_state = DsmState::Loaded; + d()->m_entry = d()->m_lib.resolve(); + bool resolved = d()->m_entry != nullptr; + if (!resolved){ + unload(); + } + + return resolved; + } + + /// Unloads the manager library. + /// Not a TWAIN call. + /// \return Whether this call unloaded the library. + bool unload() noexcept{ + assert(isValid()); + + if (d()->m_state != DsmState::Loaded){ + return false; + } + + closeRootWindow(); + d()->m_lib.unload(); + d()->m_state = DsmState::PreSession; + return true; + } + + /// Opens the manager. + ReturnCode open(Handle rootWindow = Handle()) noexcept{ + assert(isValid()); + + if (d()->m_state != DsmState::Loaded){ + return ReturnCode::Failure; + } + +#if defined(TWPP_DETAIL_OS_WIN) + if (rootWindow){ + closeRootWindow(); + d()->m_rootWindow = rootWindow; + d()->m_ownRootWindow = false; + } else { + if (!d()->m_rootWindow || !d()->m_ownRootWindow){ + d()->m_rootWindow = Handle(CreateWindowA("STATIC", nullptr, 0, 0, 0, 0, 0, nullptr, nullptr, nullptr, nullptr)); + if (!d()->m_rootWindow){ + return ReturnCode::Failure; + } + } + + d()->m_ownRootWindow = true; + rootWindow = d()->m_rootWindow; + } +#elif !defined(TWPP_DETAIL_OS_MAC) && !defined(TWPP_DETAIL_OS_LINUX) +# error "manager open setup for your platform here" +#endif + + auto rc = dsm(nullptr, DataGroup::Control, Dat::Parent, Msg::OpenDsm, rootWindow); + if (success(rc)){ + Detail::resetMemFuncs(); + if (d()->m_appId.isDsmV2()){ + Detail::EntryPoint e; + if (success(dsm(nullptr, DataGroup::Control, Dat::EntryPoint, Msg::Get, e))){ + Detail::setMemFuncs(e.m_alloc, e.m_free, e.m_lock, e.m_unlock); + } + } + + d()->m_state = DsmState::Open; + } + + return rc; + } + + /// Closes the manager. + ReturnCode close() noexcept{ + assert(isValid()); + + // no need to check state, dsm will do it for us + +#if defined(TWPP_DETAIL_OS_WIN) + Handle rootWindow = d()->m_rootWindow; +#elif defined(TWPP_DETAIL_OS_MAC) || defined(TWPP_DETAIL_OS_LINUX) + Handle rootWindow; +#else +# error "close manager for your platform here" +#endif + + auto rc = dsm(nullptr, DataGroup::Control, Dat::Parent, Msg::CloseDsm, rootWindow); + if (success(rc)){ + d()->m_state = DsmState::Loaded; + } + + return rc; + } + + /// Creates a valid closed source. + /// Whether the source may be opened depends whether + /// a source with the supplied product name and manufacturer exists. + /// \throw std::bad_alloc + Source createSource(const Str32& productName, const Str32& manufacturer){ + assert(isValid()); + + return Source(d(), Identity(Version(), DataGroup::Control, manufacturer, Str32(), productName)); + } + + /// Creates a valid closed default source. + /// It is almost certain the source may be opened. + /// \throw std::bad_alloc + ReturnCode defaultSource(Source& out){ + Identity id; + auto rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::GetDefault, id); + if (success(rc)){ + out = Source(d(), id); + } + + return rc; + } + + /// Sets default source. + ReturnCode setDefaultSource(Source& in) noexcept{ + return dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::Set, in.d()->m_srcId); + } + + /// Lists all available sources. + /// \tparam Container Container type, usually std::vector. + /// \param out The container to be filled with sources. + /// \return {RC::Success if one source, RC::EndOfList if more sources, RC::Failure if error.} + template + ReturnCode sources(Container& out){ + Identity id; + auto rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::GetFirst, id); + if (success(rc)){ + do { + out.push_back(Source(d(), id)); + + rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::GetNext, id); + } while(success(rc)); + } + + return rc; + } + + /// Shows a source-selection dialog. + /// Available only on Windows and MacOS. + ReturnCode showSourceDialog(Source& out){ + Identity id; + ReturnCode rc = dsm(nullptr, DataGroup::Control, Dat::Identity, Msg::UserSelect, id); + if (success(rc)){ + out = Source(d(), id); + } + + return rc; + } + + /// Obtains the last manager status. + ReturnCode status(Status& status) noexcept{ + return dsm(nullptr, DataGroup::Control, Dat::Status, Msg::Get, status); + } + + /// The current manager TWAIN state. + DsmState state() const noexcept{ + assert(isValid()); + + return d()->m_state; + } + + /// Application identity the manager was/will be open with. + const Identity& identity() const noexcept{ + assert(isValid()); + + return d()->m_appId; + } + + /// Whether this object is a valid manager. + /// Valid manager object is created using constructor with at least one parameter. + /// Using constructor without any parameters results in invalid manager. + bool isValid() const noexcept{ + return static_cast(m_data); + } + + operator bool() noexcept{ + return isValid(); + } + +private: + void closeRootWindow() noexcept{ +#if defined(TWPP_DETAIL_OS_WIN) + if (d()->m_rootWindow && d()->m_ownRootWindow){ + DestroyWindow(static_cast(d()->m_rootWindow.raw())); + d()->m_ownRootWindow = Handle(); + } +#elif !defined(TWPP_DETAIL_OS_MAC) && !defined(TWPP_DETAIL_OS_LINUX) +# error "closeRootWindow for your platform here" +#endif + } + + Detail::ManagerData* d() noexcept{ + return m_data.get(); + } + + const Detail::ManagerData* d() const noexcept{ + return m_data.get(); + } + + template + ReturnCode dsm(Identity* dest, DataGroup dg, Dat dat, Msg msg, T& data){ + return dsmPtr(dest, dg, dat, msg, &data); + } + + ReturnCode dsmPtr(Identity* dest, DataGroup dg, Dat dat, Msg msg, void* data){ + assert(isValid()); + + return d()->m_entry(&d()->m_appId, dest, dg, dat, msg, data); + } + + std::unique_ptr m_data; + +}; + +} + +#endif // TWPP_DETAIL_FILE_APPLICATION_HPP + diff --git a/twpp/audio.hpp b/twpp/audio.hpp new file mode 100644 index 00000000..6aa8491e --- /dev/null +++ b/twpp/audio.hpp @@ -0,0 +1,119 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_AUDIO_HPP +#define TWPP_DETAIL_FILE_AUDIO_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Information about current audio transfer. +/// ArgType::AudioInfo +class AudioInfo { + +public: + /// Creates empty audio info. + constexpr AudioInfo() noexcept : + m_name(), m_reserved(){} + + /// Creates audio info with set name of audio data. + explicit constexpr AudioInfo(const Str255& name, UInt32 reserved = 0) noexcept : + m_name(name), m_reserved(reserved){} + + /// Name of audio data. + constexpr const Str255& name() const noexcept{ + return m_name; + } + + /// Name of audio data. + Str255& name() noexcept{ + return m_name; + } + + constexpr UInt32 reserved() const noexcept{ + return m_reserved; + } + + void setReserved(UInt32 reserved) noexcept{ + m_reserved = reserved; + } + +private: + Str255 m_name; + UInt32 m_reserved; + +}; + +/// Owner of audio transfer handle. +class AudioNativeXfer { + +public: + template + using Data = Detail::Lock::type>; + + template + using ConstData = Detail::Lock::type>; + + + /// Creates an empty handle owner. + AudioNativeXfer() noexcept : + m_handle(){} + + /// Creates a memory area of desired size for audio native transfer. + /// \throw std::bad_alloc + explicit AudioNativeXfer(UInt32 size) : + m_handle(Detail::alloc(size)){} + + /// Audio data. + template + Data data() noexcept{ + return m_handle.lock::type>(); + } + + /// Audio data. + template + ConstData data() const noexcept{ + return m_handle.lock::type>(); + } + + /// Releases the owned handle. + /// The user becomes responsible for freeing the handle. + Handle release() noexcept{ + return m_handle.release(); + } + +private: + Detail::UniqueHandle m_handle; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_AUDIO_HPP + diff --git a/twpp/capability.hpp b/twpp/capability.hpp new file mode 100644 index 00000000..728e2068 --- /dev/null +++ b/twpp/capability.hpp @@ -0,0 +1,2294 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_CAPABILITY_HPP +#define TWPP_DETAIL_FILE_CAPABILITY_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +/// Mapping of capability type to type identifier and data type. +template struct Cap {}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Alarm DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str128; typedef Str128 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef XferMech DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int16; typedef Int16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef CameraSide DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef ClearBuffers DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef DeviceEvent::Type DataType;}; // Capability->UInt16, DeviceEvent->UInt32 +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str32; typedef Str32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef DoubleFeedDetection DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef DoubleFeedResponse DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef DoubleFeedSensitivity DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Duplex DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef CapType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FeederAlignment DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FeederOrder DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FeederPocket DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef DiscardBlankPages DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelType DataType;}; // only BW/Gray +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef AutoSize DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef SearchMode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef BarCodeType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef UInt16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef BitDepthReduction DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef BitOrder DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef BitOrder DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef UInt16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Compression DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt8; typedef UInt8 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FeederType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FilmType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Filter DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Flash DataType;}; // Capability->UInt16, DeviceEvent->UInt32 +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FlipRotation DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Frame; typedef Frame DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str32; typedef Str32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef IccProfile DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef ImageFileFormat DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef ImageFilter DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef ImageMerge DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int16; typedef JpegQuality DataType;}; // JpegQuality or 0-100 +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef JpegSubSampling DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef LightPath DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef LightSource DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef UInt16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Mirror DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef IndicatorsMode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef NoiseFilter DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Orientation DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef OverScan DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef SearchMode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PatchCode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelFlavor DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelFlavor DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PixelType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef ColorFormat DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef BarCodeType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Twpp::InfoId DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PatchCode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PaperSize DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef UInt16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Unit DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef XferMech DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int16; typedef Int16 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef JobControl DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Language DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PaperHandling DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PowerSupply DataType;}; // Capability->UInt16, DeviceEvent->Int32 +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Printer DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef FontStyle DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str32; typedef Str32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef IndexTrigger DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef PrinterMode DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Fix32; typedef Fix32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef Segmented DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef CapType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt16; typedef CapType DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int32; typedef Int32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Str32; typedef Str32 DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Cap {static constexpr const Type twty = Type::Int16; typedef Int16 DataType;}; + +TWPP_DETAIL_PACK_BEGIN +// certain apps assume that size of OneValue item is always at least 4 bytes +// add padding that extends the sign of signed integers +// and pads with zeroes for unsigned integers +// all other cases use their data types directly +template // false, any +struct OneValueProxy { + OneValueProxy& operator=(const DataType& value) noexcept{ + m_data = value; + return *this; + } + + operator const DataType&() const noexcept{ + return m_data; + } + + operator DataType&() noexcept{ + return m_data; + } + + DataType m_data; +}; + +template +struct OneValueProxy { + OneValueProxy& operator=(DataType value) noexcept{ + m_signed = static_cast(value); + return *this; + } + + operator DataType() const noexcept{ + return m_data; + } + + operator DataType&() noexcept{ + return m_data; + } + + union { + DataType m_data; + Int32 m_signed; + }; +}; + +template +struct OneValueProxy { + OneValueProxy& operator=(DataType value) noexcept{ + m_unsigned = static_cast(value); + return *this; + } + + operator DataType() const noexcept{ + return m_data; + } + + operator DataType&() noexcept{ + return m_data; + } + + union { + DataType m_data; + UInt32 m_unsigned; + }; +}; + +template +struct OneValueData { + Type m_itemType; + OneValueProxy::value> m_item; +}; + +template +struct ArrayData { + Type m_itemType; + UInt32 m_numItems; + DataType m_items[1]; +}; + +template +struct EnumerationData { + Type m_itemType; + UInt32 m_numItems; + UInt32 m_currIndex; + UInt32 m_defIndex; + DataType m_items[1]; +}; + +// Range items are always 4 bytes large, +// add padding for smaller data types +template +struct RangeProxy { + typedef typename std::conditional< + std::is_signed::value, Int32, UInt32 + >::type InnerType; + + RangeProxy& operator=(DataType value) noexcept{ + m_data = value; + return *this; + } + + operator DataType() const noexcept{ + return static_cast(m_data); + } + + operator DataType&() noexcept{ + return *alias_cast(&m_data); + } + + InnerType m_data; +}; + +template<> +struct RangeProxy { + RangeProxy& operator=(Fix32 value) noexcept{ + m_data = value; + return *this; + } + + operator Fix32() const noexcept{ + return m_data; + } + + operator Fix32&() noexcept{ + return m_data; + } + + Fix32 m_data; +}; + +template +struct RangeData { + Type m_itemType; + RangeProxy m_minValue; + RangeProxy m_maxValue; + RangeProxy m_stepSize; + RangeProxy m_defValue; + RangeProxy m_currValue; +}; +TWPP_DETAIL_PACK_END + + +template +struct IsNumeric { + static constexpr bool value = std::is_integral::value || std::is_same::value; +}; + +} + +class Capability; + +/// Capability container holding a single value. +/// \tparam twty ID of the internal data type. +/// \tparam DataType Exported data type. +template::Type> +class OneValue { + + friend class Capability; + +public: + static constexpr const ConType contype = ConType::OneValue; + typedef DataType* iterator; + typedef const DataType* const_iterator; + + /// Creates an invalid container. + constexpr OneValue() noexcept{} + + /// ID of the internal data type. + Type type() const noexcept{ + return m_data->m_itemType; + } + + /// The contained value. + DataType& item() noexcept{ + return m_data->m_item; + } + + /// The contained value. + const DataType& item() const noexcept{ + return m_data->m_item; + } + + /// Sets the contained value. + void setItem(const DataType& item) noexcept{ + m_data->m_item = item; + } + + operator bool() const noexcept{ + return m_data; + } + + + iterator begin() noexcept{ + return &m_data->m_item; + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + return &m_data->m_item; + } + + iterator end() noexcept{ + return &m_data->m_item + 1; + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + return &m_data->m_item + 1; + } + +private: + OneValue(Handle h) : m_data(h){} + + Detail::Lock > m_data; + +}; + +// disable OneValue for incompatible types +template +class OneValue; +template +class OneValue; + + +/// Capability container holding an array of values. +/// \tparam twty ID of the internal data type. +/// \tparam DataType Exported data type. +template::Type> +class Array { + + friend class Capability; + +public: + static constexpr const ConType contype = ConType::Array; + typedef DataType* iterator; + typedef const DataType* const_iterator; + + /// Creates an invalid container. + constexpr Array() noexcept{} + + /// ID of the internal data type. + Type type() const noexcept{ + return m_data->m_itemType; + } + + /// Number of items in the array. + UInt32 size() const noexcept{ + return m_data->m_numItems; + } + + /// Access contained value in array. + DataType& at(std::size_t i) noexcept{ + return m_data->m_items[i]; + } + + /// Access contained value in array. + const DataType& at(std::size_t i) const noexcept{ + return m_data->m_items[i]; + } + + /// Sets value in array. + void set(std::size_t i, const DataType& val) noexcept{ + at(i) = val; + } + + + DataType& operator[](std::size_t i) noexcept{ + return at(i); + } + + const DataType& operator[](std::size_t i) const noexcept{ + return at(i); + } + + operator bool() const noexcept{ + return m_data; + } + + + iterator begin() noexcept{ + return m_data->m_items; + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + return m_data->m_items; + } + + iterator end() noexcept{ + return m_data->m_items + m_data->m_numItems; + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + return m_data->m_items + m_data->m_numItems; + } + +private: + Array(Handle h) : m_data(h){} + + Detail::Lock > m_data; + +}; + +// disable Array for incompatible types +template +class Array; +template +class Array; + + +/// Capability container holding an array of values, +/// and default and current indexes. +/// \tparam twty ID of the internal data type. +/// \tparam DataType Exported data type. +template::Type> +class Enumeration { + + friend class Capability; + +public: + static constexpr const ConType contype = ConType::Enumeration; + typedef DataType* iterator; + typedef const DataType* const_iterator; + + /// Creates an invalid container. + constexpr Enumeration() noexcept{} + + /// ID of the internal data type. + Type type() const noexcept{ + return m_data->m_itemType; + } + + /// Number of items in the array. + UInt32 size() const noexcept{ + return m_data->m_numItems; + } + + + /// Index of the currently selected item. + UInt32 currentIndex() const noexcept{ + return m_data->m_currIndex; + } + + /// Sets index of the currently selected item. + void setCurrentIndex(UInt32 index) noexcept{ + m_data->m_currIndex = index; + } + + /// Item at the current index. + DataType& currentItem() noexcept{ + return at(m_data->m_currIndex); + } + + /// Item at the current index. + const DataType& currentItem() const noexcept{ + return at(m_data->m_currIndex); + } + + /// Sets item at the current index. + void setCurrentItem(const DataType& item) noexcept{ + currentItem() = item; + } + + + /// Index of the default item. + UInt32 defaultIndex() const noexcept{ + return m_data->m_defIndex; + } + + /// Sets index of the default item. + void setDefaultIndex(UInt32 index) noexcept{ + m_data->m_defIndex = index; + } + + /// Item at the default index. + DataType& defaultItem() noexcept{ + return at(m_data->m_defIndex); + } + + /// Item at the default index. + const DataType& defaultItem() const noexcept{ + return at(m_data->m_defIndex); + } + + /// Sets item at the default index. + void setDefaultItem(const DataType& item) noexcept{ + defaultItem() = item; + } + + + /// Access contained value in array. + DataType& at(std::size_t i) noexcept{ + return m_data->m_items[i]; + } + + /// Access contained value in array. + const DataType& at(std::size_t i) const noexcept{ + return m_data->m_items[i]; + } + + /// Sets value in array. + void set(std::size_t i, const DataType& val) noexcept{ + at(i) = val; + } + + + DataType& operator[](std::size_t i) noexcept{ + return at(i); + } + + const DataType& operator[](std::size_t i) const noexcept{ + return at(i); + } + + operator bool() const noexcept{ + return m_data; + } + + + iterator begin() noexcept{ + return m_data->m_items; + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + return m_data->m_items; + } + + iterator end() noexcept{ + return m_data->m_items + m_data->m_numItems; + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + return m_data->m_items + m_data->m_numItems; + } + +private: + Enumeration(Handle h) : m_data(h){} + + Detail::Lock > m_data; + +}; + +// disable Enumeration for incompatible types +template +class Enumeration; +template +class Enumeration; + + +/// Capability container holding a range of numeric values, +/// and default and current values. +/// \tparam twty ID of the internal data type. +/// \tparam DataType Exported data type. +template::Type> +class Range { + + friend class Capability; + static_assert(Detail::IsNumeric::value, "not a numeric type"); + +private: + static constexpr const ConType contype = ConType::Range; + template + class IteratorImpl { + + friend class Range; + + public: + constexpr IteratorImpl() noexcept : + m_curr(), m_parent(nullptr){} + + IterDataType operator*() const noexcept{ + return m_curr; + } + + IteratorImpl& operator++() noexcept{ // prefix + m_curr += step(); + checkValue(); + return *this; + } + + IteratorImpl operator++(int) noexcept{ // postfix + IteratorImpl ret(*this); + m_curr += step(); + checkValue(); + return ret; + } + + IteratorImpl& operator--() noexcept{ // prefix + m_curr -= step(); + return *this; + } + + IteratorImpl operator--(int) noexcept{ // postfix + IteratorImpl ret(*this); + m_curr -= step(); + return ret; + } + + bool operator==(const IteratorImpl& o) const noexcept{ + return m_curr == o.m_curr && + (m_parent == o.m_parent || + (m_parent && o.m_parent && step() == o.step()) + ); + } + + bool operator!=(const IteratorImpl& o) const noexcept{ + return (*this == o); + } + + private: + IterDataType step() const noexcept{ + return m_parent->stepSize(); + } + + IterDataType max() const noexcept{ + return m_parent->maxValue(); + } + + void checkValue() noexcept{ + // avoid infinite loops in case no such N exists: `min + N * step == max` + if (m_curr > max()){ + m_curr = max() + step(); + } + } + + IteratorImpl(IterDataType curr, const Range& parent) noexcept : + m_curr(curr), m_parent(&parent){} + + IterDataType m_curr; + const Range* m_parent; + + }; + +public: + typedef IteratorImpl const_iterator; + + /// Creates an invalid container. + constexpr Range() noexcept{} + + /// ID of the internal data type. + Type type() const noexcept{ + return m_data->m_itemType; + } + + /// Minimal value in the range. + DataType minValue() const noexcept{ + return m_data->m_minValue; + } + + /// Sets minimal value in the range. + void setMinValue(DataType val) noexcept{ + m_data->m_minValue = val; + } + + /// Maximal value in the range. + DataType maxValue() const noexcept{ + return m_data->m_maxValue; + } + + /// Sets maximal value in the range. + void setMaxValue(DataType val) noexcept{ + m_data->m_maxValue = val; + } + + /// Size of a single step. + DataType stepSize() const noexcept{ + return m_data->m_stepSize; + } + + ///Sets size of a single step. + void setStepSize(DataType val) noexcept{ + m_data->m_stepSize = val; + } + + /// Default value in the range. + DataType defaultValue() const noexcept{ + return m_data->m_defValue; + } + + /// Sets default value in the range. + void setDefaultValue(DataType val) noexcept{ + m_data->m_defValue = val; + } + + /// Current value in the range. + DataType currentValue() const noexcept{ + return m_data->m_currValue; + } + + /// Sets current value in the range. + void setCurrentValue(DataType val) noexcept{ + m_data->m_currValue = val; + } + + operator bool() const noexcept{ + return m_data; + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + return const_iterator(m_data->m_minValue, *this); + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + auto step = m_data->m_stepSize; + if (step != DataType()){ + return const_iterator(m_data->m_maxValue + step, *this); + } else { + return cbegin(); // no items with step equal to zero + } + } + +private: + Range(Handle h) : m_data(h){} + + Detail::Lock > m_data; + +}; + +// disable Range for incompatible types +// (non-numeric types) +template +class Range; +template +class Range; +template +class Range; +template +class Range; +template +class Range; +template +class Range; +template +class Range; +template +class Range; + + +namespace Detail { + +template +class CapDataImpl; + +template +class CapData; + +/// Capability iterator. +/// The default implementation is designed for non-numeric values. +/// Meaning it can't handle ranges. +template // false +class CapIterator { + + friend class Capability; + + template + friend class CapDataImpl; + +public: + constexpr CapIterator() noexcept : + m_ptr(nullptr){} + + DataType& operator*() const noexcept{ + return *m_ptr; + } + + CapIterator& operator++() noexcept{ // prefix + ++m_ptr; + return *this; + } + + CapIterator operator++(int) noexcept{ // postfix + CapIterator ret(*this); + ++m_ptr; + return ret; + } + + CapIterator& operator--() noexcept{ // prefix + --m_ptr; + return *this; + } + + CapIterator operator--(int) noexcept{ // postfix + CapIterator ret(*this); + --m_ptr; + return ret; + } + + bool operator==(const CapIterator& o) const noexcept{ + return m_ptr == o.m_ptr; + } + + bool operator!=(const CapIterator& o) const noexcept{ + return !(*this == o); + } + +private: + constexpr CapIterator(DataType* ptr) noexcept : + m_ptr(ptr){} + + DataType* m_ptr; + +}; + +/// Capability iterator. +/// This specialization can handles numeric values only. +/// Ranges included. +template +class CapIterator { + + friend class Capability; + + template + friend class CapDataImpl; + +public: + typedef typename std::remove_const::type ReturnType; + + constexpr CapIterator() noexcept : + m_ptr(nullptr), m_isPtr(true){} + + ReturnType operator*() const noexcept{ + if (m_isPtr){ + return *m_ptr; + } else { + return *m_rng; + } + } + + CapIterator& operator++() noexcept{ // prefix + if (m_isPtr){ + ++m_ptr; + } else { + ++m_rng; + } + + return *this; + } + + CapIterator operator++(int) noexcept{ // postfix + CapIterator ret(*this); + if (m_isPtr){ + ++m_ptr; + } else { + ++m_rng; + } + + return ret; + } + + CapIterator& operator--() noexcept{ // prefix + if (m_isPtr){ + --m_ptr; + } else { + --m_rng; + } + + return *this; + } + + CapIterator operator--(int) noexcept{ // postfix + CapIterator ret(*this); + if (m_isPtr){ + --m_ptr; + } else { + --m_rng; + } + + return ret; + } + + bool operator==(const CapIterator& o) const noexcept{ + if (m_isPtr != o.m_isPtr){ + return false; + } + + return m_isPtr ? m_ptr == o.m_ptr : m_rng == o.m_rng; + } + + bool operator!=(const CapIterator& o) const noexcept{ + return !(*this == o); + } + +private: + constexpr CapIterator(DataType* ptr) noexcept : + m_ptr(ptr), m_isPtr(true){} + + constexpr CapIterator(typename Range::const_iterator rng) noexcept : + m_rng(rng), m_isPtr(false){} + + union { + DataType* m_ptr; + typename Range::const_iterator m_rng; + }; + bool m_isPtr; + +}; + +/// Capability iterator lock implementation. +/// The default implementation is designed for non-numeric values. +/// Meaning it can't handle ranges. +template::Type> // numeric=false +class CapDataImpl { + + friend class Capability; + + template + friend class CapData; + +public: + typedef CapIterator const_iterator; + + /// Creates an invalid container. + constexpr CapDataImpl() noexcept : + m_data(){ + + static_assert(type != Type::DontCare, "type may not be DontCare"); + static_assert(sizeof(typename Detail::Twty::Type) == sizeof(DataType), "type sizes dont match"); + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + return const_iterator(reinterpret_cast(m_data.data() + offset())); + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + return const_iterator(reinterpret_cast(m_data.data() + offset()) + size()); + } + + UInt32 size() const noexcept{ + switch (m_conType){ + case ConType::Array: + case ConType::Enumeration: + return reinterpret_cast*>(m_data.data())->m_numItems; + case ConType::OneValue: + return 1; + case ConType::Range: + default: + return 0; // should not happen + } + } + +private: + CapDataImpl(const Capability& cap); + + UInt32 offset() const noexcept{ + switch (m_conType){ + case ConType::Array: + return sizeof(Type) + sizeof(UInt32); + case ConType::Enumeration: + return sizeof(Type) + 3 * sizeof(UInt32); + case ConType::OneValue: + return sizeof(Type); + case ConType::Range: + default: + return 0; // should not happen + } + } + + ConType m_conType; + Detail::Lock m_data; // actual type resolved at runtime + +}; + +/// Capability iterator lock implementation. +/// This specialization can handles numeric values only. +/// Ranges included. +template +class CapDataImpl { + + friend class Capability; + + template + friend class CapData; + +public: + typedef CapIterator const_iterator; + + /// Creates an invalid container. + constexpr CapDataImpl() noexcept : + m_data(){ + + static_assert(type != Type::DontCare, "type may not be DontCare"); + static_assert(sizeof(typename Detail::Twty::Type) == sizeof(DataType), "type sizes dont match"); + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + if (m_conType != ConType::Range){ + return const_iterator(reinterpret_cast(m_data.data() + offset())); + } else { + const auto& rng = *Detail::alias_cast*>(&m_data); + return const_iterator(rng.cbegin()); + } + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + if (m_conType != ConType::Range){ + return const_iterator(reinterpret_cast(m_data.data() + offset()) + size()); + } else { + const auto& rng = *Detail::alias_cast*>(&m_data); + return const_iterator(rng.cend()); + } + } + + UInt32 size() const noexcept{ + switch (m_conType){ + case ConType::Array: + case ConType::Enumeration: + return reinterpret_cast*>(m_data.data())->m_numItems; + case ConType::OneValue: + return 1; + case ConType::Range: { + auto& rng = *reinterpret_cast*>(m_data.data()); + if (rng.m_stepSize != DataType()){ + return static_cast((Detail::abs(rng.m_maxValue - rng.m_minValue) / rng.m_stepSize).toFloat()) + 1; + } else { + return 0; + } + } + default: + return 0; // should not happen + } + } + +private: + CapDataImpl(const Capability& cap); + + UInt32 offset() const noexcept{ + switch (m_conType){ + case ConType::Array: + return sizeof(Type) + sizeof(UInt32); + case ConType::Enumeration: + return sizeof(Type) + 3 * sizeof(UInt32); + case ConType::OneValue: + return sizeof(Type); + case ConType::Range: + default: + return 0; // should not happen + } + } + + ConType m_conType; + Detail::Lock m_data; // actual type resolved at runtime + +}; + +/// Capability iterator lock. +template +class CapData : public CapDataImpl::value, DataType> { + + typedef CapDataImpl::value, DataType> Base; + +public: + constexpr CapData() noexcept{} + + CapData(const Capability& cap) : + Base(cap){} + +}; + + +/// Capability current item implementation. +/// The default implementation is designed for non-numeric values. +/// Meaning it can't handle ranges. +template // false +struct CurrentItemImpl { + static DataType item(Capability& cap); +}; + +/// Capability current item implementation. +/// This specialization can handles numeric values only. +/// Ranges included. +template +struct CurrentItemImpl { + static DataType item(Capability& cap); +}; + +/// Capability current item. +template +struct CurrentItem : CurrentItemImpl::value> { + +}; + +} + +/// Base capability exception. +class CapabilityException : public Exception { + +public: + virtual const char* what() const noexcept override{ + return "Capability handling error."; + } + +}; + +/// Invalid or unsupported container capability exception. +class ContainerException : public CapabilityException { + +public: + virtual const char* what() const noexcept override{ + return "Unexpected container."; + } + +}; + +/// Invalid, unsupported or mismatched item type identifier capability exception. +class ItemTypeException : public CapabilityException { + +public: + virtual const char* what() const noexcept override{ + return "Invalid item type."; + } + +}; + +/// No data capability exception. +/// Capability does not contain any data (container). +class DataException : public CapabilityException { + +public: + virtual const char* what() const noexcept override{ + return "No data."; + } + +}; + +TWPP_DETAIL_PACK_BEGIN +/// TWAIN capability. +/// Any access to containers must be finished before destroying +/// the according capability instance. +class Capability { + + template + friend class Detail::CapDataImpl; + +public: + /// Creates capability holding OneValue container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param value Initial value. + /// \throw std::bad_alloc + template + static Capability createOneValue(CapType cap, const DataType& value = DataType()){ + Capability ret(cap, ConType::OneValue, type, sizeof(Detail::OneValueData)); + auto ov = ret.oneValue(); + ov.setItem(value); + return std::move(ret); + } + + /// Creates capability holding OneValue container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param value Initial value. + /// \throw std::bad_alloc + template + static Capability createOneValue(CapType cap, const typename Detail::Twty::Type& value = typename Detail::Twty::Type()){ + return createOneValue::Type>(cap, value); + } + + /// Creates capability holding OneValue container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param value Initial value. + /// \throw std::bad_alloc + template + static Capability createOneValue(CapType cap, const T& value = T()){ + return createOneValue::twty, T>(cap, value); + } + + /// Creates capability holding OneValue container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param value Initial value. + /// \throw std::bad_alloc + template + static Capability createOneValue(const typename Detail::Cap::DataType& value = typename Detail::Cap::DataType()){ + return createOneValue::twty, typename Detail::Cap::DataType>(cap, value); + } + + + /// Creates capability holding Array container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, UInt32 size){ + Capability ret(cap, ConType::Array, type, sizeof(Detail::ArrayData) - sizeof(DataType) + size * sizeof(DataType)); + auto arr = ret.array(); + arr.m_data->m_numItems = size; + return std::move(ret); + } + + /// Creates capability holding Array container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, UInt32 size){ + return createArray::Type>(cap, size); + } + + /// Creates capability holding Array container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, std::initializer_list values){ + Capability ret = createArray(cap, static_cast(values.size())); + auto arr = ret.array(); + + UInt32 i = 0; + for (const auto& val : values){ + arr[i] = val; + i++; + } + + return std::move(ret); + } + + /// Creates capability holding Array container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, std::initializer_list::Type> values){ + return createArray::Type>(cap, values); + } + + /// Creates capability holding Array container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, UInt32 size){ + return createArray::twty, T>(cap, size); + } + + /// Creates capability holding Array container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \throw std::bad_alloc + template + static Capability createArray(CapType cap, std::initializer_list values){ + return createArray::twty, T>(cap, values); + } + + /// Creates capability holding Array container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param size Number of elements in the array. + /// \throw std::bad_alloc + template + static Capability createArray(UInt32 size){ + return createArray::twty, typename Detail::Cap::DataType>(cap, size); + } + + /// Creates capability holding Array container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param values Initial values in the array. + /// \throw std::bad_alloc + template + static Capability createArray(std::initializer_list::DataType> values){ + return createArray::twty, typename Detail::Cap::DataType>(cap, values); + } + + + /// Creates capability holding Enumeration container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, UInt32 size, UInt32 currIndex = 0, UInt32 defIndex = 0){ + Capability ret(cap, ConType::Enumeration, type, sizeof(Detail::EnumerationData) - sizeof(DataType) + size * sizeof(DataType)); + auto enm = ret.enumeration(); + enm.m_data->m_numItems = size; + enm.m_data->m_currIndex = currIndex; + enm.m_data->m_defIndex = defIndex; + return std::move(ret); + } + + /// Creates capability holding Enumeration container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, UInt32 size, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::Type>(cap, size, currIndex, defIndex); + } + + /// Creates capability holding Enumeration container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, std::initializer_list values, UInt32 currIndex = 0, UInt32 defIndex = 0){ + Capability ret = createEnumeration(cap, static_cast(values.size()), currIndex, defIndex); + auto enm = ret.enumeration(); + + UInt32 i = 0; + for (const auto& val : values){ + enm[i] = val; + i++; + } + + return std::move(ret); + } + + /// Creates capability holding Enumeration container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, std::initializer_list::Type> values, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::Type>(cap, values, currIndex, defIndex); + } + + /// Creates capability holding Enumeration container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param size Number of elements in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, UInt32 size, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::twty, T>(cap, size, currIndex, defIndex); + } + + /// Creates capability holding Enumeration container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param values Initial values in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(CapType cap, std::initializer_list values, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::twty, T>(cap, values, currIndex, defIndex); + } + + /// Creates capability holding Enumeration container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param size Number of elements in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(UInt32 size, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::twty, typename Detail::Cap::DataType>(cap, size, currIndex, defIndex); + } + + /// Creates capability holding Enumeration container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param values Initial values in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + template + static Capability createEnumeration(std::initializer_list::DataType> values, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return createEnumeration::twty, typename Detail::Cap::DataType>(cap, values, currIndex, defIndex); + } + + + /// Creates capability holding Range container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \param cap Capability type. + /// \param min Minimal range value. + /// \param max Maximal range value. + /// \param step Size of a single step. + /// \param curr Current value. + /// \param def Default value. + /// \throw std::bad_alloc + template + static Capability createRange(CapType cap, DataType min, DataType max, DataType step, DataType curr, DataType def){ + Capability ret(cap, ConType::Range, type, sizeof(Detail::RangeData)); + auto rng = ret.range(); + rng.setMinValue(min); + rng.setMaxValue(max); + rng.setStepSize(step); + rng.setCurrentValue(curr); + rng.setDefaultValue(def); + return std::move(ret); + } + + /// Creates capability holding Range container. + /// \tparam type ID of the internal data type. + /// \param cap Capability type. + /// \param min Minimal range value. + /// \param max Maximal range value. + /// \param step Size of a single step. + /// \param curr Current value. + /// \param def Default value. + /// \throw std::bad_alloc + template + static Capability createRange( + CapType cap, + typename Detail::Twty::Type min, + typename Detail::Twty::Type max, + typename Detail::Twty::Type step, + typename Detail::Twty::Type curr, + typename Detail::Twty::Type def + ){ + return createRange::Type>(cap, min, max, step, curr, def); + } + + /// Creates capability holding Range container. + /// \tparam T Data type. + /// \param cap Capability type. + /// \param min Minimal range value. + /// \param max Maximal range value. + /// \param step Size of a single step. + /// \param curr Current value. + /// \param def Default value. + /// \throw std::bad_alloc + template + static Capability createRange(CapType cap, T min, T max, T step, T curr, T def){ + return createRange::twty, T>(cap, min, max, step, curr, def); + } + + /// Creates capability holding Range container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \param min Minimal range value. + /// \param max Maximal range value. + /// \param step Size of a single step. + /// \param curr Current value. + /// \param def Default value. + /// \throw std::bad_alloc + template + static Capability createRange( + typename Detail::Cap::DataType min, + typename Detail::Cap::DataType max, + typename Detail::Cap::DataType step, + typename Detail::Cap::DataType curr, + typename Detail::Cap::DataType def + ){ + return createRange::twty, typename Detail::Cap::DataType>( + cap, min, max, step, curr, def); + } + + + /// Creates capability of the supplied type without any data. + /// Useful for retrieving data from data source. + explicit Capability(CapType cap) noexcept : + m_cap(cap), m_conType(ConType::DontCare), m_cont(){} + + Capability(Capability&&) = default; + Capability& operator=(Capability&&) = default; + + /// Capability type. + CapType type() const noexcept{ + return m_cap; + } + + /// Container type. + ConType container() const noexcept{ + return m_conType; + } + + /// Item type. + /// Valid only if the capability contains data. + /// \throw DataException When there is no data. + Type itemType() const{ + if (!m_cont){ + throw DataException(); + } + + return *m_cont.lock().data(); + } + + operator bool() const noexcept{ + return m_cont; + } + + /// Contained OneValue container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not OneValue. + /// \throw ItemTypeException When item type does not match. + template + OneValue oneValue(){ + return containerCheck(); + } + + /// Contained OneValue container. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not OneValue. + /// \throw ItemTypeException When item type does not match. + template + OneValue::Type> oneValue(){ + return oneValue::Type>(); + } + + /// Contained OneValue container. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not OneValue. + /// \throw ItemTypeException When item type does not match. + template + OneValue::twty, T> oneValue(){ + return oneValue::twty, T>(); + } + + /// Contained OneValue container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not OneValue. + /// \throw ItemTypeException When item type does not match. + template + OneValue::twty, typename Detail::Cap::DataType> oneValue(){ + return oneValue::twty, typename Detail::Cap::DataType>(); + } + + /// Contained Array container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Array. + /// \throw ItemTypeException When item type does not match. + template + Array array(){ + return containerCheck(); + } + + /// Contained Array container. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Array. + /// \throw ItemTypeException When item type does not match. + template + Array::Type> array(){ + return array::Type>(); + } + + /// Contained Array container. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Array. + /// \throw ItemTypeException When item type does not match. + template + Array::twty, T> array(){ + return array::twty, T>(); + } + + /// Contained Array container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Array. + /// \throw ItemTypeException When item type does not match. + template + Array::twty, typename Detail::Cap::DataType> array(){ + return array::twty, typename Detail::Cap::DataType>(); + } + + /// Contained Enumeration container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Enumeration enumeration(){ + return containerCheck(); + } + + /// Contained Enumeration container. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Enumeration::Type> enumeration(){ + return enumeration::Type>(); + } + + /// Contained Enumeration container. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Enumeration::twty, T> enumeration(){ + return enumeration::twty, T>(); + } + + /// Contained Enumeration container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Enumeration::twty, typename Detail::Cap::DataType> enumeration(){ + return enumeration::twty, typename Detail::Cap::DataType>(); + } + + /// Contained Range container. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Range range(){ + return containerCheck(); + } + + /// Contained Range container. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + template + Range::Type> range(){ + return range::Type>(); + } + + /// Contained Range container. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Range. + /// \throw ItemTypeException When item type does not match. + template + Range::twty, T> range(){ + return range::twty, T>(); + } + + /// Contained Range container. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Range. + /// \throw ItemTypeException When item type does not match. + template + Range::twty, typename Detail::Cap::DataType> range(){ + return range::twty, typename Detail::Cap::DataType>(); + } + + template + using Data = Detail::CapData; + + /// Returns a data container for iterating over all possible values. + /// Use this only if you don't care about current or default values and container type. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is invalid. + /// \throw ItemTypeException When item type does not match. + template + Data data() const{ + return *this; + } + + /// Returns a data container for iterating over all possible values. + /// Use this only if you don't care about current or default values and container type. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is invalid. + /// \throw ItemTypeException When item type does not match. + template + Data::Type> data() const{ + return *this; + } + + /// Returns a data container for iterating over all possible values. + /// Use this only if you don't care about current or default values and container type. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is invalid. + /// \throw ItemTypeException When item type does not match. + template + Data::twty, T> data() const{ + return *this; + } + + /// Returns a data container for iterating over all possible values. + /// Use this only if you don't care about current or default values and container type. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is invalid. + /// \throw ItemTypeException When item type does not match. + template + Data::twty, typename Detail::Cap::DataType> data() const{ + return *this; + } + + + /// Returns a copy of the current item of this capability. + /// Can be used only with Enumeration, OneValue, and Range containers. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration, OneValue, nor Range. + /// \throw ItemTypeException When item type does not match. + template + DataType currentItem(){ + return Detail::CurrentItem::item(*this); + } + + /// Returns a copy of the current item of this capability. + /// Can be used only with Enumeration, OneValue, and Range containers. + /// \tparam type ID of the internal data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration, OneValue, nor Range. + /// \throw ItemTypeException When item type does not match. + template + typename Detail::Twty::Type currentItem(){ + return currentItem::Type>(); + } + + /// Returns a copy of the current item of this capability. + /// Can be used only with Enumeration, OneValue, and Range containers. + /// \tparam T Data type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration, OneValue, nor Range. + /// \throw ItemTypeException When item type does not match. + template + T currentItem(){ + return currentItem::twty, T>(); + } + + /// Returns a copy of the current item of this capability. + /// Can be used only with Enumeration, OneValue, and Range containers. + /// \tparam cap Capability type. Data types are set accordingly. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration, OneValue, nor Range. + /// \throw ItemTypeException When item type does not match. + template + typename Detail::Cap::DataType currentItem(){ + return currentItem::twty, typename Detail::Cap::DataType>(); + } + +private: + /// \throw DataException + /// \throw ContainerException + /// \throw ItemTypeException + Capability(CapType cap, ConType conType, Type twty, UInt32 size) : + m_cap(cap), m_conType(conType), m_cont(Detail::alloc(size)){ + + *m_cont.lock().data() = twty; + } + + template class Container, Type type, typename DataType> + Container containerCheck(){ + static_assert(type != Type::DontCare, "type may not be DontCare"); + static_assert(sizeof(typename Detail::Twty::Type) == sizeof(DataType), "type sizes dont match"); + + if (!m_cont){ + throw DataException(); + } + + if (Container::contype != container()){ + throw ContainerException(); + } + + Container ret(m_cont.get()); + if (type != ret.type()){ + throw ItemTypeException(); + } + + return std::move(ret); + } + + CapType m_cap; + ConType m_conType; + Detail::UniqueHandle m_cont; + +}; +TWPP_DETAIL_PACK_END + +/// Invalid, unsupported or mismatched item type identifier capability exception. +/// Holds the Capability instance that caused the exception. +class CapItemTypeException : public ItemTypeException { + +public: + CapItemTypeException(Capability cap) noexcept : + m_cap(std::move(cap)){} + + CapItemTypeException(CapItemTypeException&&) = default; + CapItemTypeException& operator=(CapItemTypeException&&) = default; + + CapItemTypeException(const CapItemTypeException&) = delete; + CapItemTypeException& operator=(const CapItemTypeException&) = delete; + + Capability& capability() noexcept{ + return m_cap; + } + + const Capability& capability() const noexcept{ + return m_cap; + } + + virtual const char* what() const noexcept override{ + return "Unexpected item type."; + } + +private: + Capability m_cap; + +}; + +/// Invalid, unexpected, unmatched capability type. +/// Holds the Capability instance that caused the exception. +class CapTypeException : public CapabilityException { + +public: + CapTypeException(Capability cap) noexcept : + m_cap(std::move(cap)){} + + CapTypeException(CapTypeException&&) = default; + CapTypeException& operator=(CapTypeException&&) = default; + + CapTypeException(const CapTypeException&) = delete; + CapTypeException& operator=(const CapTypeException&) = delete; + + Capability& capability() noexcept{ + return m_cap; + } + + const Capability& capability() const noexcept{ + return m_cap; + } + + virtual const char* what() const noexcept override{ + return "Unexpected capability type."; + } + +private: + Capability m_cap; + +}; + +class Source; + +/// Convenience Capability wrapper class. +/// Guaranteed to contain the same capability type and item type +/// throughout the whole lifetime. +template +class Cap { + + friend class Source; + +public: + typedef typename Detail::Cap::DataType DataType; + static constexpr const Type twty = Detail::Cap::twty; + + /// Creates capability holding OneValue container. + /// \param value Initial value. + /// \throw std::bad_alloc + static Cap createOneValue(const DataType& value = DataType()){ + return Cap(Capability::createOneValue(value), 0); + } + + + /// Creates capability holding Array container. + /// \param size Number of elements in the array. + /// \throw std::bad_alloc + static Cap createArray(UInt32 size){ + return Cap(Capability::createArray(size), 0); + } + + /// Creates capability holding Array container. + /// \param values Initial values in the array. + /// \throw std::bad_alloc + static Cap createArray(std::initializer_list values){ + return Cap(Capability::createArray(values), 0); + } + + + /// Creates capability holding Enumeration container. + /// \param size Number of elements in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + static Cap createEnumeration(UInt32 size, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return Cap(Capability::createEnumeration(size, currIndex, defIndex), 0); + } + + /// Creates capability holding Enumeration container. + /// \param values Initial values in the array. + /// \param currIndex Index of the currently selected item. + /// \param defIndex Index of the default item. + /// \throw std::bad_alloc + static Cap createEnumeration(std::initializer_list values, UInt32 currIndex = 0, UInt32 defIndex = 0){ + return Cap(Capability::createEnumeration(values, currIndex, defIndex), 0); + } + + + /// Creates capability holding Range container. + /// \param min Minimal range value. + /// \param max Maximal range value. + /// \param step Size of a single step. + /// \param curr Current value. + /// \param def Default value. + /// \throw std::bad_alloc + static Cap createRange(DataType min, DataType max, DataType step, DataType curr, DataType def){ + return Cap(Capability::createRange(min, max, step, curr, def), 0); + } + + /// Creates capability of the supplied type without any data. + /// Useful for retrieving data from data source. + Cap() noexcept : m_cap(cap){} + + /// Converts Capability to Cap. + /// The capability ownership is taken over. + /// Capability type and item type checkings are performed. In case of exception, + /// the original Capability instance may be retrieved from the exception object. + /// \param capability Capability to be converted to Cap. + /// \throw CapTypeException When input capability type does not match the + /// capability type of this template class. + /// \throw CapItemTypeException When input capability item type does not match + /// the expected item type of the capability. + explicit Cap(Capability capability) : + m_cap(std::move(capability)){ + + checkTypes(); + } + + Cap(Cap&&) = default; + Cap& operator=(Cap&&) = default; + + Cap(const Cap&) = delete; + Cap& operator=(const Cap&) = delete; + + /// Capability type. + CapType type() const noexcept{ + return m_cap.type(); + } + + /// Container type. + ConType container() const noexcept{ + return m_cap.container(); + } + + /// Item type. + /// Valid only if the capability contains data. + /// \throw DataException When there is no data. + Type itemType() const{ + return m_cap.itemType(); + } + + operator bool() const noexcept{ + return m_cap; + } + + /// Contained OneValue container. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not OneValue. + /// \throw ItemTypeException When item type does not match. + OneValue oneValue(){ + return m_cap.oneValue(); + } + + /// Contained Array container. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Array. + /// \throw ItemTypeException When item type does not match. + Array array(){ + return m_cap.array(); + } + + /// Contained Enumeration container. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + Enumeration enumeration(){ + return m_cap.enumeration(); + } + + /// Contained Range container. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration. + /// \throw ItemTypeException When item type does not match. + Range range(){ + return m_cap.range(); + } + + + typedef Detail::CapData Data; + + /// Returns a data container for iterating over all possible values. + /// Use this only if you don't care about current or default values and container type. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is invalid. + /// \throw ItemTypeException When item type does not match. + Data data() const{ + return m_cap.data(); + } + + + /// Returns a copy of the current item of this capability. + /// Can be used only with Enumeration, OneValue, and Range containers. + /// \throw DataException When there is no data. + /// \throw ContainerException When container is not Enumeration, OneValue, nor Range. + /// \throw ItemTypeException When item type does not match. + DataType currentItem(){ + return m_cap.currentItem(); + } + + /// Moves out the contained Capability instance. + /// This instance becomes empty. + Capability toCapability() noexcept{ + return std::move(m_cap); + } + +private: + Cap(Capability capability, int) noexcept : + m_cap(std::move(capability)){} + + void checkTypes(){ + if (m_cap){ + if (m_cap.type() != cap){ + throw CapTypeException(std::move(m_cap)); + } + + if (m_cap.itemType() != twty){ + throw CapItemTypeException(std::move(m_cap)); + } + } + } + + Capability m_cap; + +}; + + +namespace Detail { + +/// \throw DataException +/// \throw ContainerException +/// \throw ItemTypeException +template // numeric = false +inline CapDataImpl::CapDataImpl(const Capability& cap) : + m_conType(cap.m_conType), m_data(cap.m_cont.get()){ + + static_assert(type != Type::DontCare, "type may not be DontCare"); + static_assert(sizeof(typename Detail::Twty::Type) == sizeof(DataType), "type sizes dont match"); + + if (!cap.m_cont){ + throw DataException(); + } + + switch (m_conType){ + case ConType::Array: + case ConType::Enumeration: + case ConType::OneValue: + break; + case ConType::Range: + default: + throw ContainerException(); + } + + if (type != cap.itemType()){ + throw ItemTypeException(); + } +} + +/// \throw DataException +/// \throw ContainerException +/// \throw ItemTypeException +template +inline CapDataImpl::CapDataImpl(const Capability& cap) : + m_conType(cap.m_conType), m_data(cap.m_cont.get()){ + + static_assert(type != Type::DontCare, "type may not be DontCare"); + static_assert(sizeof(typename Detail::Twty::Type) == sizeof(DataType), "type sizes dont match"); + + if (!cap.m_cont){ + throw DataException(); + } + + switch (m_conType){ + case ConType::Array: + case ConType::Enumeration: + case ConType::OneValue: + case ConType::Range: + break; + default: + throw ContainerException(); + } + + if (type != cap.itemType()){ + throw ItemTypeException(); + } +} + +/// \throw DataException +/// \throw ContainerException +/// \throw ItemTypeException +template // false +DataType CurrentItemImpl::item(Capability& cap){ + switch (cap.container()){ + case ConType::Enumeration: + return cap.enumeration().currentItem(); + + case ConType::OneValue: + return cap.oneValue().item(); + + default: + throw ContainerException(); + } +} + +/// \throw DataException +/// \throw ContainerException +/// \throw ItemTypeException +template +DataType CurrentItemImpl::item(Capability& cap){ + switch (cap.container()){ + case ConType::Enumeration: + return cap.enumeration().currentItem(); + + case ConType::OneValue: + return cap.oneValue().item(); + + case ConType::Range: + return cap.range().currentValue(); + + default: + throw ContainerException(); + } +} + +} + +} + +#endif // TWPP_DETAIL_FILE_CAPABILITY_HPP + diff --git a/twpp/cie.hpp b/twpp/cie.hpp new file mode 100644 index 00000000..2a1f6410 --- /dev/null +++ b/twpp/cie.hpp @@ -0,0 +1,269 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_CIE_HPP +#define TWPP_DETAIL_FILE_CIE_HPP + +#if 0 +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Part of CieColor structure. +class CiePoint { + +public: + /// Creates zero-initialized cie point. + constexpr CiePoint() noexcept : + m_x(), m_y(), m_z(){} + + /// Creates cie point with desired values. + constexpr CiePoint(Fix32 x, Fix32 y, Fix32 z) noexcept : + m_x(x), m_y(y), m_z(z){} + + /// X value of CIE space. + constexpr Fix32 x() const noexcept{ + return m_x; + } + + /// Y value of CIE space. + constexpr Fix32 y() const noexcept{ + return m_y; + } + + /// Z value of CIE space. + constexpr Fix32 z() const noexcept{ + return m_z; + } + + /// Sets x value of CIE space. + void setX(Fix32 x) noexcept{ + m_x = x; + } + + /// Sets y value of CIE space. + void setY(Fix32 y) noexcept{ + m_y = y; + } + + /// Sets z value of CIE space. + void setZ(Fix32 z) noexcept{ + m_z = z; + } + +private: + Fix32 m_x; + Fix32 m_y; + Fix32 m_z; + +}; + +/// Defines parameters for channel transformations. +/// Part of TransformStage. +class DecodeFunction { + +public: + /// Creates zero-initialized decode function. + constexpr DecodeFunction() noexcept{} + + /// Creates initialized decode function. + constexpr DecodeFunction( + Fix32 startIn, + Fix32 breakIn, + Fix32 endIn, + Fix32 startOut, + Fix32 breakOut, + Fix32 endOut, + Fix32 gamma, + Fix32 sampleCount + ) noexcept : + m_startIn(startIn), m_breakIn(breakIn), m_endIn(endIn), + m_startOut(startOut), m_breakOut(breakOut), m_endOut(endOut), + m_gamma(gamma), m_sampleCount(sampleCount){} + + /// Starting input value. + constexpr Fix32 startIn() const noexcept{ + return m_startIn; + } + + /// Sets starting input value. + void setStartIn(Fix32 startIn) noexcept{ + m_startIn = startIn; + } + + /// Ending input value. + constexpr Fix32 breakIn() const noexcept{ + return m_breakIn; + } + + /// Sets ending input value. + void setBreakIn(Fix32 breakIn) noexcept{ + m_breakIn = breakIn; + } + + /// Input value when to switch from linear to gamma transformation. + constexpr Fix32 endIn() const noexcept{ + return m_endIn; + } + + /// Sets input value when to switch from linear to gamma transformation. + void setEndIn(Fix32 endIn) noexcept{ + m_endIn = endIn; + } + + /// Starting output value. + constexpr Fix32 startOut() const noexcept{ + return m_startOut; + } + + /// Sets starting output value. + void setStartOut(Fix32 startOut) noexcept{ + m_startOut = startOut; + } + + /// Ending output value. + constexpr Fix32 breakOut() const noexcept{ + return m_breakOut; + } + + /// Sets ending output value. + void setBreakOut(Fix32 breakOut) noexcept{ + m_breakOut = breakOut; + } + + /// Output value when to switch from linear to gamma transformation. + constexpr Fix32 endOut() const noexcept{ + return m_endOut; + } + + /// Sets output value when to switch from linear to gamma transformation. + void setEndOut(Fix32 endOut) noexcept{ + m_endOut = endOut; + } + + /// Constant, exponential used in gamma funciton. + constexpr Fix32 gamma() const noexcept{ + return m_gamma; + } + + /// Sets constant, exponential used in gamma funciton. + void setGamma(Fix32 gamma) noexcept{ + m_gamma = gamma; + } + + /// Number of samples in lookup table. + constexpr Fix32 sampleCount() const noexcept{ + return m_sampleCount; + } + + /// Sets number of samples in lookup table. + void setSampleCount(Fix32 sampleCount) noexcept{ + m_sampleCount = sampleCount; + } + +private: + Fix32 m_startIn; + Fix32 m_breakIn; + Fix32 m_endIn; + Fix32 m_startOut; + Fix32 m_breakOut; + Fix32 m_endOut; + Fix32 m_gamma; + Fix32 m_sampleCount; + +}; + +/// Parameters of ABC or LMN transformations. +/// Refer to manual for more information about members. +class TransformStage { + +public: + typedef std::array Decode; + typedef std::array, 3> Mix; + + constexpr TransformStage() noexcept : + m_decode(), m_mix(){} + + constexpr TransformStage(const Decode& decode) noexcept : + m_decode(decode), m_mix(){} + + constexpr TransformStage(const Mix& mix) noexcept : + m_decode(), m_mix(mix){} + + constexpr TransformStage(const Decode& decode, const Mix& mix) noexcept : + m_decode(decode), m_mix(mix){} + + constexpr const Decode& decode() const noexcept{ + return m_decode; + } + + Decode& decode() noexcept{ + return m_decode; + } + + constexpr const Mix& mix() const noexcept{ + return m_mix; + } + + Mix& mix() noexcept{ + return m_mix; + } + +private: + Decode m_decode; + Mix m_mix; + +}; + +namespace Unsupported { + +// TODO CieColor +/// Cie color +/// Currently stub, more info required. +struct CieColor { + UInt16 m_colorSpace; + Bool m_lowEndian; + Bool m_deviceDependent; + Int32 m_versionNumber; + TransformStage m_stageAbc; + TransformStage m_stageLmn; + CiePoint m_whitePoint; + CiePoint m_blackPoint; + CiePoint m_whitePaper; + CiePoint m_blackInk; + Fix32 m_samples[1]; // <- how many elements? how to use? +}; + +} + +TWPP_DETAIL_PACK_END + +} +#endif + +#endif // TWPP_DETAIL_FILE_CIE_HPP + diff --git a/twpp/curveresponse.hpp b/twpp/curveresponse.hpp new file mode 100644 index 00000000..e5d71f71 --- /dev/null +++ b/twpp/curveresponse.hpp @@ -0,0 +1,116 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_CURVERESPONSE_HPP +#define TWPP_DETAIL_FILE_CURVERESPONSE_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +/// Base response class. +class CurveResponse { + +public: + CurveResponse() noexcept{} + + /// Creates a new (Rgb|Gray)Response with default elements, make sure that info.bitsPerPixel() is <= 8. + /// \throw RangeException When info.bitsPerPixel() is negative or greater than 8. + explicit CurveResponse(const ImageInfo& info) : CurveResponse(info.bitsPerPixel()){} + + /// Creates a new (Rgb|Gray)Response with default elements, make sure that bitsPerPixel is <= 8. + /// \throw RangeException When bitsPerPixel is negative or greater than 8. + explicit CurveResponse(Int16 bitsPerPixel){ + if (bitsPerPixel <= 0 || bitsPerPixel > 8){ + throw RangeException(); + } + + UInt16 size = 1 << static_cast(bitsPerPixel); + m_data.reset(new Element8[size]); + for (UInt16 i = 0; i < size; i++){ + m_data[i] = Element8(static_cast(i)); // 0..255 max + } + } + + /// Array of size `2^ImageInfo.bitesPerPixel()`, up to 256 elements (2^8) + Element8* data() noexcept{ + return m_data.get(); + } + + /// Array of size `2^ImageInfo.bitesPerPixel()`, up to 256 elements (2^8) + const Element8* data() const noexcept{ + return m_data.get(); + } + +private: + std::unique_ptr m_data; + +}; + +} + +/// Rgb response class. +class RgbResponse : public Detail::CurveResponse { + +public: + RgbResponse() noexcept{} + + /// Creates a new RgbResponse with default elements, make sure that info.bitesPerPixel() is <= 8. + /// \throw RangeException When info.bitsPerPixel() is negative or greater than 8. + explicit RgbResponse(const ImageInfo& info) : + Detail::CurveResponse(info) {} + + /// Creates a new RgbResponse with default elements, make sure that bitsPerPixel is <= 8. + /// \throw RangeException When bitsPerPixel is negative or greater than 8. + explicit RgbResponse(Int16 bitsPerPixel) : + Detail::CurveResponse(bitsPerPixel) {} + +}; + +/// Gray response class. +class GrayResponse : public Detail::CurveResponse { + +public: + GrayResponse() noexcept{} + + /// Creates a new GrayResponse with default elements, make sure that info.bitesPerPixel() is <= 8. + /// \throw RangeException When info.bitsPerPixel() is negative or greater than 8. + explicit GrayResponse(const ImageInfo& info) : + Detail::CurveResponse(info) {} + + /// Creates a new GrayResponse with default elements, make sure that bitsPerPixel is <= 8. + /// \throw RangeException When bitsPerPixel is negative or greater than 8. + explicit GrayResponse(Int16 bitsPerPixel) : + Detail::CurveResponse(bitsPerPixel) {} + +}; + +} + +#endif // TWPP_DETAIL_FILE_CURVERESPONSE_HPP + diff --git a/twpp/customdata.hpp b/twpp/customdata.hpp new file mode 100644 index 00000000..cac74aae --- /dev/null +++ b/twpp/customdata.hpp @@ -0,0 +1,71 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_CUSTOMDATA_HPP +#define TWPP_DETAIL_FILE_CUSTOMDATA_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure for sending custom data to source or application. +class CustomData { + +public: + template + using Data = typename Detail::Lock; + + /// Creates empty custom data. + CustomData() noexcept : + m_size(0), m_handle(){} + + /// Creates custom data with allocated memory. + /// \throw std::bad_alloc + explicit CustomData(UInt32 size) : + m_size(size), m_handle(Detail::alloc(size)){} + + /// Locks and returns pointer to custom data memory. + template + Data lock() const noexcept{ + return Data(m_handle); + } + + /// The size of contained memory block. + UInt32 size() const noexcept{ + return m_size; + } + +private: + UInt32 m_size; + Detail::UniqueHandle m_handle; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_CUSTOMDATA_HPP diff --git a/twpp/datasource.hpp b/twpp/datasource.hpp new file mode 100644 index 00000000..f0c436dd --- /dev/null +++ b/twpp/datasource.hpp @@ -0,0 +1,2213 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2018 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_DATASOURCE_HPP +#define TWPP_DETAIL_FILE_DATASOURCE_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +TWPP_DETAIL_PACK_BEGIN +struct AppCapability { + + CapType m_cap; + ConType m_conType; + Handle m_cont; + +}; +TWPP_DETAIL_PACK_END + +struct DoNotFreeHandle { + + DoNotFreeHandle(Handle handle){ + Detail::GlobalMemFuncs::doNotFreeHandle = handle; + } + + ~DoNotFreeHandle(){ + Detail::GlobalMemFuncs::doNotFreeHandle = Handle(); + } + +}; + +} + +#define TWPP_ENTRY(SourceClass)\ + extern "C" TWPP_DETAIL_EXPORT Twpp::ReturnCode TWPP_DETAIL_CALLSTYLE \ + DS_Entry(Twpp::Identity* origin, Twpp::DataGroup dg, Twpp::Dat dat, Twpp::Msg msg, void* data){\ + static_assert(\ + std::is_base_of, SourceClass>::value ||\ + std::is_base_of, SourceClass>::value,\ + "Class " #SourceClass " is not derived from SourceFromThis."\ + );\ + return SourceClass::entry(origin, dg, dat, msg, data);\ + } + +/// Result of a data source operation. +/// Contains both return code and status. +class Result { + +public: + /// Creates successful result. + constexpr Result() noexcept : + m_status(), m_rc(ReturnCode::Success){} + + /// Creates result with supplied return code and status. + constexpr Result(ReturnCode rc, Status status) noexcept : + m_status(status), m_rc(rc){} + + /// Status part of the result. + constexpr Status status() const noexcept{ + return m_status; + } + + /// Return code part of the result. + constexpr ReturnCode returnCode() const noexcept{ + return m_rc; + } + + /// Sets status part of the result. + void setStatus(Status status) noexcept{ + m_status = status; + } + + /// Sets return code part of the result. + void setReturnCode(ReturnCode rc) noexcept{ + m_rc = rc; + } + + constexpr operator ReturnCode() const noexcept{ + return m_rc; + } + + constexpr operator Status() const noexcept{ + return m_status; + } + +private: + Status m_status; + ReturnCode m_rc; + +}; + +static constexpr inline bool success(const Result& res) noexcept{ + return success(res.returnCode()); +} + + +namespace Detail { + +template // false +struct StaticCustomBaseProc { + Result operator()(Dat, Msg, void*){ + return {ReturnCode::Failure, ConditionCode::BadProtocol}; + } +}; + +template +struct StaticCustomBaseProc { + Result operator()(Dat dat, Msg msg, void* data){ + return Derived::staticCustomBase(dat, msg, data); + } +}; + +TWPP_DETAIL_CREATE_HAS_STATIC_METHOD(defaultIdentity) +TWPP_DETAIL_CREATE_HAS_STATIC_METHOD(staticCustomBase) + +} + +namespace SourceFromThisProcs { + +/// Returns data source identity not associated with any instance. +const Identity& defaultIdentity(); + +/// Processes custom TWAIN operations without having any opened connection. +/// DataGroup is always Control. +/// \param dat Type of data. Dat::CustomBase + X. +/// \param msg Message, action to perform. +/// \param data The data, may be null. +/// \return Operation result code. +Result staticCustomBase(Dat dat, Msg msg, void* data); + +} + +/// Base class of a TWAIN data source. +/// It handles instances creation and all static calls. +/// +/// The derived class must: +/// 1) Implement at least all pure virtual methods. +/// 2) Provide `static const Identity& defaultIdentity()`. +/// 3) If hasStaticCustomBaseProc == true, provide +/// `static Result staticCustomBase(Dat dat, Msg msg, void* data)`. +/// +/// After defining your source class, do not forget to use macro +/// TWPP_ENTRY() +/// where the name is a literal, not string: +/// +/// TWPP_ENTRY(Source) // <- no semicolon required +/// \tparam Derived The class inheriting from this. +/// \tparam hasStaticCustomBaseProc {Whether the Derived +/// class handles static custom base operations, see above.} +template +class SourceFromThis { + +public: + SourceFromThis(const SourceFromThis&) = delete; + SourceFromThis& operator=(const SourceFromThis&) = delete; + + SourceFromThis(SourceFromThis&&) = delete; + SourceFromThis& operator=(SourceFromThis&&) = delete; + + virtual ~SourceFromThis() noexcept = default; + +protected: + /// Creates closed instance. + constexpr SourceFromThis() noexcept : + m_lastStatus(ConditionCode::Bummer), m_state(DsState::Closed){} + + /// The last TWAIN status. + Status lastStatus() const noexcept{ + return m_lastStatus; + } + + /// Current TWAIN state. + DsState state() const noexcept{ + return m_state; + } + + /// Whether the source is in the supplied TWAIN state. + bool inState(DsState state) const noexcept{ + return m_state == state; + } + + /// Whether the source is between min and max states (both inclusive). + bool inState(DsState min, DsState max) const noexcept{ + return m_state >= min && m_state <= max; + } + + /// Whether there exists an enabled source. + static bool hasEnabled() noexcept{ + for (auto& src : g_sources){ + if (src.inState(DsState::Enabled, DsState::Xferring)){ + return true; + } + } + + return false; + } + + /// Source identity. + const Identity& sourceIdentity() const noexcept{ + return m_srcId; + } + + /// Identity of the application that opened the source. + const Identity& applicationIdentity() const noexcept{ + return m_appId; + } + + /// Sets current TWAIN state, use with care. + void setState(DsState state) noexcept{ + m_state = state; + } + + /// Sets current source identity, use with care. + void setSourceIdentity(const Identity& sourceIdentity) noexcept{ + m_srcId = sourceIdentity; + } + + /// Sets current application identity, use with care. + void setApplicationIdentity(const Identity& appIdentity) noexcept{ + m_appId = appIdentity; + } + + /// Shortcut for Result(RC::Success, CC::Success). + static constexpr Result success() noexcept{ + return {ReturnCode::Success, ConditionCode::Success}; + } + + /// Shortcut for Result(RC::Failure, CC::BadValue). + static constexpr Result badValue() noexcept{ + return {ReturnCode::Failure, ConditionCode::BadValue}; + } + + /// Shortcut for Result(RC::Failure, CC::BadProtocol). + static constexpr Result badProtocol() noexcept{ + return {ReturnCode::Failure, ConditionCode::BadProtocol}; + } + + /// Shortcut for Result(RC::Failure, CC::SeqError). + static constexpr Result seqError() noexcept{ + return {ReturnCode::Failure, ConditionCode::SeqError}; + } + + /// Shortcut for Result(RC::Failure, CC::CapBadOperation). + static constexpr Result capBadOperation() noexcept{ + return {ReturnCode::Failure, ConditionCode::CapBadOperation}; + } + + /// Shortcut for Result(RC::Failure, CC::CapUnsupported). + static constexpr Result capUnsupported() noexcept{ + return {ReturnCode::Failure, ConditionCode::CapUnsupported}; + } + + /// Shortcut for Result(RC::Failure, CC::Bummber). + static constexpr Result bummer() noexcept{ + return {ReturnCode::Failure, ConditionCode::Bummer}; + } + + + /// Notifies application about clicking on OK button. + ReturnCode notifyCloseOk() noexcept{ + return notifyApp(Msg::CloseDsOk); + } + + /// Notifies application about clicking on Cancel button. + ReturnCode notifyCloseCancel() noexcept{ + return notifyApp(Msg::CloseDsReq); + } + + /// Notifies application about a device event. + ReturnCode notifyDeviceEvent() noexcept{ + return notifyApp(Msg::DeviceEvent); + } + + /// Notifies application about ready transfer (after clicking scan button is GUI is shown). + ReturnCode notifyXferReady() noexcept{ + return notifyApp(Msg::XferReady); + } + + + + /// Root of source TWAIN calls. + /// \param origin Identity of the caller. + /// \param dg Data group of the call. + /// \param dat Type of data. + /// \param msg Message, action to perform. + /// \param data The data, may be null. + virtual Result call(const Identity& origin, DataGroup dg, Dat dat, Msg msg, void* data){ + switch (dg){ + case DataGroup::Control: + return control(origin, dat, msg, data); + + case DataGroup::Image: + return image(origin, dat, msg, data); + + case DataGroup::Audio: + return audio(origin, dat, msg, data); + + default: + return badProtocol(); + + } + } + + /// Root of source control TWAIN calls. + /// \param origin Identity of the caller. + /// \param dat Type of data. + /// \param msg Message, action to perform. + /// \param data The data, may be null. + virtual Result control(const Identity& origin, Dat dat, Msg msg, void* data){ + if (!data){ + // all control triplets require data + return badValue(); + } + + switch (dat){ + case Dat::Capability: + return capability(origin, msg, *static_cast(data)); + case Dat::CustomData: + return customData(origin, msg, *static_cast(data)); + case Dat::DeviceEvent: + return deviceEvent(origin, msg, *static_cast(data)); + case Dat::Event: // Windows only + return event(origin, msg, *static_cast(data)); + case Dat::FileSystem: + return fileSystem(origin, msg, *static_cast(data)); + case Dat::Identity: + return identity(origin, msg, *static_cast(data)); + case Dat::PassThrough: + return passThrough(origin, msg, *static_cast(data)); + case Dat::PendingXfers: + return pendingXfers(origin, msg, *static_cast(data)); + case Dat::SetupFileXfer: + return setupFileXfer(origin, msg, *static_cast(data)); + case Dat::SetupMemXfer: + return setupMemXfer(origin, msg, *static_cast(data)); + case Dat::Status: + return status(origin, msg, *static_cast(data)); + case Dat::StatusUtf8: + return statusUtf8(origin, msg, *static_cast(data)); + case Dat::UserInterface: + return userInterface(origin, msg, *static_cast(data)); + case Dat::XferGroup: { + return xferGroup(origin, msg, *static_cast(data)); + } + default: + return badProtocol(); + } + } + + /// Capability TWAIN call. + /// Reset, set and set constraint operations are limited to + /// state DsState::Open (4), override this method if you + /// support CapType::ExtendedCaps. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Capability data. + virtual Result capability(const Identity& origin, Msg msg, Capability& data){ + switch (msg){ + case Msg::Get: + // 4 - 7 + return capabilityGet(origin, data); + + case Msg::GetCurrent: + // 4 - 7 + return capabilityGetCurrent(origin, data); + + case Msg::GetDefault: + // 4 - 7 + return capabilityGetDefault(origin, data); + + case Msg::GetHelp: + if (!inState(DsState::Open)){ + return seqError(); + } + + return capabilityGetHelp(origin, data); + + case Msg::GetLabel: + if (!inState(DsState::Open)){ + return seqError(); + } + + return capabilityGetLabel(origin, data); + + case Msg::GetLabelEnum: + if (!inState(DsState::Open)){ + return seqError(); + } + + return capabilityGetLabelEnum(origin, data); + + case Msg::QuerySupport: + // 4 - 7 + return capabilityQuerySupport(origin, data); + + case Msg::Reset: + // 4, extended: 5, 6, 7 + if (!inState(DsState::Open)){ + return seqError(); + } + + return capabilityReset(origin, data); + + case Msg::ResetAll: + if (!inState(DsState::Open)){ + return seqError(); + } + + return capabilityResetAll(origin); // data has no meaning here + + case Msg::Set: + // 4, extended: 5, 6, 7 + if (!inState(DsState::Open)){ + return seqError(); + } + + if (!data){ + return badValue(); + } + + return capabilitySet(origin, data); + + case Msg::SetConstraint: + // 4, extended: 5, 6, 7 + if (!inState(DsState::Open)){ + return seqError(); + } + + if (!data){ + return badValue(); + } + + return capabilitySetConstraint(origin, data); + + default: + return badProtocol(); + } + } + + /// Get capability TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGet(const Identity& origin, Capability& data) = 0; + + /// Get current capability TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGetCurrent(const Identity& origin, Capability& data) = 0; + + /// Get default capability TWAIN call. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGetDefault(const Identity& origin, Capability& data) = 0; + + /// Get help capability TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGetHelp(const Identity& origin, Capability& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get label capability TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGetLabel(const Identity& origin, Capability& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get label enum capability TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityGetLabelEnum(const Identity& origin, Capability& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Query support capability TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityQuerySupport(const Identity& origin, Capability& data) = 0; + + /// Reset capability TWAIN call. + /// Always called in correct state: 4, if you support extended + /// capabilities, override `capability` method. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilityReset(const Identity& origin, Capability& data) = 0; + + /// Reset all capability TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + virtual Result capabilityResetAll(const Identity& origin) = 0; + + /// Set capability TWAIN call. + /// Always called in correct state: 4, if you support extended + /// capabilities, override `capability` method. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilitySet(const Identity& origin, Capability& data) = 0; + + /// Set capability TWAIN call. + /// Always called in correct state: 4, if you support extended + /// capabilities, override `capability` method. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Capability data. + virtual Result capabilitySetConstraint(const Identity& origin, Capability& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + + + /// Custom data TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Custom data. + virtual Result customData(const Identity& origin, Msg msg, CustomData& data){ + if (!inState(DsState::Open)){ + return seqError(); + } + + switch (msg){ + case Msg::Get: + return customDataGet(origin, data); + + case Msg::Set: + return customDataSet(origin, data); + + default: + return badProtocol(); + } + } + + /// Get custom data TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Custom data. + virtual Result customDataGet(const Identity& origin, CustomData& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Set custom data TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Custom data. + virtual Result customDataSet(const Identity& origin, CustomData& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Device event TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Device event data. + virtual Result deviceEvent(const Identity& origin, Msg msg, DeviceEvent& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + return deviceEventGet(origin, data); + } + + /// Get device event TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Device event data. + virtual Result deviceEventGet(const Identity& origin, DeviceEvent& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + + + /// Event TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Event data. + virtual Result event(const Identity& origin, Msg msg, Event& data){ + if (msg != Msg::ProcessEvent){ + return badProtocol(); + } + + if (!inState(DsState::Enabled, DsState::Xferring)){ + return seqError(); + } + + return eventProcess(origin, data); + } + +#if defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_MAC) + /// Process event TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Event data. + virtual Result eventProcess(const Identity& origin, Event& data) = 0; +#elif defined(TWPP_DETAIL_OS_LINUX) + /// Process event TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Event data. + virtual Result eventProcess(const Identity& origin, Event& data){ + Detail::unused(origin, data); + return badProtocol(); + } +#else +# error "eventProcess for your platform here" +#endif + + /// Identity TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Identity data. + virtual Result identity(const Identity& origin, Msg msg, Identity& data){ + Result rc; + switch (msg){ + case Msg::Get: + // any state + data = sourceIdentity(); + return success(); + + case Msg::OpenDs: { + if (!inState(DsState::Closed)){ + return seqError(); + } + + setSourceIdentity(data); + setApplicationIdentity(origin); + rc = identityOpenDs(origin); + if (Twpp::success(rc)){ + setState(DsState::Open); + } + + return rc; + } + + case Msg::CloseDs: { + if (!inState(DsState::Open)){ + return seqError(); + } + + rc = identityCloseDs(origin); + if (Twpp::success(rc)){ + setState(DsState::Closed); + } + + return rc; + } + + default: + return badProtocol(); + } + } + + /// Open source identity TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + virtual Result identityOpenDs(const Identity& origin) = 0; + + /// Close source identity TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + virtual Result identityCloseDs(const Identity& origin) = 0; + + /// File system TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data File system data. + virtual Result fileSystem(const Identity& origin, Msg msg, FileSystem& data){ + switch (msg){ + case Msg::AutomaticCaptureDir: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemAutomatic(origin, data); + + case Msg::ChangeDir: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemChange(origin, data); + + case Msg::Copy: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemCopy(origin, data); + + case Msg::CreateDir: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemCreate(origin, data); + + case Msg::Delete: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemDelete(origin, data); + + case Msg::FormatMedia: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemFormat(origin, data); + + case Msg::GetClose: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return fileSystemGetClose(origin, data); + + case Msg::GetFirstFile: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return fileSystemGetFirst(origin, data); + + case Msg::GetInfo: + // 4 - 7 + return fileSystemGetInfo(origin, data); + + case Msg::GetNextFile: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return fileSystemGetNext(origin, data); + + case Msg::Rename: + if (!inState(DsState::Open)){ + return seqError(); + } + + return fileSystemRename(origin, data); + + default: + return badProtocol(); + } + } + + /// Automatic capture directory file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemAutomatic(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Change directory file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemChange(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + + /// Copy file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemCopy(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Create directory file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemCreate(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Delete file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemDelete(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Format media file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemFormat(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get close file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemGetClose(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get first file file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemGetFirst(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get info file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemGetInfo(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get next file file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemGetNext(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Rename file system TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data File system data. + virtual Result fileSystemRename(const Identity& origin, FileSystem& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + + /// Pass through TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Pass through data. + virtual Result passThrough(const Identity& origin, Msg msg, PassThrough& data){ + if (msg != Msg::PassThrough){ + return badProtocol(); + } + + // 4 - 7 + return passThroughPass(origin, data); + } + + /// Pass through pass through TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Pass through data. + virtual Result passThroughPass(const Identity& origin, PassThrough& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Pending xfers TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Pending xfers data. + virtual Result pendingXfers(const Identity& origin, Msg msg, PendingXfers& data){ + switch (msg){ + case Msg::EndXfer: { + if (!inState(DsState::XferReady, DsState::Xferring)){ + return seqError(); + } + + auto rc = pendingXfersEnd(origin, data); + if (Twpp::success(rc)){ + DataGroup xferGroup = DataGroup::Image; + if (!Twpp::success(this->xferGroup(origin, Msg::Get, xferGroup))){ + xferGroup = DataGroup::Image; + } + + if (xferGroup == DataGroup::Audio){ + setState(DsState::XferReady); + } else { + setState(data.count() ? DsState::XferReady : DsState::Enabled); + } + } + + return rc; + } + + + case Msg::Reset: { + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = pendingXfersReset(origin, data); + if (Twpp::success(rc)){ + DataGroup xferGroup = DataGroup::Image; + if (!Twpp::success(this->xferGroup(origin, Msg::Get, xferGroup))){ + xferGroup = DataGroup::Image; + } + + if (xferGroup != DataGroup::Audio){ + setState(DsState::Enabled); + } + } + + return rc; + } + + case Msg::StopFeeder: + if (!inState(DsState::XferReady)){ + return seqError(); + } + + return pendingXfersStopFeeder(origin, data); + + case Msg::Get: + if (!inState(DsState::Open, DsState::Xferring)){ + return seqError(); + } + + return pendingXfersGet(origin, data); + + default: + return badProtocol(); + } + } + + /// Get pending xfers TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Pending xfers data. + virtual Result pendingXfersGet(const Identity& origin, PendingXfers& data) = 0; + + /// End xfer pending xfers TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Pending xfers data. + virtual Result pendingXfersEnd(const Identity& origin, PendingXfers& data) = 0; + + /// Reset xfers pending xfers TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Pending xfers data. + virtual Result pendingXfersReset(const Identity& origin, PendingXfers& data) = 0; + + /// Stop feeder pending xfers TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Pending xfers data. + virtual Result pendingXfersStopFeeder(const Identity& origin, PendingXfers& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Setup file xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Setup file xfer data. + virtual Result setupFileXfer(const Identity& origin, Msg msg, SetupFileXfer& data){ + switch (msg){ + case Msg::Get: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return setupFileXferGet(origin, data); + + case Msg::GetDefault: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return setupFileXferGetDefault(origin, data); + + case Msg::Set: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return setupFileXferSet(origin, data); + + case Msg::Reset: + if (!inState(DsState::Open)){ + return seqError(); + } + + return setupFileXferReset(origin, data); + + default: + return badProtocol(); + } + } + + /// Get setup file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Setup file xfer data. + virtual Result setupFileXferGet(const Identity& origin, SetupFileXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get default setup file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Setup file xfer data. + virtual Result setupFileXferGetDefault(const Identity& origin, SetupFileXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Set setup file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Setup file xfer data. + virtual Result setupFileXferSet(const Identity& origin, SetupFileXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Reset setup file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Setup file xfer data. + virtual Result setupFileXferReset(const Identity& origin, SetupFileXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Setup memory xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Setup memory xfer data. + virtual Result setupMemXfer(const Identity& origin, Msg msg, SetupMemXfer& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return setupMemXferGet(origin, data); + } + + /// Get setup memory xfer TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Setup memory xfer data. + virtual Result setupMemXferGet(const Identity& origin, SetupMemXfer& data) = 0; + + /// Status TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Status data. + virtual Result status(const Identity& origin, Msg msg, Status& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + return statusGet(origin, data); + } + + /// Get status TWAIN call. + /// Always called in correct state. + /// Default implementation returns last status. + /// \param origin Identity of the caller. + /// \param data Status data. + virtual Result statusGet(const Identity& origin, Status& data){ + Detail::unused(origin); + data = lastStatus(); + return success(); + } + + /// Status utf8 TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Status utf8 data. + virtual Result statusUtf8(const Identity& origin, Msg msg, StatusUtf8& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + // 3 - 7 + return statusUtf8Get(origin, data); + } + + /// Get status utf8 TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Status utf8 data. + virtual Result statusUtf8Get(const Identity& origin, StatusUtf8& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// User interface TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data User interface data. + virtual Result userInterface(const Identity& origin, Msg msg, UserInterface& data){ + Result rc; + switch (msg){ + case Msg::DisableDs: + if (!inState(DsState::Enabled)){ + return seqError(); + } + + rc = userInterfaceDisable(origin, data); + if (Twpp::success(rc)){ + setState(DsState::Open); + } + + return rc; + + case Msg::EnableDs: + if (!inState(DsState::Open) || hasEnabled()){ // only a single source can be enabled at any given time + return seqError(); + } + + rc = userInterfaceEnable(origin, data); + if (Twpp::success(rc) || rc == ReturnCode::CheckStatus){ + if (inState(DsState::Open)){ // allow userInterfaceEnable to transfer to higher states + setState(DsState::Enabled); + } + } + + return rc; + + case Msg::EnableDsUiOnly: + if (!inState(DsState::Open)){ + return seqError(); + } + + rc = userInterfaceEnableUiOnly(origin, data); + if (Twpp::success(rc)){ + setState(DsState::Enabled); + } + + return rc; + + default: + return badProtocol(); + } + } + + /// Disable user interface TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data User interface data. + virtual Result userInterfaceDisable(const Identity& origin, UserInterface& data) = 0; + + /// Enable user interface TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data User interface data. + virtual Result userInterfaceEnable(const Identity& origin, UserInterface& data) = 0; + + /// Enable UI only user interface TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data User interface data. + virtual Result userInterfaceEnableUiOnly(const Identity& origin, UserInterface& data) = 0; + + /// Xfer group TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Xfer group data. + virtual Result xferGroup(const Identity& origin, Msg msg, DataGroup& data){ + switch (msg){ + case Msg::Get: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return xferGroupGet(origin, data); + + case Msg::Set: + if (!inState(DsState::XferReady)){ + return seqError(); + } + + return xferGroupSet(origin, data); + + default: + return badProtocol(); + } + } + + /// Get xfer group TWAIN call. + /// Always called in correct state. + /// Default implementation returns DataGroup::Image. + /// \param origin Identity of the caller. + /// \param data Xfer group data. + virtual Result xferGroupGet(const Identity& origin, DataGroup& data){ + Detail::unused(origin); + data = DataGroup::Image; + return success(); + } + + /// Set xfer group TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Xfer group data. + virtual Result xferGroupSet(const Identity& origin, DataGroup& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Root of source image TWAIN calls. + /// + /// Special data to type casts: + /// ExtImageInfo: reinterpret_cast(data) + /// GrayResponse: reinterpret_cast(data) + /// RgbResponse: reinterpret_cast(data) + /// + /// \param origin Identity of the caller. + /// \param dat Type of data. + /// \param msg Message, action to perform. + /// \param data The data, may be null. + virtual Result image(const Identity& origin, Dat dat, Msg msg, void* data){ + if (dat != Dat::ImageFileXfer && !data){ + return badValue(); + } + + switch (dat){ + // TODO CieColor + /*case Dat::CieColor: + return cieColor(origin, msg, *static_cast(data));*/ + case Dat::ExtImageInfo: + return extImageInfo(origin, msg, reinterpret_cast(data)); // ExtImageInfo is simply a `pointer to TW_EXTIMAGEINFO` + case Dat::GrayResponse: + return grayResponse(origin, msg, reinterpret_cast(data)); // GrayResponse is simply a `pointer to TW_GRAYRESPONSE` + case Dat::IccProfile: + return iccProfile(origin, msg, *static_cast(data)); + case Dat::ImageFileXfer: + return imageFileXfer(origin, msg); + case Dat::ImageInfo: + return imageInfo(origin, msg, *static_cast(data)); + case Dat::ImageLayout: + return imageLayout(origin, msg, *static_cast(data)); + case Dat::ImageMemFileXfer: + return imageMemFileXfer(origin, msg, *static_cast(data)); + case Dat::ImageMemXfer: + return imageMemXfer(origin, msg, *static_cast(data)); + case Dat::ImageNativeXfer: + return imageNativeXfer(origin, msg, *static_cast(data)); + case Dat::JpegCompression: + return jpegCompression(origin, msg, *static_cast(data)); + case Dat::Palette8: + return palette8(origin, msg, *static_cast(data)); + case Dat::RgbResponse: + return rgbResponse(origin, msg, reinterpret_cast(data)); // RgbResponse is simply a `pointer to TW_RGBRESPONSE` + default: + return badProtocol(); + } + } + + // TODO CieColor + /* + /// Cie color TWAIN call. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Cie color data. + virtual Result cieColor(const Identity& origin, Msg msg, CieColor& data){ + Detail::unused(origin, msg, data); + return badProtocol(); + }*/ + + /// Ext image info TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Ext image info data. + virtual Result extImageInfo(const Identity& origin, Msg msg, ExtImageInfo& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::Xferring)){ + return seqError(); + } + + return extImageInfoGet(origin, data); + } + + /// Get ext image info TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Ext image info data. + virtual Result extImageInfoGet(const Identity& origin, ExtImageInfo& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Gray response TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Gray response data. + virtual Result grayResponse(const Identity& origin, Msg msg, GrayResponse& data){ + if (!inState(DsState::Open)){ + return seqError(); + } + + switch (msg){ + case Msg::Set: + return grayResponseSet(origin, data); + + case Msg::Reset: + return grayResponseReset(origin, data); + + default: + return badProtocol(); + } + } + + /// Set gray response TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Gray response data. + virtual Result grayResponseSet(const Identity& origin, GrayResponse& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Reset gray response TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Gray response data. + virtual Result grayResponseReset(const Identity& origin, GrayResponse& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// ICC profile TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data ICC profile data. + virtual Result iccProfile(const Identity& origin, Msg msg, IccProfileMemory& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady, DsState::Xferring)){ + return seqError(); + } + + return iccProfileGet(origin, data); + } + + /// Get ICC profile TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data ICC profile data. + virtual Result iccProfileGet(const Identity& origin, IccProfileMemory& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Image file xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + virtual Result imageFileXfer(const Identity& origin, Msg msg){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = imageFileXferGet(origin); + if (rc == ReturnCode::XferDone){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get image file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// Always called in correct state. + /// \param origin Identity of the caller. + virtual Result imageFileXferGet(const Identity& origin){ + Detail::unused(origin); + return badProtocol(); + } + + /// Image info TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Image info data. + virtual Result imageInfo(const Identity& origin, Msg msg, ImageInfo& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady, DsState::Xferring)){ + return seqError(); + } + + return imageInfoGet(origin, data); + } + + /// Get image info TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image info data. + virtual Result imageInfoGet(const Identity& origin, ImageInfo& data) = 0; + + + /// Image layout TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Image layout data. + virtual Result imageLayout(const Identity& origin, Msg msg, ImageLayout& data){ + switch (msg){ + case Msg::Get: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return imageLayoutGet(origin, data); + + case Msg::GetDefault: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return imageLayoutGetDefault(origin, data); + + case Msg::Set: + if (!inState(DsState::Open)){ + return seqError(); + } + + return imageLayoutSet(origin, data); + + case Msg::Reset: + if (!inState(DsState::Open)){ + return seqError(); + } + + return imageLayoutReset(origin, data); + + default: + return badProtocol(); + } + } + + /// Get image layout TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image layout data. + virtual Result imageLayoutGet(const Identity& origin, ImageLayout& data) = 0; + + /// Get default image layout TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image layout data. + virtual Result imageLayoutGetDefault(const Identity& origin, ImageLayout& data) = 0; + + /// Set image layout TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image layout data. + virtual Result imageLayoutSet(const Identity& origin, ImageLayout& data) = 0; + + /// Reset image layout TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image layout data. + virtual Result imageLayoutReset(const Identity& origin, ImageLayout& data) = 0; + + + /// Image memory file xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Image memory file xfer data. + virtual Result imageMemFileXfer(const Identity& origin, Msg msg, ImageMemFileXfer& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = imageMemFileXferGet(origin, data); + if (rc == ReturnCode::XferDone){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get image memory file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Image memory file xfer data. + virtual Result imageMemFileXferGet(const Identity& origin, ImageMemFileXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Image memory xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Image memory xfer data. + virtual Result imageMemXfer(const Identity& origin, Msg msg, ImageMemXfer& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady, DsState::Xferring)){ + return seqError(); + } + + auto rc = imageMemXferGet(origin, data); + if (Twpp::success(rc) || rc == ReturnCode::XferDone){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get image memory xfer TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Image memory xfer data. + virtual Result imageMemXferGet(const Identity& origin, ImageMemXfer& data) = 0; + + /// Image native xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Handle to image native xfer data. + virtual Result imageNativeXfer(const Identity& origin, Msg msg, ImageNativeXfer& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = imageNativeXferGet(origin, data); + if (rc == ReturnCode::XferDone){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get image native xfer TWAIN call. + /// Always called in correct state. + /// \param origin Identity of the caller. + /// \param data Handle to image native xfer data. + virtual Result imageNativeXferGet(const Identity& origin, ImageNativeXfer& data) = 0; + + /// JPEG compression TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data JPEG compression data. + virtual Result jpegCompression(const Identity& origin, Msg msg, JpegCompression& data){ + switch (msg){ + case Msg::Get: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return jpegCompressionGet(origin, data); + + case Msg::GetDefault: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return jpegCompressionGetDefault(origin, data); + + case Msg::Set: + if (!inState(DsState::Open)){ + return seqError(); + } + + return jpegCompressionSet(origin, data); + + case Msg::Reset: + if (!inState(DsState::Open)){ + return seqError(); + } + + return jpegCompressionReset(origin, data); + + default: + return badProtocol(); + } + } + + /// Get JPEG compression TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data JPEG compression data. + virtual Result jpegCompressionGet(const Identity& origin, JpegCompression& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get default JPEG compression TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data JPEG compression data. + virtual Result jpegCompressionGetDefault(const Identity& origin, JpegCompression& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Set JPEG compression TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data JPEG compression data. + virtual Result jpegCompressionSet(const Identity& origin, JpegCompression& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Reset JPEG compression TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data JPEG compression data. + virtual Result jpegCompressionReset(const Identity& origin, JpegCompression& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Palette8 TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Palette8 data. + virtual Result palette8(const Identity& origin, Msg msg, Palette8& data){ + switch (msg){ + case Msg::Get: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return palette8Get(origin, data); + + case Msg::GetDefault: + if (!inState(DsState::Open, DsState::XferReady)){ + return seqError(); + } + + return palette8GetDefault(origin, data); + + case Msg::Set: + if (!inState(DsState::Open)){ + return seqError(); + } + + return palette8Set(origin, data); + + case Msg::Reset: + if (!inState(DsState::Open)){ + return seqError(); + } + + return palette8Reset(origin, data); + + default: + return badProtocol(); + } + } + + /// Get Palette8 TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Palette8 data. + virtual Result palette8Get(const Identity& origin, Palette8& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Get default Palette8 TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Palette8 data. + virtual Result palette8GetDefault(const Identity& origin, Palette8& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Set Palette8 TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Palette8 data. + virtual Result palette8Set(const Identity& origin, Palette8& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Reset Palette8 TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Palette8 data. + virtual Result palette8Reset(const Identity& origin, Palette8& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// RGB response TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data RGB response data. + virtual Result rgbResponse(const Identity& origin, Msg msg, RgbResponse& data){ + if (!inState(DsState::Open)){ + return seqError(); + } + + switch (msg){ + case Msg::Set: + return rgbResponseSet(origin, data); + + case Msg::Reset: + return rgbResponseReset(origin, data); + + default: + return badProtocol(); + } + } + + /// Set RGB response TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data RGB response data. + virtual Result rgbResponseSet(const Identity& origin, RgbResponse& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Reset RGB response TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data RGB response data. + virtual Result rgbResponseReset(const Identity& origin, RgbResponse& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + + /// Root of source audio TWAIN calls. + /// \param origin Identity of the caller. + /// \param dat Type of data. + /// \param msg Message, action to perform. + /// \param data The data, may be null. + virtual Result audio(const Identity& origin, Dat dat, Msg msg, void* data){ + if (dat != Dat::AudioFileXfer && !data){ + return badValue(); + } + + switch (dat){ + case Dat::AudioFileXfer: + return audioFileXfer(origin, msg); + case Dat::AudioInfo: + return audioInfo(origin, msg, *static_cast(data)); + case Dat::AudioNativeXfer: + return audioNativeXfer(origin, msg, *static_cast(data)); + default: + return badProtocol(); + } + } + + /// Audio file xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + virtual Result audioFileXfer(const Identity& origin, Msg msg){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = audioFileXferGet(origin); + if (rc == ReturnCode::XferDone){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get audio file xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + virtual Result audioFileXferGet(const Identity& origin){ + Detail::unused(origin); + return badProtocol(); + } + + /// Audio info TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Audio info data. + virtual Result audioInfo(const Identity& origin, Msg msg, AudioInfo& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady, DsState::Xferring)){ + return seqError(); + } + + return audioInfoGet(origin, data); + } + + /// Get audio info TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Audio info data. + virtual Result audioInfoGet(const Identity& origin, AudioInfo& data){ + Detail::unused(origin, data); + return badProtocol(); + } + + /// Audio native xfer TWAIN call. + /// \param origin Identity of the caller. + /// \param msg Message, action to perform. + /// \param data Handle to audio native xfer data. + virtual Result audioNativeXfer(const Identity& origin, Msg msg, AudioNativeXfer& data){ + if (msg != Msg::Get){ + return badProtocol(); + } + + if (!inState(DsState::XferReady)){ + return seqError(); + } + + auto rc = audioNativeXferGet(origin, data); + if (Twpp::success(rc)){ + setState(DsState::Xferring); + } + + return rc; + } + + /// Get audio native xfer TWAIN call. + /// Always called in correct state. + /// Default implementation does nothing. + /// \param origin Identity of the caller. + /// \param data Handle to audio native xfer data. + virtual Result audioNativeXferGet(const Identity& origin, AudioNativeXfer& data){ + Detail::unused(origin, data); + return badProtocol(); + } + +private: + ReturnCode notifyApp(Msg msg) noexcept{ + switch (msg){ + case Msg::XferReady: + if (!inState(DsState::Enabled)){ + return ReturnCode::Failure; + } + + break; + case Msg::CloseDsOk: + case Msg::CloseDsReq: + if (!inState(DsState::Enabled, DsState::Xferring)){ + return ReturnCode::Failure; + } + + break; + default: + break; + } + + auto rc = g_entry(&m_srcId, &m_appId, DataGroup::Control, Dat::Null, msg, nullptr); + if (Twpp::success(rc)){ + switch (msg){ + case Msg::XferReady: + setState(DsState::XferReady); + break; + case Msg::CloseDsOk: + case Msg::CloseDsReq: + setState(DsState::Enabled); + break; + default: + break; + } + } + + return rc; + } + + Result callRoot(Identity* origin, DataGroup dg, Dat dat, Msg msg, void* data) noexcept{ + if (!origin){ + return badProtocol(); + } + + bool isCapability = dg == DataGroup::Control && dat == Dat::Capability && data != nullptr; + try { + return isCapability + ? callCapability(*origin, dg, dat, msg, data) + : call(*origin, dg, dat, msg, data); + } catch (const std::bad_alloc&){ + return {ReturnCode::Failure, ConditionCode::LowMemory}; + } catch (...){ + // the exception would be caught in the static handler below + // that would set static status, we want to set local one + return bummer(); + } + } + + Result callCapability(const Identity& origin, DataGroup dg, Dat dat, Msg msg, void* data){ + // it is the responsibility of the APP to free capability handle + // we must assume the APP does not set the handle to zero after freeing it + // that would break capability (handle) move-assignment operator + // make sure such handle is not freed + Detail::AppCapability& cap = *static_cast(data); + Detail::DoNotFreeHandle doNotFree(cap.m_cont); + Detail::unused(doNotFree); + + return call(origin, dg, dat, msg, data); + } + + + Identity m_srcId; + Identity m_appId; + Status m_lastStatus; + DsState m_state; + + + static typename std::list::iterator find(Identity* origin) noexcept{ + if (origin){ + for (auto it = g_sources.begin(); it != g_sources.end(); ++it){ + if (it->m_appId.id() == origin->id()){ + return it; + } + } + } + + return g_sources.end(); + } + + static void resetDsm(){ + g_entry = nullptr; + +#if defined(TWPP_DETAIL_OS_WIN32) + g_dsm.unload(); +#endif + } + + static Result staticCall(typename std::list::iterator src, Identity* origin, + DataGroup dg, Dat dat, Msg msg, void* data){ + +#if defined(TWPP_DETAIL_OS_WIN32) + if (!g_entry){ + if (!g_dsm && !g_dsm.load(true)){ + return bummer(); + } + + g_entry = g_dsm.resolve(); + } +#endif + + if (!g_entry){ + return bummer(); + } + + auto rc = src->callRoot(origin, dg, dat, msg, data); + src->m_lastStatus = rc.status(); + + if (dg == DataGroup::Control && dat == Dat::Identity && ( + (msg == Msg::CloseDs && Twpp::success(rc)) || + (msg == Msg::OpenDs && !Twpp::success(rc)) + ) + ){ + g_sources.erase(src); + if (g_sources.empty()){ + resetDsm(); + } + } + + return rc; + } + + static Result staticControl(Identity* origin, DataGroup dg, Dat dat, Msg msg, void* data){ + if (dg != DataGroup::Control){ + return seqError(); + } + + switch (dat){ + case Dat::EntryPoint: + if (msg == Msg::Set){ + if (!data){ + return badValue(); + } + + auto& e = *static_cast(data); + g_entry = e.m_entry; + Detail::setMemFuncs(e.m_alloc, e.m_free, e.m_lock, e.m_unlock); + return success(); + } + + break; + + case Dat::Status: { + if (msg == Msg::Get){ + if (!data){ + return badValue(); + } + + *static_cast(data) = g_lastStatus; + return success(); + } + + break; + } + + case Dat::Identity: { + switch (msg){ + case Msg::Get: { + if (!data){ + return badValue(); + } + + static_assert(Detail::HasStaticMethod_defaultIdentity::value, + "Your source class lacks `static const Identity& defaultIdentity()` method."); + + auto& ident = *static_cast(data); + const Identity& def = Derived::defaultIdentity(); + ident = Identity(ident.id(), def.version(), def.protocolMajor(), + def.protocolMinor(), def.dataGroupsRaw(), def.manufacturer(), + def.productFamily(), def.productName()); + + return success(); + } + + case Msg::OpenDs: { + g_sources.emplace_back(); + return staticCall(--g_sources.end(), origin, dg, dat, msg, data); + } + + case Msg::CloseDs: + // not open yet + return success(); + + default: + break; + } + + break; + } + + default: + if (dat >= Dat::CustomBase){ + static_assert(Detail::HasStaticMethod_staticCustomBase::value || + !hasStaticCustomBaseProc, + "Your source class lacks `static Result staticCustomBase(Dat, Msg, void*)` method."); + + return Detail::StaticCustomBaseProc()(dat, msg, data); + } + + break; + } + + return badProtocol(); + } + +public: + /// TWAIN entry, do not call from data source. + static ReturnCode entry(Identity* origin, DataGroup dg, Dat dat, Msg msg, void* data) noexcept{ + auto src = find(origin); + try { + auto rc = src == g_sources.end() ? + staticControl(origin, dg, dat, msg, data) : + staticCall(src, origin, dg, dat, msg, data); + + g_lastStatus = rc.status(); + return rc.returnCode(); + } catch (const std::bad_alloc&) { + g_lastStatus = ConditionCode::LowMemory; + return ReturnCode::Failure; + } catch (...){ + // we can't throw exceptions out of data sources + // the C interface can't really handle them + // especially when there are different implementations + g_lastStatus = ConditionCode::Bummer; + return ReturnCode::Failure; + } + } + +private: + static std::list g_sources; + static Detail::DsmEntry g_entry; + static Status g_lastStatus; + +#if defined(TWPP_DETAIL_OS_WIN32) + static Detail::DsmLib g_dsm; // only old windows dsm requires this +#endif + +}; + +template +std::list SourceFromThis::g_sources; + +template +Detail::DsmEntry SourceFromThis::g_entry; + +template +Status SourceFromThis::g_lastStatus = ConditionCode::Bummer; + +#if defined(TWPP_DETAIL_OS_WIN32) +template +Detail::DsmLib SourceFromThis::g_dsm; +#endif + +} + +#endif // TWPP_DETAIL_FILE_DATASOURCE_HPP + diff --git a/twpp/deviceevent.hpp b/twpp/deviceevent.hpp new file mode 100644 index 00000000..cdf530a5 --- /dev/null +++ b/twpp/deviceevent.hpp @@ -0,0 +1,251 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_DEVICEEVENT_HPP +#define TWPP_DETAIL_FILE_DEVICEEVENT_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Information about event sent by source. +class DeviceEvent { + +public: + /// Event type. + enum class Type : UInt16 { // Capability->UInt16, DeviceEvent->UInt32 + CheckAutomaticCapture = 0, + CheckBattery = 1, + CheckDeviceOnline = 2, + CheckFlash = 3, + CheckPowerSupply = 4, + CheckResolution = 5, + DeviceAdded = 6, + DeviceOffline = 7, + DeviceReady = 8, + DeviceRemoved = 9, + ImageCaptured = 10, + ImageDeleted = 11, + PaperDoubleFeed = 12, + PaperJam = 13, + LampFailure = 14, + PowerSave = 15, + PowerSaveNotify = 16, + CustomEvents = 0x8000 + }; + + /// Creates event with only type and device name set. + static constexpr DeviceEvent simple(Type type, const Str255& deviceName) noexcept; + + /// Creates event for checking battery. + static constexpr DeviceEvent checkBattery( + const Str255& deviceName, + UInt32 batteryMinutes, + Int16 batteryPercentage + ) noexcept; + + /// Creates event for checking power supply. + static constexpr DeviceEvent checkPowerSupply( + const Str255& deviceName, + PowerSupply powerSupply + ) noexcept; + + /// Creates event for checking resolution. + static constexpr DeviceEvent checkResolution( + const Str255& deviceName, + Fix32 xres, + Fix32 yres + ) noexcept; + + /// Creates event for checking flash settings. + static constexpr DeviceEvent checkFlash( + const Str255& deviceName, + Flash flash + ) noexcept; + + /// Creates event for checking number of images camera is going to capture. + static constexpr DeviceEvent checkAutomaticCapture( + const Str255& deviceName, + UInt32 autoCapture, + UInt32 timeBeforeFirstCapture, + UInt32 timeBetweenCaptures + ) noexcept; + + /// Creates uninitialized deice event. + constexpr DeviceEvent() noexcept : + m_type(static_cast(Type::CheckAutomaticCapture)), m_batteryMinutes(0), + m_batteryPercent(0), m_powerSupply(static_cast(PowerSupply::External)), + m_flashUsed(static_cast(Flash::None)), m_autoCapture(0), + m_timeBeforeFirstCapture(0), m_timeBetweenCaptures(0){} + + /// Event type. + constexpr Type type() const noexcept{ + return static_cast(m_type); + } + + /// Name of the device that sent the event. + constexpr const Str255& deviceName() const noexcept{ + return m_deviceName; + } + + /// Minutes of battery power remaining. + /// Valid only for Type::CheckBattery. + constexpr UInt32 batteryMinutes() const noexcept{ + return m_batteryMinutes; + } + + /// Percentage of battery power remaining. + /// Valid only for Type::CheckBattery. + constexpr Int16 batteryPercentage() const noexcept{ + return m_batteryPercent; + } + + /// Power supply in use. + /// Valid only for Type::CheckPowerSupply. + constexpr PowerSupply powerSupply() const noexcept{ + return static_cast(m_powerSupply); + } + + /// X resolution. + /// Valif only for Type::CheckResolution. + constexpr Fix32 xResolution() const noexcept{ + return m_xres; + } + + /// Y resolution. + /// Valid only for Type::CheckResolution. + constexpr Fix32 yResolution() const noexcept{ + return m_yres; + } + + /// Flash settings. + /// Valid only for Type::CheckFlash. + constexpr Flash flash() const noexcept{ + return static_cast(m_flashUsed); + } + + /// Number of images camera will capture. + /// Valid only for Type::CheckAutomaticCapture. + constexpr UInt32 automaticCapture() const noexcept{ + return m_autoCapture; + } + + /// Number of seconds before first capture. + /// Valid only for Type::CheckAutomaticCapture. + constexpr UInt32 timeBeforeFirstCapture() const noexcept{ + return m_timeBeforeFirstCapture; + } + + /// Number of 1/100-seconds between captures. + /// Valid only for Type::CheckAutomaticCapture. + constexpr UInt32 timeBetweenCaptures() const noexcept{ + return m_timeBetweenCaptures; + } + +private: + constexpr DeviceEvent( + Type type, + const Str255& deviceName, + UInt32 batteryMinutes, + Int16 batteryPercentage, + PowerSupply powerSupply, + Fix32 xres, + Fix32 yres, + Flash flash, + UInt32 autoCapture, + UInt32 tbfc, + UInt32 tbc + ) noexcept : + m_type(static_cast(type)), m_deviceName(deviceName), + m_batteryMinutes(batteryMinutes), m_batteryPercent(batteryPercentage), + m_powerSupply(static_cast(powerSupply)), m_xres(xres), m_yres(yres), + m_flashUsed(static_cast(flash)), m_autoCapture(autoCapture), + m_timeBeforeFirstCapture(tbfc), m_timeBetweenCaptures(tbc){} + + UInt32 m_type; + Str255 m_deviceName; + UInt32 m_batteryMinutes; + Int16 m_batteryPercent; + Int32 m_powerSupply; + Fix32 m_xres; + Fix32 m_yres; + UInt32 m_flashUsed; + UInt32 m_autoCapture; + UInt32 m_timeBeforeFirstCapture; + UInt32 m_timeBetweenCaptures; + +}; +TWPP_DETAIL_PACK_END + +// must be defined outside the class because of msvc2015 +constexpr inline DeviceEvent DeviceEvent::simple(Type type, const Str255& deviceName) noexcept{ + return DeviceEvent(type, deviceName, 0, 0, PowerSupply::External, Fix32(), Fix32(), Flash::None, 0, 0, 0); +} + +constexpr inline DeviceEvent DeviceEvent::checkBattery( + const Str255& deviceName, + UInt32 batteryMinutes, + Int16 batteryPercentage +) noexcept{ + return DeviceEvent(Type::CheckBattery, deviceName, batteryMinutes, batteryPercentage, PowerSupply::External, Fix32(), Fix32(), Flash::None, 0, 0, 0); +} + +constexpr inline DeviceEvent DeviceEvent::checkPowerSupply( + const Str255& deviceName, + PowerSupply powerSupply +) noexcept{ + return DeviceEvent(Type::CheckPowerSupply, deviceName, 0, 0, powerSupply, Fix32(), Fix32(), Flash::None, 0, 0, 0); +} + +constexpr inline DeviceEvent DeviceEvent::checkResolution( + const Str255& deviceName, + Fix32 xres, + Fix32 yres +) noexcept{ + return DeviceEvent(Type::CheckResolution, deviceName, 0, 0, PowerSupply::External, xres, yres, Flash::None, 0, 0, 0); +} + +constexpr inline DeviceEvent DeviceEvent::checkFlash( + const Str255& deviceName, + Flash flash +) noexcept{ + return DeviceEvent(Type::CheckFlash, deviceName, 0, 0, PowerSupply::External, Fix32(), Fix32(), flash, 0, 0, 0); +} + +constexpr inline DeviceEvent DeviceEvent::checkAutomaticCapture( + const Str255& deviceName, + UInt32 autoCapture, + UInt32 timeBeforeFirstCapture, + UInt32 timeBetweenCaptures +) noexcept{ + return DeviceEvent(Type::CheckAutomaticCapture, deviceName, 0, 0, PowerSupply::External, + Fix32(), Fix32(), Flash::None, autoCapture, timeBeforeFirstCapture, timeBetweenCaptures); +} + +} + +#endif // TWPP_DETAIL_FILE_DEVICEEVENT_HPP diff --git a/twpp/element8.hpp b/twpp/element8.hpp new file mode 100644 index 00000000..585d5712 --- /dev/null +++ b/twpp/element8.hpp @@ -0,0 +1,118 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_ELEMENT8_HPP +#define TWPP_DETAIL_FILE_ELEMENT8_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Element in a palette consisting of 3 parts (RGB, CMY, ...) +/// in the order of the type alphabetic representation. +class Element8 { + +public: + /// Creates zero-initialized element. + constexpr Element8() noexcept : + m_index(0), m_channel1(0), m_channel2(0), m_channel3(0){} + + /// Creates zero-initialized element with specified index. + explicit constexpr Element8(UInt8 index) noexcept : + m_index(index), m_channel1(0), m_channel2(0), m_channel3(0){} + + /// Creates element with set channels. + constexpr Element8( + UInt8 channel1, + UInt8 channel2, + UInt8 channel3 + ) noexcept : + m_index(0), m_channel1(channel1), m_channel2(channel2), + m_channel3(channel3){} + + /// Creates element with set channels at index. + constexpr Element8( + UInt8 index, + UInt8 channel1, + UInt8 channel2, + UInt8 channel3 + ) noexcept : + m_index(index), m_channel1(channel1), m_channel2(channel2), + m_channel3(channel3){} + + /// Index of the element in palette. + constexpr UInt8 index() const noexcept{ + return m_index; + } + + /// Sets index of the element in palette. + void setIndex(UInt8 index) noexcept{ + m_index = index; + } + + /// Channel 1 information. + constexpr UInt8 channel1() const noexcept{ + return m_channel1; + } + + /// Sets channel 1 information. + void setChannel1(UInt8 channel1) noexcept{ + m_channel1 = channel1; + } + + /// Channel 2 information. + constexpr UInt8 channel2() const noexcept{ + return m_channel2; + } + + /// Sets channel 2 information. + void setChannel2(UInt8 channel2) noexcept{ + m_channel2 = channel2; + } + + /// Channel 3 information. + constexpr UInt8 channel3() const noexcept{ + return m_channel3; + } + + /// Sets channel 3 information. + void setChannel3(UInt8 channel3) noexcept{ + m_channel3 = channel3; + } + +private: + UInt8 m_index; + UInt8 m_channel1; + UInt8 m_channel2; + UInt8 m_channel3; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_ELEMENT8_HPP diff --git a/twpp/enums.hpp b/twpp/enums.hpp new file mode 100644 index 00000000..9a51b964 --- /dev/null +++ b/twpp/enums.hpp @@ -0,0 +1,1459 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_ENUMS_HPP +#define TWPP_DETAIL_FILE_ENUMS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +enum class Alarm : UInt16 { + General = 0, // aka TWAL_ALARM + FeederError = 1, + FeederWarning = 2, + BarCode = 3, + DoubleFeed = 4, + Jam = 5, + PatchCode = 6, + Power = 7, + Skew = 8 +}; + +/// Argument types. +enum class Dat : UInt16 { + Null = 0x0000, + Capability = 0x0001, + Event = 0x0002, + Identity = 0x0003, + Parent = 0x0004, + PendingXfers = 0x0005, + SetupMemXfer = 0x0006, + SetupFileXfer = 0x0007, + Status = 0x0008, + UserInterface = 0x0009, + XferGroup = 0x000a, + CustomData = 0x000c, + DeviceEvent = 0x000d, + FileSystem = 0x000e, + PassThrough = 0x000f, + Callback = 0x0010, + StatusUtf8 = 0x0011, + Callback2 = 0x0012, + ImageInfo = 0x0101, + ImageLayout = 0x0102, + ImageMemXfer = 0x0103, + ImageNativeXfer = 0x0104, + ImageFileXfer = 0x0105, + CieColor = 0x0106, + GrayResponse = 0x0107, + RgbResponse = 0x0108, + JpegCompression = 0x0109, + Palette8 = 0x010a, + ExtImageInfo = 0x010b, + Filter = 0x010c, + AudioFileXfer = 0x0201, + AudioInfo = 0x0202, + AudioNativeXfer = 0x0203, + IccProfile = 0x0401, + ImageMemFileXfer = 0x0402, + EntryPoint = 0x0403, + + CustomBase = 0x8000 +}; + +/// Values of CapType::IAutoSize. +enum class AutoSize : UInt16 { + None = 0, + Auto = 1, + Current = 2 +}; + +/// Values of CapType::ISupportedBarcodeTypes. +enum class BarCodeType : UInt16 { + ThreeOfNine = 0, + ThreeOfFiveInterleaved = 1, + ThreeOfFiveNonInterleaved = 2, + Code93 = 3, + Code128 = 4, + Ucc128 = 5, + CodaBar = 6, + Upca = 7, + Upce = 8, + Ean8 = 9, + Ean13 = 10, + Postnet = 11, + Pdf417 = 12, + TwoOfFiveIndustrial = 13, + TwoOfFiveMatrix = 14, + TwoOfFiveDatalogic = 15, + TwoOfFiveIata = 16, + ThreeOfNineFullAscii = 17, + CodaBarWithStartStop = 18, + MaxiCode = 19, + QrCode = 20 +}; + +/// Values of CapType::IBitDepthReduction. +enum class BitDepthReduction : UInt16 { + Threshold = 0, + HalfTone = 1, + CustHalfTone = 2, + Diffusion = 3, + DynamicThreshold = 4 +}; + +/// Values of CapType::IBitOrder. +enum class BitOrder : UInt16 { + LsbFirst = 0, + MsbFirst = 1 +}; + +/// Values of CapType::CameraSide. +enum class CameraSide : UInt16 { + Both = 0, + Top = 1, + Bottom = 2 +}; + +enum class ConditionCode : UInt16 { + Success = 0, + Bummer = 1, + LowMemory = 2, + NoDs = 3, + MaxConnections = 4, + OperationError = 5, + BadCap = 6, + BadProtocol = 9, + BadValue = 10, + SeqError = 11, + BadDest = 12, + CapUnsupported = 13, + CapBadOperation = 14, + CapSeqError = 15, + Denied = 16, + FileExists = 17, + FileNotFound = 18, + NotEmpty = 19, + PaperJam = 20, + PaperDoubleFeed = 21, + FileWriteError = 22, + CheckDeviceOnline = 23, + InterLock = 24, + DamagedCorner = 25, + FocusError = 26, + DocTooLight = 27, + DocTooDark = 28, + NoMedia = 29, + + CustomBase = 0x8000 +}; + +typedef ConditionCode CC; + +static inline constexpr bool success(CC cc) noexcept{ + return cc == CC::Success; +} + +/// Capability container type. +enum class ConType : UInt16 { + Array = 3, + Enumeration = 4, + OneValue = 5, + Range = 6, + DontCare = 0xFFFF +}; + +/// Capability type. +enum class CapType : UInt16 { + XferCount = 0x0001, + ICompression = 0x0100, + IPixelType = 0x0101, + IUnits = 0x0102, + IXferMech = 0x0103, + Author = 0x1000, + Caption = 0x1001, + FeederEnabled = 0x1002, + FeederLoaded = 0x1003, + TimeDate = 0x1004, + SupportedCaps = 0x1005, + ExtendedCaps = 0x1006, + AutoFeed = 0x1007, + ClearPage = 0x1008, + FeedPage = 0x1009, + RewindPage = 0x100a, + Indicators = 0x100b, + PaperDetectable = 0x100d, + UiControllable = 0x100e, + DeviceOnline = 0x100f, + AutoScan = 0x1010, + ThumbnailsEnabled = 0x1011, + Duplex = 0x1012, + DuplexEnabled = 0x1013, + EnableDsUiOnly = 0x1014, + CustomDsData = 0x1015, + Endorser = 0x1016, + JobControl = 0x1017, + Alarms = 0x1018, + AlarmVolume = 0x1019, + AutomaticCapture = 0x101a, + TimeBeforeFirstCapture = 0x101b, + TimeBetweenCaptures = 0x101c, + ClearBuffers = 0x101d, + MaxBatchBuffers = 0x101e, + DeviceTimeDate = 0x101f, + PowerSupply = 0x1020, + CameraPreviewUi = 0x1021, + DeviceEvent = 0x1022, + SerialNumber = 0x1024, + Printer = 0x1026, + PrinterEnabled = 0x1027, + PrinterIndex = 0x1028, + PrinterMode = 0x1029, + PrinterString = 0x102a, + PrinterSuffix = 0x102b, + Language = 0x102c, + FeederAlignment = 0x102d, + FeederOrder = 0x102e, + ReacquireAllowed = 0x1030, + BatteryMinutes = 0x1032, + BatteryPercentage = 0x1033, + CameraSide = 0x1034, + Segmented = 0x1035, + CameraEnabled = 0x1036, + CameraOrder = 0x1037, + MicrEnabled = 0x1038, + FeederPrep = 0x1039, + FeederPocket = 0x103a, + AutomaticSenseMedium = 0x103b, + CustomInterfaceGuid = 0x103c, + SupportedCapsSegmentUnique = 0x103d, + SupportedDats = 0x103e, + DoubleFeedDetection = 0x103f, + DoubleFeedDetectionLength = 0x1040, + DoubleFeedDetectionSensitivity = 0x1041, + DoubleFeedDetectionResponse = 0x1042, + PaperHandling = 0x1043, + IndicatorsMode = 0x1044, + PrinterVerticalOffset = 0x1045, + PowerSaveTime = 0x1046, + PrinterCharRotation = 0x1047, + PrinterFontStyle = 0x1048, + PrinterIndexLeadChar = 0x1049, + PrinterIndexMaxValue = 0x104A, + PrinterIndexNumDigits = 0x104B, + PrinterIndexStep = 0x104C, + PrinterIndexTrigger = 0x104D, + PrinterStringPreview = 0x104E, + IAutoBright = 0x1100, + IBrightness = 0x1101, + IContrast = 0x1103, + ICustHalfTone = 0x1104, + IExposureTime = 0x1105, + IFilter = 0x1106, + IFlashUsed = 0x1107, + IGamma = 0x1108, + IHalfTones = 0x1109, + IHighLight = 0x110a, + IImageFileFormat = 0x110c, + ILampState = 0x110d, + ILightSource = 0x110e, + IOrientation = 0x1110, + IPhysicalWidth = 0x1111, + IPhysicalHeight = 0x1112, + IShadow = 0x1113, + IFrames = 0x1114, + IXNativeResolution = 0x1116, + IYNativeResolution = 0x1117, + IXResolution = 0x1118, + IYResolution = 0x1119, + IMaxFrames = 0x111a, + ITiles = 0x111b, + IBitOrder = 0x111c, + ICcittKFactor = 0x111d, + ILightPath = 0x111e, + IPixelFlavor = 0x111f, + IPlanarChunky = 0x1120, + IRotation = 0x1121, + ISupportedSizes = 0x1122, + IThreshold = 0x1123, + IXScaling = 0x1124, + IYScaling = 0x1125, + IBitOrderCodes = 0x1126, + IPixelFlavorCodes = 0x1127, + IJpegPixelType = 0x1128, + ITimeFill = 0x112a, + IBitDepth = 0x112b, + IBitDepthReduction = 0x112c, + IUndefinedImageSize = 0x112d, + IImageDataSet = 0x112e, + IExtImageInfo = 0x112f, + IMinimumHeight = 0x1130, + IMinimumWidth = 0x1131, + IAutoDiscardBlankPages = 0x1134, + IFlipRotation = 0x1136, + IBarCodeDetectionEnabled = 0x1137, + ISupportedBarCodeTypes = 0x1138, + IBarCodeMaxSearchPriorities = 0x1139, + IBarCodeSearchPriorities = 0x113a, + IBarCodeSearchMode = 0x113b, + IBarCodeMaxRetries = 0x113c, + IBarCodeTimeOut = 0x113d, + IZoomFactor = 0x113e, + IPatchCodeDetectionEnabled = 0x113f, + ISupportedPatchCodeTypes = 0x1140, + IPatchCodeMaxSearchPriorities = 0x1141, + IPatchCodeSearchPriorities = 0x1142, + IPatchCodeSearchMode = 0x1143, + IPatchCodeMaxRetries = 0x1144, + IPatchCodeTimeOut = 0x1145, + IFlashUsed2 = 0x1146, + IImageFilter = 0x1147, + INoiseFilter = 0x1148, + IOverScan = 0x1149, + IAutomaticBorderDetection = 0x1150, + IAutomaticDeskew = 0x1151, + IAutomaticRotate = 0x1152, + IJpegQuality = 0x1153, + IFeederType = 0x1154, + IIccProfile = 0x1155, + IAutoSize = 0x1156, + IAutomaticCropUsesFrame = 0x1157, + IAutomaticLengthDetection = 0x1158, + IAutomaticColorEnabled = 0x1159, + IAutomaticColorNonColorPixelType = 0x115a, + IColorManagementEnabled = 0x115b, + IImageMerge = 0x115c, + IImageMergeHeightThreshold = 0x115d, + ISupportedExtImageInfo = 0x115e, + IFilmType = 0x115f, + IMirror = 0x1160, + IJpegSubSampling = 0x1161, + AXferMech = 0x1202, + CustomBase = 0x8000 +}; + +/// Values of CapType::ClearBuffers. +enum class ClearBuffers : UInt16 { + Auto = 0, + Clear = 1, + NoClear = 2 +}; + +/// Values of CapType::IPlanarChunky. +enum class ColorFormat : UInt16 { + Chunky = 0, + Planar = 1 +}; + +typedef ColorFormat PlanarChunky; + +/// Values of CapType::ICompression. +/// Also used in ImageInfo and ImageMemXfer. +enum class Compression : UInt16 { + None = 0, + PackBits = 1, + Group31D = 2, + Group31DEol = 3, + Group32D = 4, + Group4 = 5, + Jpeg = 6, + Lzw = 7, + JBig = 8, + Png = 9, + Rle4 = 10, + Rle8 = 11, + BitFields = 12, + Ziz = 13, + Jpeg2000 = 14, + DontCare = 0xFFFF +}; + +/// Countries for Version. +enum class Country : UInt16 { + Afghanistan = 1001, + Algeria = 213, + AmericanSamoa = 684, + Andorra = 033, + Angola = 1002, + Anguilla = 8090, + Antigua = 8091, + Argentina = 54, + Aruba = 297, + Ascensioni = 247, + Australia = 61, + Austria = 43, + Bahamas = 8092, + Bahrain = 973, + Bangladesh = 880, + Barbados = 8093, + Belgium = 32, + Belize = 501, + Benin = 229, + Bermuda = 8094, + Bhutan = 1003, + Bolivia = 591, + Botswana = 267, + Britain = 6, + BritVirginIs = 8095, + Brazil = 55, + Brunei = 673, + Bulgaria = 359, + BurkinaFaso = 1004, + Burma = 1005, + Burundi = 1006, + Camaroon = 237, + Canada = 2, + CapeVerdeIs = 238, + CaymanIs = 8096, + CentralAfRep = 1007, + Chad = 1008, + Chile = 56, + China = 86, + ChristmasIs = 1009, + CocosIs = 1009, + Colombia = 57, + Comoros = 1010, + Congo = 1011, + CookIs = 1012, + Costarica = 506, + Cuba = 005, + Cyprus = 357, + Czechoslovakia = 42, + Denmark = 45, + Djibouti = 1013, + Dominica = 8097, + DomincanRep = 8098, + EasterIs = 1014, + Ecuador = 593, + Egypt = 20, + ElSalvador = 503, + EqGuinea = 1015, + Ethiopia = 251, + FalklandIs = 1016, + FaeroeIs = 298, + FijiIslands = 679, + Finland = 358, + France = 33, + FrAntilles = 596, + FrGuiana = 594, + FrPolyneisa = 689, + FutanaIs = 1043, + Gabon = 241, + Gambia = 220, + Germany = 49, + Ghana = 233, + Gibralter = 350, + Greece = 30, + Greenland = 299, + Grenada = 8099, + Grenedines = 8015, + Guadeloupe = 590, + Guam = 671, + GuantanamoBay = 5399, + Guatemala = 502, + Guinea = 224, + GuineaBissau = 1017, + Guyana = 592, + Haiti = 509, + Honduras = 504, + HongKong = 852, + Hungary = 36, + Iceland = 354, + India = 91, + Indonesia = 62, + Iran = 98, + Iraq = 964, + Ireland = 353, + Israel = 972, + Italy = 39, + IvoryCoast = 225, + Jamaica = 8010, + Japan = 81, + Jordan = 962, + Kenya = 254, + Kiribati = 1018, + Korea = 82, + Kuwait = 965, + Laos = 1019, + Lebanon = 1020, + Liberia = 231, + Libya = 218, + Liechtenstein = 41, + Luxenbourg = 352, + Macao = 853, + Madagascar = 1021, + Malawi = 265, + Malaysia = 60, + Maldives = 960, + Mali = 1022, + Malta = 356, + MarshallIs = 692, + Mauritania = 1023, + Mauritius = 230, + Mexico = 3, + Micronesia = 691, + Miquelon = 508, + Monaco = 33, + Mongolia = 1024, + Montserrat = 8011, + Morocco = 212, + Mozambique = 1025, + Namibia = 264, + Nauru = 1026, + Nepal = 977, + Netherlands = 31, + NethAntilles = 599, + Nevis = 8012, + NewCaledonia = 687, + NewZealand = 64, + Nicaragua = 505, + Niger = 227, + Nigeria = 234, + Niue = 1027, + Norfolki = 1028, + Norway = 47, + Oman = 968, + Pakistan = 92, + Palau = 1029, + Panama = 507, + Paraguay = 595, + Peru = 51, + Phillippines = 63, + PitcairnIs = 1030, + PNewGuinea = 675, + Poland = 48, + Portugal = 351, + Qatar = 974, + Reunioni = 1031, + Romania = 40, + Rwanda = 250, + Saipan = 670, + SanMarino = 39, + SaoTome = 1033, + SaudiArabia = 966, + Senegal = 221, + Seychellesis = 1034, + SierraLeone = 1035, + Singapore = 65, + SolomonIs = 1036, + Somali = 1037, + SouthAfrica = 27, + Spain = 34, + SriLanka = 94, + StHelena = 1032, + StKitts = 8013, + StLucia = 8014, + StPierre = 508, + StVincent = 8015, + Sudan = 1038, + Suriname = 597, + Swaziland = 268, + Sweden = 46, + Switzerland = 41, + Syria = 1039, + Taiwan = 886, + Tanzania = 255, + Thailand = 66, + Tobago = 8016, + Togo = 228, + Tongais = 676, + Trinidad = 8016, + Tunisia = 216, + Turkey = 90, + TurksCaicos = 8017, + Tuvalu = 1040, + Uganda = 256, + Ussr = 7, + UaEmirates = 971, + UnitedKingdom = 44, + Usa = 1, + Uruguay = 598, + Vanuatu = 1041, + VaticanCity = 39, + Venezuela = 58, + Wake = 1042, + WallisIs = 1043, + WesternSahara = 1044, + WesternSamoa = 1045, + Yemen = 1046, + Yugoslavia = 38, + Zaire = 243, + Zambia = 260, + Zimbabwe = 263, + Albania = 355, + Armenia = 374, + Azerbaijan = 994, + Belarus = 375, + BosniaHerzgo = 387, + Cambodia = 855, + Croatia = 385, + CzechRepublic = 420, + DiegoGarcia = 246, + Eritrea = 291, + Estonia = 372, + Georgia = 995, + Latvia = 371, + Lesotho = 266, + Lithuania = 370, + Macedonia = 389, + MayotteIs = 269, + Moldova = 373, + Myanmar = 95, + NorthKorea = 850, + Puertorico = 787, + Russia = 7, + Serbia = 381, + Slovakia = 421, + Slovenia = 386, + SouthKorea = 82, + Ukraine = 380, + UsVirginIs = 340, + Vietnam = 84 +}; + +/// Data group for distinguishing different categories of TWAIN operations. +enum class DataGroup : UInt32 { + Control = 0x0001L, + Image = 0x0002L, + Audio = 0x0004L +}; + +typedef DataGroup DG; + +static constexpr inline UInt32 operator~(DataGroup g) noexcept{ + return ~static_cast(g); +} + +static constexpr inline UInt32 operator|(DataGroup a, DataGroup b) noexcept{ + return static_cast(a) | static_cast(b); +} + +static constexpr inline UInt32 operator|(DataGroup a, UInt32 b) noexcept{ + return static_cast(a) | b; +} + +static constexpr inline UInt32 operator&(DataGroup a, DataGroup b) noexcept{ + return static_cast(a) & static_cast(b); +} + +static constexpr inline UInt32 operator&(UInt32 a, DataGroup b) noexcept{ + return static_cast(a) & b; +} + + +/// Values of CapType::IAutoDiscardBlankPages. +enum class DiscardBlankPages : Int32 { + Disabled = -2, + Auto = -1 +}; + +static constexpr inline DiscardBlankPages discardBytes(Int32 value) noexcept{ + return static_cast(value); +} + +/// Values of CapType::DoubleFeedDetection. +enum class DoubleFeedDetection : UInt16 { + Ultrasonic = 0, + ByLength = 1, + Infrared = 2, +}; + +/// Values of CapType::DoubleFeedDetectionResponse. +enum class DoubleFeedResponse : UInt16 { + Stop = 0, + StopAndWait = 1, + Sound = 2, + DoNotImprint = 3 +}; + +/// Values of CapType::DoubleFeedDetectionSensitivity. +enum class DoubleFeedSensitivity : UInt16 { + Low = 0, + Medium = 1, + High = 2 +}; + +/// Values of CapType::Duplex. +enum class Duplex : UInt16 { + None = 0, + OnePass = 1, + TwoPass = 2 +}; + +/// Values for CapType::FeederAlignment. +enum class FeederAlignment : UInt16 { + None = 0, + Left = 1, + Center = 2, + Right = 3 +}; + +/// Values for CapType::FeederOrder. +enum class FeederOrder : UInt16 { + FirstPageFirst = 0, + LastPageFirst = 1 +}; + + +/// Values for CapType::FeederPocket. +enum class FeederPocket : UInt16 { + PError = 0, + P1 = 1, + P2 = 2, + P3 = 3, + P4 = 4, + P5 = 5, + P6 = 6, + P7 = 7, + P8 = 8, + P9 = 9, + P10 = 10, + P11 = 11, + P12 = 12, + P13 = 13, + P14 = 14, + P15 = 15, + P16 = 16 +}; + +/// Values for CapType::IFeederType. +enum class FeederType : UInt16 { + General = 0, + Photo = 1, +}; + +/// Values for CapType::IFilmType. +enum class FilmType : UInt16 { + Positive = 0, + Negative = 1 +}; + +/// Values for CapType::IFilter. +enum class Filter : UInt16 { + Red = 0, + Green = 1, + Blue = 2, + None = 3, + White = 4, + Cyan = 5, + Magenta = 6, + Yellow = 7, + Black = 8 +}; + +/// Values for CapType::IFlashUsed2 and DeviceEvent.flash. +enum class Flash : UInt16 { // Capability->UInt16, DeviceEvent->UInt32 + None = 0, + Off = 1, + On = 2, + Auto = 3, + RedEye = 4 +}; + +/// Values for CapType::IFlipRotation. +enum class FlipRotation : UInt16 { + Book = 0, + Fanfold = 1 +}; + +/// Values for CapType::PrinterFontStyle +enum class FontStyle : UInt16 { + Normal = 0, + Bold = 1, + Italic = 2, + LargeSize = 3, + SmallSize = 4 +}; + +/// Values for CapType::IIccProfile. +enum class IccProfile : UInt16 { + None = 0, + Link = 1, + Embed = 2 +}; + +/// Values for CapType::IImageFileFormat. +enum class ImageFileFormat : UInt16 { + Tiff = 0, + Pict = 1, + Bmp = 2, + Xbm = 3, + Jfif = 4, + Fpx = 5, + TiffMulti = 6, + Png = 7, + Spiff = 8, + Exif = 9, + Pdf = 10, + Jp2 = 11, + Jpx = 13, + Dejavu = 14, + PdfA = 15, + PdfA2 = 16 +}; + +/// Values for CapType::IImageFilter. +enum class ImageFilter : UInt16 { + None = 0, + Auto = 1, + LowPass = 2, + BandPass = 3, + HighPass = 4, + Text = 3, + FineLine = 4 +}; + +/// Values of CapType::IImageMerge. +enum class ImageMerge : UInt16 { + None = 0, + FrontOnTop = 1, + FrontOnBottom = 2, + FrontOnLeft = 3, + FrontOnRight = 4 +}; + +/// Values of CapType::PrinterIndexTrigger. +enum class IndexTrigger : UInt16 { + Page = 0, + Patch1 = 1, + Patch2 = 2, + Patch3 = 3, + Patch4 = 4, + PatchT = 5, + Patch6 = 6 +}; + +/// Values of CapType::IndicatorsMode. +enum class IndicatorsMode : UInt16 { + Info = 0, + Warning = 1, + Error = 2, + Warmup = 3 +}; + +/// Values of CapType::JobControl. +enum class JobControl : UInt16 { + None = 0, + InclSepContScan = 1, + InclSepStopScan = 2, + ExclSepContScan = 3, + ExclSepStopScap = 4 +}; + +/// Values of CapType::IJpegQuality. +enum class JpegQuality : Int16 { + Unknown = -4, + Low = -3, + Medium = -2, + High = -1 +}; + +static constexpr inline JpegQuality jpegQuality(Int16 value) noexcept{ + return static_cast(value); +} + + +/// Values of CapType::IJpegSubSampling. +enum class JpegSubSampling : UInt16 { + Jp444Ycbcr = 0, + Jp444Rgb = 1, + Jp422 = 2, + Jp421 = 3, + Jp411 = 4, + Jp420 = 5, + Jp410 = 6, + Jp311 = 7 +}; + +/// Values of CapType::Language and Version structure. +enum class Language : UInt16 { + UserLocale = 0xFFFF, + Afrikaans = 14, + Albania = 15, + Arabic = 16, + ArabicAlgeria = 17, + ArabicBahrain = 18, + ArabicEgypt = 19, + ArabicIraq = 20, + ArabicJordan = 21, + ArabicKuwait = 22, + ArabicLebanon = 23, + ArabicLibya = 24, + ArabicMorocco = 25, + ArabicOman = 26, + ArabicQatar = 27, + ArabicSaudiArabia = 28, + ArabicSyria = 29, + ArabicTunisia = 30, + ArabicUae = 31, + ArabicYemen = 32, + Basque = 33, + ByeloRussian = 34, + Bulgarian = 35, + Catalan = 36, + Chinese = 37, + ChineseHongKong = 38, + ChinesePrc = 39, + ChineseSingapore = 40, + ChineseSimplified = 41, + ChineseTaiwan = 42, + ChineseTraditional = 43, + Croatia = 44, + Czech = 45, + Danish = 0, + Dutch = 1, + DutchBelgian = 46, + English = 2, + EnglishAustralian = 47, + EnglishCanadian = 48, + EnglishIreland = 49, + EnglishNewZealand = 50, + EnglishSouthAfrica = 51, + EnglishUk = 52, + EnglishUsa = 13, + Estonian = 53, + Faeroese = 54, + Farsi = 55, + Finnish = 4, + French = 5, + FrenchBelgian = 56, + FrenchCanadian = 3, + FrenchLuxembourg = 57, + FrenchSwiss = 58, + German = 6, + GermanAustrian = 59, + GermanLuxembourg = 60, + GermanLiechtenstein = 61, + GermanSwiss = 62, + Greek = 63, + Hebrew = 64, + Hungarian = 65, + Icelandic = 7, + Indonesian = 66, + Italian = 8, + ItalianSwiss = 67, + Japanese = 68, + Korean = 69, + KoreanJohab = 70, + Latvian = 71, + Lithuanian = 72, + Norwegian = 9, + NorwegianBokmal = 73, + NorwegianNynorsk = 74, + Polish = 75, + Portuguese = 10, + PortugueseBrazil = 76, + Romanian = 77, + Russian = 78, + SerbianLatin = 79, + Slovak = 80, + Slovenian = 81, + Spanish = 11, + SpanishMexican = 82, + SpanishModern = 83, + Swedish = 12, + Thai = 84, + Turkish = 85, + Ukranian = 86, + Assamese = 87, + Bengali = 88, + Bihari = 89, + Bodo = 90, + Dogri = 91, + Gujarati = 92, + Haryanvi = 93, + Hindi = 94, + Kannada = 95, + Kashmiri = 96, + Malayalam = 97, + Marathi = 98, + Marwari = 99, + Meghalayan = 100, + Mizo = 101, + Naga = 102, + Orissi = 103, + Punjabi = 104, + Pushtu = 105, + SerbianCyrillic = 106, + Sikkimi = 107, + SwedishFinland = 108, + Tamil = 109, + Telugu = 110, + Tripuri = 111, + Urdu = 112, + Vietnamese = 113 +}; + +/// Values of CapType::ILightPath. +enum class LightPath : UInt16 { + Reflective = 0, + Transmissive = 1 +}; + +/// Values of CapType::ILightSource. +enum class LightSource : UInt16 { + Red = 0, + Green = 1, + Blue = 2, + None = 3, + White = 4, + Uv = 5, + Ir = 6 +}; + +/// Values for CapType::IMirror. +enum class Mirror : UInt16 { + None = 0, + Vertical = 1, + Horizontal = 2 +}; + +/// Values of possible actions of TWAIN operations. +enum class Msg : UInt16 { + Null = 0x0000, + Get = 0x0001, + GetCurrent = 0x0002, + GetDefault = 0x0003, + GetFirst = 0x0004, + GetNext = 0x0005, + Set = 0x0006, + Reset = 0x0007, + QuerySupport = 0x0008, + GetHelp = 0x0009, + GetLabel = 0x000a, + GetLabelEnum = 0x000b, + SetConstraint = 0x000c, + XferReady = 0x0101, + CloseDsReq = 0x0102, + CloseDsOk = 0x0103, + DeviceEvent = 0x0104, + OpenDsm = 0x0301, + CloseDsm = 0x0302, + OpenDs = 0x0401, + CloseDs = 0x0402, + UserSelect = 0x0403, + DisableDs = 0x0501, + EnableDs = 0x0502, + EnableDsUiOnly = 0x0503, + ProcessEvent = 0x0601, + EndXfer = 0x0701, + StopFeeder = 0x0702, + ChangeDir = 0x0801, + CreateDir = 0x0802, + Delete = 0x0803, + FormatMedia = 0x0804, + GetClose = 0x0805, + GetFirstFile = 0x0806, + GetInfo = 0x0807, + GetNextFile = 0x0808, + Rename = 0x0809, + Copy = 0x080A, + AutomaticCaptureDir = 0x080B, + PassThrough = 0x0901, + RegisterCallback = 0x0902, + ResetAll = 0x0A01, + CustomBase = 0x8000 +}; + +/// Capability action support flags. +enum class MsgSupport : Int32 { + Get = 0x0001, + Set = 0x0002, + GetDefault = 0x0004, + GetCurrent = 0x0008, + Reset = 0x0010, + SetConstraint = 0x0020, + GetHelp = 0x0100, + GetLabel = 0x0200, + GetLabelEnum = 0x0400 +}; + +static inline constexpr MsgSupport operator|(MsgSupport a, MsgSupport b){ + return static_cast(static_cast(a) | static_cast(b)); +} + +static inline constexpr MsgSupport operator&(MsgSupport a, MsgSupport b){ + return static_cast(static_cast(a) & static_cast(b)); +} + +static inline constexpr MsgSupport operator^(MsgSupport a, MsgSupport b){ + return static_cast(static_cast(a) ^ static_cast(b)); +} + +/// Action support flags, nothing supported. +static constexpr const MsgSupport msgSupportEmpty = static_cast(0); + +/// Action support flags, all `get` actions. +static constexpr const MsgSupport msgSupportGetAll = MsgSupport::Get | MsgSupport::GetDefault | MsgSupport::GetCurrent; + +/// Action support flags, all `get` actions, `set` and `reset`. +static constexpr const MsgSupport msgSupportGetAllSetReset = msgSupportGetAll | MsgSupport::Set | MsgSupport::Reset; + +/// Values for CapType::INoiseFilter. +enum class NoiseFilter : UInt16 { + None = 0, + Auto = 1, + LonePixel = 2, + MajorityRule = 3 +}; + +/// Values for CapType::IOrientation. +enum class Orientation : UInt16 { + Rot0 = 0, + Rot90 = 1, + Rot180 = 2, + Rot270 = 3, + Portrait = 0, + Landscape = 3, + Auto = 4, + AutoText = 5, + AutoPicture = 6 +}; + +/// Values for CapType::IOverscan. +enum class OverScan : UInt16 { + None = 0, + Auto = 1, + TopBottom = 2, + LeftRight = 3, + All = 4 +}; + +/// Values for CapType::PaperHandling. +enum class PaperHandling : UInt16 { + Normal = 0, + Fragile = 1, + Thick = 2, + TriFold = 3, + Photograph = 4 +}; + +/// Values for CapType::ISupportedSizes. +enum class PaperSize : UInt16 { + None = 0, + A4 = 1, + JisB5 = 2, + UsLetter = 3, + UsLegal = 4, + A5 = 5, + IsoB4 = 6, + IsoB6 = 7, + UsLedger = 9, + UsExecutive = 10, + A3 = 11, + IsoB3 = 12, + A6 = 13, + C4 = 14, + C5 = 15, + C6 = 16, + Ps4A0 = 17, // 4A0 + Ps2A0 = 18, // 2A0 + A0 = 19, + A1 = 20, + A2 = 21, + A7 = 22, + A8 = 23, + A9 = 24, + A10 = 25, + IsoB0 = 26, + IsoB1 = 27, + IsoB2 = 28, + IsoB5 = 29, + IsoB7 = 30, + IsoB8 = 31, + IsoB9 = 32, + IsoB10 = 33, + JisB0 = 34, + JisB1 = 35, + JisB2 = 36, + JisB3 = 37, + JisB4 = 38, + JisB6 = 39, + JisB7 = 40, + JisB8 = 41, + JisB9 = 42, + JisB10 = 43, + C0 = 44, + C1 = 45, + C2 = 46, + C3 = 47, + C7 = 48, + C8 = 49, + C9 = 50, + C10 = 51, + UsStatement = 52, + BusinessCard = 53, + MaxSize = 54 +}; + +/// Values for CapType::IPixelFlavor, CapType::IPixelFlavorCodes, InfoId::PixelFlavor. +/// Chocolate - pixel represents darkest data. +/// Vanilla - pixel represents lightest data. +enum class PixelFlavor : UInt16 { + Chocolate = 0, + Vanilla = 1 +}; + +/// Values for CapType::IPixelType, ImageInfo. +enum class PixelType : UInt16 { + BlackWhite = 0, + Gray = 1, + Rgb = 2, + Palette = 3, + Cmy = 4, + Cmyk = 5, + Yuv = 6, + Yuvk = 7, + CieXyz = 8, + Lab = 9, + SRgb = 10, + ScRgb = 11, + Infrared = 16 +}; + +/// Values for CapType::PowerSupply. +enum class PowerSupply : UInt16 { // Capability->UInt16, DeviceEvent->Int32 + External = 0, + Battery = 1, +}; + +/// Values for CapType::Printer. +enum class Printer : UInt16 { + ImprinterTopBefore = 0, + ImprinterTopAfter = 1, + ImprinterBottomBefore = 2, + ImprinterBottomAfter = 3, + EndorserTopBefore = 4, + EndorserTopAfter = 5, + EndorserBottomBefore = 6, + EndorserBottomAfter = 7 +}; + +/// Values for CapType::PrinterMode. +enum class PrinterMode : UInt16 { + SingleString = 0, + MultiString = 1, + CompoundString = 2 +}; + +enum class ReturnCode : UInt16 { + Success = 0, + Failure = 1, + CheckStatus = 2, + Cancel = 3, + DsEvent = 4, + NotDsEvent = 5, + XferDone = 6, + EndOfList = 7, + InfoNotSupported = 8, + DataNotAvailable = 9, + Busy = 10, + ScannerLocked = 11, + + CustomBase = 0x8000 +}; + +typedef ReturnCode RC; + +static inline constexpr bool success(ReturnCode rc) noexcept{ + return rc == RC::Success; +} + + +/// Values for CapType::IBarCodeSearchMode. +enum class SearchMode : UInt16 { + Horizontal = 0, + Vertical = 1, + HorizVert = 2, + VertHoriz = 3 +}; + +/// Values for CapType::Segmented. +enum class Segmented : UInt16 { + None = 0, + Auto = 1, + Manual = 2 +}; + +/// TWAIN manager states. +enum class DsmState : UInt16 { + PreSession = 1, + Loaded = 2, + Open = 3 +}; + +/// TWAIN source states. +enum class DsState : UInt16 { + Closed = 3, + Open = 4, + Enabled = 5, + XferReady = 6, + Xferring = 7 +}; + +/// Values for CapType::IUnits. +enum class Unit : UInt16 { + Inches = 0, + CentiMetres = 1, + Picas = 2, + Points = 3, + Twips = 4, + Pixels = 5, + MilliMetres = 6 +}; + +/// Values for CapType::IXferMech, CapType::AXferMech. +enum class XferMech : UInt16 { + Native = 0, + File = 1, + Memory = 2, + MemFile = 4, +}; + + +/// Type of the extended information. +enum class InfoId : UInt16 { + BarCodeX = 0x1200, + BarCodeY = 0x1201, + BarCodeText = 0x1202, + BarCodeType = 0x1203, + DeShadeTop = 0x1204, + DeShadeLeft = 0x1205, + DeShadeHeight = 0x1206, + DeShadeWidth = 0x1207, + DeShadeSize = 0x1208, + SpecklesRemoved = 0x1209, + HorzLineXCoord = 0x120A, + HorzLineYCoord = 0x120B, + HorzLineLength = 0x120C, + HorzLineThickness = 0x120D, + VertLineXCoord = 0x120E, + VertLineYCoord = 0x120F, + VertLineLength = 0x1210, + VertLineThickness = 0x1211, + PatchCode = 0x1212, + EndorsedText = 0x1213, + FormConfidence = 0x1214, + FormTemplateMatch = 0x1215, + FormTemplatePageMatch = 0x1216, + FormHorzDocOffset = 0x1217, + FormVertDocOffset = 0x1218, + BarCodeCount = 0x1219, + BarCodeConfidence = 0x121A, + BarCodeRotation = 0x121B, + BarCodeTextLength = 0x121C, + DeShadeCount = 0x121D, + DeShadeBlackCountOld = 0x121E, + DeShadeBlackCountNew = 0x121F, + DeShadeBlackRlMin = 0x1220, + DeShadeBlackRlMax = 0x1221, + DeShadeWhiteCountOld = 0x1222, + DeShadeWhiteCountNew = 0x1223, + DeShadeWhiteRlMin = 0x1224, + DeShadEWhiteRlAve = 0x1225, + DeShadeWhiteRlMax = 0x1226, + BlackSpecklesRemoved = 0x1227, + WhiteSpecklesRemoved = 0x1228, + HorzLineCount = 0x1229, + VertLineCount = 0x122A, + DeskewStatus = 0x122B, + SkewOriginalAngle = 0x122C, + SkewFinalAngle = 0x122D, + SkewConfidence = 0x122E, + SkewWindowX1 = 0x122F, + SkewWindowY1 = 0x1230, + SkewWindowX2 = 0x1231, + SkewWindowY2 = 0x1232, + SkewWindowX3 = 0x1233, + SkewWindowY3 = 0x1234, + SkewWindowX4 = 0x1235, + SkewWindowY4 = 0x1236, + BookName = 0x1238, + ChapterNumber = 0x1239, + DocumentNumber = 0x123A, + PageNumber = 0x123B, + Camera = 0x123C, + FrameNumber = 0x123D, + Frame = 0x123E, + PixelFlavor = 0x123F, + IccProfile = 0x1240, + LastSegment = 0x1241, + SegmentNumber = 0x1242, + MagData = 0x1243, + MagType = 0x1244, + PageSide = 0x1245, + FileSystemSource = 0x1246, + ImageMerged = 0x1247, + MagDataLength = 0x1248, + PaperCount = 0x1249, + PrinterText = 0x124A +}; + +/// Values for InfoId::BarCodeRotation. +enum class BarCodeRotation : UInt16 { + Rot0 = 0, + Rot90 = 1, + Rot180 = 2, + Rot270 = 3, + RotUnknown = 4 +}; + +/// Values for InfoId::PageSide. +enum class PageSide : UInt16 { + Top = 1, + Bottom = 2 +}; + +/// Values for InfoId::DeskewStatus. +enum class DeskewStatus : UInt16 { + Success = 0, + ReportOnly = 1, + Fail = 2, + Disabled = 3 +}; + +/// Values for InfoId::MagType. +enum class MagType : UInt16 { + Micr = 0, + Raw = 1, + Invalid = 2 +}; + +/// Values for InfoId::PatchCode. +enum class PatchCode : UInt16 { + P1 = 0, + P2 = 1, + P3 = 2, + P4 = 3, + P6 = 4, + PT = 5 +}; + +} + +#endif // TWPP_DETAIL_FILE_ENUMS_HPP + diff --git a/twpp/env.hpp b/twpp/env.hpp new file mode 100644 index 00000000..fae3d4b5 --- /dev/null +++ b/twpp/env.hpp @@ -0,0 +1,356 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_ENV_HPP +#define TWPP_DETAIL_FILE_ENV_HPP + +// ============= +// Twpp specific + +namespace Twpp { + +namespace Detail { + +enum { + ProtoMajor = 2, + ProtoMinor = 3, + Dsm2 = 0x10000000L, + App2 = 0x20000000L, + Ds2 = 0x40000000L +}; + +} + +} + +#if defined(TWPP_IS_DS) +# define TWPP_DETAIL_IS_DS 1 +#else +# define TWPP_DETAIL_IS_DS 0 +#endif + + +// =========== +// OS specific + +// Windows +#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64) +# define TWPP_DETAIL_OS_WIN 1 +# if defined(WIN64) || defined(_WIN64) +# define TWPP_DETAIL_OS_WIN64 1 +# else +# define TWPP_DETAIL_OS_WIN32 1 +# endif +# if !defined(WIN32_LEAN_AND_MEAN) +# define WIN32_LEAN_AND_MEAN +# endif +# if !defined(NOMINMAX) +# define NOMINMAX +# endif +extern "C" { +# include +} +# define TWPP_DETAIL_CALLSTYLE PASCAL +# define TWPP_DETAIL_EXPORT __declspec(dllexport) +namespace Twpp { + +namespace Detail { + +typedef HANDLE RawHandle; + + +namespace DsmLibOs { + +typedef HMODULE Handle; +static constexpr const Handle nullHandle = nullptr; + +template +static inline T resolve(Handle h) noexcept{ + return reinterpret_cast(::GetProcAddress(h, "DSM_Entry")); +} + +# if defined(TWPP_DETAIL_OS_WIN32) +static inline Handle load(bool old) noexcept{ + if (old){ + auto h = ::LoadLibraryA("TWAIN_32.dll"); + if (!h){ + h = ::LoadLibraryA("TWAINDSM.dll"); + } + + return h; + } else { + auto h = ::LoadLibraryA("TWAINDSM.dll"); + if (!h){ + h = ::LoadLibraryA("TWAIN_32.dll"); + } + + return h; + } +} +# else +static inline Handle load(bool) noexcept{ + return ::LoadLibraryA("TWAINDSM.dll"); +} +# endif + +static inline void unload(Handle h) noexcept{ + ::FreeLibrary(h); +} + +} // namespace DsmLibOs + +} // namespace Detail + +} // namespace Twpp + + +// Mac OS +#elif defined(__APPLE__) +# pragma message "No testing has been done on this platform, this framework might not work correctly." +# define TWPP_DETAIL_OS_MAC 1 +# include +extern "C" { +# include +# include +# include +# include +# include +} +# define TWPP_DETAIL_CALLSTYLE pascal +namespace Twpp { + +namespace Detail { + +typedef Handle RawHandle; + + +namespace DsmLibOs { + +typedef void* Handle; +static constexpr const Handle nullHandle = nullptr; + +template +static inline T resolve(Handle h) noexcept{ + return reinterpret_cast(::dlsym(h, "DSM_Entry")); +} + +static inline Handle load(bool) noexcept{ + return ::dlopen("/System/Library/Frameworks/TWAIN.framework/TWAIN", RTLD_LAZY); +} + +static inline void unload(Handle h) noexcept{ + ::dlclose(h); +} + +} // namespace DsmLibOs + +template +struct MacStatic { + + static const ::Class g_autoreleasePool; + static const ::SEL g_release; + static const ::SEL g_alloc; + static const ::SEL g_init; + + static const ::SEL g_nextEvent; + static const ::SEL g_postEvent; + static const ::SEL g_sendEvent; + static const ::id g_app; + static const ::id g_distantFuture; + + static const ::Class g_event; + static const ::SEL g_otherEventWithType; + +}; + +template const ::Class MacStatic::g_autoreleasePool = objc_getClass("NSAutoreleasePool"); +template const ::SEL MacStatic::g_release = sel_registerName("release"); +template const ::SEL MacStatic::g_alloc = sel_registerName("alloc"); +template const ::SEL MacStatic::g_init = sel_registerName("init"); + +template const ::SEL MacStatic::g_nextEvent = sel_registerName("nextEventMatchingMask:untilDate:inMode:dequeue:"); +template const ::SEL MacStatic::g_postEvent = sel_registerName("postEvent:atStart:"); +template const ::SEL MacStatic::g_sendEvent = sel_registerName("sendEvent:"); +template const ::id MacStatic::g_app = objc_msgSend(reinterpret_cast<::id>(objc_getClass("NSApplication")), sel_registerName("sharedApplication")); +template const ::id MacStatic::g_distantFuture = objc_msgSend(reinterpret_cast<::id>(objc_getClass("NSDate")), sel_registerName("distantFuture")); + +template const ::Class MacStatic::g_event = objc_getClass("NSEvent"); +template const ::SEL MacStatic::g_otherEventWithType = sel_registerName("otherEventWithType:location:modifierFlags:timestamp:windowNumber:context:subtype:data1:data2:"); + +class NSAutoreleasePool { + +public: + NSAutoreleasePool() noexcept : + m_id(createPool()) {} + + ~NSAutoreleasePool(){ + release(); + } + + NSAutoreleasePool(const NSAutoreleasePool&) = delete; + NSAutoreleasePool& operator=(const NSAutoreleasePool&) = delete; + + NSAutoreleasePool(NSAutoreleasePool&& o) noexcept : + m_id(o.m_id){ + + o.m_id = nullptr; + } + + NSAutoreleasePool& operator=(NSAutoreleasePool&& o) noexcept{ + if (this != &o){ + release(); + std::swap(m_id, o.m_id); + } + + return *this; + } + + void release() noexcept{ + if (m_id != nullptr){ + objc_msgSend(m_id, MacStatic::g_release); + m_id = nullptr; + } + } + +private: + static ::id createPool() noexcept{ + auto poolId = objc_msgSend(reinterpret_cast<::id>(MacStatic::g_autoreleasePool), MacStatic::g_alloc); + return objc_msgSend(poolId, MacStatic::g_init); + } + + ::id m_id; + +}; + +namespace NSLoop { + +static constexpr ::NSUInteger NSAnyEventMask = std::numeric_limits<::NSUInteger>::max(); +static constexpr ::NSUInteger NSApplicationDefined = 15; + +static void processEvent() noexcept{ + auto event = objc_msgSend(MacStatic::g_app, MacStatic::g_nextEvent, NSAnyEventMask, MacStatic::g_distantFuture, kCFRunLoopDefaultMode, YES); + objc_msgSend(MacStatic::g_app, MacStatic::g_sendEvent, event); +} + +static void postDummy() noexcept{ + auto event = objc_msgSend(reinterpret_cast<::id>(MacStatic::g_event), MacStatic::g_otherEventWithType, NSApplicationDefined, nullptr, 1, 0.0, 0, nullptr, static_cast(0), 0, 0); + objc_msgSend(MacStatic::g_app, MacStatic::g_postEvent, event, NO); +} + +} // namespace NSLoop + +} // namespace Detail + +} // namespace Twpp + +// Linux +#elif defined(__linux__) +# warning "No testing has been done on this platform, this framework might not work correctly." +# define TWPP_DETAIL_OS_LINUX 1 +extern "C" { +# include +} +# define TWPP_DETAIL_CALLSTYLE +namespace Twpp { + +namespace Detail { + +typedef void* RawHandle; + + +namespace DsmLibOs { + +typedef void* Handle; +static constexpr const Handle nullHandle = nullptr; + +template +static inline T resolve(Handle h) noexcept{ + return reinterpret_cast(::dlsym(h, "DSM_Entry")); +} + +static inline Handle load(bool) noexcept{ + return ::dlopen("libtwaindsm.so", RTLD_LAZY); +} + +static inline void unload(Handle h) noexcept{ + ::dlclose(h); +} + +} // namespace DsmLibOs + +} // namespace Detail + +} // namespace Twpp + +// fail everything else +#else +# error "unsupported platform, supports only Windows, Mac OS and Linux" +#endif + + +// ================= +// compiler specific + +// MSVC +#if defined(_MSC_VER) +# define TWPP_DETAIL_PACK_BEGIN \ + __pragma(pack (push, beforeTwpp)) \ + __pragma(pack (2)) +# define TWPP_DETAIL_PACK_END __pragma(pack (pop, beforeTwpp)); + +// GNU or CLang +#elif defined(__GNUC__) || defined(__clang__) +# if defined(TWPP_DETAIL_OS_MAC) +# define TWPP_DETAIL_PACK_BEGIN _Pragma("options align = power") +# define TWPP_DETAIL_PACK_END _Pragma("options align = reset") +# else +# define TWPP_DETAIL_PACK_BEGIN \ + _Pragma("pack (push, beforeTwpp)") \ + _Pragma("pack (2)") +# define TWPP_DETAIL_PACK_END _Pragma("pack (pop, beforeTwpp)") +# endif +# if !defined(TWPP_DETAIL_EXPORT) +# define TWPP_DETAIL_EXPORT __attribute__((__visibility__("default"))) +# endif + +// Borland +#elif defined(__BORLAND__) || defined(__BORLANDC__) || defined(__CODEGEARC__) +# define TWPP_DETAIL_PACK_BEGIN _Pragma("option -a2") +# define TWPP_DETAIL_PACK_END _Pragma("option -a") + +// fail everything else +#else +# error "unsupported compiler, please define your own TWPP_DETAIL_PACK_BEGIN and TWPP_DETAIL_PACK_END and possibly TWPP_DETAIL_EXPORT in twpp/env.hpp and send me your patch" +#endif + + +#if (!defined(_MSC_VER) && __cplusplus < 201103L) || (defined(_MSC_VER) && _MSC_VER < 1900) // msvc2015 +# error "C++11 or later is required" +#endif + + +#endif // TWPP_DETAIL_FILE_ENV_HPP + diff --git a/twpp/event.hpp b/twpp/event.hpp new file mode 100644 index 00000000..1aff32dc --- /dev/null +++ b/twpp/event.hpp @@ -0,0 +1,72 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_EVENT_HPP +#define TWPP_DETAIL_FILE_EVENT_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Loop event on Windows. +/// Used while waiting for transfer. +/// See manual for more info. +class Event { + +public: + constexpr Event() noexcept : + m_event(nullptr), m_msg(Msg::Null){} + + constexpr Event(void* event, Msg msg) noexcept : + m_event(event), m_msg(msg){} + + constexpr void* event() const noexcept{ + return m_event; + } + + void setEvent(void* event) noexcept{ + m_event = event; + } + + constexpr Msg message() const noexcept{ + return m_msg; + } + + void setMessage(Msg msg) noexcept{ + m_msg = msg; + } + +private: + void* m_event; + Msg m_msg; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_EVENT_HPP diff --git a/twpp/exception.hpp b/twpp/exception.hpp new file mode 100644 index 00000000..3aa34dc2 --- /dev/null +++ b/twpp/exception.hpp @@ -0,0 +1,42 @@ +#ifndef TWPP_DETAIL_FILE_EXCEPTION_HPP +#define TWPP_DETAIL_FILE_EXCEPTION_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +/// Base class of TWPP exceptions. +class Exception : public std::exception { + +public: + virtual const char* what() const noexcept override{ + return "General TWPP error."; + } + +}; + +/// Invalid type exception. +/// Used when an invalid or unsupported type identifier is used. +class TypeException : public Exception { + +public: + virtual const char* what() const noexcept override{ + return "Invalid type."; + } + +}; + +/// Value out of valid range exception. +class RangeException : Exception { + +public: + virtual const char* what() const noexcept override{ + return "Value out of allowed range."; + } + +}; + +} + +#endif // TWPP_DETAIL_FILE_EXCEPTION_HPP + diff --git a/twpp/extimageinfo.hpp b/twpp/extimageinfo.hpp new file mode 100644 index 00000000..3fb452f9 --- /dev/null +++ b/twpp/extimageinfo.hpp @@ -0,0 +1,532 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_EXTIMAGEINFO_HPP +#define TWPP_DETAIL_FILE_EXTIMAGEINFO_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +/// Mapping of info type to type identifier and data type. +template struct Ext {}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef BarCodeRotation DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Handle; typedef char DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef BarCodeType DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef PatchCode DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef DeskewStatus DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Frame; typedef Frame DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt16; typedef PixelFlavor DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt16; typedef MagType DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Bool; typedef Bool DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef char DataType;}; // NOTE: InfoId::MagData may also contain Handle +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; +template<> struct Ext {static constexpr const Type twty = Type::UInt16; typedef PageSide DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::UInt32; typedef UInt32 DataType;}; + +template<> struct Ext {static constexpr const Type twty = Type::Str255; typedef Str255 DataType;}; + +} + +class Info; +class ExtImageInfo; + +namespace Detail { + +static Handle handleItem(Info& info) noexcept; + +static void deleteInfo(Info& info) noexcept; + +} + +TWPP_DETAIL_PACK_BEGIN +/// Extended image information entry. +class Info { + + friend class ExtImageInfo; + friend Handle Detail::handleItem(Info& info) noexcept; + friend void Detail::deleteInfo(Info& info) noexcept; + static constexpr const UInt32 DATA_HANDLE_THRESHOLD = sizeof(UIntPtr); // NOTE: specification says 4 bytes, yet pointer size makes more sense + +public: + template + class Items { + + friend class Info; + + public: + typedef Detail::MaybeLock Data; + + constexpr Items() noexcept : + m_parent(nullptr){} + + Items(const Items&) = default; + Items& operator=(const Items&) = default; + + Items(Items&&) = default; + Items& operator=(Items&&) = default; + + operator bool() const noexcept{ + return m_data; + } + + Data at(UInt32 i) const{ + if (m_parent->hasDataHandle() && m_parent->type() == Type::Handle){ + return reinterpret_cast(m_data.data())[i]; + } else { + return reinterpret_cast(m_data.data() + i * typeSize(m_parent->type())); + } + } + + Data operator[](UInt32 i) const{ + return at(i); + } + + private: + Items(Info& parent, Detail::MaybeLock data) noexcept : + m_parent(&parent), m_data(data){} + + Info* m_parent; + Detail::MaybeLock m_data; + // [items] <=> !(big and handle) + // [handles]->handles*[items] <=> big and handle (this should teoretically not happen) + + }; + + Info(const Info&) = delete; + Info& operator=(const Info&) = delete; + + Info(Info&&) = delete; + Info& operator=(Info&&) = delete; + + /// Information type ID. + InfoId id() const noexcept{ + return m_infoId; + } + + /// Information data type ID. + Type type() const noexcept{ + return m_itemType; + } + + /// Number of items in this entry. + UInt16 size() const noexcept{ + return m_numItems; + } + + /// Allocates space for the supplied number of items. + /// Allocating handles is not supported. + /// \tparam id Information type ID. Data types are set accordingly. + /// \param count Number of items to allocate. + /// \throw TypeException When `type` is handle or invalid. + /// \throw std::bad_alloc + template + void allocSimple(UInt16 count = 1){ + allocSimple(Detail::Ext::twty, count); + } + + /// Allocates space for the supplied number of items. + /// Allocating handles is not supported. + /// \param type Data type ID. + /// \param count Number of items to allocate. + /// \throw TypeException When `type` is handle or invalid. + /// \throw std::bad_alloc + void allocSimple(Type type, UInt16 count = 1){ + if (type == Type::Handle){ + throw TypeException(); + } + + if (type == m_itemType && count == m_numItems){ + return; + } + + auto itemSize = typeSize(type); + + bool big = hasDataHandle(type, count); + // [items] <=> !big + // handle->[items] <=> big + + Detail::UniqueHandle newItem; + if (big){ + newItem = Detail::alloc(itemSize * count); + } + + Detail::deleteInfo(*this); + + if (big){ + *Detail::alias_cast(&m_item) = newItem.release(); + } + + m_itemType = type; + m_numItems = count; + } + + /// Allocates a single memory area owned by a handle. + /// Info type changes to handle. + /// \param itemSize Number of bytes to allocate. + /// \throw std::bad_alloc + void allocHandle(UInt32 itemSize){ + // handle->[chars] + auto newItem = Detail::UniqueHandle(Detail::alloc(itemSize)); + + Detail::deleteInfo(*this); + *Detail::alias_cast(&m_item) = newItem.release(); + + m_itemType = Type::Handle; + m_numItems = 1; + } + + /// Status of this entry. + ReturnCode returnCode() const noexcept{ + return m_returnCode; + } + + /// Sets status of this entry. + void setReturnCode(ReturnCode rc) noexcept{ + m_returnCode = rc; + } + + /// Returns items contained in this entry. + /// \tparam type ID of the internal data type. + /// \tparam DataType Exported data type. + /// \throw TypeException When types don't match. + template + Items items(){ + if (type != m_itemType || (type != Type::Handle && typeSize(type) != sizeof(DataType))){ + throw TypeException(); + } + + return itemsPriv(); + } + + /// Returns items contained in this entry. + /// \tparam type ID of the internal data type. + /// \throw TypeException When types don't match. + template + Items::Type> items(){ + if (type != m_itemType){ + throw TypeException(); + } + + return itemsPriv::Type>(); + } + + /// Returns items contained in this entry. + /// \tparam id Information type ID. Data types are set accordingly. + /// \throw TypeException When types don't match. + template + Items::DataType> items(){ + if (Detail::Ext::twty != m_itemType){ + throw TypeException(); + } + + return itemsPriv::DataType>(); + } + +private: + bool hasDataHandle() const{ + return hasDataHandle(type(), size()); + } + + static bool hasDataHandle(Type type, UInt16 size){ + return type != Type::DontCare && size * typeSize(type) > DATA_HANDLE_THRESHOLD; + } + + template + Items itemsPriv(){ + bool big = hasDataHandle(); + bool handle = m_itemType == Type::Handle; + + Detail::MaybeLock lock; + if (!big && !handle){ + lock = Detail::alias_cast(&m_item); + } else { + lock = *Detail::alias_cast(&m_item); + } + + return {*this, std::move(lock)}; + } + + template + static bool arrContains(const T(& arr)[len], const T& val) noexcept{ + for (std::size_t i = 0; i < len; i++){ + if (arr[i] == val){ + return true; + } + } + + return false; + } + + InfoId m_infoId; + Type m_itemType; + UInt16 m_numItems; + ReturnCode m_returnCode; + UIntPtr m_item; + // [items] <=> !big and !handle + // handle->[items] <=> big xor handle + // handle->[handles]->handles*[items] <=> big and handle (this should teoretically not happen) + +}; + +namespace Detail { + +static inline Handle handleItem(Info& info) noexcept{ + return Handle(*Detail::alias_cast(&info.m_item)); +} + +static inline void deleteInfo(Info& info) noexcept{ + bool big = isType(info.type()) && info.hasDataHandle(); + bool handle = info.type() == Type::Handle; + + // [items] <=> !big and !handle + // handle->[items] <=> big xor handle + // handle->[handles]->handles*[items] <=> big and handle (this should teoretically not happen) + + if (big && handle){ + Detail::Lock lock(handleItem(info)); + for (UInt16 i = 0; i < info.size(); i++){ + Detail::free(lock.data()[i]); + } + } + + if (big || handle){ + Detail::free(handleItem(info)); + } +} + +struct ExtImageInfoData { + UInt32 m_numInfos; + Info m_infos[1]; +}; + +} + +TWPP_DETAIL_PACK_END +/// Extended image information. +/// Application sends list of info IDs, +/// source sets their data. +class ExtImageInfo { + +public: + typedef Info* iterator; + typedef const Info* const_iterator; + + /// Creates an invalid object. + ExtImageInfo() noexcept {} + + /// Creates a new structure for all supplied info IDs. + /// Sources must not call this constructor, they + /// are required to fill data in existing instance. + /// \param ids List of requested info IDs to be filled in by the source. + ExtImageInfo(std::initializer_list ids) : + m_data(new char[sizeof(Detail::ExtImageInfoData) - sizeof(Info) + ids.size() * sizeof(Info)]()){ + + d()->m_numInfos = static_cast(ids.size()); + + Info* infos = d()->m_infos; + + UInt32 i = 0; + for (auto id : ids){ + auto& info = infos[i]; + i++; + + info.m_infoId = id; + info.m_itemType = Type::DontCare; + } + } + + ExtImageInfo(ExtImageInfo&&) = default; + ExtImageInfo& operator=(ExtImageInfo&&) = default; + + operator bool() const noexcept{ + return isValid(); + } + + bool isValid() const noexcept{ + return static_cast(m_data); + } + + /// Number of requested entries. + UInt32 size() const noexcept{ + assert(isValid()); + return d()->m_numInfos; + } + + /// Information entry. + Info& at(UInt32 i) noexcept{ + assert(isValid()); + return d()->m_infos[i]; + } + + /// Information entry. + const Info& at(UInt32 i) const noexcept{ + assert(isValid()); + return d()->m_infos[i]; + } + + Info& operator[](UInt32 i) noexcept{ + return at(i); + } + + const Info& operator[](UInt32 i) const noexcept{ + return at(i); + } + + + iterator begin() noexcept{ + assert(isValid()); + return d()->m_infos; + } + + const_iterator begin() const noexcept{ + return cbegin(); + } + + const_iterator cbegin() const noexcept{ + assert(isValid()); + return d()->m_infos; + } + + iterator end() noexcept{ + assert(isValid()); + return d()->m_infos + d()->m_numInfos; + } + + const_iterator end() const noexcept{ + return cend(); + } + + const_iterator cend() const noexcept{ + assert(isValid()); + return d()->m_infos + d()->m_numInfos; + } + +private: + Detail::ExtImageInfoData* d() noexcept{ + return reinterpret_cast(m_data.get()); + } + + Detail::ExtImageInfoData* d() const noexcept{ + return reinterpret_cast(m_data.get()); + } + + struct Deleter { + void operator()(char* ptr) noexcept{ + Detail::ExtImageInfoData* data = reinterpret_cast(ptr); + if (data){ + for (UInt32 i = 0; i < data->m_numInfos; i++){ + Detail::deleteInfo(data->m_infos[i]); + } + + delete [] ptr; + } + } + }; + + std::unique_ptr m_data; + +}; + +} + +#endif // TWPP_DETAIL_FILE_EXTIMAGEINFO_HPP + diff --git a/twpp/filesystem.hpp b/twpp/filesystem.hpp new file mode 100644 index 00000000..b7bbc79d --- /dev/null +++ b/twpp/filesystem.hpp @@ -0,0 +1,248 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_FILESYSTEM_HPP +#define TWPP_DETAIL_FILE_FILESYSTEM_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure representing device filesystem and operations on it. +class FileSystem { + +public: + /// Type of file. + enum class Type : Int32 { + Camera = 0, + CameraTop = 1, + CameraBottom = 2, + CameraPreview = 3, + Domain = 4, + Host = 5, + Directory = 6, + Image = 7, + Unknown = 8 + }; + + /// Creates uninitialized file system. + constexpr FileSystem() noexcept : + m_context(nullptr), m_recursiveBool(), m_fileType(Type::Camera), m_size(), + m_freeSpace(), m_newImageSize(), m_numberOfFiles(), m_numberOfSnippets(), + m_deviceGroupMask(), m_reserved(){} + + /// Creates file system with input and output paths and optional context. + constexpr FileSystem(const Str255& inputPath, const Str255& outputPath, void* context = nullptr) noexcept : + m_inputPath(inputPath), m_outputPath(outputPath), m_context(context), + m_recursiveBool(), m_fileType(Type::Camera), m_size(), m_freeSpace(), m_newImageSize(), + m_numberOfFiles(), m_numberOfSnippets(), m_deviceGroupMask(), m_reserved(){} + + /// Input or source file. + constexpr const Str255& inputPath() const noexcept{ + return m_inputPath; + } + + /// Sets input or source file. + void setInputPath(const Str255& path) noexcept{ + m_inputPath = path; + } + + /// Operation result, or destination file. + constexpr const Str255& outputPath() const noexcept{ + return m_outputPath; + } + + /// Sets operation result, or destination file. + void setOutputPath(const Str255& path) noexcept{ + m_outputPath = path; + } + + /// Source specific context. + constexpr void* context() const noexcept{ + return m_context; + } + + /// Sets source specific context. + void setContext(void* context) noexcept{ + m_context = context; + } + + /// Whether the operation is recursive. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::Delete. + constexpr Bool recursive() const noexcept{ + return m_recursiveBool; + } + + /// Sets whether the operation is recursive. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::Delete. + void setRecursive(Bool recursive) noexcept{ + m_recursiveBool = recursive; + } + + /// File type. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr Type type() const noexcept{ + return m_fileType; + } + + /// Sets file type. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void setType(Type type) noexcept{ + m_fileType = type; + } + + /// Number of bytes of the entry. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr UInt32 size() const noexcept{ + return m_size; + } + + /// Sets number of bytes of the entry. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void setSize(UInt32 size) noexcept{ + m_size = size; + } + + /// Creation date of the file. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + /// YYYY/MM/DD HH:mm:SS:sss + constexpr const Str32& createdTimeDate() const noexcept{ + return m_createdTimeDate; + } + + /// Sets creation date of the file. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + /// YYYY/MM/DD HH:mm:SS:sss + void setCreatedTimeDate(const Str32& val) noexcept{ + m_createdTimeDate = val; + } + + /// Modification date of the file. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + /// YYYY/MM/DD HH:mm:SS:sss + constexpr const Str32& modifiedTimeDate() const noexcept{ + return m_modifiedTimeDate; + } + + /// Sets modification date of the file. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + /// YYYY/MM/DD HH:mm:SS:sss + void setModifiedTimeDate(const Str32& val) noexcept{ + m_modifiedTimeDate = val; + } + + /// Number of bytes left on the device. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr UInt32 freeSpace() const noexcept{ + return m_freeSpace; + } + + /// Sets number of bytes left on the device. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void setFreeSpace(UInt32 freeSpace) noexcept{ + m_freeSpace = freeSpace; + } + + /// Estimated image size in bytes. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr Int32 newImageSize() const noexcept{ + return m_newImageSize; + } + + /// Sets estimated image size in bytes. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void setNewImageSize(Int32 newImageSize) noexcept{ + m_newImageSize = newImageSize; + } + + /// Total number of files including subdirectories. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr UInt32 files() const noexcept{ + return m_numberOfFiles; + } + + /// Sets total number of files including subdirectories. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void setFiles(UInt32 files) noexcept{ + m_numberOfFiles = files; + } + + /// Number of audio snippets. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + constexpr UInt32 snippets() const noexcept{ + return m_numberOfSnippets; + } + + /// Sets number of audio snippets. + /// Valid for Msg::GetInfo, Msg::GetFileFirst and Msg::GetFileNext. + void snippets(UInt32 snippets) noexcept{ + m_numberOfSnippets = snippets; + } + + /// See manual for explanation of this field, `DeviceGroupMask`. + constexpr UInt32 groupMask() const noexcept{ + return m_deviceGroupMask; + } + + /// See manual for explanation of this field, `DeviceGroupMask`. + void groupMask(UInt32 groupMask) noexcept{ + m_deviceGroupMask = groupMask; + } + +private: + void unused() const{ + Detail::unused(m_reserved); + } + + Str255 m_inputPath; + Str255 m_outputPath; + void* m_context; + + // Copy, Delete + union { + int m_recursive; + Bool m_recursiveBool; + }; + + // GetInfo + Type m_fileType; + UInt32 m_size; + Str32 m_createdTimeDate; + Str32 m_modifiedTimeDate; + UInt32 m_freeSpace; + Int32 m_newImageSize; + UInt32 m_numberOfFiles; + UInt32 m_numberOfSnippets; + UInt32 m_deviceGroupMask; + Int8 m_reserved[508]; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_FILESYSTEM_HPP diff --git a/twpp/fix32.hpp b/twpp/fix32.hpp new file mode 100644 index 00000000..fc99b792 --- /dev/null +++ b/twpp/fix32.hpp @@ -0,0 +1,198 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_FIX32_HPP +#define TWPP_DETAIL_FILE_FIX32_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +static constexpr inline Int32 floatToValue(float val){ + return static_cast( + (val >= 0.0f) ? + (val * 65536.0f + 0.5f) : + (val * 65536.0f - 0.5f) + ); +} + +static constexpr inline Int16 floatToWhole(float val){ + return static_cast(floatToValue(val) >> 16); +} + +static constexpr inline UInt16 floatToFrac(float val){ + return static_cast(floatToValue(val) & 0xFFFF); +} + +} + +TWPP_DETAIL_PACK_BEGIN +/// TWAIN fixed point fractional type. +/// The fractional part has resolution of 1/65536. +class Fix32 { + +public: + /// Creates zero-initialized fixed type. + constexpr Fix32() noexcept : + m_whole(0), m_frac(0){} + + /// Creates fixed type from float at compile time if possible. + constexpr Fix32(float value) noexcept : + m_whole(Detail::floatToWhole(value)), m_frac(Detail::floatToFrac(value)){} + + /// Creates fixed type from whole and fractional parts. + /// The fractional part has resolution of 1/65536. + constexpr Fix32(Int16 whole, UInt16 frac) noexcept : + m_whole(whole), m_frac(frac){} + + + /// Whole part of this fixed type. + constexpr Int16 whole() const noexcept{ + return m_whole; + } + + /// Sets whole part of this fixed type. + void setWhole(Int16 whole) noexcept{ + m_whole = whole; + } + + /// Fractional part of this fixed type. + /// Resolution of 1/65536. + constexpr UInt16 frac() const noexcept{ + return m_frac; + } + + /// Sets fractional part of this fixed type. + /// Resolution of 1/65536. + void setFrac(UInt16 frac) noexcept{ + m_frac = frac; + } + + explicit constexpr operator float() const noexcept{ + return m_whole + m_frac / 65536.0f; + } + + constexpr float toFloat() const noexcept{ + return m_whole + m_frac / 65536.0f; + } + + constexpr Fix32 operator-() const noexcept{ + return -toFloat(); + } + +private: + Int16 m_whole; + UInt16 m_frac; + +}; +TWPP_DETAIL_PACK_END + +namespace Detail { + +static inline constexpr Fix32 fix32AddHelper(Int32 frac, Int16 whole){ + return frac < 65536 ? Fix32(whole, frac) : Fix32(whole + 1, frac - 65536); +} + +static inline constexpr Fix32 fix32SubHelper(Int32 frac, Int16 whole){ + return frac >= 0 ? Fix32(whole, frac) : Fix32(whole - 1, frac + 65536); +} + +} + +static inline constexpr bool operator>(Fix32 a, Fix32 b) noexcept{ + return a.whole() > b.whole() || (a.whole() == b.whole() && a.frac() > b.frac()); +} + +static inline constexpr bool operator<(Fix32 a, Fix32 b) noexcept{ + return a.whole() < b.whole() || (a.whole() == b.whole() && a.frac() < b.frac()); +} + +static inline constexpr bool operator>=(Fix32 a, Fix32 b) noexcept{ + return !(a < b); +} + +static inline constexpr bool operator<=(Fix32 a, Fix32 b) noexcept{ + return !(a > b); +} + +static inline constexpr bool operator==(Fix32 a, Fix32 b) noexcept{ + return a.whole() == b.whole() && a.frac() == b.frac(); +} + +static inline constexpr bool operator!=(Fix32 a, Fix32 b) noexcept{ + return !(a == b); +} + +static inline constexpr Fix32 operator+(Fix32 a, Fix32 b) noexcept{ + return Detail::fix32AddHelper(static_cast(a.frac()) + b.frac(), a.whole() + b.whole()); +} + +static inline constexpr Fix32 operator-(Fix32 a, Fix32 b) noexcept{ + return Detail::fix32SubHelper(static_cast(a.frac()) - b.frac(), a.whole() - b.whole()); +} + +static inline constexpr Fix32 operator*(Fix32 a, Fix32 b) noexcept{ + return Fix32(static_cast(a) * static_cast(b)); +} + +static inline constexpr Fix32 operator/(Fix32 a, Fix32 b) noexcept{ // wonder about zero b + return Fix32(static_cast(a) / static_cast(b)); +} + +static inline Fix32& operator+=(Fix32& a, Fix32 b) noexcept{ + return a = a + b; +} + +static inline Fix32& operator-=(Fix32& a, Fix32 b) noexcept{ + return a = a - b; +} + +static inline Fix32& operator*=(Fix32& a, Fix32 b) noexcept{ + return a = a * b; +} + +static inline Fix32& operator/=(Fix32& a, Fix32 b) noexcept{ // wonder about zero b + return a = a / b; +} + +namespace Literals { + +static inline constexpr Fix32 operator "" _fix(long double val) noexcept{ + return Fix32(static_cast(val)); +} + +static inline constexpr Fix32 operator "" _fix(unsigned long long val) noexcept{ + return Fix32(static_cast(val)); +} + +} + +} + +#endif // TWPP_DETAIL_FILE_FIX32_HPP + diff --git a/twpp/frame.hpp b/twpp/frame.hpp new file mode 100644 index 00000000..7c878160 --- /dev/null +++ b/twpp/frame.hpp @@ -0,0 +1,106 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_FRAME_HPP +#define TWPP_DETAIL_FILE_FRAME_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Section of an image to retrieve. +class Frame { + +public: + /// Creates zero-initialized frame. + constexpr Frame() noexcept{} + + /// Creates frame with set top-left and bottom-right corners. + constexpr Frame(Fix32 left, Fix32 top, Fix32 right, Fix32 bottom) noexcept : + m_left(left), m_top(top), m_right(right), m_bottom(bottom){} + + /// Left position of the image frame. + constexpr Fix32 left() const noexcept{ + return m_left; + } + + /// Sets left position of the image frame. + void setLeft(Fix32 left) noexcept{ + m_left = left; + } + + /// Top position of the image frame. + constexpr Fix32 top() const noexcept{ + return m_top; + } + + /// Sets top position of the image frame. + void setTop(Fix32 top) noexcept{ + m_top = top; + } + + /// Right position of the image frame. + constexpr Fix32 right() const noexcept{ + return m_right; + } + + /// Sets right position of the image frame. + void setRight(Fix32 right) noexcept{ + m_right = right; + } + + /// Bottom position of the image frame. + constexpr Fix32 bottom() const noexcept{ + return m_bottom; + } + + /// Sets bottom position of the image frame. + void setBottom(Fix32 bottom) noexcept{ + m_bottom = bottom; + } + +private: + Fix32 m_left; + Fix32 m_top; + Fix32 m_right; + Fix32 m_bottom; + +}; +TWPP_DETAIL_PACK_END + +static constexpr inline bool operator==(const Frame& a, const Frame& b) noexcept{ + return a.left() == b.left() && a.top() == b.top() && a.right() == b.right() && a.bottom() == b.bottom(); +} + +static constexpr inline bool operator!=(const Frame& a, const Frame& b) noexcept{ + return !(a == b); +} + +} + +#endif // TWPP_DETAIL_FILE_FRAME_HPP + diff --git a/twpp/identity.hpp b/twpp/identity.hpp new file mode 100644 index 00000000..b50e9308 --- /dev/null +++ b/twpp/identity.hpp @@ -0,0 +1,247 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_IDENTITY_HPP +#define TWPP_DETAIL_FILE_IDENTITY_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +static constexpr const UInt32 identV2 = TWPP_DETAIL_IS_DS ? Detail::Ds2 : Detail::App2; + +} + +TWPP_DETAIL_PACK_BEGIN +/// Source or application version information. +class Version { + +public: + /// Creates default-initialized version. + constexpr Version() noexcept : + m_majorNum(0), m_minorNum(0), m_language(Language::English), + m_country(Country::UnitedKingdom){} + + /// Creates version initialized with supplied values. + constexpr Version( + UInt16 majorNumber, + UInt16 minorNumber, + Language language, + Country country, + const Str32& info = Str32()) noexcept : + m_majorNum(majorNumber), m_minorNum(minorNumber), m_language(language), + m_country(country), m_info(info){} + + /// Major version number of the source or application. + constexpr UInt16 majorNumber() const noexcept{ + return m_majorNum; + } + + /// Sets major version number of the source or application. + void setMajorNumber(UInt16 major) noexcept{ + m_majorNum = major; + } + + /// Minor version number of the source or application. + constexpr UInt16 minorNumber() const noexcept{ + return m_minorNum; + } + + /// Sets minor version number of the source or application. + void setMinorNumber(UInt16 minor) noexcept{ + m_minorNum = minor; + } + + /// Language of the source or application. + constexpr Language language() const noexcept{ + return m_language; + } + + /// Sets language of the source or application. + void setLanguage(Language language) noexcept{ + m_language = language; + } + + /// Original country of the source or application. + constexpr Country country() const noexcept{ + return m_country; + } + + /// Set original country of the source or application. + void setCountry(Country country) noexcept{ + m_country = country; + } + + /// Additional version information of the source or application. + constexpr const Str32& info() const noexcept{ + return m_info; + } + + /// Sets additional version information of the source or application. + void setInfo(const Str32& info) noexcept{ + m_info = info; + } + +private: + UInt16 m_majorNum; + UInt16 m_minorNum; + Language m_language; + Country m_country; + Str32 m_info; + +}; + +/// Source or application identity. +/// Uniquely identifies an endpoint. +class Identity { + +public: + typedef +#if defined(TWPP_DETAIL_OS_MAC) + void* +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + UInt32 +#else +# error "Identity::Id for your platform here" +#endif + Id; + + /// Creates default-initialized identity. + /// ID is set to zero. + /// TWAIN protocol is always Detail::ProtoMajor and Detail::ProtoMinor. + /// Supported group always contains DG::Control and V2. + constexpr Identity() noexcept : + m_id(), m_protoMaj(Detail::ProtoMajor), m_protoMin(Detail::ProtoMinor), + m_groups(DataGroup::Control | Detail::identV2){} + + /// Creates identity initialized with supplied values. + /// ID is set to zero. + /// TWAIN protocol is always Detail::ProtoMajor and Detail::ProtoMinor. + /// Supported group always contains DG::Control and V2. + constexpr Identity( + const Version& version, + DataGroup group, + const Str32& manufacturer, + const Str32& productFamily, + const Str32& productName) noexcept : + m_id(), m_version(version), m_protoMaj(Detail::ProtoMajor), + m_protoMin(Detail::ProtoMinor), m_groups(DataGroup::Control | group | Detail::identV2), + m_manuf(manufacturer), m_prodFamily(productFamily), m_prodName(productName){} + + /// Creates identity initialized with supplied values. + constexpr Identity( + Id id, + const Version& version, + UInt16 protoMajor, + UInt16 protoMinor, + UInt32 groups, + const Str32& manufacturer, + const Str32& productFamily, + const Str32& productName) noexcept : + m_id(id), m_version(version), m_protoMaj(protoMajor), m_protoMin(protoMinor), + m_groups(groups), m_manuf(manufacturer), m_prodFamily(productFamily), + m_prodName(productName){} + + /// DSM-supplied ID of this identity. + constexpr Id id() const{ + return m_id; + } + + /// Version information. + constexpr const Version& version() const noexcept{ + return m_version; + } + + /// Whether a data group is supported. + constexpr bool supports(DataGroup group) const noexcept{ + return (m_groups & group) != 0; + } + + /// Whether this is V2 application. + constexpr bool isAppV2() const noexcept{ + return (m_groups & Detail::App2) != 0; + } + + /// Whether this is V2 DSM. + constexpr bool isDsmV2() const noexcept{ + return (m_groups & Detail::Dsm2) != 0; + } + + /// Whether this is V2 source. + constexpr bool isDsV2() const noexcept{ + return (m_groups & Detail::Ds2) != 0; + } + + /// The manufacturer. + /// Manufacturer and product name uniquely identify a source. + constexpr const Str32& manufacturer() const noexcept{ + return m_manuf; + } + + /// The product name. + /// Manufacturer and product name uniquely identify a source. + constexpr const Str32& productName() const noexcept{ + return m_prodName; + } + + /// The product family. + constexpr const Str32& productFamily() const noexcept{ + return m_prodFamily; + } + + /// Raw data group flags. + constexpr UInt32 dataGroupsRaw() const noexcept{ + return m_groups; + } + + /// TWAIN protocol major version. + constexpr UInt16 protocolMajor() const noexcept{ + return m_protoMaj; + } + + /// TWAIN protocol minor version. + constexpr UInt16 protocolMinor() const noexcept{ + return m_protoMin; + } + +private: + Id m_id; + Version m_version; + UInt16 m_protoMaj; + UInt16 m_protoMin; + UInt32 m_groups; + Str32 m_manuf; + Str32 m_prodFamily; + Str32 m_prodName; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_IDENTITY_HPP diff --git a/twpp/imageinfo.hpp b/twpp/imageinfo.hpp new file mode 100644 index 00000000..78cbf84d --- /dev/null +++ b/twpp/imageinfo.hpp @@ -0,0 +1,190 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_IMAGEINFO_HPP +#define TWPP_DETAIL_FILE_IMAGEINFO_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Contains information about transfered image. +class ImageInfo { + + typedef Detail::FixedArray BitsPerSampleImpl; + +public: + typedef Int16 BitsPerSample[8]; + + /// Creates zero-initialized info. + constexpr ImageInfo() noexcept : + m_imgWidth(0), m_imgHeight(0), m_spp(0), m_bps(), m_bpp(0), + m_planar(0), m_pixelType(PixelType::BlackWhite), m_compression(Compression::None){} + + /// Creates info with supplied values. + template + constexpr ImageInfo( + Fix32 xResolution, + Fix32 yResolution, + Int32 width, + Int32 height, + Int16 samplesPerPixel, + const Int16(& bitsPerSample)[inputSize], + Int16 bitsPerPixel, + Bool planar, + PixelType pixelType, + Compression compression + ) noexcept : + m_xres(xResolution), m_yres(yResolution), m_imgWidth(width), m_imgHeight(height), + m_spp(samplesPerPixel), m_bps(bitsPerSample), m_bpp(bitsPerPixel), m_planar(planar), + m_pixelType(pixelType), m_compression(compression){} + + /// X-axis resolution of the image. + constexpr Fix32 xResolution() const noexcept{ + return m_xres; + } + + /// Sets x-axis resolution of the image. + void setXResolution(Fix32 xres) noexcept{ + m_xres = xres; + } + + /// Y-axis resolution of the image. + constexpr Fix32 yResolution() const noexcept{ + return m_yres; + } + + /// Sets y-axis resolution of the image. + void setYResolution(Fix32 yres) noexcept{ + m_yres = yres; + } + + /// Image width in pixels. + constexpr Int32 width() const noexcept{ + return m_imgWidth; + } + + /// Sets image width in pixels. + void setWidth(Int32 width) noexcept{ + m_imgWidth = width; + } + + /// Image height in pixels. + constexpr Int32 height() const noexcept{ + return m_imgHeight; + } + + /// Sets image height in pixels. + void setHeight(Int32 height) noexcept{ + m_imgHeight = height; + } + + /// Samples per single pixel. + constexpr Int16 samplesPerPixel() const noexcept{ + return m_spp; + } + + /// Sets samples per single pixel. + void setSamplesPerPixel(Int16 spp) noexcept{ + m_spp = spp; + } + + /// Array of bits per sample. + /// Contains `samplesPerPixel` entries. + constexpr const BitsPerSample& bitsPerSample() const noexcept{ + return m_bps.array(); + } + + /// Array of bits per sample. + /// Contains `samplesPerPixel` entries. + BitsPerSample& bitsPerSample() noexcept{ + return m_bps.array(); + } + + /// Total number of bits per pixel. + /// This should be true: bitsPerPixel = SUM[i=0..samplesPerPixel-1](bitsPerSample[i]) + constexpr Int16 bitsPerPixel() const noexcept{ + return m_bpp; + } + + /// Sets total number of bits per pixel. + /// This should be true: bitsPerPixel = SUM[i=0..samplesPerPixel-1](bitsPerSample[i]) + void setBitsPerPixel(Int16 bpp) noexcept{ + m_bpp = bpp; + } + + /// Whether the image is planar (consists of several sample planes) or is chunky + /// (samples are transferes in one plane and are interlaced). + constexpr Bool planar() const noexcept{ + return m_planar; + } + + /// Sets whether the image is planar (consists of several sample planes) or is chunky + /// (samples are transferes in one plane and are interlaced). + void setPlanar(Bool planar) noexcept{ + m_planar = planar; + } + + /// The type of image. + constexpr PixelType pixelType() const noexcept{ + return m_pixelType; + } + + /// Sets the type of image. + void setPixelType(PixelType pixelType) noexcept{ + m_pixelType = pixelType; + } + + /// Image compression. + constexpr Compression compression() const noexcept{ + return m_compression; + } + + /// Sets image compression. + void compression(Compression compression) noexcept{ + m_compression = compression; + } + +private: + Fix32 m_xres; + Fix32 m_yres; + Int32 m_imgWidth; + Int32 m_imgHeight; + Int16 m_spp; + BitsPerSampleImpl m_bps; + Int16 m_bpp; + Bool m_planar; + PixelType m_pixelType; + Compression m_compression; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_IMAGEINFO_HPP + diff --git a/twpp/imagelayout.hpp b/twpp/imagelayout.hpp new file mode 100644 index 00000000..c61eb5b9 --- /dev/null +++ b/twpp/imagelayout.hpp @@ -0,0 +1,100 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_IMAGELAYOUT_HPP +#define TWPP_DETAIL_FILE_IMAGELAYOUT_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Provides image size and its position on the scanner and information about order of the image. +class ImageLayout { + +public: + /// Creates layout. + constexpr ImageLayout( + const Frame& frame = Frame(), + UInt32 documentNumber = 1, + UInt32 pageNumber = 1, + UInt32 frameNumber = 1 + ) noexcept : + m_frame(frame), m_docNumber(documentNumber), + m_pageNumber(pageNumber), m_frameNumber(frameNumber){} + + /// The image frame. + constexpr const Frame& frame() const noexcept{ + return m_frame; + } + + /// Sets the image frame. + void setFrame(const Frame& frame) noexcept{ + m_frame = frame; + } + + /// Number of the document, set by source. + constexpr UInt32 documentNumber() const noexcept{ + return m_docNumber; + } + + /// Sets number of the document. + void setDocumentNumber(UInt32 documentNumber) noexcept{ + m_docNumber = documentNumber; + } + + /// Number of the page, set by source. + constexpr UInt32 pageNumber() const noexcept{ + return m_pageNumber; + } + + /// Sets number of the page. + void setPageNumber(UInt32 pageNumber) noexcept{ + m_pageNumber = pageNumber; + } + + /// Number of the frame, set by source. + constexpr UInt32 frameNumber() const noexcept{ + return m_frameNumber; + } + + /// Sets number of the frame. + void setFrameNumber(UInt32 frameNumber) noexcept{ + m_frameNumber = frameNumber; + } + +private: + Frame m_frame; + UInt32 m_docNumber; + UInt32 m_pageNumber; + UInt32 m_frameNumber; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_IMAGELAYOUT_HPP diff --git a/twpp/imagememxfer.hpp b/twpp/imagememxfer.hpp new file mode 100644 index 00000000..2be7a3a4 --- /dev/null +++ b/twpp/imagememxfer.hpp @@ -0,0 +1,207 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_IMAGEMEMXFER_HPP +#define TWPP_DETAIL_FILE_IMAGEMEMXFER_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +namespace Detail { + +/// Structure holding the information and data of memory and memory file transfers. +class ImageMemXferImpl { + +public: + /// Creates a zero-initialized structure without any memory. + ImageMemXferImpl() noexcept : + m_compression(Compression::None), m_bytesPerRow(0), m_columns(0), m_rows(0), + m_xoff(0), m_yoff(0), m_bytesWritten(0){} + + /// Creates an initialized structure from the supplied values and memory. + /// The ownership of the memory is taken over. + ImageMemXferImpl( + Compression compression, + UInt32 bytesPerRow, + UInt32 columns, + UInt32 rows, + UInt32 xOffset, + UInt32 yOffset, + UInt32 bytesWritten, + Memory memory + ) noexcept : + m_compression(compression), m_bytesPerRow(bytesPerRow), + m_columns(columns), m_rows(rows), m_xoff(xOffset), m_yoff(yOffset), + m_bytesWritten(bytesWritten), m_memory(std::move(memory)){} + + /// Compression used in the transfer. + Compression compression() const noexcept{ + return m_compression; + } + + /// Sets compression used in the transfer. + void setCompression(Compression compression) noexcept{ + m_compression = compression; + } + + /// Number of bytes per single row. + UInt32 bytesPerRow() const noexcept{ + return m_bytesPerRow; + } + + /// Sets number of bytes per single row. + void setBytesPerRow(UInt32 bytesPerRow) noexcept{ + m_bytesPerRow = bytesPerRow; + } + + /// Number of columns in the transfer. + UInt32 columns() const noexcept{ + return m_columns; + } + + /// Sets number of columns in the transfer. + void setColumns(UInt32 columns) noexcept{ + m_columns = columns; + } + + /// Number of rows in the transfer. + UInt32 rows() const noexcept{ + return m_rows; + } + + /// Sets number of rows in the transfer. + void setRows(UInt32 rows) noexcept{ + m_rows = rows; + } + + /// X offset from top-left corner in pixels of the image data in the transfer. + UInt32 xOffset() const noexcept{ + return m_xoff; + } + + /// Sets X offset from top-left corner in pixels of the image data in the transfer. + void setXOffset(UInt32 xOffset) noexcept{ + m_xoff = xOffset; + } + + /// Y offset from top-left corner in pixels of the image data in the transfer. + UInt32 yOffset() const noexcept{ + return m_yoff; + } + + /// Sets Y offset from top-left corner in pixels of the image data in the transfer. + void setYOffset(UInt32 yOffset) noexcept{ + m_yoff = yOffset; + } + + /// Number of bytes in this transfer, always contains whole rows or tiles. + UInt32 bytesWritten() const noexcept{ + return m_bytesWritten; + } + + /// Sets number of bytes in this transfer. + void setBytesWritten(UInt32 bytesWritten) noexcept{ + m_bytesWritten = bytesWritten; + } + + /// Contained memory structure. + const Memory& memory() const noexcept{ + return m_memory; + } + + /// Contained memory structure. + Memory& memory() noexcept{ + return m_memory; + } + +private: + Compression m_compression; + UInt32 m_bytesPerRow; + UInt32 m_columns; + UInt32 m_rows; + UInt32 m_xoff; + UInt32 m_yoff; + UInt32 m_bytesWritten; + Memory m_memory; + +}; + +} + +/// Structure holding the information and data of memory transfer. +class ImageMemXfer : public Detail::ImageMemXferImpl { + +public: + /// Creates a zero-initialized structure without any memory. + ImageMemXfer() noexcept : Detail::ImageMemXferImpl(){} + + /// Creates an initialized structure from the supplied values and memory. + /// The ownership of the memory is taken over. + ImageMemXfer( + Compression compression, + UInt32 bytesPerRow, + UInt32 columns, + UInt32 rows, + UInt32 xOffset, + UInt32 yOffset, + UInt32 bytesWritten, + Memory memory + ) noexcept : Detail::ImageMemXferImpl( + compression, bytesPerRow, columns, rows, xOffset, + yOffset, bytesWritten, std::move(memory)){} + +}; + +/// Structure holding the information and data of memory file transfer. +class ImageMemFileXfer : public Detail::ImageMemXferImpl { + +public: + /// Creates a zero-initialized structure without any memory. + ImageMemFileXfer() noexcept : Detail::ImageMemXferImpl(){} + + /// Creates an initialized structure from the supplied values and memory. + /// The ownership of the memory is taken over. + ImageMemFileXfer( + Compression compression, + UInt32 bytesPerRow, + UInt32 columns, + UInt32 rows, + UInt32 xOffset, + UInt32 yOffset, + UInt32 bytesWritten, + Memory memory + ) noexcept : Detail::ImageMemXferImpl( + compression, bytesPerRow, columns, rows, xOffset, + yOffset, bytesWritten, std::move(memory)){} + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_IMAGEMEMXFER_HPP diff --git a/twpp/imagenativexfer.hpp b/twpp/imagenativexfer.hpp new file mode 100644 index 00000000..c47a045f --- /dev/null +++ b/twpp/imagenativexfer.hpp @@ -0,0 +1,98 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_IMAGENATIVEXFER_HPP +#define TWPP_DETAIL_FILE_IMAGENATIVEXFER_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure holding native transfer image handle. +class ImageNativeXfer { + +public: + template + using Data = Detail::Lock::type>; + + template + using ConstData = Detail::Lock::type>; + + + /// Creates empty, invalid native transfer. + ImageNativeXfer() noexcept : + m_handle(){} + + /// Creates a new ImageNativeXfer object from a handle. + /// The ownership of the handle is taken over. + explicit ImageNativeXfer(Handle h) : + m_handle(h){} + + /// Creates uninitialized native image with defines size in bytes. + /// \throw std::bad_alloc + explicit ImageNativeXfer(UInt32 size) : + m_handle(Detail::alloc(size)){} + + /// Data of this native transfer. + /// Actual type depends on system and source. + /// Windows sources use BMP format without file header, version varies. + /// Linux uses TIFF, version varies. + /// Mac uses QuickDraw Picture. + template + Data data() noexcept{ + return m_handle.lock::type>(); + } + + /// Data of this native transfer. + /// Actual type depends on system and source. + /// Windows sources use BMP format without file header, version varies. + /// Linux uses TIFF, version varies. + /// Mac uses QuickDraw Picture. + template + ConstData data() const noexcept{ + return m_handle.lock::type>(); + } + + operator bool() const noexcept{ + return m_handle; + } + + /// Releases the contained handle, making user responsible for freeing it. + Handle release() noexcept{ + return m_handle.release(); + } + +private: + Detail::UniqueHandle m_handle; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_IMAGENATIVEXFER_HPP + diff --git a/twpp/internal.hpp b/twpp/internal.hpp new file mode 100644 index 00000000..8abe3602 --- /dev/null +++ b/twpp/internal.hpp @@ -0,0 +1,158 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_INTERNAL_HPP +#define TWPP_DETAIL_FILE_INTERNAL_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +struct AudioFileXfer {}; +struct ImageFileXfer {}; +typedef Memory IccProfileMemory; + +namespace Detail { + +typedef ReturnCode (TWPP_DETAIL_CALLSTYLE* DsmEntry)( + Identity* origin, + Identity* dest, + DataGroup dg, + Dat dat, + Msg msg, + void* data +); + +typedef DsmEntry CallBackFunc; + +typedef +#if defined(TWPP_DETAIL_OS_MAC) +void* +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) +UInt32 +#else +# error "CallBackConstant for your platform here" +#endif +CallBackConstant; + + +TWPP_DETAIL_PACK_BEGIN +struct EntryPoint { + constexpr EntryPoint() noexcept : + m_size(sizeof(EntryPoint)), m_entry(nullptr), m_alloc(nullptr), + m_free(nullptr), m_lock(nullptr), m_unlock(nullptr){} + + UInt32 m_size; + DsmEntry m_entry; + MemAlloc m_alloc; + MemFree m_free; + MemLock m_lock; + MemUnlock m_unlock; +}; + +struct CallBack { + + constexpr CallBack(CallBackFunc func, CallBackConstant constant, Msg msg) noexcept : + m_func(func), m_constant(constant), m_msg(msg){} + + CallBackFunc m_func; + CallBackConstant m_constant; + Msg m_msg; + +}; + +struct CallBack2 { + + constexpr CallBack2(CallBackFunc func, UIntPtr constant, Msg msg) noexcept : + m_func(func), m_constant(constant), m_msg(msg){} + + CallBackFunc m_func; + UIntPtr m_constant; + Msg m_msg; +}; +TWPP_DETAIL_PACK_END + +/// Manages DSM dll/so/framework connection. +class DsmLib { + +public: + constexpr DsmLib() noexcept : + m_handle(DsmLibOs::nullHandle){} + + ~DsmLib(){ + unload(); + } + + DsmLib(const DsmLib&) = delete; + DsmLib& operator=(const DsmLib&) = delete; + + DsmLib(DsmLib&& o) noexcept : + m_handle(o.m_handle){ + + o.m_handle = DsmLibOs::nullHandle; + } + + DsmLib& operator=(DsmLib&& o) noexcept{ + if (&o != this){ + unload(); + + m_handle = o.m_handle; + o.m_handle = DsmLibOs::nullHandle; + } + + return *this; + } + + operator bool() const noexcept{ + return m_handle != DsmLibOs::nullHandle; + } + + bool load(bool preferOld = false) noexcept{ + m_handle = DsmLibOs::load(preferOld); + return m_handle != DsmLibOs::nullHandle; + } + + void unload() noexcept{ + if (m_handle != DsmLibOs::nullHandle){ + DsmLibOs::unload(m_handle); + m_handle = DsmLibOs::nullHandle; + } + } + + DsmEntry resolve() const noexcept{ + return DsmLibOs::resolve(m_handle); + } + +private: + DsmLibOs::Handle m_handle; + +}; + +} + +} + +#endif // TWPP_DETAIL_FILE_INTERNAL_HPP diff --git a/twpp/jpegcompression.hpp b/twpp/jpegcompression.hpp new file mode 100644 index 00000000..b42a1764 --- /dev/null +++ b/twpp/jpegcompression.hpp @@ -0,0 +1,173 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_JPEGCOMPRESSION_HPP +#define TWPP_DETAIL_FILE_JPEGCOMPRESSION_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// See manual for more info. +class JpegCompression { + +public: + typedef UInt16 UInt16Arr4[4]; + typedef Memory MemoryArr2[2]; + typedef Memory MemoryArr4[4]; + + JpegCompression() noexcept : + m_colorSpace(PixelType::BlackWhite), m_subSampling(0x10001000), m_components(0), + m_restartFrequency(0), m_quantMap(), m_huffmanMap(){} + + template< + std::size_t quantTableMapSize, + std::size_t quantTableSize, + std::size_t huffmanTableMapSize, + std::size_t huffmanDcSize, + std::size_t huffmanAcSize + > + JpegCompression( + PixelType colorSpace, + UInt32 subSampling, + UInt16 components, + UInt16 restartFrequency, + const UInt16(& quantTableMap)[quantTableMapSize], + Memory(& quantTable)[quantTableSize], + const UInt16(& huffmanTableMap)[huffmanTableMapSize], + Memory(& huffmanDc)[huffmanDcSize], + Memory(& huffmanAc)[huffmanAcSize] + ) noexcept : + m_colorSpace(colorSpace), + m_subSampling(subSampling), + m_components(components), + m_restartFrequency(restartFrequency), + m_quantMap(quantTableMap), + m_huffmanMap(huffmanTableMap){ + + for (std::size_t i = 0; i < quantTableSize; i++){ + m_quantTable[i] = std::move(quantTable[i]); + } + + for (std::size_t i = 0; i < huffmanDcSize; i++){ + m_huffmanDc[i] = std::move(huffmanDc[i]); + } + + for (std::size_t i = 0; i < huffmanAcSize; i++){ + m_huffmanAc[i] = std::move(huffmanAc[i]); + } + } + + PixelType pixelType() const noexcept{ + return m_colorSpace; + } + + void setPixelType(PixelType pixelType) noexcept{ + m_colorSpace = pixelType; + } + + UInt32 subSampling() const noexcept{ + return m_subSampling; + } + + void setSubSampling(UInt32 subSampling) noexcept{ + m_subSampling = subSampling; + } + + UInt16 components() const noexcept{ + return m_components; + } + + void setComponents(UInt16 components) noexcept{ + m_components = components; + } + + UInt16 restartFrequency() const noexcept{ + return m_restartFrequency; + } + + void setRestartFrequency(UInt16 restartFrequency) noexcept{ + m_restartFrequency = restartFrequency; + } + + const UInt16Arr4& quantTableMap() const noexcept{ + return m_quantMap.array(); + } + + UInt16Arr4& quantTableMap() noexcept{ + return m_quantMap.array(); + } + + const MemoryArr4& quantTable() const noexcept{ + return m_quantTable; + } + + MemoryArr4& quantTable() noexcept{ + return m_quantTable; + } + + const UInt16Arr4& huffmanTableMap() const noexcept{ + return m_huffmanMap.array(); + } + + UInt16Arr4& huffmanTableMap() noexcept{ + return m_huffmanMap.array(); + } + + const MemoryArr2& huffmanDc() const noexcept{ + return m_huffmanDc; + } + + MemoryArr2& huffmanDc() noexcept{ + return m_huffmanDc; + } + + const MemoryArr2& huffmanAc() const noexcept{ + return m_huffmanAc; + } + + MemoryArr2& huffmanAc() noexcept{ + return m_huffmanAc; + } + +private: + PixelType m_colorSpace; + UInt32 m_subSampling; + UInt16 m_components; + UInt16 m_restartFrequency; + Detail::FixedArray m_quantMap; + MemoryArr4 m_quantTable; + Detail::FixedArray m_huffmanMap; + MemoryArr2 m_huffmanDc; + MemoryArr2 m_huffmanAc; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_JPEGCOMPRESSION_HPP diff --git a/twpp/memory.hpp b/twpp/memory.hpp new file mode 100644 index 00000000..63859b13 --- /dev/null +++ b/twpp/memory.hpp @@ -0,0 +1,194 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_MEMORY_HPP +#define TWPP_DETAIL_FILE_MEMORY_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +namespace Flags { + +enum { + AppOwns = 0x0001, + DsmOwns = 0x0002, + DsOwns = 0x0004, + Pointer = 0x0008, + Handle = 0x0010 +}; + + +#if !defined(TWPP_IS_DS) +static constexpr const UInt32 thisOwns = AppOwns; +static constexpr const UInt32 otherOwns = DsOwns; +#else +static constexpr const UInt32 thisOwns = DsOwns; +static constexpr const UInt32 otherOwns = AppOwns; +#endif + +} + +} + +TWPP_DETAIL_PACK_BEGIN +/// Holds and potentially owns a block of memory using either pointer or handle. +class Memory { + +public: + typedef Detail::MaybeLock Data; + typedef Detail::MaybeLock ConstData; + + /// Creates an empty memory. + constexpr Memory() noexcept : + m_flags(0), m_size(0), m_data(nullptr){} + + /// Creates a memory block of supplied size. + /// \throw std::bad_alloc + explicit Memory(UInt32 size) : + m_flags(Detail::Flags::thisOwns | Detail::Flags::Handle), m_size(size), + m_data(Detail::alloc(size).raw()){} + + /// Creates a new memory object from Handle. + /// The memory ownership is taken over. + /// \param h The handle, see thisOwns for more information about memory ownership. + /// \param size Size of the memory in bytes, that handle h manages. + /// \param thisOwns { + /// If true, this object frees the memory once it goes out of scope. + /// + /// If false the memory is not freed, and MUST be passed to the other side + /// (APP->DS or DS->APP) of the connection, that will free it. + /// } + Memory(Handle h, UInt32 size, bool thisOwns = true) noexcept : + m_flags((thisOwns ? Detail::Flags::thisOwns : Detail::Flags::otherOwns) | Detail::Flags::Handle), + m_size(size), + m_data(h.raw()){} + + /// Creates a memory object from container. + /// The memory object does NOT take over the ownership of the data. + /// Make sure the container is destroyed after the memory object is. + template + explicit Memory(const Container& container) noexcept : + m_flags(Detail::Flags::thisOwns | Detail::Flags::Pointer), + m_size(sizeof(Container::value_type) * container.size()), + m_data(container.data()){} + + /// Creates a memory object from pointer. + /// The memory object does NOT take over the ownership of the data. + /// Make sure the data is destroyed after the memory object is. + constexpr Memory(void* data, UInt32 size) noexcept : + m_flags(Detail::Flags::thisOwns | Detail::Flags::Pointer), m_size(size), + m_data(data){} + + ~Memory(){ + freePriv(); + } + + Memory(const Memory& o) = delete; + Memory& operator=(const Memory& o) = delete; + + Memory(Memory&& o) noexcept : + m_flags(o.m_flags), m_size(o.m_size), m_data(o.m_data) + { + o.m_flags = 0; + o.m_size = 0; + o.m_data = nullptr; + } + + Memory& operator=(Memory&& o) noexcept{ + if (&o != this){ + freePriv(); + + m_flags = o.m_flags; + m_size = o.m_size; + m_data = o.m_data; + + o.m_flags = 0; + o.m_size = 0; + o.m_data = nullptr; + } + + return *this; + } + + /// The data in this memory block. + ConstData data() const noexcept{ + return m_flags & Detail::Flags::Handle ? + ConstData(Handle(static_cast(m_data))) : + ConstData(static_cast(m_data)); + } + + /// The data in this memory block. + Data data() noexcept{ + return m_flags & Detail::Flags::Handle ? + Data(Handle(static_cast(m_data))) : + Data(static_cast(m_data)); + } + + /// Number of bytes in the memory block. + UInt32 size() const noexcept{ + return m_size; + } + + /// In case of handle, frees memory regardless its owner; does nothing otherwise (pointer). + /// Potentially unsafe operation. + void free(){ + if (m_flags & Detail::Flags::Handle){ + Handle h(static_cast(m_data)); + if (h){ + Detail::free(h); + } + + m_size = 0; + m_data = nullptr; + m_flags = 0; + } + } + +private: + void freePriv(){ + if (m_flags & Detail::Flags::thisOwns){ + if (m_flags & Detail::Flags::Handle){ + Detail::free(Handle(static_cast(m_data))); + } + } + } + + UInt32 m_flags; + UInt32 m_size; + void* m_data; + +}; +TWPP_DETAIL_PACK_END + + + +} + +#endif // TWPP_DETAIL_FILE_MEMORY_HPP + diff --git a/twpp/memoryops.hpp b/twpp/memoryops.hpp new file mode 100644 index 00000000..abf499a4 --- /dev/null +++ b/twpp/memoryops.hpp @@ -0,0 +1,439 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_MEMORYOPS_HPP +#define TWPP_DETAIL_FILE_MEMORYOPS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +extern "C" { + +typedef Handle::Raw (TWPP_DETAIL_CALLSTYLE* MemAlloc)(UInt32 size); +typedef void (TWPP_DETAIL_CALLSTYLE* MemFree)(Handle::Raw handle); +typedef void* (TWPP_DETAIL_CALLSTYLE* MemLock)(Handle::Raw handle); +typedef void (TWPP_DETAIL_CALLSTYLE* MemUnlock)(Handle::Raw handle); + +} + +// templates behave as if they were defined in at most one module +// ideal for storing static data +template +struct GlobalMemFuncs { + +#if defined(TWPP_DETAIL_OS_WIN) + static Handle::Raw TWPP_DETAIL_CALLSTYLE defAlloc(UInt32 size){ + return ::GlobalAlloc(GHND, size); + } + + static void TWPP_DETAIL_CALLSTYLE defFree(Handle::Raw handle){ + ::GlobalFree(handle); + } + + static void* TWPP_DETAIL_CALLSTYLE defLock(Handle::Raw handle){ + return ::GlobalLock(handle); + } + + static void TWPP_DETAIL_CALLSTYLE defUnlock(Handle::Raw handle){ + ::GlobalUnlock(handle); + } +#elif defined(TWPP_DETAIL_OS_MAC) + static Handle::Raw TWPP_DETAIL_CALLSTYLE defAlloc(UInt32 size){ + return ::NewHandle(size); + } + + static void TWPP_DETAIL_CALLSTYLE defFree(Handle::Raw handle){ + ::DisposeHandle(handle); + } + + static void* TWPP_DETAIL_CALLSTYLE defLock(Handle::Raw handle){ + return *handle; + } + + static void TWPP_DETAIL_CALLSTYLE defUnlock(Handle::Raw){ + // noop + } +#elif !defined(TWPP_DETAIL_OS_LINUX) // Linux doesnt need default functions +# error "default memory functions for your platform here" +#endif + + static MemAlloc alloc; + static MemFree free; + static MemLock lock; + static MemUnlock unlock; + +#if defined(TWPP_IS_DS) + static Handle doNotFreeHandle; +#endif + +}; + +#if defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_MAC) +template +MemAlloc GlobalMemFuncs::alloc = GlobalMemFuncs::defAlloc; + +template +MemFree GlobalMemFuncs::free = GlobalMemFuncs::defFree; + +template +MemLock GlobalMemFuncs::lock = GlobalMemFuncs::defLock; + +template +MemUnlock GlobalMemFuncs::unlock = GlobalMemFuncs::defUnlock; +#elif defined(TWPP_DETAIL_OS_LINUX) +template +MemAlloc GlobalMemFuncs::alloc = nullptr; + +template +MemFree GlobalMemFuncs::free = nullptr; + +template +MemLock GlobalMemFuncs::lock = nullptr; + +template +MemUnlock GlobalMemFuncs::unlock = nullptr; +#else +# error "default memory functions setup for your platform here" +#endif + +#if defined(TWPP_IS_DS) + template + Handle GlobalMemFuncs::doNotFreeHandle; +#endif + +inline static void setMemFuncs(MemAlloc alloc, MemFree free, MemLock lock, MemUnlock unlock) noexcept{ + GlobalMemFuncs::alloc = alloc; + GlobalMemFuncs::free = free; + GlobalMemFuncs::lock = lock; + GlobalMemFuncs::unlock = unlock; +} + +inline static void resetMemFuncs() noexcept{ +#if defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_MAC) + GlobalMemFuncs::alloc = GlobalMemFuncs::defAlloc; + GlobalMemFuncs::free = GlobalMemFuncs::defFree; + GlobalMemFuncs::lock = GlobalMemFuncs::defLock; + GlobalMemFuncs::unlock = GlobalMemFuncs::defUnlock; +#elif defined(TWPP_DETAIL_OS_LINUX) + GlobalMemFuncs::alloc = nullptr; + GlobalMemFuncs::free = nullptr; + GlobalMemFuncs::lock = nullptr; + GlobalMemFuncs::unlock = nullptr; +#else +# error "resetMemFuncs for your platform here" +#endif +} + +inline static Handle alloc(UInt32 size){ + auto h = GlobalMemFuncs::alloc(size); + if (!h){ + throw std::bad_alloc(); + } + + return Handle(h); +} + +inline static void* lock(Handle handle) noexcept{ + return GlobalMemFuncs::lock(handle.raw()); +} + +inline static void unlock(Handle handle) noexcept{ + GlobalMemFuncs::unlock(handle.raw()); +} + +inline static void free(Handle handle) noexcept{ + GlobalMemFuncs::free(handle.raw()); +} + +template +static inline T* typeLock(Handle handle) noexcept{ + return static_cast(lock(handle)); +} + +/// A lock that can contain either handle or raw pointer. +/// Locks and unlocks handle, noop for pointer. +template +class MaybeLock { + +public: + constexpr MaybeLock() noexcept : + m_handle(), m_pointer(nullptr){} + + MaybeLock(Handle h) noexcept : + m_handle(h), m_pointer(typeLock(h)){} + + constexpr MaybeLock(T* ptr) noexcept : + m_handle(), m_pointer(ptr){} + + ~MaybeLock(){ + unlock(); + } + + MaybeLock(const MaybeLock& o) noexcept : + m_handle(o.m_handle), m_pointer(o.m_handle ? typeLock(o.m_handle) : o.m_pointer){} + + MaybeLock& operator=(const MaybeLock& o) noexcept{ + if (&o != this){ + unlock(); + + m_handle = o.m_handle; + m_pointer = m_handle ? typeLock(m_handle) : o.m_pointer; + } + + return *this; + } + + + MaybeLock(MaybeLock&& o) noexcept : + m_handle(o.m_handle), m_pointer(o.m_pointer){ + + o.m_handle = Handle(); + o.m_pointer = nullptr; + } + + MaybeLock& operator=(MaybeLock&& o) noexcept{ + if (&o != this){ + unlock(); + + m_handle = o.m_handle; + m_pointer = o.m_pointer; + + o.m_handle = Handle(); + o.m_pointer = nullptr; + } + + return *this; + } + + T* data() const noexcept{ + return m_pointer; + } + + operator T*() const noexcept{ + return m_pointer; + } + + T* operator->() noexcept{ + return m_pointer; + } + + T* operator->() const noexcept{ + return m_pointer; + } + + bool hasData() const noexcept{ + return m_pointer; + } + + operator bool() const noexcept{ + return m_pointer; + } + +private: + void unlock() noexcept{ + if (m_handle){ + Detail::unlock(m_handle); + } + } + + Handle m_handle; + T* m_pointer; + +}; + +/// Simple handle lock. +/// Locks on creation and unlocks on destruction. +template +class Lock { + +public: + constexpr Lock() noexcept : + m_handle(), m_pointer(nullptr){} + + Lock(Handle h) noexcept : + m_handle(h), m_pointer(typeLock(h)){} + + ~Lock(){ + unlock(); + } + + + Lock(const Lock& o) noexcept : + m_handle(o.m_handle), m_pointer(typeLock(o.m_handle)){} + + Lock& operator=(const Lock& o) noexcept{ + if (&o != this){ + unlock(); + + m_handle = o.m_handle; + m_pointer = typeLock(m_handle); + } + + return *this; + } + + + Lock(Lock&& o) noexcept : + m_handle(o.m_handle), m_pointer(o.m_pointer){ + + o.m_handle = Handle(); + o.m_pointer = nullptr; + } + + Lock& operator=(Lock&& o) noexcept{ + if (&o != this){ + unlock(); + + m_handle = o.m_handle; + m_pointer = o.m_pointer; + + o.m_handle = Handle(); + o.m_pointer = nullptr; + } + + return *this; + } + + + T* data() const noexcept{ + return m_pointer; + } + + operator T*() const noexcept{ + return m_pointer; + } + + T* operator->() noexcept{ + return m_pointer; + } + + T* operator->() const noexcept{ + return m_pointer; + } + + bool hasData() const noexcept{ + return m_pointer; + } + + operator bool() const noexcept{ + return m_pointer; + } + +private: + void unlock() noexcept{ + if (m_handle){ + Detail::unlock(m_handle); + } + } + + Handle m_handle; + T* m_pointer; + +}; + +/// Owns a handle and frees it upon destruction, +/// unless `release` is called beforehand. +class UniqueHandle { + +public: + constexpr UniqueHandle(Handle h = Handle()) noexcept : + m_handle(h){} + + ~UniqueHandle(){ + free(); + } + + UniqueHandle(const UniqueHandle&) = delete; + UniqueHandle& operator=(const UniqueHandle&) = delete; + + UniqueHandle(UniqueHandle&& o) noexcept : + m_handle(o.m_handle){ + + o.m_handle = Handle(); + } + + UniqueHandle& operator=(UniqueHandle&& o) noexcept{ + if (&o != this){ + free(); + + m_handle = o.m_handle; + + o.m_handle = Handle(); + } + + return *this; + } + + operator bool() const noexcept{ + return m_handle; + } + + /// The contained handle. + Handle get() noexcept{ + return m_handle; + } + + /// The contained handle. + Handle get() const noexcept{ + return m_handle; + } + + /// Releases the contained handle, making the user responsible for freeing it. + Handle release() noexcept{ + Handle ret = m_handle; + m_handle = Handle(); + return ret; + } + + template + Lock lock() const{ + return m_handle; + } + +private: + void free() noexcept{ +#if defined(TWPP_IS_DS) + if (m_handle && m_handle != GlobalMemFuncs::doNotFreeHandle){ +#else + if (m_handle){ +#endif + Detail::free(m_handle); + } + } + + Handle m_handle; + +}; + +} + +} + +#endif // TWPP_DETAIL_FILE_MEMORYOPS_HPP + diff --git a/twpp/palette8.hpp b/twpp/palette8.hpp new file mode 100644 index 00000000..71a05bcc --- /dev/null +++ b/twpp/palette8.hpp @@ -0,0 +1,145 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_PALETTE8_HPP +#define TWPP_DETAIL_FILE_PALETTE8_HPP + +#include "../twpp.hpp" + + +namespace Twpp { + +namespace Detail { + +// specialization for Element8 +// we also want to set index of the element when placing it inside array +template +struct FixedArrayData > { + + static constexpr Element8 updateIndex(UInt8 index, const Element8& e) noexcept{ + return Element8(index, e.channel1(), e.channel2(), e.channel3()); + } + + template + constexpr FixedArrayData(const Element8(& arr)[inputSize]) noexcept : + m_arr{updateIndex(i, FixedArrayFlat(arr)[i])...}{} + + constexpr FixedArrayData() noexcept : + m_arr{Element8(i)...}{} + + Element8 m_arr[arraySize]; + +}; + +} + + +TWPP_DETAIL_PACK_BEGIN +/// Palette information for memory transfers +class Palette8 { + +public: + enum class Type : UInt16 { + Rgb = 0, + Gray = 1, + Cmy = 2 + }; + + typedef Element8 Element8Arr256[256]; + + /// Creates an uninitialized palette. + constexpr Palette8() noexcept : + m_size(0), m_type(Type::Rgb), m_colors(){} + + /// Creates a palette with the supplied type and elements. + template + constexpr Palette8(Type type, const Element8(& colors)[inputSize]) noexcept : + m_size(inputSize), m_type(type), + m_colors(colors){ + + static_assert(inputSize <= 256, "too many colors"); + } + + /// Creates a palette with the supplied type and elements from container. + /// \throw RangeException When there are more than 256 colors. + template + Palette8(Type type, const Container& colors) : + m_size(static_cast(colors.size())), m_type(type){ + + if (colors.size() > 256){ + throw RangeException(); + } + + auto& array = m_colors.array(); + for (UInt16 i = 0; i < m_size; i++){ + array[i] = colors[i]; + array[i].setIndex(i); + } + } + + /// Creates a palette with the supplied type and elements. + /// \throw RangeException When there are more than 256 colors. + Palette8(Type type, const Element8* colors, UInt16 size) : + m_size(size), m_type(type){ + + if (m_size > 256){ + throw RangeException(); + } + + auto& array = m_colors.array(); + for (UInt16 i = 0; i < m_size; i++){ + array[i] = colors[i]; + array[i].setIndex(static_cast(i)); // 0..255 max + } + } + + /// Number of elements in the palette. + constexpr UInt16 size() const noexcept{ + return m_size; + } + + /// Type of palette data. + constexpr Type type() const noexcept{ + return m_type; + } + + /// Array of palette elements. + constexpr const Element8Arr256& colors() const noexcept{ + return m_colors.array(); + } + +private: + UInt16 m_size; + Type m_type; + Detail::FixedArray m_colors; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_PALETTE8_HPP + diff --git a/twpp/passthrough.hpp b/twpp/passthrough.hpp new file mode 100644 index 00000000..49c33fd7 --- /dev/null +++ b/twpp/passthrough.hpp @@ -0,0 +1,126 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_PASSTHROUGH_HPP +#define TWPP_DETAIL_FILE_PASSTHROUGH_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure for raw comminication with device in source. +/// See manual for more information, DAT_PASSTHRU, MSG_PASSTHRU. +class PassThrough { + +public: + enum class Direction : Int32 { + Get = 1, + Set = 2 + }; + + constexpr PassThrough( + void* command, + UInt32 commandSize, + Direction direction, + void* data, + UInt32 dataSize, + UInt32 dataXfered + ) noexcept : + m_cmd(command), m_cmdSize(commandSize), + m_direction(direction), + m_data(data), m_dataSize(dataSize), m_dataXfered(dataXfered){} + + constexpr void* command() const noexcept{ + return m_cmd; + } + + constexpr UInt32 commandSize() const noexcept{ + return m_cmdSize; + } + + template + void setCommand(const Container& command) noexcept{ + m_cmd = command.data(); + m_cmdSize = sizeof(Container::value_type) * command.size(); + } + + void setCommand(void* command, UInt32 size) noexcept{ + m_cmd = command; + m_cmdSize = size; + } + + constexpr Direction direction() const noexcept{ + return m_direction; + } + + void setDirection(Direction direction) noexcept{ + m_direction = direction; + } + + constexpr void* data() const noexcept{ + return m_data; + } + + constexpr UInt32 dataSize() const noexcept{ + return m_dataSize; + } + + template + void setData(const Container& data) noexcept{ + m_data = data.data(); + m_dataSize = sizeof(Container::value_type) * data.size(); + m_dataXfered = 0; + } + + void setData(void* data, UInt32 dataSize) noexcept{ + m_data = data; + m_dataSize = dataSize; + m_dataXfered = 0; + } + + constexpr UInt32 dataXfered() const noexcept{ + return m_dataXfered; + } + + void setDataXfered(Int32 dataXfered) noexcept{ + m_dataXfered = dataXfered; + } + +private: + void* m_cmd; + UInt32 m_cmdSize; + Direction m_direction; + void* m_data; + UInt32 m_dataSize; + UInt32 m_dataXfered; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_PASSTHROUGH_HPP diff --git a/twpp/pendingxfers.hpp b/twpp/pendingxfers.hpp new file mode 100644 index 00000000..9ba875b7 --- /dev/null +++ b/twpp/pendingxfers.hpp @@ -0,0 +1,86 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_PENDINGXFERS_HPP +#define TWPP_DETAIL_FILE_PENDINGXFERS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Reports number of pending images, transfers. +class PendingXfers { + +public: + /// Job control settings. + enum class JobPatch : UInt32 { + None = 0x0000, + MidSeparator = 0x0001, + P1 = 0x0002, + P2 = 0x0003, + P3 = 0x0004, + P4 = 0x0005, + P6 = 0x0006, + PT = 0x0007 + }; + + /// Creates object to report number of pending transfers. + /// \param count Number of pending transfers. + /// \param patch Job control settings. + constexpr PendingXfers(UInt16 count = 0, JobPatch patch = JobPatch::None) noexcept : + m_count(count), m_eoj(patch){} + + /// Number of pending images/transfers. + constexpr UInt16 count() const noexcept{ + return m_count; + } + + /// Sets number of pending images/transfers. + void setCount(UInt16 count) noexcept{ + m_count = count; + } + + /// Job control settings. + constexpr JobPatch jobPatch() const noexcept{ + return m_eoj; + } + + /// Sets job control settings. + void setJobPatch(JobPatch eoj) noexcept{ + m_eoj = eoj; + } + +private: + UInt16 m_count; + JobPatch m_eoj; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_PENDINGXFERS_HPP diff --git a/twpp/setupfilexfer.hpp b/twpp/setupfilexfer.hpp new file mode 100644 index 00000000..f4a4a2f3 --- /dev/null +++ b/twpp/setupfilexfer.hpp @@ -0,0 +1,103 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_SETUPFILEXFER_HPP +#define TWPP_DETAIL_FILE_SETUPFILEXFER_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure for setting up file transfer. +class SetupFileXfer { + +public: + /// Creates zero-initialized instance. + constexpr SetupFileXfer() noexcept : + m_format(ImageFileFormat::Tiff), m_volRefNum(0){} + + /// Creates instance with set file path and format. + /// And volume reference number on Mac OS. + /// \param filePath Path to transfered file. + /// \param format File format. + /// \param vrn Volume reference number. Mac OS only. + constexpr SetupFileXfer( + const Str255& filePath, + ImageFileFormat format, + Int16 vrn +#if defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + = -1 +#elif !defined(TWPP_DETAIL_OS_MAC) +# error "Volume reference number for your platform here" +#endif + ) noexcept : + m_filePath(filePath), m_format(format), + m_volRefNum(vrn){} + + /// Path to transfered file. + constexpr const Str255& filePath() const noexcept{ + return m_filePath; + } + + /// Sets path to transfered file. + void setFilePath(const Str255& filePath) noexcept{ + m_filePath = filePath; + } + + /// Format of the transfered file. + constexpr ImageFileFormat format() const noexcept{ + return m_format; + } + + /// Sets format of the transfered file. + void setFormat(ImageFileFormat format) noexcept{ + m_format = format; + } + + /// Volume reference number. + /// Mac OS only. + constexpr Int16 volumeReferenceNumber() const noexcept{ + return m_volRefNum; + } + + /// Sets volume reference number. + /// Mac OS only. + void setVolumeReferenceNumber(Int16 volumeReferenceNumber) noexcept{ + m_volRefNum = volumeReferenceNumber; + } + +private: + Str255 m_filePath; + ImageFileFormat m_format; + Int16 m_volRefNum; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_SETUPFILEXFER_HPP diff --git a/twpp/setupmemxfer.hpp b/twpp/setupmemxfer.hpp new file mode 100644 index 00000000..e645f685 --- /dev/null +++ b/twpp/setupmemxfer.hpp @@ -0,0 +1,92 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_SETUPMEMXFER_HPP +#define TWPP_DETAIL_FILE_SETUPMEMXFER_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure for setting up memory transfer. +class SetupMemXfer { + +public: + /// Creates zero-initialized instance. + constexpr SetupMemXfer() noexcept : + m_minSize(0), m_maxSize(0), m_prefSize(0){} + + /// Creates an initialized instance with set minimal, maximal and preferred sizes. + /// Must be true, or the behaviour is undefined: minSize <= preferredSize <= maxSize + constexpr SetupMemXfer( + UInt32 minSize, + UInt32 maxSize, + UInt32 preferredSize + ) noexcept : + m_minSize(minSize), m_maxSize(maxSize), m_prefSize(preferredSize){} + + /// Minimal supported buffer size in bytes. + constexpr UInt32 minSize() const noexcept{ + return m_minSize; + } + + /// Sets minimal supported buffer size in bytes. + void setMinSize(UInt32 minSize) noexcept{ + m_minSize = minSize; + } + + /// Maximal supported buffer size in bytes. + constexpr UInt32 maxSize() const noexcept{ + return m_maxSize; + } + + /// Sets maximal supported buffer size in bytes. + void setMaxSize(UInt32 maxSize) noexcept{ + m_maxSize = maxSize; + } + + /// Preferred buffer size in bytes. + constexpr UInt32 preferredSize() const noexcept{ + return m_prefSize; + } + + /// Sets preferred buffer size in bytes. + void setPreferredSize(UInt32 prefSize) noexcept{ + m_prefSize = prefSize; + } + +private: + UInt32 m_minSize; + UInt32 m_maxSize; + UInt32 m_prefSize; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_SETUPMEMXFER_HPP diff --git a/twpp/status.hpp b/twpp/status.hpp new file mode 100644 index 00000000..7d72a5f2 --- /dev/null +++ b/twpp/status.hpp @@ -0,0 +1,230 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_STATUS_HPP +#define TWPP_DETAIL_FILE_STATUS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Additional status information about a performed TWAIN operation. +class Status { + +public: + /// Creates operation status. + /// \param cond Status condition code. + /// \param data Additional status data, source-specific. + constexpr Status(CC cond = CC::Success, UInt16 data = 0) noexcept : + m_cond(cond), m_data(data){} + + /// Status condition code. + constexpr CC condition() const noexcept{ + return m_cond; + } + + /// Sets status condition code. + void setCondition(CC cc) noexcept{ + m_cond = cc; + } + + /// Aditional status data, source-specific. + constexpr UInt16 data() const noexcept{ + return m_data; + } + + /// Sets aditional status data, source-specific. + void setData(UInt16 data) noexcept{ + m_data = data; + } + + constexpr operator CC() const noexcept{ + return m_cond; + } + + constexpr operator bool() const noexcept{ + return success(m_cond); + } + + constexpr bool operator==(CC o) const noexcept{return m_cond == o;} + constexpr bool operator!=(CC o) const noexcept{return m_cond != o;} + + constexpr bool operator==(Status o) const noexcept{return m_cond == o.m_cond && m_data == o.m_data;} + constexpr bool operator!=(Status o) const noexcept{return m_cond != o.m_cond || m_data != o.m_data;} + + +private: + CC m_cond; + UInt16 m_data; + +}; + +static inline constexpr bool success(Status stat) noexcept{ + return stat; +} + +/// Structure for translating status to UTF8 text. +class StatusUtf8 { + +public: + typedef Detail::Lock ConstString; + + + /// Creates a status utf8 without string data. + StatusUtf8(Status status = Status()) noexcept : + m_status(status), m_size(0), m_string(){} + + /// Creates a status utf8 containing copy of string data. + /// The string must be null-terminated. + /// \tparam inputSize Size of the string including null terminator. + /// \param str The string, must be null-terminated. + /// \throw std::bad_alloc + template + StatusUtf8(Status status, const char(& str)[inputSize]) : + m_status(status), m_size(inputSize), m_string(Detail::alloc(inputSize)){ + + std::copy(str, str + inputSize, string().data()); + } + + /// Creates a new status utf8 containing a copy of the supplied string. + /// \param status + /// \param str Utf-8 string to copy, must be null-terminated. + /// \throw RangeException When string is too long, could not insert null terminator. + /// \throw std::bad_alloc + StatusUtf8(Status status, const char* str) : + m_status(status), m_size(0), m_string(){ + + auto len = strlen(str); + if (len >= std::numeric_limits::max()){ + throw RangeException(); + } + + m_size = static_cast(len) + 1; + m_string = Detail::alloc(m_size); + std::copy(str, str + len + 1, m_string.lock().data()); + } + + /// Creates a new status utf8 containing a copy of the supplied string. + /// \param status + /// \param str Utf-8 string to copy. + /// \throw RangeException When string is too long, could not insert null terminator. + /// \throw std::bad_alloc + StatusUtf8(Status status, const std::string& str) : + m_status(status), m_size(0), m_string(){ + + auto len = str.length(); + if (len >= std::numeric_limits::max()){ + throw RangeException(); + } + + m_size = static_cast(len) + 1; + m_string = Detail::alloc(m_size); + + auto lock = m_string.lock(); + std::copy(str.cbegin(), str.cend(), lock.data()); + lock[len] = '\0'; + } + + /// Creates a new StatusUtf8 containing a copy of the supplied string. + /// \param status + /// \param str Utf-8 string to copy, null terminator is not required. + /// \param strSize {Number of bytes to copy including null terminator. + /// Null terminator is inserted automatically.} + /// \throw RangeException When string is too short to satisfy the requested size. + /// \throw std::bad_alloc + StatusUtf8(Status status, const char* str, UInt32 strSize) : + m_status(status), m_size(0), m_string(){ + + auto len = strlen(str); + if (len < strSize){ + throw RangeException(); + } + + m_size = static_cast(strSize) + 1; + m_string = Detail::alloc(m_size); + + auto lock = m_string.lock(); + std::copy(str, str + strSize, lock.data()); + lock[strSize] = '\0'; + } + + StatusUtf8(const StatusUtf8&) = delete; + StatusUtf8& operator=(const StatusUtf8&) = delete; + + StatusUtf8(StatusUtf8&& o) noexcept : + m_status(o.m_status), m_size(o.m_size), m_string(std::move(o.m_string)){ + + o.m_status = Status(); + o.m_size = 0; + } + + StatusUtf8& operator=(StatusUtf8&& o) noexcept{ + if (&o != this){ + m_status = o.m_status; + m_size = o.m_size; + m_string = std::move(o.m_string); + + o.m_status = Status(); + o.m_size = 0; + } + + return *this; + } + + /// Returns the interpreted status. + Status status() const noexcept{ + return m_status; + } + + /// Sets the status to be interpreted. + void setStatus(Status status) noexcept{ + m_status = status; + } + + /// Returns the total number of bytes including null byte. + UInt32 size() const noexcept{ + return m_string ? m_size : 0; + } + + /// The UTF8 string itself. + ConstString string() const noexcept{ + return m_string.lock(); + } + +private: + Status m_status; + UInt32 m_size; + Detail::UniqueHandle m_string; + +}; + +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_STATUS_HPP + diff --git a/twpp/strings.hpp b/twpp/strings.hpp new file mode 100644 index 00000000..86984022 --- /dev/null +++ b/twpp/strings.hpp @@ -0,0 +1,310 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_STRINGS_HPP +#define TWPP_DETAIL_FILE_STRINGS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +// specialization for twain strings +// on mac os, these strings do not contain null terminator +// instead, the first byte contains the length +template +struct FixedArrayData > { + + template + constexpr FixedArrayData(const char(& arr)[inputSize]) noexcept : + m_arr{ +#if defined(TWPP_DETAIL_OS_MAC) + unsignedToSigned(inputSize - 1), +#elif !defined(TWPP_DETAIL_OS_WIN) && !defined(TWPP_DETAIL_OS_LINUX) +# error "string data setup for yout platform here" +#endif + FixedArrayFlat(arr)[i]... + }{} + + constexpr FixedArrayData() noexcept : + m_arr(){} + + char m_arr[arraySize]; + +}; + +// specialization for twain strings +// on mac os, these strings do not contain null terminator +// instead, the first byte contains the length +// so we provide one less index for the fixed array +// on windows, its element is zero-initialized due to it not being specified +// on mac os, the first byte contains the length, so the index is not used anyway +template +struct FixedArray : public FixedArrayData::Result> { + + typedef FixedArrayData::Result> ParentType; + typedef char Array[arraySize]; + + constexpr FixedArray() noexcept : + ParentType(){} + + template + constexpr FixedArray(const char(& arr)[inputSize]) noexcept : + ParentType(arr){ + + static_assert(inputSize <= arraySize, "string literal is too long"); + } + + constexpr const Array& array() const noexcept{ + return ParentType::m_arr; + } + + Array& array() noexcept{ + return ParentType::m_arr; + } + +}; + +/// TWAIN string template. +/// \tparam arraySize String capacity, including either null byte, or length byte (Mac OS). +template +class Str : private FixedArray{ + + typedef FixedArray DataType; + +public: + typedef const char* const_iterator; + typedef char* iterator; + + /// Maximal number of characters this string may hold. + /// Excluding null byte (length byte). + static constexpr UInt32 maxSize() noexcept{ + return arraySize - 1; + } + + static_assert(maxSize() <= std::numeric_limits::max(), "string type exceeds allowed sizes"); + + + /// Creates an empty, zero-initialized string. + constexpr Str() noexcept{} + + /// Creates a compile-time string from string literal (or char array). + /// \tparam inputSize Size of the string literal including null terminator. + /// \param str The string literal. + template + constexpr Str(const char(& str)[inputSize]) noexcept : + DataType(str){ + + static_assert(inputSize <= arraySize, "string literal is too long"); + } + + /// Alias to length(). + constexpr UInt32 size() const noexcept{ + return length(); + } + + /// Length of the string (number of 8-bit characters). + /// O(1) on Mac OS, O(n) anywhere else. + constexpr UInt32 length() const noexcept{ +#if defined(TWPP_DETAIL_OS_MAC) + return static_cast(this->array()[0]); +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + return strLen(data()); +#else +# error "String::length for your platform here" +#endif + } + + /// Pointer to constant data. + /// On Mac OS, the data is NOT null-terminated, + /// and points to the first character after size byte. + /// This operation is unsafe, and its use may not be platform-independent. + constexpr const char* data() const noexcept{ +#if defined(TWPP_DETAIL_OS_MAC) + return this->array() + 1; +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + return this->array(); +#else +# error "String::data for your platform here" +#endif + } + + /// Pointer to data. + /// On Mac OS, the data is NOT null-terminated, + /// and points to the first character after size byte. + /// This operation is unsafe, and its use may not be platform-independent. + char* data() noexcept{ +#if defined(TWPP_DETAIL_OS_MAC) + return this->array() + 1; +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + return this->array(); +#else +# error "String::data for your platform here" +#endif + } + + /// Sets string data. + /// Copies as much data as possible, discarding the rest. + /// The data needn't be null terminated. + /// \param str Data to copy. + /// \param size Maximal number of bytes to copy. + /// \return Number of bytes copied - the new length of this string. + UInt32 setData(const char* data, UInt32 size) noexcept{ + char* arr = this->data(); + UInt32 i = 0; + + auto maxLen = std::min(maxSize(), size); + for ( ; i < maxLen && *data; i++, data++){ + arr[i] = *data; + } + +#if defined(TWPP_DETAIL_OS_MAC) + *reinterpret_cast(this->array()) = static_cast(i); +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + arr[i] = '\0'; +#else +# error "String::setData for your platform here" +#endif + + return i; + } + + /// Sets string data. + /// Copies as much data as possible, discarding the rest. + /// The string must be null terminated. + /// \param str String to copy. + /// \return Number of characters copied - the new length of this string. + UInt32 setData(const char* str) noexcept{ + return setData(str, maxSize()); + } + + /// Sets string data from container (e.g. std::string). + /// Copies as much data as possible, discarding the rest. + /// The string needn't be null terminated. + /// \tparam Contaier Container type. + /// \param cont Container with data to be copied. + /// \return Number of characters copied - the new length of this string. + template::value>::type> + UInt32 setData(const Container& cont) noexcept{ + return setData(cont.data(), static_cast(std::min(cont.size(), maxSize()))); + } + + char operator[](UInt32 i) const noexcept{ + return data()[i]; + } + + char& operator[](UInt32 i) noexcept{ + return data()[i]; + } + + iterator begin() noexcept{ + return data(); + } + + constexpr const_iterator begin() const noexcept{ + return cbegin(); + } + + constexpr const_iterator cbegin() const noexcept{ + return data(); + } + + iterator end() noexcept{ + return data() + length(); + } + + constexpr const_iterator end() const noexcept{ + return cend(); + } + + constexpr const_iterator cend() const noexcept{ + return data() + length(); + } + + std::string string() const{ + return std::string(cbegin(), cend()); + } + +}; + +} + +template +constexpr bool operator==(const Detail::Str& a, const Detail::Str& b) noexcept{ + // length() is O(1) on mac os, O(n) anywhere else +#if defined(TWPP_DETAIL_OS_MAC) + return a.length() == b.length() && Detail::strCmp(a.data(), b.data()) == 0; +#elif defined(TWPP_DETAIL_OS_WIN) || defined(TWPP_DETAIL_OS_LINUX) + return Detail::strCmp(a.data(), b.data()) == 0; +#else +# error "String equals operator for your platform here" +#endif + +} + +template +constexpr bool operator<(const Detail::Str& a, const Detail::Str& b) noexcept{ + return Detail::strCmp(a.data(), b.data()) < 0; +} + +template +constexpr bool operator>(const Detail::Str& a, const Detail::Str& b) noexcept{ + return Detail::strCmp(a.data(), b.data()) > 0; +} + +template +constexpr bool operator!=(const Detail::Str& a, const Detail::Str& b) noexcept{ + return !(a == b); +} + +template +constexpr bool operator<=(const Detail::Str& a, const Detail::Str& b) noexcept{ + return !(a > b); +} + +template +constexpr bool operator>=(const Detail::Str& a, const Detail::Str& b) noexcept{ + return !(a < b); +} + +/// TWAIN string that can contain up to 33 characters (bytes). +typedef Detail::Str<34> Str32; + +/// TWAIN string that can contain up to 65 characters (bytes). +typedef Detail::Str<66> Str64; + +/// TWAIN string that can contain up to 129 characters (bytes). +typedef Detail::Str<130> Str128; + +/// TWAIN string that can contain up to 255 characters (bytes). +typedef Detail::Str<256> Str255; + +} + + +#endif // TWPP_DETAIL_FILE_STRINGS_HPP + diff --git a/twpp/types.hpp b/twpp/types.hpp new file mode 100644 index 00000000..ef01d754 --- /dev/null +++ b/twpp/types.hpp @@ -0,0 +1,88 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_TYPES_HPP +#define TWPP_DETAIL_FILE_TYPES_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +typedef std::uintptr_t UIntPtr; +typedef std::uint8_t UInt8; +typedef std::uint16_t UInt16; +typedef std::uint32_t UInt32; +typedef std::int8_t Int8; +typedef std::int16_t Int16; +typedef std::int32_t Int32; + +/// Boolean value. +/// Implemented as a class to provide better type safety. +class Bool { + +public: + constexpr Bool(bool value = false) noexcept : + m_value(value){} + + constexpr operator bool() const noexcept{ + return m_value != 0; + } + +private: + Int16 m_value; + +}; + +/// Handle to memory area. +/// Implemented as a class to provide better type safety. +class Handle { + +public: + typedef Detail::RawHandle Raw; + + constexpr explicit Handle(Raw raw = Raw()) noexcept : + m_raw(raw){} + + /// Underlying OS-dependent handle. + constexpr Raw raw() const noexcept{ + return m_raw; + } + + constexpr operator bool() const noexcept{ + return m_raw != Raw(); + } + +private: + Raw m_raw; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_TYPES_HPP + diff --git a/twpp/typesops.hpp b/twpp/typesops.hpp new file mode 100644 index 00000000..3c187fdb --- /dev/null +++ b/twpp/typesops.hpp @@ -0,0 +1,149 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_TYPESOPS_HPP +#define TWPP_DETAIL_FILE_TYPESOPS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +/// Enumeration representing basic types. +enum class Type : UInt16 { + DontCare = 0xFFFF, + Int8 = 0x0000, + Int16 = 0x0001, + Int32 = 0x0002, + UInt8 = 0x0003, + UInt16 = 0x0004, + UInt32 = 0x0005, + Bool = 0x0006, + Fix32 = 0x0007, + Frame = 0x0008, + Str32 = 0x0009, + Str64 = 0x000a, + Str128 = 0x000b, + Str255 = 0x000c, + Handle = 0x000f +}; + +/// Whether the enum value actually is a type, DontCare is not a type. +static inline bool isType(Type type){ + switch (type){ + case Type::Int8: + case Type::UInt8: + case Type::Int16: + case Type::UInt16: + case Type::Int32: + case Type::UInt32: + case Type::Bool: + case Type::Fix32: + case Type::Str32: + case Type::Str64: + case Type::Str128: + case Type::Str255: + case Type::Frame: + case Type::Handle: + return true; + + default: + return false; + } +} + +/// Size in bytes of a type represented by enum value. +static inline UInt32 typeSize(Type type){ + switch (type){ + case Type::Int8: return sizeof(Int8); + case Type::UInt8: return sizeof(UInt8); + case Type::Int16: return sizeof(Int16); + case Type::UInt16: return sizeof(UInt16); + case Type::Int32: return sizeof(Int32); + case Type::UInt32: return sizeof(UInt32); + case Type::Bool: return sizeof(Bool); + case Type::Fix32: return sizeof(Fix32); + case Type::Str32: return sizeof(Str32); + case Type::Str64: return sizeof(Str64); + case Type::Str128: return sizeof(Str128); + case Type::Str255: return sizeof(Str255); + case Type::Frame: return sizeof(Frame); + case Type::Handle: return sizeof(Handle); + default: throw TypeException(); + } +} + +namespace Detail { + +/// Conversion from Type enum to actual data type. +template struct Twty {}; +template<> struct Twty {typedef Int8 Type;}; +template<> struct Twty {typedef Int16 Type;}; +template<> struct Twty {typedef Int32 Type;}; +template<> struct Twty {typedef UInt8 Type;}; +template<> struct Twty {typedef UInt16 Type;}; +template<> struct Twty {typedef UInt32 Type;}; +template<> struct Twty {typedef Bool Type;}; +template<> struct Twty {typedef Fix32 Type;}; +template<> struct Twty {typedef Frame Type;}; +template<> struct Twty {typedef Str32 Type;}; +template<> struct Twty {typedef Str64 Type;}; +template<> struct Twty {typedef Str128 Type;}; +template<> struct Twty {typedef Str255 Type;}; +template<> struct Twty {typedef Handle Type;}; + + +// Conversion from data type to Type enum helpers. +template struct Tytw; + +template // true +struct TytwHelper : Tytw::type> {}; + +template +struct TytwHelper {}; + +/// Conversion from data type to Type enum. +template struct Tytw : TytwHelper::value> {}; +template<> struct Tytw {static constexpr const Type twty = Type::Int8;}; +template<> struct Tytw {static constexpr const Type twty = Type::Int16;}; +template<> struct Tytw {static constexpr const Type twty = Type::Int32;}; +template<> struct Tytw {static constexpr const Type twty = Type::UInt8;}; +template<> struct Tytw {static constexpr const Type twty = Type::UInt16;}; +template<> struct Tytw {static constexpr const Type twty = Type::UInt32;}; +template<> struct Tytw {static constexpr const Type twty = Type::Bool;}; +template<> struct Tytw {static constexpr const Type twty = Type::Fix32;}; +template<> struct Tytw {static constexpr const Type twty = Type::Frame;}; +template<> struct Tytw {static constexpr const Type twty = Type::Str32;}; +template<> struct Tytw {static constexpr const Type twty = Type::Str64;}; +template<> struct Tytw {static constexpr const Type twty = Type::Str128;}; +template<> struct Tytw {static constexpr const Type twty = Type::Str255;}; +template<> struct Tytw {static constexpr const Type twty = Type::Handle;}; + +} + +} + +#endif // TWPP_DETAIL_FILE_TYPESOPS_HPP + diff --git a/twpp/userinterface.hpp b/twpp/userinterface.hpp new file mode 100644 index 00000000..ba42bcd0 --- /dev/null +++ b/twpp/userinterface.hpp @@ -0,0 +1,79 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015-2017 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_USERINTERFACE_HPP +#define TWPP_DETAIL_FILE_USERINTERFACE_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +TWPP_DETAIL_PACK_BEGIN +/// Structure holding parameters for enabling or disabling data source. +class UserInterface { + +public: + /// Creates a new UserInterface. + /// \param showUi Whether to show internal DS GUI. Disabling DS GUI might not be supported. + /// \param modalUi Whether DS GUI should be modal. Not used on Linux. Might not be supported on Windows. + /// \param parent Windows-only, others set to null. Handle to parent window. This object does NOT take ownership. +#if defined(TWPP_DETAIL_OS_WIN) + constexpr UserInterface(Bool showUi, Bool modalUi, Handle parent) noexcept : + m_showUi(showUi), m_modalUi(modalUi), m_parent(parent){} +#elif defined(TWPP_DETAIL_OS_MAC) || defined(TWPP_DETAIL_OS_LINUX) + constexpr UserInterface(Bool showUi, Bool modalUi, Handle parent = Handle()) noexcept : + m_showUi(showUi), m_modalUi(modalUi), m_parent(parent){} +#else +# error "UserInterface constructor for your platform here" +#endif + + /// Whether to show internal DS GUI. + constexpr Bool showUi() const noexcept{ + return m_showUi; + } + + /// Whether DS GUI should be modal + constexpr Bool modalUi() const noexcept{ + return m_modalUi; + } + + /// Handle to parent window. + constexpr Handle parent() const noexcept{ + return m_parent; + } + +private: + Bool m_showUi; + Bool m_modalUi; + Handle m_parent; + +}; +TWPP_DETAIL_PACK_END + +} + +#endif // TWPP_DETAIL_FILE_USERINTERFACE_HPP + diff --git a/twpp/utils.hpp b/twpp/utils.hpp new file mode 100644 index 00000000..04ea4b58 --- /dev/null +++ b/twpp/utils.hpp @@ -0,0 +1,482 @@ +/* + +The MIT License (MIT) + +Copyright (c) 2015 Martin Richter + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +*/ + +#ifndef TWPP_DETAIL_FILE_UTILS_HPP +#define TWPP_DETAIL_FILE_UTILS_HPP + +#include "../twpp.hpp" + +namespace Twpp { + +namespace Detail { + +/// Creates a template for testing whether a class contains public static method. +/// Use this macro anywhere a class may be defined, and pass method name +/// as its parameter. Then use `HasStaticMethod_` template. +/// +/// E. g.: +/// TWPP_DETAIL_CREATE_HAS_STATIC_METHOD(myMethod) // <- semicolon not required +/// HasStaticMethod_myMethod::value +/// +/// This test whether `MyClass` has static method `void MyClass::myMethod(int, char)`. +/// That is whether you may do this: +/// MyClass::myMethod(10, 'a'); +#define TWPP_DETAIL_CREATE_HAS_STATIC_METHOD(methodName) \ + template\ + class HasStaticMethod_ ## methodName;\ + \ + template\ + class HasStaticMethod_ ## methodName {\ + \ + template\ + static constexpr auto test(U*) ->\ + typename std::is_same()...)), Ret>::type;\ + \ + template\ + static constexpr std::false_type test(...);\ + \ + public:\ + typedef decltype(test(0)) type;\ + static constexpr const bool value = type::value;\ + \ + }; + +/// Creates a template for testing whether a class contains public method. +/// Use this macro anywhere a class may be defined, and pass method name +/// as its parameter. Then use `HasMethod_` template. +/// +/// E. g.: +/// TWPP_DETAIL_CREATE_HAS_METHOD(myMethod) // <- semicolon not required +/// HasMethod_myMethod::value +/// +/// This test whether `MyClass` has method (AKA member function) `void MyClass::myMethod(int, char)`. +/// That is whether you may do this: +/// MyClass o ... ; +/// o.myMethod(10, 'a'); +#define TWPP_DETAIL_CREATE_HAS_METHOD(methodName) \ + template\ + class HasMethod_ ## methodName;\ + \ + template\ + class HasMethod_ ## methodName {\ + \ + template\ + static constexpr auto test(U*) ->\ + typename std::is_same().methodName(std::declval()...)), Ret>::type;\ + \ + template\ + static constexpr std::false_type test(...);\ + \ + public:\ + typedef decltype(test(0)) type;\ + static constexpr const bool value = type::value;\ + \ + }; + +/// Performs a pointer type cast, suppresses strict aliasing warnings. +/// \tparam T Type of the returned pointer. Must be pointer type (e.g. `char*`). +/// \param ptr Pointer to be cast. +/// \return Cast pointer. +template +static constexpr inline T alias_cast(void* ptr) noexcept{ + return reinterpret_cast(ptr); +} + +/// Performs a constant pointer type cast, suppresses strict aliasing warnings. +/// \tparam T Type of the returned pointer. Must be pointer type (e.g. `char*`). +/// \param ptr Pointer to be cast. +/// \return Cast pointer. +template +static constexpr inline T alias_cast(const void* ptr) noexcept{ + return reinterpret_cast(ptr); +} + +/// Suppresses warnings about unused parameters or arguments. +/// \tparam Args List of argument types. No need to specify explicitly. +template +static inline void unused(const Args& ...) noexcept{} + + + +// CODE FROM http://www.macieira.org/blog/2011/07/initialising-an-array-with-cx0x-using-constexpr-and-variadic-templates/ +// BEGIN +template struct IndexList {}; + +template struct Append; +template +struct Append, Right>{ typedef IndexList Result; }; + +template struct Indexes { + typedef typename Append::Result, N - 1>::Result Result; +}; +template<> struct Indexes<0> { typedef IndexList<> Result; }; +// END + +/// Converts an array of arbitary size to array-like recursive structure of fixed size (at compile time). +/// Provide template specialization if special handling of elements is required, and you do care +/// about their positions - otherwise see FixedArrayData below. +/// \tparam T Element type. +/// \tparam arraySize Number of elements in the fixed array. +template +struct FixedArrayFlat : FixedArrayFlat { + + /// The index this structure (with this `arraySize`) holds. + static constexpr const std::size_t g_index = arraySize - 1; + + /// Performs the conversion from arbiraty-size array to fixed-size structure. + /// We use left recursion to initialize values of all inherited structures first. + /// Then the value of this one is initialized, either copied from the input array itself, + /// or default-initialized in case the array is not large enough. + /// \tparam inputSize {Size of the input array. If smaller than the fixed array, + /// excessive elements are default-initialized (may be changed in specializations). + /// Providing larger array results in undefined behaviour.} + /// \param arr The arbitary-size array. + template + constexpr inline FixedArrayFlat(const T(& arr)[inputSize]) noexcept : + FixedArrayFlat(arr), m_val(g_index < inputSize ? arr[g_index] : T()){} + + /// Returns value contained at specific index. + /// If the index if smaller than the size of the input array, a value is returned + /// as if the operation was performed on that array. Otherwise a default value + /// of the type `T` is returned (or anything else a specialization provides). + /// Behaviour of this operator is undefined if the index equals to or is greater than + /// the size of the fixed array. + /// \param i Value index. + /// \return Value at index. + constexpr inline T operator[](std::size_t i) const noexcept{ + return i == g_index ? m_val : FixedArrayFlat::operator [](i); + } + + /// Value held by this structure. + T m_val; + +}; + +/// Converts an array of arbitary size to array-like recursive structure of fixed size (at compile time). +/// This template specialization terminates the recursion. +/// No need to provide any further specializations. +/// \tparam T Element type. +template +struct FixedArrayFlat { + + template + constexpr inline FixedArrayFlat(const T(&)[inputSize]) noexcept{} + + constexpr inline T operator[](std::size_t) const noexcept{ + return T(); + } + +}; + + +/// Converts an array of arbitary size to array of fixed size at compile time. +/// The job itself is done in the specialization below. +/// \tparam T Element type. +/// \tparam arraySize Number of elements in the fixed array. +/// \tparam IndexList Type holding indexes of the fixed array. +template +struct FixedArrayData {}; + +/// Converts an array of arbitary size to array of fixed size at compile time. +/// Provide template specialization if special handling of elements is required, and you +/// don't care about their positions. +/// \tparam T Element type. +/// \tparam arraySize Number of elements in the fixed array. +/// \tparam i Indexes of the fixed array. +template +struct FixedArrayData > { + + /// Performs the conversion from arbiraty-size array to fixed-size array. + /// Uses FixedArrayFlat to extend the input array to desired size. + /// \tparam inputSize Size of the input array. + /// \param arr The input array. + template + constexpr FixedArrayData(const T(& arr)[inputSize]) noexcept : + m_arr{FixedArrayFlat(arr)[i]...}{} + + /// Creates default-initialized array. + constexpr FixedArrayData() noexcept : + m_arr(){} + + /// The fixed array. + T m_arr[arraySize]; + +}; + +/// Compile-time constructible fixed-size array of type `T` and length `arraySize`. +/// The array can be constructed from variable-sized array +/// of up to `arraySize` elements at compile time. +/// \tparam T Element type. +/// \tparam arraySize Number of elements in the array. +template +struct FixedArray : public FixedArrayData::Result> { + + typedef FixedArrayData::Result> ParentType; + typedef T Array[arraySize]; + + /// Creates default-initialized array. + constexpr FixedArray() noexcept : + ParentType(){} + + /// Creates fixed-size array from variable-size array at compile time. + /// If the size of input array exceeds `arraySize`, a compile-time error is emited. + /// \tparam inputSize Number of elements of the input array. + /// \param arr The input array. + template + constexpr FixedArray(const T(& arr)[inputSize]) noexcept : + ParentType(arr){ + + static_assert(inputSize <= arraySize, "array literal is too big"); + } + + /// The contained array. + constexpr const Array& array() const noexcept{ + return ParentType::m_arr; + } + + /// The contained array. + Array& array() noexcept{ + return ParentType::m_arr; + } + +}; + +/// Joins two arrays at compile time. +/// The job itself is done in the specialization below. +/// \tparam T Element type. +/// \tparam lenA Size of the first array. +/// \tparam lenB Size of the second array. +/// \tparam IndexList Type holding indexes of the resulting array. +template +struct ArrayJoinData {}; + +/// Joins two arrays at compile time. +/// The result of this operation is an array that contains all the elements +/// from the first array immediately followed by all the elements from +/// the second array. +/// \tparam T Element type. +/// \tparam lenA Size of the first array. +/// \tparam lenB Size of the second array. +/// \tparam i Indexes of the resulting array. +template +struct ArrayJoinData > { + + /// Performs the join operation. + /// \param a The first array. + /// \param b The second array. + constexpr ArrayJoinData(const T(& a)[lenA], const T(& b)[lenB]) noexcept : + m_arr{(i < lenA ? a[i] : b[i - lenA])...}{} + + /// The resulting array. + T m_arr[lenA + lenB]; + +}; + +/// Compile-time join operation of two arrays of the same type. +/// \tparam T Element type. +/// \tparam lenA Size of the first array. +/// \tparam lenB Size of the second array. +template +struct ArrayJoin : public ArrayJoinData::Result> { + + typedef ArrayJoinData::Result> ParentType; + typedef T Array[lenA + lenB]; + + /// Performs the join operation. + /// \param a The first array. + /// \param b The second array. + constexpr ArrayJoin(const T(& a)[lenA], const T(& b)[lenB]) noexcept : + ParentType(a, b){} + + /// The joined array. + constexpr const Array& array() const noexcept{ + return ParentType::m_arr; + } + + /// The joined array. + Array& array() noexcept{ + return ParentType::m_arr; + } + +}; + +/// Performs compile-time array join operation. +/// This is a helper function, see ArrayJoin and ArrayJoinData for more info. +/// \tparam T Element type. +/// \tparam lenA Size of the first array. +/// \tparam lenB Size of the second array. +/// \param a The first array. +/// \param b The second array. +/// \return The joined array. +template +static constexpr inline ArrayJoin arrayJoin(const T(& a)[lenA], const T(& b)[lenB]) noexcept{ + return {a, b}; +} + + +/// The loop that checks the suffix at compile time, see endsWith below. +/// Checks are performed from right to left. +/// \tparam T Element type. +/// \tparam arrLen The size of the array to be checked for the suffix. +/// \tparam subLen The size of the suffix array. +/// \param arr The array to be checked for the suffix. +/// \param sub The suffix array. +/// \param endOff Offset from the last element to be checked in this call. +/// \return Whether the suffix is contained. +template +static constexpr inline bool endsWithLoop(const T(& arr)[arrLen], const T(& sub)[subLen], std::size_t endOff){ + return endOff >= subLen || (arr[arrLen - 1 - endOff] == sub[subLen - 1 - endOff] && endsWithLoop(arr, sub, endOff + 1)); +} + +/// Checks whether the input array contains supplied suffix at compile time. +/// \tparam T Element type. +/// \tparam arrLen The size of the array to be checked for the suffix. +/// \tparam subLen The size of the suffix array. +/// \param arr The array to be checked for the suffix. +/// \param sub The suffix array. +/// \return Whether the suffix is contained. +template +static constexpr inline bool endsWith(const T(& arr)[arrLen], const T(& sub)[subLen]){ + return arrLen >= subLen && endsWithLoop(arr, sub, 0); +} + +/// Implementation of compile-time C string length. +/// Uses tail recursion. +/// \param str The string, or its remaining part. +/// \param len Length of the previous, already processed, part of the string. +/// \return Length of the string. +static constexpr inline std::size_t strLenImpl(const char* str, std::size_t len = 0) noexcept{ + return *str == '\0' ? len : strLenImpl(str + 1, len + 1); +} + +/// Compile-time C string length. +/// \param str The string. +/// \return Length of the string. +static constexpr inline std::size_t strLen(const char* str) noexcept{ + return strLenImpl(str); +} + + +/// Unsigned to signed conversion, using static_cast. +/// Available only if integers are represented using 2 complement. +/// Specialization handles non-2 complement cases. +/// \tparam T An integral type. +/// \tparam _2complement Whether ints are represented as 2 complement. +template // true +struct UnsigToSig { + typedef typename std::make_signed::type Signed; + typedef typename std::make_unsigned::type Unsigned; + + static constexpr Signed convert(Unsigned val) noexcept{ + return static_cast(val); + } +}; + +/// Unsigned to signed conversion. +/// This specialization is used when architecture does not use 2 complement. +/// \tparam T An integral type. +template +struct UnsigToSig { + typedef typename std::make_signed::type Signed; + typedef typename std::make_unsigned::type Unsigned; + + static constexpr Signed convert(Unsigned val) noexcept{ + return val <= std::numeric_limits::max() ? + static_cast(val) : + static_cast(val - std::numeric_limits::min()) + std::numeric_limits::min(); + } +}; + +/// Converts, at compile time, an unsigned integer to its signed counterpart. +/// This holds true: unsignedValue == static_cast(unsignedToSigned(unsignedValue)) +/// \tparam T Unsigned integral type. +/// \param val Unsigned value to be converted to signed. +/// \return Signed value that can be converted back to its unsigned type. +template::value>::type> +static constexpr inline typename std::make_signed::type unsignedToSigned(T val) noexcept{ + typedef typename std::make_signed::type Signed; + typedef typename std::make_unsigned::type Unsigned; + + return UnsigToSig(-1) == static_cast(~Unsigned(0))>::convert(val); +} + +/// Compares two C strings at compile time as if strcmp was used. +/// \param a First string. +/// \param b Second string. +/// \return See strcmp. +static constexpr inline int strCmp(const char* a, const char* b) noexcept{ + return *a != *b ? (static_cast(*a) - *b) : (*a == '\0' ? 0 : strCmp(a + 1, b + 1)); +} + +/// Absolute value. +/// Default implementation handles signed values +/// of non-integral types. +/// \tparam T Data type. +/// \tparam integral Whether the type is integral. +/// \tparam unsig Whether the data type is unsigned. +template // false, false +struct Abs { + static constexpr inline T abs(T a) noexcept{ + return a >= T() ? a : -a; + } +}; + +/// Absolute value. +/// This handles signed values of integral types. +/// \tparam T Data type. +template +struct Abs { + static constexpr inline T abs(T a) noexcept{ + return std::abs(a); + } +}; + +/// Absolute value. +/// This handles unsigned values. +/// \tparam T Data type. +template +struct Abs { + static constexpr inline T abs(T a) noexcept{ + return a; + } +}; + +/// Absolute value. +/// Handles anything that has `bool operator >=(const T&)` (or equiv.), +/// `T operator-()`, and its default value represents `zero`. +/// \tparam T Data type. +/// \param a Value. +template +static constexpr inline T abs(T a) noexcept{ + return Abs::value, std::is_unsigned::value>::abs(a); +} + +} + +} + +#endif // TWPP_DETAIL_FILE_UTILS_HPP +