mirror of http://192.168.1.51:8099/lmh188/twain3.0
391 lines
10 KiB
C++
391 lines
10 KiB
C++
#include "ImageApplyAutoCrop.h"
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#include "ImageProcess_Public.h"
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CImageApplyAutoCrop::CImageApplyAutoCrop()
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: m_isCrop(false)
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, m_isDesaskew(false)
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, m_isFillBlank(false)
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, m_isConvexHull(true)
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, m_isFillColor(false)
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, m_threshold(40)
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, m_noise(8)
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, m_indent(5)
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, m_normalCrop(false)
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{
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}
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CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex, bool isFillColor,
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double threshold, int noise, int indent, bool normalCrop)
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: m_isCrop(isCrop)
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, m_isDesaskew(isDesaskew)
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, m_isFillBlank(isFillBlank)
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, m_isConvexHull(isConvex)
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, m_isFillColor(isFillColor)
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, m_threshold(threshold)
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, m_noise(noise)
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, m_indent(indent)
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, m_fixedSize(fixedSize)
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, m_normalCrop(normalCrop)
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{
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}
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CImageApplyAutoCrop::~CImageApplyAutoCrop()
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{
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}
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cv::Mat concatenateMatrix(const cv::Mat& first, const cv::Mat& second)
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{
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cv::Mat mul1 = cv::Mat::eye(3, 3, CV_64F);
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cv::Mat mul2 = cv::Mat::eye(3, 3, CV_64F);
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cv::Mat mul_r;
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first.convertTo(mul_r, CV_64F);
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mul_r.row(0).copyTo(mul1.row(0));
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mul_r.row(1).copyTo(mul1.row(1));
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second.convertTo(mul_r, CV_64F);
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mul_r.row(0).copyTo(mul2.row(0));
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mul_r.row(1).copyTo(mul2.row(1));
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mul1 = mul2 * mul1;
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mul_r = first.clone();
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mul1.row(0).copyTo(mul_r.row(0));
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mul1.row(1).copyTo(mul_r.row(1));
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return mul_r;
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}
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std::vector<cv::Mat> comMat()
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{
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std::vector<cv::Mat> mats;
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cv::Point2f srcTri[3];
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srcTri[0] = cv::Point2f(1, 1);
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srcTri[1] = cv::Point2f(1, 0);
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srcTri[2] = cv::Point2f(0, 1);
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const float fact = 0.1f;
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float pos[] = { 0, 2 * fact, fact };
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cv::Point2f dstTri[3];
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dstTri[0] = cv::Point2f(1, 1);
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dstTri[1] = cv::Point2f(1, 0.5);
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dstTri[2] = cv::Point2f(0, 1);
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for (int i = 0; i < 3; i++)
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{
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dstTri[0] = cv::Point2f(1, 1 + pos[i]);
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dstTri[1] = cv::Point2f(1, pos[i]);
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dstTri[2] = cv::Point2f(0, 1 + pos[i]);
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mats.push_back(cv::getAffineTransform(srcTri, dstTri));
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}
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return mats;
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}
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void brightSharp(cv::Mat& src)
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{
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const float a = -0.49f;
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const float b = 3.0f;
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//float kernel_data[] = {
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// a, 0, 0, 0, a,
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// 0, 0, a, 0, 0,
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// 0, a, b, a, 0,
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// 0, 0, a, 0, 0,
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// a, 0, 0, 0, a };
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float kernel_data[] = {
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0, a, 0,
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a, b, a,
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0, a, 0
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};
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cv::Mat kernel(3, 3, CV_32FC1, kernel_data);
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cv::filter2D(src, src, src.depth(), kernel);
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}
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void CImageApplyAutoCrop::apply(cv::Mat& pDib, int side)
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{
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(void)side;
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if (pDib.empty()) return;
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if (m_normalCrop)
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{
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cv::Rect roi = cv::Rect((pDib.cols - m_fixedSize.width) / 2, side == 0 ? 75 : 145, m_fixedSize.width, m_fixedSize.height) & cv::Rect(0, 0, pDib.cols, pDib.rows);
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pDib = pDib(roi).clone();
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m_rect = cv::RotatedRect(cv::Point2f(roi.x + roi.width / 2, roi.y + roi.height / 2), cv::Size2f(roi.width, roi.height), 0.0f);
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return;
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}
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if (!m_isCrop && !m_isDesaskew && !m_isFillBlank && m_fixedSize.empty()) return;
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cv::Mat src = pDib;
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cv::Mat thre;
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cv::Mat dst;
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hg::threshold_Mat(src, thre, m_threshold);
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if (m_noise > 0)
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{
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cv::Mat element = getStructuringElement(cv::MORPH_RECT, cv::Size(m_noise, 1));
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cv::morphologyEx(thre, thre, cv::MORPH_OPEN, element);
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}
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std::vector<cv::Vec4i> hierarchy;
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std::vector<std::vector<cv::Point>> contours;
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hg::findContours(thre, contours, hierarchy, cv::RETR_EXTERNAL);
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m_maxContour = hg::getMaxContour(contours, hierarchy);
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if (m_maxContour.size() == 0)
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{
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thre.release();
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//<2F><><EFBFBD><EFBFBD>ǹ̶<C7B9><CCB6><EFBFBD><EFBFBD>棬<EFBFBD>뷵<EFBFBD>ز<EFBFBD><D8B2>к<EFBFBD>ijߴ<C4B3>
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if (!m_isCrop)
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pDib = pDib(cv::Rect((pDib.cols - m_fixedSize.width) / 2, (pDib.rows - m_fixedSize.height) / 2, m_fixedSize.width, m_fixedSize.height) & cv::Rect(0, 0, pDib.cols, pDib.rows)).clone();
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply");
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#endif // LOG
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return;
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}
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thre.release();
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dst.release();
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cv::RotatedRect rect = hg::getBoundingRect(m_maxContour);
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m_rect = rect;
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cv::Rect boudingRect = cv::boundingRect(m_maxContour);
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boudingRect.x -= 1;
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boudingRect.y -= 1;
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boudingRect.width += 2;
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boudingRect.height += 2;
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if (m_isDesaskew && rect.angle != 0)
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{
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cv::Point2f srcTri[4], srcTri_temp[3], dstTri[3];
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rect.points(srcTri);
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dstTri[0] = cv::Point2f(0, rect.size.height - 1);
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dstTri[1] = cv::Point2f(0, 0);
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dstTri[2] = cv::Point2f(rect.size.width - 1, 0);
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srcTri_temp[0] = dstTri[0];
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srcTri_temp[1] = dstTri[1];
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srcTri_temp[2] = dstTri[2];
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cv::Mat warp_mat;
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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if (src.channels() == 1)
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{
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cv::warpAffine(src, dst, warp_mat, rect.size, cv::INTER_LINEAR);
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}
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else
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{
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cv::Mat bgr[3];
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cv::split(src, bgr);
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auto mats = comMat();
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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warp_mat = concatenateMatrix(mats[0], warp_mat);
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//warp_mat = mats[0];
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cv::warpAffine(bgr[0], bgr[0], warp_mat, rect.size, cv::INTER_LINEAR);
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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warp_mat = concatenateMatrix(mats[1], warp_mat);
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//warp_mat = mats[1];
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cv::warpAffine(bgr[1], bgr[1], warp_mat, rect.size, cv::INTER_LINEAR);
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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warp_mat = concatenateMatrix(mats[2], warp_mat);
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//warp_mat = mats[2];
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cv::warpAffine(bgr[2], bgr[2], warp_mat, rect.size, cv::INTER_LINEAR);
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cv::merge(bgr, 3, dst);
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}
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double* ptr_m = reinterpret_cast<double*>(warp_mat.data);
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double a = ptr_m[0];
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double b = ptr_m[1];
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double c = ptr_m[2];
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double d = ptr_m[3];
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double e = ptr_m[4];
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double f = ptr_m[5];
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for (cv::Point& p : m_maxContour)
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{
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p.x = static_cast<int>(a * p.x + b * p.y + c);
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p.y = static_cast<int>(d * p.x + e * p.y + f);
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}
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}
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else
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{
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auto t_rect = boudingRect & cv::Rect(0, 0, src.cols, src.rows);
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dst = src(t_rect);
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if (dst.channels() == 3)
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{
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cv::Mat bgr[3];
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cv::split(dst, bgr);
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auto mats = comMat();
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for (int i = 0; i < 3; i++)
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{
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cv::warpAffine(bgr[i], bgr[i], mats[i], t_rect.size(), cv::INTER_LINEAR);
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}
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cv::merge(bgr, 3, dst);
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}
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}
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cv::Scalar autoBGColor;
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if (m_isFillBlank)
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{
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cv::Mat thre_dst;
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hg::threshold_Mat(dst, thre_dst, m_threshold);
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if (m_indent > 0)
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{
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for (size_t i = 0, length = m_maxContour.size() - 1; i < length; i++)
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cv::line(thre_dst, m_maxContour[i], m_maxContour[i + 1], cv::Scalar::all(0), m_indent * 2);
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cv::line(thre_dst, *m_maxContour.begin(), *m_maxContour.rbegin(), cv::Scalar::all(0), m_indent * 2);
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}
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//cv::imwrite("abc.jpg", thre_dst);
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hierarchy.clear();
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contours.clear();
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m_maxContour.clear();
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hg::findContours(thre_dst, contours, hierarchy, cv::RETR_EXTERNAL);
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if (m_isConvexHull)
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{
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m_maxContour = hg::getMaxContour(contours, hierarchy);
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if (m_maxContour.size() == 0)
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{
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thre.release();
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//<2F><><EFBFBD><EFBFBD>ǹ̶<C7B9><CCB6><EFBFBD><EFBFBD>棬<EFBFBD>뷵<EFBFBD>ز<EFBFBD><D8B2>к<EFBFBD>ijߴ<C4B3>
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if (!m_isCrop)
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pDib = pDib(cv::Rect((pDib.cols - m_fixedSize.width) / 2, (pDib.rows - m_fixedSize.height) / 2, m_fixedSize.width, m_fixedSize.height) & cv::Rect(0, 0, pDib.cols, pDib.rows)).clone();
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply");
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#endif // LOG
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return;
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}
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hg::convexHull(m_maxContour, m_maxContour);
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contours.clear();
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contours.push_back(m_maxContour);
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}
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contours.push_back(std::vector<cv::Point>());
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contours[contours.size() - 1].push_back(cv::Point(-1, dst.rows - 1));
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contours[contours.size() - 1].push_back(cv::Point(-1, -1));
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contours[contours.size() - 1].push_back(cv::Point(dst.cols, -1));
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contours[contours.size() - 1].push_back(cv::Point(dst.cols, dst.rows));
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autoBGColor = m_isFillColor ? getBackGroudColor(pDib, rect.size.area()) : cv::Scalar(255, 255, 255);
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hg::fillPolys(dst, contours, autoBGColor);
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}
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else
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{
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m_maxContour.clear();
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m_maxContour.push_back(cv::Point(-1, dst.rows));
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m_maxContour.push_back(cv::Point(-1, -1));
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m_maxContour.push_back(cv::Point(dst.cols, -1));
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m_maxContour.push_back(cv::Point(dst.cols, dst.rows));
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}
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pDib.release();
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if (/*(m_isCrop && side == 0) || (side == 1 && m_fixedSize.width * m_fixedSize.height == 0)*/ m_isCrop)
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pDib = dst.clone();
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else
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{
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pDib = cv::Mat(m_fixedSize, dst.type(), m_isFillBlank ? autoBGColor : cv::Scalar(0, 0, 0));
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cv::Rect roi;
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roi.x = dst.cols > pDib.cols ? (dst.cols - pDib.cols) / 2 : 0;
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roi.width = cv::min(pDib.cols, dst.cols);
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roi.y = dst.rows > pDib.rows ? (dst.rows - pDib.rows) / 2 : 0;
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roi.height = cv::min(pDib.rows, dst.rows);
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cv::Rect rect((pDib.cols - roi.width) / 2, (pDib.rows - roi.height) / 2, roi.width, roi.height);
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for (cv::Point& p : m_maxContour)
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p += roi.tl();
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dst(roi).copyTo(pDib(rect));
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}
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#ifdef LOG
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FileTools::write_log("imgprc.txt", "exit CImageApplyAutoCrop apply8");
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#endif // LOG
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}
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void CImageApplyAutoCrop::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
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{
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if (mats.empty()) return;
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if (!mats[0].empty()) {
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apply(mats[0], 0);
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m_rects.push_back(m_rect);
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brightSharp(mats[0]);
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}
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if (isTwoSide && mats.size() > 1)
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{
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cv::Size dSize = m_fixedSize;
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if (!mats[0].empty())
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m_fixedSize = mats[0].size();
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if (!mats[1].empty()) {
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apply(mats[1], 1);
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m_rects.push_back(m_rect);
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brightSharp(mats[1]);
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}
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if (!mats[0].empty())
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m_fixedSize = dSize;
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}
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}
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cv::Scalar CImageApplyAutoCrop::getBackGroudColor(const cv::Mat& image, int total)
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{
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if (image.channels() == 3)
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{
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cv::Mat image_bgr[3];
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cv::split(image, image_bgr);
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uchar bgr[3];
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for (size_t i = 0; i < 3; i++)
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bgr[i] = getBackGroudChannelMean(image_bgr[i], total);
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return cv::Scalar(bgr[0], bgr[1], bgr[2]);
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}
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else
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return cv::Scalar::all(getBackGroudChannelMean(image, total));
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}
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uchar CImageApplyAutoCrop::getBackGroudChannelMean(const cv::Mat& gray, int total)
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{
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cv::Mat image_clone;
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cv::resize(gray, image_clone, cv::Size(), 0.25, 0.25);
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int threnshold = total / 32;
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int channels[] = { 0 };
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int nHistSize[] = { 256 };
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float range[] = { 0, 256 };
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const float* fHistRanges[] = { range };
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cv::Mat hist;
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cv::calcHist(&image_clone, 1, channels, cv::Mat(), hist, 1, nHistSize, fHistRanges, true, false);
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int hist_array[256];
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for (int i = 0; i < 256; i++)
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hist_array[i] = hist.at<float>(i, 0);
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int length = 1;
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const int length_max = 255 - m_threshold;
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while (length < length_max)
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{
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for (size_t i = m_threshold + 1; i < 256 - length; i++)
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{
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int count = 0;
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uint pixSum = 0;
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for (size_t j = 0; j < length; j++)
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{
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count += hist_array[j + i];
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pixSum += hist_array[j + i] * (i + j);
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}
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if (count >= threnshold)
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return pixSum / count;
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}
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length++;
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}
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return 255;
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}
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