mirror of http://192.168.1.51:8099/lmh188/twain3.0
225 lines
6.1 KiB
C++
225 lines
6.1 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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{
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}
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CImageApplyAutoCrop::CImageApplyAutoCrop(bool isCrop, bool isDesaskew, bool isFillBlank, const cv::Size& fixedSize, bool isConvex, bool isFillColor, double threshold, int noise, int indent)
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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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{
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}
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CImageApplyAutoCrop::~CImageApplyAutoCrop()
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{
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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_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, m_noise));
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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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return;
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}
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thre.release();
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cv::RotatedRect rect = hg::getBoundingRect(m_maxContour);
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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];
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cv::Point2f 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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cv::Mat warp_mat;
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warp_mat = cv::getAffineTransform(srcTri, dstTri);
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//cv::warpAffine(src, dst, warp_mat, rect.size,cv::INTER_LANCZOS4);
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cv::warpAffine(src, dst, warp_mat, rect.size);
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}
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else
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dst = src(boudingRect & cv::Rect(0, 0, src.cols, src.rows));
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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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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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std::vector<cv::Point> rectEdge{ cv::Point(0, 0) ,cv::Point(thre_dst.cols - 1, 0),
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cv::Point(thre_dst.cols - 1, thre_dst.rows - 1), cv::Point(0, thre_dst.rows - 1) };
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std::vector<std::vector<cv::Point>> rectEdges{ rectEdge };
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cv::drawContours(thre_dst, rectEdges, 0, cv::Scalar::all(0));
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cv::Mat element = cv::getStructuringElement(cv::MorphShapes::MORPH_RECT, cv::Size(m_indent, m_indent));
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cv::erode(thre_dst, thre_dst, element, cv::Point(-1, -1), 1);
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}
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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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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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hg::fillPolys(dst, contours, m_isFillColor ? getBackGroudColor(pDib, rect.size.area()) : cv::Scalar(255, 255, 255));
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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 ? cv::Scalar(255, 255, 255) : 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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}
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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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}
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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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