From d16483caf113b4030196810573fe87eef6765b3e Mon Sep 17 00:00:00 2001 From: maxbang <946568130@qq.com> Date: Tue, 17 Dec 2024 03:23:39 -0500 Subject: [PATCH 1/2] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20src/PBBiology/src/PBIm?= =?UTF-8?q?ageProcess.cpp?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 修改魔术棒功能 Signed-off-by: maxbang <946568130@qq.com> --- src/PBBiology/src/PBImageProcess.cpp | 245 +++++++++++++-------------- 1 file changed, 121 insertions(+), 124 deletions(-) diff --git a/src/PBBiology/src/PBImageProcess.cpp b/src/PBBiology/src/PBImageProcess.cpp index 64c8c8a..8293479 100644 --- a/src/PBBiology/src/PBImageProcess.cpp +++ b/src/PBBiology/src/PBImageProcess.cpp @@ -2,7 +2,7 @@ #include -//㷨 +//区域生长算法 int RegionGrow(cv::Mat& src, cv::Mat& matDst, cv::Point2i pt, int th) { cv::Point2i ptGrowing; @@ -16,39 +16,39 @@ int RegionGrow(cv::Mat& src, cv::Mat& matDst, cv::Point2i pt, int th) vcGrowPt.push_back(pt); matDst.at(pt.y, pt.x) = 255; - while (!vcGrowPt.empty()) //ջΪ + while (!vcGrowPt.empty()) //生长栈不为空则生长 { - pt = vcGrowPt.back(); //ȡһ + pt = vcGrowPt.back(); //取出一个生长点 vcGrowPt.pop_back(); - std::vector temp_vcGrowPt; //ʱջ - int temp_vcGrowPt_size = 0; //Ϊڱֱʹtemp_vcGrowPt.size() + std::vector temp_vcGrowPt; //临时生长点栈 + int temp_vcGrowPt_size = 0; //可生长方向数量，因为存在被其余生长点先生长情况，不可直接使用temp_vcGrowPt.size() nSrcValue = src.at(pt.y, pt.x); - //ֱ԰˸ϵĵ + //分别对八个方向上的点进行生长 for (int i = 0; i < 8; ++i) { ptGrowing.x = pt.x + DIR[i][0]; ptGrowing.y = pt.y + DIR[i][1]; - //ǷDZԵ + //检查是否是边缘点 if (ptGrowing.x < 0 || ptGrowing.y < 0 || ptGrowing.x >(src.cols - 1) || (ptGrowing.y > src.rows - 1)) continue; - nGrowLable = matDst.at(ptGrowing.y, ptGrowing.x); //ǰĻҶֵ - if (nGrowLable == 0) //ǵ㻹ûб + nGrowLable = matDst.at(ptGrowing.y, ptGrowing.x); //当前待生长点的灰度值 + if (nGrowLable == 0) //如果标记点还没有被生长 { nCurValue = src.at(ptGrowing.y, ptGrowing.x); - if (abs(nCurValue - nSrcValue) < th) //ֵΧ + if (abs(nCurValue - nSrcValue) < th) //在阈值范围内则生长 { // matDst.at(ptGrowing.y, ptGrowing.x) = 255; temp_vcGrowPt_size++; - temp_vcGrowPt.push_back(ptGrowing); //һѹջ + temp_vcGrowPt.push_back(ptGrowing); //将下一个生长点压入栈中 } } else { temp_vcGrowPt_size++; } } - //ڵ㲻ǵЧ + //相邻的生长点不是单向生长，则生长点有效 if (temp_vcGrowPt_size >= 1) { mat_cnt++; matDst.at(pt.y, pt.x) = 255; @@ -56,43 +56,43 @@ int RegionGrow(cv::Mat& src, cv::Mat& matDst, cv::Point2i pt, int th) } } return mat_cnt; - // bitwise_and(src, matDst, matDst); //Աԭͼ + // bitwise_and(src, matDst, matDst); //与运算可以保留原图像数据 } -// Բεĺ +// 定义拟合圆形的函数 void FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, float& Circle_R) { - //м - double sumX1 = 0.0; //Xiĺ(1~n) X1X1η + //定义计算中间变量 + double sumX1 = 0.0; //代表Xi的和(从1~n) ，X1代表X的1次方 double sumY1 = 0.0; - double sumX2 = 0.0; //(Xi)^2ĺ(i1~n)X2XĶη + double sumX2 = 0.0; //代表(Xi)^2的和(i从1~n)，X2代表X的二次方 double sumY2 = 0.0; double sumX3 = 0.0; double sumY3 = 0.0; double sumX1Y1 = 0.0; double sumX1Y2 = 0.0; double sumX2Y1 = 0.0; - const double N = (double)Circle_Data.size();//ĸ + const double N = (double)Circle_Data.size();//获得输入点的个数 - for (int i = 0; i < Circle_Data.size(); ++i)// + for (int i = 0; i < Circle_Data.size(); ++i)//遍历组中所有数据 { double x = 0; double y = 0; - x = Circle_Data[i].x; //еix - y = Circle_Data[i].y; //еiy - double x2 = x * x; //x^2 - double y2 = y * y; //y^2 - double x3 = x2 * x; //x^3 - double y3 = y2 * y; //y^3 - double xy = x * y; //xy - double x1y2 = x * y2; //x*y^2 - double x2y1 = x2 * y; //x^2*y + x = Circle_Data[i].x; //获得组中第i个点的x坐标 + y = Circle_Data[i].y; //获得组中第i个点的y坐标 + double x2 = x * x; //计算x^2 + double y2 = y * y; //计算y^2 + double x3 = x2 * x; //计算x^3 + double y3 = y2 * y; //计算y^3 + double xy = x * y; //计算xy + double x1y2 = x * y2; //计算x*y^2 + double x2y1 = x2 * y; //计算x^2*y - sumX1 += x; //sumX=sumX+x;xĺ - sumY1 += y; //sumY=sumY+y;yĺ - sumX2 += x2; //x^2ĺ - sumY2 += y2; //y^2ĺ - sumX3 += x3; //x^3ĺ + sumX1 += x; //sumX=sumX+x;计算x坐标的和 + sumY1 += y; //sumY=sumY+y;计算y坐标的和 + sumX2 += x2; //计算x^2的和 + sumY2 += y2; //计算各个点的y^2的和 + sumX3 += x3; //计算x^3的和 sumY3 += y3; sumX1Y1 += xy; sumX1Y2 += x1y2; @@ -117,11 +117,11 @@ void FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, float& int RANSAC_FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, float& Circle_R, float thresh) { - // RANSACС + // 定义RANSAC迭代次数和最小样本数 int iterations = 1000; int min_samples = 3; - // ʹRANSAC㷨Բ + // 使用RANSAC算法拟合圆形 float best_radius = 0; Point2f best_center; std::vector is_inlier(Circle_Data.size(), 0); @@ -132,7 +132,7 @@ int RANSAC_FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, f while (sample_count < iterations) { - // ѡС + // 随机选择最小样本数个点 vector points; for (int j = 0; j < min_samples; j++) { @@ -141,12 +141,12 @@ int RANSAC_FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, f points.push_back(point); } - // ʹС˷Բ + // 使用最小二乘法拟合圆形 float radius; Point2f center; FitCircleCenter(points, center, radius); - // еԲ֮ľ룬ȷڵ + // 计算所有点与圆之间的距离，以确定内点 vector inliers; for (int i = 0; i < Circle_Data.size(); i++) { @@ -160,28 +160,28 @@ int RANSAC_FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, f inliers.push_back(point); } } - // Բ + // 更新最佳拟合圆形 if (inliers.size() > max_inlier_num) { max_inlier_num = inliers.size(); is_inlier = is_inlier_tmp; best_radius = radius; best_center = center; } - //6. µѴ + //6. 更新迭代的最佳次数 if (inliers.size() == 0) { iterations = 1000; } else { - double epsilon = 1.0 - double(inliers.size()) / (double)Circle_Data.size(); //Ұֵ - double p = 0.9; //д1ĸ + double epsilon = 1.0 - double(inliers.size()) / (double)Circle_Data.size(); //野值点比例 + double p = 0.9; //所有样本中存在1个好样本的概率 double s = 3.0; iterations = int(std::log(1.0 - p) / std::log(1.0 - std::pow((1.0 - epsilon), s))); } sample_count++; } - //7. ŵĽӦڵ + //7. 基于最优的结果所对应的内点做最终拟合 std::vector inliers; inliers.reserve(max_inlier_num); for (int i = 0; i < is_inlier.size(); i++) @@ -297,9 +297,9 @@ int defaultIsoData(int* data) // { // return dst; // } -// //brightness_offset:ƫƷΧ -255 +255 -// //contrast_factor:ԱȶӷΧ 0.1 3.01.0Ϊ䣩 -// //opacity_factor:͸ӷΧ 0 10Ϊ͸1Ϊ͸ +// //brightness_offset:亮度偏移范围 -255 到 +255 +// //contrast_factor:对比度因子范围 0.1 到 3.0（1.0为不变） +// //opacity_factor:透明度因子范围 0 到 1（0为透明，1为不透明） // // Mat img8bit; // src.convertTo(img8bit, CV_8UC1, 0.00390625); @@ -311,7 +311,7 @@ int defaultIsoData(int* data) // img_with_opacity.convertTo(img_with_opacity, CV_8UC1); // // Mat img_with_opacity_rgb; -// cvtColor(img_with_opacity, img_with_opacity_rgb, COLOR_GRAY2BGR); // ͨҶͼתΪͨRGBͼ +// cvtColor(img_with_opacity, img_with_opacity_rgb, COLOR_GRAY2BGR); // 将单通道灰度图像转换为三通道RGB图像 // // for (int y = 0; y < pseudoImg.rows; y++) { // for (int x = 0; x < pseudoImg.cols; x++) { @@ -424,30 +424,30 @@ Mat bgr_scale_image(Mat src, float maxVal, float minVal) //int blendImages(const Mat& src, const Mat& mark, const Mat& dst, double alpha) //{ -// // ͼͺʹС +// // 检查输入图像的类型和大小 // if (src.type() != CV_16UC1 || mark.type() != CV_8UC3) // { -// return -1; // +// return -1; // 错误处理 // } // -// // alpha 0-100 ķΧתΪ 0-1 +// // 将 alpha 从 0-100 的范围转换为 0-1 // double alpha_normalized = alpha / 100.0; // -// // src 16 λתΪ 8 λ +// // 将 src 从 16 位转换为 8 位 // Mat src8U; -// src.convertTo(src8U, CV_8UC1, 1.0 / 256); // 16λֵŵ0-255Χ +// src.convertTo(src8U, CV_8UC1, 1.0 / 256); // 将16位值缩放到0-255范围 // -// // src8U תΪɫͼԱ mark ں +// // 将 src8U 转换为彩色图像，以便与 mark 融合 // Mat srcColor; -// cvtColor(src8U, srcColor, COLOR_GRAY2RGB); // תΪ BGR ɫͼ +// cvtColor(src8U, srcColor, COLOR_GRAY2RGB); // 转换为 BGR 彩色图像 // -// // һͼ +// // 创建一个输出图像 // Mat blended; // -// // ʹ addWeighted ں +// // 使用 addWeighted 进行融合 // addWeighted(srcColor, 1, mark,alpha_normalized, 0.0, blended); // blended.copyTo(dst); -// return 1; // ɹ +// return 1; // 成功 //} @@ -792,9 +792,9 @@ Mat render_mask_image(Mat src, Mat pseudoImg, int brightness_offset, double cont { return dst; } - //brightness_offset:ƫƷΧ -255 +255 - //contrast_factor:ԱȶӷΧ 0.1 3.01.0Ϊ䣩 - //opacity_factor:͸ӷΧ 0 10Ϊ͸1Ϊ͸ + //brightness_offset:亮度偏移范围 -255 到 +255 + //contrast_factor:对比度因子范围 0.1 到 3.0（1.0为不变） + //opacity_factor:透明度因子范围 0 到 1（0为透明，1为不透明） Mat img8bit; src.convertTo(img8bit, CV_8UC1, 0.00390625); @@ -806,7 +806,7 @@ Mat render_mask_image(Mat src, Mat pseudoImg, int brightness_offset, double cont img_with_opacity.convertTo(img_with_opacity, CV_8UC1); Mat img_with_opacity_rgb; - cvtColor(img_with_opacity, img_with_opacity_rgb, COLOR_GRAY2BGR); // ͨҶͼתΪͨRGBͼ + cvtColor(img_with_opacity, img_with_opacity_rgb, COLOR_GRAY2BGR); // 将单通道灰度图像转换为三通道RGB图像 for (int y = 0; y < pseudoImg.rows; y++) { for (int x = 0; x < pseudoImg.cols; x++) { @@ -1212,71 +1212,68 @@ Mat get_photon_image(Mat src, float sec, float Wcm, float Hcm, float sr) return dst; } -Mat get_magic_wand_image(Mat src, int x, int y, int th) +Mat get_magic_wand_image(Mat src,int x,int y,float max,float min) { - std::cout << "1" << std::endl; Mat matDst = cv::Mat::zeros(src.size(), CV_8UC1); - std::cout << "11" << std::endl; - cv::Point2i pt(x, y); - std::cout << "12" << std::endl; - cv::Point2i ptGrowing; - std::cout << "13" << std::endl; - int nGrowLable = 0; - int nSrcValue = 0; - int nCurValue = 0; - int mat_cnt = 0; - int DIR[8][2] = { { -1, -1 }, { 0, -1 }, { 1, -1 }, { 1, 0 }, { 1, 1 }, { 0, 1 }, { -1, 1 }, { -1, 0 } }; - std::cout << "14" << std::endl; - std::vector vcGrowPt; - std::cout << "15" << std::endl; - vcGrowPt.push_back(pt); - std::cout << "16" << std::endl; - matDst.at(pt.y, pt.x) = 255; - std::cout << "17" << std::endl; - std::cout << "w:" << src.rows << "h:" << src.cols << std::endl; - std::cout << pt.y <<":1:" << pt.x << std::endl; - nSrcValue = src.at(pt.y, pt.x); - std::cout << "2" << std::endl; - while (!vcGrowPt.empty()) + cv::Point2i pt(x,y); + int w = src.cols; + int h = src.rows; + // int nSrcValue = src.at(pt.y, pt.x); + int nSrcValue = src.data[pt.y * w + pt.x]; + if(nSrcValue < min) { - pt = vcGrowPt.back(); - vcGrowPt.pop_back(); - - std::vector temp_vcGrowPt; - int temp_vcGrowPt_size = 0; - // nSrcValue = src.at(pt.y, pt.x); - //ֱ԰˸ϵĵ - for (int i = 0; i < 8; ++i) - { - ptGrowing.x = pt.x + DIR[i][0]; - ptGrowing.y = pt.y + DIR[i][1]; - //ǷDZԵ - if (ptGrowing.x < 0 || ptGrowing.y < 0 || ptGrowing.x >(src.cols - 1) || (ptGrowing.y > src.rows - 1)) - continue; - - nGrowLable = matDst.at(ptGrowing.y, ptGrowing.x); //ǰĻҶֵ - if (nGrowLable == 0) //ǵ㻹ûб - { - nCurValue = src.at(ptGrowing.y, ptGrowing.x); - if (abs(nCurValue - nSrcValue) < th) //ֵΧ - { - // matDst.at(ptGrowing.y, ptGrowing.x) = 255; - temp_vcGrowPt_size++; - temp_vcGrowPt.push_back(ptGrowing); //һѹջ - } - } - else { - temp_vcGrowPt_size++; - } - } - std::cout << "3" << std::endl; - //ڵ㲻ǵЧ - if (temp_vcGrowPt_size >= 1) { - mat_cnt++; - matDst.at(pt.y, pt.x) = 255; - vcGrowPt.insert(vcGrowPt.end(), temp_vcGrowPt.begin(), temp_vcGrowPt.end()); - } - std::cout << "4" << std::endl; + return matDst; } + + cv::Point2i ptGrowing; + int nGrowLable = 0; + int nCurValue = 0; + int mat_cnt = 0; + int DIR[8][2] = { { -1, -1 }, { 0, -1 }, { 1, -1 }, { 1, 0 }, { 1, 1 }, { 0, 1 }, { -1, 1 }, { -1, 0 } }; + std::vector vcGrowPt; + vcGrowPt.push_back(pt); + // matDst.at(pt.y, pt.x) = 255; + matDst.data[pt.y * w + pt.x] = 255; + while (!vcGrowPt.empty()) + { + pt = vcGrowPt.back(); + vcGrowPt.pop_back(); + + std::vector temp_vcGrowPt; + int temp_vcGrowPt_size = 0; + // nSrcValue = src.at(pt.y, pt.x); + //分别对八个方向上的点进行生长 + for (int i = 0; i < 8; ++i) + { + ptGrowing.x = pt.x + DIR[i][0]; + ptGrowing.y = pt.y + DIR[i][1]; + //检查是否是边缘点 + if (ptGrowing.x < 0 || ptGrowing.y < 0 || ptGrowing.x >(src.cols - 1) || (ptGrowing.y > src.rows - 1)) + continue; + + // nGrowLable = matDst.at(ptGrowing.y, ptGrowing.x); + nGrowLable = matDst.data[ptGrowing.y * w + ptGrowing.x]; //当前待生长点的灰度值 + if (nGrowLable == 0) //如果标记点还没有被生长 + { + nCurValue = src.data[ptGrowing.y * w + ptGrowing.x]; + if (nCurValue >= min) //在阈值范围内则生长 + { + // matDst.at(ptGrowing.y, ptGrowing.x) = 255; + temp_vcGrowPt_size++; + temp_vcGrowPt.push_back(ptGrowing); //将下一个生长点压入栈中 + } + } + else { + temp_vcGrowPt_size++; + } + } + //相邻的生长点不是单向生长，则生长点有效 + if (temp_vcGrowPt_size >= 1) { + mat_cnt++; + // matDst.at(pt.y, pt.x) = 255; + matDst.data[pt.y * w + pt.x] = 255; + vcGrowPt.insert(vcGrowPt.end(), temp_vcGrowPt.begin(), temp_vcGrowPt.end()); + } + } return matDst; -} +} \ No newline at end of file -- 2.39.5 From 4fcc93856ebc79e7822c6062e89b915a069d16a1 Mon Sep 17 00:00:00 2001 From: maxbang <946568130@qq.com> Date: Tue, 17 Dec 2024 03:25:44 -0500 Subject: [PATCH 2/2] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20src/PBBiology/include/?= =?UTF-8?q?PBImageProcess.h?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 修改魔术棒功能 Signed-off-by: maxbang <946568130@qq.com> --- src/PBBiology/include/PBImageProcess.h | 64 +++++++++++++------------- 1 file changed, 32 insertions(+), 32 deletions(-) diff --git a/src/PBBiology/include/PBImageProcess.h b/src/PBBiology/include/PBImageProcess.h index 5c8ba53..5e95fb8 100644 --- a/src/PBBiology/include/PBImageProcess.h +++ b/src/PBBiology/include/PBImageProcess.h @@ -10,28 +10,28 @@ using namespace std; using namespace cv; -// +//生长函数 int RegionGrow(cv::Mat& src, cv::Mat& matDst, cv::Point2i pt, int th); -//С˷ȡԲ +//最小二乘法取圆 void FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, float& Circle_R); -//С˷ȡԲ +//最优最小二乘法取圆 int RANSAC_FitCircleCenter(vector& Circle_Data, Point2f& Circle_Center, float& Circle_R, float thresh); -//С˷ȡԲ +//生长最优最小二乘法取圆 void RANSAC_FitCircleCenter_with_throw(vector& Circle_Data, Point2f& Circle_Center, float& Circle_R); -//ֵֵ +//二值化阈值计算 int IJIsoData(int* data); int defaultIsoData(int* data); -////maskȾͼ -////srcmaskCV_16UC1ͼ -////dstCV_8UC3ɫͼ -////maxminmaskѡȾСֵ -////colorɫ -////reverseǷתɫ +////根据mask渲染图像 +////src、mask：输入CV_16UC1图像 +////dst：输出CV_8UC3彩色图像 +////max、min：mask像素选择渲染的最大最小值 +////color：颜色类型 +////reverse：是否反转颜色 //int render_mask_image(Mat src, Mat mask, Mat dst, float max, float min, ColorTable color, bool reverse); // ///// -///// ںͼ +///// 融合两张图 ///// ///// ///// @@ -40,41 +40,41 @@ int defaultIsoData(int* data); ///// //int blendImages(const Mat& src, const Mat& mark, const Mat& dst, double alpha); ////int render_image(Mat src, Mat& dst, float max, float min, ColorTable color, bool reverse); -////ϳȾͼsrcͼpseudoImgǹȾͼbrightness_offsetȣcontrast_factorԱȶȣcontrast_factor͸ȣںͼ -////brightness_offset:ƫƷΧ -255 +255 -////contrast_factor:ԱȶӷΧ 0.1 3.01.0Ϊ䣩 -////opacity_factor:͸ӷΧ 0 10Ϊ͸1Ϊ͸ +////合成渲染图像，src是老鼠图，pseudoImg是光子渲染图，brightness_offset亮度，contrast_factor对比度，contrast_factor透明度，返回融合图 +////brightness_offset:亮度偏移范围 -255 到 +255 +////contrast_factor:对比度因子范围 0.1 到 3.0（1.0为不变） +////opacity_factor:透明度因子范围 0 到 1（0为透明，1为不透明） //Mat render_mask_image(Mat src, Mat pseudoImg, int brightness_offset, double contrast_factor, double opacity_factor); -////ȡɫcolorɫͣbgr_tabпռɫָ룬reverseǷת +////获取颜色表，color颜色类型，bgr_tab是有空间的颜色表指针，reverse是否反转 //void get_bgr_tab(ColorTable color, uint8_t(*bgr_tab)[3], bool reverse); -////ɫֱͼw=200,h_color=10һɫߣbgr_tabпռɫָ +////生产颜色表的直条图，w=200,h_color=10是一个颜色高，bgr_tab是有空间的颜色表指针 //Mat bgr_tab_image(int w, int h_onecolor, uint8_t(*bgr_tab)[3]); //int pseudo_color_processing(Mat src, Mat dst, float max, float min, uint8_t(*bgr_tab)[3]); // -//// ѡĹ +//// 获得选中区域的光子数 //PseudoInfo get_pseudo_info(Mat src,int x,int y,int w,int h,float max,float min); // //Mat bgr_scale_image(Mat src, float maxVal, float minVal); -//ϳȾͼsrcͼpseudoImgǹȾͼbrightness_offsetȣcontrast_factorԱȶȣcontrast_factor͸ȣںͼ -//brightness_offset:ƫƷΧ -255 +255 -//contrast_factor:ԱȶӷΧ 0.1 3.01.0Ϊ䣩 -//opacity_factor:͸ӷΧ 0 10Ϊ͸1Ϊ͸ +//合成渲染图像，src是老鼠图，pseudoImg是光子渲染图，brightness_offset亮度，contrast_factor对比度，contrast_factor透明度，返回融合图 +//brightness_offset:亮度偏移范围 -255 到 +255 +//contrast_factor:对比度因子范围 0.1 到 3.0（1.0为不变） +//opacity_factor:透明度因子范围 0 到 1（0为透明，1为不透明） Mat render_mask_image(Mat src, Mat pseudoImg, int brightness_offset, double contrast_factor, double opacity_factor); -//ȡɫcolorɫͣbgr_tabпռɫָ룬reverseǷת +//获取颜色表，color颜色类型，bgr_tab是有空间的颜色表指针，reverse是否反转 void get_bgr_tab(ColorTable color, uint8_t(*bgr_tab)[3], bool reverse); -//ɫֱͼw=200,h_color=10һɫߣbgr_tabпռɫָ +//生产颜色表的直条图，w=200,h_color=10是一个颜色高，bgr_tab是有空间的颜色表指针 Mat bgr_tab_image(int w, int h_onecolor, uint8_t(*bgr_tab)[3]); -//ͳƼsrcͼ16bitcountͼfloatĹӼͼ룻maskĤͼmaxmin趨ĴС +//统计计算结果，src是输入图像，16bit的count图或者float的光子计算结果图都可以输入；mask是掩膜图；max和min是设定的大小 PseudoInfo get_pseudo_info(Mat src, Mat mask, float max, float min); -//ɹȾͼsrcȾǰͼdstȾͼmaxmin趨ĴСbgr_tabпռɫָ +//生成光子渲染图，src是渲染前图，dst是渲染后图，max和min是设定的大小，bgr_tab是有空间的颜色表指针 int pseudo_color_processing(Mat src, Mat dst, float max, float min, uint8_t(*bgr_tab)[3]); -//ɴߵֱͼsrcbgr_tab_imageɵͼmaxValminVal趨ĴСscientific_flagǷѧ +//生成带标尺的直条图，src是bgr_tab_image生成的图，maxVal和minVal是设定的大小，scientific_flag是否科学计数法 Mat bgr_scale_image(Mat src, float maxVal, float minVal, int scientific_flag); -//ȡӼͼsrcȾǰԭʼͼsecWcm=27ʵʿHcm=18ʵʸߣsrĬ1.0CV_32FC1ĸӽͼ +//获取光子计算图，src输入渲染前原始图，sec是拍摄秒数，Wcm=27是实际宽，Hcm=18是实际高，sr是默认1.0；返回CV_32FC1的浮点光子结果图 Mat get_photon_image(Mat src, float sec, float Wcm, float Hcm, float sr); -//ħܣsrcǴ8bitͼx,yǵλõ꣬ -//th趨ز1020֮ģʵʵһ£Ǻ͵λõزthΧڵһأᱻѡ -Mat get_magic_wand_image(Mat src, int x, int y, int th); \ No newline at end of file +//魔术棒功能，src是处理成8bit的图，x,y是点击位置的坐标，max和min是设定的大小,max和min需要注意除以256，使用0-255数据 +//点击位置的像素差在[min,max]范围内的连在一起的像素，都会被框选 +Mat get_magic_wand_image(Mat src,int x,int y,float max,float min); \ No newline at end of file -- 2.39.5