一、读取图像
//图片路径 QString appPath = QCoreApplication::applicationDirPath(); QString imagePath = appPath + "/sun.png"; //读取图像 cv::Mat img = cv::imread(imagePath.toStdString()); //IMREAD_GRAYSCALE 灰度图 IMREAD_UNCHANGED 具有透明通道 if (img.empty()) { qDebug()<< "Could not load image!\n"; return; } //创建窗口 cv::namedWindow("input", cv::WINDOW_AUTOSIZE); //显示图像 cv::imshow("input", img); //参数为0一直阻塞 cv::waitKey(0); //销毁窗口 cv::destroyAllWindows();
二、保存图像
//保存为png透明通道 vector<int>opts; opts.push_back(IMWRITE_PAM_FORMAT_RGB_ALPHA); imwrite("D:/img_bgra.png", img, opts); //保存为单通道灰度图像 img = cv::imread(imagePath.toStdString(), IMREAD_GRAYSCALE); vector<int> opts_gray; opts_gray.push_back(IMWRITE_PAM_FORMAT_GRAYSCALE); imwrite("D:/img_gray.png", img, opts_gray); //保存为默认的彩色BGR图像 imwrite("D:/img_BGR.png", img); //保存为png彩色压缩图像 img = imread(imagePath.toStdString(), IMREAD_ANYCOLOR); vector<int> opts_png_anycolor; opts_png_anycolor.push_back(IMWRITE_PAM_FORMAT_GRAYSCALE); opts_png_anycolor.push_back(9); imwrite("D:/img_png_anycolor.png", img, opts_png_anycolor); //保存为JPG高压缩比图像 img = imread(imagePath.toStdString(), IMREAD_COLOR); vector<int> opts_jpeg; opts_jpeg.push_back(IMWRITE_JPEG_QUALITY); opts_jpeg.push_back(50); opts_jpeg.push_back(IMWRITE_JPEG_OPTIMIZE); opts_jpeg.push_back(1); imwrite("D:/img_jpeg.jpg", img, opts_jpeg);
三、加载视频
//视频路径 QString appPath = QCoreApplication::applicationDirPath(); QString videoPath = appPath + "/vtest.avi"; cv::VideoCapture capture; capture.open(videoPath.toStdString(),CAP_FFMPEG); //从摄像头读取 //capture.open(0, CAP_DSHOW); cv::Mat frame; while (true) { //读帧 bool ret = capture.read(frame); if (!ret) break; imshow("frame", frame); //添加帧处理 等待 100 毫秒，检查用户是否按下键盘上的按键 char c = waitKey(100); //按下的是 ESC 键 (ASCII 值为 27)，则跳出循环，停止播放视频 if (c == 27) break; } waitKey(0); destroyAllWindows();
四、获取视频属性
//视频路径 QString appPath = QCoreApplication::applicationDirPath(); QString videoPath = appPath + "/vtest.avi"; cv::VideoCapture capture; capture.open(videoPath.toStdString(),CAP_FFMPEG); qDebug() << u8"高：" << capture.get(CAP_PROP_FRAME_HEIGHT); qDebug() << u8"宽：" << capture.get(CAP_PROP_FRAME_WIDTH); qDebug() << u8"帧率FPS：" << QString::number(capture.get(CAP_PROP_FPS)); qDebug() << u8"总帧率：" << capture.get(CAP_PROP_FRAME_COUNT);
五、保存视频
//视频路径 QString appPath = QCoreApplication::applicationDirPath(); QString videoPath = appPath + "/vtest.avi"; cv::VideoCapture capture; capture.open(videoPath.toStdString(), CAP_FFMPEG); qDebug() << u8"高：" << capture.get(CAP_PROP_FRAME_HEIGHT); qDebug() << u8"宽：" << capture.get(CAP_PROP_FRAME_WIDTH); qDebug() << u8"帧率FPS：" << capture.get(CAP_PROP_FPS); qDebug() << u8"总帧率：" << capture.get(CAP_PROP_FRAME_COUNT); //保存视频路径 QString savevideoPath = appPath + "/output.avi"; cv::VideoWriter writer(savevideoPath.toStdString(), capture.get(CAP_PROP_FOURCC), capture.get(CAP_PROP_FPS), Size(capture.get(CAP_PROP_FRAME_WIDTH), capture.get(CAP_PROP_FRAME_HEIGHT))); cv::Mat frame; while (true) { //读帧 bool ret = capture.read(frame); if (!ret) break; imshow("frame", frame); //添加帧处理 writer.write(frame); //等待 100 毫秒，检查用户是否按下键盘上的按键 char c = waitKey(100); //按下的是 ESC 键 (ASCII 值为 27)，则跳出循环，停止播放视频 if (c == 27) break; } capture.release(); writer.release(); waitKey(0); destroyAllWindows();
六、Mat遍历
- 数组下标
for (int row = 0; row < h; row++) { for (int col = 0; col < w; col++) { if (dim == 1)//灰度图像 { int pv = image.at<uchar>(row,col);//像素是字节类型 image.at<uchar>(row, col) = 255 - pv; } if (dim == 3)//彩色图像 { Vec3b bgr = image.at<Vec3b>(row, col); image.at<Vec3b>(row, col)[0] = 255 - bgr[0]; image.at<Vec3b>(row, col)[1] = 255 - bgr[1]; image.at<Vec3b>(row, col)[2] = 255 - bgr[2]; } } }
- 指针
for (int row = 0; row < h; row++) { uchar* current_row = image.ptr<uchar>(row); for (int col = 0; col < w; col++) { if (dim == 1)//灰度图像 { int pv = *current_row; *current_row++ = 255 - *current_row; } if (dim == 3)//彩色图像 { *current_row++ = 255 - *current_row; *current_row++ = 255 - *current_row; *current_row++ = 255 - *current_row; } } }
七、Mat加减乘除
#include <opencv2/opencv.hpp> using namespace cv; int main() { Mat image = imread("image.jpg"); if (image.empty()) { std::cout << "无法加载图像" << std::endl; return -1; } // 加法变换 Mat addResult; add(image, Scalar(50, 50, 50), addResult); // 将像素值增加50 // 减法变换 Mat subtractResult; subtract(image, Scalar(50, 50, 50), subtractResult); // 将像素值减去50 // 乘法变换 Mat multiplyResult; multiply(image, Scalar(0.5, 0.5, 0.5), multiplyResult); // 将像素值乘以0.5 // 除法变换 Mat divideResult; divide(image, Scalar(2.0, 2.0, 2.0), divideResult); // 将像素值除以2.0 imshow("Original Image", image); imshow("Addition Result", addResult); imshow("Subtraction Result", subtractResult); imshow("Multiplication Result", multiplyResult); imshow("Division Result", divideResult); waitKey(0); return 0; }
七、亮度调节demo
Mat src, dst, m; int lightness = 50; static void on_track(int, void *) { m = Scalar(lightness, lightness, lightness); //add(src,m,dst); subtract(src, m, dst); imshow("亮度调节", dst); } void on_pushButton_brightness_clicked() { namedWindow("亮度调节", WINDOW_AUTOSIZE); QString appPath = QCoreApplication::applicationDirPath()+"/A.jpg"; src = cv::imread(appPath.toStdString()); dst = Mat::zeros(src.size(), src.type()); m = Mat::zeros(src.size(), src.type()); int max_value = 100; createTrackbar("Value Bar:", "亮度调节", &lightness, max_value, on_track); on_track(50, 0); }
static void on_track(int b, void* user_data) { Mat image = *((Mat *)user_data); Mat dst = Mat::zeros(image.size(), image.type()); Mat m = Mat::zeros(image.size(), image.type()); m = Scalar(b, b, b); //add(image,m,dst); subtract(image, m, dst); imshow("亮度调节", dst); } void introduction::on_pushButton_brightness_clicked() { namedWindow("亮度调节", WINDOW_AUTOSIZE); int lightness = 50; int max_value = 100; //img为已经读入的图像 createTrackbar("Value Bar:", "亮度调节", &lightness, max_value, on_track,(void*)(&img)); on_track(50, &img); }
八、亮度对比度调节
static void on_track_lightness(int b, void* user_data) { Mat image = *((Mat *)user_data); if (image.empty()) return; Mat dst = Mat::zeros(image.size(), image.type()); Mat m = Mat::zeros(image.size(), image.type()); addWeighted(image, 1.0, m, 0, b, dst); imshow("亮度对比度调节", dst); } static void on_track_contrast(int b, void* user_data) { Mat image = *((Mat *)user_data); Mat dst = Mat::zeros(image.size(), image.type()); Mat m = Mat::zeros(image.size(), image.type()); double contrast = b / 100.0; addWeighted(image, contrast, m, 0.0, 0, dst); imshow("亮度对比度调节", dst); } void brightness_demo() { namedWindow("亮度对比度调节", WINDOW_AUTOSIZE); int lightness = 50; int max_value = 100; int contrast_value = 100; createTrackbar("Value Bar:", "亮度对比度调节", &lightness, max_value, on_track_lightness,(void*)(&img)); createTrackbar("Constrast Bar:", "亮度对比度调节", &contrast_value, 200, on_track_contrast, (void*)(&img)); on_track_lightness(50, &img); }
九、键盘响应操作
//图片路径 QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; //读取图像 img = cv::imread(imagePath.toStdString()); if (img.empty()) return; cv::namedWindow("input", cv::WINDOW_AUTOSIZE); //显示图像 cv::imshow("input", img); Mat dst = Mat::zeros(img.size(),img.type()); while (true) { char c = waitKey(100); std::cout << c << std::endl; if (c == 27) break; if (c == 49)//Key 1 { cvtColor(img, dst, COLOR_BGR2GRAY); } if (c == 50)//Key 2 { cvtColor(img, dst, COLOR_BGR2HSV); } if (c == 51)//Key 3 { dst = Scalar(50, 50, 50); add(img, dst, dst); } cv::imshow("input", dst); } //参数为0一直阻塞 cv::waitKey(0); //销毁窗口 cv::destroyAllWindows();
十、OpenCV自带颜色表
//图片路径 QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; //读取图像 img = cv::imread(imagePath.toStdString()); if (img.empty()) return; cv::namedWindow("input", cv::WINDOW_AUTOSIZE); cv::Mat dst; int color_map = COLORMAP_AUTUMN; while (true) { int c = cv::waitKey(2000); if (c == 27) { break; } applyColorMap(img, dst, color_map%21); color_map++; cv::imshow("input", dst); } cv::waitKey(0); cv::destroyAllWindows();
十一、图像像素逻辑操作
cv::Mat m1 = cv::Mat::zeros(Size(256, 256), CV_8UC3); cv::Mat m2 = cv::Mat::zeros(Size(256, 256), CV_8UC3); rectangle(m1, Rect(100, 100, 80, 80),Scalar(255,255,0),-1,LINE_8,0); rectangle(m2, Rect(150, 150, 80, 80), Scalar(0, 255, 255), -1, LINE_8, 0); imshow("m1", m1); imshow("m2", m2); Mat dst; bitwise_and(m1, m2, dst); imshow("与操作", dst); bitwise_or(m1, m2, dst); imshow("或操作", dst); QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; bitwise_not(img, dst); imshow("非操作", dst); bitwise_xor(m1, m2, dst); imshow("异或操作", dst); cv::waitKey(0); cv::destroyAllWindows();
十二、通道分离、合并、混和
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; std::vector<Mat> mv; cv::split(img, mv); imshow("B", mv[0]); imshow("G", mv[1]); imshow("R", mv[2]); cv::Mat dst; mv[1] = 0; mv[2] = 0; cv::merge(mv, dst); imshow("Blue", dst); int from_to[] = { 0,2,1,1,2,0 }; cv::mixChannels(&img, 1, &dst, 1, from_to,3); imshow("通道混合", dst);
十三、图像色彩空间转换
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/sun.png"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; imshow("img", img); cv::Mat hsv; cv::cvtColor(img,hsv,COLOR_BGR2HSV); cv::Mat mask; inRange(hsv, Scalar(0,0,221), Scalar(180,30,255), mask); Mat redback = Mat::zeros(img.size(), img.type()); redback = Scalar(40, 40, 200); bitwise_not(mask, mask); imshow("mask", mask); img.copyTo(redback, mask); imshow("roi", redback);
十四、图像像素值统计
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; double minv, maxv; Point minLoc, maxLoc; std::vector<Mat> mv; split(img, mv); for (int i = 0; i < mv.size(); i++) { //图像必须单通道 minMaxLoc(mv[i], &minv, &maxv, &minLoc, &maxLoc, cv::Mat()); std::cout << "channel" << i << "min value" << minv << "max value" << maxv<<std::endl ; } Mat mean, stddev; //计算均值方差 meanStdDev(img,mean,stddev); std::cout << "mean" << mean << "stddev" << stddev << std::endl;
十五、图像几何形状绘制
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat bg = Mat::zeros(img.size(),img.type()); Rect rect; rect.x = 200; rect.y = 200; rect.width = 100; rect.height = 50; rectangle(bg, rect, Scalar(0, 0, 255), -1,8,0); circle(bg, Point(50, 100), 15, Scalar(255, 0, 0), 2); line(bg, Point(100, 100), Point(100, 200), Scalar(0, 255, 0), 2, LINE_AA, 0); RotatedRect rrt(Point(200, 200),Size(100, 200), 90.0); ellipse(bg, rrt, Scalar(0, 255, 255), 2, 8); Mat dst; addWeighted(img, 0.7,bg,0.3,0, dst); imshow("Draw", dst);
十六、随机数与随机颜色绘制
Mat bg = Mat::zeros(Size(512,512), CV_8UC3); int w = bg.cols; int h = bg.rows; RNG rng(12345); while (true) { int c = cv::waitKey(10); if (c == 27) { break; } int x1 = rng.uniform(0, w); int y1 = rng.uniform(0, h); int x2 = rng.uniform(0, w); int y2 = rng.uniform(0, h); bg = Scalar(0, 0, 0); line(bg, Point(x1, y1), Point(x2, y2), Scalar(rng.uniform(0,255), rng.uniform(0, 255), rng.uniform(0, 255)), 2, LINE_AA, 0); imshow("Draw_random", bg); }
十七、多边形填充与绘制
Mat bg = Mat::zeros(Size(512, 512), CV_8UC3); Point p1(100, 100); Point p2(350, 100); Point p3(450, 280); Point p4(320, 450); Point p5(80, 400); std::vector<Point> pts; pts.push_back(p1); pts.push_back(p2); pts.push_back(p3); pts.push_back(p4); pts.push_back(p5); polylines(bg, pts, true, Scalar(0, 0, 255), 2, 8, 0); fillPoly(bg, pts, Scalar(0, 255, 255),8, 0); std::vector<std::vector<Point>> contours; contours.push_back(pts); drawContours(bg, contours, -1, Scalar(255, 0, 255), 2); imshow("Draw_polygon", bg);
十八、鼠标操作（画红色方框截取图像）
Point sp(-1, -1); Point ep(-1, -1); Mat temp; static void on_draw(int event, int x, int y, int flags,void *user_data) { Mat image = *((Mat *)user_data); if (event == EVENT_LBUTTONDOWN) { sp.x = x; sp.y = y; } else if (event == EVENT_LBUTTONUP) { ep.x = x; ep.y = y; int dx = ep.x - sp.x; int dy = ep.y - sp.y; if (dx > 0 && dy > 0) { Rect rect(sp.x,sp.y,dx,dy); rectangle(image, rect, Scalar(0, 0, 255), 2, 8, 0); imshow("mouse_draw", image); imshow("roi", image(rect)); sp.x = -1; sp.y = -1; } } else if (event == EVENT_MOUSEMOVE) { if (sp.x > 0 && sp.y > 0) { ep.x = x; ep.y = y; int dx = ep.x - sp.x; int dy = ep.y - sp.y; if (dx > 0 && dy > 0) { temp.copyTo(image); Rect rect(sp.x, sp.y, dx, dy); rectangle(image, rect, Scalar(0, 0, 255), 2, 8, 0); imshow("mouse_draw", image); } } } } void mouse_demo() { QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; temp = img.clone(); namedWindow("mouse_draw", WINDOW_AUTOSIZE); setMouseCallback("mouse_draw", on_draw,(void*)(&img)); imshow("mouse_draw", img); }
十九、图像归一化
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; img.convertTo(img, CV_32F); normalize(img, dst, 1.0, 0, NORM_MINMAX); imshow("normalize",dst);
二十、图像缩放
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat zoomin, zoomout; int h = img.rows; int w = img.cols; cv::resize(img, zoomin, Size(w/2,h/2),0,0,INTER_LINEAR); imshow("zoomin", zoomin); cv::resize(img, zoomout, Size(w * 2, h * 2), 0, 0, INTER_LINEAR); imshow("zoomout", zoomout);
二十一、图像翻转
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; flip(img, dst, 0);//上下翻转 imshow("flip0", dst); flip(img, dst, 1);//左右翻转 imshow("flip1", dst); flip(img, dst, -1);//180°旋转 imshow("flip-1", dst); int h = img.rows; int w = img.cols; Mat M = getRotationMatrix2D(Point2f(w / 2, h / 2), 45, 1.0); double cos = abs(M.at<double>(0, 0)); double sin = abs(M.at<double>(0, 1)); int nw = cos * w + sin * h; int nh = sin * w + cos * h; M.at<double>(0, 2) = M.at<double>(0, 2) + (nw / 2 - w / 2); M.at<double>(1, 2) = M.at<double>(1, 2) + (nh / 2 - h / 2); warpAffine(img, dst, M, Size(nw,nh),INTER_LINEAR,0,Scalar(255,0,0)); imshow("rotate", dst);
二十二、图像直方图
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; // 三通道分离 std::vector<Mat> bgr_plane; split(img, bgr_plane); // 定义参数变量 const int channels[1] = { 0 }; const int bins[1] = { 256 }; float hranges[2] = { 0,255 }; const float* ranges[1] = { hranges }; Mat b_hist; Mat g_hist; Mat r_hist; // 计算Blue, Green, Red通道的直方图 calcHist(&bgr_plane[0], 1, 0, Mat(), b_hist, 1, bins, ranges); calcHist(&bgr_plane[1], 1, 0, Mat(), g_hist, 1, bins, ranges); calcHist(&bgr_plane[2], 1, 0, Mat(), r_hist, 1, bins, ranges); // 显示直方图 int hist_w = 512; int hist_h = 400; int bin_w = cvRound((double)hist_w / bins[0]); Mat histImage = Mat::zeros(hist_h, hist_w, CV_8UC3); // 归一化直方图数据 normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat()); normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat()); normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat()); // 绘制直方图曲线 for (int i = 1; i < bins[0]; i++) { line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(b_hist.at<float>(i - 1))), Point(bin_w*(i), hist_h - cvRound(b_hist.at<float>(i))), Scalar(255, 0, 0), 2, 8, 0); line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(g_hist.at<float>(i - 1))), Point(bin_w*(i), hist_h - cvRound(g_hist.at<float>(i))), Scalar(0, 255, 0), 2, 8, 0); line(histImage, Point(bin_w*(i - 1), hist_h - cvRound(r_hist.at<float>(i - 1))), Point(bin_w*(i), hist_h - cvRound(r_hist.at<float>(i))), Scalar(0, 0, 255), 2, 8, 0); } // 显示直方图 namedWindow("Histogram Demo", WINDOW_AUTOSIZE); imshow("Histogram Demo", histImage);
二十三、二维直方图
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; // 2D 直方图 Mat hsv, hs_hist; cvtColor(img, hsv, COLOR_BGR2HSV); int hbins = 30, sbins = 32; int hist_bins[] = { hbins, sbins }; float h_range[] = { 0, 180 }; float s_range[] = { 0, 256 }; const float* hs_ranges[] = { h_range, s_range }; int hs_channels[] = { 0, 1 }; calcHist(&hsv, 1, hs_channels, Mat(), hs_hist, 2, hist_bins, hs_ranges, true, false); double maxVal = 0; minMaxLoc(hs_hist, 0, &maxVal, 0, 0); int scale = 10; Mat hist2d_image = Mat::zeros(sbins*scale, hbins * scale, CV_8UC3); for (int h = 0; h < hbins; h++) { for (int s = 0; s < sbins; s++) { float binVal = hs_hist.at<float>(h, s); int intensity = cvRound(binVal * 255 / maxVal); rectangle(hist2d_image, Point(h*scale, s*scale), Point((h + 1)*scale - 1, (s + 1)*scale - 1), Scalar::all(intensity), -1); } } applyColorMap(hist2d_image, hist2d_image, COLORMAP_JET); imshow("H-S Histogram", hist2d_image); imwrite("D:/hist_2d.png", hist2d_image);
二十四、直方图均衡化
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat gray; cvtColor(img, gray, COLOR_BGR2GRAY); imshow("灰度图像", gray); Mat dst; equalizeHist(gray, dst);//只支持单通道灰度图像 imshow("直方图均衡化演示", dst);
二十五、直方图均衡化
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat gray; cvtColor(img, gray, COLOR_BGR2GRAY); imshow("灰度图像", gray); Mat dst; equalizeHist(gray, dst);//只支持单通道灰度图像 imshow("直方图均衡化演示", dst);
二十六、图像卷积
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; blur(img, dst, Size(15, 15), Point(-1, -1)); imshow("图像卷积", dst);
二十七、图像卷积
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; blur(img, dst, Size(15, 15), Point(-1, -1)); imshow("图像卷积", dst);
二十八、高斯模糊
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; GaussianBlur(img, dst, Size(0, 0), 15);//ksize正数奇数 imshow("高斯模糊", dst);
二十九、高斯双边模糊
QString appPath = QCoreApplication::applicationDirPath(); imagePath = appPath + "/A.jpg"; img = cv::imread(imagePath.toStdString()); if (img.empty()) return; Mat dst; bilateralFilter(img, dst, 0, 100, 10); imshow("双边模糊", dst);
三十、人脸识别
std::string root_dir = "D:/opencv/sources/samples/dnn/face_detector/"; dnn::Net net = dnn::readNetFromTensorflow(root_dir + "opencv_face_detector_uint8.pb", root_dir + "opencv_face_detector.pbtxt"); //VideoCapture capture("D:/code/opencv_tutorial_data/images/example_dsh.mp4"); VideoCapture capture(0, CAP_DSHOW); Mat frame; while (true) { capture.read(frame); if (frame.empty()) { break; } Mat blob = dnn::blobFromImage(frame, 1.0, Size(300, 300), Scalar(104, 177, 123), false, false); net.setInput(blob);// NCHW Mat probs = net.forward(); Mat detectionMat(probs.size[2], probs.size[3], CV_32F, probs.ptr<float>()); // 解析结果 for (int i = 0; i < detectionMat.rows; i++) { float confidence = detectionMat.at<float>(i, 2); if (confidence > 0.5) { int x1 = static_cast<int>(detectionMat.at<float>(i, 3)*frame.cols); int y1 = static_cast<int>(detectionMat.at<float>(i, 4)*frame.rows); int x2 = static_cast<int>(detectionMat.at<float>(i, 5)*frame.cols); int y2 = static_cast<int>(detectionMat.at<float>(i, 6)*frame.rows); Rect box(x1, y1, x2 - x1, y2 - y1); rectangle(frame, box, Scalar(0, 0, 255), 2, 8, 0); } } imshow("人脸检测演示", frame); int c = waitKey(1); if (c == 27) { // 退出 break; } }
