视频流抓取人脸和眼睛
#include<opencv2/opencv.hpp> #include<iostream> using namespace cv; using namespace std; CascadeClassifier face_cascader; //分类器 CascadeClassifier eye_cascader; String facefile = "D:/Appinstall/opencv-3.4.4_vc15/etc/haarcascades/haarcascade_frontalface_alt.xml"; String eyefile = "D:/Appinstall/opencv-3.4.4_vc15/etc/haarcascades/haarcascade_eye.xml"; int main(int argc, char** argv) { if (!face_cascader.load(facefile)) { printf("could not load face feature data...\n"); return -1; } if (!eye_cascader.load(eyefile)) { printf("could not load eye feature data...\n"); return -1; } namedWindow("camera-demo", CV_WINDOW_AUTOSIZE); VideoCapture capture(0); //读取摄像头视频流 Mat frame; Mat gray; vector<Rect> faces; vector<Rect> eyes; while (capture.read(frame)) { cvtColor(frame, gray, COLOR_BGR2GRAY); equalizeHist(gray, gray); face_cascader.detectMultiScale(gray, faces, 1.2, 3, 0, Size(30, 30)); for (size_t t = 0; t < faces.size(); t++) { Rect roi; roi.x = faces[static_cast<int>(t)].x; roi.y = faces[static_cast<int>(t)].y; roi.width = faces[static_cast<int>(t)].width; roi.height = faces[static_cast<int>(t)].height / 2; Mat faceROI = frame(roi); eye_cascader.detectMultiScale(faceROI, eyes, 1.2, 3, 0, Size(20, 20)); for (size_t k = 0; k < eyes.size(); k++) { Rect rect; rect.x = faces[static_cast<int>(t)].x + eyes[k].x; rect.y = faces[static_cast<int>(t)].y + eyes[k].y; rect.width = eyes[k].width; rect.height = eyes[k].height; rectangle(frame, rect, Scalar(0, 255, 0), 2, 8, 0); } rectangle(frame, faces[static_cast<int>(t)], Scalar(0, 0, 255), 2, 8, 0); } imshow("camera-demo", frame); char c = waitKey(30); if (c == 27) { break; } } waitKey(0); return 0; }