opencv::视频人脸检测

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 -;
    }
    if (!eye_cascader.load(eyefile)) {
        printf("could not load eye feature data...\n");
        return -;
    }
    namedWindow("camera-demo", CV_WINDOW_AUTOSIZE);
    VideoCapture capture(); //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, , , Size(, ));
        for (size_t t = ; 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 / ;

            Mat faceROI = frame(roi);
            eye_cascader.detectMultiScale(faceROI, eyes, 1.2, , , Size(, ));
            for (size_t k = ; 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(, , ), , , );
            }
            rectangle(frame, faces[static_cast<int>(t)], Scalar(, , ), , , );
        }
        imshow("camera-demo", frame);
        char c = waitKey();
        if (c == ) {
            break;
        }
    }
    waitKey();
    return ;
}