opencv real-time face detection

Camera real-time face detection

Requires using the parameters of the face training library;
opencv3.4.14资源包
将opencv源代码中：./data/haarcascades Folder assignment worksbin目录下.
opencvFor environment construction, you can see my previous articles:OpenCV安装、QT、VS配置项目设置

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

void PrintMs(const char* text = "")
{
    
	static long long last = 0;
	long long cur = getTickCount();
	if (last == 0)
	{
    
		last = cur;
		return;
	}
	long long ms = 0;
	ms = ((double)(cur - last) / getTickFrequency()) * 1000;
	if (*text != 0)
	{
    
		printf("%s = %dms\n", text, ms);
	}
	last = getTickCount();
}

int main(int argc, char** argv) {
    
	String cascadeFilePath = "./haarcascades/haarcascade_frontalface_alt.xml";
	CascadeClassifier face_cascade;
	if (!face_cascade.load(cascadeFilePath)) {
    
		printf("could not load haar data...\n");
		return -1;
	}
	Mat src, gray_src;
	VideoCapture cam(0);
	if (!cam.isOpened())
	{
    
		cout << "cam open failed!" << endl;
		getchar();
		return -1;
	}
	while (true)
	{
    
		PrintMs();
		cam.read(src);
		if (src.empty()) break;
		flip(src, src, 1);
		cvtColor(src, gray_src, COLOR_BGR2GRAY);
		equalizeHist(gray_src, gray_src); // 直方图均衡化,Facilitates face detection
		imshow("input image", src);

		vector<Rect> faces;
		face_cascade.detectMultiScale(gray_src, faces, 1.1, 2, 0, Size(30, 30));
		for (size_t t = 0; t < faces.size(); t++) {
    
			rectangle(src, faces[t], Scalar(0, 0, 255), 2, 8, 0);
		}
		namedWindow("output", CV_WINDOW_AUTOSIZE);
		imshow("output", src);
		PrintMs("face detect time: ");  // AMD5800H 120ms左右

		if (waitKey(5) == 'q') break;
	}
	

	waitKey(0);
	return 0;
}