opencv 人脸识别

// face_recog_from_picture.cpp: 定义控制台应用程序的入口点。
#include<opencv2/opencv.hpp>
#include<iostream>
using namespace std;
using namespace cv;
int main(int argc,char *argv[])
{
  Mat img = imread("she.jpg");
  namedWindow("display");
  imshow("display", img); 
  /*********************************** 1.加载人脸检测器  ******************************/
  // 建立级联分类器
  CascadeClassifier cascade;
  // 加载训练好的 人脸检测器（.xml）
  const string path = "./xml/haarcascade_frontalface_alt.xml";
  if ( ! cascade.load(path))
  {
    cout << "cascade load failed!\n";
  }
  //计时
  double t = 0;
  t = (double)getTickCount();
  /*********************************** 2.人脸检测 ******************************/
  vector<Rect> faces(0);
  cascade.detectMultiScale(img, faces, 1.1, 5, 0 ,Size(30,30));
  cout << "detect face number is :" << faces.size() << endl;
  /********************************  3.显示人脸矩形框 ******************************/
  if (faces.size() > 0)
  {
    for (size_t i = 0;i < faces.size();i++)
    {
      rectangle(img, faces[i], Scalar(150, 0, 0), 3, 8, 0); 
    }
  }
  else cout << "未检测到人脸" << endl;
  t = (double)getTickCount() - t;  //getTickCount():  Returns the number of ticks per second.
  cout << "检测人脸用时：" << t * 1000 / getTickFrequency() << "ms (不计算加载模型的时间）" << endl;
  namedWindow("face_detect");
  double scale = 0.8;
  Size dsize = Size(img.cols*scale, img.rows*scale);
  Mat img2 = Mat(dsize, CV_32S);
  resize(img, img2, dsize);
  imshow("face_detect", img2);
  while(waitKey(0)!='k') ;
  destroyWindow("display");
  destroyWindow("face_detect");
    return 0;
}