人脸识别中的检测（在Opencv中加入了QT）

 #include <opencv2/highgui/highgui.hpp>
 #include <opencv2/imgproc/imgproc.hpp>
 #include <opencv2/core/core.hpp>
 #include <opencv2/objdetect/objdetect.hpp>
 #include <QDebug>

 using namespace cv;

 void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                     CascadeClassifier& nestedCascade,
                     double scale, bool tryflip );

 int main()
 {
     VideoCapture cap();    //打开默认摄像头
     if(!cap.isOpened())
     {
         return -;
     }
     Mat frame;
     Mat edges;

     CascadeClassifier cascade, nestedCascade;
     bool stop = false;
     //训练好的文件名称，放置在可执行文件同目录下
     cascade.load("haarcascade_frontalface_alt.xml");
     nestedCascade.load("haarcascade_eye_tree_eyeglasses.xml");
     while(!stop)
     {
         cap>>frame;
         detectAndDraw( frame, cascade, nestedCascade,, );
         if(waitKey() >=)
             stop = true;
     }
     return ;
 }
 void detectAndDraw( Mat& img, CascadeClassifier& cascade,
                     CascadeClassifier& nestedCascade,
                     double scale, bool tryflip )
 {
     int i = ;
     double t = ;
     //建立用于存放人脸的向量容器
     vector<Rect> faces, faces2;
     //定义一些颜色，用来标示不同的人脸
     const static Scalar colors[] =  { CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,),
         CV_RGB(,,)} ;
     //建立缩小的图片，加快检测速度
     //nt cvRound (double value) 对一个double型的数进行四舍五入，并返回一个整型数！
     Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
     //转成灰度图像，Harr特征基于灰度图
     cvtColor( img, gray, CV_BGR2GRAY );
     //改变图像大小，使用双线性差值
     resize( gray, smallImg, smallImg.size(), , , INTER_LINEAR );
     //变换后的图像进行直方图均值化处理
     equalizeHist( smallImg, smallImg );

     //程序开始和结束插入此函数获取时间，经过计算求得算法执行时间
     t = (double)cvGetTickCount();
     //检测人脸
     //detectMultiScale函数中smallImg表示的是要检测的输入图像为smallImg，faces表示检测到的人脸目标序列，1.1表示
     //每次图像尺寸减小的比例为1.1，2表示每一个目标至少要被检测到3次才算是真的目标(因为周围的像素和不同的窗口大
     //小都可以检测到人脸),CV_HAAR_SCALE_IMAGE表示不是缩放分类器来检测，而是缩放图像，Size(30, 30)为目标的
     //最小最大尺寸
     cascade.detectMultiScale( smallImg, faces,
         1.1, ,
         //|CV_HAAR_FIND_BIGGEST_OBJECT
         //|CV_HAAR_DO_ROUGH_SEARCH
         |CV_HAAR_SCALE_IMAGE
         ,
         Size(, ));
     //如果使能，翻转图像继续检测
     if( tryflip )
     {
         flip(smallImg, smallImg, );
         cascade.detectMultiScale( smallImg, faces2,
                                  1.1, ,
                                  //|CV_HAAR_FIND_BIGGEST_OBJECT
                                  //|CV_HAAR_DO_ROUGH_SEARCH
                                  |CV_HAAR_SCALE_IMAGE
                                  ,
                                  Size(, ) );
         for( vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
         {
             faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
         }
     }
     t = (double)cvGetTickCount() - t;
  //   qDebug( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
     for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
     {
         Mat smallImgROI;
         vector<Rect> nestedObjects;
         Point center;
         Scalar color = colors[i%];
         int radius;

         double aspect_ratio = (double)r->width/r->height;
         if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )
         {
             //标示人脸时在缩小之前的图像上标示，所以这里根据缩放比例换算回去
             center.x = cvRound((r->x + r->width*0.5)*scale);
             center.y = cvRound((r->y + r->height*0.5)*scale);
             radius = cvRound((r->width + r->height)*0.25*scale);
             circle( img, center, radius, color, , ,  );
         }
         else
             rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
                        cvPoint(cvRound((r->x + r->width-)*scale), cvRound((r->y + r->height-)*scale)),
                        color, , , );
         if( nestedCascade.empty() )
             continue;
         smallImgROI = smallImg(*r);
         //同样方法检测人眼
         nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
             1.1, ,
             //|CV_HAAR_FIND_BIGGEST_OBJECT
             //|CV_HAAR_DO_ROUGH_SEARCH
             //|CV_HAAR_DO_CANNY_PRUNING
             |CV_HAAR_SCALE_IMAGE
             ,
             Size(, ) );
         for( vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
         {
             center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
             center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
             radius = cvRound((nr->width + nr->height)*0.25*scale);
             circle( img, center, radius, color, , ,  );
         }
     }
     cv::imshow( "result", img );
 }