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 );

 }