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OpenCV实现人脸检测(face detection) 代码 - C++教程 - 编程入门网
2016-12-30 14:00:45   来源:   评论:0 点击:

人脸检测使用detectMultiScale函数和CascadeClassifier(级联分类器);需要注意的是: VS2012, 使用低版本的OpenCV(如2 4 3)会出现问题, 导

人脸检测使用detectMultiScale函数和CascadeClassifier(级联分类器);

需要注意的是: VS2012, 使用低版本的OpenCV(如2.4.3)会出现问题, 导致CascadeClassifier无法加载(load)模型;

升级至OpenCV2.4.7即可, 并使用VS2012的库;

代码如下(VS2012):

#include <opencv.hpp>        #include <iostream>  #include <iterator>  #include <string>  #include <stdio.h>        using namespace std;  using namespace cv;        void detectAndDraw( Mat& img, CascadeClassifier& cascade,                      CascadeClassifier& nestedCascade,                      double scale, bool tryflip );        string cascadeName = "haarcascade_frontalface_alt.xml";  string nestedCascadeName = "haarcascade_eye_tree_eyeglasses.xml";        int main( int argc, const char** argv )  {      cv::CascadeClassifier cascade, nestedCascade;      double scale = 1;      bool tryflip = true;      cv::Mat image = imread( "girls.jpg", 1 );      cascade.load( cascadeName );      nestedCascade.load( nestedCascadeName );      detectAndDraw( image, cascade, nestedCascade, scale, tryflip);      cv::waitKey(0);      return 0;  }        void detectAndDraw( Mat& img, CascadeClassifier& cascade,                      CascadeClassifier& nestedCascade,                      double scale, bool tryflip )  {      int i = 0;      double t = 0;      vector<Rect> faces, faces2;      const static Scalar colors[] =  { CV_RGB(0,0,255),          CV_RGB(0,128,255),          CV_RGB(0,255,255),          CV_RGB(0,255,0),          CV_RGB(255,128,0),          CV_RGB(255,255,0),          CV_RGB(255,0,0),          CV_RGB(255,0,255)} ;      Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );            cvtColor( img, gray, CV_BGR2GRAY );      resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );      equalizeHist( smallImg, smallImg );      // 返回栏目页:http://www.bianceng.cn/Programming/cplus/    t = (double)cvGetTickCount();      cascade.detectMultiScale( smallImg, faces,          1.1, 2, 0          //|CV_HAAR_FIND_BIGGEST_OBJECT          |CV_HAAR_DO_ROUGH_SEARCH //效果最好          //|CV_HAAR_SCALE_IMAGE          //|CV_HAAR_DO_CANNY_PRUNING          ,          Size(30, 30) );      if( tryflip )      {          flip(smallImg, smallImg, 1); //翻转          cascade.detectMultiScale( smallImg, faces2,                                   1.1, 2, 0                                   //|CV_HAAR_FIND_BIGGEST_OBJECT                                   |CV_HAAR_DO_ROUGH_SEARCH                                   //|CV_HAAR_SCALE_IMAGE                                   //|CV_HAAR_DO_CANNY_PRUNING                                   ,                                   Size(30, 30) );          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;      printf( "detection time = %g msn", 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%8];          int radius;                double aspect_ratio = (double)r->width/r->height;          if( 0.75 < aspect_ratio && aspect_ratio < 1.3 )          {              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, 3, 8, 0 );          }          else            rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),                         cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),                         color, 3, 8, 0);          if( nestedCascade.empty() )              continue;          smallImgROI = smallImg(*r);          nestedCascade.detectMultiScale( smallImgROI, nestedObjects,              1.1, 2, 0              //|CV_HAAR_FIND_BIGGEST_OBJECT              //|CV_HAAR_DO_ROUGH_SEARCH              //|CV_HAAR_DO_CANNY_PRUNING              |CV_HAAR_SCALE_IMAGE              ,              Size(30, 30) );          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, 3, 8, 0 );          }      }      cv::imshow( "result", img );  }

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