OpenCV - 人脸检测(face detection) 代码
人脸检测(face detection) 代码
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 ); 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 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%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 ); }
