人脸检测or五官检测

总结：

If you have a detected face (frontal face) a rough positions of the left and right eye regions are then estimated using anthropometric relations as show below.

#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"#include <iostream>
#include <stdio.h>using namespace std;
using namespace cv;static void help()
{cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n""This classifier can recognize many ~rigid objects, it's most known use is for faces.\n""Usage:\n""./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n""   [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n""   [--scale=<image scale greater or equal to 1, try 1.3 for example>\n""   [filename|camera_index]\n\n""see facedetect.cmd for one call:\n""./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye.xml\" --scale=1.3 \n""Hit any key to quit.\n""Using OpenCV version " << CV_VERSION << "\n" << endl;
}void detectAndDraw( Mat& img,CascadeClassifier& cascade, CascadeClassifier& nestedCascade,double scale);String cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml";
String nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";int main( int argc, const char** argv )
{CvCapture* capture = 0;Mat frame, frameCopy, image;const String scaleOpt = "--scale=";size_t scaleOptLen = scaleOpt.length();const String cascadeOpt = "--cascade=";size_t cascadeOptLen = cascadeOpt.length();const String nestedCascadeOpt = "--nested-cascade";size_t nestedCascadeOptLen = nestedCascadeOpt.length();String inputName;help();CascadeClassifier cascade, nestedCascade;double scale = 1;for( int i = 1; i < argc; i++ ){cout << "Processing " << i << " " <<  argv[i] << endl;if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 ){cascadeName.assign( argv[i] + cascadeOptLen );cout << "  from which we have cascadeName= " << cascadeName << endl;}else if( nestedCascadeOpt.compare( 0, nestedCascadeOptLen, argv[i], nestedCascadeOptLen ) == 0 ){if( argv[i][nestedCascadeOpt.length()] == '=' )nestedCascadeName.assign( argv[i] + nestedCascadeOpt.length() + 1 );if( !nestedCascade.load( nestedCascadeName ) )cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;}else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 ){if( !sscanf( argv[i] + scaleOpt.length(), "%lf", &scale ) || scale < 1 )scale = 1;cout << " from which we read scale = " << scale << endl;}else if( argv[i][0] == '-' ){cerr << "WARNING: Unknown option %s" << argv[i] << endl;}elseinputName.assign( argv[i] );}if( !cascade.load( cascadeName ) ){cerr << "ERROR: Could not load classifier cascade" << endl;cerr << "Usage: facedetect [--cascade=<cascade_path>]\n""   [--nested-cascade[=nested_cascade_path]]\n""   [--scale[=<image scale>\n""   [filename|camera_index]\n" << endl ;return -1;}if( inputName.empty() || (isdigit(inputName.c_str()[0]) && inputName.c_str()[1] == '\0') ){capture = cvCaptureFromCAM( inputName.empty() ? 0 : inputName.c_str()[0] - '0' );int c = inputName.empty() ? 0 : inputName.c_str()[0] - '0' ;if(!capture) cout << "Capture from CAM " <<  c << " didn't work" << endl;}else if( inputName.size() ){image = imread( inputName, 1 );if( image.empty() ){capture = cvCaptureFromAVI( inputName.c_str() );if(!capture) cout << "Capture from AVI didn't work" << endl;}}else{image = imread( "lena.jpg", 1 );if(image.empty()) cout << "Couldn't read lena.jpg" << endl;}cvNamedWindow( "result", 1 );if( capture ){cout << "In capture ..." << endl;for(;;){IplImage* iplImg = cvQueryFrame( capture );frame = iplImg;if( frame.empty() )break;if( iplImg->origin == IPL_ORIGIN_TL )frame.copyTo( frameCopy );elseflip( frame, frameCopy, 0 );detectAndDraw( frameCopy, cascade, nestedCascade, scale );if( waitKey( 10 ) >= 0 )goto _cleanup_;}waitKey(0);_cleanup_:cvReleaseCapture( &capture );}else{cout << "In image read" << endl;if( !image.empty() ){detectAndDraw( image, cascade, nestedCascade, scale );waitKey(0);}else if( !inputName.empty() ){/* assume it is a text file containing thelist of the image filenames to be processed - one per line */FILE* f = fopen( inputName.c_str(), "rt" );if( f ){char buf[1000+1];while( fgets( buf, 1000, f ) ){int len = (int)strlen(buf), c;while( len > 0 && isspace(buf[len-1]) )len--;buf[len] = '\0';cout << "file " << buf << endl;image = imread( buf, 1 );if( !image.empty() ){detectAndDraw( image, cascade, nestedCascade, scale );c = waitKey(0);if( c == 27 || c == 'q' || c == 'Q' )break;}else{cerr << "Aw snap, couldn't read image " << buf << endl;}}fclose(f);}}}cvDestroyWindow("result");return 0;
}void detectAndDraw( Mat& img,CascadeClassifier& cascade, CascadeClassifier& nestedCascade,double scale)
{int i = 0;double t = 0;vector<Rect> faces;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|CV_HAAR_SCALE_IMAGE,Size(30, 30) );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;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 );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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