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// WARNING: this sample is under construction! Use it on your own risk.
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#include "opencv2/objdetect/objdetect.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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#include "opencv2/imgproc/imgproc.hpp" |
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#include <iostream> |
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#include <stdio.h> |
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using namespace std; |
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using namespace cv; |
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static void help() |
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{ |
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cout << "\nThis program demonstrates the multi cascade recognizer. It is a generalization of facedetect sample.\n\n" |
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"Usage: ./multicascadeclassifier \n" |
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" --cascade1=<cascade_path> this is the primary trained classifier such as frontal face\n" |
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" [--cascade2=[this an optional secondary classifier such as profile face or eyes]]\n" |
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" input video or image\n\n" |
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"Example: ./multicascadeclassifier --cascade1=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --cascade2=\"../../data/haarcascades/haarcascade_eye.xml\"\n\n" |
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"Using OpenCV version " << CV_VERSION << endl << endl; |
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} |
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void DetectAndDraw(Mat& img, CascadeClassifier& cascade); |
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String cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml"; |
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String nestedCascadeName = "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml"; |
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int main( int argc, const char** argv ) |
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{ |
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CvCapture* capture = 0; |
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Mat frame, image; |
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if (argc == 0) |
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{ |
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help(); |
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return 0; |
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} |
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const String cascadeOpt = "--cascade1="; |
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size_t cascadeOptLen = cascadeOpt.length(); |
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string inputName; |
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for( int i = 1; i < argc; i++ ) |
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{ |
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cout << "Processing argument #" << i << ": " << argv[i] << endl; |
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if( cascadeOpt.compare( 0, cascadeOptLen, argv[i], cascadeOptLen ) == 0 ) |
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{ |
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cascadeName.assign( argv[i] + cascadeOptLen ); |
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cout << " from which we have cascadeName= " << cascadeName << endl; |
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} |
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else if( argv[i][0] == '-' ) |
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{ |
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cerr << "WARNING: Unknown option " << argv[i] << endl; |
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} |
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else |
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inputName.assign( argv[i] ); |
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} |
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CascadeClassifier cascade; |
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if( !cascade.load( cascadeName ) ) |
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{ |
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cerr << "ERROR: Could not load cascade classifier \"" << cascadeName << "\"" << endl; |
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help(); |
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return -1; |
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} |
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if( inputName.size() ) |
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{ |
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image = imread( inputName, 1 ); |
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if( image.empty() ) |
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{ |
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capture = cvCaptureFromAVI( inputName.c_str() ); |
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if( !capture ) |
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cout << "Capture from AVI don't work" << endl; |
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} |
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} |
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else |
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{ |
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cout << "Please provide input file." << endl; |
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return -1; |
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} |
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cvNamedWindow( "result", 1 ); |
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if( capture ) |
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{ |
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for(;;) |
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{ |
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IplImage* iplImg = cvQueryFrame( capture ); |
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frame = iplImg; |
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if( frame.empty() ) |
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break; |
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DetectAndDraw( frame, cascade ); |
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if( waitKey( 10 ) >= 0 ) |
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goto _cleanup_; |
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} |
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waitKey(0); |
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_cleanup_: |
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cvReleaseCapture( &capture ); |
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} |
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else if( !image.empty() ) |
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{ |
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DetectAndDraw( image, cascade ); |
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waitKey(0); |
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} |
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else |
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{ |
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cout << "Please provide correct input file." << endl; |
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} |
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cvDestroyWindow("result"); |
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return 0; |
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} |
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void DetectAndDraw( Mat& img, CascadeClassifier& cascade) |
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{ |
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int i = 0; |
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double t = 0; |
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vector<Rect> faces; |
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const static Scalar colors[] = { CV_RGB(0,0,255), |
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CV_RGB(0,128,255), |
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CV_RGB(0,255,255), |
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CV_RGB(0,255,0), |
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CV_RGB(255,128,0), |
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CV_RGB(255,255,0), |
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CV_RGB(255,0,0), |
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CV_RGB(255,0,255)} ; |
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Mat gray; |
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Mat frame( cvRound(img.rows), cvRound(img.cols), CV_8UC1 ); |
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cvtColor( img, gray, CV_BGR2GRAY ); |
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resize( gray, frame, frame.size(), 0, 0, INTER_LINEAR ); |
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equalizeHist( frame, frame ); |
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t = (double)cvGetTickCount(); |
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cascade.detectMultiScale( frame, faces, |
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1.1, 2, 0 |
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//|CV_HAAR_FIND_BIGGEST_OBJECT
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//|CV_HAAR_DO_ROUGH_SEARCH
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|CV_HAAR_SCALE_IMAGE |
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, |
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Size(30, 30) ); |
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t = (double)cvGetTickCount() - t; |
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printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) ); |
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for( vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++ ) |
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{ |
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Point center; |
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Scalar color = colors[i%8]; |
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int radius; |
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center.x = cvRound(r->x + r->width*0.5); |
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center.y = cvRound(r->y + r->height*0.5); |
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radius = (int)(cvRound(r->width + r->height)*0.25); |
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circle( img, center, radius, color, 3, 8, 0 ); |
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} |
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cv::imshow( "result", img ); |
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} |
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