#include "opencv2/objdetect.hpp" #include "opencv2/highgui.hpp" #include "opencv2/imgproc.hpp" #include "opencv2/core/utility.hpp" #include "opencv2/highgui/highgui_c.h" #include #include #include #include using namespace std; using namespace cv; static void help() { cout << "\nThis program demonstrates the smile detector.\n" "Usage:\n" "./smiledetect [--cascade= this is the frontal face classifier]\n" " [--smile-cascade=[]]\n" " [--scale=]\n" " [--try-flip]\n" " [video_filename|camera_index]\n\n" "Example:\n" "./smiledetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --smile-cascade=\"../../data/haarcascades/haarcascade_smile.xml\" --scale=2.0\n\n" "During execution:\n\tHit any key to quit.\n" "\tUsing OpenCV version " << CV_VERSION << "\n" << endl; } void detectAndDraw( Mat& img, CascadeClassifier& cascade, CascadeClassifier& nestedCascade, double scale, bool tryflip ); string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml"; string nestedCascadeName = "../../data/haarcascades/haarcascade_smile.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 = "--smile-cascade"; size_t nestedCascadeOptLen = nestedCascadeOpt.length(); const string tryFlipOpt = "--try-flip"; size_t tryFlipOptLen = tryFlipOpt.length(); string inputName; bool tryflip = false; 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 ); } 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( tryFlipOpt.compare( 0, tryFlipOptLen, argv[i], tryFlipOptLen ) == 0 ) { tryflip = true; cout << " will try to flip image horizontally to detect assymetric objects\n"; } else if( argv[i][0] == '-' ) { cerr << "WARNING: Unknown option " << argv[i] << endl; } else inputName.assign( argv[i] ); } if( !cascade.load( cascadeName ) ) { cerr << "ERROR: Could not load face cascade" << endl; help(); return -1; } if( !nestedCascade.load( nestedCascadeName ) ) { cerr << "ERROR: Could not load smile cascade" << endl; help(); 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() ) { capture = cvCaptureFromAVI( inputName.c_str() ); if(!capture) cout << "Capture from AVI didn't work" << endl; } cvNamedWindow( "result", 1 ); if( capture ) { cout << "In capture ..." << endl; cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl; for(;;) { IplImage* iplImg = cvQueryFrame( capture ); frame = cv::cvarrToMat(iplImg); if( frame.empty() ) break; if( iplImg->origin == IPL_ORIGIN_TL ) frame.copyTo( frameCopy ); else flip( frame, frameCopy, 0 ); detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip ); if( waitKey( 10 ) >= 0 ) goto _cleanup_; } waitKey(0); _cleanup_: cvReleaseCapture( &capture ); } else { cerr << "ERROR: Could not initiate capture" << endl; help(); return -1; } cvDestroyWindow("result"); return 0; } void detectAndDraw( Mat& img, CascadeClassifier& cascade, CascadeClassifier& nestedCascade, double scale, bool tryflip) { int i = 0; vector 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, COLOR_BGR2GRAY ); resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR ); equalizeHist( smallImg, smallImg ); cascade.detectMultiScale( smallImg, faces, 1.1, 2, 0 //|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_DO_ROUGH_SEARCH |CASCADE_SCALE_IMAGE , Size(30, 30) ); if( tryflip ) { flip(smallImg, smallImg, 1); cascade.detectMultiScale( smallImg, faces2, 1.1, 2, 0 //|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_DO_ROUGH_SEARCH |CASCADE_SCALE_IMAGE , Size(30, 30) ); for( vector::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)); } } for( vector::iterator r = faces.begin(); r != faces.end(); r++, i++ ) { Mat smallImgROI; vector 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); const int half_height=cvRound((float)r->height/2); r->y=r->y + half_height; r->height = half_height; smallImgROI = smallImg(*r); nestedCascade.detectMultiScale( smallImgROI, nestedObjects, 1.1, 0, 0 //|CASCADE_FIND_BIGGEST_OBJECT //|CASCADE_DO_ROUGH_SEARCH //|CASCADE_DO_CANNY_PRUNING |CASCADE_SCALE_IMAGE , Size(30, 30) ); // The number of detected neighbors depends on image size (and also illumination, etc.). The // following steps use a floating minimum and maximum of neighbors. Intensity thus estimated will be //accurate only after a first smile has been displayed by the user. const int smile_neighbors = (int)nestedObjects.size(); static int max_neighbors=-1; static int min_neighbors=-1; if (min_neighbors == -1) min_neighbors = smile_neighbors; max_neighbors = MAX(max_neighbors, smile_neighbors); // Draw rectangle on the left side of the image reflecting smile intensity float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1); int rect_height = cvRound((float)img.rows * intensityZeroOne); CvScalar col = CV_RGB((float)255 * intensityZeroOne, 0, 0); rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1); } cv::imshow( "result", img ); }