diff --git a/samples/c/smiledetect.cpp b/samples/c/smiledetect.cpp index dd2b03edf4..63254dca8c 100644 --- a/samples/c/smiledetect.cpp +++ b/samples/c/smiledetect.cpp @@ -14,12 +14,12 @@ static void help() cout << "\nThis program demonstrates the smile detector.\n" "Usage:\n" "./smiledetect [--cascade= this is the frontal face classifier]\n" - " [--smile-cascade[=smile_cascade_path]]\n" - " [--scale=]\n" + " [--smile-cascade=[]]\n" + " [--scale=]\n" " [--try-flip]\n" - " [filename|camera_index]\n\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=1.3\n\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; } @@ -31,10 +31,6 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade, string cascadeName = "../../data/haarcascades/haarcascade_frontalface_alt.xml"; string nestedCascadeName = "../../data/haarcascades/haarcascade_smile.xml"; -// The number of detected neighbors depends on image size, these are for performing an approximate mapping to a maximum number of neighbors -const float coef1 = 0.3190; -const float coef2 = -48.7187; - int main( int argc, const char** argv ) { @@ -68,8 +64,6 @@ int main( int argc, const char** argv ) { 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 ) { @@ -92,7 +86,13 @@ int main( int argc, const char** argv ) if( !cascade.load( cascadeName ) ) { - cerr << "ERROR: Could not load classifier cascade" << endl; + 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; } @@ -105,17 +105,8 @@ int main( int argc, const char** argv ) } 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; + capture = cvCaptureFromAVI( inputName.c_str() ); + if(!capture) cout << "Capture from AVI didn't work" << endl; } cvNamedWindow( "result", 1 ); @@ -123,6 +114,8 @@ int main( int argc, const char** argv ) 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 ); @@ -147,43 +140,9 @@ _cleanup_: } else { - cout << "In image read" << endl; - if( !image.empty() ) - { - detectAndDraw( image, cascade, nestedCascade, scale, tryflip ); - waitKey(0); - } - else if( !inputName.empty() ) - { - /* assume it is a text file containing the - list 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, tryflip ); - c = waitKey(0); - if( c == 27 || c == 'q' || c == 'Q' ) - break; - } - else - { - cerr << "Aw snap, couldn't read image " << buf << endl; - } - } - fclose(f); - } - } + cerr << "ERROR: Could not initiate capture" << endl; + help(); + return -1; } cvDestroyWindow("result"); @@ -206,8 +165,6 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade, CV_RGB(255,0,255)} ; Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 ); - const int max_neighbors = MAX(0, cvRound((float)coef1*smallImg.cols + coef2)); - cvtColor( img, gray, CV_BGR2GRAY ); resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR ); equalizeHist( smallImg, smallImg ); @@ -234,6 +191,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade, 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; @@ -254,8 +212,6 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade, 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; const int half_height=cvRound((float)r->height/2); r->y=r->y + half_height; @@ -270,13 +226,21 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade, , Size(30, 30) ); - // Draw rectangle reflecting confidence + // 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 = nestedObjects.size(); - cout << "Detected " << smile_neighbors << " smile neighbors" << endl; - const int rect_height = cvRound((float)img.rows * smile_neighbors / max_neighbors); - CvScalar col = CV_RGB((float)255 * smile_neighbors / max_neighbors, 0, 0); - rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1); - } + 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); - cv::imshow( "result", img ); + // 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 ); }