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Update samples/c/smiledetect.cpp
- Changed to floating neighbor maximum mode - Fixed some previous errors.
This commit is contained in:
Oscar Deniz Suarez
parent
379dcf87d5
commit
8cfba6456b
@ -14,12 +14,12 @@ static void help()
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cout << "\nThis program demonstrates the smile detector.\n"
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"Usage:\n"
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"./smiledetect [--cascade=<cascade_path> this is the frontal face classifier]\n"
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" [--smile-cascade[=smile_cascade_path]]\n"
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" [--scale=<image scale greater or equal to 1, try 1.3 for example. The larger the faster the processing>]\n"
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" [--smile-cascade=[<smile_cascade_path>]]\n"
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" [--scale=<image scale greater or equal to 1, try 2.0 for example. The larger the faster the processing>]\n"
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" [--try-flip]\n"
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" [filename|camera_index]\n\n"
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" [video_filename|camera_index]\n\n"
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"Example:\n"
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"./smiledetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --smile-cascade=\"../../data/haarcascades/haarcascade_smile.xml\" --scale=1.3\n\n"
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"./smiledetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --smile-cascade=\"../../data/haarcascades/haarcascade_smile.xml\" --scale=2.0\n\n"
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"During execution:\n\tHit any key to quit.\n"
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"\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
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}
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@ -31,10 +31,6 @@ 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_smile.xml";
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// The number of detected neighbors depends on image size, these are for performing an approximate mapping to a maximum number of neighbors
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const float coef1 = 0.3190;
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const float coef2 = -48.7187;
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int main( int argc, const char** argv )
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{
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@ -68,8 +64,6 @@ int main( int argc, const char** argv )
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{
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if( argv[i][nestedCascadeOpt.length()] == '=' )
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nestedCascadeName.assign( argv[i] + nestedCascadeOpt.length() + 1 );
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if( !nestedCascade.load( nestedCascadeName ) )
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cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
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}
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else if( scaleOpt.compare( 0, scaleOptLen, argv[i], scaleOptLen ) == 0 )
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{
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@ -92,7 +86,13 @@ int main( int argc, const char** argv )
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if( !cascade.load( cascadeName ) )
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{
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cerr << "ERROR: Could not load classifier cascade" << endl;
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cerr << "ERROR: Could not load face cascade" << endl;
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help();
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return -1;
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}
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if( !nestedCascade.load( nestedCascadeName ) )
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{
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cerr << "ERROR: Could not load smile cascade" << endl;
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help();
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return -1;
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}
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@ -105,17 +105,8 @@ int main( int argc, const char** argv )
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}
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else 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) cout << "Capture from AVI didn't work" << endl;
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}
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}
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else
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{
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image = imread( "lena.jpg", 1 );
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if(image.empty()) cout << "Couldn't read lena.jpg" << endl;
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capture = cvCaptureFromAVI( inputName.c_str() );
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if(!capture) cout << "Capture from AVI didn't work" << endl;
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}
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cvNamedWindow( "result", 1 );
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@ -123,6 +114,8 @@ int main( int argc, const char** argv )
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if( capture )
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{
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cout << "In capture ..." << endl;
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cout << endl << "NOTE: Smile intensity will only be valid after a first smile has been detected" << endl;
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for(;;)
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{
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IplImage* iplImg = cvQueryFrame( capture );
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@ -147,43 +140,9 @@ _cleanup_:
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}
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else
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{
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cout << "In image read" << endl;
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if( !image.empty() )
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{
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detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
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waitKey(0);
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}
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else if( !inputName.empty() )
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{
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/* assume it is a text file containing the
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list of the image filenames to be processed - one per line */
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FILE* f = fopen( inputName.c_str(), "rt" );
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if( f )
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{
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char buf[1000+1];
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while( fgets( buf, 1000, f ) )
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{
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int len = (int)strlen(buf), c;
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while( len > 0 && isspace(buf[len-1]) )
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len--;
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buf[len] = '\0';
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cout << "file " << buf << endl;
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image = imread( buf, 1 );
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if( !image.empty() )
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{
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detectAndDraw( image, cascade, nestedCascade, scale, tryflip );
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c = waitKey(0);
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if( c == 27 || c == 'q' || c == 'Q' )
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break;
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}
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else
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{
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cerr << "Aw snap, couldn't read image " << buf << endl;
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}
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}
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fclose(f);
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}
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}
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cerr << "ERROR: Could not initiate capture" << endl;
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help();
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return -1;
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}
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cvDestroyWindow("result");
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@ -206,8 +165,6 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
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CV_RGB(255,0,255)} ;
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Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
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const int max_neighbors = MAX(0, cvRound((float)coef1*smallImg.cols + coef2));
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cvtColor( img, gray, CV_BGR2GRAY );
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resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
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equalizeHist( smallImg, smallImg );
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@ -234,6 +191,7 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
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faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
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}
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}
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for( vector<Rect>::iterator r = faces.begin(); r != faces.end(); r++, i++ )
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{
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Mat smallImgROI;
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@ -254,8 +212,6 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
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rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
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cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),
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color, 3, 8, 0);
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if( nestedCascade.empty() )
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continue;
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const int half_height=cvRound((float)r->height/2);
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r->y=r->y + half_height;
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@ -270,13 +226,21 @@ void detectAndDraw( Mat& img, CascadeClassifier& cascade,
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,
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Size(30, 30) );
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// Draw rectangle reflecting confidence
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// The number of detected neighbors depends on image size (and also illumination, etc.). The
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// following steps use a floating minimum and maximum of neighbors. Intensity thus estimated will be
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//accurate only after a first smile has been displayed by the user.
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const int smile_neighbors = nestedObjects.size();
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cout << "Detected " << smile_neighbors << " smile neighbors" << endl;
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const int rect_height = cvRound((float)img.rows * smile_neighbors / max_neighbors);
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CvScalar col = CV_RGB((float)255 * smile_neighbors / max_neighbors, 0, 0);
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rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1);
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}
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static int max_neighbors=-1;
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static int min_neighbors=-1;
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if (min_neighbors == -1) min_neighbors = smile_neighbors;
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max_neighbors = MAX(max_neighbors, smile_neighbors);
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cv::imshow( "result", img );
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// Draw rectangle on the left side of the image reflecting smile intensity
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float intensityZeroOne = ((float)smile_neighbors - min_neighbors) / (max_neighbors - min_neighbors + 1);
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int rect_height = cvRound((float)img.rows * intensityZeroOne);
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CvScalar col = CV_RGB((float)255 * intensityZeroOne, 0, 0);
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rectangle(img, cvPoint(0, img.rows), cvPoint(img.cols/10, img.rows - rect_height), col, -1);
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}
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cv::imshow( "result", img );
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}
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