Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with
or
.
Download ZIP
Browse files

Added smile detector

  • Loading branch information...
commit 379dcf87d56b83723db09580d90004170b48d61f 1 parent 39baa22
@odeniz odeniz authored
Showing with 8,635 additions and 0 deletions.
  1. +8,353 −0 data/haarcascades/haarcascade_smile.xml
  2. +282 −0 samples/c/smiledetect.cpp
View
8,353 data/haarcascades/haarcascade_smile.xml
8,353 additions, 0 deletions not shown
View
282 samples/c/smiledetect.cpp
@@ -0,0 +1,282 @@
+#include "opencv2/objdetect/objdetect.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+#include <iostream>
+#include <iterator>
+#include <stdio.h>
+
+using namespace std;
+using namespace cv;
+
+static void help()
+{
+ cout << "\nThis program demonstrates the smile detector.\n"
+ "Usage:\n"
+ "./smiledetect [--cascade=<cascade_path> this is the frontal face classifier]\n"
+ " [--smile-cascade[=smile_cascade_path]]\n"
+ " [--scale=<image scale greater or equal to 1, try 1.3 for example. The larger the faster the processing>]\n"
+ " [--try-flip]\n"
+ " [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"
+ "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";
+
+// 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 )
+{
+ 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 );
+ 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( 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 classifier 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() )
+ {
+ 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 );
+ else
+ flip( frame, frameCopy, 0 );
+
+ detectAndDraw( frameCopy, cascade, nestedCascade, scale, tryflip );
+
+ 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, 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);
+ }
+ }
+ }
+
+ cvDestroyWindow("result");
+ return 0;
+}
+
+void detectAndDraw( Mat& img, CascadeClassifier& cascade,
+ CascadeClassifier& nestedCascade,
+ double scale, bool tryflip)
+{
+ int i = 0;
+ vector<Rect> 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 );
+
+ 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 );
+
+ 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) );
+ if( tryflip )
+ {
+ flip(smallImg, smallImg, 1);
+ cascade.detectMultiScale( smallImg, faces2,
+ 1.1, 2, 0
+ //|CV_HAAR_FIND_BIGGEST_OBJECT
+ //|CV_HAAR_DO_ROUGH_SEARCH
+ |CV_HAAR_SCALE_IMAGE
+ ,
+ Size(30, 30) );
+ for( vector<Rect>::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<Rect>::iterator r = faces.begin(); r != faces.end(); r++, i++ )
+ {
+ Mat smallImgROI;
+ vector<Rect> 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);
+ if( nestedCascade.empty() )
+ continue;
+
+ 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
+ //|CV_HAAR_FIND_BIGGEST_OBJECT
+ //|CV_HAAR_DO_ROUGH_SEARCH
+ //|CV_HAAR_DO_CANNY_PRUNING
+ |CV_HAAR_SCALE_IMAGE
+ ,
+ Size(30, 30) );
+
+ // Draw rectangle reflecting confidence
+ 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);
+ }
+
+ cv::imshow( "result", img );
+}
Please sign in to comment.
Something went wrong with that request. Please try again.