Merge pull request #525 from odeniz:2.4

samples/c/smiledetect.cpp

+#include "opencv2/objdetect/objdetect.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+#include <cctype>
+#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 2.0 for example. The larger the faster the processing>]\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 = 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<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 );
+
+    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);
+
+        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) );
+
+        // 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();
+        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 );
+}