converted some OpenCV C samples to C++

samples/c/convexhull.c

@@ -1,97 +0,0 @@
-#include <opencv2/imgproc/imgproc.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-#define ARRAY  1
-
-int main( int argc, char** argv )
-{
-    IplImage* img = cvCreateImage( cvSize( 500, 500 ), 8, 3 );
-#if !ARRAY
-    CvMemStorage* storage = cvCreateMemStorage(0);
-#endif
-
-    cvNamedWindow( "hull", 1 );
-
-    for(;;)
-    {
-        char key;
-        int i, count = rand()%100 + 1, hullcount;
-        CvPoint pt0;
-#if !ARRAY
-        CvSeq* ptseq = cvCreateSeq( CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvContour),
-                                     sizeof(CvPoint), storage );
-        CvSeq* hull;
-
-        for( i = 0; i < count; i++ )
-        {
-            pt0.x = rand() % (img->width/2) + img->width/4;
-            pt0.y = rand() % (img->height/2) + img->height/4;
-            cvSeqPush( ptseq, &pt0 );
-        }
-        hull = cvConvexHull2( ptseq, 0, CV_CLOCKWISE, 0 );
-        hullcount = hull->total;
-#else
-        CvPoint* points = (CvPoint*)malloc( count * sizeof(points[0]));
-        int* hull = (int*)malloc( count * sizeof(hull[0]));
-        CvMat pointMat = cvMat( 1, count, CV_32SC2, points );
-        CvMat hullMat = cvMat( 1, count, CV_32SC1, hull );
-
-        for( i = 0; i < count; i++ )
-        {
-            pt0.x = rand() % (img->width/2) + img->width/4;
-            pt0.y = rand() % (img->height/2) + img->height/4;
-            points[i] = pt0;
-        }
-        cvConvexHull2( &pointMat, &hullMat, CV_CLOCKWISE, 0 );
-        hullcount = hullMat.cols;
-#endif
-        cvZero( img );
-        for( i = 0; i < count; i++ )
-        {
-#if !ARRAY
-            pt0 = *CV_GET_SEQ_ELEM( CvPoint, ptseq, i );
-#else
-            pt0 = points[i];
-#endif
-            cvCircle( img, pt0, 2, CV_RGB( 255, 0, 0 ), CV_FILLED, CV_AA, 0 );
-        }
-
-#if !ARRAY
-        pt0 = **CV_GET_SEQ_ELEM( CvPoint*, hull, hullcount - 1 );
-#else
-        pt0 = points[hull[hullcount-1]];
-#endif
-
-        for( i = 0; i < hullcount; i++ )
-        {
-#if !ARRAY
-            CvPoint pt = **CV_GET_SEQ_ELEM( CvPoint*, hull, i );
-#else
-            CvPoint pt = points[hull[i]];
-#endif
-            cvLine( img, pt0, pt, CV_RGB( 0, 255, 0 ), 1, CV_AA, 0 );
-            pt0 = pt;
-        }
-
-        cvShowImage( "hull", img );
-
-        key = (char) cvWaitKey(0);
-        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
-            break;
-
-#if !ARRAY
-        cvClearMemStorage( storage );
-#else
-        free( points );
-        free( hull );
-#endif
-    }
-
-    cvDestroyWindow( "hull" );
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"convexhull.c");
-#endif
-

samples/c/demhist.c

@@ -1,120 +0,0 @@
-#include <opencv2/imgproc/imgproc_c.h>
-#include <opencv2/highgui/highgui.hpp>
-
-#include <stdio.h>
-
-char file_name[] = "baboon.jpg";
-
-int _brightness = 100;
-int _contrast = 100;
-
-int hist_size = 64;
-float range_0[]={0,256};
-float* ranges[] = { range_0 };
-IplImage *src_image = 0, *dst_image = 0, *hist_image = 0;
-CvHistogram *hist;
-uchar lut[256];
-CvMat* lut_mat;
-
-/* brightness/contrast callback function */
-void update_brightcont( int arg )
-{
-    int brightness = _brightness - 100;
-    int contrast = _contrast - 100;
-    int i, bin_w;
-    float max_value = 0;
-
-    /*
-     * The algorithm is by Werner D. Streidt
-     * (http://visca.com/ffactory/archives/5-99/msg00021.html)
-     */
-    if( contrast > 0 )
-    {
-        double delta = 127.*contrast/100;
-        double a = 255./(255. - delta*2);
-        double b = a*(brightness - delta);
-        for( i = 0; i < 256; i++ )
-        {
-            int v = cvRound(a*i + b);
-            if( v < 0 )
-                v = 0;
-            if( v > 255 )
-                v = 255;
-            lut[i] = (uchar)v;
-        }
-    }
-    else
-    {
-        double delta = -128.*contrast/100;
-        double a = (256.-delta*2)/255.;
-        double b = a*brightness + delta;
-        for( i = 0; i < 256; i++ )
-        {
-            int v = cvRound(a*i + b);
-            if( v < 0 )
-                v = 0;
-            if( v > 255 )
-                v = 255;
-            lut[i] = (uchar)v;
-        }
-    }
-
-    cvLUT( src_image, dst_image, lut_mat );
-    cvShowImage( "image", dst_image );
-
-    cvCalcHist( &dst_image, hist, 0, NULL );
-    cvZero( dst_image );
-    cvGetMinMaxHistValue( hist, 0, &max_value, 0, 0 );
-    cvScale( hist->bins, hist->bins, ((double)hist_image->height)/max_value, 0 );
-    /*cvNormalizeHist( hist, 1000 );*/
-
-    cvSet( hist_image, cvScalarAll(255), 0 );
-    bin_w = cvRound((double)hist_image->width/hist_size);
-
-    for( i = 0; i < hist_size; i++ )
-        cvRectangle( hist_image, cvPoint(i*bin_w, hist_image->height),
-                     cvPoint((i+1)*bin_w, hist_image->height - cvRound(cvGetReal1D(hist->bins,i))),
-                     cvScalarAll(0), -1, 8, 0 );
-
-    cvShowImage( "histogram", hist_image );
-}
-
-
-int main( int argc, char** argv )
-{
-    // Load the source image. HighGUI use.
-    src_image = cvLoadImage( argc == 2 ? argv[1] : file_name, 0 );
-
-    if( !src_image )
-    {
-        printf("Image was not loaded.\n");
-        return -1;
-    }
-
-    dst_image = cvCloneImage(src_image);
-    hist_image = cvCreateImage(cvSize(320,200), 8, 1);
-    hist = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
-    lut_mat = cvCreateMatHeader( 1, 256, CV_8UC1 );
-    cvSetData( lut_mat, lut, 0 );
-
-    cvNamedWindow("image", 0);
-    cvNamedWindow("histogram", 0);
-
-    cvCreateTrackbar("brightness", "image", &_brightness, 200, update_brightcont);
-    cvCreateTrackbar("contrast", "image", &_contrast, 200, update_brightcont);
-
-    update_brightcont(0);
-    cvWaitKey(0);
-
-    cvReleaseImage(&src_image);
-    cvReleaseImage(&dst_image);
-
-    cvReleaseHist(&hist);
-
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"demhist.c");
-#endif
-

samples/c/dft.c

@@ -1,136 +0,0 @@
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-// Rearrange the quadrants of Fourier image so that the origin is at
-// the image center
-// src & dst arrays of equal size & type
-void cvShiftDFT(CvArr * src_arr, CvArr * dst_arr )
-{
-    CvMat * tmp=0;
-    CvMat q1stub, q2stub;
-    CvMat q3stub, q4stub;
-    CvMat d1stub, d2stub;
-    CvMat d3stub, d4stub;
-    CvMat * q1, * q2, * q3, * q4;
-    CvMat * d1, * d2, * d3, * d4;
-
-    CvSize size = cvGetSize(src_arr);
-    CvSize dst_size = cvGetSize(dst_arr);
-    int cx, cy;
-
-    if(dst_size.width != size.width ||
-       dst_size.height != size.height){
-        cvError( CV_StsUnmatchedSizes, "cvShiftDFT", "Source and Destination arrays must have equal sizes", __FILE__, __LINE__ );
-    }
-
-    if(src_arr==dst_arr){
-        tmp = cvCreateMat(size.height/2, size.width/2, cvGetElemType(src_arr));
-    }
-
-    cx = size.width/2;
-    cy = size.height/2; // image center
-
-    q1 = cvGetSubRect( src_arr, &q1stub, cvRect(0,0,cx, cy) );
-    q2 = cvGetSubRect( src_arr, &q2stub, cvRect(cx,0,cx,cy) );
-    q3 = cvGetSubRect( src_arr, &q3stub, cvRect(cx,cy,cx,cy) );
-    q4 = cvGetSubRect( src_arr, &q4stub, cvRect(0,cy,cx,cy) );
-    d1 = cvGetSubRect( src_arr, &d1stub, cvRect(0,0,cx,cy) );
-    d2 = cvGetSubRect( src_arr, &d2stub, cvRect(cx,0,cx,cy) );
-    d3 = cvGetSubRect( src_arr, &d3stub, cvRect(cx,cy,cx,cy) );
-    d4 = cvGetSubRect( src_arr, &d4stub, cvRect(0,cy,cx,cy) );
-
-    if(src_arr!=dst_arr){
-        if( !CV_ARE_TYPES_EQ( q1, d1 )){
-            cvError( CV_StsUnmatchedFormats, "cvShiftDFT", "Source and Destination arrays must have the same format", __FILE__, __LINE__ );
-        }
-        cvCopy(q3, d1, 0);
-        cvCopy(q4, d2, 0);
-        cvCopy(q1, d3, 0);
-        cvCopy(q2, d4, 0);
-    }
-    else{
-        cvCopy(q3, tmp, 0);
-        cvCopy(q1, q3, 0);
-        cvCopy(tmp, q1, 0);
-        cvCopy(q4, tmp, 0);
-        cvCopy(q2, q4, 0);
-        cvCopy(tmp, q2, 0);
-    }
-}
-
-int main(int argc, char ** argv)
-{
-    const char* filename = argc >=2 ? argv[1] : "lena.jpg";
-    IplImage * im;
-
-    IplImage * realInput;
-    IplImage * imaginaryInput;
-    IplImage * complexInput;
-    int dft_M, dft_N;
-    CvMat* dft_A, tmp;
-    IplImage * image_Re;
-    IplImage * image_Im;
-    double m, M;
-
-    im = cvLoadImage( filename, CV_LOAD_IMAGE_GRAYSCALE );
-    if( !im )
-        return -1;
-
-    realInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
-    imaginaryInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 1);
-    complexInput = cvCreateImage( cvGetSize(im), IPL_DEPTH_64F, 2);
-
-    cvScale(im, realInput, 1.0, 0.0);
-    cvZero(imaginaryInput);
-    cvMerge(realInput, imaginaryInput, NULL, NULL, complexInput);
-
-    dft_M = cvGetOptimalDFTSize( im->height - 1 );
-    dft_N = cvGetOptimalDFTSize( im->width - 1 );
-
-    dft_A = cvCreateMat( dft_M, dft_N, CV_64FC2 );
-    image_Re = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
-    image_Im = cvCreateImage( cvSize(dft_N, dft_M), IPL_DEPTH_64F, 1);
-
-    // copy A to dft_A and pad dft_A with zeros
-    cvGetSubRect( dft_A, &tmp, cvRect(0,0, im->width, im->height));
-    cvCopy( complexInput, &tmp, NULL );
-    if( dft_A->cols > im->width )
-    {
-        cvGetSubRect( dft_A, &tmp, cvRect(im->width,0, dft_A->cols - im->width, im->height));
-        cvZero( &tmp );
-    }
-
-    // no need to pad bottom part of dft_A with zeros because of
-    // use nonzero_rows parameter in cvDFT() call below
-
-    cvDFT( dft_A, dft_A, CV_DXT_FORWARD, complexInput->height );
-
-    cvNamedWindow("win", 0);
-    cvNamedWindow("magnitude", 0);
-    cvShowImage("win", im);
-
-    // Split Fourier in real and imaginary parts
-    cvSplit( dft_A, image_Re, image_Im, 0, 0 );
-
-    // Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
-    cvPow( image_Re, image_Re, 2.0);
-    cvPow( image_Im, image_Im, 2.0);
-    cvAdd( image_Re, image_Im, image_Re, NULL);
-    cvPow( image_Re, image_Re, 0.5 );
-
-    // Compute log(1 + Mag)
-    cvAddS( image_Re, cvScalarAll(1.0), image_Re, NULL ); // 1 + Mag
-    cvLog( image_Re, image_Re ); // log(1 + Mag)
-
-
-    // Rearrange the quadrants of Fourier image so that the origin is at
-    // the image center
-    cvShiftDFT( image_Re, image_Re );
-
-    cvMinMaxLoc(image_Re, &m, &M, NULL, NULL, NULL);
-    cvScale(image_Re, image_Re, 1.0/(M-m), 1.0*(-m)/(M-m));
-    cvShowImage("magnitude", image_Re);
-
-    cvWaitKey(-1);
-    return 0;
-}

samples/c/distrans.c

@@ -1,184 +0,0 @@
-#include <opencv2/imgproc/imgproc_c.h>
-#include <opencv2/highgui/highgui.hpp>
-
-#include <stdio.h>
-
-char wndname[] = "Distance transform";
-char tbarname[] = "Threshold";
-int mask_size = CV_DIST_MASK_5;
-int build_voronoi = 0;
-int edge_thresh = 100;
-int dist_type = CV_DIST_L1;
-
-// The output and temporary images
-IplImage* dist = 0;
-IplImage* dist8u1 = 0;
-IplImage* dist8u2 = 0;
-IplImage* dist8u = 0;
-IplImage* dist32s = 0;
-
-IplImage* gray = 0;
-IplImage* edge = 0;
-IplImage* labels = 0;
-
-// threshold trackbar callback
-void on_trackbar( int dummy )
-{
-    static const uchar colors[][3] =
-    {
-        {0,0,0},
-        {255,0,0},
-        {255,128,0},
-        {255,255,0},
-        {0,255,0},
-        {0,128,255},
-        {0,255,255},
-        {0,0,255},
-        {255,0,255}
-    };
-
-    int msize = mask_size;
-    int _dist_type = build_voronoi ? CV_DIST_L2 : dist_type;
-
-    cvThreshold( gray, edge, (float)edge_thresh, (float)edge_thresh, CV_THRESH_BINARY );
-
-    if( build_voronoi )
-        msize = CV_DIST_MASK_5;
-
-    if( _dist_type == CV_DIST_L1 )
-    {
-        cvDistTransform( edge, edge, _dist_type, msize, NULL, NULL );
-        cvConvert( edge, dist );
-    }
-    else
-        cvDistTransform( edge, dist, _dist_type, msize, NULL, build_voronoi ? labels : NULL );
-
-    if( !build_voronoi )
-    {
-        // begin "painting" the distance transform result
-        cvConvertScale( dist, dist, 5000.0, 0 );
-        cvPow( dist, dist, 0.5 );
-
-        cvConvertScale( dist, dist32s, 1.0, 0.5 );
-        cvAndS( dist32s, cvScalarAll(255), dist32s, 0 );
-        cvConvertScale( dist32s, dist8u1, 1, 0 );
-        cvConvertScale( dist32s, dist32s, -1, 0 );
-        cvAddS( dist32s, cvScalarAll(255), dist32s, 0 );
-        cvConvertScale( dist32s, dist8u2, 1, 0 );
-        cvMerge( dist8u1, dist8u2, dist8u2, 0, dist8u );
-        // end "painting" the distance transform result
-    }
-    else
-    {
-        int i, j;
-        for( i = 0; i < labels->height; i++ )
-        {
-            int* ll = (int*)(labels->imageData + i*labels->widthStep);
-            float* dd = (float*)(dist->imageData + i*dist->widthStep);
-            uchar* d = (uchar*)(dist8u->imageData + i*dist8u->widthStep);
-            for( j = 0; j < labels->width; j++ )
-            {
-                int idx = ll[j] == 0 || dd[j] == 0 ? 0 : (ll[j]-1)%8 + 1;
-                int b = cvRound(colors[idx][0]);
-                int g = cvRound(colors[idx][1]);
-                int r = cvRound(colors[idx][2]);
-                d[j*3] = (uchar)b;
-                d[j*3+1] = (uchar)g;
-                d[j*3+2] = (uchar)r;
-            }
-        }
-    }
-
-    cvShowImage( wndname, dist8u );
-}
-
-int main( int argc, char** argv )
-{
-    char* filename = argc == 2 ? argv[1] : (char*)"stuff.jpg";
-
-    if( (gray = cvLoadImage( filename, 0 )) == 0 )
-        return -1;
-
-    printf( "Hot keys: \n"
-        "\tESC - quit the program\n"
-        "\tC - use C/Inf metric\n"
-        "\tL1 - use L1 metric\n"
-        "\tL2 - use L2 metric\n"
-        "\t3 - use 3x3 mask\n"
-        "\t5 - use 5x5 mask\n"
-        "\t0 - use precise distance transform\n"
-        "\tv - switch Voronoi diagram mode on/off\n"
-        "\tSPACE - loop through all the modes\n" );
-
-    dist = cvCreateImage( cvGetSize(gray), IPL_DEPTH_32F, 1 );
-    dist8u1 = cvCloneImage( gray );
-    dist8u2 = cvCloneImage( gray );
-    dist8u = cvCreateImage( cvGetSize(gray), IPL_DEPTH_8U, 3 );
-    dist32s = cvCreateImage( cvGetSize(gray), IPL_DEPTH_32S, 1 );
-    edge = cvCloneImage( gray );
-    labels = cvCreateImage( cvGetSize(gray), IPL_DEPTH_32S, 1 );
-
-    cvNamedWindow( wndname, 1 );
-
-    cvCreateTrackbar( tbarname, wndname, &edge_thresh, 255, on_trackbar );
-
-    for(;;)
-    {
-        int c;
-
-        // Call to update the view
-        on_trackbar(0);
-
-        c = cvWaitKey(0);
-
-        if( (char)c == 27 )
-            break;
-
-        if( (char)c == 'c' || (char)c == 'C' )
-            dist_type = CV_DIST_C;
-        else if( (char)c == '1' )
-            dist_type = CV_DIST_L1;
-        else if( (char)c == '2' )
-            dist_type = CV_DIST_L2;
-        else if( (char)c == '3' )
-            mask_size = CV_DIST_MASK_3;
-        else if( (char)c == '5' )
-            mask_size = CV_DIST_MASK_5;
-        else if( (char)c == '0' )
-            mask_size = CV_DIST_MASK_PRECISE;
-        else if( (char)c == 'v' )
-            build_voronoi ^= 1;
-        else if( (char)c == ' ' )
-        {
-            if( build_voronoi )
-            {
-                build_voronoi = 0;
-                mask_size = CV_DIST_MASK_3;
-                dist_type = CV_DIST_C;
-            }
-            else if( dist_type == CV_DIST_C )
-                dist_type = CV_DIST_L1;
-            else if( dist_type == CV_DIST_L1 )
-                dist_type = CV_DIST_L2;
-            else if( mask_size == CV_DIST_MASK_3 )
-                mask_size = CV_DIST_MASK_5;
-            else if( mask_size == CV_DIST_MASK_5 )
-                mask_size = CV_DIST_MASK_PRECISE;
-            else if( mask_size == CV_DIST_MASK_PRECISE )
-                build_voronoi = 1;
-        }
-    }
-
-    cvReleaseImage( &gray );
-    cvReleaseImage( &edge );
-    cvReleaseImage( &dist );
-    cvReleaseImage( &dist8u );
-    cvReleaseImage( &dist8u1 );
-    cvReleaseImage( &dist8u2 );
-    cvReleaseImage( &dist32s );
-    cvReleaseImage( &labels );
-
-    cvDestroyWindow( wndname );
-
-    return 0;
-}

samples/c/drawing.c

@@ -1,177 +0,0 @@
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-#define NUMBER 100
-#define DELAY 5
-char wndname[] = "Drawing Demo";
-
-CvScalar random_color(CvRNG* rng)
-{
-    int icolor = cvRandInt(rng);
-    return CV_RGB(icolor&255, (icolor>>8)&255, (icolor>>16)&255);
-}
-
-int main( int argc, char** argv )
-{
-    int line_type = CV_AA; // change it to 8 to see non-antialiased graphics
-    int i;
-    CvPoint pt1,pt2;
-    double angle;
-    CvSize sz;
-    CvPoint  ptt[6];
-    CvPoint* pt[2];
-    int  arr[2];
-    CvFont font;
-    CvRNG rng;
-    int width = 1000, height = 700;
-    int width3 = width*3, height3 = height*3;
-    CvSize text_size;
-    int ymin = 0;
-    // Load the source image
-    IplImage* image = cvCreateImage( cvSize(width,height), 8, 3 );
-    IplImage* image2;
-
-    // Create a window
-    cvNamedWindow(wndname, 1 );
-    cvZero( image );
-    cvShowImage(wndname,image);
-    cvWaitKey(DELAY);
-
-    rng = cvRNG((unsigned)-1);
-    pt[0] = &(ptt[0]);
-    pt[1] = &(ptt[3]);
-
-    arr[0] = 3;
-    arr[1] = 3;
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt1.x=cvRandInt(&rng) % width3 - width;
-        pt1.y=cvRandInt(&rng) % height3 - height;
-        pt2.x=cvRandInt(&rng) % width3 - width;
-        pt2.y=cvRandInt(&rng) % height3 - height;
-
-        cvLine( image, pt1, pt2, random_color(&rng), cvRandInt(&rng)%10, line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt1.x=cvRandInt(&rng) % width3 - width;
-        pt1.y=cvRandInt(&rng) % height3 - height;
-        pt2.x=cvRandInt(&rng) % width3 - width;
-        pt2.y=cvRandInt(&rng) % height3 - height;
-
-        cvRectangle( image,pt1, pt2, random_color(&rng), cvRandInt(&rng)%10-1, line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt1.x=cvRandInt(&rng) % width3 - width;
-        pt1.y=cvRandInt(&rng) % height3 - height;
-        sz.width =cvRandInt(&rng)%200;
-        sz.height=cvRandInt(&rng)%200;
-        angle = (cvRandInt(&rng)%1000)*0.180;
-
-        cvEllipse( image, pt1, sz, angle, angle - 100, angle + 200,
-                   random_color(&rng), cvRandInt(&rng)%10-1, line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt[0][0].x=cvRandInt(&rng) % width3 - width;
-        pt[0][0].y=cvRandInt(&rng) % height3 - height;
-        pt[0][1].x=cvRandInt(&rng) % width3 - width;
-        pt[0][1].y=cvRandInt(&rng) % height3 - height;
-        pt[0][2].x=cvRandInt(&rng) % width3 - width;
-        pt[0][2].y=cvRandInt(&rng) % height3 - height;
-        pt[1][0].x=cvRandInt(&rng) % width3 - width;
-        pt[1][0].y=cvRandInt(&rng) % height3 - height;
-        pt[1][1].x=cvRandInt(&rng) % width3 - width;
-        pt[1][1].y=cvRandInt(&rng) % height3 - height;
-        pt[1][2].x=cvRandInt(&rng) % width3 - width;
-        pt[1][2].y=cvRandInt(&rng) % height3 - height;
-
-        cvPolyLine( image, pt, arr, 2, 1, random_color(&rng), cvRandInt(&rng)%10, line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt[0][0].x=cvRandInt(&rng) % width3 - width;
-        pt[0][0].y=cvRandInt(&rng) % height3 - height;
-        pt[0][1].x=cvRandInt(&rng) % width3 - width;
-        pt[0][1].y=cvRandInt(&rng) % height3 - height;
-        pt[0][2].x=cvRandInt(&rng) % width3 - width;
-        pt[0][2].y=cvRandInt(&rng) % height3 - height;
-        pt[1][0].x=cvRandInt(&rng) % width3 - width;
-        pt[1][0].y=cvRandInt(&rng) % height3 - height;
-        pt[1][1].x=cvRandInt(&rng) % width3 - width;
-        pt[1][1].y=cvRandInt(&rng) % height3 - height;
-        pt[1][2].x=cvRandInt(&rng) % width3 - width;
-        pt[1][2].y=cvRandInt(&rng) % height3 - height;
-
-        cvFillPoly( image, pt, arr, 2, random_color(&rng), line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 0; i< NUMBER; i++)
-    {
-        pt1.x=cvRandInt(&rng) % width3 - width;
-        pt1.y=cvRandInt(&rng) % height3 - height;
-
-        cvCircle( image, pt1, cvRandInt(&rng)%300, random_color(&rng),
-                  cvRandInt(&rng)%10-1, line_type, 0 );
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    for (i = 1; i< NUMBER; i++)
-    {
-        pt1.x=cvRandInt(&rng) % width3 - width;
-        pt1.y=cvRandInt(&rng) % height3 - height;
-
-        cvInitFont( &font, cvRandInt(&rng) % 8,
-                    (cvRandInt(&rng)%100)*0.05+0.1, (cvRandInt(&rng)%100)*0.05+0.1,
-                    (cvRandInt(&rng)%5)*0.1, cvRound(cvRandInt(&rng)%10), line_type );
-
-        cvPutText( image, "Testing text rendering!", pt1, &font, random_color(&rng));
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    cvInitFont( &font, CV_FONT_HERSHEY_COMPLEX, 3, 3, 0.0, 5, line_type );
-
-    cvGetTextSize( "OpenCV forever!", &font, &text_size, &ymin );
-
-    pt1.x = (width - text_size.width)/2;
-    pt1.y = (height + text_size.height)/2;
-    image2 = cvCloneImage(image);
-
-    for( i = 0; i < 255; i++ )
-    {
-        cvSubS( image2, cvScalarAll(i), image, 0 );
-        cvPutText( image, "OpenCV forever!", pt1, &font, CV_RGB(255,i,i));
-        cvShowImage(wndname,image);
-        if(cvWaitKey(DELAY) >= 0) return 0;
-    }
-
-    // Wait for a key stroke; the same function arranges events processing
-    cvWaitKey(0);
-    cvReleaseImage(&image);
-    cvReleaseImage(&image2);
-    cvDestroyWindow(wndname);
-
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"drawing.c");
-#endif

samples/c/edge.c

@@ -1,62 +0,0 @@
-#include <opencv2/imgproc/imgproc_c.h>
-#include <opencv2/highgui/highgui.hpp>
-
-char wndname[] = "Edge";
-char tbarname[] = "Threshold";
-int edge_thresh = 1;
-
-IplImage *image = 0, *cedge = 0, *gray = 0, *edge = 0;
-
-// define a trackbar callback
-void on_trackbar(int h)
-{
-    cvSmooth( gray, edge, CV_BLUR, 3, 3, 0, 0 );
-    cvNot( gray, edge );
-
-    // Run the edge detector on grayscale
-    cvCanny(gray, edge, (float)edge_thresh, (float)edge_thresh*3, 3);
-
-    cvZero( cedge );
-    // copy edge points
-    cvCopy( image, cedge, edge );
-
-    cvShowImage(wndname, cedge);
-}
-
-int main( int argc, char** argv )
-{
-    char* filename = argc == 2 ? argv[1] : (char*)"fruits.jpg";
-
-    if( (image = cvLoadImage( filename, 1)) == 0 )
-        return -1;
-
-    // Create the output image
-    cedge = cvCreateImage(cvSize(image->width,image->height), IPL_DEPTH_8U, 3);
-
-    // Convert to grayscale
-    gray = cvCreateImage(cvSize(image->width,image->height), IPL_DEPTH_8U, 1);
-    edge = cvCreateImage(cvSize(image->width,image->height), IPL_DEPTH_8U, 1);
-    cvCvtColor(image, gray, CV_BGR2GRAY);
-
-    // Create a window
-    cvNamedWindow(wndname, 1);
-
-    // create a toolbar
-    cvCreateTrackbar(tbarname, wndname, &edge_thresh, 100, on_trackbar);
-
-    // Show the image
-    on_trackbar(0);
-
-    // Wait for a key stroke; the same function arranges events processing
-    cvWaitKey(0);
-    cvReleaseImage(&image);
-    cvReleaseImage(&gray);
-    cvReleaseImage(&edge);
-    cvDestroyWindow(wndname);
-
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"edge.c");
-#endif

samples/c/ffilldemo.c

@@ -1,177 +0,0 @@
-#include <opencv2/imgproc/imgproc_c.h>
-#include <opencv2/highgui/highgui.hpp>
-
-IplImage* color_img0;
-IplImage* mask;
-IplImage* color_img;
-IplImage* gray_img0 = NULL;
-IplImage* gray_img = NULL;
-int ffill_case = 1;
-int lo_diff = 20, up_diff = 20;
-int connectivity = 4;
-int is_color = 1;
-int is_mask = 0;
-int new_mask_val = 255;
-
-void on_mouse( int event, int x, int y, int flags, void* param )
-{
-    if( !color_img )
-        return;
-
-    switch( event )
-    {
-    case CV_EVENT_LBUTTONDOWN:
-        {
-            CvPoint seed = cvPoint(x,y);
-            int lo = ffill_case == 0 ? 0 : lo_diff;
-            int up = ffill_case == 0 ? 0 : up_diff;
-            int flags = connectivity + (new_mask_val << 8) +
-                        (ffill_case == 1 ? CV_FLOODFILL_FIXED_RANGE : 0);
-            int b = rand() & 255, g = rand() & 255, r = rand() & 255;
-            CvConnectedComp comp;
-
-            if( is_mask )
-                cvThreshold( mask, mask, 1, 128, CV_THRESH_BINARY );
-
-            if( is_color )
-            {
-                CvScalar color = CV_RGB( r, g, b );
-                cvFloodFill( color_img, seed, color, CV_RGB( lo, lo, lo ),
-                             CV_RGB( up, up, up ), &comp, flags, is_mask ? mask : NULL );
-                cvShowImage( "image", color_img );
-            }
-            else
-            {
-                CvScalar brightness = cvRealScalar((r*2 + g*7 + b + 5)/10);
-                cvFloodFill( gray_img, seed, brightness, cvRealScalar(lo),
-                             cvRealScalar(up), &comp, flags, is_mask ? mask : NULL );
-                cvShowImage( "image", gray_img );
-            }
-
-            printf("%g pixels were repainted\n", comp.area );
-
-            if( is_mask )
-                cvShowImage( "mask", mask );
-        }
-        break;
-    }
-}
-
-int main( int argc, char** argv )
-{
-    char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
-
-    if( (color_img0 = cvLoadImage(filename,1)) == 0 )
-        return 0;
-
-    printf( "Hot keys: \n"
-            "\tESC - quit the program\n"
-            "\tc - switch color/grayscale mode\n"
-            "\tm - switch mask mode\n"
-            "\tr - restore the original image\n"
-            "\ts - use null-range floodfill\n"
-            "\tf - use gradient floodfill with fixed(absolute) range\n"
-            "\tg - use gradient floodfill with floating(relative) range\n"
-            "\t4 - use 4-connectivity mode\n"
-            "\t8 - use 8-connectivity mode\n" );
-
-    color_img = cvCloneImage( color_img0 );
-    gray_img0 = cvCreateImage( cvSize(color_img->width, color_img->height), 8, 1 );
-    cvCvtColor( color_img, gray_img0, CV_BGR2GRAY );
-    gray_img = cvCloneImage( gray_img0 );
-    mask = cvCreateImage( cvSize(color_img->width + 2, color_img->height + 2), 8, 1 );
-
-    cvNamedWindow( "image", 0 );
-    cvCreateTrackbar( "lo_diff", "image", &lo_diff, 255, NULL );
-    cvCreateTrackbar( "up_diff", "image", &up_diff, 255, NULL );
-
-    cvSetMouseCallback( "image", on_mouse, 0 );
-
-    for(;;)
-    {
-        int c;
-
-        if( is_color )
-            cvShowImage( "image", color_img );
-        else
-            cvShowImage( "image", gray_img );
-
-        c = cvWaitKey(0);
-        switch( (char) c )
-        {
-        case '\x1b':
-            printf("Exiting ...\n");
-            goto exit_main;
-        case 'c':
-            if( is_color )
-            {
-                printf("Grayscale mode is set\n");
-                cvCvtColor( color_img, gray_img, CV_BGR2GRAY );
-                is_color = 0;
-            }
-            else
-            {
-                printf("Color mode is set\n");
-                cvCopy( color_img0, color_img, NULL );
-                cvZero( mask );
-                is_color = 1;
-            }
-            break;
-        case 'm':
-            if( is_mask )
-            {
-                cvDestroyWindow( "mask" );
-                is_mask = 0;
-            }
-            else
-            {
-                cvNamedWindow( "mask", 0 );
-                cvZero( mask );
-                cvShowImage( "mask", mask );
-                is_mask = 1;
-            }
-            break;
-        case 'r':
-            printf("Original image is restored\n");
-            cvCopy( color_img0, color_img, NULL );
-            cvCopy( gray_img0, gray_img, NULL );
-            cvZero( mask );
-            break;
-        case 's':
-            printf("Simple floodfill mode is set\n");
-            ffill_case = 0;
-            break;
-        case 'f':
-            printf("Fixed Range floodfill mode is set\n");
-            ffill_case = 1;
-            break;
-        case 'g':
-            printf("Gradient (floating range) floodfill mode is set\n");
-            ffill_case = 2;
-            break;
-        case '4':
-            printf("4-connectivity mode is set\n");
-            connectivity = 4;
-            break;
-        case '8':
-            printf("8-connectivity mode is set\n");
-            connectivity = 8;
-            break;
-        }
-    }
-
-exit_main:
-
-    cvDestroyWindow( "test" );
-    cvReleaseImage( &gray_img );
-    cvReleaseImage( &gray_img0 );
-    cvReleaseImage( &color_img );
-    cvReleaseImage( &color_img0 );
-    cvReleaseImage( &mask );
-
-    return 1;
-}
-
-#ifdef _EiC
-main(1,"ffilldemo.c");
-#endif

samples/c/fitellipse.cpp

@@ -14,113 +14,70 @@
 *
 *
 ********************************************************************************/
-#include "opencv2/imgproc/imgproc_c.h"
+#include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/highgui/highgui.hpp"
 
-int slider_pos = 70;
+#include <iostream>
 
-// Load the source image. HighGUI use.
+using namespace cv;
-IplImage *image02 = 0, *image03 = 0, *image04 = 0;
+using namespace std;
 
-void process_image(int h);
+int sliderPos = 70;
+
+Mat image;
+
+void processImage(int, void*);
 
 int main( int argc, char** argv )
 {
     const char* filename = argc == 2 ? argv[1] : (char*)"stuff.jpg";
+    image = imread(filename, 0);
+    if( image.empty() )
+    {
+        cout << "Usage: fitellipse <image_name>\n";
+        return 0;
+    }
 
-    // load image and force it to be grayscale
+    imshow("source", image);
-    if( (image03 = cvLoadImage(filename, 0)) == 0 )
+    namedWindow("result", 1);
-        return -1;
-
-    // Create the destination images
-    image02 = cvCloneImage( image03 );
-    image04 = cvCloneImage( image03 );
-
-    // Create windows.
-    cvNamedWindow("Source", 1);
-    cvNamedWindow("Result", 1);
-
-    // Show the image.
-    cvShowImage("Source", image03);
     
     // Create toolbars. HighGUI use.
-    cvCreateTrackbar( "Threshold", "Result", &slider_pos, 255, process_image );
+    createTrackbar( "threshold", "result", &sliderPos, 255, processImage );
-
+    processImage(0, 0);
-    process_image(0);
 
     // Wait for a key stroke; the same function arranges events processing
-    cvWaitKey(0);
+    waitKey();
-    cvReleaseImage(&image02);
-    cvReleaseImage(&image03);
-
-    cvDestroyWindow("Source");
-    cvDestroyWindow("Result");
-
     return 0;
 }
 
 // Define trackbar callback functon. This function find contours,
 // draw it and approximate it by ellipses.
-void process_image(int h)
+void processImage(int h, void*)
 {
-    CvMemStorage* storage;
+    vector<vector<Point> > contours;
-    CvSeq* contour;
+    Mat bimage = image >= sliderPos;
-
-    // Create dynamic structure and sequence.
-    storage = cvCreateMemStorage(0);
-    contour = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint) , storage);
-
-    // Threshold the source image. This needful for cvFindContours().
-    cvThreshold( image03, image02, slider_pos, 255, CV_THRESH_BINARY );
     
-    // Find all contours.
+    findContours(bimage, contours, CV_RETR_LIST, CV_CHAIN_APPROX_NONE);
-    cvFindContours( image02, storage, &contour, sizeof(CvContour),
-                    CV_RETR_LIST, CV_CHAIN_APPROX_NONE, cvPoint(0,0));
 
-    // Clear images. IPL use.
+    Mat cimage = Mat::zeros(bimage.size(), CV_8UC3);
-    cvZero(image02);
-    cvZero(image04);
 
-    // This cycle draw all contours and approximate it by ellipses.
+    for(size_t i = 0; i < contours.size(); i++)
-    for(;contour;contour = contour->h_next)
     {
-        int count = contour->total; // This is number point in contour
+        size_t count = contours[i].size();
-        CvPoint center;
-        CvSize size;
-        CvBox2D box;
-
-        // Number point must be more than or equal to 6 (for cvFitEllipse_32f).
         if( count < 6 )
             continue;
         
-        CvMat* points_f = cvCreateMat( 1, count, CV_32FC2 );
+        Mat pointsf;
-        CvMat points_i = cvMat( 1, count, CV_32SC2, points_f->data.ptr );
+        Mat(contours[i]).convertTo(pointsf, CV_32F);
-        cvCvtSeqToArray( contour, points_f->data.ptr, CV_WHOLE_SEQ );
+        RotatedRect box = fitEllipse(pointsf);
-        cvConvert( &points_i, points_f );
-
-        // Fits ellipse to current contour.
-        box = cvFitEllipse2( points_f );
         
-        // Draw current contour.
+        box.angle = -box.angle;
-        cvDrawContours(image04,contour,CV_RGB(255,255,255),CV_RGB(255,255,255),0,1,8,cvPoint(0,0));
+        if( MAX(box.size.width, box.size.height) > MIN(box.size.width, box.size.height)*30 )
-
+            continue;
-        // Convert ellipse data from float to integer representation.
+        drawContours(cimage, contours, (int)i, Scalar::all(255), 1, 8);
-        center = cvPointFrom32f(box.center);
-        size.width = cvRound(box.size.width*0.5);
-        size.height = cvRound(box.size.height*0.5);
-
-        // Draw ellipse.
-        cvEllipse(image04, center, size,
-                  -box.angle, 0, 360,
-                  CV_RGB(0,0,255), 1, CV_AA, 0);
 
-        cvReleaseMat(&points_f);
+        ellipse(cimage, box, Scalar(0,0,255), 1, CV_AA);
     }
 
-    // Show image. HighGUI use.
+    imshow("result", cimage);
-    cvShowImage( "Result", image04 );
 }
-
-#ifdef _EiC
-main(1,"fitellipse.c");
-#endif

samples/c/intrinsics.yml

@@ -0,0 +1,23 @@
+%YAML:1.0
+M1: !!opencv-matrix
+   rows: 3
+   cols: 3
+   dt: d
+   data: [ 5.3480326845051309e+02, 0., 3.3568643204394891e+02, 0.,
+       5.3480326845051309e+02, 2.4066183054066337e+02, 0., 0., 1. ]
+D1: !!opencv-matrix
+   rows: 1
+   cols: 5
+   dt: d
+   data: [ 2.9589439552724328e-01, -1.0354662043042675e+00, 0., 0., 0. ]
+M2: !!opencv-matrix
+   rows: 3
+   cols: 3
+   dt: d
+   data: [ 5.3480326845051309e+02, 0., 3.3455744527912015e+02, 0.,
+       5.3480326845051309e+02, 2.4205324573376600e+02, 0., 0., 1. ]
+D2: !!opencv-matrix
+   rows: 1
+   cols: 5
+   dt: d
+   data: [ -1.6916358306948096e-01, -1.1214173641213163e-01, 0., 0., 0. ]

samples/c/kmeans.c

@@ -1,84 +0,0 @@
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/core/core.hpp"
-
-int main( int argc, char** argv )
-{
-    #define MAX_CLUSTERS 5
-    CvScalar color_tab[MAX_CLUSTERS];
-    IplImage* img = cvCreateImage( cvSize( 500, 500 ), 8, 3 );
-    CvRNG rng = cvRNG(-1);
-    CvPoint ipt;
-
-    color_tab[0] = CV_RGB(255,0,0);
-    color_tab[1] = CV_RGB(0,255,0);
-    color_tab[2] = CV_RGB(100,100,255);
-    color_tab[3] = CV_RGB(255,0,255);
-    color_tab[4] = CV_RGB(255,255,0);
-
-    cvNamedWindow( "clusters", 1 );
-
-    for(;;)
-    {
-        char key;
-        int k, cluster_count = cvRandInt(&rng)%MAX_CLUSTERS + 1;
-        int i, sample_count = cvRandInt(&rng)%1000 + 1;
-        CvMat* points = cvCreateMat( sample_count, 1, CV_32FC2 );
-        CvMat* clusters = cvCreateMat( sample_count, 1, CV_32SC1 );
-        cluster_count = MIN(cluster_count, sample_count);
-
-        /* generate random sample from multigaussian distribution */
-        for( k = 0; k < cluster_count; k++ )
-        {
-            CvPoint center;
-            CvMat point_chunk;
-            center.x = cvRandInt(&rng)%img->width;
-            center.y = cvRandInt(&rng)%img->height;
-            cvGetRows( points, &point_chunk, k*sample_count/cluster_count,
-                       k == cluster_count - 1 ? sample_count :
-                       (k+1)*sample_count/cluster_count, 1 );
-
-            cvRandArr( &rng, &point_chunk, CV_RAND_NORMAL,
-                       cvScalar(center.x,center.y,0,0),
-                       cvScalar(img->width*0.1,img->height*0.1,0,0));
-        }
-
-        /* shuffle samples */
-        for( i = 0; i < sample_count/2; i++ )
-        {
-            CvPoint2D32f* pt1 = (CvPoint2D32f*)points->data.fl + cvRandInt(&rng)%sample_count;
-            CvPoint2D32f* pt2 = (CvPoint2D32f*)points->data.fl + cvRandInt(&rng)%sample_count;
-            CvPoint2D32f temp;
-            CV_SWAP( *pt1, *pt2, temp );
-        }
-
-        printf( "iterations=%d\n", cvKMeans2( points, cluster_count, clusters,
-                cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0 ),
-                5, 0, 0, 0, 0 ));
-
-        cvZero( img );
-
-        for( i = 0; i < sample_count; i++ )
-        {
-            int cluster_idx = clusters->data.i[i];
-            ipt.x = (int)points->data.fl[i*2];
-            ipt.y = (int)points->data.fl[i*2+1];
-            cvCircle( img, ipt, 2, color_tab[cluster_idx], CV_FILLED, CV_AA, 0 );
-        }
-
-        cvReleaseMat( &points );
-        cvReleaseMat( &clusters );
-
-        cvShowImage( "clusters", img );
-
-        key = (char) cvWaitKey(0);
-        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
-            break;
-    }
-
-    cvDestroyWindow( "clusters" );
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"kmeans.c");
-#endif

samples/c/laplace.c

@@ -1,76 +0,0 @@
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/imgproc/imgproc.hpp"
-
-#include <ctype.h>
-#include <stdio.h>
-
-int sigma = 3;
-int smoothType = CV_GAUSSIAN;
-
-int main( int argc, char** argv )
-{
-    IplImage* laplace = 0;
-    IplImage* colorlaplace = 0;
-    IplImage* planes[3] = { 0, 0, 0 };
-    CvCapture* capture = 0;
-
-    if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
-        capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
-    else if( argc == 2 )
-        capture = cvCaptureFromAVI( argv[1] );
-
-    if( !capture )
-    {
-        fprintf(stderr,"Could not initialize capturing...\n");
-        return -1;
-    }
-
-    cvNamedWindow( "Laplacian", 0 );
-    cvCreateTrackbar( "Sigma", "Laplacian", &sigma, 15, 0 );
-
-    for(;;)
-    {
-        IplImage* frame = 0;
-        int i, c, ksize;
-
-        frame = cvQueryFrame( capture );
-        if( !frame )
-            break;
-
-        if( !laplace )
-        {
-            for( i = 0; i < 3; i++ )
-                planes[i] = cvCreateImage( cvGetSize(frame), 8, 1 );
-            laplace = cvCreateImage( cvGetSize(frame), IPL_DEPTH_16S, 1 );
-            colorlaplace = cvCreateImage( cvGetSize(frame), 8, 3 );
-        }
-
-        ksize = (sigma*5)|1;
-        cvSmooth( frame, colorlaplace, smoothType, ksize, ksize, sigma, sigma );
-        cvSplit( colorlaplace, planes[0], planes[1], planes[2], 0 );
-        for( i = 0; i < 3; i++ )
-        {
-            cvLaplace( planes[i], laplace, 5 );
-            cvConvertScaleAbs( laplace, planes[i], (sigma+1)*0.25, 0 );
-        }
-        cvMerge( planes[0], planes[1], planes[2], 0, colorlaplace );
-        colorlaplace->origin = frame->origin;
-
-        cvShowImage("Laplacian", colorlaplace );
-
-        c = cvWaitKey(30);
-        if( c == ' ' )
-            smoothType = smoothType == CV_GAUSSIAN ? CV_BLUR : smoothType == CV_BLUR ? CV_MEDIAN : CV_GAUSSIAN;
-        if( c == 'q' || c == 'Q' || (c & 255) == 27 )
-            break;
-    }
-
-    cvReleaseCapture( &capture );
-    cvDestroyWindow("Laplacian");
-
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"laplace.c");
-#endif

samples/c/minarea.c

@@ -1,100 +0,0 @@
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/imgproc/imgproc_c.h"
-
-#define ARRAY  1
-
-int main( int argc, char** argv )
-{
-    IplImage* img = cvCreateImage( cvSize( 500, 500 ), 8, 3 );
-#if !ARRAY
-    CvMemStorage* storage = cvCreateMemStorage(0);
-#endif
-
-    cvNamedWindow( "rect & circle", 1 );
-
-    for(;;)
-    {
-        char key;
-        int i, count = rand()%100 + 1;
-        CvPoint pt0, pt;
-        CvBox2D box;
-        CvPoint2D32f box_vtx[4];
-        CvPoint2D32f center;
-        CvPoint icenter;
-        float radius;
-#if !ARRAY
-        CvSeq* ptseq = cvCreateSeq( CV_SEQ_KIND_GENERIC|CV_32SC2, sizeof(CvContour),
-                                     sizeof(CvPoint), storage );
-        for( i = 0; i < count; i++ )
-        {
-            pt0.x = rand() % (img->width/2) + img->width/4;
-            pt0.y = rand() % (img->height/2) + img->height/4;
-            cvSeqPush( ptseq, &pt0 );
-        }
-#ifndef _EiC /* unfortunately, here EiC crashes */
-        box = cvMinAreaRect2( ptseq, 0 );
-#endif
-        cvMinEnclosingCircle( ptseq, &center, &radius );
-#else
-        CvPoint* points = (CvPoint*)malloc( count * sizeof(points[0]));
-        CvMat pointMat = cvMat( 1, count, CV_32SC2, points );
-
-        for( i = 0; i < count; i++ )
-        {
-            pt0.x = rand() % (img->width/2) + img->width/4;
-            pt0.y = rand() % (img->height/2) + img->height/4;
-            points[i] = pt0;
-        }
-#ifndef _EiC
-        box = cvMinAreaRect2( &pointMat, 0 );
-#endif
-        cvMinEnclosingCircle( &pointMat, &center, &radius );
-#endif
-        cvBoxPoints( box, box_vtx );
-        cvZero( img );
-        for( i = 0; i < count; i++ )
-        {
-#if !ARRAY
-            pt0 = *CV_GET_SEQ_ELEM( CvPoint, ptseq, i );
-#else
-            pt0 = points[i];
-#endif
-            cvCircle( img, pt0, 2, CV_RGB( 255, 0, 0 ), CV_FILLED, CV_AA, 0 );
-        }
-
-#ifndef _EiC
-        pt0.x = cvRound(box_vtx[3].x);
-        pt0.y = cvRound(box_vtx[3].y);
-        for( i = 0; i < 4; i++ )
-        {
-            pt.x = cvRound(box_vtx[i].x);
-            pt.y = cvRound(box_vtx[i].y);
-            cvLine(img, pt0, pt, CV_RGB(0, 255, 0), 1, CV_AA, 0);
-            pt0 = pt;
-        }
-#endif
-        icenter.x = cvRound(center.x);
-        icenter.y = cvRound(center.y);
-        cvCircle( img, icenter, cvRound(radius), CV_RGB(255, 255, 0), 1, CV_AA, 0 );
-
-        cvShowImage( "rect & circle", img );
-
-        key = (char) cvWaitKey(0);
-        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
-            break;
-
-#if !ARRAY
-        cvClearMemStorage( storage );
-#else
-        free( points );
-#endif
-    }
-
-    cvDestroyWindow( "rect & circle" );
-    return 0;
-}
-
-#ifdef _EiC
-main(1,"convexhull.c");
-#endif
-

samples/c/watershed.cpp

@@ -1,146 +0,0 @@
-#include "opencv2/imgproc/imgproc_c.h"
-#include "opencv2/highgui/highgui.hpp"
-#include <stdio.h>
-#include <stdlib.h>
-
-IplImage* marker_mask = 0;
-IplImage* markers = 0;
-IplImage* img0 = 0, *img = 0, *img_gray = 0, *wshed = 0;
-CvPoint prev_pt = {-1,-1};
-
-void on_mouse( int event, int x, int y, int flags, void* )
-{
-    if( !img )
-        return;
-
-    if( event == CV_EVENT_LBUTTONUP || !(flags & CV_EVENT_FLAG_LBUTTON) )
-        prev_pt = cvPoint(-1,-1);
-    else if( event == CV_EVENT_LBUTTONDOWN )
-        prev_pt = cvPoint(x,y);
-    else if( event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON) )
-    {
-        CvPoint pt = cvPoint(x,y);
-        if( prev_pt.x < 0 )
-            prev_pt = pt;
-        cvLine( marker_mask, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );
-        cvLine( img, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );
-        prev_pt = pt;
-        cvShowImage( "image", img );
-    }
-}
-
-
-int main( int argc, char** argv )
-{
-    char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
-    CvMemStorage* storage = cvCreateMemStorage(0);
-    CvRNG rng = cvRNG(-1);
-
-    if( (img0 = cvLoadImage(filename,1)) == 0 )
-        return 0;
-
-    printf( "Hot keys: \n"
-            "\tESC - quit the program\n"
-            "\tr - restore the original image\n"
-            "\tw or SPACE - run watershed algorithm\n"
-            "\t\t(before running it, roughly mark the areas on the image)\n"
-            "\t  (before that, roughly outline several markers on the image)\n" );
-    
-    cvNamedWindow( "image", 1 );
-    cvNamedWindow( "watershed transform", 1 );
-
-    img = cvCloneImage( img0 );
-    img_gray = cvCloneImage( img0 );
-    wshed = cvCloneImage( img0 );
-    marker_mask = cvCreateImage( cvGetSize(img), 8, 1 );
-    markers = cvCreateImage( cvGetSize(img), IPL_DEPTH_32S, 1 );
-    cvCvtColor( img, marker_mask, CV_BGR2GRAY );
-    cvCvtColor( marker_mask, img_gray, CV_GRAY2BGR );
-
-    cvZero( marker_mask );
-    cvZero( wshed );
-    cvShowImage( "image", img );
-    cvShowImage( "watershed transform", wshed );
-    cvSetMouseCallback( "image", on_mouse, 0 );
-
-    for(;;)
-    {
-        int c = cvWaitKey(0);
-
-        if( (char)c == 27 )
-            break;
-
-        if( (char)c == 'r' )
-        {
-            cvZero( marker_mask );
-            cvCopy( img0, img );
-            cvShowImage( "image", img );
-        }
-
-        if( (char)c == 'w' || (char)c == ' ' )
-        {
-            CvSeq* contours = 0;
-            CvMat* color_tab = 0;
-            int i, j, comp_count = 0;
-            
-            cvClearMemStorage(storage);
-            
-            //cvSaveImage( "wshed_mask.png", marker_mask );
-            //marker_mask = cvLoadImage( "wshed_mask.png", 0 );
-            cvFindContours( marker_mask, storage, &contours, sizeof(CvContour),
-                            CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
-            cvZero( markers );
-            for( ; contours != 0; contours = contours->h_next, comp_count++ )
-            {
-                cvDrawContours( markers, contours, cvScalarAll(comp_count+1),
-                                cvScalarAll(comp_count+1), -1, -1, 8, cvPoint(0,0) );
-            }
-
-            if( comp_count == 0 )
-                continue;
-            
-            color_tab = cvCreateMat( 1, comp_count, CV_8UC3 );
-            for( i = 0; i < comp_count; i++ )
-            {
-                uchar* ptr = color_tab->data.ptr + i*3;
-                ptr[0] = (uchar)(cvRandInt(&rng)%180 + 50);
-                ptr[1] = (uchar)(cvRandInt(&rng)%180 + 50);
-                ptr[2] = (uchar)(cvRandInt(&rng)%180 + 50);
-            }
-
-            {
-            double t = (double)cvGetTickCount();
-            cvWatershed( img0, markers );
-            t = (double)cvGetTickCount() - t;
-            printf( "exec time = %gms\n", t/(cvGetTickFrequency()*1000.) );
-            }
-
-            // paint the watershed image
-            for( i = 0; i < markers->height; i++ )
-                for( j = 0; j < markers->width; j++ )
-                {
-                    int idx = CV_IMAGE_ELEM( markers, int, i, j );
-                    uchar* dst = &CV_IMAGE_ELEM( wshed, uchar, i, j*3 );
-                    if( idx == -1 )
-                        dst[0] = dst[1] = dst[2] = (uchar)255;
-                    else if( idx <= 0 || idx > comp_count )
-                        dst[0] = dst[1] = dst[2] = (uchar)0; // should not get here
-                    else
-                    {
-                        uchar* ptr = color_tab->data.ptr + (idx-1)*3;
-                        dst[0] = ptr[0]; dst[1] = ptr[1]; dst[2] = ptr[2];
-                    }
-                }
-
-            cvAddWeighted( wshed, 0.5, img_gray, 0.5, 0, wshed );
-            cvShowImage( "watershed transform", wshed );
-            cvReleaseMat( &color_tab );
-        }
-    }
-
-    return 1;
-}
-
-#ifdef _EiC
-main(1,"watershed.cpp");
-#endif

samples/cpp/camshiftdemo.cpp

@@ -1,7 +1,7 @@
 #include <opencv2/video/tracking.hpp>
 #include <opencv2/highgui/highgui.hpp>
 
-#include <stdio.h>
+#include <iostream>
 #include <ctype.h>
 
 IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;
@@ -21,25 +21,19 @@ float hranges_arr[] = {0,180};
 float* hranges = hranges_arr;
 int vmin = 10, vmax = 256, smin = 30;
 
-void on_mouse( int event, int x, int y, int flags, void* param )
+void onMouse( int event, int x, int y, int flags, void* param )
 {
-    if( !image )
+    if( selectObject )
-        return;
-
-    if( image->origin )
-        y = image->height - y;
-
-    if( select_object )
     {
         selection.x = MIN(x, origin.x);
         selection.y = MIN(y, origin.y);
-        selection.width = selection.x + CV_IABS(x - origin.x);
+        selection.width = selection.x + std::abs(x - origin.x);
-        selection.height = selection.y + CV_IABS(y - origin.y);
+        selection.height = selection.y + std::abs(y - origin.y);
 
         selection.x = MAX(selection.x, 0);
         selection.y = MAX(selection.y, 0);
-        selection.width = MIN( selection.width, image->width );
+        selection.width = MIN(selection.width, image.cols);
-        selection.height = MIN( selection.height, image->height );
+        selection.height = MIN(selection.height, image.rows);
         selection.width -= selection.x;
         selection.height -= selection.y;
     }
@@ -47,23 +41,23 @@ void on_mouse( int event, int x, int y, int flags, void* param )
     switch( event )
     {
     case CV_EVENT_LBUTTONDOWN:
-        origin = cvPoint(x,y);
+        origin = Point(x,y);
-        selection = cvRect(x,y,0,0);
+        selection = Rect(x,y,0,0);
-        select_object = 1;
+        selectObject = true;
         break;
     case CV_EVENT_LBUTTONUP:
-        select_object = 0;
+        selectObject = false;
         if( selection.width > 0 && selection.height > 0 )
-            track_object = -1;
+            trackObject = -1;
         break;
     }
 }
 
 
-CvScalar hsv2rgb( float hue )
+Scalar hsv2rgb( float hue )
 {
     int rgb[3], p, sector;
-    static const int sector_data[][3]=
+    static const int sectorData[][3]=
         {{0,2,1}, {1,2,0}, {1,0,2}, {2,0,1}, {2,1,0}, {0,1,2}};
     hue *= 0.033333333333333333333333333333333f;
     sector = cvFloor(hue);
@@ -218,7 +212,3 @@ int main( int argc, char** argv )
 
     return 0;
 }
-
-#ifdef _EiC
-main(1,"camshiftdemo.c");
-#endif

samples/cpp/convexhull.cpp

@@ -0,0 +1,52 @@
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+using namespace cv;
+
+int main( int argc, char** argv )
+{
+    Mat img(500, 500, CV_8UC3);
+    RNG& rng = theRNG();
+
+    for(;;)
+    {
+        char key;
+        int i, count = (unsigned)rng%100 + 1;
+        
+        vector<Point> points;
+
+        for( i = 0; i < count; i++ )
+        {
+            Point pt;
+            pt.x = rng.uniform(img.cols/4, img.cols*3/4);
+            pt.y = rng.uniform(img.rows/4, img.rows*3/4);
+            
+            points.push_back(pt);
+        }
+        
+        vector<int> hull;
+        convexHull(Mat(points), hull, CV_CLOCKWISE);
+        
+        img = Scalar::all(0);
+        for( i = 0; i < count; i++ )
+            circle(img, points[i], 3, Scalar(0, 0, 255), CV_FILLED, CV_AA);
+        
+        int hullcount = (int)hull.size();
+        Point pt0 = points[hull[hullcount-1]];
+        
+        for( i = 0; i < hullcount; i++ )
+        {
+            Point pt = points[hull[i]];
+            line(img, pt0, pt, Scalar(0, 255, 0), 1, CV_AA);
+            pt0 = pt;
+        }
+
+        imshow("hull", img);
+
+        key = (char)waitKey();
+        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
+            break;
+    }
+
+    return 0;
+}

samples/cpp/demhist.cpp

@@ -0,0 +1,80 @@
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+int _brightness = 100;
+int _contrast = 100;
+
+Mat image;
+
+/* brightness/contrast callback function */
+void updateBrightnessContrast( int arg, void* )
+{
+    int histSize = 64;
+    int brightness = _brightness - 100;
+    int contrast = _contrast - 100;
+
+    /*
+     * The algorithm is by Werner D. Streidt
+     * (http://visca.com/ffactory/archives/5-99/msg00021.html)
+     */
+    double a, b;
+    if( contrast > 0 )
+    {
+        double delta = 127.*contrast/100;
+        a = 255./(255. - delta*2);
+        b = a*(brightness - delta);
+    }
+    else
+    {
+        double delta = -128.*contrast/100;
+        a = (256.-delta*2)/255.;
+        b = a*brightness + delta;
+    }
+
+    Mat dst, hist;
+    image.convertTo(dst, CV_8U, a, b);
+    imshow("image", dst);
+
+    calcHist(&dst, 1, 0, Mat(), hist, 1, &histSize, 0);
+    Mat histImage = Mat::ones(200, 320, CV_8U)*255;
+    
+    normalize(hist, hist, 0, histImage.rows, CV_MINMAX, CV_32F);
+
+    histImage = Scalar::all(255);
+    int binW = cvRound((double)histImage.cols/histSize);
+
+    for( int i = 0; i < histSize; i++ )
+        rectangle( histImage, Point(i*binW, histImage.rows),
+                   Point((i+1)*binW, histImage.rows - cvRound(hist.at<float>(i))),
+                   Scalar::all(0), -1, 8, 0 );
+    imshow("histogram", histImage);
+}
+
+
+int main( int argc, char** argv )
+{
+    // Load the source image. HighGUI use.
+    image = imread( argc == 2 ? argv[1] : "baboon.jpg", 0 );
+
+    if( image.empty() )
+    {
+        cout << "Image was not loaded.\n";
+        return -1;
+    }
+
+    namedWindow("image", 0);
+    namedWindow("histogram", 0);
+
+    createTrackbar("brightness", "image", &_brightness, 200, updateBrightnessContrast);
+    createTrackbar("contrast", "image", &_contrast, 200, updateBrightnessContrast);
+
+    updateBrightnessContrast(0, 0);
+    waitKey();
+
+    return 0;
+}

samples/cpp/dft.cpp

@@ -0,0 +1,67 @@
+#include <opencv2/core/core.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+int main(int argc, char ** argv)
+{
+    const char* filename = argc >=2 ? argv[1] : "lena.jpg";
+
+    Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
+    if( img.empty() )
+    {
+        cout << "Usage: dft <image_name>" << endl;
+        return -1;
+    }
+
+    int M = getOptimalDFTSize( img.rows );
+    int N = getOptimalDFTSize( img.cols );
+    Mat padded;
+    copyMakeBorder(img, padded, 0, M - img.rows, 0, N - img.cols, BORDER_CONSTANT, Scalar::all(0));
+    
+    Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
+    Mat complexImg;
+    merge(planes, 2, complexImg);
+    
+    dft(complexImg, complexImg);
+    
+    // compute log(1 + sqrt(Re(DFT(img))**2 + Im(DFT(img))**2))
+    split(complexImg, planes);
+    magnitude(planes[0], planes[1], planes[0]);
+    Mat mag = planes[0];
+    mag += Scalar::all(1);
+    log(mag, mag);
+    
+    // crop the spectrum, if it has an odd number of rows or columns
+    mag = mag(Rect(0, 0, mag.cols & -2, mag.rows & -2));
+    
+    int cx = mag.cols/2;
+    int cy = mag.rows/2;
+    
+    // rearrange the quadrants of Fourier image
+    // so that the origin is at the image center
+    Mat tmp;
+    Mat q0(mag, Rect(0, 0, cx, cy));
+    Mat q1(mag, Rect(cx, 0, cx, cy));
+    Mat q2(mag, Rect(0, cy, cx, cy));
+    Mat q3(mag, Rect(cx, cy, cx, cy));
+    
+    q0.copyTo(tmp);
+    q3.copyTo(q0);
+    tmp.copyTo(q3);
+    
+    q1.copyTo(tmp);
+    q2.copyTo(q1);
+    tmp.copyTo(q2);
+    
+    normalize(mag, mag, 0, 1, CV_MINMAX);
+    
+    imshow("spectrum magnitude", mag);
+    waitKey();
+    return 0;
+}
+

samples/cpp/distrans.cpp

@@ -0,0 +1,156 @@
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+#include <stdio.h>
+
+using namespace cv;
+
+int maskSize0 = CV_DIST_MASK_5;
+bool buildVoronoi = false;
+int edgeThresh = 100;
+int distType0 = CV_DIST_L1;
+
+// The output and temporary images
+Mat gray;
+
+// threshold trackbar callback
+void onTrackbar( int, void* )
+{
+    static const Scalar colors[] =
+    {
+        Scalar(0,0,0),
+        Scalar(255,0,0),
+        Scalar(255,128,0),
+        Scalar(255,255,0),
+        Scalar(0,255,0),
+        Scalar(0,128,255),
+        Scalar(0,255,255),
+        Scalar(0,0,255),
+        Scalar(255,0,255)
+    };
+
+    int maskSize = buildVoronoi ? CV_DIST_MASK_5 : maskSize0;
+    int distType = buildVoronoi ? CV_DIST_L2 : distType0;
+
+    Mat edge = gray >= edgeThresh, dist, labels, dist8u;
+
+    if( !buildVoronoi )
+        distanceTransform( edge, dist, distType, maskSize );
+    else
+        distanceTransform( edge, dist, labels, distType, maskSize );
+
+    if( !buildVoronoi )
+    {
+        // begin "painting" the distance transform result
+        dist *= 5000;
+        pow(dist, 0.5, dist);
+        
+        Mat dist32s, dist8u1, dist8u2;
+        
+        dist.convertTo(dist32s, CV_32S, 1, 0.5);
+        dist32s &= Scalar::all(255);
+        
+        dist32s.convertTo(dist8u1, CV_8U, 1, 0);
+        dist32s *= -1;
+        
+        dist32s += Scalar::all(255);
+        dist32s.convertTo(dist8u2, CV_8U);
+        
+        Mat planes[] = {dist8u1, dist8u2, dist8u2};
+        merge(planes, 3, dist8u); 
+    }
+    else
+    {
+        dist8u.create(labels.size(), CV_8UC3);
+        for( int i = 0; i < labels.rows; i++ )
+        {
+            const int* ll = (const int*)labels.ptr(i);
+            const float* dd = (const float*)dist.ptr(i);
+            uchar* d = (uchar*)dist8u.ptr(i);
+            for( int j = 0; j < labels.cols; j++ )
+            {
+                int idx = ll[j] == 0 || dd[j] == 0 ? 0 : (ll[j]-1)%8 + 1;
+                int b = cvRound(colors[idx][0]);
+                int g = cvRound(colors[idx][1]);
+                int r = cvRound(colors[idx][2]);
+                d[j*3] = (uchar)b;
+                d[j*3+1] = (uchar)g;
+                d[j*3+2] = (uchar)r;
+            }
+        }
+    }
+
+    imshow("Distance Map", dist8u );
+}
+
+int main( int argc, char** argv )
+{
+    char* filename = argc == 2 ? argv[1] : (char*)"stuff.jpg";
+    gray = imread(filename, 0);
+    if(gray.empty())
+    {
+        printf("Usage: distrans <image_name>\n");
+        return 0;
+    }
+
+    printf( "Hot keys: \n"
+        "\tESC - quit the program\n"
+        "\tC - use C/Inf metric\n"
+        "\tL1 - use L1 metric\n"
+        "\tL2 - use L2 metric\n"
+        "\t3 - use 3x3 mask\n"
+        "\t5 - use 5x5 mask\n"
+        "\t0 - use precise distance transform\n"
+        "\tv - switch Voronoi diagram mode on/off\n"
+        "\tSPACE - loop through all the modes\n" );
+
+    namedWindow("Distance Map", 1);
+    createTrackbar("Brightness Threshold", "Distance Map", &edgeThresh, 255, onTrackbar, 0);
+
+    for(;;)
+    {
+        // Call to update the view
+        onTrackbar(0, 0);
+
+        int c = cvWaitKey(0);
+
+        if( (char)c == 27 )
+            break;
+
+        if( (char)c == 'c' || (char)c == 'C' )
+            distType0 = CV_DIST_C;
+        else if( (char)c == '1' )
+            distType0 = CV_DIST_L1;
+        else if( (char)c == '2' )
+            distType0 = CV_DIST_L2;
+        else if( (char)c == '3' )
+            maskSize0 = CV_DIST_MASK_3;
+        else if( (char)c == '5' )
+            maskSize0 = CV_DIST_MASK_5;
+        else if( (char)c == '0' )
+            maskSize0 = CV_DIST_MASK_PRECISE;
+        else if( (char)c == 'v' )
+            buildVoronoi = !buildVoronoi;
+        else if( (char)c == ' ' )
+        {
+            if( buildVoronoi )
+            {
+                buildVoronoi = false;
+                maskSize0 = CV_DIST_MASK_3;
+                distType0 = CV_DIST_C;
+            }
+            else if( distType0 == CV_DIST_C )
+                distType0 = CV_DIST_L1;
+            else if( distType0 == CV_DIST_L1 )
+                distType0 = CV_DIST_L2;
+            else if( maskSize0 == CV_DIST_MASK_3 )
+                maskSize0 = CV_DIST_MASK_5;
+            else if( maskSize0 == CV_DIST_MASK_5 )
+                maskSize0 = CV_DIST_MASK_PRECISE;
+            else if( maskSize0 == CV_DIST_MASK_PRECISE )
+                buildVoronoi = true;
+        }
+    }
+
+    return 0;
+}

samples/cpp/drawing.cpp

@@ -0,0 +1,174 @@
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+using namespace cv;
+
+static Scalar randomColor(RNG& rng)
+{
+    int icolor = (unsigned)rng;
+    return Scalar(icolor&255, (icolor>>8)&255, (icolor>>16)&255);
+}
+
+int main( int argc, char** argv )
+{
+    char wndname[] = "Drawing Demo";
+    const int NUMBER = 100;
+    const int DELAY = 5;
+    int lineType = CV_AA; // change it to 8 to see non-antialiased graphics
+    int i, width = 1000, height = 700;
+    int x1 = -width/2, x2 = width*3/2, y1 = -height/2, y2 = height*3/2;
+    RNG rng(-1);
+
+    Mat image = Mat::zeros(height, width, CV_8UC3);
+    imshow(wndname, image);
+    waitKey(DELAY);
+
+    for (i = 0; i < NUMBER; i++)
+    {
+        Point pt1, pt2;
+        pt1.x = rng.uniform(x1, x2);
+        pt1.y = rng.uniform(y1, y2);
+        pt2.x = rng.uniform(x1, x2);
+        pt2.y = rng.uniform(y1, y2);
+
+        line( image, pt1, pt2, randomColor(rng), rng.uniform(1,10), lineType );
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    for (i = 0; i < NUMBER; i++)
+    {
+        Point pt1, pt2;
+        pt1.x = rng.uniform(x1, x2);
+        pt1.y = rng.uniform(y1, y2);
+        pt2.x = rng.uniform(x1, x2);
+        pt2.y = rng.uniform(y1, y2);
+        int thickness = rng.uniform(-3, 10);
+        
+        rectangle( image, pt1, pt2, randomColor(rng), MAX(thickness, -1), lineType );
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+    
+    for (i = 0; i < NUMBER; i++)
+    {
+        Point center;
+        center.x = rng.uniform(x1, x2);
+        center.y = rng.uniform(y1, y2);
+        Size axes;
+        axes.width = rng.uniform(0, 200);
+        axes.height = rng.uniform(0, 200);
+        double angle = rng.uniform(0, 180);
+
+        ellipse( image, center, axes, angle, angle - 100, angle + 200,
+                 randomColor(rng), rng.uniform(-1,9), lineType );
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    for (i = 0; i< NUMBER; i++)
+    {
+        Point pt[2][3];
+        pt[0][0].x = rng.uniform(x1, x2);
+        pt[0][0].y = rng.uniform(y1, y2);
+        pt[0][1].x = rng.uniform(x1, x2); 
+        pt[0][1].y = rng.uniform(y1, y2); 
+        pt[0][2].x = rng.uniform(x1, x2);
+        pt[0][2].y = rng.uniform(y1, y2);
+        pt[1][0].x = rng.uniform(x1, x2); 
+        pt[1][0].y = rng.uniform(y1, y2);
+        pt[1][1].x = rng.uniform(x1, x2); 
+        pt[1][1].y = rng.uniform(y1, y2);
+        pt[1][2].x = rng.uniform(x1, x2); 
+        pt[1][2].y = rng.uniform(y1, y2);
+        const Point* ppt[2] = {pt[0], pt[1]};
+        int npt[] = {3, 3};
+        
+        polylines(image, ppt, npt, 2, true, randomColor(rng), rng.uniform(1,10), lineType);
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+    
+    for (i = 0; i< NUMBER; i++)
+    {
+        Point pt[2][3];
+        pt[0][0].x = rng.uniform(x1, x2);
+        pt[0][0].y = rng.uniform(y1, y2);
+        pt[0][1].x = rng.uniform(x1, x2); 
+        pt[0][1].y = rng.uniform(y1, y2); 
+        pt[0][2].x = rng.uniform(x1, x2);
+        pt[0][2].y = rng.uniform(y1, y2);
+        pt[1][0].x = rng.uniform(x1, x2); 
+        pt[1][0].y = rng.uniform(y1, y2);
+        pt[1][1].x = rng.uniform(x1, x2); 
+        pt[1][1].y = rng.uniform(y1, y2);
+        pt[1][2].x = rng.uniform(x1, x2); 
+        pt[1][2].y = rng.uniform(y1, y2);
+        const Point* ppt[2] = {pt[0], pt[1]};
+        int npt[] = {3, 3};
+        
+        fillPoly(image, ppt, npt, 2, randomColor(rng), lineType);
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    for (i = 0; i < NUMBER; i++)
+    {
+        Point center;
+        center.x = rng.uniform(x1, x2);
+        center.y = rng.uniform(y1, y2);
+        
+        circle(image, center, rng.uniform(0, 300), randomColor(rng),
+               rng.uniform(-1, 9), lineType);
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    for (i = 1; i < NUMBER; i++)
+    {
+        Point org;
+        org.x = rng.uniform(x1, x2);
+        org.y = rng.uniform(y1, y2);
+
+        putText(image, "Testing text rendering", org, rng.uniform(0,8),
+                rng.uniform(0,100)*0.05+0.1, randomColor(rng), rng.uniform(1, 10), lineType);
+        
+        imshow(wndname, image);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    Size textsize = getTextSize("OpenCV forever!", CV_FONT_HERSHEY_COMPLEX, 3, 5, 0);
+    Point org((width - textsize.width)/2, (height - textsize.height)/2);
+    
+    Mat image2;
+    for( i = 0; i < 255; i += 2 )
+    {
+        image2 = image - Scalar::all(i);
+        putText(image2, "OpenCV forever!", org, CV_FONT_HERSHEY_COMPLEX, 3,
+                Scalar(i, i, 255), 5, lineType);
+        
+        imshow(wndname, image2);
+        if(waitKey(DELAY) >= 0)
+            return 0;
+    }
+
+    waitKey();
+    return 0;
+}
+
+#ifdef _EiC
+main(1,"drawing.c");
+#endif

samples/cpp/edge.cpp

@@ -0,0 +1,52 @@
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+int edgeThresh = 1;
+Mat image, gray, edge, cedge;
+
+// define a trackbar callback
+void onTrackbar(int, void*)
+{
+    blur(gray, edge, Size(3,3));
+
+    // Run the edge detector on grayscale
+    Canny(edge, edge, edgeThresh, edgeThresh*3, 3);
+    cedge = Scalar::all(0);
+    
+    image.copyTo(cedge, edge);
+    imshow("Edge map", cedge);
+}
+
+int main( int argc, char** argv )
+{
+    char* filename = argc == 2 ? argv[1] : (char*)"fruits.jpg";
+
+    image = imread(filename, 1);
+    if(image.empty())
+    {
+        cout << "Usage: edge <image_name>" << endl;
+        return -1;
+    }
+
+    cedge.create(image.size(), image.type());
+    cvtColor(image, gray, CV_BGR2GRAY);
+
+    // Create a window
+    namedWindow("Edge map", 1);
+
+    // create a toolbar
+    createTrackbar("Canny threshold", "Edge map", &edgeThresh, 100, onTrackbar);
+
+    // Show the image
+    onTrackbar(0, 0);
+
+    // Wait for a key stroke; the same function arranges events processing
+    waitKey(0);
+
+    return 0;
+}

samples/cpp/ffilldemo.cpp

@@ -0,0 +1,156 @@
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui/highgui.hpp>
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+Mat image0, image, gray, mask;
+int ffillMode = 1;
+int loDiff = 20, upDiff = 20;
+int connectivity = 4;
+int isColor = true;
+bool useMask = false;
+int newMaskVal = 255;
+
+void onMouse( int event, int x, int y, int, void* param )
+{
+    if( event != CV_EVENT_LBUTTONDOWN )
+        return;
+
+    Point seed = Point(x,y);
+    int lo = ffillMode == 0 ? 0 : loDiff;
+    int up = ffillMode == 0 ? 0 : upDiff;
+    int flags = connectivity + (newMaskVal << 8) +
+                (ffillMode == 1 ? CV_FLOODFILL_FIXED_RANGE : 0);
+    int b = (unsigned)theRNG() & 255;
+    int g = (unsigned)theRNG() & 255;
+    int r = (unsigned)theRNG() & 255;
+    Rect ccomp;
+
+    Scalar newVal = isColor ? Scalar(b, g, r) : Scalar(r*0.299 + g*0.587 + b*0.114);
+    Mat dst = isColor ? image : gray;
+    int area;
+    
+    if( useMask )
+    {
+        threshold(mask, mask, 1, 128, CV_THRESH_BINARY);
+        area = floodFill(dst, mask, seed, newVal, &ccomp, Scalar(lo, lo, lo),
+                  Scalar(up, up, up), flags);
+        imshow( "mask", mask );
+    }
+    else
+    {
+        area = floodFill(dst, seed, newVal, &ccomp, Scalar(lo, lo, lo),
+                  Scalar(up, up, up), flags);
+    }
+    
+    imshow("image", dst);
+    cout << area << " pixels were repainted\n";
+}
+
+
+int main( int argc, char** argv )
+{
+    char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
+    image0 = imread(filename, 1);
+    
+    if( image0.empty() )
+    {
+        cout << "Usage: ffilldemo <image_name>\n";
+        return 0;
+    }
+
+    cout << "Hot keys: \n"
+            "\tESC - quit the program\n"
+            "\tc - switch color/grayscale mode\n"
+            "\tm - switch mask mode\n"
+            "\tr - restore the original image\n"
+            "\ts - use null-range floodfill\n"
+            "\tf - use gradient floodfill with fixed(absolute) range\n"
+            "\tg - use gradient floodfill with floating(relative) range\n"
+            "\t4 - use 4-connectivity mode\n"
+            "\t8 - use 8-connectivity mode\n";
+
+    image0.copyTo(image);
+    cvtColor(image0, gray, CV_BGR2GRAY);
+    mask.create(image0.rows+2, image0.cols+2, CV_8UC1);
+
+    namedWindow( "image", 0 );
+    createTrackbar( "lo_diff", "image", &loDiff, 255, 0 );
+    createTrackbar( "up_diff", "image", &upDiff, 255, 0 );
+
+    setMouseCallback( "image", onMouse, 0 );
+
+    for(;;)
+    {
+        imshow("image", isColor ? image : gray);
+
+        int c = waitKey(0);
+        switch( (char)c )
+        {
+        case 27:
+            cout << "Exiting ...\n";
+            return 0;
+        case 'c':
+            if( isColor )
+            {
+                cout << "Grayscale mode is set\n";
+                cvtColor(image0, gray, CV_BGR2GRAY);
+                mask = Scalar::all(0);
+                isColor = false;
+            }
+            else
+            {
+                cout << "Color mode is set\n";
+                image0.copyTo(image);
+                mask = Scalar::all(0);
+                isColor = true;
+            }
+            break;
+        case 'm':
+            if( useMask )
+            {
+                destroyWindow( "mask" );
+                useMask = false;
+            }
+            else
+            {
+                namedWindow( "mask", 0 );
+                mask = Scalar::all(0);
+                imshow("mask", mask);
+                useMask = true;
+            }
+            break;
+        case 'r':
+            cout << "Original image is restored\n";
+            image0.copyTo(image);
+            cvtColor(image, gray, CV_BGR2GRAY);
+            mask = Scalar::all(0);
+            break;
+        case 's':
+            cout << "Simple floodfill mode is set\n";
+            ffillMode = 0;
+            break;
+        case 'f':
+            cout << "Fixed Range floodfill mode is set\n";
+            ffillMode = 1;
+            break;
+        case 'g':
+            cout << "Gradient (floating range) floodfill mode is set\n";
+            ffillMode = 2;
+            break;
+        case '4':
+            cout << "4-connectivity mode is set\n";
+            connectivity = 4;
+            break;
+        case '8':
+            cout << "8-connectivity mode is set\n";
+            connectivity = 8;
+            break;
+        }
+    }
+
+    return 0;
+}

samples/cpp/kmeans.cpp

@@ -0,0 +1,65 @@
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/core/core.hpp"
+
+using namespace cv;
+
+int main( int argc, char** argv )
+{
+    const int MAX_CLUSTERS = 5;
+    Scalar colorTab[] =
+    {
+        Scalar(0, 0, 255),
+        Scalar(0,255,0),
+        Scalar(255,100,100),
+        Scalar(255,0,255),
+        Scalar(0,255,255)
+    };
+        
+    Mat img(500, 500, CV_8UC3);
+    RNG rng(12345);
+
+    for(;;)
+    {
+        int k, clusterCount = rng.uniform(2, MAX_CLUSTERS+1);
+        int i, sampleCount = rng.uniform(1, 1001);
+        Mat points(sampleCount, 1, CV_32FC2), labels;
+        
+        clusterCount = MIN(clusterCount, sampleCount);
+        Mat centers(clusterCount, 1, points.type());
+
+        /* generate random sample from multigaussian distribution */
+        for( k = 0; k < clusterCount; k++ )
+        {
+            Point center;
+            center.x = rng.uniform(0, img.cols);
+            center.y = rng.uniform(0, img.rows);
+            Mat pointChunk = points.rowRange(k*sampleCount/clusterCount,
+                                             k == clusterCount - 1 ? sampleCount :
+                                             (k+1)*sampleCount/clusterCount);
+            rng.fill(pointChunk, CV_RAND_NORMAL, Scalar(center.x, center.y), Scalar(img.cols*0.05, img.rows*0.05));
+        }
+
+        randShuffle(points, 1, &rng);
+
+        kmeans(points, clusterCount, labels, 
+               TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0),
+               3, KMEANS_PP_CENTERS, &centers);
+
+        img = Scalar::all(0);
+
+        for( i = 0; i < sampleCount; i++ )
+        {
+            int clusterIdx = labels.at<int>(i);
+            Point ipt = points.at<Point2f>(i);
+            circle( img, ipt, 2, colorTab[clusterIdx], CV_FILLED, CV_AA );
+        }
+
+        imshow("clusters", img);
+
+        char key = (char)waitKey();
+        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
+            break;
+    }
+
+    return 0;
+}

samples/cpp/laplace.cpp

@@ -0,0 +1,60 @@
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+#include <ctype.h>
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+int sigma = 3;
+int smoothType = CV_GAUSSIAN;
+
+int main( int argc, char** argv )
+{
+    VideoCapture cap;
+
+    if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
+        cap.open(argc == 2 ? argv[1][0] - '0' : 0);
+    else if( argc == 2 )
+        cap.open(argv[1]);
+
+    if( !cap.isOpened() )
+    {
+        cout << "Could not initialize capturing...\n";
+        return -1;
+    }
+
+    namedWindow( "Laplacian", 0 );
+    createTrackbar( "Sigma", "Laplacian", &sigma, 15, 0 );
+
+    Mat smoothed, laplace, result;
+    
+    for(;;)
+    {
+        Mat frame;
+        cap >> frame;
+        if( frame.empty() )
+            break;
+
+        int ksize = (sigma*5)|1;
+        if(smoothType == CV_GAUSSIAN)
+            GaussianBlur(frame, smoothed, Size(ksize, ksize), sigma, sigma);
+        else if(smoothType == CV_BLUR)
+            blur(frame, smoothed, Size(ksize, ksize));
+        else
+            medianBlur(frame, smoothed, ksize);
+        
+        Laplacian(smoothed, laplace, CV_16S, 5);
+        convertScaleAbs(laplace, result, (sigma+1)*0.25);
+        imshow("Laplacian", result);
+
+        int c = waitKey(30);
+        if( c == ' ' )
+            smoothType = smoothType == CV_GAUSSIAN ? CV_BLUR : smoothType == CV_BLUR ? CV_MEDIAN : CV_GAUSSIAN;
+        if( c == 'q' || c == 'Q' || (c & 255) == 27 )
+            break;
+    }
+
+    return 0;
+}

samples/cpp/letter_recog.cpp

@@ -0,0 +1,530 @@
+#include "opencv2/core/core_c.h"
+#include "opencv2/ml/ml.hpp"
+
+/*
+The sample demonstrates how to train Random Trees classifier
+(or Boosting classifier, or MLP - see main()) using the provided dataset.
+
+We use the sample database letter-recognition.data
+from UCI Repository, here is the link:
+
+Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998).
+UCI Repository of machine learning databases
+[http://www.ics.uci.edu/~mlearn/MLRepository.html].
+Irvine, CA: University of California, Department of Information and Computer Science.
+
+The dataset consists of 20000 feature vectors along with the
+responses - capital latin letters A..Z.
+The first 16000 (10000 for boosting)) samples are used for training
+and the remaining 4000 (10000 for boosting) - to test the classifier.
+*/
+
+// This function reads data and responses from the file <filename>
+static int
+read_num_class_data( const char* filename, int var_count,
+                     CvMat** data, CvMat** responses )
+{
+    const int M = 1024;
+    FILE* f = fopen( filename, "rt" );
+    CvMemStorage* storage;
+    CvSeq* seq;
+    char buf[M+2];
+    float* el_ptr;
+    CvSeqReader reader;
+    int i, j;
+
+    if( !f )
+        return 0;
+
+    el_ptr = new float[var_count+1];
+    storage = cvCreateMemStorage();
+    seq = cvCreateSeq( 0, sizeof(*seq), (var_count+1)*sizeof(float), storage );
+
+    for(;;)
+    {
+        char* ptr;
+        if( !fgets( buf, M, f ) || !strchr( buf, ',' ) )
+            break;
+        el_ptr[0] = buf[0];
+        ptr = buf+2;
+        for( i = 1; i <= var_count; i++ )
+        {
+            int n = 0;
+            sscanf( ptr, "%f%n", el_ptr + i, &n );
+            ptr += n + 1;
+        }
+        if( i <= var_count )
+            break;
+        cvSeqPush( seq, el_ptr );
+    }
+    fclose(f);
+
+    *data = cvCreateMat( seq->total, var_count, CV_32F );
+    *responses = cvCreateMat( seq->total, 1, CV_32F );
+
+    cvStartReadSeq( seq, &reader );
+
+    for( i = 0; i < seq->total; i++ )
+    {
+        const float* sdata = (float*)reader.ptr + 1;
+        float* ddata = data[0]->data.fl + var_count*i;
+        float* dr = responses[0]->data.fl + i;
+
+        for( j = 0; j < var_count; j++ )
+            ddata[j] = sdata[j];
+        *dr = sdata[-1];
+        CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
+    }
+
+    cvReleaseMemStorage( &storage );
+    delete el_ptr;
+    return 1;
+}
+
+static
+int build_rtrees_classifier( char* data_filename,
+    char* filename_to_save, char* filename_to_load )
+{
+    CvMat* data = 0;
+    CvMat* responses = 0;
+    CvMat* var_type = 0;
+    CvMat* sample_idx = 0;
+
+    int ok = read_num_class_data( data_filename, 16, &data, &responses );
+    int nsamples_all = 0, ntrain_samples = 0;
+    int i = 0;
+    double train_hr = 0, test_hr = 0;
+    CvRTrees forest;
+    CvMat* var_importance = 0;
+
+    if( !ok )
+    {
+        printf( "Could not read the database %s\n", data_filename );
+        return -1;
+    }
+
+    printf( "The database %s is loaded.\n", data_filename );
+    nsamples_all = data->rows;
+    ntrain_samples = (int)(nsamples_all*0.8);
+
+    // Create or load Random Trees classifier
+    if( filename_to_load )
+    {
+        // load classifier from the specified file
+        forest.load( filename_to_load );
+        ntrain_samples = 0;
+        if( forest.get_tree_count() == 0 )
+        {
+            printf( "Could not read the classifier %s\n", filename_to_load );
+            return -1;
+        }
+        printf( "The classifier %s is loaded.\n", data_filename );
+    }
+    else
+    {
+        // create classifier by using <data> and <responses>
+        printf( "Training the classifier ...\n");
+
+        // 1. create type mask
+        var_type = cvCreateMat( data->cols + 1, 1, CV_8U );
+        cvSet( var_type, cvScalarAll(CV_VAR_ORDERED) );
+        cvSetReal1D( var_type, data->cols, CV_VAR_CATEGORICAL );
+
+        // 2. create sample_idx
+        sample_idx = cvCreateMat( 1, nsamples_all, CV_8UC1 );
+        {
+            CvMat mat;
+            cvGetCols( sample_idx, &mat, 0, ntrain_samples );
+            cvSet( &mat, cvRealScalar(1) );
+
+            cvGetCols( sample_idx, &mat, ntrain_samples, nsamples_all );
+            cvSetZero( &mat );
+        }
+
+        // 3. train classifier
+        forest.train( data, CV_ROW_SAMPLE, responses, 0, sample_idx, var_type, 0,
+            CvRTParams(10,10,0,false,15,0,true,4,100,0.01f,CV_TERMCRIT_ITER));
+        printf( "\n");
+    }
+
+    // compute prediction error on train and test data
+    for( i = 0; i < nsamples_all; i++ )
+    {
+        double r;
+        CvMat sample;
+        cvGetRow( data, &sample, i );
+
+        r = forest.predict( &sample );
+        r = fabs((double)r - responses->data.fl[i]) <= FLT_EPSILON ? 1 : 0;
+
+        if( i < ntrain_samples )
+            train_hr += r;
+        else
+            test_hr += r;
+    }
+
+    test_hr /= (double)(nsamples_all-ntrain_samples);
+    train_hr /= (double)ntrain_samples;
+    printf( "Recognition rate: train = %.1f%%, test = %.1f%%\n",
+            train_hr*100., test_hr*100. );
+
+    printf( "Number of trees: %d\n", forest.get_tree_count() );
+
+    // Print variable importance
+    var_importance = (CvMat*)forest.get_var_importance();
+    if( var_importance )
+    {
+        double rt_imp_sum = cvSum( var_importance ).val[0];
+        printf("var#\timportance (in %%):\n");
+        for( i = 0; i < var_importance->cols; i++ )
+            printf( "%-2d\t%-4.1f\n", i,
+            100.f*var_importance->data.fl[i]/rt_imp_sum);
+    }
+
+    //Print some proximitites
+    printf( "Proximities between some samples corresponding to the letter 'T':\n" );
+    {
+        CvMat sample1, sample2;
+        const int pairs[][2] = {{0,103}, {0,106}, {106,103}, {-1,-1}};
+
+        for( i = 0; pairs[i][0] >= 0; i++ )
+        {
+            cvGetRow( data, &sample1, pairs[i][0] );
+            cvGetRow( data, &sample2, pairs[i][1] );
+            printf( "proximity(%d,%d) = %.1f%%\n", pairs[i][0], pairs[i][1],
+                forest.get_proximity( &sample1, &sample2 )*100. );
+        }
+    }
+
+    // Save Random Trees classifier to file if needed
+    if( filename_to_save )
+        forest.save( filename_to_save );
+
+    cvReleaseMat( &sample_idx );
+    cvReleaseMat( &var_type );
+    cvReleaseMat( &data );
+    cvReleaseMat( &responses );
+
+    return 0;
+}
+
+
+static
+int build_boost_classifier( char* data_filename,
+    char* filename_to_save, char* filename_to_load )
+{
+    const int class_count = 26;
+    CvMat* data = 0;
+    CvMat* responses = 0;
+    CvMat* var_type = 0;
+    CvMat* temp_sample = 0;
+    CvMat* weak_responses = 0;
+
+    int ok = read_num_class_data( data_filename, 16, &data, &responses );
+    int nsamples_all = 0, ntrain_samples = 0;
+    int var_count;
+    int i, j, k;
+    double train_hr = 0, test_hr = 0;
+    CvBoost boost;
+
+    if( !ok )
+    {
+        printf( "Could not read the database %s\n", data_filename );
+        return -1;
+    }
+
+    printf( "The database %s is loaded.\n", data_filename );
+    nsamples_all = data->rows;
+    ntrain_samples = (int)(nsamples_all*0.5);
+    var_count = data->cols;
+
+    // Create or load Boosted Tree classifier
+    if( filename_to_load )
+    {
+        // load classifier from the specified file
+        boost.load( filename_to_load );
+        ntrain_samples = 0;
+        if( !boost.get_weak_predictors() )
+        {
+            printf( "Could not read the classifier %s\n", filename_to_load );
+            return -1;
+        }
+        printf( "The classifier %s is loaded.\n", data_filename );
+    }
+    else
+    {
+        // !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+        //
+        // As currently boosted tree classifier in MLL can only be trained
+        // for 2-class problems, we transform the training database by
+        // "unrolling" each training sample as many times as the number of
+        // classes (26) that we have.
+        //
+        // !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+
+        CvMat* new_data = cvCreateMat( ntrain_samples*class_count, var_count + 1, CV_32F );
+        CvMat* new_responses = cvCreateMat( ntrain_samples*class_count, 1, CV_32S );
+
+        // 1. unroll the database type mask
+        printf( "Unrolling the database...\n");
+        for( i = 0; i < ntrain_samples; i++ )
+        {
+            float* data_row = (float*)(data->data.ptr + data->step*i);
+            for( j = 0; j < class_count; j++ )
+            {
+                float* new_data_row = (float*)(new_data->data.ptr +
+                                new_data->step*(i*class_count+j));
+                for( k = 0; k < var_count; k++ )
+                    new_data_row[k] = data_row[k];
+                new_data_row[var_count] = (float)j;
+                new_responses->data.i[i*class_count + j] = responses->data.fl[i] == j+'A';
+            }
+        }
+
+        // 2. create type mask
+        var_type = cvCreateMat( var_count + 2, 1, CV_8U );
+        cvSet( var_type, cvScalarAll(CV_VAR_ORDERED) );
+        // the last indicator variable, as well
+        // as the new (binary) response are categorical
+        cvSetReal1D( var_type, var_count, CV_VAR_CATEGORICAL );
+        cvSetReal1D( var_type, var_count+1, CV_VAR_CATEGORICAL );
+
+        // 3. train classifier
+        printf( "Training the classifier (may take a few minutes)...\n");
+        boost.train( new_data, CV_ROW_SAMPLE, new_responses, 0, 0, var_type, 0,
+            CvBoostParams(CvBoost::REAL, 100, 0.95, 5, false, 0 ));
+        cvReleaseMat( &new_data );
+        cvReleaseMat( &new_responses );
+        printf("\n");
+    }
+
+    temp_sample = cvCreateMat( 1, var_count + 1, CV_32F );
+    weak_responses = cvCreateMat( 1, boost.get_weak_predictors()->total, CV_32F ); 
+
+    // compute prediction error on train and test data
+    for( i = 0; i < nsamples_all; i++ )
+    {
+        int best_class = 0;
+        double max_sum = -DBL_MAX;
+        double r;
+        CvMat sample;
+        cvGetRow( data, &sample, i );
+        for( k = 0; k < var_count; k++ )
+            temp_sample->data.fl[k] = sample.data.fl[k];
+
+        for( j = 0; j < class_count; j++ )
+        {
+            temp_sample->data.fl[var_count] = (float)j;
+            boost.predict( temp_sample, 0, weak_responses );
+            double sum = cvSum( weak_responses ).val[0];
+            if( max_sum < sum )
+            {
+                max_sum = sum;
+                best_class = j + 'A';
+            }
+        }
+
+        r = fabs(best_class - responses->data.fl[i]) < FLT_EPSILON ? 1 : 0;
+
+        if( i < ntrain_samples )
+            train_hr += r;
+        else
+            test_hr += r;
+    }
+
+    test_hr /= (double)(nsamples_all-ntrain_samples);
+    train_hr /= (double)ntrain_samples;
+    printf( "Recognition rate: train = %.1f%%, test = %.1f%%\n",
+            train_hr*100., test_hr*100. );
+
+    printf( "Number of trees: %d\n", boost.get_weak_predictors()->total );
+
+    // Save classifier to file if needed
+    if( filename_to_save )
+        boost.save( filename_to_save );
+
+    cvReleaseMat( &temp_sample );
+    cvReleaseMat( &weak_responses );
+    cvReleaseMat( &var_type );
+    cvReleaseMat( &data );
+    cvReleaseMat( &responses );
+
+    return 0;
+}
+
+
+static
+int build_mlp_classifier( char* data_filename,
+    char* filename_to_save, char* filename_to_load )
+{
+    const int class_count = 26;
+    CvMat* data = 0;
+    CvMat train_data;
+    CvMat* responses = 0;
+    CvMat* mlp_response = 0;
+
+    int ok = read_num_class_data( data_filename, 16, &data, &responses );
+    int nsamples_all = 0, ntrain_samples = 0;
+    int i, j;
+    double train_hr = 0, test_hr = 0;
+    CvANN_MLP mlp;
+
+    if( !ok )
+    {
+        printf( "Could not read the database %s\n", data_filename );
+        return -1;
+    }
+
+    printf( "The database %s is loaded.\n", data_filename );
+    nsamples_all = data->rows;
+    ntrain_samples = (int)(nsamples_all*0.8);
+
+    // Create or load MLP classifier
+    if( filename_to_load )
+    {
+        // load classifier from the specified file
+        mlp.load( filename_to_load );
+        ntrain_samples = 0;
+        if( !mlp.get_layer_count() )
+        {
+            printf( "Could not read the classifier %s\n", filename_to_load );
+            return -1;
+        }
+        printf( "The classifier %s is loaded.\n", data_filename );
+    }
+    else
+    {
+        // !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+        //
+        // MLP does not support categorical variables by explicitly.
+        // So, instead of the output class label, we will use
+        // a binary vector of <class_count> components for training and,
+        // therefore, MLP will give us a vector of "probabilities" at the
+        // prediction stage
+        //
+        // !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+
+        CvMat* new_responses = cvCreateMat( ntrain_samples, class_count, CV_32F );
+
+        // 1. unroll the responses
+        printf( "Unrolling the responses...\n");
+        for( i = 0; i < ntrain_samples; i++ )
+        {
+            int cls_label = cvRound(responses->data.fl[i]) - 'A';
+            float* bit_vec = (float*)(new_responses->data.ptr + i*new_responses->step);
+            for( j = 0; j < class_count; j++ )
+                bit_vec[j] = 0.f;
+            bit_vec[cls_label] = 1.f;
+        }
+        cvGetRows( data, &train_data, 0, ntrain_samples );
+
+        // 2. train classifier
+        int layer_sz[] = { data->cols, 100, 100, class_count };
+        CvMat layer_sizes =
+            cvMat( 1, (int)(sizeof(layer_sz)/sizeof(layer_sz[0])), CV_32S, layer_sz );
+        mlp.create( &layer_sizes );
+        printf( "Training the classifier (may take a few minutes)...\n");
+        mlp.train( &train_data, new_responses, 0, 0,
+            CvANN_MLP_TrainParams(cvTermCriteria(CV_TERMCRIT_ITER,300,0.01),
+#if 1
+            CvANN_MLP_TrainParams::BACKPROP,0.001));
+#else
+            CvANN_MLP_TrainParams::RPROP,0.05));
+#endif
+        cvReleaseMat( &new_responses );
+        printf("\n");
+    }
+
+    mlp_response = cvCreateMat( 1, class_count, CV_32F );
+
+    // compute prediction error on train and test data
+    for( i = 0; i < nsamples_all; i++ )
+    {
+        int best_class;
+        CvMat sample;
+        cvGetRow( data, &sample, i );
+        CvPoint max_loc = {0,0};
+        mlp.predict( &sample, mlp_response );
+        cvMinMaxLoc( mlp_response, 0, 0, 0, &max_loc, 0 );
+        best_class = max_loc.x + 'A';
+
+        int r = fabs((double)best_class - responses->data.fl[i]) < FLT_EPSILON ? 1 : 0;
+
+        if( i < ntrain_samples )
+            train_hr += r;
+        else
+            test_hr += r;
+    }
+
+    test_hr /= (double)(nsamples_all-ntrain_samples);
+    train_hr /= (double)ntrain_samples;
+    printf( "Recognition rate: train = %.1f%%, test = %.1f%%\n",
+            train_hr*100., test_hr*100. );
+
+    // Save classifier to file if needed
+    if( filename_to_save )
+        mlp.save( filename_to_save );
+
+    cvReleaseMat( &mlp_response );
+    cvReleaseMat( &data );
+    cvReleaseMat( &responses );
+
+    return 0;
+}
+
+
+int main( int argc, char *argv[] )
+{
+    char* filename_to_save = 0;
+    char* filename_to_load = 0;
+    char default_data_filename[] = "./letter-recognition.data";
+    char* data_filename = default_data_filename;
+    int method = 0;
+
+    int i;
+    for( i = 1; i < argc; i++ )
+    {
+        if( strcmp(argv[i],"-data") == 0 ) // flag "-data letter_recognition.xml"
+        {
+            i++;
+            data_filename = argv[i];
+        }
+        else if( strcmp(argv[i],"-save") == 0 ) // flag "-save filename.xml"
+        {
+            i++;
+            filename_to_save = argv[i];
+        }
+        else if( strcmp(argv[i],"-load") == 0) // flag "-load filename.xml"
+        {
+            i++;
+            filename_to_load = argv[i];
+        }
+        else if( strcmp(argv[i],"-boost") == 0)
+        {
+            method = 1;
+        }
+        else if( strcmp(argv[i],"-mlp") == 0 )
+        {
+            method = 2;
+        }
+        else
+            break;
+    }
+
+    if( i < argc ||
+        (method == 0 ?
+        build_rtrees_classifier( data_filename, filename_to_save, filename_to_load ) :
+        method == 1 ?
+        build_boost_classifier( data_filename, filename_to_save, filename_to_load ) :
+        method == 2 ?
+        build_mlp_classifier( data_filename, filename_to_save, filename_to_load ) :
+        -1) < 0)
+    {
+        printf("This is letter recognition sample.\n"
+                "The usage: letter_recog [-data <path to letter-recognition.data>] \\\n"
+                "  [-save <output XML file for the classifier>] \\\n"
+                "  [-load <XML file with the pre-trained classifier>] \\\n"
+                "  [-boost|-mlp] # to use boost/mlp classifier instead of default Random Trees\n" );
+    }
+    return 0;
+}

samples/cpp/minarea.cpp

@@ -0,0 +1,47 @@
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+using namespace cv;
+
+int main( int argc, char** argv )
+{
+    Mat img(500, 500, CV_8UC3);
+    RNG& rng = theRNG();
+
+    for(;;)
+    {
+        int i, count = rng.uniform(1, 101);
+        vector<Point> points;
+        for( i = 0; i < count; i++ )
+        {
+            Point pt;
+            pt.x = rng.uniform(img.cols/4, img.cols*3/4);
+            pt.y = rng.uniform(img.rows/4, img.rows*3/4);
+            
+            points.push_back(pt);
+        }
+        
+        RotatedRect box = minAreaRect(Mat(points));
+        Point2f center, vtx[4];
+        float radius = 0;
+        minEnclosingCircle(Mat(points), center, radius);
+        box.points(vtx);
+        
+        img = Scalar::all(0);
+        for( i = 0; i < count; i++ )
+            circle( img, points[i], 3, Scalar(0, 0, 255), CV_FILLED, CV_AA );
+
+        for( i = 0; i < 4; i++ )
+            line(img, vtx[i], vtx[(i+1)%4], Scalar(0, 255, 0), 1, CV_AA);
+        
+        circle(img, center, cvRound(radius), Scalar(0, 255, 255), 1, CV_AA); 
+
+        imshow( "rect & circle", img );
+
+        char key = (char)cvWaitKey();
+        if( key == 27 || key == 'q' || key == 'Q' ) // 'ESC'
+            break;
+    }
+    return 0;
+}
+

samples/cpp/squares.cpp

@@ -0,0 +1,154 @@
+// The "Square Detector" program.
+// It loads several images subsequentally and tries to find squares in
+// each image
+
+#include "opencv2/core/core.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+
+#include <iostream>
+#include <math.h>
+#include <string.h>
+
+using namespace cv;
+using namespace std;
+
+int thresh = 50, N = 11;
+const char* wndname = "Square Detection Demo";
+
+// helper function:
+// finds a cosine of angle between vectors
+// from pt0->pt1 and from pt0->pt2
+double angle( Point pt1, Point pt2, Point pt0 )
+{
+    double dx1 = pt1.x - pt0.x;
+    double dy1 = pt1.y - pt0.y;
+    double dx2 = pt2.x - pt0.x;
+    double dy2 = pt2.y - pt0.y;
+    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
+}
+
+// returns sequence of squares detected on the image.
+// the sequence is stored in the specified memory storage
+void findSquares( const Mat& image, vector<vector<Point> >& squares )
+{
+    squares.clear();
+    
+    Mat pyr, timg, gray0(image.size(), CV_8U), gray;
+    
+    // down-scale and upscale the image to filter out the noise
+    pyrDown(image, pyr, Size(image.cols/2, image.rows/2));
+    pyrUp(pyr, timg, image.size());
+    vector<vector<Point> > contours;
+    
+    // find squares in every color plane of the image
+    for( int c = 0; c < 3; c++ )
+    {
+        int ch[] = {c, 0};
+        mixChannels(&timg, 1, &gray0, 1, ch, 1);
+        
+        // try several threshold levels
+        for( int l = 0; l < N; l++ )
+        {
+            // hack: use Canny instead of zero threshold level.
+            // Canny helps to catch squares with gradient shading
+            if( l == 0 )
+            {
+                // apply Canny. Take the upper threshold from slider
+                // and set the lower to 0 (which forces edges merging)
+                Canny(gray0, gray, 0, thresh, 5);
+                // dilate canny output to remove potential
+                // holes between edge segments
+                dilate(gray, gray, Mat(), Point(-1,-1));
+            }
+            else
+            {
+                // apply threshold if l!=0:
+                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
+                gray = gray0 >= (l+1)*255/N;
+            }
+
+            // find contours and store them all as a list
+            findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
+
+            vector<Point> approx;
+            
+            // test each contour
+            for( size_t i = 0; i < contours.size(); i++ )
+            {
+                // approximate contour with accuracy proportional
+                // to the contour perimeter
+                approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);
+                
+                // square contours should have 4 vertices after approximation
+                // relatively large area (to filter out noisy contours)
+                // and be convex.
+                // Note: absolute value of an area is used because
+                // area may be positive or negative - in accordance with the
+                // contour orientation
+                if( approx.size() == 4 &&
+                    fabs(contourArea(Mat(approx))) > 1000 &&
+                    isContourConvex(Mat(approx)) )
+                {
+                    double maxCosine = 0;
+
+                    for( int j = 2; j < 5; j++ )
+                    {
+                        // find the maximum cosine of the angle between joint edges
+                        double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
+                        maxCosine = MAX(maxCosine, cosine);
+                    }
+
+                    // if cosines of all angles are small
+                    // (all angles are ~90 degree) then write quandrange
+                    // vertices to resultant sequence
+                    if( maxCosine < 0.3 )
+                        squares.push_back(approx);
+                }
+            }
+        }
+    }
+}
+
+
+// the function draws all the squares in the image
+void drawSquares( Mat& image, const vector<vector<Point> >& squares )
+{
+    for( size_t i = 0; i < squares.size(); i++ )
+    {
+        const Point* p = &squares[i][0];
+        int n = (int)squares[i].size();
+        polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, CV_AA);
+    }
+
+    imshow(wndname, image);
+}
+
+
+int main(int argc, char** argv)
+{
+    static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
+        "pic4.png", "pic5.png", "pic6.png", 0 };
+
+    namedWindow( wndname, 1 );
+    vector<vector<Point> > squares;
+    
+    for( int i = 0; names[i] != 0; i++ )
+    {
+        Mat image = imread(names[i], 1);
+        if( image.empty() )
+        {
+            cout << "Couldn't load " << names[i] << endl;
+            continue;
+        }
+        
+        findSquares(image, squares);
+        drawSquares(image, squares);
+
+        int c = waitKey();
+        if( (char)c == 27 )
+            break;
+    }
+
+    return 0;
+}

samples/cpp/stereo_calib.cpp

@@ -0,0 +1,388 @@
+/* This is sample from the OpenCV book. The copyright notice is below */
+
+/* *************** License:**************************
+   Oct. 3, 2008
+   Right to use this code in any way you want without warrenty, support or any guarentee of it working.
+
+   BOOK: It would be nice if you cited it:
+   Learning OpenCV: Computer Vision with the OpenCV Library
+     by Gary Bradski and Adrian Kaehler
+     Published by O'Reilly Media, October 3, 2008
+ 
+   AVAILABLE AT: 
+     http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
+     Or: http://oreilly.com/catalog/9780596516130/
+     ISBN-10: 0596516134 or: ISBN-13: 978-0596516130    
+
+   OTHER OPENCV SITES:
+   * The source code is on sourceforge at:
+     http://sourceforge.net/projects/opencvlibrary/
+   * The OpenCV wiki page (As of Oct 1, 2008 this is down for changing over servers, but should come back):
+     http://opencvlibrary.sourceforge.net/
+   * An active user group is at:
+     http://tech.groups.yahoo.com/group/OpenCV/
+   * The minutes of weekly OpenCV development meetings are at:
+     http://pr.willowgarage.com/wiki/OpenCV
+   ************************************************** */
+
+#include "opencv2/calib3d/calib3d.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc_c.h"
+
+#include <vector>
+#include <string>
+#include <algorithm>
+#include <stdio.h>
+#include <ctype.h>
+
+using namespace std;
+
+//
+// Given a list of chessboard images, the number of corners (nx, ny)
+// on the chessboards, and a flag: useCalibrated for calibrated (0) or
+// uncalibrated (1: use cvStereoCalibrate(), 2: compute fundamental
+// matrix separately) stereo. Calibrate the cameras and display the
+// rectified results along with the computed disparity images.
+//
+static void
+StereoCalib(const char* path, const char* imageList, int useUncalibrated)
+{
+    CvRect roi1, roi2;
+    int nx = 0, ny = 0;
+    int displayCorners = 1;
+    int showUndistorted = 1;
+    bool isVerticalStereo = false;//OpenCV can handle left-right
+                                      //or up-down camera arrangements
+    const int maxScale = 1;
+    const float squareSize = 1.f; //Set this to your actual square size
+    FILE* f = fopen(imageList, "rt");
+    int i, j, lr, nframes = 0, n, N = 0;
+    vector<string> imageNames[2];
+    vector<CvPoint3D32f> objectPoints;
+    vector<CvPoint2D32f> points[2];
+    vector<CvPoint2D32f> temp_points[2];
+    vector<int> npoints;
+//    vector<uchar> active[2];
+    int is_found[2] = {0, 0};
+    vector<CvPoint2D32f> temp;
+    CvSize imageSize = {0,0};
+    // ARRAY AND VECTOR STORAGE:
+    double M1[3][3], M2[3][3], D1[5], D2[5];
+    double R[3][3], T[3], E[3][3], F[3][3];
+    double Q[4][4];
+    CvMat _M1 = cvMat(3, 3, CV_64F, M1 );
+    CvMat _M2 = cvMat(3, 3, CV_64F, M2 );
+    CvMat _D1 = cvMat(1, 5, CV_64F, D1 );
+    CvMat _D2 = cvMat(1, 5, CV_64F, D2 );
+    CvMat matR = cvMat(3, 3, CV_64F, R );
+    CvMat matT = cvMat(3, 1, CV_64F, T );
+    CvMat matE = cvMat(3, 3, CV_64F, E );
+    CvMat matF = cvMat(3, 3, CV_64F, F );
+    
+    CvMat matQ = cvMat(4, 4, CV_64FC1, Q);
+
+    char buf[1024];
+    
+    if( displayCorners )
+        cvNamedWindow( "corners", 1 );
+// READ IN THE LIST OF CHESSBOARDS:
+    if( !f )
+    {
+        fprintf(stderr, "can not open file %s\n", imageList );
+        return;
+    }
+    
+    if( !fgets(buf, sizeof(buf)-3, f) || sscanf(buf, "%d%d", &nx, &ny) != 2 )
+        return;
+    n = nx*ny;
+    temp.resize(n);
+    temp_points[0].resize(n);
+    temp_points[1].resize(n);
+    
+    for(i=0;;i++)
+    {
+        int count = 0, result=0;
+        lr = i % 2;
+        vector<CvPoint2D32f>& pts = temp_points[lr];//points[lr];
+        if( !fgets( buf, sizeof(buf)-3, f ))
+            break;
+        size_t len = strlen(buf);
+        while( len > 0 && isspace(buf[len-1]))
+            buf[--len] = '\0';
+        if( buf[0] == '#')
+            continue;
+	char fullpath[1024];
+	sprintf(fullpath, "%s/%s", path, buf);
+        IplImage* img = cvLoadImage( fullpath, 0 );
+        if( !img )
+        {
+            printf("Cannot read file %s\n", fullpath);
+            return;
+        }
+        imageSize = cvGetSize(img);
+        imageNames[lr].push_back(buf);
+    //FIND CHESSBOARDS AND CORNERS THEREIN:
+        for( int s = 1; s <= maxScale; s++ )
+        {
+            IplImage* timg = img;
+            if( s > 1 )
+            {
+                timg = cvCreateImage(cvSize(img->width*s,img->height*s),
+                    img->depth, img->nChannels );
+                cvResize( img, timg, CV_INTER_CUBIC );
+            }
+            result = cvFindChessboardCorners( timg, cvSize(nx, ny),
+                &temp[0], &count,
+                CV_CALIB_CB_ADAPTIVE_THRESH |
+                CV_CALIB_CB_NORMALIZE_IMAGE);
+            if( timg != img )
+                cvReleaseImage( &timg );
+            if( result || s == maxScale )
+                for( j = 0; j < count; j++ )
+            {
+                temp[j].x /= s;
+                temp[j].y /= s;
+            }
+            if( result )
+                break;
+        }
+        if( displayCorners )
+        {
+            printf("%s\n", buf);
+            IplImage* cimg = cvCreateImage( imageSize, 8, 3 );
+            cvCvtColor( img, cimg, CV_GRAY2BGR );
+            cvDrawChessboardCorners( cimg, cvSize(nx, ny), &temp[0],
+                count, result );
+            IplImage* cimg1 = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3);
+            cvResize(cimg, cimg1);
+            cvShowImage( "corners", cimg1 );
+            cvReleaseImage( &cimg );
+            cvReleaseImage( &cimg1 );
+            int c = cvWaitKey(1000);
+            if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
+                exit(-1);
+        }
+        else
+            putchar('.');
+        //N = pts.size();
+        //pts.resize(N + n, cvPoint2D32f(0,0));
+        //active[lr].push_back((uchar)result);
+        is_found[lr] = result > 0 ? 1 : 0;
+    //assert( result != 0 );
+        if( result )
+        {
+         //Calibration will suffer without subpixel interpolation
+            cvFindCornerSubPix( img, &temp[0], count,
+                cvSize(11, 11), cvSize(-1,-1),
+                cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,
+                30, 0.01) );
+            copy( temp.begin(), temp.end(), pts.begin() );
+        }
+        cvReleaseImage( &img );
+        
+        if(lr)
+        {
+            if(is_found[0] == 1 && is_found[1] == 1)
+            {
+                assert(temp_points[0].size() == temp_points[1].size());
+                int current_size = points[0].size();
+                
+                points[0].resize(current_size + temp_points[0].size(), cvPoint2D32f(0.0, 0.0));
+                points[1].resize(current_size + temp_points[1].size(), cvPoint2D32f(0.0, 0.0));
+                
+                copy(temp_points[0].begin(), temp_points[0].end(), points[0].begin() + current_size);
+                copy(temp_points[1].begin(), temp_points[1].end(), points[1].begin() + current_size);
+                
+                nframes++;
+
+                printf("Pair successfully detected...\n");
+            }
+            
+            is_found[0] = 0;
+            is_found[1] = 0;
+            
+        }
+    }
+    fclose(f);
+    printf("\n");
+// HARVEST CHESSBOARD 3D OBJECT POINT LIST:
+    objectPoints.resize(nframes*n);
+    for( i = 0; i < ny; i++ )
+        for( j = 0; j < nx; j++ )
+        objectPoints[i*nx + j] =
+        cvPoint3D32f(i*squareSize, j*squareSize, 0);
+    for( i = 1; i < nframes; i++ )
+        copy( objectPoints.begin(), objectPoints.begin() + n,
+        objectPoints.begin() + i*n );
+    npoints.resize(nframes,n);
+    N = nframes*n;
+    CvMat _objectPoints = cvMat(1, N, CV_32FC3, &objectPoints[0] );
+    CvMat _imagePoints1 = cvMat(1, N, CV_32FC2, &points[0][0] );
+    CvMat _imagePoints2 = cvMat(1, N, CV_32FC2, &points[1][0] );
+    CvMat _npoints = cvMat(1, npoints.size(), CV_32S, &npoints[0] );
+    cvSetIdentity(&_M1);
+    cvSetIdentity(&_M2);
+    cvZero(&_D1);
+    cvZero(&_D2);
+    
+// CALIBRATE THE STEREO CAMERAS
+    printf("Running stereo calibration ...");
+    fflush(stdout);
+    cvStereoCalibrate( &_objectPoints, &_imagePoints1,
+        &_imagePoints2, &_npoints,
+        &_M1, &_D1, &_M2, &_D2,
+        imageSize, &matR, &matT, &matE, &matF,
+        cvTermCriteria(CV_TERMCRIT_ITER+
+        CV_TERMCRIT_EPS, 100, 1e-5),
+        CV_CALIB_FIX_ASPECT_RATIO +
+        CV_CALIB_ZERO_TANGENT_DIST +
+        CV_CALIB_SAME_FOCAL_LENGTH +
+        CV_CALIB_FIX_K3);
+    printf(" done\n");
+    
+// CALIBRATION QUALITY CHECK
+// because the output fundamental matrix implicitly
+// includes all the output information,
+// we can check the quality of calibration using the
+// epipolar geometry constraint: m2^t*F*m1=0
+    vector<CvPoint3D32f> lines[2];
+    points[0].resize(N);
+    points[1].resize(N);
+    _imagePoints1 = cvMat(1, N, CV_32FC2, &points[0][0] );
+    _imagePoints2 = cvMat(1, N, CV_32FC2, &points[1][0] );
+    lines[0].resize(N);
+    lines[1].resize(N);
+    CvMat _L1 = cvMat(1, N, CV_32FC3, &lines[0][0]);
+    CvMat _L2 = cvMat(1, N, CV_32FC3, &lines[1][0]);
+//Always work in undistorted space
+    cvUndistortPoints( &_imagePoints1, &_imagePoints1,
+        &_M1, &_D1, 0, &_M1 );
+    cvUndistortPoints( &_imagePoints2, &_imagePoints2,
+        &_M2, &_D2, 0, &_M2 );
+    cvComputeCorrespondEpilines( &_imagePoints1, 1, &matF, &_L1 );
+    cvComputeCorrespondEpilines( &_imagePoints2, 2, &matF, &_L2 );
+    double avgErr = 0;
+    for( i = 0; i < N; i++ )
+    {
+        double err = fabs(points[0][i].x*lines[1][i].x +
+            points[0][i].y*lines[1][i].y + lines[1][i].z)
+            + fabs(points[1][i].x*lines[0][i].x +
+            points[1][i].y*lines[0][i].y + lines[0][i].z);
+        avgErr += err;
+    }
+    printf( "avg err = %g\n", avgErr/(nframes*n) );
+    
+    // save intrinsic parameters
+    CvFileStorage* fstorage = cvOpenFileStorage("intrinsics.yml", NULL, CV_STORAGE_WRITE);
+    cvWrite(fstorage, "M1", &_M1);
+    cvWrite(fstorage, "D1", &_D1);
+    cvWrite(fstorage, "M2", &_M2);
+    cvWrite(fstorage, "D2", &_D2);
+    cvReleaseFileStorage(&fstorage);
+    
+//COMPUTE AND DISPLAY RECTIFICATION
+    if( showUndistorted )
+    {
+        CvMat* mx1 = cvCreateMat( imageSize.height,
+            imageSize.width, CV_32F );
+        CvMat* my1 = cvCreateMat( imageSize.height,
+            imageSize.width, CV_32F );
+        CvMat* mx2 = cvCreateMat( imageSize.height,
+            imageSize.width, CV_32F );
+        CvMat* my2 = cvCreateMat( imageSize.height,
+            imageSize.width, CV_32F );
+        CvMat* img1r = cvCreateMat( imageSize.height,
+            imageSize.width, CV_8U );
+        CvMat* img2r = cvCreateMat( imageSize.height,
+            imageSize.width, CV_8U );
+        CvMat* disp = cvCreateMat( imageSize.height,
+            imageSize.width, CV_16S );
+        double R1[3][3], R2[3][3], P1[3][4], P2[3][4];
+        CvMat _R1 = cvMat(3, 3, CV_64F, R1);
+        CvMat _R2 = cvMat(3, 3, CV_64F, R2);
+// IF BY CALIBRATED (BOUGUET'S METHOD)
+        if( useUncalibrated == 0 )
+        {
+            CvMat _P1 = cvMat(3, 4, CV_64F, P1);
+            CvMat _P2 = cvMat(3, 4, CV_64F, P2);
+
+            cvStereoRectify( &_M1, &_M2, &_D1, &_D2, imageSize,
+                &matR, &matT,
+                &_R1, &_R2, &_P1, &_P2, &matQ,
+                CV_CALIB_ZERO_DISPARITY,
+                1, imageSize, &roi1, &roi2);
+            
+            CvFileStorage* file = cvOpenFileStorage("extrinsics.yml", NULL, CV_STORAGE_WRITE);
+            cvWrite(file, "R", &matR);
+            cvWrite(file, "T", &matT);    
+            cvWrite(file, "R1", &_R1);
+            cvWrite(file, "R2", &_R2);
+            cvWrite(file, "P1", &_P1);    
+            cvWrite(file, "P2", &_P2);    
+            cvWrite(file, "Q", &matQ);
+            cvReleaseFileStorage(&file);
+                        
+            isVerticalStereo = fabs(P2[1][3]) > fabs(P2[0][3]);
+            if(!isVerticalStereo)
+                roi2.x += imageSize.width;
+            else
+                roi2.y += imageSize.height;
+    //Precompute maps for cvRemap()
+            cvInitUndistortRectifyMap(&_M1,&_D1,&_R1,&_P1,mx1,my1);
+            cvInitUndistortRectifyMap(&_M2,&_D2,&_R2,&_P2,mx2,my2);
+        }
+//OR ELSE HARTLEY'S METHOD
+        else if( useUncalibrated == 1 || useUncalibrated == 2 )
+     // use intrinsic parameters of each camera, but
+     // compute the rectification transformation directly
+     // from the fundamental matrix
+        {
+            double H1[3][3], H2[3][3], iM[3][3];
+            CvMat _H1 = cvMat(3, 3, CV_64F, H1);
+            CvMat _H2 = cvMat(3, 3, CV_64F, H2);
+            CvMat _iM = cvMat(3, 3, CV_64F, iM);
+    //Just to show you could have independently used F
+            if( useUncalibrated == 2 )
+                cvFindFundamentalMat( &_imagePoints1,
+                &_imagePoints2, &matF);
+            cvStereoRectifyUncalibrated( &_imagePoints1,
+                &_imagePoints2, &matF,
+                imageSize,
+                &_H1, &_H2, 3);
+            cvInvert(&_M1, &_iM);
+            cvMatMul(&_H1, &_M1, &_R1);
+            cvMatMul(&_iM, &_R1, &_R1);
+            cvInvert(&_M2, &_iM);
+            cvMatMul(&_H2, &_M2, &_R2);
+            cvMatMul(&_iM, &_R2, &_R2);
+    //Precompute map for cvRemap()
+            cvInitUndistortRectifyMap(&_M1,&_D1,&_R1,&_M1,mx1,my1);
+
+            cvInitUndistortRectifyMap(&_M2,&_D1,&_R2,&_M2,mx2,my2);
+        }
+        else
+            assert(0);
+        
+        
+        cvReleaseMat( &mx1 );
+        cvReleaseMat( &my1 );
+        cvReleaseMat( &mx2 );
+        cvReleaseMat( &my2 );
+        cvReleaseMat( &img1r );
+        cvReleaseMat( &img2r );
+        cvReleaseMat( &disp );
+    }
+}
+
+int main(int argc, char** argv)
+{
+    if(argc > 1 && !strcmp(argv[1], "--help"))
+    {
+        printf("Usage:\n ./stereo_calib <path to images> <file wtih image list>\n");
+        return 0;
+    }	
+
+    StereoCalib(argc > 1 ? argv[1] : ".", argc > 2 ? argv[2] : "stereo_calib.txt", 0);
+    return 0;
+}
+

samples/cpp/stereo_calib.txt

@@ -0,0 +1,27 @@
+9 6
+left01.jpg
+right01.jpg
+left02.jpg
+right02.jpg
+left03.jpg
+right03.jpg
+left04.jpg
+right04.jpg
+left05.jpg
+right05.jpg
+left06.jpg
+right06.jpg
+left07.jpg
+right07.jpg
+left08.jpg
+right08.jpg
+left09.jpg
+right09.jpg
+left11.jpg
+right11.jpg
+left12.jpg
+right12.jpg
+left13.jpg
+right13.jpg
+left14.jpg
+right14.jpg

samples/cpp/stereo_match.cpp

@@ -0,0 +1,265 @@
+/*
+ *  stereo_match.cpp
+ *  calibration
+ *
+ *  Created by Victor  Eruhimov on 1/18/10.
+ *  Copyright 2010 Argus Corp. All rights reserved.
+ *
+ */
+
+#include "opencv2/calib3d/calib3d.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+
+#include <stdio.h>
+
+using namespace cv;
+
+void saveXYZ(const char* filename, const Mat& mat)
+{
+    const double max_z = 1.0e4;
+    FILE* fp = fopen(filename, "wt");
+    for(int y = 0; y < mat.rows; y++)
+    {
+        for(int x = 0; x < mat.cols; x++)
+        {
+            Vec3f point = mat.at<Vec3f>(y, x);
+            if(fabs(point[2] - max_z) < FLT_EPSILON || fabs(point[2]) > max_z) continue;
+            fprintf(fp, "%f %f %f\n", point[0], point[1], point[2]);
+        }
+    }
+    fclose(fp);
+}
+
+void print_help()
+{
+    printf("Usage: stereo_match <left_image> <right_image> [--algorithm=bm|sgbm|hh] [--blocksize=<block_size>]\n"
+           "[--max-disparity=<max_disparity>] [-i <intrinsic_filename>] [-e <extrinsic_filename>]\n"
+           "[--no-display] [-o <disparity_image>] [-p <point_cloud_file>]\n");
+}
+
+int main(int argc, char** argv)
+{
+    const char* algorithm_opt = "--algorithm=";
+    const char* maxdisp_opt = "--max-disparity=";
+    const char* blocksize_opt = "--blocksize=";
+    const char* nodisplay_opt = "--no-display=";
+    
+    if(argc < 3)
+    {
+        print_help();
+        return 0;
+    }
+    const char* img1_filename = 0;
+    const char* img2_filename = 0;
+    const char* intrinsic_filename = 0;
+    const char* extrinsic_filename = 0;
+    const char* disparity_filename = 0;
+    const char* point_cloud_filename = 0;
+    
+    enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2 };
+    int alg = STEREO_SGBM;
+    int SADWindowSize = 0, numberOfDisparities = 0;
+    bool no_display = false;
+    
+    StereoBM bm;
+    StereoSGBM sgbm;
+    
+    for( int i = 1; i < argc; i++ )
+    {
+        if( argv[i][0] != '-' )
+        {
+            if( !img1_filename )
+                img1_filename = argv[i];
+            else
+                img2_filename = argv[i];
+        }
+        else if( strncmp(argv[i], algorithm_opt, strlen(algorithm_opt)) == 0 )
+        {
+            char* _alg = argv[i] + strlen(algorithm_opt);
+            alg = strcmp(_alg, "bm") == 0 ? STEREO_BM :
+                  strcmp(_alg, "sgbm") == 0 ? STEREO_SGBM :
+                  strcmp(_alg, "hh") == 0 ? STEREO_HH : -1;
+            if( alg < 0 )
+            {
+                printf("Command-line parameter error: Unknown stereo algorithm\n\n");
+                print_help();
+                return -1;
+            }
+        }
+        else if( strncmp(argv[i], maxdisp_opt, strlen(maxdisp_opt)) == 0 )
+        {
+            if( sscanf( argv[i] + strlen(maxdisp_opt), "%d", &numberOfDisparities ) != 1 ||
+                numberOfDisparities < 1 || numberOfDisparities % 16 != 0 )
+            {
+                printf("Command-line parameter error: The max disparity (--maxdisparity=<...>) must be a positive integer divisible by 16\n");
+                print_help();
+                return -1;
+            }
+        }
+        else if( strncmp(argv[i], blocksize_opt, strlen(blocksize_opt)) == 0 )
+        {
+            if( sscanf( argv[i] + strlen(blocksize_opt), "%d", &SADWindowSize ) != 1 ||
+                SADWindowSize < 1 || SADWindowSize % 2 != 1 )
+            {
+                printf("Command-line parameter error: The block size (--blocksize=<...>) must be a positive odd number\n");
+                return -1;
+            }
+        }
+        else if( strcmp(argv[i], nodisplay_opt) == 0 )
+            no_display = true;
+        else if( strcmp(argv[i], "-i" ) == 0 )
+            intrinsic_filename = argv[++i];
+        else if( strcmp(argv[i], "-e" ) == 0 )
+            extrinsic_filename = argv[++i];
+        else if( strcmp(argv[i], "-o" ) == 0 )
+            disparity_filename = argv[++i];
+        else if( strcmp(argv[i], "-p" ) == 0 )
+            point_cloud_filename = argv[++i];
+        else
+        {
+            printf("Command-line parameter error: unknown option %s\n", argv[i]);
+            return -1;
+        }
+    }
+    
+    if( !img1_filename || !img2_filename )
+    {
+        printf("Command-line parameter error: both left and right images must be specified\n");
+        return -1;
+    }
+    
+    if( (intrinsic_filename != 0) ^ (extrinsic_filename != 0) )
+    {
+        printf("Command-line parameter error: either both intrinsic and extrinsic parameters must be specified, or none of them (when the stereo pair is already rectified)\n");
+        return -1;
+    }
+    
+    if( extrinsic_filename == 0 && point_cloud_filename )
+    {
+        printf("Command-line parameter error: extrinsic and intrinsic parameters must be specified to compute the point cloud\n");
+        return -1;
+    }
+    
+    int color_mode = alg == STEREO_BM ? 0 : -1;
+    Mat img1 = imread(img1_filename, color_mode);
+    Mat img2 = imread(img2_filename, color_mode);
+    Size img_size = img1.size();
+    
+    Rect roi1, roi2;
+    Mat Q;
+    
+    if( intrinsic_filename )
+    {
+        // reading intrinsic parameters
+        FileStorage fs(intrinsic_filename, CV_STORAGE_READ);
+        if(!fs.isOpened())
+        {
+            printf("Failed to open file %s\n", intrinsic_filename);
+            return -1;
+        }
+        
+        Mat M1, D1, M2, D2;
+        fs["M1"] >> M1;
+        fs["D1"] >> D1;
+        fs["M2"] >> M2;
+        fs["D2"] >> D2;
+        
+        fs.open(extrinsic_filename, CV_STORAGE_READ);
+        if(!fs.isOpened())
+        {
+            printf("Failed to open file %s\n", extrinsic_filename);
+            return -1;
+        }
+        
+        Mat R, T, R1, P1, R2, P2;
+        fs["R"] >> R;
+        fs["T"] >> T;
+        
+        stereoRectify( M1, D1, M2, D2, img_size, R, T, R1, R2, P1, P2, Q, -1, img_size, &roi1, &roi2 );
+        
+        Mat map11, map12, map21, map22;
+        initUndistortRectifyMap(M1, D1, R1, P1, img_size, CV_16SC2, map11, map12);
+        initUndistortRectifyMap(M2, D2, R2, P2, img_size, CV_16SC2, map21, map22);
+        
+        Mat img1r, img2r;
+        remap(img1, img1r, map11, map12, INTER_LINEAR);
+        remap(img2, img2r, map21, map22, INTER_LINEAR);
+        
+        img1 = img1r;
+        img2 = img2r;
+    }
+    
+    numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : img_size.width/8;
+    
+    bm.state->roi1 = roi1;
+    bm.state->roi2 = roi2;
+    bm.state->preFilterCap = 31;
+    bm.state->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 9;
+    bm.state->minDisparity = 0;
+    bm.state->numberOfDisparities = numberOfDisparities;
+    bm.state->textureThreshold = 10;
+    bm.state->uniquenessRatio = 15;
+    bm.state->speckleWindowSize = 100;
+    bm.state->speckleRange = 32;
+    bm.state->disp12MaxDiff = 1;
+    
+    sgbm.preFilterCap = 63;
+    sgbm.SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 3;
+    
+    int cn = img1.channels();
+    
+    sgbm.P1 = 8*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
+    sgbm.P2 = 32*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
+    sgbm.minDisparity = 0;
+    sgbm.numberOfDisparities = numberOfDisparities;
+    sgbm.uniquenessRatio = 10;
+    sgbm.speckleWindowSize = bm.state->speckleWindowSize;
+    sgbm.speckleRange = bm.state->speckleRange;
+    sgbm.disp12MaxDiff = 1;
+    sgbm.fullDP = alg == STEREO_HH;
+    
+    Mat disp, disp8;
+    //Mat img1p, img2p, dispp;
+    //copyMakeBorder(img1, img1p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);
+    //copyMakeBorder(img2, img2p, 0, 0, numberOfDisparities, 0, IPL_BORDER_REPLICATE);
+    
+    int64 t = getTickCount();
+    if( alg == STEREO_BM )
+        bm(img1, img2, disp);
+    else
+        sgbm(img1, img2, disp);
+    t = getTickCount() - t;
+    printf("Time elapsed: %fms\n", t*1000/getTickFrequency());
+
+    //disp = dispp.colRange(numberOfDisparities, img1p.cols);
+    disp.convertTo(disp8, CV_8U, 255/(numberOfDisparities*16.));
+    if( !no_display )
+    {
+        namedWindow("left", 1);
+        imshow("left", img1);
+        namedWindow("right", 1);
+        imshow("right", img2);
+        namedWindow("disparity", 0);
+        imshow("disparity", disp8);
+        printf("press any key to continue...");
+        fflush(stdout);
+        waitKey();
+        printf("\n");
+    }
+    
+    if(disparity_filename)
+        imwrite(disparity_filename, disp8);
+    
+    if(point_cloud_filename)
+    {
+        printf("storing the point cloud...");
+        fflush(stdout);
+        Mat xyz;
+        reprojectImageTo3D(disp, xyz, Q, true);
+        saveXYZ(point_cloud_filename, xyz);
+        printf("\n");
+    }
+    
+    return 0;
+}

samples/cpp/watershed.cpp

@@ -0,0 +1,127 @@
+#include "opencv2/imgproc/imgproc.hpp"
+#include "opencv2/highgui/highgui.hpp"
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+Mat markerMask, img;
+Point prevPt(-1, -1);
+
+void onMouse( int event, int x, int y, int flags, void* )
+{
+    if( x < 0 || x >= img.cols || y < 0 || y >= img.rows )
+        return;
+    if( event == CV_EVENT_LBUTTONUP || !(flags & CV_EVENT_FLAG_LBUTTON) )
+        prevPt = Point(-1,-1);
+    else if( event == CV_EVENT_LBUTTONDOWN )
+        prevPt = Point(x,y);
+    else if( event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON) )
+    {
+        Point pt(x, y);
+        if( prevPt.x < 0 )
+            prevPt = pt;
+        line( markerMask, prevPt, pt, Scalar::all(255), 5, 8, 0 );
+        line( img, prevPt, pt, Scalar::all(255), 5, 8, 0 );
+        prevPt = pt;
+        imshow("image", img);
+    }
+}
+
+
+int main( int argc, char** argv )
+{
+    char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
+    Mat img0 = imread(filename, 1), imgGray;
+    
+    if( img0.empty() )
+    {
+        cout << "Usage: watershed <image_name>\n";
+        return 0;
+    }
+
+    cout << "Hot keys: \n"
+            "\tESC - quit the program\n"
+            "\tr - restore the original image\n"
+            "\tw or SPACE - run watershed algorithm\n"
+            "\t\t(before running it, roughly mark the areas on the image)\n"
+            "\t  (before that, roughly outline several markers on the image)\n";
+    
+    namedWindow( "image", 1 );
+
+    img0.copyTo(img);
+    cvtColor(img, markerMask, CV_BGR2GRAY);
+    cvtColor(markerMask, imgGray, CV_GRAY2BGR);
+    markerMask = Scalar::all(0);
+    imshow( "image", img );
+    setMouseCallback( "image", onMouse, 0 );
+
+    for(;;)
+    {
+        int c = waitKey(0);
+
+        if( (char)c == 27 )
+            break;
+
+        if( (char)c == 'r' )
+        {
+            markerMask = Scalar::all(0);
+            img0.copyTo(img);
+            imshow( "image", img );
+        }
+
+        if( (char)c == 'w' || (char)c == ' ' )
+        {
+            int i, j, compCount = 0;
+            vector<vector<Point> > contours;
+            vector<Vec4i> hierarchy;
+            
+            findContours(markerMask, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
+            
+            Mat markers(markerMask.size(), CV_32S);
+            markers = Scalar::all(0);
+            int idx = 0;
+            for( ; idx >= 0; idx = hierarchy[idx][0], compCount++ )
+                drawContours(markers, contours, idx, Scalar::all(compCount+1), -1, 8, hierarchy, INT_MAX);
+
+            if( compCount == 0 )
+                continue;
+            
+            vector<Vec3b> colorTab;
+            for( i = 0; i < compCount; i++ )
+            {
+                int b = theRNG().uniform(180, 230);
+                int g = theRNG().uniform(180, 230);
+                int r = theRNG().uniform(180, 230);
+                
+                colorTab.push_back(Vec3b((uchar)b, (uchar)g, (uchar)r));
+            }
+
+            double t = (double)getTickCount();
+            watershed( img0, markers );
+            t = (double)getTickCount() - t;
+            printf( "execution time = %gms\n", t*1000./getTickFrequency() );
+
+            Mat wshed(markers.size(), CV_8UC3);
+            
+            // paint the watershed image
+            for( i = 0; i < markers.rows; i++ )
+                for( j = 0; j < markers.cols; j++ )
+                {
+                    int idx = markers.at<int>(i,j);
+                    if( idx == -1 )
+                        wshed.at<Vec3b>(i,j) = Vec3b(255,255,255);
+                    else if( idx <= 0 || idx > compCount )
+                        wshed.at<Vec3b>(i,j) = Vec3b(0,0,0);
+                    else
+                        wshed.at<Vec3b>(i,j) = colorTab[idx - 1];
+                }
+
+            wshed = wshed*0.5 + imgGray*0.5;
+            imshow( "watershed transform", wshed );
+        }
+    }
+
+    return 0;
+}