/// ****************************************************
///
/// CARTOON FILTER
///
/// ****************************************************
bool testApp::cvFilterCartoon(ofxCvColorImage &src, ofxCvColorImage &dst, int w, int h)
{
//CvtColor(src, dst, code)
//cv::cvtColor(inputFrame, bgr, CV_BGRA2BGR);
// cv::pyrMeanShiftFiltering(bgr.clone(), bgr, sp, sr);
// PyrMeanShiftFiltering(src, dst, sp, sr, max_level=1, termcrit=(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 5, 1))
// Temporary storage.
IplImage* pyr = cvCreateImage( cvSize(w,h), IPL_DEPTH_8U, 3 );
IplImage* edges = cvCreateImage( cvSize(w,h), IPL_DEPTH_8U, 1 );
IplImage* edgesRgb = cvCreateImage( cvSize(w,h), IPL_DEPTH_8U, 3 );
//cvSet(s, cvScalar(0,0,0));
ofxCvGrayscaleImage tempGrayImg;
tempGrayImg.allocate(w, h);
tempGrayImg.setFromColorImage(src);
//------------------------------
cvPyrMeanShiftFiltering(src.getCvImage(), pyr, 10, 10);
// cv::Canny(gray, edges, 150, 150);
cvCanny(tempGrayImg.getCvImage(), edges, 150,150);
cvCvtColor(edges, edgesRgb, CV_GRAY2RGB);
cvAbsDiff(pyr, edgesRgb, pyr);
//cvAbsDiff(colorImg.getCvImage(), lastFrame.getCvImage(), colorDiff.getCvImage());
dst.setFromPixels((unsigned char *)pyr->imageData, w, h);
return true;
}
////////////////////////////////////////////////////////////////////////////////
// [http://stackoverflow.com/questions/4831813/image-segmentation-using-mean-shift-explained]
// "The Mean Shift segmentation is a local homogenization technique that is
// very useful for damping shading or tonality differences in localized objects.
// [...] replaces each pixel with the mean of the pixels in a range-r
// neighborhood and whose value is within a distance d."
static void posterize_image(IplImage* input)
{
// this line reduces the amount of colours
cvAndS( input, cvScalar(0xF8, 0xF8, 0xF8), input);
int colour_radius = 4; // number of colour classes ~= 256/colour_radius
int pixel_radius = 2;
int levels = 1;
cvPyrMeanShiftFiltering(input, input, pixel_radius, colour_radius, levels);
}
void cv::pyrMeanShiftFiltering( const Mat& src, Mat& dst,
double sp, double sr, int maxLevel,
TermCriteria termcrit )
{
if( src.empty() )
return;
dst.create( src.size(), src.type() );
CvMat _src = src, _dst = dst;
cvPyrMeanShiftFiltering( &_src, &_dst, sp, sr, maxLevel, termcrit );
}
int main( int argc, char** argv )
{
char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";
CvTermCriteria termcrit=cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,5,1);
double spRadius = 20.0, colorRadius = 40.0;
int max_level = 2;
if( (src = cvLoadImage(filename,-1)) == 0 )
return 0;
help();
cvNamedWindow( "Image", 1 );
cvNamedWindow( "Segmented", 1);
dst = cvCloneImage( src );
cvShowImage( "Image", src );
for(;;)
{
char c;
do {//In linux, we get rid of shift codes which turn c negative.
c = cvWaitKey(0);
if(c < 0) c = -c;
} while( (c == 30) || (c == 31)); //Shift codes
// printf("c=%d\n",c);
if(( (char)c == 27) || ((char)c == 'q') || ((char)c == 'Q') )//Quit
break;
switch(c){
case 'H':
case 'h':
help();
break;
case's': //save image as watershed.jpg
cvSaveImage("pyrMeanShiftInput.jpg",src);
cvSaveImage("pyrMeanShiftOutput.jpg",dst);
printf("Saved image pyrMeanShift*.jpg\n");
break;
case 'm':
max_level -= 1;
if(max_level <0) max_level = 0;
printf("max_level = %d\n",max_level);
break;
case 'M'://"
max_level += 1;
printf("max_level = %d\n",max_level);
break;
case 'r':
spRadius -= 1.0;
if(spRadius < 1.0) spRadius = 1.0;
printf("spRadius = %lf\n",spRadius);
break;
case 'R':
spRadius += 1.0;
printf("spRadius = %lf\n",spRadius);
break;
case 'c':
colorRadius -= 1.0;
if(colorRadius < 1.0) colorRadius = 1.0;
printf("colorRadius = %lf\n",colorRadius);
break;
case 'C':
colorRadius += 1.0;
printf("colorRadius = %lf\n",colorRadius);
break;
case 'p':
case '\n':
double t = (double)cvGetTickCount();
cvPyrMeanShiftFiltering( src, dst, spRadius, colorRadius, max_level, termcrit);
t = (double)cvGetTickCount() - t;
printf("For params image(x,y)=(%d,%d) max_level=%d, Radius color=%lf, space=%lf\n",
src->width,src->height,max_level,colorRadius,spRadius);
printf( "exec time = %gms\n", t/(cvGetTickFrequency()*1000.) );
cvShowImage( "Segmented", dst );
break;
}
}
return 1;
}
