//Takes avg pixel color value (3x3 grid)
CvScalar avgpixelcolor(IplImage*image,CvPoint seed,int gridSize){
CvScalar pixColor;
cvSetImageROI(image, cvRect(seed.x,seed.y,gridSize,gridSize)); //Restrict Color Avg to ROI
IplImage*b=cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,1); //Channel Holders
IplImage*g=cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,1);
IplImage*r=cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,1);
cvSplit(image,b,g,r,NULL); //Split Color Spaces and Average
pixColor.val[0]=cvMean(b);
pixColor.val[1]=cvMean(g);
pixColor.val[2]=cvMean(r);
cvResetImageROI(image);
cvReleaseImage(&b);
cvReleaseImage(&g);
cvReleaseImage(&r);
return pixColor;
}
double ImageProcessorCV::Mean(CByteImage *pImage1, CByteImage *pImage2)
{
if (pImage1->width != pImage2->width || pImage1->height != pImage2->height ||
pImage1->type != pImage2->type || pImage1->type != CByteImage::eGrayScale)
return -1;
IplImage *pIplImage1 = IplImageAdaptor::Adapt(pImage1);
IplImage *pIplImage2 = IplImageAdaptor::Adapt(pImage2);
double dRet = cvMean(pIplImage1, pIplImage2);
cvReleaseImageHeader(&pIplImage1);
cvReleaseImageHeader(&pIplImage2);
return dRet;
}
void pix_opencv_patreco :: loadMess (t_symbol *s, int argc, t_atom* argv)
{
t_symbol* filename;
int id;
if ( argc != 2 ) {
error("wrong arguments : load <id> <filename>");
return;
} else if ( argv[0].a_type != A_FLOAT || argv[1].a_type != A_SYMBOL ) {
error("wrong arguments : load <id> <filename>");
return;
} else {
id = atom_getfloat(&argv[0]);
filename = atom_getsymbol(&argv[1]);
}
if ( filename->s_name[0] == 0 ) {
error("no filename passed to load message");
return;
}
if ( filename == NULL ) {
error("%s is not a valid matrix", filename->s_name);
return;
}
Mat img = imread(filename->s_name,0);
if ( img.data == NULL ){
error("failed to load image '%s'", filename->s_name);
puts("failed to laod images");
return;
}
if(img.cols!=img.rows){
error("%s is not a square pattern", filename->s_name);
puts("not a square pattern");
return;
}
cv::Mat src(m_pattern_size, m_pattern_size, CV_8UC1);
Point2f center((m_pattern_size-1)/2.0f,(m_pattern_size-1)/2.0f);
Mat rot_mat(2,3,CV_32F);
//~ std::map<int PatternLib>::iterator it;
//~ it = m_patternLibrary.find(id);
//~ if ( m_patternLibrary.find(id) != m_patternLibrary.end() ){
// TODO remove item from the map
//~ }
PatternLib pattern;
pattern.id = id;
cv::resize(img, src, Size(m_pattern_size,m_pattern_size));
if ( m_detector->m_ART_pattern ) {
Mat subImg = src(cv::Range(m_pattern_size/4,3*m_pattern_size/4), cv::Range(m_pattern_size/4,3*m_pattern_size/4));
pattern.pattern[0] = subImg;
pattern.mean[0] = cvMean(&((CvMat)subImg));
pattern.norm[0] = cv::norm(subImg, NORM_L1);
//~ m_patternLibrary.push_back(subImg);
}
else {
//~ m_patternLibrary.push_back(src);
pattern.pattern[0] = src;
pattern.mean[0] = cvMean(&((CvMat)src));
pattern.norm[0] = cv::norm(src, NORM_L1);
}
rot_mat = getRotationMatrix2D( center, 90, 1.0);
for (int i=1; i<4; i++){
Mat dst= Mat(m_pattern_size, m_pattern_size, CV_8UC1);
rot_mat = getRotationMatrix2D( center, -i*90, 1.0);
cv::warpAffine( src, dst , rot_mat, Size(m_pattern_size,m_pattern_size));
if ( m_detector->m_ART_pattern ) {
Mat subImg = dst(cv::Range(m_pattern_size/4,3*m_pattern_size/4), cv::Range(m_pattern_size/4,3*m_pattern_size/4)); // AV crop 25% on each side -> specific to AR tag ?
pattern.pattern[i];
pattern.mean[i] = cvMean(&((CvMat)subImg));
pattern.norm[i] = cv::norm(subImg, NORM_L1);
//~ m_patternLibrary.push_back(subImg);
} else {
pattern.pattern[i] = dst;
pattern.mean[i] = cvMean(&((CvMat)dst));
pattern.norm[i] = cv::norm(dst, NORM_L1);
//~ m_patternLibrary.push_back(dst);
}
}
t_atom data_out;
SETFLOAT(&data_out, m_patternLibrary.size());
outlet_anything( m_dataout, gensym("patternCount"), 1, &data_out);
}
