float YARPObjectAnalysis::SpotInternals(YARPImageOf<YarpPixelBGR>& src_seg,
YARPImageOf<YarpPixelMono>& in_mask,
YARPImageOf<YarpPixelMono>& out_mask,
YARPImageOf<YarpPixelBGR>& dest)
{
YARPShapeBoundary sb;
sb.SetFromMask(in_mask);
sb.ScaleAboutCenter(shrink);
YARPImageOf<YarpPixelMono> mask_small;
SatisfySize(src_seg,mask_small);
sb.GetMask(mask_small);
ColorMap color_map, color_map2, color_id;
YARPImageOf<YarpPixelInt> cluster0, cluster1;
SatisfySize(src_seg,cluster0);
SatisfySize(src_seg,cluster1);
int iid = 1;
IMGFOR(src_seg,x,y)
{
NetInt32 addr = HashColor(src_seg(x,y));
ColorMap::iterator it = color_id.find(addr);
if (it == color_id.end())
{
color_id[addr] = iid;
it = color_id.find(addr);
iid++;
}
cluster0(x,y) = (*it).second;
}
void AdaptiveManifoldFilterN::filter(InputArray src, OutputArray dst, InputArray joint)
{
CV_Assert(sigma_s_ >= 1 && (sigma_r_ > 0 && sigma_r_ <= 1));
num_pca_iterations_ = std::max(1, num_pca_iterations_);
initBuffers(src, joint);
curTreeHeight = tree_height_ <= 0 ? computeManifoldTreeHeight(sigma_s_, sigma_r_) : tree_height_;
sigma_r_over_sqrt_2 = (float) (sigma_r_ / sqrt(2.0));
const double seedCoef = jointCn[0].at<float>(srcSize.height/2, srcSize.width/2);
const uint64 baseCoef = numeric_limits<uint64>::max() / 0xFFFF;
rnd.state = static_cast<int64>(baseCoef*seedCoef);
Mat1b cluster0(srcSize, 0xFF);
vector<Mat> eta0(jointCnNum);
for (int i = 0; i < jointCnNum; i++)
h_filter(jointCn[i], eta0[i], (float)sigma_s_);
buildManifoldsAndPerformFiltering(eta0, cluster0, 1);
gatherResult(src, dst);
}