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HoG features for blocks only

I am trying to compute HOG functions for a block only. I investigated the hog.cpp specified in the opencv/module/gpu/src/ section. Below is the code that I change to a computer for block functions only.

 void cv::gpu::HOGDescriptor::getDescriptors(const GpuMat& img, Size win_stride, GpuMat& descriptors, int descr_format) { CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0); computeBlockHistograms(img); // give block back /* const size_t block_hist_size = getBlockHistogramSize(); Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride); Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride); descriptors.create(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F); */ switch (descr_format) { case DESCR_FORMAT_ROW_BY_ROW: hog::extract_descrs_by_rows(win_size.height, win_size.width, block_stride.height, block_stride.width, win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors); break; case DESCR_FORMAT_COL_BY_COL: hog::extract_descrs_by_cols(win_size.height, win_size.width, block_stride.height, block_stride.width, win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors); break; default: CV_Error(CV_StsBadArg, "Unknown descriptor format"); } }

Here is the computeBlockHistograms code.

 void cv::gpu::HOGDescriptor::computeBlockHistograms(const GpuMat& img) { computeGradient(img, grad, qangle); size_t block_hist_size = getBlockHistogramSize(); Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride); // block_hists.create(1, block_hist_size * blocks_per_img.area(), CV_32F); block_hists = getBuffer(1, static_cast<int>(block_hist_size * blocks_per_img.area()), CV_32F, block_hists_buf); hog::compute_hists(nbins, block_stride.width, block_stride.height, img.rows, img.cols, grad, qangle, (float)getWinSigma(), block_hists.ptr<float>()); hog::normalize_hists(nbins, block_stride.width, block_stride.height, img.rows, img.cols, block_hists.ptr<float>(), (float)threshold_L2hys); }

EDIT: I enable the getDescriptor function also from hog.cpp

 void cv::gpu::HOGDescriptor::getDescriptors(const GpuMat& img, Size win_stride, GpuMat& descriptors, int descr_format) { CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0); computeBlockHistograms(img); const size_t block_hist_size = getBlockHistogramSize(); Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride); Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride); descriptors.create(wins_per_img.area(), static_cast<int>(blocks_per_win.area() * block_hist_size), CV_32F); switch (descr_format) { case DESCR_FORMAT_ROW_BY_ROW: hog::extract_descrs_by_rows(win_size.height, win_size.width, block_stride.height, block_stride.width, win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors); break; case DESCR_FORMAT_COL_BY_COL: hog::extract_descrs_by_cols(win_size.height, win_size.width, block_stride.height, block_stride.width, win_stride.height, win_stride.width, img.rows, img.cols, block_hists.ptr<float>(), descriptors); break; default: CV_Error(CV_StsBadArg, "Unknown descriptor format"); } }

Can someone help me get the block-only HOG functions. EDITED: I am only interested in calculating the HOG functions for the various window size preservation functions for the cell and blocking them.

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I changed the following functions to calculate HOG descriptors for blocks only.

 void cv::gpu::HOGDescriptor::getDescriptorsBlock(const GpuMat& img, Size win_stride, GpuMat& descriptors, FileStorage fs3, string fileName, double scale, int width, int height, size_t lev) { CV_Assert(win_stride.width % block_stride.width == 0 && win_stride.height % block_stride.height == 0); size_t block_hist_size = getBlockHistogramSize(); computeBlockHistograms(img); Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride); // Size blocks_per_win = numPartsWithin(win_size, block_size, block_stride); // Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride); // copy block_hists from GPU to CPU/ float dest_ptr[block_hist_size * blocks_per_img.area()]; cudaMemcpy( &dest_ptr[0], block_hists.ptr<float>(), block_hist_size *blocks_per_img.area()*sizeof(CV_32F), cudaMemcpyDeviceToHost); std::cout<<"( "<<width<< " ," << height<< ")"<< std::endl; std::cout <<lev<< std::endl; // write to yml file int level = lev; fs3<<"Scale"<<scale; fs3 <<"Level"<<level; fs3<<"Width"<<width<<"Height"<<height; fs3 << "features" << "["; for (unsigned int i = 0; i < (block_hist_size * blocks_per_img.area()) ; i++ ) { fs3 << dest_ptr[i]; } fs3 << "]"; }

The following is a description of the HOG descriptors for multiscale images.

 void cv::gpu::HOGDescriptor::getDescriptorsMultiScale(const GpuMat& img, Size win_stride, double scale0, unsigned int count) { CV_Assert(img.type() == CV_8UC1 || img.type() == CV_8UC4); vector<double> level_scale; double scale = 1.; int levels = 0; for (levels = 0; levels < nlevels; levels++) { level_scale.push_back(scale); if (cvRound(img.cols/scale) < win_size.width || cvRound(img.rows/scale) < win_size.height || scale0 <= 1) break; scale *= scale0; } levels = std::max(levels, 1); level_scale.resize(levels); image_scales.resize(levels); // open yml file with image ID FileStorage fs3; char fileName[20]; GpuMat descriptors; sprintf (fileName, "%04d", count); fs3.open(fileName, FileStorage::WRITE); for (size_t i = 0; i < level_scale.size(); i++) { scale = level_scale[i]; Size sz(cvRound(img.cols / scale), cvRound(img.rows / scale)); GpuMat smaller_img; if (sz == img.size()) smaller_img = img; else { image_scales[i].create(sz, img.type()); switch (img.type()) { case CV_8UC1: hog::resize_8UC1(img, image_scales[i]); break; case CV_8UC4: hog::resize_8UC4(img, image_scales[i]); break; } smaller_img = image_scales[i]; } std::cout<<"scale "<<level_scale[i]<<std::endl; // calculate descriptors for blocks getDescriptorsBlock( smaller_img, win_stride, descriptors, fs3, fileName, scale, smaller_img.cols, smaller_img.rows, i); // detect(smaller_img, locations, hit_threshold, win_stride, padding); } // close yml file fs3.release(); }

Remember to add the definition of these two functions to OpenCV / modules / GPU / include / opencv2 / GPU / gpu.hpp

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