我正在尝试仅计算块的HOG功能。我浏览了hog.cpp下列出的opencv/module/gpu/src/。下面是我仅将代码块功能更改为计算机的代码。
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");
}
}
这也是
computeBlockHistograms代码。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);
}
编辑:我也从
hog.cpp包括getDescriptor函数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");
}
}
有人可以帮我获得仅限块的HOG功能。
编辑:我只想计算不同窗口大小的HOG功能，并保持单元格和块的功能相同。
最佳答案
我修改了以下函数，仅计算块的HOG描述符。
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 << "]";
}
下面是计算多比例图像的HOG描述符的方法。
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();
}
不要忘记在这两个函数中添加定义
opencv/modules/gpu/include/opencv2/gpu/gpu.hpp
关于c++ - HoG功能仅适用于块，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/31158790/