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added getDescriptors function (draft version)

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This commit is contained in:
Alexey Spizhevoy 2010-11-17 17:10:23 +00:00
parent 2d01558479
commit 8adc62016b
3 changed files with 70 additions and 24 deletions
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9
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -1001,13 +1001,15 @@ namespace cv
void setSVMDetector(const vector<float>& detector);
bool checkDetectorSize() const;
void computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle);
void detect(const GpuMat& img, vector<Point>& found_locations, double hit_threshold=0,
Size win_stride=Size(), Size padding=Size());
void detectMultiScale(const GpuMat& img, vector<Rect>& found_locations,
double hit_threshold=0, Size win_stride=Size(), Size padding=Size(),
double scale0=1.05, int group_threshold=2);
////TODO: test it
//void getDescriptors(const GpuMat& img, Size win_stride, vector<GpuMat>& descriptors)
Size win_size;
Size block_size;
Size block_stride;
@ -1032,6 +1034,11 @@ namespace cv
private:
static int numPartsWithin(int size, int part_size, int stride);
static Size numPartsWithin(Size size, Size part_size, Size stride);
void computeBlockHistograms(const GpuMat& img);
void computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle);
GpuMat grad, qangle;
};
}

4
modules/gpu/src/cuda/hog.cu
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@ -423,11 +423,13 @@ void classify_hists(int win_height, int win_width, int block_stride_y, int block
img_win_width, img_block_width, win_block_stride_x, win_block_stride_y,
block_hists, coefs, free_coef, threshold, labels);
cudaSafeCall(cudaThreadSynchronize());
}
}
//------------------------------------------------------------
// Gradients computation
template <int nthreads>
__global__ void compute_gradients_8UC4_kernel(int height, int width, const PtrElemStep img,
float angle_scale, PtrElemStepf grad, PtrElemStep qangle)

81
modules/gpu/src/hog.cpp
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@ -53,8 +53,6 @@ void cv::gpu::HOGDescriptor::setSVMDetector(const vector<float>&) { throw_nogpu(
void cv::gpu::HOGDescriptor::computeGradient(const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::HOGDescriptor::detect(const GpuMat&, vector<Point>&, double, Size, Size) { throw_nogpu(); }
void cv::gpu::HOGDescriptor::detectMultiScale(const GpuMat&, vector<Rect>&, double, Size, Size, double, int) { throw_nogpu(); }
int cv::gpu::HOGDescriptor::numPartsWithin(int, int, int) { throw_nogpu(); return 0; }
cv::Size cv::gpu::HOGDescriptor::numPartsWithin(cv::Size, cv::Size, cv::Size) { throw_nogpu(); return cv::Size(); }
std::vector<float> cv::gpu::HOGDescriptor::getDefaultPeopleDetector() { throw_nogpu(); return std::vector<float>(); }
std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector_48x96() { throw_nogpu(); return std::vector<float>(); }
std::vector<float> cv::gpu::HOGDescriptor::getPeopleDetector_64x128() { throw_nogpu(); return std::vector<float>(); }
@ -197,30 +195,12 @@ void cv::gpu::HOGDescriptor::computeGradient(const GpuMat& img, GpuMat& grad, Gp
}
void cv::gpu::HOGDescriptor::detect(const GpuMat& img, vector<Point>& hits, double hit_threshold,
Size win_stride, Size padding)
void cv::gpu::HOGDescriptor::computeBlockHistograms(const GpuMat& img)
{
hits.clear();
if (detector.empty())
return;
GpuMat grad, qangle;
computeGradient(img, grad, qangle);
if (win_stride == Size())
win_stride = block_stride;
else
CV_Assert(win_stride.width % block_stride.width == 0 &&
win_stride.height % block_stride.height == 0);
CV_Assert(padding == Size(0, 0));
computeGradient(img, grad, qangle);
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);
Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride);
labels.create(1, wins_per_img.area(), CV_8U);
block_hists.create(1, block_hist_size * blocks_per_img.area(), CV_32F);
hog::compute_hists(nbins, block_stride.width, block_stride.height,
@ -229,6 +209,63 @@ void cv::gpu::HOGDescriptor::detect(const GpuMat& img, vector<Point>& hits, doub
hog::normalize_hists(nbins, block_stride.width, block_stride.height, img.rows, img.cols,
block_hists.ptr<float>(), (float)threshold_L2hys);
}
////TODO: test it
//void cv::gpu::HOGDescriptor::getDescriptors(const GpuMat& img, Size win_stride,
// vector<GpuMat>& descriptors)
//{
// CV_Assert(win_stride.width % block_stride.width == 0 &&
// win_stride.height % block_stride.height == 0);
//
// computeBlockHistograms(img);
//
// Size blocks_per_img = numPartsWithin(img.size(), block_size, block_stride);
// GpuMat hists_reshaped = block_hists.reshape(0, blocks_per_img.height);
//
// const int 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.resize(wins_per_img.area());
// for (int i = 0; i < wins_per_img.height; ++i)
// {
// for (int j = 0; j < wins_per_img.width; ++j)
// {
// Range rows;
// rows.start = i * (blocks_per_win.height + 1);
// rows.end = rows.start + blocks_per_win.height;
//
// Range cols;
// cols.start = j * (blocks_per_win.width + 1) * block_hist_size;
// cols.end = cols.start + blocks_per_win.width * block_hist_size;
//
// descriptors[i * wins_per_img.width + j] = hists_reshaped(rows, cols);
// }
// }
//}
void cv::gpu::HOGDescriptor::detect(const GpuMat& img, vector<Point>& hits, double hit_threshold,
Size win_stride, Size padding)
{
CV_Assert(padding == Size(0, 0));
hits.clear();
if (detector.empty())
return;
computeBlockHistograms(img);
if (win_stride == Size())
win_stride = block_stride;
else
CV_Assert(win_stride.width % block_stride.width == 0 &&
win_stride.height % block_stride.height == 0);
Size wins_per_img = numPartsWithin(img.size(), win_size, win_stride);
labels.create(1, wins_per_img.area(), CV_8U);
hog::classify_hists(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>(),