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#include "precomp.hpp"
using namespace cv;
using namespace cv::cuda;
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) || !defined(HAVE_OPENCV_CUDAARITHM)
Ptr<cuda::CornersDetector> cv::cuda::createGoodFeaturesToTrackDetector(int, int, double, double, int, bool, double) { throw_no_cuda(); return Ptr<cuda::CornersDetector>(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace cuda { namespace device
{
namespace gfft
{
int findCorners_gpu(PtrStepSzf eig, float threshold, PtrStepSzb mask, float2* corners, int max_count);
void sortCorners_gpu(PtrStepSzf eig, float2* corners, int count);
}
}}}
namespace
{
class GoodFeaturesToTrackDetector : public CornersDetector
{
public:
GoodFeaturesToTrackDetector(int srcType, int maxCorners, double qualityLevel, double minDistance,
int blockSize, bool useHarrisDetector, double harrisK);
void detect(InputArray image, OutputArray corners, InputArray mask, Stream& stream);
private:
int maxCorners_;
double qualityLevel_;
double minDistance_;
Ptr<cuda::CornernessCriteria> cornerCriteria_;
GpuMat Dx_;
GpuMat Dy_;
GpuMat buf_;
GpuMat eig_;
GpuMat tmpCorners_;
};
GoodFeaturesToTrackDetector::GoodFeaturesToTrackDetector(int srcType, int maxCorners, double qualityLevel, double minDistance,
int blockSize, bool useHarrisDetector, double harrisK) :
maxCorners_(maxCorners), qualityLevel_(qualityLevel), minDistance_(minDistance)
{
CV_Assert( qualityLevel_ > 0 && minDistance_ >= 0 && maxCorners_ >= 0 );
cornerCriteria_ = useHarrisDetector ?
cuda::createHarrisCorner(srcType, blockSize, 3, harrisK) :
cuda::createMinEigenValCorner(srcType, blockSize, 3);
}
void GoodFeaturesToTrackDetector::detect(InputArray _image, OutputArray _corners, InputArray _mask, Stream& stream)
{
// TODO : implement async version
(void) stream;
using namespace cv::cuda::device::gfft;
GpuMat image = _image.getGpuMat();
GpuMat mask = _mask.getGpuMat();
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) );
ensureSizeIsEnough(image.size(), CV_32FC1, eig_);
cornerCriteria_->compute(image, eig_);
double maxVal = 0;
cuda::minMax(eig_, 0, &maxVal);
ensureSizeIsEnough(1, std::max(1000, static_cast<int>(image.size().area() * 0.05)), CV_32FC2, tmpCorners_);
int total = findCorners_gpu(eig_, static_cast<float>(maxVal * qualityLevel_), mask, tmpCorners_.ptr<float2>(), tmpCorners_.cols);
if (total == 0)
{
_corners.release();
return;
}
sortCorners_gpu(eig_, tmpCorners_.ptr<float2>(), total);
if (minDistance_ < 1)
{
tmpCorners_.colRange(0, maxCorners_ > 0 ? std::min(maxCorners_, total) : total).copyTo(_corners);
}
else
{
std::vector<Point2f> tmp(total);
Mat tmpMat(1, total, CV_32FC2, (void*)&tmp[0]);
tmpCorners_.colRange(0, total).download(tmpMat);
std::vector<Point2f> tmp2;
tmp2.reserve(total);
const int cell_size = cvRound(minDistance_);
const int grid_width = (image.cols + cell_size - 1) / cell_size;
const int grid_height = (image.rows + cell_size - 1) / cell_size;
std::vector< std::vector<Point2f> > grid(grid_width * grid_height);
for (int i = 0; i < total; ++i)
{
Point2f p = tmp[i];
bool good = true;
int x_cell = static_cast<int>(p.x / cell_size);
int y_cell = static_cast<int>(p.y / cell_size);
int x1 = x_cell - 1;
int y1 = y_cell - 1;
int x2 = x_cell + 1;
int y2 = y_cell + 1;
// boundary check
x1 = std::max(0, x1);
y1 = std::max(0, y1);
x2 = std::min(grid_width - 1, x2);
y2 = std::min(grid_height - 1, y2);
for (int yy = y1; yy <= y2; yy++)
{
for (int xx = x1; xx <= x2; xx++)
{
std::vector<Point2f>& m = grid[yy * grid_width + xx];
if (!m.empty())
{
for(size_t j = 0; j < m.size(); j++)
{
float dx = p.x - m[j].x;
float dy = p.y - m[j].y;
if (dx * dx + dy * dy < minDistance_ * minDistance_)
{
good = false;
goto break_out;
}
}
}
}
}
break_out:
if(good)
{
grid[y_cell * grid_width + x_cell].push_back(p);
tmp2.push_back(p);
if (maxCorners_ > 0 && tmp2.size() == static_cast<size_t>(maxCorners_))
break;
}
}
_corners.create(1, static_cast<int>(tmp2.size()), CV_32FC2);
GpuMat corners = _corners.getGpuMat();
corners.upload(Mat(1, static_cast<int>(tmp2.size()), CV_32FC2, &tmp2[0]));
}
}
}
Ptr<cuda::CornersDetector> cv::cuda::createGoodFeaturesToTrackDetector(int srcType, int maxCorners, double qualityLevel, double minDistance,
int blockSize, bool useHarrisDetector, double harrisK)
{
return Ptr<cuda::CornersDetector>(
new GoodFeaturesToTrackDetector(srcType, maxCorners, qualityLevel, minDistance, blockSize, useHarrisDetector, harrisK));
}
#endif /* !defined (HAVE_CUDA) */