opencv/modules/cudaimgproc/src/hough_segments.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// License Agreement
// For Open Source Computer Vision Library
//
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#include "precomp.hpp"
using namespace cv;
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using namespace cv::cuda;
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#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
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Ptr<cuda::HoughSegmentDetector> cv::cuda::createHoughSegmentDetector(float, float, int, int, int) { throw_no_cuda(); return Ptr<HoughSegmentDetector>(); }
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#else /* !defined (HAVE_CUDA) */
namespace cv { namespace cuda { namespace device
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{
namespace hough
{
int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
}
namespace hough_lines
{
void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20);
}
namespace hough_segments
{
int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength);
}
}}}
namespace
{
class HoughSegmentDetectorImpl : public HoughSegmentDetector
{
public:
HoughSegmentDetectorImpl(float rho, float theta, int minLineLength, int maxLineGap, int maxLines) :
rho_(rho), theta_(theta), minLineLength_(minLineLength), maxLineGap_(maxLineGap), maxLines_(maxLines)
{
}
void detect(InputArray src, OutputArray lines);
void setRho(float rho) { rho_ = rho; }
float getRho() const { return rho_; }
void setTheta(float theta) { theta_ = theta; }
float getTheta() const { return theta_; }
void setMinLineLength(int minLineLength) { minLineLength_ = minLineLength; }
int getMinLineLength() const { return minLineLength_; }
void setMaxLineGap(int maxLineGap) { maxLineGap_ = maxLineGap; }
int getMaxLineGap() const { return maxLineGap_; }
void setMaxLines(int maxLines) { maxLines_ = maxLines; }
int getMaxLines() const { return maxLines_; }
void write(FileStorage& fs) const
{
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fs << "name" << "PHoughLinesDetector_CUDA"
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<< "rho" << rho_
<< "theta" << theta_
<< "minLineLength" << minLineLength_
<< "maxLineGap" << maxLineGap_
<< "maxLines" << maxLines_;
}
void read(const FileNode& fn)
{
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CV_Assert( String(fn["name"]) == "PHoughLinesDetector_CUDA" );
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rho_ = (float)fn["rho"];
theta_ = (float)fn["theta"];
minLineLength_ = (int)fn["minLineLength"];
maxLineGap_ = (int)fn["maxLineGap"];
maxLines_ = (int)fn["maxLines"];
}
private:
float rho_;
float theta_;
int minLineLength_;
int maxLineGap_;
int maxLines_;
GpuMat accum_;
GpuMat list_;
GpuMat result_;
};
void HoughSegmentDetectorImpl::detect(InputArray _src, OutputArray lines)
{
using namespace cv::cuda::device::hough;
using namespace cv::cuda::device::hough_lines;
using namespace cv::cuda::device::hough_segments;
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GpuMat src = _src.getGpuMat();
CV_Assert( src.type() == CV_8UC1 );
CV_Assert( src.cols < std::numeric_limits<unsigned short>::max() );
CV_Assert( src.rows < std::numeric_limits<unsigned short>::max() );
ensureSizeIsEnough(1, src.size().area(), CV_32SC1, list_);
unsigned int* srcPoints = list_.ptr<unsigned int>();
const int pointsCount = buildPointList_gpu(src, srcPoints);
if (pointsCount == 0)
{
lines.release();
return;
}
const int numangle = cvRound(CV_PI / theta_);
const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho_);
CV_Assert( numangle > 0 && numrho > 0 );
ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, accum_);
accum_.setTo(Scalar::all(0));
DeviceInfo devInfo;
linesAccum_gpu(srcPoints, pointsCount, accum_, rho_, theta_, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
ensureSizeIsEnough(1, maxLines_, CV_32SC4, result_);
int linesCount = houghLinesProbabilistic_gpu(src, accum_, result_.ptr<int4>(), maxLines_, rho_, theta_, maxLineGap_, minLineLength_);
if (linesCount == 0)
{
lines.release();
return;
}
result_.cols = linesCount;
result_.copyTo(lines);
}
}
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Ptr<HoughSegmentDetector> cv::cuda::createHoughSegmentDetector(float rho, float theta, int minLineLength, int maxLineGap, int maxLines)
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{
return makePtr<HoughSegmentDetectorImpl>(rho, theta, minLineLength, maxLineGap, maxLines);
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}
#endif /* !defined (HAVE_CUDA) */