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refactored HoughLines (converted it into Algorithm)

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This commit is contained in:
Vladislav Vinogradov
2013-04-30 12:51:33 +04:00
parent 48fb8c4f8a
commit 1652540a1f
6 changed files with 325 additions and 118 deletions
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81
modules/gpuimgproc/include/opencv2/gpuimgproc.hpp
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@@ -220,18 +220,82 @@ inline void Canny(InputArray dx, InputArray dy, OutputArray edges, double low_th
/////////////////////////// Hough Transform ////////////////////////////
struct HoughLinesBuf
//////////////////////////////////////
// HoughLines
class CV_EXPORTS HoughLinesDetector : public Algorithm
{
GpuMat accum;
GpuMat list;
public:
virtual void detect(InputArray src, OutputArray lines) = 0;
virtual void downloadResults(InputArray d_lines, OutputArray h_lines, OutputArray h_votes = noArray()) = 0;
virtual void setRho(float rho) = 0;
virtual float getRho() const = 0;
virtual void setTheta(float theta) = 0;
virtual float getTheta() const = 0;
virtual void setThreshold(int threshold) = 0;
virtual int getThreshold() const = 0;
virtual void setDoSort(bool doSort) = 0;
virtual bool getDoSort() const = 0;
virtual void setMaxLines(int maxLines) = 0;
virtual int getMaxLines() const = 0;
};
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines, OutputArray h_votes = noArray());
CV_EXPORTS Ptr<HoughLinesDetector> createHoughLinesDetector(float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
// obsolete
__OPENCV_GPUIMGPROC_DEPR_BEFORE__ void HoughLines(InputArray src, OutputArray lines, float rho, float theta, int threshold,
bool doSort = false, int maxLines = 4096) __OPENCV_GPUIMGPROC_DEPR_AFTER__;
inline void HoughLines(InputArray src, OutputArray lines, float rho, float theta, int threshold, bool doSort, int maxLines)
{
gpu::createHoughLinesDetector(rho, theta, threshold, doSort, maxLines)->detect(src, lines);
}
//////////////////////////////////////
// HoughLinesP
//! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS void HoughLinesP(const GpuMat& image, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096);
class CV_EXPORTS HoughSegmentDetector : public Algorithm
{
public:
virtual void detect(InputArray src, OutputArray lines) = 0;
virtual void setRho(float rho) = 0;
virtual float getRho() const = 0;
virtual void setTheta(float theta) = 0;
virtual float getTheta() const = 0;
virtual void setMinLineLength(int minLineLength) = 0;
virtual int getMinLineLength() const = 0;
virtual void setMaxLineGap(int maxLineGap) = 0;
virtual int getMaxLineGap() const = 0;
virtual void setMaxLines(int maxLines) = 0;
virtual int getMaxLines() const = 0;
};
CV_EXPORTS Ptr<HoughSegmentDetector> createHoughSegmentDetector(float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096);
// obsolete
__OPENCV_GPUIMGPROC_DEPR_BEFORE__ void HoughLinesP(InputArray src, OutputArray lines,
float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096) __OPENCV_GPUIMGPROC_DEPR_AFTER__;
inline void HoughLinesP(InputArray src, OutputArray lines, float rho, float theta, int minLineLength, int maxLineGap, int maxLines)
{
gpu::createHoughSegmentDetector(rho, theta, minLineLength, maxLineGap, maxLines)->detect(src, lines);
}
//////////////////////////////////////
// HoughCircles
struct HoughCirclesBuf
{
@@ -245,6 +309,9 @@ CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, int method, flo
CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
CV_EXPORTS void HoughCirclesDownload(const GpuMat& d_circles, OutputArray h_circles);
//////////////////////////////////////
// GeneralizedHough
//! finds arbitrary template in the grayscale image using Generalized Hough Transform
//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.