Extensive wrapping of CUDA functionalities for Python
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@@ -829,55 +829,55 @@ enum MarkerTypes
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};
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//! finds arbitrary template in the grayscale image using Generalized Hough Transform
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class CV_EXPORTS GeneralizedHough : public Algorithm
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class CV_EXPORTS_W GeneralizedHough : public Algorithm
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{
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public:
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//! set template to search
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virtual void setTemplate(InputArray templ, Point templCenter = Point(-1, -1)) = 0;
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virtual void setTemplate(InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1)) = 0;
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CV_WRAP virtual void setTemplate(InputArray templ, Point templCenter = Point(-1, -1)) = 0;
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CV_WRAP virtual void setTemplate(InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1)) = 0;
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//! find template on image
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virtual void detect(InputArray image, OutputArray positions, OutputArray votes = noArray()) = 0;
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virtual void detect(InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = noArray()) = 0;
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CV_WRAP virtual void detect(InputArray image, OutputArray positions, OutputArray votes = noArray()) = 0;
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CV_WRAP virtual void detect(InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = noArray()) = 0;
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//! Canny low threshold.
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virtual void setCannyLowThresh(int cannyLowThresh) = 0;
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virtual int getCannyLowThresh() const = 0;
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CV_WRAP virtual void setCannyLowThresh(int cannyLowThresh) = 0;
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CV_WRAP virtual int getCannyLowThresh() const = 0;
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//! Canny high threshold.
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virtual void setCannyHighThresh(int cannyHighThresh) = 0;
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virtual int getCannyHighThresh() const = 0;
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CV_WRAP virtual void setCannyHighThresh(int cannyHighThresh) = 0;
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CV_WRAP virtual int getCannyHighThresh() const = 0;
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//! Minimum distance between the centers of the detected objects.
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virtual void setMinDist(double minDist) = 0;
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virtual double getMinDist() const = 0;
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CV_WRAP virtual void setMinDist(double minDist) = 0;
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CV_WRAP virtual double getMinDist() const = 0;
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//! Inverse ratio of the accumulator resolution to the image resolution.
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virtual void setDp(double dp) = 0;
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virtual double getDp() const = 0;
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CV_WRAP virtual void setDp(double dp) = 0;
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CV_WRAP virtual double getDp() const = 0;
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//! Maximal size of inner buffers.
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virtual void setMaxBufferSize(int maxBufferSize) = 0;
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virtual int getMaxBufferSize() const = 0;
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CV_WRAP virtual void setMaxBufferSize(int maxBufferSize) = 0;
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CV_WRAP virtual int getMaxBufferSize() const = 0;
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};
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//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
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//! Detects position only without translation and rotation
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class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough
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class CV_EXPORTS_W GeneralizedHoughBallard : public GeneralizedHough
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{
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public:
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//! R-Table levels.
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virtual void setLevels(int levels) = 0;
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virtual int getLevels() const = 0;
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CV_WRAP virtual void setLevels(int levels) = 0;
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CV_WRAP virtual int getLevels() const = 0;
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//! The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.
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virtual void setVotesThreshold(int votesThreshold) = 0;
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virtual int getVotesThreshold() const = 0;
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CV_WRAP virtual void setVotesThreshold(int votesThreshold) = 0;
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CV_WRAP virtual int getVotesThreshold() const = 0;
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};
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//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
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//! Detects position, translation and rotation
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class CV_EXPORTS GeneralizedHoughGuil : public GeneralizedHough
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class CV_EXPORTS_W GeneralizedHoughGuil : public GeneralizedHough
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{
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public:
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//! Angle difference in degrees between two points in feature.
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