refactored HoughLines (converted it into Algorithm)

modules/gpu/perf4au/main.cpp

@@ -86,13 +86,14 @@ PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))
     {
         cv::gpu::GpuMat d_image(image);
         cv::gpu::GpuMat d_lines;
-        cv::gpu::HoughLinesBuf d_buf;
 
-        cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+        cv::Ptr<cv::gpu::HoughSegmentDetector> hough = cv::gpu::createHoughSegmentDetector(rho, theta, minLineLenght, maxLineGap);
+
+        hough->detect(d_image, d_lines);
 
         TEST_CYCLE()
         {
-            cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+            hough->detect(d_image, d_lines);
         }
     }
     else

modules/gpuimgproc/include/opencv2/gpuimgproc.hpp

@@ -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.

modules/gpuimgproc/perf/perf_hough.cpp

@@ -103,9 +103,10 @@ PERF_TEST_P(Sz, HoughLines,
     {
         const cv::gpu::GpuMat d_src(src);
         cv::gpu::GpuMat d_lines;
-        cv::gpu::HoughLinesBuf d_buf;
 
-        TEST_CYCLE() cv::gpu::HoughLines(d_src, d_lines, d_buf, rho, theta, threshold);
+        cv::Ptr<cv::gpu::HoughLinesDetector> hough = cv::gpu::createHoughLinesDetector(rho, theta, threshold);
+
+        TEST_CYCLE() hough->detect(d_src, d_lines);
 
         cv::Mat gpu_lines(d_lines.row(0));
         cv::Vec2f* begin = gpu_lines.ptr<cv::Vec2f>(0);
@@ -151,9 +152,10 @@ PERF_TEST_P(Image, HoughLinesP,
     {
         const cv::gpu::GpuMat d_mask(mask);
         cv::gpu::GpuMat d_lines;
-        cv::gpu::HoughLinesBuf d_buf;
 
-        TEST_CYCLE() cv::gpu::HoughLinesP(d_mask, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
+        cv::Ptr<cv::gpu::HoughSegmentDetector> hough = cv::gpu::createHoughSegmentDetector(rho, theta, minLineLenght, maxLineGap);
+
+        TEST_CYCLE() hough->detect(d_mask, d_lines);
 
         cv::Mat gpu_lines(d_lines);
         cv::Vec4i* begin = gpu_lines.ptr<cv::Vec4i>();

modules/gpuimgproc/test/test_hough.cpp

@@ -94,11 +94,13 @@ GPU_TEST_P(HoughLines, Accuracy)
     cv::Mat src(size, CV_8UC1);
     generateLines(src);
 
+    cv::Ptr<cv::gpu::HoughLinesDetector> hough = cv::gpu::createHoughLinesDetector(rho, theta, threshold);
+
     cv::gpu::GpuMat d_lines;
-    cv::gpu::HoughLines(loadMat(src, useRoi), d_lines, rho, theta, threshold);
+    hough->detect(loadMat(src, useRoi), d_lines);
 
     std::vector<cv::Vec2f> lines;
-    cv::gpu::HoughLinesDownload(d_lines, lines);
+    hough->downloadResults(d_lines, lines);
 
     cv::Mat dst(size, CV_8UC1);
     drawLines(dst, lines);

samples/gpu/houghlines.cpp

@@ -41,7 +41,7 @@ int main(int argc, const char* argv[])
     {
         const int64 start = getTickCount();
 
-        HoughLinesP(mask, lines_cpu, 1, CV_PI / 180, 50, 60, 5);
+        cv::HoughLinesP(mask, lines_cpu, 1, CV_PI / 180, 50, 60, 5);
 
         const double timeSec = (getTickCount() - start) / getTickFrequency();
         cout << "CPU Time : " << timeSec * 1000 << " ms" << endl;
@@ -56,11 +56,12 @@ int main(int argc, const char* argv[])
 
     GpuMat d_src(mask);
     GpuMat d_lines;
-    HoughLinesBuf d_buf;
     {
         const int64 start = getTickCount();
 
-        gpu::HoughLinesP(d_src, d_lines, d_buf, 1.0f, (float) (CV_PI / 180.0f), 50, 5);
+        Ptr<gpu::HoughSegmentDetector> hough = gpu::createHoughSegmentDetector(1.0f, (float) (CV_PI / 180.0f), 50, 5);
+
+        hough->detect(d_src, d_lines);
 
         const double timeSec = (getTickCount() - start) / getTickFrequency();
         cout << "GPU Time : " << timeSec * 1000 << " ms" << endl;