Merge remote-tracking branch 'upstream/3.4' into merge-3.4

Author: alalek

modules/img_hash/src/radial_variance_hash.cpp

@@ -266,7 +266,7 @@ class RadialVarianceHashImpl CV_FINAL : public ImgHashBase::ImgHashImpl
         }
         else
         {
-            hash = 0;
+            hash.setTo(cv::Scalar::all(0));
         }
     }
 

modules/ximgproc/include/opencv2/ximgproc/structured_edge_detection.hpp

@@ -102,31 +102,31 @@ class CV_EXPORTS_W StructuredEdgeDetection : public Algorithm
 
     The algorithm underlies this function is much more robust to texture presence, than common
     approaches, e.g. Sobel
-    @param _src source image (RGB, float, in [0;1]) to detect edges
-    @param _dst destination image (grayscale, float, in [0;1]) where edges are drawn
+    @param src source image (RGB, float, in [0;1]) to detect edges
+    @param dst destination image (grayscale, float, in [0;1]) where edges are drawn
     @sa Sobel, Canny
      */
-    CV_WRAP virtual void detectEdges(cv::InputArray _src, cv::OutputArray _dst) const = 0;
+    CV_WRAP virtual void detectEdges(cv::InputArray src, cv::OutputArray dst) const = 0;
 
     /** @brief The function computes orientation from edge image.
 
-    @param _src edge image.
-    @param _dst orientation image.
+    @param src edge image.
+    @param dst orientation image.
      */
-    CV_WRAP virtual void computeOrientation(cv::InputArray _src, cv::OutputArray _dst) const = 0;
+    CV_WRAP virtual void computeOrientation(cv::InputArray src, cv::OutputArray dst) const = 0;
 
 
     /** @brief The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
 
     @param edge_image edge image from detectEdges function.
     @param orientation_image orientation image from computeOrientation function.
-    @param _dst suppressed image (grayscale, float, in [0;1])
+    @param dst suppressed image (grayscale, float, in [0;1])
     @param r radius for NMS suppression.
     @param s radius for boundary suppression.
     @param m multiplier for conservative suppression.
     @param isParallel enables/disables parallel computing.
      */
-    CV_WRAP virtual void edgesNms(cv::InputArray edge_image, cv::InputArray orientation_image, cv::OutputArray _dst, int r = 2, int s = 0, float m = 1, bool isParallel = true) const = 0;
+    CV_WRAP virtual void edgesNms(cv::InputArray edge_image, cv::InputArray orientation_image, cv::OutputArray dst, int r = 2, int s = 0, float m = 1, bool isParallel = true) const = 0;
 };
 
 /*!

modules/ximgproc/samples/structured_edge_detection.cpp

@@ -1,39 +1,29 @@
 /**************************************************************************************
-The structered edge demo requires you to provide a model.
+The structured forests for fast edge detection demo requires you to provide a model.
 This model can be found at the opencv_extra repository on Github on the following link:
 https://github.com/opencv/opencv_extra/blob/master/testdata/cv/ximgproc/model.yml.gz
 ***************************************************************************************/
 
 #include <opencv2/ximgproc.hpp>
 #include "opencv2/highgui.hpp"
-#include "opencv2/core/utility.hpp"
 #include <iostream>
 
 using namespace cv;
 using namespace cv::ximgproc;
 
 const char* keys =
 {
-    "{i || input image name}"
-    "{m || model name}"
-    "{o || output image name}"
+    "{i || input image file name}"
+    "{m || model file name}"
+    "{o || output image file name}"
 };
 
 int main( int argc, const char** argv )
 {
-    bool printHelp = ( argc == 1 );
-    printHelp = printHelp || ( argc == 2 && String(argv[1]) == "--help" );
-    printHelp = printHelp || ( argc == 2 && String(argv[1]) == "-h" );
-
-    if ( printHelp )
-    {
-        std::cout << "\nThis sample demonstrates structured forests for fast edge detection\n"
-               "Call:\n"
-               "    structured_edge_detection -i=in_image_name -m=model_name [-o=out_image_name]\n\n";
-        return 0;
-    }
-
     CommandLineParser parser(argc, argv, keys);
+    parser.about("This sample demonstrates usage of structured forests for fast edge detection");
+    parser.printMessage();
+
     if ( !parser.check() )
     {
         parser.printErrors();
@@ -44,39 +34,63 @@ int main( int argc, const char** argv )
     String inFilename = parser.get<String>("i");
     String outFilename = parser.get<String>("o");
 
-    Mat image = imread(inFilename, 1);
+    //! [imread]
+    Mat image = imread(inFilename, IMREAD_COLOR);
     if ( image.empty() )
         CV_Error(Error::StsError, String("Cannot read image file: ") + inFilename);
+    //! [imread]
 
     if ( modelFilename.size() == 0)
         CV_Error(Error::StsError, String("Empty model name"));
 
+    //! [convert]
     image.convertTo(image, DataType<float>::type, 1/255.0);
+    //! [convert]
 
-    Mat edges(image.size(), image.type());
-
+    TickMeter tm;
+    tm.start();
+    //! [create]
     Ptr<StructuredEdgeDetection> pDollar =
         createStructuredEdgeDetection(modelFilename);
+    //! [create]
+
+    tm.stop();
+    std::cout << "createStructuredEdgeDetection() time : " << tm << std::endl;
+
+    tm.reset();
+    tm.start();
+    //! [detect]
+    Mat edges;
     pDollar->detectEdges(image, edges);
+    //! [detect]
+    tm.stop();
+    std::cout << "detectEdges() time : " << tm << std::endl;
 
+    tm.reset();
+    tm.start();
+    //! [nms]
     // computes orientation from edge map
     Mat orientation_map;
     pDollar->computeOrientation(edges, orientation_map);
 
     // suppress edges
     Mat edge_nms;
     pDollar->edgesNms(edges, orientation_map, edge_nms, 2, 0, 1, true);
+    //! [nms]
+
+    tm.stop();
+    std::cout << "nms time : " << tm << std::endl;
 
+    //! [imshow]
     if ( outFilename.size() == 0 )
     {
-        namedWindow("edges", 1);
         imshow("edges", edges);
-        namedWindow("edges nms", 1);
         imshow("edges nms", edge_nms);
         waitKey(0);
     }
     else
         imwrite(outFilename, 255*edges);
+    //! [imshow]
 
     return 0;
 }

modules/ximgproc/test/test_fld.cpp

@@ -292,7 +292,8 @@ TEST_F(ximgproc_ED, ManySmallCircles)
     size_t lines_size = 6264;
     size_t ellipses_size = 2449;
     EXPECT_EQ(detector->getSegments().size(), segments_size);
-    EXPECT_EQ(lines.size(), lines_size);
+    EXPECT_GE(lines.size(), lines_size);
+    EXPECT_LE(lines.size(), lines_size + 2);
     EXPECT_EQ(ellipses.size(), ellipses_size);
 }
 }} // namespace

modules/ximgproc/tutorials/prediction.markdown

@@ -46,41 +46,22 @@ Explanation
 -----------
 
 -#  **Load source color image**
-    @code{.cpp}
-    cv::Mat image = cv::imread(inFilename, 1);
-    if ( image.empty() )
-    {
-        printf("Cannot read image file: %s\n", inFilename.c_str());
-        return -1;
-    }
-    @endcode
-
--#  **Convert source image to [0;1] range**
-    @code{.cpp}
-    image.convertTo(image, cv::DataType<float>::type, 1/255.0);
-    @endcode
+
+    @snippet ximgproc/samples/structured_edge_detection.cpp imread
+
+-#  **Convert source image to float [0;1] range**
+
+    @snippet ximgproc/samples/structured_edge_detection.cpp convert
 
 -#  **Run main algorithm**
-    @code{.cpp}
-    cv::Mat edges(image.size(), image.type());
 
-    cv::Ptr<StructuredEdgeDetection> pDollar =
-        cv::createStructuredEdgeDetection(modelFilename);
-    pDollar->detectEdges(image, edges);
-    @endcode
+    @snippet ximgproc/samples/structured_edge_detection.cpp create
+    @snippet ximgproc/samples/structured_edge_detection.cpp detect
+    @snippet ximgproc/samples/structured_edge_detection.cpp nms
 
 -#  **Show results**
-    @code{.cpp}
-    if ( outFilename == "" )
-    {
-        cv::namedWindow("edges", 1);
-        cv::imshow("edges", edges);
-
-        cv::waitKey(0);
-    }
-    else
-        cv::imwrite(outFilename, 255*edges);
-    @endcode
+
+    @snippet ximgproc/samples/structured_edge_detection.cpp imshow
 
 Literature
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