Merge branch 4.x

modules/features/include/opencv2/features.hpp

@@ -563,7 +563,7 @@ public:
     CV_WRAP static Ptr<GFTTDetector> create( int maxCorners=1000, double qualityLevel=0.01, double minDistance=1,
                                              int blockSize=3, bool useHarrisDetector=false, double k=0.04 );
     CV_WRAP static Ptr<GFTTDetector> create( int maxCorners, double qualityLevel, double minDistance,
-                                             int blockSize, int gradiantSize, bool useHarrisDetector=false, double k=0.04 );
+                                             int blockSize, int gradientSize, bool useHarrisDetector=false, double k=0.04 );
     CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0;
     CV_WRAP virtual int getMaxFeatures() const = 0;
 
@@ -645,6 +645,11 @@ public:
       CV_PROP_RW bool filterByConvexity;
       CV_PROP_RW float minConvexity, maxConvexity;
 
+      /** @brief Flag to enable contour collection.
+      If set to true, the detector will store the contours of the detected blobs in memory,
+      which can be retrieved after the detect() call using getBlobContours().
+      @note Default value is false.
+      */
       CV_PROP_RW bool collectContours;
 
       void read( const FileNode& fn );
@@ -658,6 +663,11 @@ public:
   CV_WRAP virtual SimpleBlobDetector::Params getParams() const = 0;
 
   CV_WRAP virtual String getDefaultName() const CV_OVERRIDE;
+
+  /** @brief Returns the contours of the blobs detected during the last call to detect().
+  @note The @ref Params::collectContours parameter must be set to true before calling
+  detect() for this method to return any data.
+  */
   CV_WRAP virtual const std::vector<std::vector<cv::Point> >& getBlobContours() const = 0;
 };
 

modules/features/src/orb.cpp

@@ -1036,7 +1036,11 @@ void ORB_Impl::detectAndCompute( InputArray _image, InputArray _mask,
     bool useOCL = false;
 #endif
 
-    Mat image = _image.getMat(), mask = _mask.getMat();
+    Mat image = _image.getMat(), mask;
+    if (!_mask.empty())
+    {
+        threshold(_mask, mask, 0, 255, THRESH_BINARY);
+    }
     if( image.type() != CV_8UC1 )
         cvtColor(_image, image, COLOR_BGR2GRAY);
 
@@ -1134,7 +1138,7 @@ void ORB_Impl::detectAndCompute( InputArray _image, InputArray _mask,
             }
 
             copyMakeBorder(currImg, extImg, border, border, border, border,
-                           BORDER_REFLECT_101+BORDER_ISOLATED);
+                           BORDER_REFLECT_101 + BORDER_ISOLATED);
             if (!mask.empty())
                 copyMakeBorder(currMask, extMask, border, border, border, border,
                                BORDER_CONSTANT+BORDER_ISOLATED);

modules/features/test/test_orb.cpp

@@ -168,4 +168,31 @@ BIGDATA_TEST(Features2D_ORB, regression_opencv_python_537)  // memory usage: ~3
     ASSERT_NO_THROW(orbPtr->detectAndCompute(img, noArray(), kps, fv));
 }
 
+TEST(Features2D_ORB, MaskValue)
+{
+    Mat gray = imread(cvtest::findDataFile("features2d/tsukuba.png"), IMREAD_GRAYSCALE);
+    ASSERT_FALSE(gray.empty());
+
+    cv::Rect roi(gray.cols/4, gray.rows/4, gray.cols/2, gray.rows/2);
+
+    Mat mask255 = Mat::zeros(gray.size(), CV_8UC1);
+    Mat mask1 = Mat::zeros(gray.size(), CV_8UC1);
+    mask255(roi).setTo(255);
+    mask1(roi).setTo(1);
+
+    Ptr<ORB> orb = cv::ORB::create();
+
+    vector<KeyPoint> keypoints_mask255, keypoints_mask1;
+    Mat descriptors_mask255, descriptors_mask1;
+
+    orb->detectAndCompute(gray, mask255, keypoints_mask255, descriptors_mask255, false);
+    orb->detectAndCompute(gray, mask1, keypoints_mask1, descriptors_mask1, false);
+
+    ASSERT_EQ(keypoints_mask255.size(), keypoints_mask1.size())
+        << "Number of keypoints differs between mask values 255 and 1";
+
+    Mat diff = descriptors_mask255 != descriptors_mask1;
+    ASSERT_EQ(countNonZero(diff), 0);
+}
+
 }} // namespace