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

modules/rgbd/src/plane.cpp

@@ -555,8 +555,8 @@ private:
         plane = Ptr<PlaneBase>(new PlaneABC(plane_grid.m_(y, x), n, (int)index_plane,
 			(float)sensor_error_a_, (float)sensor_error_b_, (float)sensor_error_c_));
 
-      Mat_<unsigned char> plane_mask = Mat_<unsigned char>::zeros(points3d.rows / block_size_,
-                                                                          points3d.cols / block_size_);
+      Mat_<unsigned char> plane_mask = Mat_<unsigned char>::zeros(divUp(points3d.rows, block_size_),
+                                                                  divUp(points3d.cols, block_size_));
       std::set<TileQueue::PlaneTile> neighboring_tiles;
       neighboring_tiles.insert(front_tile);
       plane_queue.remove(front_tile.y_, front_tile.x_);

modules/rgbd/test/test_normal.cpp

@@ -441,4 +441,15 @@ TEST(Rgbd_Plane, compute)
   test.safe_run();
 }
 
+TEST(Rgbd_Plane, regression_2309_valgrind_check)
+{
+    Mat points(640, 480, CV_32FC3, Scalar::all(0));
+    rgbd::RgbdPlane plane_detector;
+    plane_detector.setBlockSize(9);  // Note, 640%9 is 1 and 480%9 is 3
+
+    Mat mask;
+    std::vector<cv::Vec4f> planes;
+    plane_detector(points, mask, planes);  // Will corrupt memory; valgrind gets triggered
+}
+
 }} // namespace

modules/text/src/text_detectorCNN.cpp

@@ -29,26 +29,29 @@ protected:
     {
         for(int k = 0; k < nbrTextBoxes; k++)
         {
-            float x_min = buffer[k*nCol + 3]*inputShape.width;
-            float y_min = buffer[k*nCol + 4]*inputShape.height;
+            float confidence_ = buffer[k*nCol + 2];
+            if (confidence_ <= FLT_EPSILON) continue;
 
-            float x_max = buffer[k*nCol + 5]*inputShape.width;
-            float y_max = buffer[k*nCol + 6]*inputShape.height;
+            float x_min_f = buffer[k*nCol + 3]*inputShape.width;
+            float y_min_f = buffer[k*nCol + 4]*inputShape.height;
 
-            CV_CheckLT(x_min, x_max, "");
-            CV_CheckLT(y_min, y_max, "");
+            float x_max_f = buffer[k*nCol + 5]*inputShape.width;
+            float y_max_f = buffer[k*nCol + 6]*inputShape.height;
 
-            x_min = std::max(0.f, x_min);
-            y_min = std::max(0.f, y_min);
+            int x_min = cvRound(std::max(0.f, x_min_f));
+            int y_min = cvRound(std::max(0.f, y_min_f));
 
-            x_max = std::min(inputShape.width - 1.f,  x_max);
-            y_max = std::min(inputShape.height - 1.f,  y_max);
+            int x_max = std::min(inputShape.width - 1,  cvRound(x_max_f));
+            int y_max = std::min(inputShape.height - 1,  cvRound(y_max_f));
 
-            int wd = cvRound(x_max - x_min);
-            int ht = cvRound(y_max - y_min);
+            if (x_min >= x_max) continue;
+            if (y_min >= y_max) continue;
 
-            Bbox.push_back(Rect(cvRound(x_min), cvRound(y_min), wd, ht));
-            confidence.push_back(buffer[k*nCol + 2]);
+            int wd = x_max - x_min;
+            int ht = y_max - y_min;
+
+            Bbox.push_back(Rect(x_min, y_min, wd, ht));
+            confidence.push_back(confidence_);
         }
     }
 

modules/xfeatures2d/src/sift.cpp

@@ -107,6 +107,8 @@
 #include <stdarg.h>
 #include <opencv2/core/hal/hal.hpp>
 
+#include <opencv2/core/utils/tls.hpp>
+
 namespace cv
 {
 namespace xfeatures2d
@@ -709,7 +711,7 @@ void SIFT_Impl::findScaleSpaceExtrema( const std::vector<Mat>& gauss_pyr, const
     const int threshold = cvFloor(0.5 * contrastThreshold / nOctaveLayers * 255 * SIFT_FIXPT_SCALE);
 
     keypoints.clear();
-    TLSData<std::vector<KeyPoint> > tls_kpts_struct;
+    TLSDataAccumulator<std::vector<KeyPoint> > tls_kpts_struct;
 
     for( int o = 0; o < nOctaves; o++ )
         for( int i = 1; i <= nOctaveLayers; i++ )