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

modules/features2d/src/blobdetector.cpp

@@ -257,7 +257,7 @@ void SimpleBlobDetectorImpl::findBlobs(InputArray _image, InputArray _binaryImag
         {
             std::vector < Point > hull;
             convexHull(contours[contourIdx], hull);
-            double area = contourArea(contours[contourIdx]);
+            double area = moms.m00;
             double hullArea = contourArea(hull);
             if (fabs(hullArea) < DBL_EPSILON)
                 continue;

modules/features2d/src/matchers.cpp

@@ -625,15 +625,20 @@ void DescriptorMatcher::checkMasks( InputArrayOfArrays _masks, int queryDescript
     if( isMaskSupported() && !masks.empty() )
     {
         // Check masks
-        size_t imageCount = std::max(trainDescCollection.size(), utrainDescCollection.size() );
+        const size_t imageCount = std::max(trainDescCollection.size(), utrainDescCollection.size() );
         CV_Assert( masks.size() == imageCount );
         for( size_t i = 0; i < imageCount; i++ )
         {
-            if( !masks[i].empty() && (!trainDescCollection[i].empty() || !utrainDescCollection[i].empty() ) )
+            if (masks[i].empty())
+                continue;
+            const bool hasTrainDesc = !trainDescCollection.empty() && !trainDescCollection[i].empty();
+            const bool hasUTrainDesc = !utrainDescCollection.empty() && !utrainDescCollection[i].empty();
+            if (hasTrainDesc || hasUTrainDesc)
             {
-                int rows = trainDescCollection[i].empty() ? utrainDescCollection[i].rows : trainDescCollection[i].rows;
-                    CV_Assert( masks[i].rows == queryDescriptorsCount &&
-                        masks[i].cols == rows && masks[i].type() == CV_8UC1);
+                const int rows = hasTrainDesc ? trainDescCollection[i].rows : utrainDescCollection[i].rows;
+                CV_Assert(masks[i].type() == CV_8UC1
+                    && masks[i].rows == queryDescriptorsCount
+                    && masks[i].cols == rows);
             }
         }
     }

modules/features2d/src/sift.simd.hpp

@@ -73,6 +73,7 @@
 
 #include <opencv2/core/hal/hal.hpp>
 #include "opencv2/core/hal/intrin.hpp"
+#include <opencv2/core/utils/buffer_area.private.hpp>
 
 namespace cv {
 
@@ -167,23 +168,17 @@ float calcOrientationHist(
     int i, j, k, len = (radius*2+1)*(radius*2+1);
 
     float expf_scale = -1.f/(2.f * sigma * sigma);
-#if CV_SIMD
-    AutoBuffer<float> bufX(len + v_float32::nlanes);
-    AutoBuffer<float> bufY(len + v_float32::nlanes);
-    AutoBuffer<float> bufO(len + v_float32::nlanes);
-    AutoBuffer<float> bufW(len + v_float32::nlanes);
-    AutoBuffer<float> bufT(n+4 + v_float32::nlanes);
-    float *X = alignPtr(bufX.data(), CV_SIMD_WIDTH);
-    float *Y = alignPtr(bufY.data(), CV_SIMD_WIDTH);
-    float *Mag = X;
-    float *Ori = alignPtr(bufO.data(), CV_SIMD_WIDTH);
-    float *W = alignPtr(bufW.data(), CV_SIMD_WIDTH);
-    float *temphist = alignPtr(bufT.data(), CV_SIMD_WIDTH)+2;
-#else
-    AutoBuffer<float> buf(len*4 + n+4);
-    float *X = buf.data(), *Y = X + len, *Mag = X, *Ori = Y + len, *W = Ori + len;
-    float* temphist = W + len + 2;
-#endif
+
+    cv::utils::BufferArea area;
+    float *X = 0, *Y = 0, *Mag, *Ori = 0, *W = 0, *temphist = 0;
+    area.allocate(X, len, CV_SIMD_WIDTH);
+    area.allocate(Y, len, CV_SIMD_WIDTH);
+    area.allocate(Ori, len, CV_SIMD_WIDTH);
+    area.allocate(W, len, CV_SIMD_WIDTH);
+    area.allocate(temphist, n+4, CV_SIMD_WIDTH);
+    area.commit();
+    temphist += 2;
+    Mag = X;
 
     for( i = 0; i < n; i++ )
         temphist[i] = 0.f;
@@ -656,7 +651,7 @@ void calcSIFTDescriptor(
             v_float32 v_rco011 = v_rc01*obin, v_rco010 = v_rc01 - v_rco011;
             v_float32 v_rco001 = v_rc00*obin, v_rco000 = v_rc00 - v_rco001;
 
-            v_int32 idx = v_fma(v_fma(r0+__1, __d_plus_2, c0+__1), __n_plus_2, o0);
+            v_int32 idx = v_muladd(v_muladd(r0+__1, __d_plus_2, c0+__1), __n_plus_2, o0);
             v_store_aligned(idx_buf, idx);
 
             v_store_aligned(rco_buf,           v_rco000);

modules/features2d/test/test_matchers_algorithmic.cpp

@@ -603,7 +603,6 @@ TEST(Features2d_DMatch, issue_11855)
                                         1, 1, 1);
     Mat targets = (Mat_<uchar>(2, 3) << 1, 1, 1,
                                         0, 0, 0);
-
     Ptr<BFMatcher> bf = BFMatcher::create(NORM_HAMMING, true);
     vector<vector<DMatch> > match;
     bf->knnMatch(sources, targets, match, 1, noArray(), true);
@@ -615,4 +614,18 @@ TEST(Features2d_DMatch, issue_11855)
     EXPECT_EQ(0.0f, match[0][0].distance);
 }
 
+TEST(Features2d_DMatch, issue_17771)
+{
+    Mat sources = (Mat_<uchar>(2, 3) << 1, 1, 0,
+                                        1, 1, 1);
+    Mat targets = (Mat_<uchar>(2, 3) << 1, 1, 1,
+                                        0, 0, 0);
+    UMat usources = sources.getUMat(ACCESS_READ);
+    UMat utargets = targets.getUMat(ACCESS_READ);
+    vector<vector<DMatch> > match;
+    Ptr<BFMatcher> ubf = BFMatcher::create(NORM_HAMMING);
+    Mat mask = (Mat_<uchar>(2, 2) << 1, 0, 0, 1);
+    EXPECT_NO_THROW(ubf->knnMatch(usources, utargets, match, 1, mask, true));
+}
+
 }} // namespace