From: Alexander Alekhin <alexander.alekhin@itseez.com>
Date: Fri, 21 Feb 2014 13:58:33 +0000 (+0400)
Subject: stitching: allow to use dynamic DescriptorMatcher
X-Git-Tag: accepted/tizen/6.0/unified/20201030.111113~3303^2~4
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=e6cc1be7e8d6e9628b07f3d347dd32a36f0f7478;p=platform%2Fupstream%2Fopencv.git

stitching: allow to use dynamic DescriptorMatcher
---

diff --git a/modules/core/src/matrix.cpp b/modules/core/src/matrix.cpp
index 32ccd03..f7aded7 100644
--- a/modules/core/src/matrix.cpp
+++ b/modules/core/src/matrix.cpp
@@ -1369,6 +1369,21 @@ void _InputArray::getUMatVector(std::vector<UMat>& umv) const
         return;
     }
 
+    if( k == UMAT )
+    {
+        UMat& v = *(UMat*)obj;
+        umv.resize(1);
+        umv[0] = v;
+        return;
+    }
+    if( k == MAT )
+    {
+        Mat& v = *(Mat*)obj;
+        umv.resize(1);
+        umv[0] = v.getUMat(accessFlags);
+        return;
+    }
+
     CV_Error(Error::StsNotImplemented, "Unknown/unsupported array type");
 }
 
diff --git a/modules/features2d/src/matchers.cpp b/modules/features2d/src/matchers.cpp
index 91ee9d9..2b56050 100644
--- a/modules/features2d/src/matchers.cpp
+++ b/modules/features2d/src/matchers.cpp
@@ -330,7 +330,7 @@ static bool ocl_match2Dispatcher(InputArray query, InputArray train, const UMat
 static bool ocl_kmatchDispatcher(InputArray query, InputArray train, const UMat &trainIdx,
                                  const UMat &distance, int distType)
 {
-        return ocl_match2Dispatcher(query, train, trainIdx, distance, distType);
+    return ocl_match2Dispatcher(query, train, trainIdx, distance, distType);
 }
 
 static bool ocl_knnMatchSingle(InputArray query, InputArray train, UMat &trainIdx,
@@ -1209,8 +1209,8 @@ FlannBasedMatcher::FlannBasedMatcher( const Ptr<flann::IndexParams>& _indexParam
 void FlannBasedMatcher::add( InputArrayOfArrays _descriptors )
 {
     DescriptorMatcher::add( _descriptors );
-    std::vector<Mat> descriptors;
-    _descriptors.getMatVector(descriptors);
+    std::vector<UMat> descriptors;
+    _descriptors.getUMatVector(descriptors);
 
     for( size_t i = 0; i < descriptors.size(); i++ )
     {
diff --git a/modules/stitching/src/matchers.cpp b/modules/stitching/src/matchers.cpp
index ceb3d3d..c303c4a 100644
--- a/modules/stitching/src/matchers.cpp
+++ b/modules/stitching/src/matchers.cpp
@@ -155,21 +155,31 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
 
     matches_info.matches.clear();
 
-    Ptr<flann::IndexParams> indexParams = makePtr<flann::KDTreeIndexParams>();
-    Ptr<flann::SearchParams> searchParams = makePtr<flann::SearchParams>();
-
-    if (features2.descriptors.depth() == CV_8U)
+    Ptr<DescriptorMatcher> matcher;
+#if 0 // TODO check this
+    if (ocl::useOpenCL())
     {
-        indexParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
-        searchParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
+        matcher = makePtr<BFMatcher>((int)NORM_L2);
     }
+    else
+#endif
+    {
+        Ptr<flann::IndexParams> indexParams = makePtr<flann::KDTreeIndexParams>();
+        Ptr<flann::SearchParams> searchParams = makePtr<flann::SearchParams>();
 
-    FlannBasedMatcher matcher(indexParams, searchParams);
+        if (features2.descriptors.depth() == CV_8U)
+        {
+            indexParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
+            searchParams->setAlgorithm(cvflann::FLANN_INDEX_LSH);
+        }
+
+        matcher = makePtr<FlannBasedMatcher>(indexParams, searchParams);
+    }
     std::vector< std::vector<DMatch> > pair_matches;
     MatchesSet matches;
 
     // Find 1->2 matches
-    matcher.knnMatch(features1.descriptors, features2.descriptors, pair_matches, 2);
+    matcher->knnMatch(features1.descriptors, features2.descriptors, pair_matches, 2);
     for (size_t i = 0; i < pair_matches.size(); ++i)
     {
         if (pair_matches[i].size() < 2)
@@ -186,7 +196,7 @@ void CpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
 
     // Find 2->1 matches
     pair_matches.clear();
-    matcher.knnMatch(features2.descriptors, features1.descriptors, pair_matches, 2);
+    matcher->knnMatch(features2.descriptors, features1.descriptors, pair_matches, 2);
     for (size_t i = 0; i < pair_matches.size(); ++i)
     {
         if (pair_matches[i].size() < 2)