Merge remote-tracking branch 'upstream/master' into bow_desc

Conflicts:
	modules/features2d/src/bagofwords.cpp

modules/features2d/src/bagofwords.cpp

@@ -204,4 +204,14 @@ void BOWImgDescriptorExtractor::compute( const Mat& descriptors, Mat& imgDescrip
     imgDescriptor /= descriptors.rows;
 }
 
+int BOWImgDescriptorExtractor::descriptorSize() const
+{
+    return vocabulary.empty() ? 0 : vocabulary.rows;
+}
+
+int BOWImgDescriptorExtractor::descriptorType() const
+{
+    return CV_32FC1;
+}
+
 }

modules/features2d/src/brisk.cpp

@@ -2003,7 +2003,7 @@ BriskLayer::BriskLayer(const cv::Mat& img_in, float scale_in, float offset_in)
   scale_ = scale_in;
   offset_ = offset_in;
   // create an agast detector
-  fast_9_16_ = new FastFeatureDetector(1, true, FastFeatureDetector::TYPE_9_16);
+  fast_9_16_ = makePtr<FastFeatureDetector>(1, true, FastFeatureDetector::TYPE_9_16);
   makeOffsets(pixel_5_8_, (int)img_.step, 8);
   makeOffsets(pixel_9_16_, (int)img_.step, 16);
 }
@@ -2025,7 +2025,7 @@ BriskLayer::BriskLayer(const BriskLayer& layer, int mode)
     offset_ = 0.5f * scale_ - 0.5f;
   }
   scores_ = cv::Mat::zeros(img_.rows, img_.cols, CV_8U);
-  fast_9_16_ = new FastFeatureDetector(1, false, FastFeatureDetector::TYPE_9_16);
+  fast_9_16_ = makePtr<FastFeatureDetector>(1, false, FastFeatureDetector::TYPE_9_16);
   makeOffsets(pixel_5_8_, (int)img_.step, 8);
   makeOffsets(pixel_9_16_, (int)img_.step, 16);
 }

modules/features2d/src/descriptors.cpp

@@ -99,7 +99,7 @@ Ptr<DescriptorExtractor> DescriptorExtractor::create(const String& descriptorExt
     {
         size_t pos = String("Opponent").size();
         String type = descriptorExtractorType.substr(pos);
-        return new OpponentColorDescriptorExtractor(DescriptorExtractor::create(type));
+        return makePtr<OpponentColorDescriptorExtractor>(DescriptorExtractor::create(type));
     }
 
     return Algorithm::create<DescriptorExtractor>("Feature2D." + descriptorExtractorType);
@@ -119,7 +119,7 @@ CV_WRAP void Feature2D::compute( const Mat& image, CV_OUT CV_IN_OUT std::vector<
 OpponentColorDescriptorExtractor::OpponentColorDescriptorExtractor( const Ptr<DescriptorExtractor>& _descriptorExtractor ) :
         descriptorExtractor(_descriptorExtractor)
 {
-    CV_Assert( !descriptorExtractor.empty() );
+    CV_Assert( descriptorExtractor );
 }
 
 static void convertBGRImageToOpponentColorSpace( const Mat& bgrImage, std::vector<Mat>& opponentChannels )
@@ -249,7 +249,7 @@ int OpponentColorDescriptorExtractor::descriptorType() const
 
 bool OpponentColorDescriptorExtractor::empty() const
 {
-    return descriptorExtractor.empty() || (DescriptorExtractor*)(descriptorExtractor)->empty();
+    return !descriptorExtractor || descriptorExtractor->empty();
 }
 
 }

modules/features2d/src/detectors.cpp

@@ -90,19 +90,19 @@ Ptr<FeatureDetector> FeatureDetector::create( const String& detectorType )
 {
     if( detectorType.find("Grid") == 0 )
     {
-        return new GridAdaptedFeatureDetector(FeatureDetector::create(
+        return makePtr<GridAdaptedFeatureDetector>(FeatureDetector::create(
                                 detectorType.substr(strlen("Grid"))));
     }
 
     if( detectorType.find("Pyramid") == 0 )
     {
-        return new PyramidAdaptedFeatureDetector(FeatureDetector::create(
+        return makePtr<PyramidAdaptedFeatureDetector>(FeatureDetector::create(
                                 detectorType.substr(strlen("Pyramid"))));
     }
 
     if( detectorType.find("Dynamic") == 0 )
     {
-        return new DynamicAdaptedFeatureDetector(AdjusterAdapter::create(
+        return makePtr<DynamicAdaptedFeatureDetector>(AdjusterAdapter::create(
                                 detectorType.substr(strlen("Dynamic"))));
     }
 
@@ -190,7 +190,7 @@ GridAdaptedFeatureDetector::GridAdaptedFeatureDetector( const Ptr<FeatureDetecto
 
 bool GridAdaptedFeatureDetector::empty() const
 {
-    return detector.empty() || (FeatureDetector*)detector->empty();
+    return !detector || detector->empty();
 }
 
 struct ResponseComparator
@@ -295,7 +295,7 @@ PyramidAdaptedFeatureDetector::PyramidAdaptedFeatureDetector( const Ptr<FeatureD
 
 bool PyramidAdaptedFeatureDetector::empty() const
 {
-    return detector.empty() || (FeatureDetector*)detector->empty();
+    return !detector || detector->empty();
 }
 
 void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask ) const

modules/features2d/src/dynamic.cpp

@@ -51,7 +51,7 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector(const Ptr<AdjusterA
 
 bool DynamicAdaptedFeatureDetector::empty() const
 {
-    return adjuster_.empty() || adjuster_->empty();
+    return !adjuster_ || adjuster_->empty();
 }
 
 void DynamicAdaptedFeatureDetector::detectImpl(const Mat& image, std::vector<KeyPoint>& keypoints, const Mat& mask) const
@@ -124,7 +124,7 @@ bool FastAdjuster::good() const
 
 Ptr<AdjusterAdapter> FastAdjuster::clone() const
 {
-    Ptr<AdjusterAdapter> cloned_obj = new FastAdjuster( init_thresh_, nonmax_, min_thresh_, max_thresh_ );
+    Ptr<AdjusterAdapter> cloned_obj(new FastAdjuster( init_thresh_, nonmax_, min_thresh_, max_thresh_ ));
     return cloned_obj;
 }
 
@@ -158,7 +158,7 @@ bool StarAdjuster::good() const
 
 Ptr<AdjusterAdapter> StarAdjuster::clone() const
 {
-    Ptr<AdjusterAdapter> cloned_obj = new StarAdjuster( init_thresh_, min_thresh_, max_thresh_ );
+    Ptr<AdjusterAdapter> cloned_obj(new StarAdjuster( init_thresh_, min_thresh_, max_thresh_ ));
     return cloned_obj;
 }
 
@@ -195,7 +195,7 @@ bool SurfAdjuster::good() const
 
 Ptr<AdjusterAdapter> SurfAdjuster::clone() const
 {
-    Ptr<AdjusterAdapter> cloned_obj = new SurfAdjuster( init_thresh_, min_thresh_, max_thresh_ );
+    Ptr<AdjusterAdapter> cloned_obj(new SurfAdjuster( init_thresh_, min_thresh_, max_thresh_ ));
     return cloned_obj;
 }
 
@@ -205,15 +205,15 @@ Ptr<AdjusterAdapter> AdjusterAdapter::create( const String& detectorType )
 
     if( !detectorType.compare( "FAST" ) )
     {
-        adapter = new FastAdjuster();
+        adapter = makePtr<FastAdjuster>();
     }
     else if( !detectorType.compare( "STAR" ) )
     {
-        adapter = new StarAdjuster();
+        adapter = makePtr<StarAdjuster>();
     }
     else if( !detectorType.compare( "SURF" ) )
     {
-        adapter = new SurfAdjuster();
+        adapter = makePtr<SurfAdjuster>();
     }
 
     return adapter;

modules/features2d/src/evaluation.cpp

@@ -257,7 +257,7 @@ struct IntersectAreaCounter
     {
         CV_Assert( miny < maxy );
         CV_Assert( dr > FLT_EPSILON );
-        
+
         int temp_bua = bua, temp_bna = bna;
         for( int i = range.begin(); i != range.end(); i++ )
         {
@@ -461,7 +461,7 @@ void cv::evaluateFeatureDetector( const Mat& img1, const Mat& img2, const Mat& H
     keypoints1 = _keypoints1 != 0 ? _keypoints1 : &buf1;
     keypoints2 = _keypoints2 != 0 ? _keypoints2 : &buf2;
 
-    if( (keypoints1->empty() || keypoints2->empty()) && fdetector.empty() )
+    if( (keypoints1->empty() || keypoints2->empty()) && !fdetector )
         CV_Error( Error::StsBadArg, "fdetector must not be empty when keypoints1 or keypoints2 is empty" );
 
     if( keypoints1->empty() )
@@ -575,7 +575,7 @@ void cv::evaluateGenericDescriptorMatcher( const Mat& img1, const Mat& img2, con
     if( keypoints1.empty() )
         CV_Error( Error::StsBadArg, "keypoints1 must not be empty" );
 
-    if( matches1to2->empty() && dmatcher.empty() )
+    if( matches1to2->empty() && !dmatcher )
         CV_Error( Error::StsBadArg, "dmatch must not be empty when matches1to2 is empty" );
 
     bool computeKeypoints2ByPrj = keypoints2.empty();

modules/features2d/src/fast_score.cpp

@@ -357,4 +357,3 @@ int cornerScore<8>(const uchar* ptr, const int pixel[], int threshold)
 }
 
 } // namespace cv
-

modules/features2d/src/features2d_init.cpp

@@ -176,7 +176,7 @@ CV_INIT_ALGORITHM(DenseFeatureDetector, "Feature2D.Dense",
                   obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale));
 
 CV_INIT_ALGORITHM(GridAdaptedFeatureDetector, "Feature2D.Grid",
-                  obj.info()->addParam(obj, "detector", obj.detector);
+                  obj.info()->addParam<FeatureDetector>(obj, "detector", obj.detector, false, 0, 0); // Extra params added to avoid VS2013 fatal error in opencv2/core.hpp (decl. of addParam)
                   obj.info()->addParam(obj, "maxTotalKeypoints", obj.maxTotalKeypoints);
                   obj.info()->addParam(obj, "gridRows", obj.gridRows);
                   obj.info()->addParam(obj, "gridCols", obj.gridCols));

modules/features2d/src/matchers.cpp

@@ -326,7 +326,7 @@ BFMatcher::BFMatcher( int _normType, bool _crossCheck )
 
 Ptr<DescriptorMatcher> BFMatcher::clone( bool emptyTrainData ) const
 {
-    BFMatcher* matcher = new BFMatcher(normType, crossCheck);
+    Ptr<BFMatcher> matcher = makePtr<BFMatcher>(normType, crossCheck);
     if( !emptyTrainData )
     {
         matcher->trainDescCollection.resize(trainDescCollection.size());
@@ -458,31 +458,31 @@ void BFMatcher::radiusMatchImpl( const Mat& queryDescriptors, std::vector<std::v
  */
 Ptr<DescriptorMatcher> DescriptorMatcher::create( const String& descriptorMatcherType )
 {
-    DescriptorMatcher* dm = 0;
+    Ptr<DescriptorMatcher> dm;
     if( !descriptorMatcherType.compare( "FlannBased" ) )
     {
-        dm = new FlannBasedMatcher();
+        dm = makePtr<FlannBasedMatcher>();
     }
     else if( !descriptorMatcherType.compare( "BruteForce" ) ) // L2
     {
-        dm = new BFMatcher(NORM_L2);
+        dm = makePtr<BFMatcher>(int(NORM_L2)); // anonymous enums can't be template parameters
     }
     else if( !descriptorMatcherType.compare( "BruteForce-SL2" ) ) // Squared L2
     {
-        dm = new BFMatcher(NORM_L2SQR);
+        dm = makePtr<BFMatcher>(int(NORM_L2SQR));
     }
     else if( !descriptorMatcherType.compare( "BruteForce-L1" ) )
     {
-        dm = new BFMatcher(NORM_L1);
+        dm = makePtr<BFMatcher>(int(NORM_L1));
     }
     else if( !descriptorMatcherType.compare("BruteForce-Hamming") ||
              !descriptorMatcherType.compare("BruteForce-HammingLUT") )
     {
-        dm = new BFMatcher(NORM_HAMMING);
+        dm = makePtr<BFMatcher>(int(NORM_HAMMING));
     }
     else if( !descriptorMatcherType.compare("BruteForce-Hamming(2)") )
     {
-        dm = new BFMatcher(NORM_HAMMING2);
+        dm = makePtr<BFMatcher>(int(NORM_HAMMING2));
     }
     else
         CV_Error( Error::StsBadArg, "Unknown matcher name" );
@@ -497,8 +497,8 @@ Ptr<DescriptorMatcher> DescriptorMatcher::create( const String& descriptorMatche
 FlannBasedMatcher::FlannBasedMatcher( const Ptr<flann::IndexParams>& _indexParams, const Ptr<flann::SearchParams>& _searchParams )
     : indexParams(_indexParams), searchParams(_searchParams), addedDescCount(0)
 {
-    CV_Assert( !_indexParams.empty() );
-    CV_Assert( !_searchParams.empty() );
+    CV_Assert( _indexParams );
+    CV_Assert( _searchParams );
 }
 
 void FlannBasedMatcher::add( const std::vector<Mat>& descriptors )
@@ -522,17 +522,17 @@ void FlannBasedMatcher::clear()
 
 void FlannBasedMatcher::train()
 {
-    if( flannIndex.empty() || mergedDescriptors.size() < addedDescCount )
+    if( !flannIndex || mergedDescriptors.size() < addedDescCount )
     {
         mergedDescriptors.set( trainDescCollection );
-        flannIndex = new flann::Index( mergedDescriptors.getDescriptors(), *indexParams );
+        flannIndex = makePtr<flann::Index>( mergedDescriptors.getDescriptors(), *indexParams );
     }
 }
 
 void FlannBasedMatcher::read( const FileNode& fn)
 {
-     if (indexParams.empty())
-         indexParams = new flann::IndexParams();
+     if (!indexParams)
+         indexParams = makePtr<flann::IndexParams>();
 
      FileNode ip = fn["indexParams"];
      CV_Assert(ip.type() == FileNode::SEQ);
@@ -570,8 +570,8 @@ void FlannBasedMatcher::read( const FileNode& fn)
         };
      }
 
-     if (searchParams.empty())
-         searchParams = new flann::SearchParams();
+     if (!searchParams)
+         searchParams = makePtr<flann::SearchParams>();
 
      FileNode sp = fn["searchParams"];
      CV_Assert(sp.type() == FileNode::SEQ);
@@ -725,7 +725,7 @@ bool FlannBasedMatcher::isMaskSupported() const
 
 Ptr<DescriptorMatcher> FlannBasedMatcher::clone( bool emptyTrainData ) const
 {
-    FlannBasedMatcher* matcher = new FlannBasedMatcher(indexParams, searchParams);
+    Ptr<FlannBasedMatcher> matcher = makePtr<FlannBasedMatcher>(indexParams, searchParams);
     if( !emptyTrainData )
     {
         CV_Error( Error::StsNotImplemented, "deep clone functionality is not implemented, because "
@@ -1066,7 +1066,7 @@ Ptr<GenericDescriptorMatcher> GenericDescriptorMatcher::create( const String& ge
     Ptr<GenericDescriptorMatcher> descriptorMatcher =
         Algorithm::create<GenericDescriptorMatcher>("DescriptorMatcher." + genericDescritptorMatcherType);
 
-    if( !paramsFilename.empty() && !descriptorMatcher.empty() )
+    if( !paramsFilename.empty() && descriptorMatcher )
     {
         FileStorage fs = FileStorage( paramsFilename, FileStorage::READ );
         if( fs.isOpened() )
@@ -1086,7 +1086,7 @@ VectorDescriptorMatcher::VectorDescriptorMatcher( const Ptr<DescriptorExtractor>
                                                   const Ptr<DescriptorMatcher>& _matcher )
                                 : extractor( _extractor ), matcher( _matcher )
 {
-    CV_Assert( !extractor.empty() && !matcher.empty() );
+    CV_Assert( extractor && matcher );
 }
 
 VectorDescriptorMatcher::~VectorDescriptorMatcher()
@@ -1152,14 +1152,14 @@ void VectorDescriptorMatcher::write (FileStorage& fs) const
 
 bool VectorDescriptorMatcher::empty() const
 {
-    return extractor.empty() || extractor->empty() ||
-           matcher.empty() || matcher->empty();
+    return !extractor || extractor->empty() ||
+           !matcher || matcher->empty();
 }
 
 Ptr<GenericDescriptorMatcher> VectorDescriptorMatcher::clone( bool emptyTrainData ) const
 {
     // TODO clone extractor
-    return new VectorDescriptorMatcher( extractor, matcher->clone(emptyTrainData) );
+    return makePtr<VectorDescriptorMatcher>( extractor, matcher->clone(emptyTrainData) );
 }
 
 }

modules/features2d/src/orb.cpp

@@ -138,13 +138,16 @@ static void computeOrbDescriptor(const KeyPoint& kpt,
     const uchar* center = &img.at<uchar>(cvRound(kpt.pt.y), cvRound(kpt.pt.x));
     int step = (int)img.step;
 
-#if 1
-    #define GET_VALUE(idx) \
-        center[cvRound(pattern[idx].x*b + pattern[idx].y*a)*step + \
-               cvRound(pattern[idx].x*a - pattern[idx].y*b)]
-#else
     float x, y;
     int ix, iy;
+#if 1
+#define GET_VALUE(idx) \
+       (x = pattern[idx].x*a - pattern[idx].y*b, \
+        y = pattern[idx].x*b + pattern[idx].y*a, \
+        ix = cvRound(x), \
+        iy = cvRound(y), \
+        *(center + iy*step + ix) )
+#else
     #define GET_VALUE(idx) \
         (x = pattern[idx].x*a - pattern[idx].y*b, \
         y = pattern[idx].x*b + pattern[idx].y*a, \

modules/features2d/src/precomp.cpp

@@ -1,44 +0,0 @@
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                        Intel License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of Intel Corporation may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-#include "precomp.hpp"
-
-/* End of file. */