Added L1 distance code and used factory functions in evaluation framework

modules/features2d/include/opencv2/features2d/features2d.hpp

@@ -1507,6 +1507,27 @@ struct CV_EXPORTS L2
     }
 };
 
+/*
+ * Manhattan distance (city block distance) functor
+ */
+template<class T>
+struct CV_EXPORTS L1
+{
+    typedef T ValueType;
+    typedef typename Accumulator<T>::Type ResultType;
+
+    ResultType operator()( const T* a, const T* b, int size ) const
+    {
+        ResultType result = ResultType();
+        for( int i = 0; i < size; i++ )
+        {
+            ResultType diff = a[i] - b[i];
+            result += fabs( diff );
+        }
+        return result;
+    }
+};
+
 
 /****************************************************************************************\
 *                                  DMatch                                     *
@@ -1755,6 +1776,7 @@ void BruteForceMatcher<Distance>::matchImpl( const Mat& descriptors_1, const Mat
 {
     vector<DMatch> matchings;
     matchImpl( descriptors_1, descriptors_2, mask, matchings);
+    matches.clear();
     matches.resize( matchings.size() );
     for( size_t i=0;i<matchings.size();i++)
     {
@@ -1776,6 +1798,7 @@ void BruteForceMatcher<Distance>::matchImpl( const Mat& descriptors_1, const Mat
     assert( DataType<ValueType>::type == descriptors_2.type() ||  descriptors_2.empty() );
 
     int dimension = descriptors_1.cols;
+    matches.clear();
     matches.resize(descriptors_1.rows);
 
     for( int i = 0; i < descriptors_1.rows; i++ )
@@ -1823,6 +1846,7 @@ void BruteForceMatcher<Distance>::matchImpl( const Mat& descriptors_1, const Mat
     assert( DataType<ValueType>::type == descriptors_2.type() ||  descriptors_2.empty() );
 
     int dimension = descriptors_1.cols;
+    matches.clear();
     matches.resize( descriptors_1.rows );
 
     for( int i = 0; i < descriptors_1.rows; i++ )
@@ -1930,8 +1954,6 @@ public:
     
     // Writes match object to a file storage
     virtual void write( FileStorage& fs ) const {};
-    
-    static GenericDescriptorMatch* CreateDescriptorMatch( const string &alg_name, const string &params_filename = string () );
 
 protected:
     KeyPointCollection collection;
@@ -1998,6 +2020,8 @@ public:
 
     virtual void match( const Mat& image, vector<KeyPoint>& points, vector<DMatch>& matches );
 
+    virtual void match( const Mat& image, vector<KeyPoint>& points, vector<vector<DMatch> >& matches, float threshold);
+
     // Classify a set of keypoints. The same as match, but returns point classes rather than indices
     virtual void classify( const Mat& image, vector<KeyPoint>& points );
 
@@ -2146,6 +2170,7 @@ protected:
     Params params;
 };
 
+GenericDescriptorMatch* createDescriptorMatch( const string& genericDescritptorMatchType, const string &paramsFilename = string () );
 /****************************************************************************************\
 *                                VectorDescriptorMatch                                   *
 \****************************************************************************************/
@@ -2159,7 +2184,7 @@ class CV_EXPORTS VectorDescriptorMatch : public GenericDescriptorMatch
 public:
     using GenericDescriptorMatch::add;
 
-    VectorDescriptorMatch( const Extractor& _extractor = Extractor(), const Matcher& _matcher = Matcher() ) :
+    VectorDescriptorMatch( Extractor *_extractor = 0, Matcher * _matcher = 0 ) :
                            extractor(_extractor), matcher(_matcher) {}
 
     ~VectorDescriptorMatch() {}
@@ -2171,8 +2196,8 @@ public:
     virtual void add( const Mat& image, vector<KeyPoint>& keypoints )
     {
         Mat descriptors;
-        extractor.compute( image, keypoints, descriptors );
-        matcher.add( descriptors );
+        extractor->compute( image, keypoints, descriptors );
+        matcher->add( descriptors );
 
         collection.add( Mat(), keypoints );
     };
@@ -2181,47 +2206,47 @@ public:
     virtual void match( const Mat& image, vector<KeyPoint>& points, vector<int>& keypointIndices )
     {
         Mat descriptors;
-        extractor.compute( image, points, descriptors );
+        extractor->compute( image, points, descriptors );
 
-        matcher.match( descriptors, keypointIndices );
+        matcher->match( descriptors, keypointIndices );
     };
 
     virtual void match( const Mat& image, vector<KeyPoint>& points, vector<DMatch>& matches )
     {
         Mat descriptors;
-        extractor.compute( image, points, descriptors );
+        extractor->compute( image, points, descriptors );
 
-        matcher.match( descriptors, matches );
+        matcher->match( descriptors, matches );
     }
 
     virtual void match( const Mat& image, vector<KeyPoint>& points, vector<vector<DMatch> >& matches, float threshold )
     {
         Mat descriptors;
-        extractor.compute( image, points, descriptors );
+        extractor->compute( image, points, descriptors );
 
-        matcher.match( descriptors, matches, threshold );
+        matcher->match( descriptors, matches, threshold );
     }
 
     virtual void clear()
     {
         GenericDescriptorMatch::clear();
-        matcher.clear();
+        matcher->clear();
     }
 
     virtual void read (const FileNode& fn)
     {
         GenericDescriptorMatch::read(fn);
-        extractor.read (fn);
+        extractor->read (fn);
     }
 
     virtual void write (FileStorage& fs) const
     {
         GenericDescriptorMatch::write(fs);
-        extractor.write (fs);
+        extractor->write (fs);
     }
 protected:
-    Extractor extractor;
-    Matcher matcher;
+    Ptr<Extractor> extractor;
+    Ptr<Matcher> matcher;
     //vector<int> classIds;
 };
 

modules/features2d/src/descriptors.cpp

@@ -40,6 +40,7 @@
 //M*/
 
 #include "precomp.hpp"
+#include <stdio.h>
 
 //#define _KDTREE
 
@@ -254,6 +255,10 @@ DescriptorMatcher* createDescriptorMatcher( const string& descriptorMatcherType
     {
         dm = new BruteForceMatcher<L2<float> >();
     }
+    else if ( !descriptorMatcherType.compare( "BruteForce-L1" ) )
+    {
+        dm = new BruteForceMatcher<L1<float> >();
+    }
     else
     {
         //CV_Error( CV_StsBadArg, "unsupported descriptor matcher type");
@@ -330,27 +335,27 @@ void GenericDescriptorMatch::clear()
     collection.clear();
 }
 
-GenericDescriptorMatch* GenericDescriptorMatch::CreateDescriptorMatch( const string &alg_name, const string &params_filename )
+GenericDescriptorMatch* createDescriptorMatch( const string& genericDescritptorMatchType, const string &paramsFilename )
 {
     GenericDescriptorMatch *descriptorMatch = 0;
-    if( ! alg_name.compare ("one_way") )
+    if( ! genericDescritptorMatchType.compare ("ONEWAY") )
     {
         descriptorMatch = new OneWayDescriptorMatch ();
     }
-    else if( ! alg_name.compare ("fern") )
+    else if( ! genericDescritptorMatchType.compare ("FERN") )
     {
         FernDescriptorMatch::Params params;
-        params.signatureSize = INT_MAX;
+        params.signatureSize = numeric_limits<int>::max();
         descriptorMatch = new FernDescriptorMatch (params);
     }
-    else if( ! alg_name.compare ("calonder") )
+    else if( ! genericDescritptorMatchType.compare ("CALONDER") )
     {
         descriptorMatch = new CalonderDescriptorMatch ();
     }
 
-    if( !params_filename.empty() && descriptorMatch != 0 )
+    if( !paramsFilename.empty() && descriptorMatch != 0 )
     {
-        FileStorage fs = FileStorage( params_filename, FileStorage::READ );
+        FileStorage fs = FileStorage( paramsFilename, FileStorage::READ );
         if( fs.isOpened() )
         {
             descriptorMatch->read( fs.root() );
@@ -460,6 +465,76 @@ void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, v
     }
 }
 
+void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, vector<vector<DMatch> >& matches, float threshold )
+{
+    matches.clear();
+    matches.resize( points.size() );
+    IplImage _image = image;
+
+
+    vector<DMatch> dmatches;
+    match( image, points, dmatches );
+    for( size_t i=0;i<matches.size();i++ )
+    {
+        matches[i].push_back( dmatches[i] );
+    }
+
+
+    /*
+    printf("Start matching %d points\n", points.size());
+    //std::cout << "Start matching " << points.size() << "points\n";
+    assert(collection.images.size() == 1);
+    int n = collection.points[0].size();
+
+    printf("n = %d\n", n);
+    for( size_t i = 0; i < points.size(); i++ )
+    {
+        //printf("Matching %d\n", i);
+        //int poseIdx = -1;
+
+        DMatch match;
+        match.indexQuery = i;
+        match.indexTrain = -1;
+
+
+        CvPoint pt = points[i].pt;
+        CvRect roi = cvRect(cvRound(pt.x - 24/4),
+                            cvRound(pt.y - 24/4),
+                            24/2, 24/2);
+        cvSetImageROI(&_image, roi);
+
+        std::vector<int> desc_idxs;
+        std::vector<int> pose_idxs;
+        std::vector<float> distances;
+        std::vector<float> _scales;
+
+
+        base->FindDescriptor(&_image, n, desc_idxs, pose_idxs, distances, _scales);
+        cvResetImageROI(&_image);
+
+        for( int j=0;j<n;j++ )
+        {
+            match.indexTrain = desc_idxs[j];
+            match.distance = distances[j];
+            matches[i].push_back( match );
+        }
+
+        //sort( matches[i].begin(), matches[i].end(), compareIndexTrain );
+        //for( int j=0;j<n;j++ )
+        //{
+            //printf( "%d %f;  ",matches[i][j].indexTrain, matches[i][j].distance);
+        //}
+        //printf("\n\n\n");
+
+
+
+        //base->FindDescriptor( &_image, 100, points[i].pt, match.indexTrain, poseIdx, match.distance );
+        //matches[i].push_back( match );
+    }
+    */
+}
+
+
 void OneWayDescriptorMatch::read( const FileNode &fn )
 {
     base = new OneWayDescriptorObject( params.patchSize, params.poseCount, string (), string (), string (),

modules/features2d/src/detectors.cpp

@@ -344,6 +344,11 @@ FeatureDetector* createDetector( const string& detectorType )
                 5/*edge_blur_size*/ );
     }
     else if( !detectorType.compare( "GFTT" ) )
+    {
+        fd = new GoodFeaturesToTrackDetector( 1000/*maxCorners*/, 0.01/*qualityLevel*/, 1./*minDistance*/,
+                                              3/*int _blockSize*/, false/*useHarrisDetector*/, 0.04/*k*/ );
+    }
+    else if( !detectorType.compare( "HARRIS" ) )
     {
         fd = new GoodFeaturesToTrackDetector( 1000/*maxCorners*/, 0.01/*qualityLevel*/, 1./*minDistance*/,
                                               3/*int _blockSize*/, true/*useHarrisDetector*/, 0.04/*k*/ );