added empty() method to common features2d classes; fixed #831

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

@@ -523,6 +523,7 @@ public:
     virtual int operator()(const Mat& img, Point2f kpt, vector<float>& signature) const;
     virtual int operator()(const Mat& patch, vector<float>& signature) const;
     virtual void clear();
+    virtual bool empty() const;
     void setVerbose(bool verbose);
     
     int getClassCount() const;
@@ -1086,6 +1087,8 @@ public:
     // GetPCAFilename: get default PCA filename
     static string GetPCAFilename () { return "pca.yml"; }
 
+    virtual bool empty() const { return m_train_feature_count <= 0 ? true : false; }
+
 protected:
     CvSize m_patch_size; // patch size
     int m_pose_count; // the number of poses for each descriptor
@@ -1212,6 +1215,9 @@ public:
     // Read detector object from a file node.
     virtual void write( FileStorage& ) const;
 
+    // Return true if detector object is empty
+    virtual bool empty() const;
+
     // Create feature detector by detector name.
     static Ptr<FeatureDetector> create( const string& detectorType );
 
@@ -1359,18 +1365,19 @@ public:
   };
 
   SimpleBlobDetector(const SimpleBlobDetector::Params &parameters = SimpleBlobDetector::Params());
+
 protected:
   struct CV_EXPORTS Center
   {
-    cv::Point2d location;
+      Point2d location;
-    double radius;
+      double radius;
-    double confidence;
+      double confidence;
   };
 
   virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
   virtual void findBlobs(const cv::Mat &image, const cv::Mat &binaryImage, std::vector<Center> &centers) const;
 
-  cv::Point2d computeGrayscaleCentroid(const cv::Mat &image, const std::vector<cv::Point> &contour) const;
+  Point2d computeGrayscaleCentroid(const cv::Mat &image, const std::vector<cv::Point> &contour) const;
 
   Params params;
 };
@@ -1422,6 +1429,7 @@ public:
                                 int gridRows=4, int gridCols=4 );
     
     // TODO implement read/write
+    virtual bool empty() const;
 
 protected:
 	virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
@@ -1442,6 +1450,7 @@ public:
     PyramidAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector, int levels=2 );
     
     // TODO implement read/write
+    virtual bool empty() const;
 
 protected:
 	virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
@@ -1500,6 +1509,8 @@ public:
 	 */
     DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjaster, int min_features=400, int max_features=500, int max_iters=5 );
 
+    virtual bool empty() const;
+
 protected:
     virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
 
@@ -1607,6 +1618,8 @@ public:
     virtual int descriptorSize() const = 0;
     virtual int descriptorType() const = 0;
 
+    virtual bool empty() const;
+
     static Ptr<DescriptorExtractor> create( const string& descriptorExtractorType );
 
 protected:
@@ -1680,6 +1693,8 @@ public:
     virtual int descriptorSize() const { return classifier_.classes(); }
     virtual int descriptorType() const { return DataType<T>::type; }
 
+    virtual bool empty() const;
+
 protected:
 	virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
 
@@ -1722,6 +1737,12 @@ template<typename T>
 void CalonderDescriptorExtractor<T>::write( FileStorage& ) const
 {}
 
+template<typename T>
+bool CalonderDescriptorExtractor<T>::empty() const
+{
+    return classifier_.trees_.empty();
+}
+
 /*
  * OpponentColorDescriptorExtractor
  *
@@ -1742,6 +1763,8 @@ public:
     virtual int descriptorSize() const;
     virtual int descriptorType() const;
 
+    virtual bool empty() const;
+
 protected:
 	virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
 
@@ -1766,7 +1789,7 @@ public:
     /// @todo read and write for brief
 
 protected:
-	virtual void computeImpl(const Mat& image, std::vector<KeyPoint>& keypoints, Mat& descriptors) const;
+    virtual void computeImpl(const Mat& image, std::vector<KeyPoint>& keypoints, Mat& descriptors) const;
 
     typedef void(*PixelTestFn)(const Mat&, const std::vector<KeyPoint>&, Mat&);
 
@@ -1924,7 +1947,7 @@ public:
     /*
      * Return true if there are not train descriptors in collection.
      */
-	bool empty() const;
+    virtual bool empty() const;
     /*
      * Return true if the matcher supports mask in match methods.
      */
@@ -2366,6 +2389,9 @@ public:
     // Writes matcher object to a file storage
     virtual void write( FileStorage& ) const;
 
+    // Return true if matching object is empty (e.g. feature detector or descriptor matcher are empty)
+    virtual bool empty() const;
+
     // Clone the matcher. If emptyTrainData is false the method create deep copy of the object, i.e. copies
     // both parameters and train data. If emptyTrainData is true the method create object copy with current parameters
     // but with empty train data.
@@ -2473,6 +2499,8 @@ public:
     virtual void read( const FileNode &fn );
     virtual void write( FileStorage& fs ) const;
 
+    virtual bool empty() const;
+
     virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
 
 protected:
@@ -2540,6 +2568,7 @@ public:
 
     virtual void read( const FileNode &fn );
     virtual void write( FileStorage& fs ) const;
+    virtual bool empty() const;
     
     virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
 
@@ -2586,6 +2615,7 @@ public:
 
     virtual void read( const FileNode& fn );
     virtual void write( FileStorage& fs ) const;
+    virtual bool empty() const;
 
     virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
 

modules/features2d/src/calonder.cpp

@@ -860,8 +860,11 @@ int RTreeClassifier::countNonZeroElements(float *vec, int n, double tol)
 void RTreeClassifier::read(const char* file_name)
 {
   std::ifstream file(file_name, std::ifstream::binary);
-  read(file);
+  if( file.is_open() )
-  file.close();
+  {
+      read(file);
+      file.close();
+  }
 }
 
 void RTreeClassifier::read(std::istream &is)

modules/features2d/src/descriptors.cpp

@@ -96,6 +96,11 @@ void DescriptorExtractor::read( const FileNode& )
 void DescriptorExtractor::write( FileStorage& ) const
 {}
 
+bool DescriptorExtractor::empty() const
+{
+    return false;
+}
+
 void DescriptorExtractor::removeBorderKeypoints( vector<KeyPoint>& keypoints,
                                                  Size imageSize, int borderSize )
 {
@@ -361,4 +366,9 @@ int OpponentColorDescriptorExtractor::descriptorType() const
     return descriptorExtractor->descriptorType();
 }
 
+bool OpponentColorDescriptorExtractor::empty() const
+{
+    return descriptorExtractor.empty() || (DescriptorExtractor*)(descriptorExtractor)->empty();
+}
+
 }

modules/features2d/src/detectors.cpp

@@ -96,6 +96,11 @@ void FeatureDetector::read( const FileNode& )
 void FeatureDetector::write( FileStorage& ) const
 {}
 
+bool FeatureDetector::empty() const
+{
+    return false;
+}
+
 Ptr<FeatureDetector> FeatureDetector::create( const string& detectorType )
 {
     FeatureDetector* fd = 0;
@@ -488,6 +493,11 @@ GridAdaptedFeatureDetector::GridAdaptedFeatureDetector( const Ptr<FeatureDetecto
     : detector(_detector), maxTotalKeypoints(_maxTotalKeypoints), gridRows(_gridRows), gridCols(_gridCols)
 {}
 
+bool GridAdaptedFeatureDetector::empty() const
+{
+    return detector.empty() || (FeatureDetector*)detector->empty();
+}
+
 struct ResponseComparator
 {
     bool operator() (const KeyPoint& a, const KeyPoint& b)
@@ -544,6 +554,11 @@ PyramidAdaptedFeatureDetector::PyramidAdaptedFeatureDetector( const Ptr<FeatureD
     : detector(_detector), levels(_levels)
 {}
 
+bool PyramidAdaptedFeatureDetector::empty() const
+{
+    return detector.empty() || (FeatureDetector*)detector->empty();
+}
+
 void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
 {
     Mat src = image;

modules/features2d/src/matchers.cpp

@@ -213,7 +213,7 @@ void DescriptorMatcher::clear()
 
 bool DescriptorMatcher::empty() const
 {
-	return trainDescCollection.size() == 0;
+    return trainDescCollection.empty();
 }
 
 void DescriptorMatcher::train()
@@ -848,6 +848,11 @@ void GenericDescriptorMatcher::read( const FileNode& )
 void GenericDescriptorMatcher::write( FileStorage& ) const
 {}
 
+bool GenericDescriptorMatcher::empty() const
+{
+    return true;
+}
+
 /*
  * Factory function for GenericDescriptorMatch creating
  */
@@ -994,13 +999,18 @@ void OneWayDescriptorMatcher::write( FileStorage& fs ) const
     base->Write (fs);
 }
 
+bool OneWayDescriptorMatcher::empty() const
+{
+    return base.empty() || base->empty();
+}
+
 Ptr<GenericDescriptorMatcher> OneWayDescriptorMatcher::clone( bool emptyTrainData ) const
 {
     OneWayDescriptorMatcher* matcher = new OneWayDescriptorMatcher( params );
 
     if( !emptyTrainData )
     {
-        CV_Error( CV_StsNotImplemented, "deep clone dunctionality is not implemented, because "
+        CV_Error( CV_StsNotImplemented, "deep clone functionality is not implemented, because "
               "OneWayDescriptorBase has not copy constructor or clone method ");
 
         //matcher->base;
@@ -1175,6 +1185,11 @@ void FernDescriptorMatcher::write( FileStorage& fs ) const
 //    classifier->write(fs);
 }
 
+bool FernDescriptorMatcher::empty() const
+{
+    return classifier.empty() || classifier->empty();
+}
+
 Ptr<GenericDescriptorMatcher> FernDescriptorMatcher::clone( bool emptyTrainData ) const
 {
     FernDescriptorMatcher* matcher = new FernDescriptorMatcher( params );
@@ -1262,6 +1277,12 @@ void VectorDescriptorMatcher::write (FileStorage& fs) const
     extractor->write (fs);
 }
 
+bool VectorDescriptorMatcher::empty() const
+{
+    return extractor.empty() || extractor->empty() ||
+           matcher.empty() || matcher->empty();
+}
+
 Ptr<GenericDescriptorMatcher> VectorDescriptorMatcher::clone( bool emptyTrainData ) const
 {
     // TODO clone extractor

modules/features2d/src/planardetect.cpp

@@ -771,6 +771,10 @@ void FernClassifier::clear()
     vector<float>().swap(posteriors);
 }
 
+bool FernClassifier::empty() const
+{
+    return features.empty();
+}
 
 int FernClassifier::getLeaf(int fern, const Mat& _patch) const
 {

tests/cv/src/afeatures2d.cpp

@@ -73,6 +73,8 @@ protected:
 
 void CV_FeatureDetectorTest::emptyDataTest()
 {
+    assert( !fdetector.empty() && !fdetector->empty() );
+
     // One image.
     Mat image;
     vector<KeyPoint> keypoints;
@@ -172,7 +174,7 @@ void CV_FeatureDetectorTest::compareKeypointSets( const vector<KeyPoint>& validK
 
 void CV_FeatureDetectorTest::regressionTest()
 {
-    assert( !fdetector.empty() );
+    assert( !fdetector.empty() && !fdetector->empty() );
     string imgFilename = string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
     string resFilename = string(ts->get_data_path()) + DETECTOR_DIR + "/" + string(name) + ".xml.gz";
 
@@ -229,7 +231,7 @@ void CV_FeatureDetectorTest::regressionTest()
 
 void CV_FeatureDetectorTest::run( int /*start_from*/ )
 {
-    if( fdetector.empty() )
+    if( fdetector.empty() || fdetector->empty() )
     {
         ts->printf( CvTS::LOG, "Feature detector is empty.\n" );
         ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
@@ -293,7 +295,7 @@ public:
             CvTest( testName, "cv::DescriptorExtractor::compute" ),
             maxDist(_maxDist), prevTime(_prevTime), dextractor(_dextractor), distance(d) {}
 protected:
-    virtual void createDescriptorExtractor() {}
+    virtual void createDescriptorExtractor(){}
 
     void compareDescriptors( const Mat& validDescriptors, const Mat& calcDescriptors )
     {
@@ -329,7 +331,7 @@ protected:
 
     void emptyDataTest()
     {
-        assert( !dextractor.empty() );
+        assert( !dextractor.empty() && !dextractor->empty() );
 
         // One image.
         Mat image;
@@ -374,7 +376,7 @@ protected:
 
     void regressionTest()
     {
-        assert( !dextractor.empty() );
+        assert( !dextractor.empty() && !dextractor->empty() );
 
         // Read the test image.
         string imgFilename =  string(ts->get_data_path()) + FEATURES2D_DIR + "/" + IMAGE_FILENAME;
@@ -449,7 +451,7 @@ protected:
     void run(int)
     {
         createDescriptorExtractor();
-        if( dextractor.empty() )
+        if( dextractor.empty() || dextractor->empty() )
         {
             ts->printf(CvTS::LOG, "Descriptor extractor is empty.\n");
             ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
@@ -495,9 +497,16 @@ public:
 protected:
     virtual void createDescriptorExtractor()
     {
+        string filename = string(CV_DescriptorExtractorTest<Distance>::ts->get_data_path()) +
+                          FEATURES2D_DIR + "/calonder_classifier.rtc";
         CV_DescriptorExtractorTest<Distance>::dextractor =
-                new CalonderDescriptorExtractor<T>( string(CV_DescriptorExtractorTest<Distance>::ts->get_data_path()) +
+                new CalonderDescriptorExtractor<T>( filename );
-                                                    FEATURES2D_DIR + "/calonder_classifier.rtc");
+        if( CV_DescriptorExtractorTest<Distance>::dextractor->empty() )
+        {
+            stringstream ss; ss << "Calonder descriptor extractor can not be loaded from file" << filename<< endl;
+            CV_DescriptorExtractorTest<Distance>::ts->printf( CvTS::LOG, ss.str().c_str() );
+            CV_DescriptorExtractorTest<Distance>::ts->set_failed_test_info( CvTS::FAIL_INVALID_TEST_DATA );
+        }
     }
 };
 
@@ -531,7 +540,8 @@ private:
 
 void CV_DescriptorMatcherTest::emptyDataTest()
 {
-    assert( !dmatcher.empty() );
+    assert( !dmatcher.empty() && !dmatcher->empty() );
+
     Mat queryDescriptors, trainDescriptors, mask;
     vector<Mat> trainDescriptorCollection, masks;
     vector<DMatch> matches;