Wrap all methods from ObjectnessBING, add create methods for all Saliency classes

modules/saliency/include/opencv2/saliency/saliencyBaseClasses.hpp

@@ -84,7 +84,7 @@ class CV_EXPORTS_W Saliency : public virtual Algorithm
    * \brief Get the name of the specific saliency type
    * \return The name of the tracker initializer
    */
-  String getClassName() const;
+  CV_WRAP String getClassName() const;
 
  protected:
 
@@ -109,10 +109,10 @@ class CV_EXPORTS_W StaticSaliency : public virtual Saliency
     algorithm calculates the optimal threshold separating those two classes, so that their
     intra-class variance is minimal.
 
-    @param saliencyMap the saliency map obtained through one of the specialized algorithms
-    @param binaryMap the binary map
+    @param _saliencyMap the saliency map obtained through one of the specialized algorithms
+    @param _binaryMap the binary map
      */
-  CV_WRAP bool computeBinaryMap( const Mat& saliencyMap, Mat& binaryMap );
+  CV_WRAP bool computeBinaryMap( InputArray _saliencyMap, OutputArray _binaryMap );
  protected:
   virtual bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap )=0;
 

modules/saliency/include/opencv2/saliency/saliencySpecializedClasses.hpp

@@ -42,7 +42,6 @@
 #ifndef __OPENCV_SALIENCY_SPECIALIZED_CLASSES_HPP__
 #define __OPENCV_SALIENCY_SPECIALIZED_CLASSES_HPP__
 
-//#include "opencv2/saliency/kyheader.hpp"
 #include <cstdio>
 #include <string>
 #include <iostream>
@@ -71,9 +70,22 @@ class CV_EXPORTS_W StaticSaliencySpectralResidual : public StaticSaliency
 {
 public:
 
-  CV_WRAP StaticSaliencySpectralResidual();
+  StaticSaliencySpectralResidual();
   virtual ~StaticSaliencySpectralResidual();
 
+  CV_WRAP static Ptr<StaticSaliencySpectralResidual> create()
+  {
+    return makePtr<StaticSaliencySpectralResidual>();
+  }
+
+  CV_WRAP bool computeSaliency( InputArray image, OutputArray saliencyMap )
+  {
+    if( image.empty() )
+      return false;
+
+    return computeSaliencyImpl( image, saliencyMap );
+  }
+
   CV_WRAP void read( const FileNode& fn );
   void write( FileStorage& fs ) const;
 
@@ -115,9 +127,22 @@ protected:
 class CV_EXPORTS_W MotionSaliencyBinWangApr2014 : public MotionSaliency
 {
 public:
-  CV_WRAP MotionSaliencyBinWangApr2014();
+  MotionSaliencyBinWangApr2014();
   virtual ~MotionSaliencyBinWangApr2014();
 
+  CV_WRAP static Ptr<MotionSaliencyBinWangApr2014> create()
+  {
+    return makePtr<MotionSaliencyBinWangApr2014>();
+  }
+
+  CV_WRAP bool computeSaliency( InputArray image, OutputArray saliencyMap )
+  {
+    if( image.empty() )
+      return false;
+
+    return computeSaliencyImpl( image, saliencyMap );
+  }
+
   /** @brief This is a utility function that allows to set the correct size (taken from the input image) in the
     corresponding variables that will be used to size the data structures of the algorithm.
     @param W width of input image
@@ -205,11 +230,24 @@ class CV_EXPORTS_W ObjectnessBING : public Objectness
 {
 public:
 
-  CV_WRAP ObjectnessBING();
+  ObjectnessBING();
   virtual ~ObjectnessBING();
 
-  void read();
-  void write() const;
+  CV_WRAP static Ptr<ObjectnessBING> create()
+  {
+    return makePtr<ObjectnessBING>();
+  }
+
+  CV_WRAP bool computeSaliency( InputArray image, OutputArray saliencyMap )
+  {
+    if( image.empty() )
+      return false;
+
+    return computeSaliencyImpl( image, saliencyMap );
+  }
+
+  CV_WRAP void read();
+  CV_WRAP void write() const;
 
   /** @brief Return the list of the rectangles' objectness value,
 
@@ -223,7 +261,7 @@ public:
     the trained model.
     @param trainingPath trained model path
      */
-  void setTrainingPath( std::string trainingPath );
+  CV_WRAP void setTrainingPath( const String& trainingPath );
 
   /** @brief This is a utility function that allows to set an arbitrary path in which the algorithm will save the
     optional results
@@ -232,29 +270,29 @@ public:
     each row).
     @param resultsDir results' folder path
      */
-  void setBBResDir( std::string resultsDir );
+  CV_WRAP void setBBResDir( const String& resultsDir );
 
-  double getBase() const
+  CV_WRAP double getBase() const
   {
     return _base;
   }
-  inline void setBase(double val)
+  CV_WRAP inline void setBase(double val)
   {
     _base = val;
   }
-  int getNSS() const
+  CV_WRAP int getNSS() const
   {
     return _NSS;
   }
-  void setNSS(int val)
+  CV_WRAP void setNSS(int val)
   {
     _NSS = val;
   }
-  int getW() const
+  CV_WRAP int getW() const
   {
     return _W;
   }
-  void setW(int val)
+  CV_WRAP void setW(int val)
   {
     _W = val;
   }

modules/saliency/src/BING/objectnessBING.cpp

@@ -88,12 +88,12 @@ void ObjectnessBING::setColorSpace( int clr )
   _bbResDir = _resultsDir + "/" + std::string( format( "BBoxesB%gW%d%s/", _base, _W, _clrName[_Clr] ).c_str() );
 }
 
-void ObjectnessBING::setTrainingPath( std::string trainingPath )
+void ObjectnessBING::setTrainingPath( const String& trainingPath )
 {
   _trainingPath = trainingPath;
 }
 
-void ObjectnessBING::setBBResDir( std::string resultsDir )
+void ObjectnessBING::setBBResDir(const String &resultsDir )
 {
   _resultsDir = resultsDir;
 }

modules/saliency/src/staticSaliency.cpp

@@ -50,9 +50,9 @@ namespace saliency
  * StaticSaliency
  */
 
-bool StaticSaliency::computeBinaryMap( const Mat& saliencyMap, Mat& BinaryMap )
+bool StaticSaliency::computeBinaryMap( InputArray _saliencyMap, OutputArray _binaryMap )
 {
-
+  Mat saliencyMap = _saliencyMap.getMat();
   Mat labels = Mat::zeros( saliencyMap.rows * saliencyMap.cols, 1, 1 );
   Mat samples = Mat_<float>( saliencyMap.rows * saliencyMap.cols, 1 );
   Mat centers;
@@ -90,6 +90,8 @@ bool StaticSaliency::computeBinaryMap( const Mat& saliencyMap, Mat& BinaryMap )
   outputMat.convertTo( outputMat, CV_8U );
 
   // adaptative thresholding using Otsu's method, to make saliency map binary
+  _binaryMap.createSameSize(outputMat, outputMat.type());
+  Mat BinaryMap = _binaryMap.getMat();
   threshold( outputMat, BinaryMap, 0, 255, THRESH_BINARY | THRESH_OTSU );
 
   return true;