commented code removed

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

@@ -75,7 +75,6 @@ class CV_EXPORTS Saliency : public virtual Algorithm
    * \param saliencyMap      The computed saliency map.
    * \return true if the saliency map is computed, false otherwise
    */
-  //bool computeSaliency( const Mat& image, Mat& saliencyMap );
   bool computeSaliency( const InputArray image, OutputArray saliencyMap );
 
   /**
@@ -85,7 +84,7 @@ class CV_EXPORTS Saliency : public virtual Algorithm
   String getClassName() const;
 
  protected:
-  //virtual bool computeSaliencyImpl( const Mat& image, Mat& saliencyMap ) = 0;
+
   virtual bool computeSaliencyImpl( const InputArray image, OutputArray saliencyMap ) = 0;
   String className;
 };

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

@@ -63,7 +63,6 @@ class CV_EXPORTS StaticSaliencySpectralResidual : public StaticSaliency
 {
 public:
 
-  //StaticSaliencySpectralResidual( const StaticSaliencySpectralResidual::Params &parameters = StaticSaliencySpectralResidual::Params() );
   StaticSaliencySpectralResidual();
   virtual ~StaticSaliencySpectralResidual();
 
@@ -75,7 +74,6 @@ protected:
   AlgorithmInfo* info() const;CV_PROP_RW
   int resImWidth;
   int resImHeight;
-  //Ptr<Size> resizedImageSize;
 
 };
 
@@ -107,16 +105,11 @@ private:
   // classification (and adaptation) functions
   bool fullResolutionDetection( const Mat& image, Mat& highResBFMask );
   bool lowResolutionDetection( const Mat& image, Mat& lowResBFMask );
-  //bool templateUpdate( Mat highResBFMask );
 
   // Background model maintenance functions
   bool templateOrdering();
   bool templateReplacement( const Mat& finalBFMask, const Mat& image );
 
-  // Decision threshold adaptation and Activity control function
-  //bool activityControl(vector<Mat> noisePixelMask);
-  //bool decisionThresholdAdaptation();
-
   // changing structure
   std::vector<Ptr<Mat> > backgroundModel;// The vector represents the background template T0---TK of reference paper.
   // Matrices are two-channel matrix. In the first layer there are the B (background value)
@@ -124,15 +117,10 @@ private:
   Mat potentialBackground;// Two channel Matrix. For each pixel, in the first level there are the Ba value (potential background value)
                           // and in the secon level there are the Ca value, the counter for each potential value.
   Mat epslonPixelsValue;  // epslon threshold
-  //Mat activityPixelsValue; // Activity level of each pixel
-  //vector<Mat> noisePixelMask; // We define a ‘noise-pixel’ as a pixel that has been classified as a foreground pixel during the full resolution
-  // detection process,however, after the low resolution detection, it has become a
-  // background pixel. In a noise-pixel mask, the identified noise-pixels are set to 1 while other pixels are 0;
 
   //fixed parameter
   bool neighborhoodCheck;
   int N_DS;// Number of template to be downsampled and used in lowResolutionDetection function
-  //Ptr<Size> imgSize;
   int imageWidth;// Width of input image
   int imageHeight;//Height of input image
   int K;// Number of background model template
@@ -144,12 +132,6 @@ private:
   int gamma;// Parameter that controls the time that the newly updated long-term background value will remain in the
             // long-term template, regardless of any subsequent background changes. A relatively large (eg gamma=3) will
             //restrain the generation of ghosts.
-  //int Ainc; // Activity Incrementation;
-  //int Bmax; // Upper-bound value for pixel activity
-  //int Bth;  // Max activity threshold
-  //int Binc, Bdec; // Threshold for pixel-level decision threshold (epslon) adaptation
-  //int deltaINC, deltaDEC; // Increment-decrement value for epslon adaptation
-  //int epslonMIN, epslonMAX; // Range values for epslon threshold
 
 };
 
@@ -254,7 +236,6 @@ private:
   // List of the rectangles' objectness value, in the same order as
   // the  vector<Vec4i> objectnessBoundingBox returned by the algorithm (in computeSaliencyImpl function)
   std::vector<float> objectnessValues;
-  //vector<Vec4i> objectnessBoundingBox;
 
 private:
   // functions

modules/saliency/samples/computeSaliency.cpp

@@ -145,7 +145,7 @@ int main( int argc, char** argv )
 
       if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
       {
-
+        std::cout << "Objectness done" << std::endl;
       }
     }
 
@@ -169,7 +169,7 @@ int main( int argc, char** argv )
         Mat saliencyMap;
         if( saliencyAlgorithm->computeSaliency( frame, saliencyMap ) )
         {
-          //std::cout << "motion saliency done" << std::endl;
+          std::cout << "current frame motion saliency done" << std::endl;
         }
 
         imshow( "image", frame );

modules/saliency/src/BING/CmShow.cpp

@@ -102,33 +102,5 @@ Mat CmShow::HistBins( CMat& color3f, CMat& val, CStr& title, bool descendShow, C
   return showImg3b;
 }
 
-/* void CmShow::showTinyMat(CStr &title, CMat &m)
- {
- int scale = 50, sz = m.rows * m.cols;
- while (sz > 200){
- scale /= 2;
- sz /= 4;
- }
-
- Mat img;
- resize(m, img, Size(), scale, scale, INTER_NEAREST );
- if (img.channels() == 3)
- cvtColor(img, img, COLOR_RGB2BGR);
- SaveShow(img, title);
- }
-
- void CmShow::SaveShow(CMat& img, CStr& title)
- {
- if (title.size() == 0)
- return;
-
- int mDepth = CV_MAT_DEPTH(img.type());
- double scale = (mDepth == CV_32F || mDepth == CV_64F ? 255 : 1);
- if (title.size() > 4 && title[title.size() - 4] == '.')
- imwrite(String(title.c_str()), img*scale);
- else if (title.size())
- imshow(String(title.c_str()), img);
- } */
-
 }  // namespace saliency
 }  // namespace cv

modules/saliency/src/BING/kyheader.hpp

@@ -53,11 +53,9 @@
 #include <time.h>
 #include <fstream>
 #include <stdint.h>
-//#include <omp.h>
 
 // TODO: reference additional headers your program requires here
-//#include "LibLinear/linear.h"
-//#include <opencv2/opencv.hpp>
+
 #include "opencv2/core.hpp"
 
 #define CV_VERSION_ID CVAUX_STR(CV_MAJOR_VERSION) CVAUX_STR(CV_MINOR_VERSION) CVAUX_STR(CV_SUBMINOR_VERSION)
@@ -67,10 +65,6 @@
 #define cvLIB(name) "opencv_" name CV_VERSION_ID
 #endif
 
-//#pragma comment( lib, cvLIB("core"))
-//#pragma comment( lib, cvLIB("imgproc"))
-//#pragma comment( lib, cvLIB("highgui"))
-
 #ifdef WIN32
 /* windows stuff */
 #else
@@ -121,13 +115,6 @@ enum
 template<typename T>
 static inline int findFromList( const T &word, const std::vector<T> &strList )
 {
-  //TODO delete test code
-  //cout << "\n\n" << "word" <<" "<< word << endl;
-  for ( int i = 0; i < strList.size(); i++ )
-  {
-    //cout <<"test word:"<< word << " " << endl;
-    //cout << "Size w " << word.size() << " Size L "<< strList[i].size() << endl;
-  }
 
   std::vector<cv::String>::iterator it = std::find( strList.begin(), strList.end(), word );
   if( it == strList.end() )
@@ -138,21 +125,8 @@ static inline int findFromList( const T &word, const std::vector<T> &strList )
   {
     int index = it - strList.begin();
     return index;
-    //vector<String>::iterator index = std::distance( strList.begin(), it );
-    //cout << "index" <<" "<< index << endl;
-    //return int( index );
   }
 }
-/*template<typename T>
- static inline int findFromList(const string &word, const vector<T> &strList) {
- //for(int i=0; i<strList.size(); i++){
- //cout <<"element: " <<strList[i]<<" "<<word << endl;
- //if (std::strcmp(word.c_str(),strList[i].c_str())==0) return i;
- }
-
- return -1;
- }
- */
 
 template<typename T> inline T sqr( T x )
 {
@@ -174,15 +148,7 @@ inline cv::Rect Vec4i2Rect( cv::Vec4i &v )
 {
   return cv::Rect( cv::Point( v[0] - 1, v[1] - 1 ), cv::Point( v[2], v[3] ) );
 }
-/*
-#ifdef __WIN32
-#define INT64 long long
-#else
-#define INT64 long
-typedef unsigned long UINT64_;
-//#define UINT64 unsigned long
-#endif
-*/
+
 
  #if defined(_MSC_VER)
  # include <intrin.h>
@@ -288,6 +254,4 @@ inline int popcnt_byte( register uint32_t u )
 }
 }
 
-/////
-
 #endif // KYHEADER_H

modules/saliency/src/BING/objectnessBING.cpp

@@ -108,12 +108,9 @@ int ObjectnessBING::loadTrainedModel( std::string modelName )  // Return -1, 0,
     return 0;
   }
 
-  //filters1f = aFilter(0.8f, 8);
-  //normalize(filters1f, filters1f, p, 1, NORM_MINMAX);
 
   normalize( filters1f, show3u, 1, 255, NORM_MINMAX, CV_8U );
   _tigF.update( filters1f );
-  //_tigF.reconstruct(filters1f);
 
   _svmSzIdxs = idx1i;
   CV_Assert( _svmSzIdxs.size() > 1 && filters1f.size() == Size(_W, _W) && filters1f.type() == CV_32F );
@@ -146,10 +143,6 @@ void ObjectnessBING::predictBBoxSI( Mat &img3u, ValStructVec<float, Vec4i> &valB
     resize( img3u, im3u, Size( cvRound( _W * imgW * 1.0 / width ), cvRound( _W * imgH * 1.0 / height ) ) );
     gradientMag( im3u, mag1u );
 
-    //Mat mag1f;
-    //mag1u.convertTo(mag1f, CV_32F);
-    //matchTemplate(mag1f, _svmFilter, matchCost1f, CV_TM_CCORR);
-
     matchCost1f = _tigF.matchTemplate( mag1u );
 
     ValStructVec<float, Point> matchCost;
@@ -449,21 +442,6 @@ bool ObjectnessBING::matRead( const std::string& filename, Mat& _M )
   Mat M;
   fs2[String( removeExtension( basename( filename ) ).c_str() )] >> M;
 
-  /* FILE* f = fopen(_S(filename), "rb");
-   if (f == NULL)
-   return false;
-   char buf[8];
-   int pre = fread(buf,sizeof(char), 5, f);
-   if (strncmp(buf, "CmMat", 5) != 0)  {
-   printf("Invalidate CvMat data file %s\n", _S(filename));
-   return false;
-   }
-   int headData[3]; // Width, height, type
-   fread(headData, sizeof(int), 3, f);
-   Mat M(headData[1], headData[0], headData[2]);
-   fread(M.data, sizeof(char), M.step * M.rows, f);
-   fclose(f); */
-
   M.copyTo( _M );
   return true;
 }

modules/saliency/src/motionSaliencyBinWangApr2014.cpp

@@ -51,15 +51,6 @@ namespace cv
 namespace saliency
 {
 
-/* cv::Ptr<Size> MotionSaliencyBinWangApr2014::getWsize()
- {
- return imgSize;
- }
- void MotionSaliencyBinWangApr2014::setWsize( const cv::Ptr<Size>& newSize )
- {
- imgSize = newSize;
- } */
-
 void MotionSaliencyBinWangApr2014::setImagesize( int W, int H )
 {
   imageWidth = W;
@@ -91,7 +82,6 @@ bool MotionSaliencyBinWangApr2014::init()
   // the position (n / 2) and ((n / 2) +1) (choose their arithmetic mean).
 
   potentialBackground = Mat( imgSize.height, imgSize.width, CV_32FC2, Scalar( NAN, 0 ) );
-  //backgroundModel = std::vector<Mat>( K + 1, Mat::zeros( imgSize->height, imgSize->width, CV_32FC2 ) );
 
   backgroundModel.resize( K + 1 );
 
@@ -122,17 +112,6 @@ bool MotionSaliencyBinWangApr2014::fullResolutionDetection( const Mat& image2, M
   float currentEpslonValue;
   bool backgFlag = false;
 
-  /*  for ( int i = 0; i <= K; i++ )
-   {
-   vector<Mat> spl;
-   split( * ( backgroundModel[i] ), spl );
-   stringstream windowTitle;
-   windowTitle << "TEST_t" << i << "B";
-   Mat convert;
-   spl[0].convertTo( convert, CV_8UC1 );
-   imshow( windowTitle.str().c_str(), convert );
-   }*/
-
   // Initially, all pixels are considered as foreground and then we evaluate with the background model
   highResBFMask.create( image.rows, image.cols, CV_32F );
   highResBFMask.setTo( 1 );
@@ -176,12 +155,10 @@ bool MotionSaliencyBinWangApr2014::fullResolutionDetection( const Mat& image2, M
           //continue;
           if( ( *currentC ) > 0 )  //The current template is active
           {
-            //cout<< "DIFFERENCE: "<<abs( currentPixelValue -  ( *currentB ) )<<endl;
             // If there is a match with a current background template
             if( abs( currentPixelValue - ( *currentB ) ) < currentEpslonValue && !backgFlag )
             {
               // The correspondence pixel in the  BF mask is set as background ( 0 value)
-              //highResBFMask.at<uchar>( i, j ) = 0;
               pMask[j] = 0;
               if( ( *currentC < L0 && z == 0 ) || ( *currentC < L1 && z == 1 ) || ( z > 1 ) )
               {
@@ -190,7 +167,6 @@ bool MotionSaliencyBinWangApr2014::fullResolutionDetection( const Mat& image2, M
 
               *currentB = ( ( 1 - alpha ) * ( *currentB ) ) + ( alpha * currentPixelValue );  // Update the template value
               backgFlag = true;
-              //break;
             }
             else
             {
@@ -347,7 +323,6 @@ bool MotionSaliencyBinWangApr2014::templateOrdering()
       }
 
       // SORT Template T0 and T1
-      //if( backgroundModel[1]->at<Vec2f>( i, j )[1] > thetaL && backgroundModel[0]->at<Vec2f>( i, j )[1] < thetaL )
       if( bgModel_1P[j][1] > thetaL && bgModel_0P[j][1] < thetaL )
       {
 
@@ -367,17 +342,6 @@ bool MotionSaliencyBinWangApr2014::templateOrdering()
 }
 bool MotionSaliencyBinWangApr2014::templateReplacement( const Mat& finalBFMask, const Mat& image )
 {
-  /* Mat test( image.rows, image.cols, CV_8U );
-   for ( int i = 0; i < test.rows; i++ )
-   {
-   for ( int j = 0; j < test.cols; j++ )
-   {
-
-   test.at<uchar>( i, j ) = (int) potentialBackground.at<Vec2f>( i, j )[0];
-   }
-   }
-   imshow( "test_BA", test );*/
-
   std::vector<Mat> temp;
   split( *backgroundModel[0], temp );
 
@@ -451,9 +415,6 @@ bool MotionSaliencyBinWangApr2014::templateReplacement( const Mat& finalBFMask,
               // Neighborhood of current pixel in the current background model template.
               // The ROI is centered in the pixel coordinates
 
-              /*if( ( i - floor( roiSize / 2 ) >= 0 ) && ( j - floor( roiSize / 2 ) >= 0 )
-               && ( i + floor( roiSize / 2 ) <= ( backgroundModel[z].rows - 1 ) )
-               && ( j + floor( roiSize / 2 ) <= ( backgroundModel[z].cols - 1 ) ) ) */
               if( i > 0 && j > 0 && i < ( backgroundModel[z]->rows - 1 ) && j < ( backgroundModel[z]->cols - 1 ) )
               {
                 split( *backgroundModel[z], mv );
@@ -550,27 +511,15 @@ bool MotionSaliencyBinWangApr2014::computeSaliencyImpl( const InputArray image,
   fullResolutionDetection( image.getMat(), highResBFMask );
   lowResolutionDetection( image.getMat(), lowResBFMask );
 
-  /*imshow( "highResBFMask", highResBFMask * 255 );
-   imshow( "lowResBFMask", lowResBFMask * 255 );
-   */
 
 // Compute the final background-foreground mask. One pixel is marked as foreground if and only if it is
 // foreground in both masks (full and low)
   bitwise_and( highResBFMask, lowResBFMask, saliencyMap );
 
-// Detect the noise pixels (i.e. for a given pixel, fullRes(pixel) = foreground and lowRes(pixel)= background)
-  //bitwise_not( lowResBFMask, not_lowResBFMask );
-  //bitwise_and( highResBFMask, not_lowResBFMask, noisePixelsMask );
-
   templateOrdering();
   templateReplacement( saliencyMap.getMat(), image.getMat() );
   templateOrdering();
 
-  /* Mat kernel = getStructuringElement( MORPH_RECT, Size( 3, 3 ));
-   Mat kernel2 = getStructuringElement( MORPH_RECT, Size( 3, 3 ));
-   morphologyEx(saliencyMap.getMat(), saliencyMap.getMat(), MORPH_OPEN, kernel);
-   morphologyEx(saliencyMap.getMat(), saliencyMap.getMat(), MORPH_CLOSE, kernel2);*/
-
   return true;
 }
 

modules/saliency/src/saliency_init.cpp

@@ -50,7 +50,6 @@ namespace saliency
 CV_INIT_ALGORITHM( StaticSaliencySpectralResidual, "SALIENCY.SPECTRAL_RESIDUAL",
                    obj.info()->addParam( obj, "resImWidth", obj.resImWidth); obj.info()->addParam( obj, "resImHeight", obj.resImHeight) );
 
-//CV_INIT_ALGORITHM( MotionSaliencySuBSENSE, "SALIENCY.SuBSENSE", );
 
 CV_INIT_ALGORITHM(
     ObjectnessBING, "SALIENCY.BING",

modules/saliency/src/staticSaliency.cpp

@@ -88,7 +88,6 @@ bool StaticSaliency::computeBinaryMap( const Mat& saliencyMap, Mat& BinaryMap )
   //Convert
   outputMat = outputMat * 255;
   outputMat.convertTo( outputMat, CV_8U );
-  //saliencyMap = outputMat;
 
   // adaptative thresholding using Otsu's method, to make saliency map binary
   threshold( outputMat, BinaryMap, 0, 255, THRESH_BINARY | THRESH_OTSU );

modules/saliency/src/staticSaliencySpectralResidual.cpp

@@ -50,21 +50,12 @@ namespace saliency
  * SaliencySpectralResidual
  */
 
-/*cv::Ptr<Size> StaticSaliencySpectralResidual::getWsize()
- {
- return resizedImageSize;
- }
- void StaticSaliencySpectralResidual::setWsize( const cv::Ptr<Size>& newSize )
- {
- resizedImageSize = newSize;
- }*/
 
 StaticSaliencySpectralResidual::StaticSaliencySpectralResidual()
 {
   className = "SPECTRAL_RESIDUAL";
   resImWidth = 64;
   resImHeight = 64;
-  //resizedImageSize = Ptr<Size>( new Size( 64, 64 ) );
 }
 
 StaticSaliencySpectralResidual::~StaticSaliencySpectralResidual()