Merge branch 'master' of dbv.inf-cv.uni-jena.de:nice/nice-semseg

semseg/SemSegContextTree3D.cpp

@@ -798,15 +798,16 @@ void SemSegContextTree3D::train ( const LabeledSet * trainp )
   getDepthVector ( trainp, zsizeVec, run3Dseg );
 
   //FIXME: memory usage
-  vector<MultiChannelImage3DT<double> > allfeats;
-  vector<MultiChannelImage3DT<unsigned short int> > nodeIndices;
+  vector<MultiChannelImage3DT<double> > allfeats;   // Feature Werte
+  vector<MultiChannelImage3DT<unsigned short int> > nodeIndices;    // Zuordnung Knoten/Baum für jeden Pixel
   vector<MultiChannelImageT<int> > labels;
 
+    // für externen Klassifikator
   vector<SparseVector*> globalCategorFeats;
   vector<map<int,int> > classesPerImage;
 
-  vector<vector<int> > rSize;
-  vector<int> amountRegionpI;
+  vector<vector<int> > rSize;   // anzahl der pixel je region
+  vector<int> amountRegionpI; // ANZAHL der regionen pro bild (von unsupervised segmentation)
 
   std::string forbidden_classes_s = conf->gS ( "analysis", "forbidden_classes", "" );
   classnames.getSelection ( forbidden_classes_s, forbidden_classes );
@@ -822,15 +823,15 @@ void SemSegContextTree3D::train ( const LabeledSet * trainp )
     rawChannels = 1;
 
   if ( useGradient )
-    rawChannels *= 3;
+    rawChannels *= 3;   // gx, gy, gz
 
-  if ( useWeijer )
+  if ( useWeijer )      // Weijer Colornames
     rawChannels += 11;
 
-  if ( useHoiemFeatures )
+  if ( useHoiemFeatures )       // geometrische Kontextmerkmale
     rawChannels += 8;
 
-  if ( useAdditionalLayer )
+  if ( useAdditionalLayer )     // beliebige Merkmale in extra Bilddateien
     rawChannels += 1;
 
 

semseg/SemSegContextTree3D.h

@@ -187,7 +187,7 @@ private:
   void addFeatureMaps ( NICE::MultiChannelImage3DT<double> &imgData, const std::vector<std::string> &filelist, int &amountRegions );
 
   /**
-   * compute best split for current settings
+   * @brief compute best split for current settings
    * @param feats features
    * @param nodeIndices matrix with current node for each feature
    * @param labels labels for each feature