van de sande opt

semseg/SemSegCsurka.cpp

@@ -1316,7 +1316,7 @@ void SemSegCsurka::classifyregions ( CachedExample *ce, NICE::Image & segresult,
   else if ( opSiftImpl == "VANDESANDE" )
   {
     // the used features
-    cSIFT = new LFColorSande ( conf, "LFColorSandeTrain" );
+    cSIFT = new LFColorSande ( conf, "LFColorSandeTest" );
   }
   else
   {

semseg/SemSegNovelty.cpp

@@ -127,7 +127,7 @@ void SemSegNovelty::visualizeRegion(const NICE::ColorImage &img, const NICE::Mat
         {
           outimage(x,y,c) = img(x,y,c);
         }
-      } 
+      }
     }
   }
 }
@@ -420,7 +420,7 @@ void SemSegNovelty::semanticseg ( CachedExample *ce, NICE::Image & segresult, NI
       double sndMaxMean ( -numeric_limits<double>::max() );     
       
       for ( int j = 0 ; j < cr.scores.size(); j++ )
-      {   
+      {
         if ( forbidden_classesTrain.find ( j ) != forbidden_classesTrain.end() )
         {
           continue;

semseg/SemSegNovelty.h

@@ -77,7 +77,7 @@ class SemSegNovelty : public SemanticSegmentation
     //! maximum uncertainty over all images
     double globalMaxUncert;
     
-    //! current examples for maximum uncertain region
+    //! current examples for most uncertain region
     Examples newTrainExamples;
    
   public: