newest

semseg/SemSegContextTree.cpp

@@ -697,25 +697,8 @@ double SemSegContextTree::getBestSplit( std::vector<NICE::MultiChannelImageT<dou
 
   set<vector<int> >selFeats;
   map<int, int> e;
-  int featcounter = 0;
-
-  for ( int iCounter = 0; iCounter < imgCount; iCounter++ )
-  {
-    int xsize = ( int )currentfeats[iCounter].width();
-    int ysize = ( int )currentfeats[iCounter].height();
-
-    for ( int x = 0; x < xsize; x++ )
-    {
-      for ( int y = 0; y < ysize; y++ )
-      {
-        if ( currentfeats[iCounter].get( x, y, tree ) == node )
-        {
-          featcounter++;
-        }
-      }
-    }
-  }
-
+  int featcounter = forest[tree][node].featcounter;
+  
   if ( featcounter < minFeats )
   {
     //cout << "only " << featcounter << " feats in current node -> it's a leaf" << endl;
@@ -734,8 +717,6 @@ double SemSegContextTree::getBestSplit( std::vector<NICE::MultiChannelImageT<dou
     //cout << "fraction["<<i<<"]: "<< fraction[i] << " a[" << i << "]: " << a[i] << endl;
   }
 
-  //cout << "a.size(): " << a.size() << endl;
-  //getchar();
   featcounter = 0;
 
   for ( int iCounter = 0; iCounter < imgCount; iCounter++ )
@@ -863,7 +844,7 @@ double SemSegContextTree::getBestSplit( std::vector<NICE::MultiChannelImageT<dou
       featsel.push_back( op );
     }
   }
-
+  
 #pragma omp parallel for private(mapit)
   for ( int f = 0; f < featsPerSplit; f++ )
   {
@@ -964,7 +945,7 @@ double SemSegContextTree::getBestSplit( std::vector<NICE::MultiChannelImageT<dou
       }
     }
   }
-
+  //getchar();
   //splitop->writeInfos();
   //cout<< "ig: " << bestig << endl;
   //FIXME: delete all features!
@@ -998,9 +979,7 @@ void SemSegContextTree::computeIntegralImage( const NICE::MultiChannelImageT<int
   int ysize = currentfeats.height();
 
   int channels = ( int )forest[0][0].dist.size();
-
 #pragma omp parallel for
-
   for ( int c = 0; c < channels; c++ )
   {
     integralImage.set( 0, 0, getMeanProb( 0, 0, c, currentfeats ), c );
@@ -1037,7 +1016,6 @@ void SemSegContextTree::computeIntegralImage( const NICE::MultiChannelImageT<int
   if ( integralImage.get( xsize - 1, ysize - 1, channels ) == 0.0 )
   {
 #pragma omp parallel for
-
     for ( int c1 = 0; c1 < channels2; c1++ )
     {
       int c = channels + c1;
@@ -1121,6 +1099,8 @@ void SemSegContextTree::train( const MultiDataset *md )
 
   getchar();*/
 
+  int amountPixels = 0;
+  
   LOOP_ALL_S( *trainp )
   {
     EACH_INFO( classno, info );
@@ -1144,6 +1124,7 @@ void SemSegContextTree::train( const MultiDataset *md )
 
     int xsize, ysize;
     ce->getImageSize( xsize, ysize );
+    amountPixels += xsize*ysize;
 
     MatrixT<int> tmpMat( xsize, ysize );
 
@@ -1268,6 +1249,7 @@ void SemSegContextTree::train( const MultiDataset *md )
     tree.push_back( TreeNode() );
     tree[0].dist = vector<double>( classes, 0.0 );
     tree[0].depth = depth;
+    tree[0].featcounter = amountPixels;
     forest.push_back( tree );
   }
 
@@ -1295,15 +1277,28 @@ void SemSegContextTree::train( const MultiDataset *md )
       startnode[tree] = t;
       //TODO vielleicht parallel wenn nächste schleife trotzdem noch parallelsiert würde, die hat mehr gewicht
       //#pragma omp parallel for
-
+#if 0
+          timer.stop();
+          cout << "time before tree: " << timer.getLast() << endl;
+          timer.start();
+#endif
       for ( int i = s; i < t; i++ )
       {
         if ( !forest[tree][i].isleaf && forest[tree][i].left < 0 )
         {
+#if 0
+                    timer.stop();
+          cout << "time 1: " << timer.getLast() << endl;
+          timer.start();
+#endif
           Operation *splitfeat = NULL;
           double splitval;
           double bestig = getBestSplit( allfeats, lastfeats, integralImgs, labels, i, splitfeat, splitval, tree );
-
+#if 0
+          timer.stop();
+          cout << "time 2: " << timer.getLast() << endl;
+          timer.start();
+#endif
           forest[tree][i].feat = splitfeat;
           forest[tree][i].decision = splitval;
 
@@ -1320,9 +1315,14 @@ void SemSegContextTree::train( const MultiDataset *md )
             forest[tree][right].dist = vector<double>( classes, 0.0 );
             forest[tree][left].depth = depth + 1;
             forest[tree][right].depth = depth + 1;
-
+            forest[tree][left].featcounter = 0;
+            forest[tree][right].featcounter = 0;
+#if 0
+                      timer.stop();
+          cout << "time 3: " << timer.getLast() << endl;
+          timer.start();
+#endif
 #pragma omp parallel for
-
             for ( int iCounter = 0; iCounter < imgcounter; iCounter++ )
             {
               int xsize = currentfeats[iCounter].width();
@@ -1346,6 +1346,7 @@ void SemSegContextTree::train( const MultiDataset *md )
                     {
                       currentfeats[iCounter].set( x, y, left, tree );
                       forest[tree][left].dist[labelmap[labels[iCounter]( x, y )]]++;
+                      forest[tree][left].featcounter++;
                     }
                     else
                     {
@@ -1356,7 +1357,13 @@ void SemSegContextTree::train( const MultiDataset *md )
                 }
               }
             }
-
+#if 0
+            timer.stop();
+          cout << "time 4: " << timer.getLast() << endl;
+          timer.start();
+#endif
+            forest[tree][right].featcounter = forest[tree][i].featcounter - forest[tree][left].featcounter;
+            
             double lcounter = 0.0, rcounter = 0.0;
 
             for ( uint d = 0; d < forest[tree][left].dist.size(); d++ )
@@ -1374,7 +1381,11 @@ void SemSegContextTree::train( const MultiDataset *md )
                 rcounter += forest[tree][right].dist[d];
               }
             }
-
+#if 0
+            timer.stop();
+          cout << "time 5: " << timer.getLast() << endl;
+          timer.start();
+#endif       
             if ( lcounter <= 0 || rcounter <= 0 )
             {
               cout << "lcounter : " << lcounter << " rcounter: " << rcounter << endl;
@@ -1431,13 +1442,23 @@ void SemSegContextTree::train( const MultiDataset *md )
           }
         }
       }
+#if 0
+           timer.stop();
+          cout << "time after tree: " << timer.getLast() << endl;
+          timer.start();
+#endif
     }
 
     //TODO: features neu berechnen!
 
     //compute integral image
     int channels = classes + allfeats[0].channels();
-
+#if 0
+              timer.stop();
+          cout << "time for part0: " << timer.getLast() << endl;
+          timer.start();
+#endif
+    
     if ( integralImgs[0].width() == 0 )
     {
       for ( int i = 0; i < imgcounter; i++ )
@@ -1448,7 +1469,14 @@ void SemSegContextTree::train( const MultiDataset *md )
         integralImgs[i].setAll( 0.0 );
       }
     }
+#if 0
+          timer.stop();
+          cout << "time for part1: " << timer.getLast() << endl;
+          timer.start();
+#endif     
+
 
+#pragma omp parallel for
     for ( int i = 0; i < imgcounter; i++ )
     {
       computeIntegralImage( currentfeats[i], allfeats[i], integralImgs[i] );
@@ -1464,7 +1492,6 @@ void SemSegContextTree::train( const MultiDataset *md )
 
 #ifdef DEBUG
     cout << "depth: " << depth << endl;
-
 #endif
   }
 

semseg/SemSegContextTree.h

@@ -44,6 +44,9 @@ public:
 
   /** depth of the node in the tree */
   int depth;
+  
+  /** how many pixels are in this node */
+  int featcounter;
 
   /** simple constructor */
   TreeNode(): left( -1 ), right( -1 ), feat( NULL ), decision( -1.0 ), isleaf( false ) {}
@@ -211,7 +214,7 @@ class SemSegContextTree : public SemanticSegmentation
 
   /** use Gaussian distributed features based on the feature position */
   bool useGaussian;
-
+  
   /** Number of trees used for the forest */
   int nbTrees;