an neuen core und vislearning angepasst

classifier/FPCnone.h

@@ -10,10 +10,10 @@
 
 #include <objrec/nice.h>
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include "objrec/classifier/fpclassifier/logisticregression/SLR.h"
-#include "objrec/cbaselib/FeaturePool.h"
-#include "objrec/math/algebra/GMSparse2.h"
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include "vislearning/classifier/fpclassifier/logisticregression/SLR.h"
+#include "vislearning/cbaselib/FeaturePool.h"
+#include "vislearning/math/algebra/GMSparse2.h"
 
 namespace OBJREC {
 
@@ -73,8 +73,8 @@ class FPCnone : public FeaturePoolClassifier
 	void setComplexity ( int size );
 
 	/** IO functions */
-	void restore (istream & is, int format = 0);
-	void store (ostream & os, int format = 0) const;
+	void restore (std::istream & is, int format = 0);
+	void store (std::ostream & os, int format = 0) const;
 	void clear ();
 };
 

libdepend.inc

@@ -1 +1,2 @@
 $(call PKG_DEPEND_INT,objrec/semanticsegmentation)
+$(call PKG_DEPEND_INT,core)

progs/adaptmedfilter.cpp

@@ -1,65 +0,0 @@
-/**
-* @file testSegmentation.cpp
-* @brief test segmentation algorithm
-* @author Björn Fröhlich
-* @date 01/20/2010
-
-*/
-#include <objrec/nice.h>
-
-#include <objrec/baselib/Config.h>
-#include <list>
-
-
-using namespace OBJREC;
-using namespace NICE;
-using namespace std;
-
-int main (int argc, char **argv)
-{
-	if(argc < 1)
-	{
-		cerr << "Bitte Bild angeben" << endl;
-		return -1;
-	}
-
-	string filename;
-	filename += argv[1];
-
-	//RSMeanShift rg;
-	NICE::Image img;
-
-	img.read(filename);
-	NICE::Image out(img);
-	
-	int masksize = 5;
-	int mh = masksize/2;
-	
-	int width = img.width();
-	int height = img.height();
-	
-	for(int x= 0; x < width; x++)
-	{
-	 for(int y = 0; y < height; y++)
-	 {
-	   vector<int> nh;
-	   for(int i = -mh; i <= mh; i++)
-	   {
-	    for(int j = -mh; j <= mh; j++)
-	    {
-	      int xpos = x + i;
-	      int ypos = y + j;
-	      if(xpos < 0 || ypos < 0 || xpos >= width || ypos >= height)
-		continue;
-	      nh.push_back(img.getPixel(xpos,ypos));
-	    }
-	   }
-	   sort(nh.begin(), nh.end());
-	   int val = nh[nh.size()/2];
-	   out.setPixel(x,y,val);
-	 }
-	}
-	
-	out.write("res.ppm");
-	return 0;
-}

progs/convertFeatures.cpp

@@ -5,23 +5,21 @@
 * @date 2007-10-12
 */
 
-#include <objrec/nice_nonvis.h>
-
 #include <fstream>
 #include <iostream>
 
-#include <objrec/cbaselib/MultiDataset.h>
+#include <vislearning/cbaselib/MultiDataset.h>
 #include <objrec/iclassifier/icgeneric/CSGeneric.h>
-#include <objrec/cbaselib/ClassificationResults.h>
+#include <vislearning/cbaselib/ClassificationResults.h>
 #include <objrec/iclassifier/codebook/MutualInformation.h>
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include <objrec/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
-#include <objrec/classifier/classifierinterfaces/VCFeaturePool.h>
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include <vislearning/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
+#include <vislearning/classifier/classifierinterfaces/VCFeaturePool.h>
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/Preprocess.h>
-#include <objrec/baselib/StringTools.h>
+#include "core/basics/Config.h"
+#include <vislearning/baselib/Preprocess.h>
+#include <core/basics/StringTools.h>
 
 #undef DEBUG
 

progs/convertFeatures2.cpp

@@ -5,23 +5,21 @@
 * @date 2007-10-12
 */
 
-#include <objrec/nice_nonvis.h>
-
 #include <fstream>
 #include <iostream>
 
-#include <objrec/cbaselib/MultiDataset.h>
+#include <vislearning/cbaselib/MultiDataset.h>
 #include <objrec/iclassifier/icgeneric/CSGeneric.h>
-#include <objrec/cbaselib/ClassificationResults.h>
+#include <vislearning/cbaselib/ClassificationResults.h>
 #include <objrec/iclassifier/codebook/MutualInformation.h>
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include <objrec/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
-#include <objrec/classifier/classifierinterfaces/VCFeaturePool.h>
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include <vislearning/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
+#include <vislearning/classifier/classifierinterfaces/VCFeaturePool.h>
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/Preprocess.h>
-#include <objrec/baselib/StringTools.h>
+#include "core/basics/Config.h"
+#include <vislearning/baselib/Preprocess.h>
+#include <core/basics/StringTools.h>
 
 #undef DEBUG
 

progs/getRelevantClasses.cpp

@@ -11,11 +11,11 @@
 #include <omp.h>
 #endif
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/StringTools.h>
-#include <objrec/baselib/ICETools.h>
+#include "core/basics/Config.h"
+#include <core/basics/StringTools.h>
+#include <vislearning/baselib/ICETools.h>
 
-#include "objrec/cbaselib/MultiDataset.h"
+#include "vislearning/cbaselib/MultiDataset.h"
 #include "core/image/MultiChannelImageT.h"
 
 #include <fstream>

progs/test.cpp

@@ -1,48 +0,0 @@
-// Beispielhafter Aufruf: BUILD_x86_64/progs/testSemanticSegmentation -config <CONFIGFILE>
-
-/**
- * @file test.cpp
- * @brief simple test program for everything
- * @author Björn Fröhlich
- * @date 03/10/2010
- */
-
-#ifdef NICE_USELIB_OPENMP
-#include <omp.h>
-#endif
-
-#include <iostream>
-#include <fstream>
-
-#include "objrec/segmentation/RSMeanShift.h"
-#include "objrec/segmentation/RSCache.h"
-
-#include "objrec/baselib/Globals.h"
-
-using namespace std;
-
-using namespace OBJREC;
-
-int main(int argc, char **argv)
-{
-	
-	Image tmp(101,195);
-	tmp.set(0);
-	string infile = "/home/froehlich/Desktop/wichtiges/coind/out.txt";
-	ifstream in(infile.c_str());
-	
-	while(!in.eof())
-	{
-		int x,y,v;
-		in >> x;
-		in >> y;
-		in >> v;
-		if(v == 0)
-			v = 1;
-		tmp.setPixel(x,y,v);
-	}
-	tmp.write("/home/froehlich/Desktop/wichtiges/coind/out.pgm");
-	
-	
-	return 0;
-}

progs/testClassifier.cpp

@@ -10,18 +10,18 @@
 #include <fstream>
 #include <iostream>
 
-#include <objrec/cbaselib/MultiDataset.h>
+#include <vislearning/cbaselib/MultiDataset.h>
 #include <objrec/iclassifier/icgeneric/CSGeneric.h>
-#include <objrec/cbaselib/ClassificationResults.h>
+#include <vislearning/cbaselib/ClassificationResults.h>
 #include <objrec/iclassifier/codebook/MutualInformation.h>
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include <objrec/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
-#include <objrec/classifier/classifierinterfaces/VCFeaturePool.h>
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include <vislearning/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
+#include <vislearning/classifier/classifierinterfaces/VCFeaturePool.h>
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/Preprocess.h>
-#include <objrec/baselib/StringTools.h>
+#include "core/basics/Config.h"
+#include <vislearning/baselib/Preprocess.h>
+#include <core/basics/StringTools.h>
 
 #undef DEBUG
 

progs/testClassifierGMM.cpp

@@ -5,25 +5,23 @@
 * @date 2007-10-12
 */
 
-#include <objrec/nice_nonvis.h>
-
 #include <fstream>
 #include <iostream>
 
-#include <objrec/cbaselib/MultiDataset.h>
+#include <vislearning/cbaselib/MultiDataset.h>
 #include <objrec/iclassifier/icgeneric/CSGeneric.h>
-#include <objrec/cbaselib/ClassificationResults.h>
+#include <vislearning/cbaselib/ClassificationResults.h>
 #include <objrec/iclassifier/codebook/MutualInformation.h>
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include <objrec/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
-#include <objrec/classifier/classifierinterfaces/VCFeaturePool.h>
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include <vislearning/classifier/fpclassifier/randomforest/FPCRandomForestTransfer.h>
+#include <vislearning/classifier/classifierinterfaces/VCFeaturePool.h>
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/Preprocess.h>
-#include <objrec/baselib/StringTools.h>
+#include "core/basics/Config.h"
+#include <vislearning/baselib/Preprocess.h>
+#include <core/basics/StringTools.h>
 
-#include "objrec/math/cluster/GMM.h"
+#include "vislearning/math/cluster/GMM.h"
 
 #undef DEBUG
 

progs/testRF.cpp

@@ -4,14 +4,12 @@
 * @author Björn Fröhlich
 * @date 06/08/2010
 */
-#include "objrec/nice.h"
+#include "core/basics/Config.h"
 
-#include "objrec/baselib/Config.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
 
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-
-#include "objrec/baselib/Globals.h"
+#include "vislearning/baselib/Globals.h"
 
 using namespace OBJREC;
 using namespace NICE;

progs/testSemanticSegmentation.cpp

@@ -11,9 +11,9 @@
 #include <omp.h>
 #endif
 
-#include <objrec/baselib/Config.h>
-#include <objrec/baselib/StringTools.h>
-#include <objrec/baselib/ICETools.h>
+#include "core/basics/Config.h"
+#include "core/basics/StringTools.h"
+#include <vislearning/baselib/ICETools.h>
 
 #include <objrec-froehlichexp/semseg/SemanticSegmentation.h>
 #include <objrec-froehlichexp/semseg/SemSegLocal.h>

semseg/FIShotton.cpp

@@ -8,8 +8,8 @@
 #include <iostream>
 
 #include "FIShotton.h"
-#include "objrec/baselib/FastFilter.h"
-#include "objrec/image/GenericImageTools.h"
+#include "vislearning/baselib/FastFilter.h"
+#include "vislearning/image/GenericImageTools.h"
 
 using namespace OBJREC;
 

semseg/FIShotton.h

@@ -7,18 +7,10 @@
 */
 #ifndef FIShottonINCLUDE
 #define FIShottonINCLUDE
-
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
  
-#include "objrec/math/mathbase/SparseVector.h"
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-
-
+#include "core/vector/SparseVector.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
 
 namespace OBJREC {
 
@@ -37,12 +29,10 @@ class FIShotton
 
 	static void buildTextonMap ( CachedExample *ce,
 				FPCRandomForests *fpcrf,
-				map<DecisionNode *, pair<long, int> > index,
+				std::map<DecisionNode *, std::pair<long, int> > index,
 				int subsamplex, 
 				int subsampley,
 				int maxdepthSegmentationForest );
-
-
 };
 
 

semseg/SemSegContextTree.cpp

@@ -1,18 +1,15 @@
-#include <objrec/nice.h>
-
-#include <iostream>
-
 #include "SemSegContextTree.h"
-#include "objrec/baselib/Globals.h"
-#include "objrec/baselib/ProgressBar.h"
-#include "objrec/baselib/StringTools.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/baselib/Globals.h"
+#include "vislearning/baselib/ProgressBar.h"
+#include "core/basics/StringTools.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/cbaselib/PascalResults.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/cbaselib/PascalResults.h"
 
 #include <omp.h>
 
+#include <iostream>
+
 #define BOUND(x,min,max) (((x)<(min))?(min):((x)>(max)?(max):(x)))
 
 using namespace OBJREC;

semseg/SemSegContextTree.h

@@ -9,8 +9,8 @@
 #define SemSegContextTreeINCLUDE
 
 #include "SemanticSegmentation.h"
-#include <objrec/math/mathbase/VVector.h>
-#include "objrec/features/localfeatures/LFColorWeijer.h"
+#include <core/vector/VVector.h>
+#include "vislearning/features/localfeatures/LFColorWeijer.h"
 
 namespace OBJREC {
 
@@ -41,7 +41,7 @@ class SemSegContextTree : public SemanticSegmentation
 	{
 	public:
 		/** probabilities for each class */
-		vector<double> probs;
+		std::vector<double> probs;
 		
 		/** left child node */
 		int left;
@@ -59,7 +59,7 @@ class SemSegContextTree : public SemanticSegmentation
 		bool isleaf;
 		
 		/** distribution in current node */
-		vector<double> dist;
+		std::vector<double> dist;
 		
 		/** depth of the node in the tree */
 		int depth;
@@ -72,13 +72,13 @@ class SemSegContextTree : public SemanticSegmentation
 	};
 	
 	/** store features */
-	VVector currentfeats;
+	NICE::VVector currentfeats;
 	
 	/** store the positions of the features */
-	VVector positions;
+	NICE::VVector positions;
 	
 	/** tree -> saved as vector of nodes */
-	vector<Node> tree;
+	std::vector<Node> tree;
 	
 	/** local features */
 	LFColorWeijer *lfcw;
@@ -96,16 +96,16 @@ class SemSegContextTree : public SemanticSegmentation
 	int featsPerSplit;
 	
 	/** count samples per label */
-	map<int,int> labelcounter;
+	std::map<int,int> labelcounter;
 	
 	/** map of labels */
-	map<int,int> labelmap;
+	std::map<int,int> labelmap;
 	
 	/** map of labels inverse*/
-	map<int,int> labelmapback;
+	std::map<int,int> labelmapback;
 	
 	/** scalefactor for balancing for each class */
-	vector<double> a;
+	std::vector<double> a;
 	
 	/** the minimum number of features allowed in a leaf */
 	int minFeats;
@@ -114,10 +114,10 @@ class SemSegContextTree : public SemanticSegmentation
 	int maxDepth;
 	
 	/** operations for pairwise features */
-	vector<Operation*> ops;
+	std::vector<Operation*> ops;
 	
 	/** vector of all possible features */
-	vector<Operation*> featsel;
+	std::vector<Operation*> featsel;
 	
 	/** use alternative calculation for information gain */
 	bool useShannonEntropy;
@@ -126,7 +126,7 @@ class SemSegContextTree : public SemanticSegmentation
 	ClassNames classnames;
 
 	/** train selection */
-	set<int> forbidden_classes;
+	std::set<int> forbidden_classes;
 	
 	/** Configfile */
 	const Config *conf;
@@ -134,7 +134,7 @@ class SemSegContextTree : public SemanticSegmentation
 	
     public:
 	/** simple constructor */
-	SemSegContextTree( const Config *conf, const MultiDataset *md );
+	SemSegContextTree( const NICE::Config *conf, const MultiDataset *md );
       
 	/** simple destructor */
 	virtual ~SemSegContextTree();
@@ -162,7 +162,7 @@ class SemSegContextTree : public SemanticSegmentation
 	 * @param splitfeat output feature position
 	 * @param splitval 
 	 */
-	void getBestSplit(const vector<MultiChannelImageT<double> > &feats, vector<vector<vector<int> > > &currentfeats,const vector<vector<vector<int> > > &labels, int node, Operation *&splitfeat, double &splitval);
+	void getBestSplit(const std::vector<MultiChannelImageT<double> > &feats, std::vector<std::vector<std::vector<int> > > &currentfeats,const std::vector<std::vector<std::vector<int> > > &labels, int node, Operation *&splitfeat, double &splitval);
 
 };
 

semseg/SemSegCsurka.cpp

@@ -2,7 +2,7 @@
 
 #include "SemSegCsurka.h"
 
-#include "objrec/baselib/ICETools.h"
+#include "vislearning/baselib/ICETools.h"
 
 #include "core/image/Filter.h"
 

semseg/SemSegCsurka.h

@@ -7,24 +7,22 @@
 #ifndef SemSegCsurkaINCLUDE
 #define SemSegCsurkaINCLUDE
 
-#include <objrec/nice.h>
- 
 #include "SemanticSegmentation.h"
 
-#include "objrec/math/ftransform/PCA.h"
+#include "vislearning/math/ftransform/PCA.h"
 
-#include "objrec/features/localfeatures/GenericLocalFeatureSelection.h"
-#include "objrec/features/localfeatures/LFonHSG.h"
-#include "objrec/features/localfeatures/LFColorSande.h"
-#include "objrec/features/localfeatures/LFColorWeijer.h"
-#include "objrec/features/localfeatures/LFReadCache.h"
-#include "objrec/features/localfeatures/LFWriteCache.h"
-#include "objrec/cbaselib/VectorFeature.h"
-#include "objrec/features/fpfeatures/SparseVectorFeature.h"
+#include "vislearning/features/localfeatures/GenericLocalFeatureSelection.h"
+#include "vislearning/features/localfeatures/LFonHSG.h"
+#include "vislearning/features/localfeatures/LFColorSande.h"
+#include "vislearning/features/localfeatures/LFColorWeijer.h"
+#include "vislearning/features/localfeatures/LFReadCache.h"
+#include "vislearning/features/localfeatures/LFWriteCache.h"
+#include "vislearning/cbaselib/VectorFeature.h"
+#include "vislearning/features/fpfeatures/SparseVectorFeature.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/Globals.h"
 
 #include "objrec/segmentation/RegionSegmentationMethod.h"
 #include "objrec/segmentation/RSMeanShift.h"
@@ -33,11 +31,11 @@
 
 #include "SemSegTools.h" 
 
-#include "objrec/math/cluster/GMM.h"
-#include "objrec/math/cluster/KMeansOnline.h"
+#include "vislearning/math/cluster/GMM.h"
+#include "vislearning/math/cluster/KMeansOnline.h"
 
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-#include "objrec/classifier/fpclassifier/logisticregression/FPCSMLR.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/fpclassifier/logisticregression/FPCSMLR.h"
 
 #include "objrec-froehlichexp/semseg/postsegmentation/PSSImageLevelPrior.h"
 #include "objrec-froehlichexp/semseg/postsegmentation/RelativeLocationPrior.h"

semseg/SemSegLocal.cpp

@@ -5,18 +5,12 @@
 * @date 05/08/2008
 
 */
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
-
 #include <iostream>
 
 #include "SemSegLocal.h"
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-#include "objrec/features/fpfeatures/PixelPairFeature.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/features/fpfeatures/PixelPairFeature.h"
 
 #include "SemSegTools.h" 
 

semseg/SemSegLocal.h

@@ -7,14 +7,8 @@
 */
 #ifndef SEMSEGLOCALINCLUDE
 #define SEMSEGLOCALINCLUDE
-
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
   
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
 #include "SemanticSegmentation.h"
 
 

semseg/SemSegRegionBased.cpp

@@ -6,13 +6,13 @@
 
 #include <iostream>
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-#include "objrec/classifier/fpclassifier/logisticregression/FPCSMLR.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/fpclassifier/logisticregression/FPCSMLR.h"
 
 #include <objrec/iclassifier/icgeneric/CSGeneric.h>
-#include "objrec/features/fpfeatures/PixelPairFeature.h"
-#include "objrec/classifier/genericClassifierSelection.h"
+#include "vislearning/features/fpfeatures/PixelPairFeature.h"
+#include "vislearning/classifier/genericClassifierSelection.h"
 
 #include "SemSegTools.h"
 
@@ -20,18 +20,18 @@
 #include "objrec/segmentation/RSCache.h"
 #include "objrec/segmentation/RSGraphBased.h"
 
-#include "objrec/baselib/Globals.h"
+#include "vislearning/baselib/Globals.h"
 
-#include <objrec/cbaselib/VectorFeature.h>
+#include <vislearning/cbaselib/VectorFeature.h>
 
-#include "objrec/features/fpfeatures/SparseVectorFeature.h"
-#include "objrec/features/localfeatures/LFColorWeijer.h"
-#include "objrec/features/localfeatures/LFColorSande.h"
-#include "objrec/features/localfeatures/LocalFeatureSift.h"
-#include "objrec/features/localfeatures/LocalFeatureOpponnentSift.h"
-#include "objrec/features/localfeatures/LocalFeatureLFInterface.h"
-#include "objrec/features/localfeatures/LocalFeatureRGBSift.h"
-#include "objrec/features/localfeatures/LFCache.h"
+#include "vislearning/features/fpfeatures/SparseVectorFeature.h"
+#include "vislearning/features/localfeatures/LFColorWeijer.h"
+#include "vislearning/features/localfeatures/LFColorSande.h"
+#include "vislearning/features/localfeatures/LocalFeatureSift.h"
+#include "vislearning/features/localfeatures/LocalFeatureOpponnentSift.h"
+#include "vislearning/features/localfeatures/LocalFeatureLFInterface.h"
+#include "vislearning/features/localfeatures/LocalFeatureRGBSift.h"
+#include "vislearning/features/localfeatures/LFCache.h"
 
 #include "objrec/features/regionfeatures/RFColor.h"
 #include "objrec/features/regionfeatures/RFHoG.h"
@@ -41,7 +41,7 @@
 
 #include "objrec/iclassifier/codebook/CodebookRandomForest.h"
 
-#include "objrec/math/cluster/GMM.h"
+#include "vislearning/math/cluster/GMM.h"
 
 #undef DEMO
 #undef WRITEFEATS

semseg/SemSegRegionBased.h

@@ -9,16 +9,16 @@
 
 #include "SemanticSegmentation.h"
 
-#include "objrec/classifier/classifierbase/FeaturePoolClassifier.h"
-#include "objrec/classifier/classifierbase/VecClassifier.h"
+#include "vislearning/classifier/classifierbase/FeaturePoolClassifier.h"
+#include "vislearning/classifier/classifierbase/VecClassifier.h"
 
 #include "objrec/segmentation/RegionSegmentationMethod.h"
 
-#include "objrec/math/mathbase/Featuretype.h"
+#include "vislearning/math/mathbase/Featuretype.h"
 #include "objrec/features/regionfeatures/RegionFeatures.h"
-#include "objrec/features/localfeatures/LocalFeature.h"
+#include "vislearning/features/localfeatures/LocalFeature.h"
 
-#include "objrec/math/ftransform/PCA.h"
+#include "vislearning/math/ftransform/PCA.h"
 
 #include "objrec-froehlichexp/semseg/postsegmentation/PPGraphCut.h"
 
@@ -31,7 +31,7 @@ namespace OBJREC
 			//! destination for saving intermediate steps
 			bool save_cache, read_cache;
 			std::string cache;
-			string classifiercache;
+			std::string classifiercache;
 			
 			//! used ClassNames
 			ClassNames cn;
@@ -98,7 +98,7 @@ namespace OBJREC
 			 * @param rg region graph
 			 * @param feats output features
 			 */
-			void getFeats(const NICE::ColorImage &cimg, const NICE::Matrix &mask, const RegionGraph &rg, vector<vector< FeatureType> > &feats) const;
+			void getFeats(const NICE::ColorImage &cimg, const NICE::Matrix &mask, const RegionGraph &rg, std::vector<std::vector< FeatureType> > &feats) const;
 
 			/**
 			 * computes or reads features and corresponding labels for learnHighLevel()
@@ -108,7 +108,7 @@ namespace OBJREC
 			 * @param examples output examples (including label)
 			 * @param mode mode 1 for examples, mode 0 for VVector
 			 */
-			void computeLF(LabeledSet::Permutation perm, VVector &feats, vector<int> &label, Examples &examples, int mode);
+			void computeLF(LabeledSet::Permutation perm, VVector &feats, std::vector<int> &label, Examples &examples, int mode);
 			
 			/**
 			 * Computes HighLevel Codebooks (i.e. GMM or PCA) if necessary
@@ -120,21 +120,21 @@ namespace OBJREC
 			 * trains the classifier
 			 * @param feats features
 			 */
-			void trainClassifier(vector<vector<FeatureType> > &feats, Examples &examples);
+			void trainClassifier(std::vector<std::vector<FeatureType> > &feats, Examples &examples);
 			
 			/**
 			 * Convert features into examples
 			 * @param feats input features
 			 * @param examples features as examples
 			 */
-			void getExample(const vector<vector<FeatureType> > &feats, Examples &examples);
+			void getExample(const std::vector<std::vector<FeatureType> > &feats, Examples &examples);
 			
 			/**
 			 * create featurepool depending on used features
 			 * @param feats input features
 			 * @param fp feature pool
 			 */
-			void getFeaturePool( const vector<vector<FeatureType> > &feats, FeaturePool &fp);
+			void getFeaturePool( const std::vector<std::vector<FeatureType> > &feats, FeaturePool &fp);
 
 			/**
 			 * classify the given features
@@ -142,14 +142,14 @@ namespace OBJREC
 			 * @param examples examples
 			 * @param probs probability for each region
 			 */
-			void classify(const vector<vector<FeatureType> > &feats, Examples &examples, vector<vector<double> > &probs);
+			void classify(const std::vector<std::vector<FeatureType> > &feats, Examples &examples, std::vector<std::vector<double> > &probs);
 			
 			/**
 			 * set the label of each region the to most probable class
 			 * @param rg 
 			 * @param probs 
 			 */
-			void labelRegions(RegionGraph &rg, vector<vector<double> > &probs);
+			void labelRegions(RegionGraph &rg, std::vector<std::vector<double> > &probs);
 			
 			/**
 			 * set label of each pixel to label of corresponding region
@@ -174,7 +174,7 @@ namespace OBJREC
 			 * @param dim new dimension
 			 * @param fn destination filename
 			 */
-			void initializePCA ( const VVector &feats, PCA &pca, int dim, string &fn );
+			void initializePCA ( const VVector &feats, PCA &pca, int dim, std::string &fn );
 			
 			/**
 			 * transform features using a given pca

semseg/SemSegSTF.cpp

@@ -5,40 +5,31 @@
 * @date 02/11/2008
 
 */
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
-
 #include <iostream>
 
 #include "SemSegSTF.h"
-#include "objrec/baselib/Globals.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/ProgressBar.h"
-#include "objrec/baselib/StringTools.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/baselib/Globals.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/ProgressBar.h"
+#include "core/basics/StringTools.h"
+#include "vislearning/baselib/Globals.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/cbaselib/PascalResults.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/cbaselib/PascalResults.h"
 
-#include "objrec/features/fpfeatures/PixelPairFeature.h"
-#include "objrec/features/fpfeatures/SemanticFeature.h"
+#include "vislearning/features/fpfeatures/PixelPairFeature.h"
+#include "vislearning/features/fpfeatures/SemanticFeature.h"
 
-#include "objrec/features/fpfeatures/FIGradients.h"
+#include "vislearning/features/fpfeatures/FIGradients.h"
 
 #include "FIShotton.h"
 
 #include "SemSegTools.h"
 
 using namespace OBJREC;
-
 using namespace std;
 using namespace NICE;
 
-
-
 SemSegSTF::SemSegSTF( const Config *conf, 
 		    const MultiDataset *md )
     : SemanticSegmentation ( conf, &(md->getClassNames("train")) )

semseg/SemSegSTF.h

@@ -8,16 +8,9 @@
 #ifndef SemSegSTFINCLUDE
 #define SemSegSTFINCLUDE
 
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
- 
 #include "SemanticSegmentation.h"
-#include "objrec/classifier/fpclassifier/randomforest/DecisionNode.h"
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
-
+#include "vislearning/classifier/fpclassifier/randomforest/DecisionNode.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
 
 namespace OBJREC {
 
@@ -38,15 +31,11 @@ class SemSegSTF : public SemanticSegmentation
 
 	bool read_seg_cache;
 	bool read_pixel_cache;
-	// refactor-nice.pl: check this substitution
-	// old: string cacheseg;
+
 	std::string cacheseg;
-	// refactor-nice.pl: check this substitution
-	// old: string cachepixel;
+
 	std::string cachepixel;
 
-	// refactor-nice.pl: check this substitution
-	// old: string resultsdatadir;
 	std::string resultsdatadir;
 
 	double alphaDetectionPrior;
@@ -67,11 +56,11 @@ class SemSegSTF : public SemanticSegmentation
 
 	int backgroundModelType;
 
-	map<DecisionNode *, pair<long, int> > index;
+	std::map<DecisionNode *, std::pair<long, int> > index;
 	FPCRandomForests *fpcSeg;
 	FPCRandomForests *fpcPixel;
 
-	map<string, LocalizationResult *> detresults;
+	std::map<std::string, LocalizationResult *> detresults;
 
 	void fillCachePixel ( CachedExample *ce );
 	void fillCacheSegmentation ( CachedExample *ce );
@@ -85,14 +74,9 @@ class SemSegSTF : public SemanticSegmentation
 	virtual ~SemSegSTF();
 
 	void semanticseg ( CachedExample *ce, 
-			   // refactor-nice.pl: check this substitution
-			   // old: Image & segresult,
 			   NICE::Image & segresult,
 			   NICE::MultiChannelImageT<double> & probabilities );
-
 };
-
-
 } // namespace
 
 #endif

semseg/SemSegTools.h

@@ -8,16 +8,10 @@
 #ifndef SEMSEGTOOLSINCLUDE
 #define SEMSEGTOOLSINCLUDE
 
-#ifdef NOVISUAL
-#include <objrec/nice_nonvis.h>
-#else
-#include <objrec/nice.h>
-#endif
-  
-#include "objrec/baselib/Config.h"
-#include "objrec/cbaselib/MultiDataset.h"
-#include "objrec/cbaselib/Example.h"
-#include "objrec/cbaselib/CachedExample.h"
+#include "core/basics/Config.h"
+#include "vislearning/cbaselib/MultiDataset.h"
+#include "vislearning/cbaselib/Example.h"
+#include "vislearning/cbaselib/CachedExample.h"
 
 
 namespace OBJREC {
@@ -45,7 +39,7 @@ class SemSegTools
 			  const LabeledSet & train,
 			  const ClassNames & cn,
 			  Examples & examples,
-			  vector<CachedExample *> & imgexamples );
+			  std::vector<CachedExample *> & imgexamples );
     
 };
 

semseg/SemanticSegmentation.cpp

@@ -8,14 +8,13 @@
 #include <iostream>
 
 #include "SemanticSegmentation.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/Globals.h"
 
 using namespace OBJREC;
-
 using namespace std;
-
 using namespace NICE;
+
 void SemanticSegmentation::convertLSetToSparseExamples(Examples &examples, LabeledSetVector &lvec)
 {
 	#ifdef DEBUG_PRINTS

semseg/SemanticSegmentation.h

@@ -10,10 +10,10 @@
 
 #include <objrec/nice.h>
  
-#include "objrec/cbaselib/MultiDataset.h"
-#include "objrec/cbaselib/LocalizationResult.h"
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/cbaselib/Example.h"
+#include "vislearning/cbaselib/MultiDataset.h"
+#include "vislearning/cbaselib/LocalizationResult.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/cbaselib/Example.h"
  
 
 namespace OBJREC {
@@ -55,18 +55,18 @@ class SemanticSegmentation
 	    @param probabilities multi-channel image with one channel for each class and
 			         corresponding probabilities for each pixel
 	*/
-	virtual void semanticseg ( CachedExample *ce, 
+	virtual void semanticseg ( OBJREC::CachedExample *ce, 
 			   NICE::Image & segresult,
 			   NICE::MultiChannelImageT<double> & probabilities ) = 0;
 			   
 	/**
 	 * convert different datatypes
 	 */
-	void convertVVectorToExamples(VVector &feats,Examples &examples, vector<int> &label);
-	void convertExamplesToVVector(VVector &feats,Examples &examples, vector<int> &label);
-	void convertExamplesToLSet(Examples &examples, LabeledSetVector &lvec);
-	void convertLSetToExamples(Examples &examples, LabeledSetVector &lvec);
-	void convertLSetToSparseExamples(Examples &examples, LabeledSetVector &lvec);
+	void convertVVectorToExamples(NICE::VVector &feats,OBJREC::Examples &examples, std::vector<int> &label);
+	void convertExamplesToVVector(NICE::VVector &feats,OBJREC::Examples &examples, std::vector<int> &label);
+	void convertExamplesToLSet(OBJREC::Examples &examples, OBJREC::LabeledSetVector &lvec);
+	void convertLSetToExamples(OBJREC::Examples &examples, OBJREC::LabeledSetVector &lvec);
+	void convertLSetToSparseExamples(OBJREC::Examples &examples, OBJREC::LabeledSetVector &lvec);
 
 	
 	/** load img from file call localize(CachedExample *ce) etc. */

semseg/postsegmentation/PPGraphCut.h

@@ -8,19 +8,17 @@
 #ifndef PPGRAPHCUTINCLUDE
 #define PPGRAPHCUTINCLUDE
 
-#include <objrec/nice.h>
-
 #include "core/image/MultiChannelImageT.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/Globals.h"
 
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
 
-#include <objrec/cbaselib/VectorFeature.h>
+#include <vislearning/cbaselib/VectorFeature.h>
 
-#include "objrec/cbaselib/ClassNames.h"
+#include "vislearning/cbaselib/ClassNames.h"
 
 #include "objrec/segmentation/RSMeanShift.h"
 
@@ -100,21 +98,21 @@ class PPGraphCut : public Persistent
 		 * @param mask 
 		 * @param probabilities for each region
 		 */
-		void optimizeImage(RegionGraph &regions, vector<vector<double> > & probabilities);
+		void optimizeImage(OBJREC::RegionGraph &regions, std::vector<std::vector<double> > & probabilities);
 		
 		/**
 		 * load data from an input stream
 		 * @param is input stream
 		 * @param format 
 		 */
-		void restore (istream & is, int format = 0);
+		void restore (std::istream & is, int format = 0);
 		
 		/**
 		 * write data to an output stream
 		 * @param os outputstream
 		 * @param format 
 		 */
-		void store (ostream & os, int format = 0) const;
+		void store (std::ostream & os, int format = 0) const;
 		
 		/**
 		 * clear all informations

semseg/postsegmentation/PPSuperregion.h

@@ -9,24 +9,22 @@
 #ifndef PPSUPERREGIONINCLUDE
 #define PPSUPERREGIONINCLUDE
 
-#include <objrec/nice.h>
-
 #include "core/image/MultiChannelImageT.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/Globals.h"
 
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
 
-#include "objrec/cbaselib/VectorFeature.h"
+#include "vislearning/cbaselib/VectorFeature.h"
 
-#include "objrec/cbaselib/ClassNames.h"
+#include "vislearning/cbaselib/ClassNames.h"
 
 #include "objrec/segmentation/RSMeanShift.h"
 
 #ifdef NICE_USELIB_ICE
-  #include <image_nonvis.h>
+#include <image_nonvis.h>
 #endif
 
 namespace OBJREC {

semseg/postsegmentation/PSSImageLevelPrior.h

@@ -9,7 +9,7 @@
 #define PSSIMAGELEVELPRIORINCLUDE
 
 #include "PostSemSeg.h"
-#include "objrec/math/mathbase/FullVector.h"
+#include "vislearning/math/mathbase/FullVector.h"
 
 
 namespace OBJREC {

semseg/postsegmentation/PSSLocalizationPrior.cpp

@@ -1,145 +0,0 @@
-/** 
-* @file PSSLocalizationPrior.cpp
-* @brief incorporate prior from localization results
-* @author Erik Rodner
-* @date 03/19/2009
-
-*/
-#include <iostream>
-#include <limits>
-
-#include "PSSLocalizationPrior.h"
-#include "objrec/baselib/StringTools.h"
-#include "objrec/baselib/Globals.h"
-#include "objrec/baselib/FileMgt.h"
-#include "objrec/cbaselib/PascalResults.h"
-
-using namespace OBJREC;
-
-using namespace std;
-using namespace NICE;
-
-PSSLocalizationPrior::PSSLocalizationPrior( const std::string & detectiondir, 
-					    const ClassNames *classNames,
-					    double alphaDetectionPrior,
-					    int subsamplex, int subsampley )
-{
-    this->subsamplex = subsampley;
-    this->subsampley = subsamplex;
-    this->alphaDetectionPrior = alphaDetectionPrior;
-    loadDetectionResults ( detectiondir, detresults, classNames );
-}
-
-PSSLocalizationPrior::~PSSLocalizationPrior()
-{
-}
-
-void PSSLocalizationPrior::loadDetectionResults ( const std::string & dir,
-				       map<string, LocalizationResult *> & results,
-				       const ClassNames *classNames )
-{
-    vector<string> files;
-    FileMgt::DirectoryRecursive ( files, dir );
-    int backgroundClassNo = classNames->getBackgroundClass();
-
-    for ( vector<string>::const_iterator i = files.begin();
-	    i != files.end(); i++ )
-    {
-
-	std::string file = *i;
-
-	std::string classtext = StringTools::baseName ( file, false );
-	int classno = classNames->classno(classtext);
-	if ( classno < 0 ) {
-	    fprintf (stderr, "Unable to find class %s\n", classtext.c_str() );
-	    fprintf (stderr, "dir %s file %s classtext %s\n", dir.c_str(),
-		file.c_str(), classtext.c_str() );
-	}
-	PascalResults::read ( results, file, classno, backgroundClassNo, true /*calibrate*/ );
-    }
-}
-
-void PSSLocalizationPrior::postprocess ( NICE::Image & result, NICE::MultiChannelImageT<double> & probabilities )
-{
-    std::string currentFilename = Globals::getCurrentImgFN();
-    std::string base = StringTools::baseName ( currentFilename, false );
-    map<string, LocalizationResult *>::const_iterator i = detresults.find ( base );
-
-    if ( i == detresults.end() )
-    {
-	fprintf (stderr, "NO detection results found for %s !\n", base.c_str());
-	return;
-    }
-
-    fprintf (stderr, "Infering detection prior\n");
-	
-    LocalizationResult *ldet = i->second;
-
-    int maxClassNo = probabilities.numChannels - 1;
-
-    int xsize = probabilities.xsize;
-    int ysize = probabilities.ysize;
-    FullVector *priormap = new FullVector [ xsize * ysize ];
-    for ( long k = 0 ; k < xsize * ysize ; k++ )
-	priormap[k].reinit(maxClassNo);
-
-    for ( LocalizationResult::const_iterator j = ldet->begin();
-					    j != ldet->end();
-					    j++ )
-    {
-	const SingleLocalizationResult *slr = *j;
-
-	int xi, yi, xa, ya;
-	const NICE::Region & r = slr->getRegion();
-	int classno = slr->r->classno;
-	double confidence = slr->r->confidence();
-	r.getRect ( xi, yi, xa, ya );
-
-	for ( int y = yi; y <= ya; y++ )
-	    for ( int x = xi; x <= xa; x++ )
-	    {
-		if ( (y<0) || (x<0) || (x>xsize-1) || (y>ysize-1) )
-		    continue;
-		if ( r.inside ( x*subsamplex, y*subsampley ) )
-		    priormap[x + y*xsize][classno] += confidence;
-	    }
-
-	long k = 0;
-	for ( int y = 0 ; y < ysize ; y++ )
-	    for ( int x = 0 ; x < xsize ; x++,k++ )
-	    {
-		FullVector & prior  = priormap[k];
-
-		if ( prior.sum() < 10e-6 )
-		    continue;
-
-		prior.normalize();
-
-		double sum = 0.0;
-		for ( int i = 0 ; i < (int)probabilities.numChannels; i++ )
-		{
-		    probabilities.data[i][k] *= pow ( prior[i], alphaDetectionPrior ); 
-		    sum += probabilities.data[i][k];
-		}
-
-		if ( sum < 10e-6 )
-		    continue;
-
-		int maxindex = 0;
-		double maxvalue = - numeric_limits<double>::max();
-		for ( int i = 0 ; i < (int)probabilities.numChannels; i++ )
-		{
-		    probabilities.data[i][k] /= sum;
-		    if ( probabilities.data[i][k] > maxvalue )
-		    {
-			maxindex = i;
-			maxvalue = probabilities.data[i][k];
-		    }
-		}
-		result.setPixel(x,y,maxindex);
-	    }
-	
-    }
-
-    delete [] priormap;
-}

semseg/postsegmentation/PSSLocalizationPrior.h

@@ -1,50 +0,0 @@
-/** 
-* @file PSSLocalizationPrior.h
-* @brief incorporate prior from localization results
-* @author Erik Rodner
-* @date 03/19/2009
-
-*/
-#ifndef PSSLOCALIZATIONPRIORINCLUDE
-#define PSSLOCALIZATIONPRIORINCLUDE
-
-
-#include "objrec/cbaselib/LocalizationResult.h"
-#include "PostSemSeg.h"
-
-
-namespace OBJREC {
-
-/** incorporate prior from localization results */
-class PSSLocalizationPrior : public PostSemSeg
-{
-
-    protected:
-	int subsamplex;
-	int subsampley;
-	double alphaDetectionPrior;
-	map<string, LocalizationResult *> detresults;
-
-	void loadDetectionResults ( const std::string & dir,
-			       map<string, LocalizationResult *> & results,
-			       const ClassNames *classNames );
-
-    public:
-  
-	/** simple constructor */
-	PSSLocalizationPrior( const std::string & detectiondir, const ClassNames *classNames,
-			      double alphaDetectionPrior,  int subsamplex = 1, int subsampley = 1 );
-      
-	/** simple destructor */
-	virtual ~PSSLocalizationPrior();
-
-	virtual void postprocess ( NICE::Image & result, NICE::MultiChannelImageT<double> & probabilities );
-
-
-     
-};
-
-
-} // namespace
-
-#endif

semseg/postsegmentation/RelativeLocationPrior.h

@@ -8,20 +8,18 @@
 #ifndef RELATIVELOCATIONPRIORINCLUDE
 #define RELATIVELOCATIONPRIORINCLUDE
 
-#include <objrec/nice.h>
-
 #include "core/image/MultiChannelImageT.h"
 
-#include "objrec/cbaselib/CachedExample.h"
-#include "objrec/baselib/Preprocess.h"
-#include "objrec/baselib/Globals.h"
+#include "vislearning/cbaselib/CachedExample.h"
+#include "vislearning/baselib/Preprocess.h"
+#include "vislearning/baselib/Globals.h"
 
-#include "objrec/classifier/fpclassifier/logisticregression/SLR.h"
-#include "objrec/classifier/fpclassifier/randomforest/FPCRandomForests.h"
+#include "vislearning/classifier/fpclassifier/logisticregression/SLR.h"
+#include "vislearning/classifier/fpclassifier/randomforest/FPCRandomForests.h"
 
-#include "objrec/features/fpfeatures/SparseVectorFeature.h"
+#include "vislearning/features/fpfeatures/SparseVectorFeature.h"
 
-#include "objrec/cbaselib/ClassNames.h"
+#include "vislearning/cbaselib/ClassNames.h"
 
 namespace OBJREC {
 
@@ -30,7 +28,7 @@ class RelativeLocationPrior : public Persistent
 
 	protected:
 		//! the priormaps
-		vector<NICE::MultiChannelImageT<double> *> priormaps;
+		std::vector<NICE::MultiChannelImageT<double> *> priormaps;
 		
 		//! the configfile
 		const Config *conf;
@@ -48,7 +46,7 @@ class RelativeLocationPrior : public Persistent
 		Examples trainingsdata;
 		
 		//! the one vs all sparse logistic classifiers
-		vector<SLR> classifiers;
+		std::vector<SLR> classifiers;
     
 		//! dimension of the features
 		int featdim;
@@ -116,14 +114,14 @@ class RelativeLocationPrior : public Persistent
 		 * @param is input stream
 		 * @param format 
 		 */
-		void restore (istream & is, int format = 0);
+		void restore (std::istream & is, int format = 0);
 		
 		/**
 		 * write data to an output stream
 		 * @param os outputstream
 		 * @param format 
 		 */
-		void store (ostream & os, int format = 0) const;
+		void store (std::ostream & os, int format = 0) const;
 		
 		/**
 		 * clear all informations

semseg/postsegmentation/libdepend.inc

@@ -1,3 +1,4 @@
 $(call PKG_DEPEND_EXT,ICE)
 $(call PKG_DEPEND_INT,objrec/cbaselib)
-$(call PKG_DEPEND_INT,objrec/mrf)
+$(call PKG_DEPEND_INT,objrec/mrf)
+$(call PKG_DEPEND_INT,core)