MRG

Code/Learning/otbConfusionMatrixCalculator.h

@@ -56,6 +56,8 @@ public:
   typedef TProdListLabel                          ProdListLabelType;
   typedef typename ProdListLabelType::Pointer     ProdListLabelPointerType;
 
+  typedef int                                     ClassLabelType;
+
   /** Type for the confusion matrix */
   typedef itk::VariableSizeMatrix<double>         ConfusionMatrixType;
   
@@ -73,6 +75,11 @@ public:
   itkGetMacro(NumberOfSamples, unsigned long);
   itkGetMacro(ConfusionMatrix, ConfusionMatrixType);
   
+  std::map<ClassLabelType, int> GetMapOfClasses() const
+  {
+    return m_MapOfClasses;
+  }
+
 protected:
   ConfusionMatrixCalculator();
   virtual ~ConfusionMatrixCalculator() {}
@@ -88,7 +95,7 @@ private:
   double                    m_KappaIndex;
   double                    m_OverallAccuracy;
 
-  std::map<int,int>         m_MapOfClasses;
+  std::map<ClassLabelType, int> m_MapOfClasses;
 
   unsigned short            m_NumberOfClasses;
   unsigned long             m_NumberOfSamples;

Code/Learning/otbConfusionMatrixCalculator.txx

@@ -66,8 +66,7 @@ ConfusionMatrixCalculator<TRefListLabel,TProdListLabel>
 
   m_NumberOfSamples = m_ReferenceLabels->Size();
   
-  // count de number of classes
-
+  // count the number of classes
   int countClasses = 0;
    while( refIterator != m_ReferenceLabels->End() )
     {

Code/Learning/otbListSampleGenerator.h

@@ -61,8 +61,7 @@ public:
   itkNewMacro(Self);
   
   typedef TImage      ImageType;
-  typedef TVectorData VectorDataType;
-  
+  typedef TVectorData VectorDataType;  
   typedef typename VectorDataType::Pointer VectorDataPointerType;
   
   typedef itk::PreOrderTreeIterator<typename VectorDataType::DataTreeType> TreeIteratorType;
@@ -73,7 +72,8 @@ public:
   typedef typename ListSampleType::Pointer        ListSamplePointerType;
   
   /** List to store the corresponding labels */
-  typedef itk::FixedArray<int, 1>                 LabelType; //note could be templated by an std:::string
+  typedef int                                     ClassLabelType;
+  typedef itk::FixedArray<ClassLabelType, 1>      LabelType; //note could be templated by an std:::string
   typedef itk::Statistics::ListSample<LabelType>  ListLabelType;
   typedef typename ListLabelType::Pointer         ListLabelPointerType;
   
@@ -102,7 +102,7 @@ public:
   itkSetClampMacro(ValidationTrainingProportion, double, 0.0, 1.0);
 
   itkGetConstMacro(NumberOfClasses, unsigned short);
-  typedef std::map<int, int> SampleNumberType;
+  typedef std::map<ClassLabelType, int> SampleNumberType;
 
   SampleNumberType GetClassesSamplesNumberTraining(void) const
   {
@@ -151,12 +151,12 @@ private:
   ListLabelPointerType  m_ValidationListLabel;
   
   
-  std::map<int, double> m_ClassesSize;
-  std::map<int, double> m_ClassesProbTraining;
-  std::map<int, double> m_ClassesProbValidation;
+  std::map<ClassLabelType, double> m_ClassesSize;
+  std::map<ClassLabelType, double> m_ClassesProbTraining;
+  std::map<ClassLabelType, double> m_ClassesProbValidation;
   
-  std::map<int, int> m_ClassesSamplesNumberTraining; //Just a counter
-  std::map<int, int> m_ClassesSamplesNumberValidation; //Just a counter
+  std::map<ClassLabelType, int> m_ClassesSamplesNumberTraining; //Just a counter
+  std::map<ClassLabelType, int> m_ClassesSamplesNumberValidation; //Just a counter
   
   typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
   RandomGeneratorType::Pointer m_RandomGenerator;

Code/Learning/otbListSampleGenerator.txx

@@ -228,7 +228,7 @@ ListSampleGenerator<TImage,TVectorData>
   
   //Go throught the classes size to find the smallest one
   double minSizeTraining = -1;
-  for (std::map<int, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
+  for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
     {
     if ((minSizeTraining < 0) || (minSizeTraining > itmap->second))
       {
@@ -254,11 +254,11 @@ ListSampleGenerator<TImage,TVectorData>
     }
   
   //Compute the probability selection for each class
-  for (std::map<int, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
+  for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
     {
     m_ClassesProbTraining[itmap->first] = minSizeTraining / itmap->second;
     }
-  for (std::map<int, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
+  for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
     {
     m_ClassesProbValidation[itmap->first] = minSizeValidation / itmap->second;
     }
@@ -280,7 +280,8 @@ ListSampleGenerator<TImage,TVectorData>
     }
   else
     {
-    for (std::map<int, double>::const_iterator itmap = m_ClassesSize.begin(); itmap != m_ClassesSize.end(); ++itmap)
+    for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesSize.begin();
+         itmap != m_ClassesSize.end(); ++itmap)
       {
       os << indent << itmap->first << ": " << itmap->second << "\n";
       }
@@ -294,13 +295,13 @@ ListSampleGenerator<TImage,TVectorData>
   else
     {
     os << indent << "** Selection probability:\n";
-    for (std::map<int, double>::const_iterator itmap = m_ClassesProbTraining.begin();
+    for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesProbTraining.begin();
         itmap != m_ClassesProbTraining.end(); ++itmap)
       {
       os << indent << itmap->first << ": " << itmap->second << "\n";
       }
     os << indent << "** Number of selected samples:\n";
-    for (std::map<int, int>::const_iterator itmap = m_ClassesSamplesNumberTraining.begin();
+    for (std::map<ClassLabelType, int>::const_iterator itmap = m_ClassesSamplesNumberTraining.begin();
         itmap != m_ClassesSamplesNumberTraining.end(); ++itmap)
       {
       os << indent << itmap->first << ": " << itmap->second << "\n";
@@ -315,13 +316,13 @@ ListSampleGenerator<TImage,TVectorData>
   else
     {
     os << indent << "** Selection probability:\n";
-    for (std::map<int, double>::const_iterator itmap = m_ClassesProbValidation.begin();
+    for (std::map<ClassLabelType, double>::const_iterator itmap = m_ClassesProbValidation.begin();
         itmap != m_ClassesProbValidation.end(); ++itmap)
       {
       os << indent << itmap->first << ": " << itmap->second << "\n";
       }
     os << indent << "** Number of selected samples:\n";
-    for (std::map<int, int>::const_iterator itmap = m_ClassesSamplesNumberValidation.begin();
+    for (std::map<ClassLabelType, int>::const_iterator itmap = m_ClassesSamplesNumberValidation.begin();
         itmap != m_ClassesSamplesNumberValidation.end(); ++itmap)
       {
       os << indent << itmap->first << ": " << itmap->second << "\n";