ENH: use only one template parameter in VectorPrediction

Modules/Applications/AppClassification/app/otbVectorClassifier.cxx

@@ -25,7 +25,7 @@ namespace otb
 namespace Wrapper
 {
 
-using VectorClassifier = VectorPrediction<false, float, unsigned int>;
+using VectorClassifier = VectorPrediction<false>;
 
 template<>
 void

Modules/Applications/AppClassification/app/otbVectorRegression.cxx

@@ -25,7 +25,7 @@ namespace otb
 namespace Wrapper
 {
 
-using VectorRegression = VectorPrediction<true, float, float>;
+using VectorRegression = VectorPrediction<true>;
 
 template<>
 void

Modules/Applications/AppClassification/include/otbVectorPrediction.h

@@ -44,7 +44,7 @@ namespace otb
 namespace Wrapper
 {
 
-template <bool RegressionMode, class ValueType, class LabelType>
+template <bool RegressionMode>
 class VectorPrediction : public Application
 {
 public:
@@ -60,8 +60,10 @@ public:
   itkTypeMacro(Self, Application)
 
   /** Filters typedef */
-  //typedef float                                         ValueType;
-  //typedef unsigned int                                  LabelType;
+  typedef float                                                         ValueType;
+  // Label type is float for regression and unsigned int for classification 
+  typedef typename std::conditional<RegressionMode, float, unsigned int>::type   LabelType;
+  
   typedef itk::FixedArray<LabelType,1>                  LabelSampleType;
   typedef itk::Statistics::ListSample<LabelSampleType>  LabelListSampleType;
 

Modules/Applications/AppClassification/include/otbVectorPrediction.hxx

@@ -26,18 +26,18 @@ namespace otb
 namespace Wrapper
 {
 
-template <bool RegressionMode, class ValueType, class LabelType>
+template <bool RegressionMode>
 void
-VectorPrediction <RegressionMode, ValueType, LabelType>
+VectorPrediction <RegressionMode>
 ::DoInit()
 {
   DoInitSpecialization();
   //TODO add assert to check that parameters has been correctly defined
 }
 
-template <bool RegressionMode, class ValueType, class LabelType>
+template <bool RegressionMode>
 void
-VectorPrediction <RegressionMode, ValueType, LabelType>
+VectorPrediction <RegressionMode>
 ::DoUpdateParameters()
 {
   if ( HasValue("in") )
@@ -72,9 +72,9 @@ VectorPrediction <RegressionMode, ValueType, LabelType>
   }
 }
 
-template <bool RegressionMode, class ValueType, class LabelType>
+template <bool RegressionMode>
 void
-VectorPrediction <RegressionMode, ValueType, LabelType>
+VectorPrediction <RegressionMode>
 ::DoExecute()
 {
   clock_t tic = clock();
@@ -161,7 +161,7 @@ VectorPrediction <RegressionMode, ValueType, LabelType>
   m_Model->Load(GetParameterString("model"));
   otbAppLogINFO("Model loaded");
 
-  typename ListSampleType::Pointer listSample = trainingShiftScaleFilter->GetOutput();
+  ListSampleType::Pointer listSample = trainingShiftScaleFilter->GetOutput();
 
   typename ConfidenceListSampleType::Pointer quality;