REFAC: use an ImageToListSampleAdaptor

Modules/Radiometry/Simulation/test/otbImageSimulationMethodSVMClassif.cxx

@@ -32,6 +32,7 @@
 #include "otbLibSVMMachineLearningModel.h"
 #include "otbImageClassificationFilter.h"
 #include "otbImageFileReader.h"
+#include "itkImageToListSampleAdaptor.h"
 
 int otbImageSimulationMethodSVMClassif(int itkNotUsed(argc), char * argv[])
 {
@@ -138,38 +139,18 @@ int otbImageSimulationMethodSVMClassif(int itkNotUsed(argc), char * argv[])
    //~ svmEstimator->DoProbabilityEstimates(true);
    //~ svmEstimator->Update();
 
-   OutputImageType::Pointer outReflectance = imageSimulation->GetOutputReflectanceImage();
-   LabelImageType::Pointer outLabels = imageSimulation->GetOutputLabelImage();
-
-  typedef SVMType::InputListSampleType InputListSampleType;
-  typedef SVMType::TargetListSampleType TargetListSampleType;
-  InputListSampleType::Pointer inputSamples = InputListSampleType::New();
-  TargetListSampleType::Pointer trainSamples = TargetListSampleType::New();
-  inputSamples->SetMeasurementVectorSize(nbBands);
-  trainSamples->SetMeasurementVectorSize(1);
-  itk::ImageRegionConstIterator<OutputImageType> itIn(outReflectance,outReflectance->GetLargestPossibleRegion() );
-  itk::ImageRegionConstIterator<LabelImageType> itLabel(outLabels, outLabels->GetLargestPossibleRegion());
-  itIn.GoToBegin();
-  itLabel.GoToBegin();
-  while (!itIn.IsAtEnd())
-    {
-    SVMType::InputSampleType sample;
-    SVMType::TargetSampleType target;
-    sample.SetSize(nbBands);
-    for (unsigned int i=0 ; i<nbBands ; i++)
-      {
-      sample[i] = itIn.Get()[i];
-      }
-    target[0] = itLabel.Value();
-    inputSamples->PushBack(sample);
-    trainSamples->PushBack(target);
-    ++itIn;
-    ++itLabel;
-    }
-
-  model->SetInputListSample(inputSamples);
-  model->SetTargetListSample(trainSamples);
-  model->DoProbabilityEstimates(true);
+  typedef itk::Statistics::ImageToListSampleAdaptor<OutputImageType> ListSampleAdaptorType;
+  typedef itk::Statistics::ImageToListSampleAdaptor<LabelImageType> TargetListSampleAdaptorType;
+
+  ListSampleAdaptorType::Pointer listSample = ListSampleAdaptorType::New();
+  listSample->SetImage(imageSimulation->GetOutputReflectanceImage());
+
+  TargetListSampleAdaptorType::Pointer targetListSample = TargetListSampleAdaptorType::New();
+  targetListSample->SetImage(imageSimulation->GetOutputLabelImage());
+
+  model->SetInputListSample(listSample);
+  model->SetTargetListSample(targetListSample);
+  model->SetDoProbabilityEstimates(true);
   model->Train();
   
    classifier->SetModel(model);