diff --git a/Examples/Learning/SVMPointSetExample.cxx b/Examples/Learning/SVMPointSetExample.cxx
index a9b50d9a1292a05cec85f7278a4eadb2bff3ce23..f24906e16bd82f97a5e205238e033fdb12d9ebc3 100644
--- a/Examples/Learning/SVMPointSetExample.cxx
+++ b/Examples/Learning/SVMPointSetExample.cxx
@@ -64,7 +64,8 @@ int main( int argc, char* argv[] )
LabelPointsContainer::Pointer lCont = LabelPointsContainer::New();
/* We learn the y>x | y<x boundary*/
- srand((unsigned)time(0));
+// srand((unsigned)time(0));
+ srand(0);
int lowest = 0;
int range = 1000;
diff --git a/Testing/Code/Learning/SVMPointSetExample.cxx b/Testing/Code/Learning/SVMPointSetExample.cxx
deleted file mode 100755
index c70d91e5731bf0da7b30af9f1ab2ce10a6416b77..0000000000000000000000000000000000000000
--- a/Testing/Code/Learning/SVMPointSetExample.cxx
+++ /dev/null
@@ -1,241 +0,0 @@
-/*=========================================================================
-
- Program: ORFEO Toolbox
- Language: C++
- Date: $Date$
- Version: $Revision$
-
-
- Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
- See OTBCopyright.txt for details.
-
-
- This software is distributed WITHOUT ANY WARRANTY; without even
- the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
- PURPOSE. See the above copyright notices for more information.
-
-=========================================================================*/
-
-#if defined(_MSC_VER)
-#pragma warning ( disable : 4786 )
-#endif
-
-#define MAIN
-
-
-#include "itkExceptionObject.h"
-#include "itkPointSet.h"
-#include <iostream>
-#include <cstdlib>
-
-#include "otbSVMPointSetModelEstimator.h"
-#include "itkPointSetToListAdaptor.h"
-#include "itkListSample.h"
-#include "otbSVMClassifier.h"
-
-
-
-int main( int argc, char* argv[] )
-{
-
-
- typedef float InputPixelType;
-
- typedef std::vector<InputPixelType> InputVectorType;
- typedef int LabelPixelType;
- const unsigned int Dimension = 2;
-
- typedef itk::PointSet< InputVectorType, Dimension >
- MeasurePointSetType;
-
- typedef itk::PointSet< LabelPixelType, Dimension > LabelPointSetType;
-
-
- MeasurePointSetType::Pointer mPSet = MeasurePointSetType::New();
- LabelPointSetType::Pointer lPSet = LabelPointSetType::New();
-
-
- typedef MeasurePointSetType::PointType MeasurePointType;
- typedef LabelPointSetType::PointType LabelPointType;
-
- typedef MeasurePointSetType::PointsContainer MeasurePointsContainer;
- typedef LabelPointSetType::PointsContainer LabelPointsContainer;
-
- MeasurePointsContainer::Pointer mCont = MeasurePointsContainer::New();
- LabelPointsContainer::Pointer lCont = LabelPointsContainer::New();
-
- /* We learn the y>x | y<x boundary*/
-// srand((unsigned)time(0));
- srand(0);
- int lowest = 0;
- int range = 1000;
-
- for(unsigned int pointId = 0; pointId<500; pointId++)
- {
-
- MeasurePointType mP;
- LabelPointType lP;
-
- int x_coord = lowest+static_cast<int>(range*(rand()/(RAND_MAX + 1.0)));
- int y_coord = lowest+static_cast<int>(range*(rand()/(RAND_MAX + 1.0)));
-
- std::cout << "coords : " << x_coord << " " << y_coord << std::endl;
- mP[0] = x_coord;
- mP[1] = y_coord;
-
- lP[0] = x_coord;
- lP[1] = y_coord;
-
-
- InputVectorType measure;
- measure.push_back(static_cast<InputPixelType>((x_coord*1.0-lowest)/range));
- measure.push_back(static_cast<InputPixelType>((y_coord*1.0-lowest)/range));
-
- LabelPixelType label;
-
- if(x_coord < y_coord)
- label= -1;
- else
- label = 1;
-
- std::cout << "Label : " << label << std::endl;
- std::cout << "Measures : " << measure[0] << " " << measure[1] << std::endl;
-
- mCont->InsertElement( pointId , mP );
- mPSet->SetPointData( pointId, measure );
-
-
- lCont->InsertElement( pointId , lP );
- lPSet->SetPointData( pointId, label );
-
-
- }
-
- mPSet->SetPoints( mCont );
- lPSet->SetPoints( lCont );
-
- typedef otb::SVMPointSetModelEstimator< MeasurePointSetType,
- LabelPointSetType > EstimatorType;
-
-
- EstimatorType::Pointer estimator = EstimatorType::New();
-
- estimator->SetInputPointSet( mPSet );
- estimator->SetTrainingPointSet( lPSet );
- estimator->SetNumberOfClasses( 2 );
-
-
- estimator->Update();
-
- std::cout << "Saving model" << std::endl;
- estimator->SaveModel("model.svm");
-
-
- // Build the test set
-
- MeasurePointSetType::Pointer tPSet = MeasurePointSetType::New();
- MeasurePointsContainer::Pointer tCont = MeasurePointsContainer::New();
-
- for(unsigned int pointId = 0; pointId<100; pointId++)
- {
-
- MeasurePointType tP;
-
- int x_coord = lowest+static_cast<int>(range*(rand()/(RAND_MAX + 1.0)));
- int y_coord = lowest+static_cast<int>(range*(rand()/(RAND_MAX + 1.0)));
-
- std::cout << "coords : " << x_coord << " " << y_coord << std::endl;
- tP[0] = x_coord;
- tP[1] = y_coord;
-
-
- InputVectorType measure;
- measure.push_back(static_cast<InputPixelType>((x_coord*1.0-lowest)/range));
- measure.push_back(static_cast<InputPixelType>((y_coord*1.0-lowest)/range));
-
-
- std::cout << "Measures : " << measure[0] << " " << measure[1] << std::endl;
-
- tCont->InsertElement( pointId , tP );
- tPSet->SetPointData( pointId, measure );
-
- }
-
- tPSet->SetPoints( tCont );
-
- // Classify
-
- typedef itk::Statistics::PointSetToListAdaptor< MeasurePointSetType >
- SampleType;
- SampleType::Pointer sample = SampleType::New();
- sample->SetPointSet( tPSet );
-
- std::cout << "Sample set to Adaptor" << std::endl;
-
-
- /** preparing classifier and decision rule object */
- typedef otb::SVMModel< SampleType::MeasurementVectorType::ValueType, LabelPixelType > ModelType;
-
- ModelType::Pointer model = estimator->GetModel();
-
- int numberOfClasses = model->GetNumberOfClasses();
-
- std::cout << "Classification for " << numberOfClasses << " classes " << std::endl;
-
- typedef otb::SVMClassifier< SampleType, LabelPixelType > ClassifierType ;
-
- ClassifierType::Pointer classifier = ClassifierType::New() ;
-
- classifier->SetNumberOfClasses(numberOfClasses) ;
- classifier->SetModel( model );
- classifier->SetSample(sample.GetPointer()) ;
- classifier->Update() ;
-
- /* Build the class map */
-
- std::cout << "classifier get output" << std::endl;
- ClassifierType::OutputType* membershipSample =
- classifier->GetOutput() ;
- std::cout << "Sample iterators" << std::endl;
- ClassifierType::OutputType::ConstIterator m_iter =
- membershipSample->Begin() ;
- ClassifierType::OutputType::ConstIterator m_last =
- membershipSample->End() ;
-
-
- double error = 0.0;
- unsigned int pointId = 0;
- while (m_iter != m_last)
- {
- ClassifierType::ClassLabelType label = m_iter.GetClassLabel();
-
- InputVectorType measure;
-
- tPSet->GetPointData(pointId, &measure);
-
- ClassifierType::ClassLabelType expectedLabel;
- if(measure[0] < measure[1])
- expectedLabel= -1;
- else
- expectedLabel = 1;
-
- double dist = fabs(measure[0] - measure[1]);
-
- if(label != expectedLabel )
- error++;
-
- std::cout << int(label) << "/" << int(expectedLabel) << " --- " << dist << std::endl;
-
-
- ++pointId;
- ++m_iter ;
- }
-
- std::cout << "Error = " << error/pointId << std::endl;
-
-
-
- return EXIT_SUCCESS;
-}
-
-