COMP: forgot to push LibSVM classes

Code/UtilitiesAdapters/OpenCV/otbLibSVMMachineLearningModel.h

+/*=========================================================================
+
+  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.
+
+=========================================================================*/
+#ifndef __otbSVMMachineLearningModel_h
+#define __otbSVMMachineLearningModel_h
+
+#include "itkLightObject.h"
+#include "itkVariableLengthVector.h"
+#include "itkFixedArray.h"
+#include "itkListSample.h"
+#include "otbMachineLearningModel.h"
+
+//include opencv
+//#include <opencv.hpp>       // opencv general include file
+//#include <ml/ml.hpp>		  // opencv machine learning include file
+
+// SVM estimator
+#include "otbSVMSampleListModelEstimator.h"
+// Validation
+#include "otbSVMClassifier.h"
+
+namespace otb
+{
+template <class TInputValue, class TTargetValue>
+class ITK_EXPORT LibSVMMachineLearningModel
+  : public MachineLearningModel <TInputValue, TTargetValue>
+{
+public:
+  /** Standard class typedefs. */
+  typedef LibSVMMachineLearningModel           Self;
+  typedef MachineLearningModel<TInputValue, TTargetValue> Superclass;
+  typedef itk::SmartPointer<Self>                         Pointer;
+  typedef itk::SmartPointer<const Self>                   ConstPointer;
+
+  // Input related typedefs
+  typedef TInputValue                                     InputValueType;
+  typedef itk::VariableLengthVector<InputValueType>       InputSampleType;
+  typedef itk::Statistics::ListSample<InputSampleType>    InputListSampleType;
+
+  // Target related typedefs
+  typedef TTargetValue                                    TargetValueType;
+  typedef itk::FixedArray<TargetValueType,1>              TargetSampleType;
+  typedef itk::Statistics::ListSample<TargetSampleType>   TargetListSampleType;
+
+  // LibSVM related typedefs
+  typedef otb::Functor::VariableLengthVectorToMeasurementVectorFunctor<InputSampleType> MeasurementVectorFunctorType;
+  typedef otb::SVMSampleListModelEstimator<InputListSampleType, TargetListSampleType, MeasurementVectorFunctorType>
+      SVMEstimatorType;
+
+  typedef otb::SVMClassifier<InputSampleType, TargetValueType> ClassifierType;
+
+  /** Run-time type information (and related methods). */
+  itkNewMacro(Self);
+  itkTypeMacro(SVMMachineLearningModel, itk::MachineLearningModel);
+
+  /** Train the machine learning model */
+  virtual void Train();
+
+  /** Predict values using the model */
+  virtual TargetSampleType Predict(const InputSampleType & input) const;
+
+  /** Save the model to file */
+  virtual void Save(char * filename, const char * name=0);
+
+  /** Load the model from file */
+  virtual void Load(char * filename, const char * name=0);
+
+  /** Determine the file type. Returns true if this ImageIO can read the
+   * file specified. */
+  virtual bool CanReadFile(const char*);
+
+  /** Determine the file type. Returns true if this ImageIO can write the
+   * file specified. */
+  virtual bool CanWriteFile(const char*);
+  //Setters/Getters to SVM model
+  // itkGetMacro(SVMType, int);
+  // itkSetMacro(SVMType, int);
+
+  itkGetMacro(KernelType, int);
+  itkSetMacro(KernelType, int);
+
+  itkGetMacro(C, float);
+  itkSetMacro(C, float);
+
+  itkGetMacro(ParameterOptimization, bool);
+  itkSetMacro(ParameterOptimization, bool);
+
+  // itkGetMacro(Epsilon, int);
+  // itkSetMacro(Epsilon, int);
+
+protected:
+  /** Constructor */
+  LibSVMMachineLearningModel();
+
+  /** Destructor */
+  virtual ~LibSVMMachineLearningModel();
+
+  /** PrintSelf method */
+  void PrintSelf(std::ostream& os, itk::Indent indent) const;
+
+private:
+  LibSVMMachineLearningModel(const Self &); //purposely not implemented
+  void operator =(const Self&); //purposely not implemented
+
+  int m_KernelType;
+  float m_C;
+  bool m_ParameterOptimization;
+  typename SVMEstimatorType::Pointer m_SVMestimator;
+};
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbLibSVMMachineLearningModel.txx"
+#endif
+
+#endif

Code/UtilitiesAdapters/OpenCV/otbLibSVMMachineLearningModel.txx

+/*=========================================================================
+
+  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.
+
+=========================================================================*/
+#ifndef __otbLibSVMMachineLearningModel_txx
+#define __otbLibSVMMachineLearningModel_txx
+
+#include "otbLibSVMMachineLearningModel.h"
+//#include "otbOpenCVUtils.h"
+
+// SVM estimator
+//#include "otbSVMSampleListModelEstimator.h"
+
+namespace otb
+{
+
+template <class TInputValue, class TOutputValue>
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::LibSVMMachineLearningModel()
+{
+  // m_SVMModel = new CvSVM;
+  // m_SVMType = CvSVM::C_SVC;
+  m_KernelType = LINEAR;
+  // m_TermCriteriaType = CV_TERMCRIT_ITER;
+  m_C = 1.0;
+  // m_Epsilon = 1e-6;
+  m_ParameterOptimization = false;
+  m_SVMestimator = SVMEstimatorType::New();
+}
+
+
+template <class TInputValue, class TOutputValue>
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::~LibSVMMachineLearningModel()
+{
+  //delete m_SVMModel;
+}
+
+/** Train the machine learning model */
+template <class TInputValue, class TOutputValue>
+void
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::Train()
+{
+  // Set up SVM's parameters
+  // CvSVMParams params;
+  // params.svm_type    = m_SVMType;
+  // params.kernel_type = m_KernelType;
+  // params.term_crit   = cvTermCriteria(m_TermCriteriaType, m_MaxIter, m_Epsilon);
+
+  // // Train the SVM
+
+  m_SVMestimator->SetC(m_C);
+  m_SVMestimator->SetKernelType(m_KernelType);
+  m_SVMestimator->SetParametersOptimization(m_ParameterOptimization);
+
+  m_SVMestimator->SetInputSampleList(this->GetInputListSample());
+  m_SVMestimator->SetTrainingSampleList(this->GetTargetListSample());
+
+  m_SVMestimator->Update();
+}
+
+template <class TInputValue, class TOutputValue>
+typename LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::TargetSampleType
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::Predict(const InputSampleType & input) const
+{
+  TargetSampleType target;
+
+  otbMsgDevMacro(<< "Starting iterations ");
+
+  MeasurementVectorFunctorType mfunctor;
+
+  target = m_SVMestimator->GetModel()->EvaluateLabel(mfunctor(input));
+
+  return target;
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::Save(char * filename, const char * name)
+{
+  m_SVMestimator->GetModel()->SaveModel(filename);
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::Load(char * filename, const char * name)
+{
+  m_SVMestimator->GetModel()->LoadModel(filename);
+}
+
+template <class TInputValue, class TOutputValue>
+bool
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::CanReadFile(const char * file)
+{
+  return false;
+}
+
+template <class TInputValue, class TOutputValue>
+bool
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::CanWriteFile(const char * file)
+{
+  return false;
+}
+
+template <class TInputValue, class TOutputValue>
+void
+LibSVMMachineLearningModel<TInputValue,TOutputValue>
+::PrintSelf(std::ostream& os, itk::Indent indent) const
+{
+  // Call superclass implementation
+  Superclass::PrintSelf(os,indent);
+}
+
+} //end namespace otb
+
+#endif