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/*=========================================================================
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 otbSVMClassifier_h
#define otbSVMClassifier_h
#include "vcl_deprecated_header.h"
#include "itkSampleClassifierFilter.h"
#include "otbSVMModel.h"
#include "itkVectorImage.h"
#include "itkListSample.h"
namespace otb
{
/** \class SVMClassifier
* \brief SVM-based classifier
*
* The first template argument is the type of the target sample data
* that this classifier will assign a class label for each measurement
* vector. The second one is the pixel type of the labels to be
* produced by the classifier.
*
* Before you call the GenerateData method to start the classification
* process, you should plug in all necessary parts ( a SVM model and a
* target sample data).
*
* The classification result is stored in a vector of Subsample object.
* Each class has its own class sample (Subsample object) that has
* InstanceIdentifiers for all measurement vectors belong to the class.
* The InstanceIdentifiers come from the target sample data. Therefore,
* the Subsample objects act as separate class masks.
*
* \deprecated
*
* \sa MachineLearningModel
* \sa LibSVMMachineLearningModel
* \sa ImageClassificationFilter
*
*
* \ingroup OTBSVMLearning
*/
template<class TSample, class TLabel>
class ITK_EXPORT SVMClassifier :
public itk::Statistics::SampleClassifierFilter<TSample>
{
public:
/** Standard class typedef*/
typedef SVMClassifier Self;
typedef itk::Statistics::SampleClassifierFilter<TSample> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macros */
itkTypeMacro(SVMClassifier, itk::Statistics::SampleClassifier);
itkNewMacro(Self);
/** Output type for GetClassSample method */
typedef itk::Statistics::MembershipSample<TSample> OutputType;
typedef itk::VariableLengthVector<float> HyperplanesDistancesType;
typedef itk::Statistics::ListSample<HyperplanesDistancesType> HyperplanesDistancesListSampleType;
/** typedefs from TSample object */
typedef typename TSample::MeasurementType MeasurementType;
typedef typename TSample::MeasurementVectorType MeasurementVectorType;
/** typedefs from Superclass */
typedef typename Superclass::MembershipFunctionVectorObjectPointer
MembershipFunctionPointerVector; //FIXME adopt new naming convention
/** typedef for label type */
typedef TLabel ClassLabelType;
/** Returns the classification result */
OutputType* GetOutput();
void SetOutput(OutputType* output);
using Superclass::SetOutput;
/** Returns the hyperplanes distances */
HyperplanesDistancesListSampleType * GetHyperplanesDistancesOutput();
/** Type definitions for the SVM Model. */
typedef SVMModel<MeasurementType, ClassLabelType> SVMModelType;
typedef typename SVMModelType::Pointer SVMModelPointer;
/** Set the model */
itkSetObjectMacro(Model, SVMModelType);
/** Get the number of classes. */
itkGetObjectMacro(Model, SVMModelType);
void Update() ITK_OVERRIDE;
protected:
SVMClassifier();
~SVMClassifier() ITK_OVERRIDE {}
void PrintSelf(std::ostream& os, itk::Indent indent) const ITK_OVERRIDE;
/** Starts the classification process */
void GenerateData() ITK_OVERRIDE;
virtual void DoClassification();
private:
/** Output pointer (MembershipSample) */
typename OutputType::Pointer m_Output;
/** Hyperplanes distances output */
typename HyperplanesDistancesListSampleType::Pointer m_HyperplanesDistancesOutput;
SVMModelPointer m_Model;
}; // end of class
} // end of namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbSVMClassifier.txx"
#endif
#endif
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