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Commit a30fb6f2 authored by Cédric Traizet's avatar Cédric Traizet
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som is now a machine learning model, ae and pca have been deactiveted

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1 merge request!4Dimensionality reduction algorithms
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app/cbDimensionalityReductionTrainer.cxx
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......@@ -9,7 +9,7 @@
#include "otbShiftScaleSampleListFilter.h"
#include "otbStatisticsXMLFileReader.h"
#include "otbSharkUtils.h"
//#include "otbSharkUtils.h"
#include <fstream> // write the model file
......
include/AutoencoderModel.txx
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#ifndef AutoencoderModel_txx
#define AutoencoderModel_txx
......
include/DimensionalityReductionModelFactory.h
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......@@ -20,7 +20,7 @@
#include "DimensionalityReductionModel.h"
#include "otbMachineLearningModelFactoryBase.h"
namespace otb
{
/** \class MachineLearningModelFactory
......
include/DimensionalityReductionModelFactory.txx
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......@@ -22,25 +22,25 @@
#include "otbConfigure.h"
#include "SOMModelFactory.h"
/*
#ifdef OTB_USE_SHARK
#include "AutoencoderModelFactory.h"
#include "PCAModelFactory.h"
#endif
*/
#include "itkMutexLockHolder.h"
namespace otb
{
/*
template <class TInputValue, class TTargetValue>
using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::Autoencoder<shark::TanhNeuron, shark::LinearNeuron>> ;
template <class TInputValue, class TTargetValue>
using TiedAutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::TiedAutoencoder< shark::TanhNeuron, shark::LinearNeuron>> ;
*/
template <class TInputValue, class TTargetValue>
using SOM2DModelFactory = SOMModelFactory<TInputValue, TTargetValue, 2> ;
......@@ -115,13 +115,13 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
RegisterFactory(SOM3DModelFactory<TInputValue,TOutputValue>::New());
RegisterFactory(SOM4DModelFactory<TInputValue,TOutputValue>::New());
RegisterFactory(SOM5DModelFactory<TInputValue,TOutputValue>::New());
/*
#ifdef OTB_USE_SHARK
RegisterFactory(PCAModelFactory<TInputValue,TOutputValue>::New());
RegisterFactory(AutoencoderModelFactory<TInputValue,TOutputValue>::New());
RegisterFactory(TiedAutoencoderModelFactory<TInputValue,TOutputValue>::New());
#endif
*/
}
template <class TInputValue, class TOutputValue>
......@@ -182,6 +182,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::UnRegisterFactory(som2dFactory);
continue;
}
/*
#ifdef OTB_USE_SHARK
// Autoencoder
......@@ -210,7 +211,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
continue;
}
#endif
*/
}
}
......
include/SOMModel.h
+ 29
− 23
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#ifndef SOMModel_h
#define SOMModel_h
#include "DimensionalityReductionModel.h"
//#include "DimensionalityReductionModel.h"
#include "otbSOMMap.h"
#include "otbSOM.h"
......@@ -11,38 +11,45 @@
#include "otbCzihoSOMLearningBehaviorFunctor.h"
#include "otbCzihoSOMNeighborhoodBehaviorFunctor.h"
#include "otbMachineLearningModelTraits.h"
#include "otbMachineLearningModel.h"
namespace otb
{
template <class TInputValue, unsigned int MapDimension>
class ITK_EXPORT SOMModel: public DimensionalityReductionModel<TInputValue,TInputValue>
class ITK_EXPORT SOMModel: public MachineLearningModel<itk::VariableLengthVector< TInputValue> , itk::VariableLengthVector< TInputValue>>
{
public:
typedef SOMModel Self;
typedef DimensionalityReductionModel<TInputValue,TInputValue> Superclass;
typedef MachineLearningModel<itk::VariableLengthVector< TInputValue> , itk::VariableLengthVector< TInputValue>> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename InputListSampleType::Pointer ListSamplePointerType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename InputListSampleType::Pointer ListSamplePointerType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef SOMMap<itk::VariableLengthVector<TInputValue>,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, MapDimension> MapType;
typedef typename MapType::SizeType SizeType;
typedef typename MapType::SpacingType SpacingType;
/// Confidence map related typedefs
typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typedef typename Superclass::ConfidenceValueType ConfidenceValueType;
typedef typename Superclass::ConfidenceSampleType ConfidenceSampleType;
typedef typename Superclass::ConfidenceListSampleType ConfidenceListSampleType;
typedef Functor::CzihoSOMLearningBehaviorFunctor SOMLearningBehaviorFunctorType;
typedef Functor::CzihoSOMNeighborhoodBehaviorFunctor SOMNeighborhoodBehaviorFunctorType;
typedef SOMMap<itk::VariableLengthVector<TInputValue>,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, MapDimension> MapType;
typedef typename MapType::SizeType SizeType;
typedef typename MapType::SpacingType SpacingType;
typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typedef Functor::CzihoSOMLearningBehaviorFunctor SOMLearningBehaviorFunctorType;
typedef Functor::CzihoSOMNeighborhoodBehaviorFunctor SOMNeighborhoodBehaviorFunctorType;
itkNewMacro(Self);
itkTypeMacro(SOMModel, DimensionalityReductionModel);
......@@ -72,8 +79,8 @@ public:
bool CanReadFile(const std::string & filename);
bool CanWriteFile(const std::string & filename);
void Save(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Load(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Save(const std::string & filename, const std::string & name="") ;
void Load(const std::string & filename, const std::string & name="") ;
void Train() ITK_OVERRIDE;
//void Dimensionality_reduction() {}; // Dimensionality reduction is done by DoPredict
......@@ -83,11 +90,10 @@ protected:
SOMModel();
~SOMModel() ITK_OVERRIDE;
virtual TargetSampleType DoPredict(const InputSampleType& input) const ITK_OVERRIDE;
private:
typename MapType::Pointer m_SOMMap;
virtual TargetSampleType DoPredict(const InputSampleType& input, ConfidenceValueType * quality = ITK_NULLPTR) const;
/** Map Parameters used for training */
......
include/SOMModel.txx
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#ifndef SOMModel_txx
#define SOMModel_txx
......@@ -177,7 +176,7 @@ void SOMModel<TInputValue, MapDimension>::Load(const std::string & filename, con
template <class TInputValue, unsigned int MapDimension>
typename SOMModel<TInputValue, MapDimension>::TargetSampleType
SOMModel<TInputValue, MapDimension>::DoPredict(const InputSampleType & value) const
SOMModel<TInputValue, MapDimension>::DoPredict(const InputSampleType & value, ConfidenceValueType * quality) const
{
unsigned int dimension =MapType::ImageDimension;
TargetSampleType target;
......
include/cbLearningApplicationBaseDR.h
+ 14
− 11
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......@@ -15,12 +15,12 @@
#include "DimensionalityReductionModelFactory.h"
#include "SOMModel.h"
/*
#ifdef OTB_USE_SHARK
#include "AutoencoderModel.h"
#include "PCAModel.h"
#endif
*/
namespace otb
{
namespace Wrapper
......@@ -99,7 +99,7 @@ public:
typedef SOMMap<itk::VariableLengthVector<TInputValue>,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 5> Map5DType;
typedef otb::SOMModel<InputValueType, 5> SOM5DModelType;
/*
#ifdef OTB_USE_SHARK
typedef shark::Autoencoder< shark::TanhNeuron, shark::LinearNeuron> AutoencoderType;
typedef otb::AutoencoderModel<InputValueType, AutoencoderType> AutoencoderModelType;
......@@ -109,7 +109,7 @@ public:
typedef otb::PCAModel<InputValueType> PCAModelType;
#endif
*/
protected:
cbLearningApplicationBaseDR();
......@@ -131,11 +131,15 @@ private:
/** Specific Init and Train methods for each machine learning model */
//@{
void InitSOMParams();
template <class somchoice>
void TrainSOM(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
void BeforeTrainSOM(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
/*
#ifdef OTB_USE_SHARK
void InitAutoencoderParams();
void InitPCAParams();
void InitSOMParams();
void BeforeTrainAutoencoder(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
template <class autoencoderchoice>
......@@ -143,10 +147,8 @@ private:
void TrainPCA(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
template <class somchoice>
void TrainSOM(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
void BeforeTrainSOM(typename ListSampleType::Pointer trainingListSample, std::string modelPath);
#endif
#endif */
//@}
};
......@@ -156,10 +158,11 @@ private:
#ifndef OTB_MANUAL_INSTANTIATION
#include "cbLearningApplicationBaseDR.txx"
#include "cbTrainSOM.txx"
/*
#ifdef OTB_USE_SHARK
#include "cbTrainAutoencoder.txx"
#include "cbTrainPCA.txx"
#endif
#endif*/
#endif
#endif
include/cbLearningApplicationBaseDR.txx
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......@@ -50,11 +50,12 @@ cbLearningApplicationBaseDR<TInputValue,TOutputValue>
InitSOMParams();
/*
#ifdef OTB_USE_SHARK
InitAutoencoderParams();
InitPCAParams();
#endif
*/
}
template <class TInputValue, class TOutputValue>
......@@ -79,7 +80,7 @@ cbLearningApplicationBaseDR<TInputValue,TOutputValue>
{
BeforeTrainSOM(trainingListSample,modelPath);
}
/*
if(modelName == "autoencoder")
{
#ifdef OTB_USE_SHARK
......@@ -104,7 +105,7 @@ cbLearningApplicationBaseDR<TInputValue,TOutputValue>
#else
otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
#endif
}
}*/
}
}
......
otb-module.cmake
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......@@ -6,9 +6,9 @@ otb_module(CbDimensionalityReduction
OTBITK
OTBShark
OTBBoost
OTBSupervised
OTBAppClassification
OTBSOM
OTBLearningBase
DESCRIPTION
"${DOCUMENTATION}"
)
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