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Commit d5ed9ebb authored by Guillaume Pasero's avatar Guillaume Pasero
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STYLE: use OTB coding style

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+41 -104
Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.h
+ 1
− 19
View file @ d5ed9ebb
......@@ -20,15 +20,12 @@
#ifndef otbAutoencoderModelFactory_h
#define otbAutoencoderModelFactory_h
//#include <shark/Models/TiedAutoencoder.h>
//#include <shark/Models/Autoencoder.h>
#include "itkObjectFactoryBase.h"
#include "itkImageIOBase.h"
namespace otb
{
template <class TInputValue, class TTargetValue, class NeuronType>
class ITK_EXPORT AutoencoderModelFactory : public itk::ObjectFactoryBase
{
......@@ -63,27 +60,12 @@ protected:
private:
AutoencoderModelFactory(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
};
/*
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>> ;
*/
} //namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbAutoencoderModelFactory.txx"
#endif
#endif
Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.txx
+ 10
− 10
View file @ d5ed9ebb
......@@ -20,7 +20,6 @@
#ifndef otbAutoencoderModelFactory_txx
#define otbAutoencoderModelFactory_txx
#include "otbAutoencoderModelFactory.h"
#include "otbAutoencoderModel.h"
......@@ -32,16 +31,15 @@ namespace otb
template <class TInputValue, class TOutputValue, class NeuronType>
AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::AutoencoderModelFactory()
{
std::string classOverride = std::string("DimensionalityReductionModel");
std::string subclass = std::string("AutoencoderModel");
this->RegisterOverride(classOverride.c_str(),
subclass.c_str(),
"Shark AE ML Model",
1,
// itk::CreateObjectFunction<AutoencoderModel<TInputValue,TOutputValue> >::New());
itk::CreateObjectFunction<AutoencoderModel<TInputValue,NeuronType > >::New());
this->RegisterOverride(
classOverride.c_str(),
subclass.c_str(),
"Shark AE ML Model",
1,
itk::CreateObjectFunction<AutoencoderModel<TInputValue,NeuronType > >::New());
}
template <class TInputValue, class TOutputValue, class NeuronType>
......@@ -50,13 +48,15 @@ AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::~AutoencoderModel
}
template <class TInputValue, class TOutputValue, class NeuronType>
const char* AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetITKSourceVersion(void) const
const char*
AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetITKSourceVersion(void) const
{
return ITK_SOURCE_VERSION;
}
template <class TInputValue, class TOutputValue, class NeuronType>
const char* AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetDescription() const
const char*
AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetDescription() const
{
return "Autoencoder model factory";
}
......
Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.h
+ 0
− 4
View file @ d5ed9ebb
......@@ -20,9 +20,7 @@
#ifndef otbDimensionalityReductionModelFactory_h
#define otbDimensionalityReductionModelFactory_h
//#include "DimensionalityReductionModel.h"
#include "otbMachineLearningModelFactoryBase.h"
#include "otbMachineLearningModel.h"
namespace otb
......@@ -54,7 +52,6 @@ public:
/** Mode in which the files is intended to be used */
typedef enum { ReadMode, WriteMode } FileModeType;
/** Create the appropriate MachineLearningModel depending on the particulars of the file. */
static DimensionalityReductionModelTypePointer CreateDimensionalityReductionModel(const std::string& path, FileModeType mode);
......@@ -74,7 +71,6 @@ private:
/** Register a single factory, ensuring it has not been registered
* twice */
static void RegisterFactory(itk::ObjectFactoryBase * factory);
};
} // end namespace otb
......
Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.txx
+ 13
− 38
View file @ d5ed9ebb
......@@ -32,15 +32,12 @@
#include "itkMutexLockHolder.h"
namespace otb
{
template <class TInputValue, class TTargetValue>
using LogAutoencoderModelFactory = AutoencoderModelFactory<TInputValue, TTargetValue, shark::LogisticNeuron> ;
template <class TInputValue, class TTargetValue>
using SOM2DModelFactory = SOMModelFactory<TInputValue, TTargetValue, 2> ;
......@@ -55,7 +52,7 @@ using SOM5DModelFactory = SOMModelFactory<TInputValue, TTargetValue, 5> ;
template <class TInputValue, class TOutputValue>
typename MachineLearningModel<itk::VariableLengthVector< TInputValue> , itk::VariableLengthVector< TOutputValue>>::Pointer
typename MachineLearningModel<itk::VariableLengthVector< TInputValue>, itk::VariableLengthVector< TOutputValue> >::Pointer
DimensionalityReductionModelFactory<TInputValue,TOutputValue>
::CreateDimensionalityReductionModel(const std::string& path, FileModeType mode)
{
......@@ -64,7 +61,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
std::list<DimensionalityReductionModelTypePointer> possibleDimensionalityReductionModel;
std::list<LightObject::Pointer> allobjects =
itk::ObjectFactoryBase::CreateAllInstance("DimensionalityReductionModel");
for(std::list<LightObject::Pointer>::iterator i = allobjects.begin();
i != allobjects.end(); ++i)
{
......@@ -75,19 +72,17 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
}
else
{
std::cerr << "Error DimensionalityReductionModel Factory did not return an DimensionalityReductionModel: "
<< (*i)->GetNameOfClass()
<< std::endl;
}
}
for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = possibleDimensionalityReductionModel.begin();
for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = possibleDimensionalityReductionModel.begin();
k != possibleDimensionalityReductionModel.end(); ++k)
{
if( mode == ReadMode )
if( mode == ReadMode )
{
if((*k)->CanReadFile(path))
{
return *k;
......@@ -99,7 +94,6 @@ for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = po
{
return *k;
}
}
}
return ITK_NULLPTR;
......@@ -111,20 +105,16 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
::RegisterBuiltInFactories()
{
itk::MutexLockHolder<itk::SimpleMutexLock> lockHolder(mutex);
RegisterFactory(SOM2DModelFactory<TInputValue,TOutputValue>::New());
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(LogAutoencoderModelFactory<TInputValue,TOutputValue>::New());
// RegisterFactory(TiedAutoencoderModelFactory<TInputValue,TOutputValue>::New());
#endif
}
template <class TInputValue, class TOutputValue>
......@@ -151,17 +141,15 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
for (itFac = factories.begin(); itFac != factories.end() ; ++itFac)
{
// SOM
SOM5DModelFactory<TInputValue,TOutputValue> *som5dFactory =
// SOM 5D
SOM5DModelFactory<TInputValue,TOutputValue> *som5dFactory =
dynamic_cast<SOM5DModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (som5dFactory)
{
itk::ObjectFactoryBase::UnRegisterFactory(som5dFactory);
continue;
}
// SOM 4D
SOM4DModelFactory<TInputValue,TOutputValue> *som4dFactory =
dynamic_cast<SOM4DModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (som4dFactory)
......@@ -169,7 +157,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::UnRegisterFactory(som4dFactory);
continue;
}
// SOM 3D
SOM3DModelFactory<TInputValue,TOutputValue> *som3dFactory =
dynamic_cast<SOM3DModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (som3dFactory)
......@@ -177,7 +165,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::UnRegisterFactory(som3dFactory);
continue;
}
// SOM 2D
SOM2DModelFactory<TInputValue,TOutputValue> *som2dFactory =
dynamic_cast<SOM2DModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (som2dFactory)
......@@ -185,9 +173,8 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::UnRegisterFactory(som2dFactory);
continue;
}
#ifdef OTB_USE_SHARK
// Autoencoder
LogAutoencoderModelFactory<TInputValue,TOutputValue> *aeFactory =
dynamic_cast<LogAutoencoderModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (aeFactory)
......@@ -195,17 +182,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::UnRegisterFactory(aeFactory);
continue;
}
/*
TiedAutoencoderModelFactory<TInputValue,TOutputValue> *taeFactory =
dynamic_cast<TiedAutoencoderModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (taeFactory)
{
itk::ObjectFactoryBase::UnRegisterFactory(taeFactory);
continue;
}
*/
// PCA
// PCA
PCAModelFactory<TInputValue,TOutputValue> *pcaFactory =
dynamic_cast<PCAModelFactory<TInputValue,TOutputValue> *>(*itFac);
if (pcaFactory)
......@@ -214,9 +191,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
continue;
}
#endif
}
}
} // end namespace otb
......
Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.h
+ 0
− 1
View file @ d5ed9ebb
......@@ -21,7 +21,6 @@
#define otbImageDimensionalityReduction_h
#include "itkImageToImageFilter.h"
//#include "DimensionalityReductionModel.h"
#include "otbMachineLearningModel.h"
#include "otbImage.h"
......
Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.txx
+ 17
− 32
View file @ d5ed9ebb
......@@ -36,8 +36,6 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
this->SetNumberOfIndexedInputs(2);
this->SetNumberOfRequiredInputs(1);
//m_DefaultLabel = itk::NumericTraits<LabelType>::ZeroValue();
this->SetNumberOfRequiredOutputs(2);
this->SetNthOutput(0,TOutputImage::New());
this->SetNthOutput(1,ConfidenceImageType::New());
......@@ -113,9 +111,7 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
// Define iterators
typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
//typedef itk::ImageRegionConstIterator<MaskImageType> MaskIteratorType;
typedef itk::ImageRegionIterator<OutputImageType> OutputIteratorType;
//typedef itk::ImageRegionIterator<ConfidenceImageType> ConfidenceMapIteratorType;
InputIteratorType inIt(inputPtr, outputRegionForThread);
OutputIteratorType outIt(outputPtr, outputRegionForThread);
......@@ -123,43 +119,36 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
// Walk the part of the image
for (inIt.GoToBegin(), outIt.GoToBegin(); !inIt.IsAtEnd() && !outIt.IsAtEnd(); ++inIt, ++outIt)
{
// Classifify
outIt.Set(m_Model->Predict(inIt.Get()));
// Classifify
outIt.Set(m_Model->Predict(inIt.Get()));
progress.CompletedPixel();
}
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::GenerateOutputInformation()
{
Superclass::GenerateOutputInformation();
Superclass::GenerateOutputInformation();
this->GetOutput()->SetNumberOfComponentsPerPixel( m_Model->GetDimension() );
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void
ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
::BatchThreadedGenerateData(const OutputImageRegionType& outputRegionForThread, itk::ThreadIdType threadId)
{
// Get the input pointers
InputImageConstPointerType inputPtr = this->GetInput();
MaskImageConstPointerType inputMaskPtr = this->GetInputMask();
OutputImagePointerType outputPtr = this->GetOutput();
ConfidenceImagePointerType confidencePtr = this->GetOutputConfidence();
// Progress reporting
itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
// Define iterators
typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
//typedef itk::ImageRegionConstIterator<MaskImageType> MaskIteratorType;
typedef itk::ImageRegionIterator<OutputImageType> OutputIteratorType;
//typedef itk::ImageRegionIterator<ConfidenceImageType> ConfidenceMapIteratorType;
InputIteratorType inIt(inputPtr, outputRegionForThread);
OutputIteratorType outIt(outputPtr, outputRegionForThread);
......@@ -168,45 +157,40 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
typedef typename ModelType::InputListSampleType InputListSampleType;
typedef typename ModelType::TargetValueType TargetValueType;
typedef typename ModelType::TargetListSampleType TargetListSampleType;
typename InputListSampleType::Pointer samples = InputListSampleType::New();
unsigned int num_features = inputPtr->GetNumberOfComponentsPerPixel();
samples->SetMeasurementVectorSize(num_features);
InputSampleType sample(num_features);
// Fill the samples
for (inIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt)
{
typename InputImageType::PixelType pix = inIt.Get();
for(size_t feat=0; feat<num_features; ++feat)
{
sample[feat]=pix[feat];
}
samples->PushBack(sample);
typename InputImageType::PixelType pix = inIt.Get();
for(size_t feat=0; feat<num_features; ++feat)
{
sample[feat]=pix[feat];
}
samples->PushBack(sample);
}
//Make the batch prediction
typename TargetListSampleType::Pointer labels;
// This call is threadsafe
labels = m_Model->PredictBatch(samples);
// Set the output values
typename TargetListSampleType::ConstIterator labIt = labels->Begin();
for (outIt.GoToBegin(); !outIt.IsAtEnd(); ++outIt)
{
itk::VariableLengthVector<TargetValueType> labelValue;
itk::VariableLengthVector<TargetValueType> labelValue;
labelValue = labIt.GetMeasurementVector();
++labIt;
outIt.Set(labelValue);
progress.CompletedPixel();
}
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void
ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
......@@ -220,8 +204,8 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
{
this->ClassicThreadedGenerateData(outputRegionForThread, threadId);
}
}
/**
* PrintSelf Method
*/
......@@ -232,5 +216,6 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
{
Superclass::PrintSelf(os, indent);
}
} // End namespace otb
#endif
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