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/*
* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef otbSOMModel_txx
#define otbSOMModel_txx
#include "otbSOMModel.h"
#include "otbSOM.h"
#include "itkMacro.h"
#include "itkImageRegionIterator.h"
#include "itkImageRegionConstIterator.h"
#include "itkImage.h"
#include <fstream>
namespace otb
{
namespace internal
{
template<typename T>
std::ostream& BinaryWrite(std::ostream& stream, const T& value)
{
return stream.write(reinterpret_cast<const char*>(&value), sizeof(T));
}
std::ostream& BinaryWriteString(std::ofstream& stream, const std::string& value)
{
return stream.write(value.c_str(), value.length());
}
template<typename T>
std::istream & BinaryRead(std::istream& stream, T& value)
{
return stream.read(reinterpret_cast<char*>(&value), sizeof(T));
}
} // end of namespace internal
template <class TInputValue, unsigned int MapDimension>
SOMModel<TInputValue, MapDimension>::SOMModel()
{
this->m_Dimension = MapType::ImageDimension;
}
template <class TInputValue, unsigned int MapDimension>
SOMModel<TInputValue, MapDimension>::~SOMModel()
{
}
template <class TInputValue, unsigned int MapDimension>
void
SOMModel<TInputValue, MapDimension>::Train()
{
typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typename EstimatorType::Pointer estimator = EstimatorType::New();
estimator->SetListSample(this->GetInputListSample());
estimator->SetMapSize(m_MapSize);
estimator->SetNeighborhoodSizeInit(m_NeighborhoodSizeInit);
estimator->SetNumberOfIterations(m_NumberOfIterations);
estimator->SetBetaInit(m_BetaInit);
estimator->SetBetaEnd(m_BetaEnd);
estimator->SetMaxWeight(m_MaxWeight);
estimator->Update();
m_SOMMap = estimator->GetOutput();
}
template <class TInputValue, unsigned int MapDimension>
bool
SOMModel<TInputValue, MapDimension>::CanReadFile(const std::string & filename)
{
try
{
this->Load(filename);
}
catch(...)
{
return false;
}
return true;
}
template <class TInputValue, unsigned int MapDimension>
bool
SOMModel<TInputValue, MapDimension>::CanWriteFile(const std::string & /*filename*/)
{
return true;
}
template <class TInputValue, unsigned int MapDimension>
void
SOMModel<TInputValue, MapDimension>::Save(const std::string & filename, const std::string & /*name*/)
{
itk::ImageRegionConstIterator<MapType> inputIterator(m_SOMMap,m_SOMMap->GetLargestPossibleRegion());
inputIterator.GoToBegin();
std::ofstream ofs(filename, std::ios::binary);
internal::BinaryWriteString(ofs,"som");
internal::BinaryWrite(ofs,static_cast<unsigned int>(MapDimension));
SizeType size = m_SOMMap->GetLargestPossibleRegion().GetSize() ;
for (size_t i=0;i<MapDimension;i++)
{
internal::BinaryWrite(ofs,size[i]);
}
internal::BinaryWrite(ofs,inputIterator.Get().GetNumberOfElements());
while(!inputIterator.IsAtEnd())
{
InputSampleType vect = inputIterator.Get();
for (size_t i=0;i<vect.GetNumberOfElements();i++)
{
internal::BinaryWrite(ofs,vect[i]);
}
++inputIterator;
}
ofs.close();
// output the map vectors in a txt file
if (this->m_WriteMap == true)
{
std::ofstream otxt(filename+".txt");
inputIterator.GoToBegin();
while(!inputIterator.IsAtEnd())
{
InputSampleType vect = inputIterator.Get();
for (size_t i=0;i<vect.GetNumberOfElements();i++)
{
otxt << vect[i] << " ";
}
otxt << std::endl;
++inputIterator;
}
otxt.close();
}
}
template <class TInputValue, unsigned int MapDimension>
void
SOMModel<TInputValue, MapDimension>::Load(const std::string & filename, const std::string & /*name*/)
{
std::ifstream ifs(filename, std::ios::binary);
/** Read the model key (should be som) */
char s[]=" ";
for (int i=0; i<3; i++)
{
internal::BinaryRead(ifs,s[i]);
}
std::string modelType(s);
/** Read the dimension of the map (should be equal to MapDimension) */
unsigned int dimension;
internal::BinaryRead(ifs,dimension);
if (modelType != "som" || dimension != MapDimension)
{
itkExceptionMacro(<< "Error opening " << filename.c_str() );
}
SizeType size;
itk::Index< MapDimension > index;
for (unsigned int i=0 ; i<MapDimension; i++)
{
internal::BinaryRead(ifs,size[i]);
index[i]=0;
}
unsigned int numberOfElements;
internal::BinaryRead(ifs,numberOfElements);
m_SOMMap = MapType::New();
typename MapType::RegionType region;
region.SetSize( size );
m_SOMMap->SetNumberOfComponentsPerPixel(numberOfElements);
region.SetIndex( index );
m_SOMMap->SetRegions( region );
m_SOMMap->Allocate();
itk::ImageRegionIterator<MapType> outputIterator(m_SOMMap,region);
outputIterator.GoToBegin();
std::string value;
while(!outputIterator.IsAtEnd())
{
InputSampleType vect(numberOfElements);
for (unsigned int i=0 ; i<numberOfElements; i++)
{
// InputValue type is not the same during training anddimredvector.
float v;
internal::BinaryRead(ifs,v);
vect[i] = static_cast<double>(v);
}
outputIterator.Set(vect);
++outputIterator;
}
ifs.close();
this->m_Dimension = MapType::ImageDimension;
}
template <class TInputValue, unsigned int MapDimension>
typename SOMModel<TInputValue, MapDimension>::TargetSampleType
SOMModel<TInputValue, MapDimension>::DoPredict(
const InputSampleType & value,
ConfidenceValueType * /*quality*/) const
{
TargetSampleType target;
target.SetSize(this->m_Dimension);
auto winner =m_SOMMap->GetWinner(value);
for (unsigned int i=0; i< this->m_Dimension ;i++)
{
target[i] = winner.GetElement(i);
}
return target;
}
} // namespace otb
#endif
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