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/*
* Copyright (C) 2005-2020 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 otbTrainDimensionalityReductionApplicationBase_hxx
#define otbTrainDimensionalityReductionApplicationBase_hxx
#include "otbTrainDimensionalityReductionApplicationBase.h"
namespace otb
{
namespace Wrapper
{
template <class TInputValue, class TOutputValue>
TrainDimensionalityReductionApplicationBase<TInputValue, TOutputValue>::TrainDimensionalityReductionApplicationBase()
{
}
template <class TInputValue, class TOutputValue>
TrainDimensionalityReductionApplicationBase<TInputValue, TOutputValue>::~TrainDimensionalityReductionApplicationBase()
{
ModelFactoryType::CleanFactories();
}
template <class TInputValue, class TOutputValue>
void TrainDimensionalityReductionApplicationBase<TInputValue, TOutputValue>::DoInit()
{
AddDocTag(Tags::Learning);
// main choice parameter that will contain all dimensionality reduction options
AddParameter(ParameterType_Choice, "algorithm", "algorithm to use for the training");
SetParameterDescription("algorithm",
"Choice of the dimensionality reduction "
"algorithm to use for the training.");
InitSOMParams();
#ifdef OTB_USE_SHARK
InitAutoencoderParams();
InitPCAParams();
#endif
}
template <class TInputValue, class TOutputValue>
void TrainDimensionalityReductionApplicationBase<TInputValue, TOutputValue>::Reduce(typename ListSampleType::Pointer /*validationListSample*/,
std::string /*modelPath*/)
{
}
template <class TInputValue, class TOutputValue>
void TrainDimensionalityReductionApplicationBase<TInputValue, TOutputValue>::Train(typename ListSampleType::Pointer trainingListSample, std::string modelPath)
{
// get the name of the chosen machine learning model
const std::string modelName = GetParameterString("algorithm");
// call specific train function
if (modelName == "som")
{
BeforeTrainSOM(trainingListSample, modelPath);
}
if (modelName == "autoencoder")
{
#ifdef OTB_USE_SHARK
BeforeTrainAutoencoder(trainingListSample, modelPath);
#else
otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
#endif
}
if (modelName == "pca")
{
#ifdef OTB_USE_SHARK
TrainPCA(trainingListSample, modelPath);
#else
otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
#endif
}
}
} // end of namespace Wrapper
} // end of namespace otb
#endif
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