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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.
*/
#include "otbPCAModel.h"
#include "otbReadDataFile.h"
typedef otb::PCAModel<double> PCAModelType;
typedef PCAModelType::InputListSampleType InputListSampleType;
typedef PCAModelType::TargetListSampleType TargetListSampleType;
int otbPCAModelNew(int itkNotUsed(argc), char * itkNotUsed(argv) [])
{
PCAModelType::Pointer model = PCAModelType::New();
return EXIT_SUCCESS;
}
int otbPCAModelCanRead(int argc, char * argv [])
{
if (argc < 2)
{
std::cerr << "Usage: " << argv[0] << " <model>" << std::endl;
return EXIT_FAILURE;
}
PCAModelType::Pointer model = PCAModelType::New();
std::string filename(argv[1]);
if (! model->CanReadFile(filename) )
{
std::cerr << "Failed to read model file : "<< filename << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
int otbPCAModeTrain(int argc, char * argv [])
{
if (argc < 3)
{
std::cerr << "Usage: " << argv[0] << " letter.scale model.out" << std::endl;
return EXIT_FAILURE;
}
// Extract data from letter.scale
InputListSampleType::Pointer samples = InputListSampleType::New();
TargetListSampleType::Pointer target = TargetListSampleType::New();
if (!otb::ReadDataFile(argv[1], samples, target))
{
std::cout << "Failed to read samples file " << argv[1] << std::endl;
return EXIT_FAILURE;
}
PCAModelType::Pointer model = PCAModelType::New();
model->SetDimension(14);
model->SetWriteEigenvectors(true);
model->SetInputListSample(samples);
model->Train();
model->Save(std::string(argv[2]));
return EXIT_SUCCESS;
}
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