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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.
*/
// Warning !! the SVM model estimator do not converge in this test !!
#include "otbVectorImage.h"
#include "otbImageFileWriter.h"
#include "otbVectorDataFileReader.h"
#include "otbVectorDataToLabelMapWithAttributesFilter.h"
#include "otbSpatialisationFilter.h"
#include "otbImageSimulationMethod.h"
#include "otbAttributesMapLabelObject.h"
#include "otbLibSVMMachineLearningModel.h"
#include "otbImageClassificationFilter.h"
#include "otbImageFileReader.h"
#include "itkImageToListSampleAdaptor.h"
int otbImageSimulationMethodSVMClassif(int itkNotUsed(argc), char* argv[])
{
const char* satRSRFilename = argv[1];
unsigned int nbBands = static_cast<unsigned int>(atoi(argv[2]));
const char* rootPath = argv[3];
unsigned int radius = atoi(argv[4]);
const char* outfilename = argv[5];
const char* outLabelfilename = argv[6];
typedef unsigned short LabelType;
const unsigned int Dimension = 2;
typedef otb::Image<LabelType, Dimension> LabelImageType;
typedef otb::VectorImage<double, Dimension> OutputImageType;
typedef otb::ImageFileWriter<OutputImageType> ImageWriterType;
typedef otb::ImageFileWriter<LabelImageType> LabelImageWriterType;
typedef otb::VectorData<double, Dimension> VectorDataType;
typedef otb::AttributesMapLabelObject<LabelType, Dimension, std::string> LabelObjectType;
typedef itk::LabelMap<LabelObjectType> LabelMapType;
typedef otb::SpatialisationFilter<LabelMapType> SpatialisationFilterType;
// typedef otb::VectorDataToLabelMapWithAttributesFilter<VectorDataType, LabelMapType> SpatialisationFilterType;
typedef otb::ProspectModel SimulationStep1Type;
typedef otb::SailModel SimulationStep2Type;
typedef otb::ProlateInterpolateImageFunction<LabelImageType> FTMType;
typedef otb::ImageSimulationMethod<VectorDataType, SpatialisationFilterType, SimulationStep1Type, SimulationStep2Type, FTMType, OutputImageType>
ImageSimulationMethodType;
typedef otb::LibSVMMachineLearningModel<double, unsigned short> SVMType;
typedef otb::ImageClassificationFilter<OutputImageType, LabelImageType> ClassificationFilterType;
/** Instantiation of pointer objects*/
ImageWriterType::Pointer writer = ImageWriterType::New();
LabelImageWriterType::Pointer labelWriter = LabelImageWriterType::New();
ImageSimulationMethodType::Pointer imageSimulation = ImageSimulationMethodType::New();
SpatialisationFilterType::Pointer spatialisationFilter = SpatialisationFilterType::New();
SVMType::Pointer model = SVMType::New();
ClassificationFilterType::Pointer classifier = ClassificationFilterType::New();
SpatialisationFilterType::SizeType objectSize;
objectSize[0] = 300;
objectSize[1] = 300;
SpatialisationFilterType::SizeType nbOjects;
nbOjects[0] = 2;
nbOjects[1] = 1;
std::vector<std::string> pathVector(2);
pathVector[0] = "JHU/becknic/rocks/sedimentary/powder/0_75/txt/greywa1f.txt";
pathVector[1] = "";
// pathVector[2]="JHU/becknic/manmade/txt/0092uuu.txt";
// pathVector[3]="JHU/becknic/vegetation/txt/conifers.txt";
// pathVector[4]="JHU/becknic/manmade/txt/0834uuu.txt";
// pathVector[5]="JHU/becknic/vegetation/txt/grass.txt";
// pathVector[6]="JHU/becknic/water/txt/coarse.txt";
// pathVector[7]="JHU/becknic/rocks/igneous/solid/txt/andesi1s.txt";
// pathVector[8]="JHU/becknic/soils/txt/0015c.txt";
std::vector<std::string> areaVector(2);
areaVector[0] = "sedimentaryRock";
areaVector[1] = "prosail";
// areaVector[2]="manmade";
// areaVector[3]="conifers";
// areaVector[4]="manmade";
// areaVector[5]="grass";
// areaVector[6]="water";
// areaVector[7]="igneousRocks";
// areaVector[8]="soils";
std::vector<LabelType> labels(2);
labels[0] = 1;
labels[1] = 2;
// labels[2]=1;
// labels[3]=2;
// labels[4]=3;
// labels[5]=2;
// labels[6]=4;
// labels[7]=5;
// labels[8]=3;
spatialisationFilter->SetObjectSize(objectSize);
spatialisationFilter->SetNumberOfObjects(nbOjects);
spatialisationFilter->SetPathVector(pathVector);
spatialisationFilter->SetAreaVector(areaVector);
spatialisationFilter->SetLabels(labels);
imageSimulation->SetSpatialisation(spatialisationFilter);
imageSimulation->SetNumberOfComponentsPerPixel(nbBands);
imageSimulation->SetSatRSRFilename(satRSRFilename);
imageSimulation->SetPathRoot(rootPath);
imageSimulation->SetRadius(radius);
// imageSimulation->SetMean();
// imageSimulation->SetVariance();
imageSimulation->UpdateData();
//~ svmEstimator->SetInputImage(imageSimulation->GetOutputReflectanceImage());
//~ svmEstimator->SetTrainingImage(imageSimulation->GetOutputLabelImage());
//~ svmEstimator->SetParametersOptimization(false);
//~ svmEstimator->DoProbabilityEstimates(true);
//~ svmEstimator->Update();
typedef itk::Statistics::ImageToListSampleAdaptor<OutputImageType> ListSampleAdaptorType;
typedef itk::Statistics::ImageToListSampleAdaptor<LabelImageType> TargetListSampleAdaptorType;
ListSampleAdaptorType::Pointer listSample = ListSampleAdaptorType::New();
listSample->SetImage(imageSimulation->GetOutputReflectanceImage());
TargetListSampleAdaptorType::Pointer targetListSample = TargetListSampleAdaptorType::New();
targetListSample->SetImage(imageSimulation->GetOutputLabelImage());
model->SetInputListSample(listSample);
model->SetTargetListSample(targetListSample);
model->SetDoProbabilityEstimates(true);
model->Train();
classifier->SetModel(model);
classifier->SetInput(imageSimulation->GetOutput());
// Write the result to an image file
writer->SetFileName(outfilename);
writer->SetInput(imageSimulation->GetOutputReflectanceImage());
writer->Update();
labelWriter->SetFileName(outLabelfilename);
// labelWriter->SetInput(imageSimulation->GetOutputLabelImage());
labelWriter->SetInput(classifier->GetOutput());
labelWriter->Update();
return EXIT_SUCCESS;
}
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