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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 "otbWrapperApplication.h"
#include "otbWrapperApplicationFactory.h"
#include "otbOGRDataSourceWrapper.h"
#include "otbOGRFeatureWrapper.h"
#include "itkVariableLengthVector.h"
#include "otbStatisticsXMLFileReader.h"
#include "itkListSample.h"
#include "otbShiftScaleSampleListFilter.h"
#include "otbDimensionalityReductionModelFactory.h"
namespace otb
{
namespace Wrapper
{
/** Utility function to negate std::isalnum */
{
return !std::isalnum(c);
class VectorDimensionalityReduction : public Application
{
public:
/** Standard class typedefs. */
typedef VectorDimensionalityReduction Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macro */
itkNewMacro(Self);
itkTypeMacro(Self, Application)
/** Filters typedef */
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typedef itk::VariableLengthVector<ValueType> InputSampleType;
typedef itk::Statistics::ListSample<InputSampleType> ListSampleType;
typedef MachineLearningModel<itk::VariableLengthVector<ValueType>, itk::VariableLengthVector<ValueType>> DimensionalityReductionModelType;
typedef DimensionalityReductionModelFactory<ValueType,ValueType> DimensionalityReductionModelFactoryType;
typedef DimensionalityReductionModelType::Pointer ModelPointerType;
/** Statistics Filters typedef */
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typedef itk::VariableLengthVector<ValueType> MeasurementType;
typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader;
typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
~VectorDimensionalityReduction() ITK_OVERRIDE
{
DimensionalityReductionModelFactoryType::CleanFactories();
}
private:
void DoInit() ITK_OVERRIDE
{
SetName("VectorDimensionalityReduction");
SetDescription("Performs dimensionality reduction of the input vector data according to a model file.");
SetDocName("Vector Dimensionality Reduction");
SetDocAuthors("OTB-Team");
SetDocLongDescription("This application performs a vector data dimensionality reduction based on a model file produced by the TrainDimensionalityReduction application.");
SetDocSeeAlso("TrainDimensionalityReduction");
AddDocTag(Tags::Learning);
AddParameter(ParameterType_InputVectorData, "in", "Name of the input vector data");
SetParameterDescription("in","The input vector data to reduce.");
AddParameter(ParameterType_InputFilename, "instat", "Statistics file");
SetParameterDescription("instat", "A XML file containing mean and standard deviation to center"
"and reduce samples before dimensionality reduction (produced by ComputeImagesStatistics application).");
MandatoryOff("instat");
AddParameter(ParameterType_InputFilename, "model", "Model file");
SetParameterDescription("model", "A model file (produced by the TrainDimensionalityReduction application,");
AddParameter(ParameterType_ListView, "feat", "Input features to use for reduction."); //
SetParameterDescription("feat","List of field names in the input vector data used as features for reduction."); //
AddParameter(ParameterType_StringList, "featout", "Names of the new output features."); //
SetParameterDescription("featout","List of field names for the output features which result from the reduction."); //
AddParameter(ParameterType_OutputFilename, "out", "Output vector data file containing the reduced vector");
SetParameterDescription("out","Output vector data file storing sample values (OGR format)."
"If not given, the input vector data file is used. In overwrite mode, the original features will be lost.");
MandatoryOff("out");
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AddParameter(ParameterType_Int, "indim", "Dimension of the input vector");
SetParameterDescription("indim","Dimension of the whole input vector, this value is required if only a part of the bands contained in the vector are used."
"If not given, the dimension is deduced from the length of the 'feat' parameter");
MandatoryOff("indim");
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AddParameter(ParameterType_Int, "pcadim", "Principal component"); //
SetParameterDescription("pcadim","This optional parameter can be set to reduce the number of eignevectors used in the PCA model file."); //
MandatoryOff("pcadim");
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AddParameter(ParameterType_String, "mode", "Writting mode"); //
SetParameterString("mode","overwrite", false);
SetParameterDescription("mode","This parameter determines if the output file is overwritten or updated [overwrite/update]. If an output file name is given, the original file is copied before creating the new features."); //
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// Doc example parameter settings
SetDocExampleParameterValue("in", "vectorData.shp");
SetDocExampleParameterValue("instat", "meanVar.xml");
SetDocExampleParameterValue("model", "model.txt");
SetDocExampleParameterValue("out", "vectorDataOut.shp");
SetDocExampleParameterValue("feat", "perimeter area width");
SetDocExampleParameterValue("featout", "perimeter area width");
//SetOfficialDocLink();
}
//
void DoUpdateParameters() ITK_OVERRIDE
{
std::string shapefile = GetParameterString("in");
otb::ogr::DataSource::Pointer ogrDS;
OGRSpatialReference oSRS("");
std::vector<std::string> options;
ogrDS = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
otb::ogr::Layer layer = ogrDS->GetLayer(0);
OGRFeatureDefn &layerDefn = layer.GetLayerDefn();
ClearChoices("feat");
//ClearChoices("featout");
for(int iField=0; iField< layerDefn.GetFieldCount(); iField++)
{
std::string item = layerDefn.GetFieldDefn(iField)->GetNameRef();
std::string key(item);
std::string::iterator end = std::remove_if( key.begin(), key.end(), IsNotAlphaNum );
std::transform( key.begin(), end, key.begin(), tolower );
/*
key.erase( std::remove_if(key.begin(),key.end(),IsNotAlphaNum), key.end());
std::transform(key.begin(), key.end(), key.begin(), tolower);*/
OGRFieldType fieldType = layerDefn.GetFieldDefn(iField)->GetType();
/* if(fieldType == OFTInteger || ogr::version_proxy::IsOFTInteger64(fieldType) || fieldType == OFTReal)
//std::string tmpKey="feat."+key;
std::string tmpKey = "feat." + key.substr( 0, static_cast<unsigned long>( end - key.begin() ) );
//} // this is the same as in otbVectorClassifier, but it doesnt work
}
void DoExecute() ITK_OVERRIDE
{
clock_t tic = clock();
std::string shapefile = GetParameterString("in");
otb::ogr::DataSource::Pointer source = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
otb::ogr::Layer layer = source->GetLayer(0);
ListSampleType::Pointer input = ListSampleType::New();
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int nbFeatures = GetSelectedItems("feat").size();
input->SetMeasurementVectorSize(nbFeatures);
otb::ogr::Layer::const_iterator it = layer.cbegin();
otb::ogr::Layer::const_iterator itEnd = layer.cend();
for( ; it!=itEnd ; ++it)
{
MeasurementType mv;
mv.SetSize(nbFeatures);
for(int idx=0; idx < nbFeatures; ++idx)
{
mv[idx] = static_cast<float>( (*it)[GetSelectedItems("feat")[idx]].GetValue<double>() );
}
input->PushBack(mv);
/** Statistics for shift/scale */
MeasurementType meanMeasurementVector;
MeasurementType stddevMeasurementVector;
if (HasValue("instat") && IsParameterEnabled("instat"))
{
StatisticsReader::Pointer statisticsReader = StatisticsReader::New();
std::string XMLfile = GetParameterString("instat");
statisticsReader->SetFileName(XMLfile);
meanMeasurementVector = statisticsReader->GetStatisticVectorByName("mean");
stddevMeasurementVector = statisticsReader->GetStatisticVectorByName("stddev");
}
else
{
meanMeasurementVector.SetSize(nbFeatures);
meanMeasurementVector.Fill(0.);
stddevMeasurementVector.SetSize(nbFeatures);
stddevMeasurementVector.Fill(1.);
}
ShiftScaleFilterType::Pointer trainingShiftScaleFilter = ShiftScaleFilterType::New();
trainingShiftScaleFilter->SetInput(input);
trainingShiftScaleFilter->SetShifts(meanMeasurementVector);
trainingShiftScaleFilter->SetScales(stddevMeasurementVector);
trainingShiftScaleFilter->Update();
otbAppLogINFO("mean used: " << meanMeasurementVector);
otbAppLogINFO("standard deviation used: " << stddevMeasurementVector);
otbAppLogINFO("Loading model");
/** Read the model */
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m_Model = DimensionalityReductionModelFactoryType::CreateDimensionalityReductionModel(GetParameterString("model"),
DimensionalityReductionModelFactoryType::ReadMode);
if (m_Model.IsNull())
{
otbAppLogFATAL(<< "Error when loading model " << GetParameterString("model") << " : unsupported model type");
}
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if (HasValue("pcadim") && IsParameterEnabled("pcadim"))
{
int dimension = GetParameterInt("pcadim");
m_Model->SetDimension(dimension );
}
m_Model->Load(GetParameterString("model"));
otbAppLogINFO("Model loaded");
/** Perform Dimensionality Reduction */
ListSampleType::Pointer listSample = trainingShiftScaleFilter->GetOutput();
ListSampleType::Pointer target = m_Model->PredictBatch(listSample);
/** Create/Update Output Shape file */
std::cout << GetParameterStringList("featout").size() << std::endl;
ogr::DataSource::Pointer output;
ogr::DataSource::Pointer buffer = ogr::DataSource::New();
bool updateMode = false;
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int nbBands = nbFeatures;
if (HasValue("indim") && IsParameterEnabled("indim"))
{nbBands = GetParameterInt("indim");}
if (IsParameterEnabled("out") && HasValue("out"))
{
// Create new OGRDataSource
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if (GetParameterString("mode")=="overwrite")
{
output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Overwrite);
otb::ogr::Layer newLayer = output->CreateLayer(GetParameterString("out"),
const_cast<OGRSpatialReference*>(layer.GetSpatialRef()),
layer.GetGeomType());
// Copy existing fields
OGRFeatureDefn &inLayerDefn = layer.GetLayerDefn();
for (int k=0 ; k<inLayerDefn.GetFieldCount()-nbBands ; k++) // we don't copy the original bands
{
OGRFieldDefn fieldDefn(inLayerDefn.GetFieldDefn(k));
newLayer.CreateField(fieldDefn);
}
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}
else if (GetParameterString("mode")=="update")
{
//output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Update_LayerCreateOnly);
// Update mode
otb::ogr::DataSource::Pointer source_output = otb::ogr::DataSource::New(GetParameterString("out"), otb::ogr::DataSource::Modes::Read);
layer = source_output->GetLayer(0);
updateMode = true;
otbAppLogINFO("Update input vector data.");
// fill temporary buffer for the transfer
otb::ogr::Layer inputLayer = layer;
layer = buffer->CopyLayer(inputLayer, std::string("Buffer"));
// close input data source
source_output->Clear();
// Re-open input data source in update mode
output = otb::ogr::DataSource::New(GetParameterString("out"), otb::ogr::DataSource::Modes::Update_LayerUpdate);
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}
else
{
otbAppLogFATAL(<< "Error when creating the output file" << GetParameterString("mode") << " : unsupported writting mode type");
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}
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otb::ogr::Layer outLayer = output->GetLayer(0);
OGRErr errStart = outLayer.ogr().StartTransaction();
if (errStart != OGRERR_NONE)
{
itkExceptionMacro(<< "Unable to start transaction for OGR layer " << outLayer.ogr().GetName() << ".");
}
// Add the field of prediction in the output layer if field not exist
for (int i=0; i<GetParameterStringList("featout").size() ;i++)
OGRFeatureDefn &layerDefn = outLayer.GetLayerDefn();
int idx = layerDefn.GetFieldIndex(GetParameterStringList("featout")[i].c_str());
if (idx >= 0)
{
if (layerDefn.GetFieldDefn(idx)->GetType() != OFTReal)
itkExceptionMacro("Field name "<< GetParameterStringList("featout")[i] << " already exists with a different type!");
}
else
{
OGRFieldDefn predictedField(GetParameterStringList("featout")[i].c_str(), OFTReal);
ogr::FieldDefn predictedFieldDef(predictedField);
outLayer.CreateField(predictedFieldDef);
}
// Fill output layer
unsigned int count=0;
auto classfieldname = GetParameterStringList("featout");
it = layer.cbegin();
itEnd = layer.cend();
for( ; it!=itEnd ; ++it, ++count)
{
ogr::Feature dstFeature(outLayer.GetLayerDefn());
dstFeature.SetFrom( *it , TRUE);
dstFeature.SetFID(it->GetFID());
for (std::size_t i=0; i<classfieldname.size(); ++i){
dstFeature[classfieldname[i]].SetValue<double>(target->GetMeasurementVector(count)[i]);
}
if (updateMode)
{
outLayer.SetFeature(dstFeature);
}
else
{
outLayer.CreateFeature(dstFeature);
}
}
if(outLayer.ogr().TestCapability("Transactions"))
{
const OGRErr errCommitX = outLayer.ogr().CommitTransaction();
if (errCommitX != OGRERR_NONE)
{
itkExceptionMacro(<< "Unable to commit transaction for OGR layer " << outLayer.ogr().GetName() << ".");
}
}
output->SyncToDisk();
clock_t toc = clock();
otbAppLogINFO( "Elapsed: "<< ((double)(toc - tic) / CLOCKS_PER_SEC)<<" seconds.");
}
ModelPointerType m_Model;
};
}
}
OTB_APPLICATION_EXPORT(otb::Wrapper::VectorDimensionalityReduction)