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Grand Francois authored9f5bf52d
/** 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"#include <time.h>namespace otb{namespace Wrapper{/** Utility function to negate std::isalnum */bool IsNotAlphaNum(char c){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 */ typedef float ValueType; 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 */ typedef itk::VariableLengthVector<ValueType> MeasurementType; typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader; typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType; ~VectorDimensionalityReduction() ITK_OVERRIDE7172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140
{
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", "Field names to be calculated."); //
SetParameterDescription("feat","List of field names in the input vector data used as features for reduction."); //
AddParameter(ParameterType_StringList, "featout", "Field names to be calculated."); //
SetParameterDescription("featout","List of field names in the input vector data used as features for 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 updated.");
MandatoryOff("out");
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");
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");
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]"); //
// 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
{
if ( HasValue("in") )
{
std::string shapefile = GetParameterString("in");
otb::ogr::DataSource::Pointer ogrDS;
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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() ) );
AddChoice(tmpKey,item);
//} // 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();
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);
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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 */
m_Model = DimensionalityReductionModelFactoryType::CreateDimensionalityReductionModel(GetParameterString("model"),
DimensionalityReductionModelFactoryType::ReadMode);
if (m_Model.IsNull())
{
otbAppLogFATAL(<< "Error when loading model " << GetParameterString("model") << " : unsupported model type");
}
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;
int nbBands = nbFeatures;
if (HasValue("indim") && IsParameterEnabled("indim"))
{nbBands = GetParameterInt("indim");}
if (IsParameterEnabled("out") && HasValue("out"))
{
// Create new OGRDataSource
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
{
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OGRFieldDefn fieldDefn(inLayerDefn.GetFieldDefn(k));
newLayer.CreateField(fieldDefn);
}
}
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);
}
else
{
otbAppLogFATAL(<< "Error when creating the output file" << GetParameterString("mode") << " : unsupported writting mode type");
}
}
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();
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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)