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/*
* Copyright (C) 2005-2022 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 otbImageDimensionalityReductionFilter_hxx
#define otbImageDimensionalityReductionFilter_hxx
#include "otbImageDimensionalityReductionFilter.h"
#include "itkImageRegionIterator.h"
#include "itkProgressReporter.h"
namespace otb
{
/**
* Constructor
*/
template <class TInputImage, class TOutputImage, class TMaskImage>
ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::ImageDimensionalityReductionFilter()
{
this->SetNumberOfIndexedInputs(2);
this->SetNumberOfRequiredInputs(1);
this->SetNumberOfRequiredOutputs(2);
this->SetNthOutput(0, TOutputImage::New());
this->SetNthOutput(1, ConfidenceImageType::New());
m_UseConfidenceMap = false;
m_BatchMode = true;
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::SetInputMask(const MaskImageType* mask)
{
this->itk::ProcessObject::SetNthInput(1, const_cast<MaskImageType*>(mask));
}
template <class TInputImage, class TOutputImage, class TMaskImage>
const typename ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::MaskImageType*
ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::GetInputMask()
{
if (this->GetNumberOfInputs() < 2)
{
return nullptr;
}
return static_cast<const MaskImageType*>(this->itk::ProcessObject::GetInput(1));
}
template <class TInputImage, class TOutputImage, class TMaskImage>
typename ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::ConfidenceImageType*
ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::GetOutputConfidence()
{
if (this->GetNumberOfOutputs() < 2)
{
return nullptr;
}
return static_cast<ConfidenceImageType*>(this->itk::ProcessObject::GetOutput(1));
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::BeforeThreadedGenerateData()
{
if (m_BatchMode)
{
#ifdef _OPENMP
// OpenMP will take care of threading
this->SetNumberOfThreads(1);
#endif
}
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::ClassicThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
itk::ThreadIdType threadId)
{
// Get the input pointers
InputImageConstPointerType inputPtr = this->GetInput();
MaskImageConstPointerType inputMaskPtr = this->GetInputMask();
OutputImagePointerType outputPtr = this->GetOutput();
ConfidenceImagePointerType confidencePtr = this->GetOutputConfidence();
// Progress reporting
itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
// Define iterators
typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
typedef itk::ImageRegionIterator<OutputImageType> OutputIteratorType;
InputIteratorType inIt(inputPtr, outputRegionForThread);
OutputIteratorType outIt(outputPtr, outputRegionForThread);
// Walk the part of the image
for (inIt.GoToBegin(), outIt.GoToBegin(); !inIt.IsAtEnd() && !outIt.IsAtEnd(); ++inIt, ++outIt)
{
// Classifify
outIt.Set(m_Model->Predict(inIt.Get()));
progress.CompletedPixel();
}
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::GenerateOutputInformation()
{
Superclass::GenerateOutputInformation();
if (!m_Model)
{
itkGenericExceptionMacro(<< "No model for dimensionality reduction");
}
this->GetOutput()->SetNumberOfComponentsPerPixel(m_Model->GetDimension());
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::BatchThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
itk::ThreadIdType threadId)
{
// Get the input pointers
InputImageConstPointerType inputPtr = this->GetInput();
MaskImageConstPointerType inputMaskPtr = this->GetInputMask();
OutputImagePointerType outputPtr = this->GetOutput();
ConfidenceImagePointerType confidencePtr = this->GetOutputConfidence();
// Progress reporting
itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
// Define iterators
typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
typedef itk::ImageRegionIterator<OutputImageType> OutputIteratorType;
InputIteratorType inIt(inputPtr, outputRegionForThread);
OutputIteratorType outIt(outputPtr, outputRegionForThread);
typedef typename ModelType::InputSampleType InputSampleType;
typedef typename ModelType::InputListSampleType InputListSampleType;
typedef typename ModelType::TargetValueType TargetValueType;
typedef typename ModelType::TargetListSampleType TargetListSampleType;
typename InputListSampleType::Pointer samples = InputListSampleType::New();
unsigned int num_features = inputPtr->GetNumberOfComponentsPerPixel();
samples->SetMeasurementVectorSize(num_features);
InputSampleType sample(num_features);
// Fill the samples
for (inIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt)
{
typename InputImageType::PixelType pix = inIt.Get();
for (size_t feat = 0; feat < num_features; ++feat)
{
sample[feat] = pix[feat];
}
samples->PushBack(sample);
}
// Make the batch prediction
typename TargetListSampleType::Pointer labels;
// This call is threadsafe
labels = m_Model->PredictBatch(samples);
// Set the output values
typename TargetListSampleType::ConstIterator labIt = labels->Begin();
for (outIt.GoToBegin(); !outIt.IsAtEnd(); ++outIt)
{
itk::VariableLengthVector<TargetValueType> labelValue;
labelValue = labIt.GetMeasurementVector();
++labIt;
outIt.Set(labelValue);
progress.CompletedPixel();
}
}
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread,
itk::ThreadIdType threadId)
{
if (m_BatchMode)
{
this->BatchThreadedGenerateData(outputRegionForThread, threadId);
}
else
{
this->ClassicThreadedGenerateData(outputRegionForThread, threadId);
}
}
/**
* PrintSelf Method
*/
template <class TInputImage, class TOutputImage, class TMaskImage>
void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
} // End namespace otb
#endif
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