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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.
*/
#ifndef otbKMeansImageClassificationFilter_txx
#define otbKMeansImageClassificationFilter_txx
#include "otbKMeansImageClassificationFilter.h"
#include "itkImageRegionIterator.h"
#include "itkNumericTraits.h"
namespace otb
{
/**
* Constructor
*/
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::KMeansImageClassificationFilter()
{
this->SetNumberOfRequiredInputs(2);
this->SetNumberOfRequiredInputs(1);
m_DefaultLabel = itk::NumericTraits<LabelType>::ZeroValue();
}
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
void
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::SetInputMask(const MaskImageType * mask)
{
this->itk::ProcessObject::SetNthInput(1, const_cast<MaskImageType *>(mask));
}
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
const typename KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::MaskImageType *
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::GetInputMask()
{
if (this->GetNumberOfInputs() < 2)
{
return ITK_NULLPTR;
}
return static_cast<const MaskImageType *>(this->itk::ProcessObject::GetInput(1));
}
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
void
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::BeforeThreadedGenerateData()
{
unsigned int sample_size = MaxSampleDimension;
unsigned int nb_classes = m_Centroids.Size() / sample_size;
for (LabelType label = 1; label <= static_cast<LabelType>(nb_classes); ++label)
{
SampleType new_centroid;
new_centroid.Fill(0);
m_CentroidsMap[label] = new_centroid;
for (unsigned int i = 0; i < MaxSampleDimension; ++i)
{
m_CentroidsMap[label][i] =
static_cast<ValueType>(m_Centroids[MaxSampleDimension * (static_cast < unsigned int > (label) - 1) + i]);
}
}
}
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
void
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::ThreadedGenerateData(const OutputImageRegionType& outputRegionForThread, itk::ThreadIdType itkNotUsed(threadId))
{
InputImageConstPointerType inputPtr = this->GetInput();
MaskImageConstPointerType inputMaskPtr = this->GetInputMask();
OutputImagePointerType outputPtr = this->GetOutput();
typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
typedef itk::ImageRegionConstIterator<MaskImageType> MaskIteratorType;
typedef itk::ImageRegionIterator<OutputImageType> OutputIteratorType;
InputIteratorType inIt(inputPtr, outputRegionForThread);
OutputIteratorType outIt(outputPtr, outputRegionForThread);
MaskIteratorType maskIt;
if (inputMaskPtr)
{
maskIt = MaskIteratorType(inputMaskPtr, outputRegionForThread);
maskIt.GoToBegin();
}
unsigned int maxDimension = SampleType::Dimension;
unsigned int sampleSize = std::min(inputPtr->GetNumberOfComponentsPerPixel(),
maxDimension);
bool validPoint = true;
while (!outIt.IsAtEnd())
{
outIt.Set(m_DefaultLabel);
++outIt;
}
outIt.GoToBegin();
validPoint = true;
typename DistanceType::Pointer distance = DistanceType::New();
while (!outIt.IsAtEnd() && (!inIt.IsAtEnd()))
{
if (inputMaskPtr)
{
validPoint = maskIt.Get() > 0;
++maskIt;
}
if (validPoint)
{
LabelType label = 1;
LabelType current_label = 1;
SampleType pixel;
pixel.Fill(0);
for (unsigned int i = 0; i < sampleSize; ++i)
{
pixel[i] = inIt.Get()[i];
}
double current_distance = distance->Evaluate(pixel, m_CentroidsMap[label]);
for (label = 2; label <= static_cast<LabelType>(m_CentroidsMap.size()); ++label)
{
double tmp_dist = distance->Evaluate(pixel, m_CentroidsMap[label]);
if (tmp_dist < current_distance)
{
current_label = label;
current_distance = tmp_dist;
}
}
outIt.Set(current_label);
}
++outIt;
++inIt;
}
}
/**
* PrintSelf Method
*/
template <class TInputImage, class TOutputImage, unsigned int VMaxSampleDimension, class TMaskImage>
void
KMeansImageClassificationFilter<TInputImage, TOutputImage, VMaxSampleDimension, TMaskImage>
::PrintSelf(std::ostream& os, itk::Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
} // End namespace otb
#endif
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