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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkImageClassifierFilter.txx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkImageClassifierFilter_txx
#define __itkImageClassifierFilter_txx
#include "itkImageClassifierFilter.h"
namespace itk {
namespace Statistics {
template< class TSample, class TInputImage, class TOutputImage >
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::ImageClassifierFilter()
{
this->m_NumberOfClasses = 0;
this->SetNumberOfRequiredInputs( 3 );
this->SetNumberOfRequiredOutputs( 1 );
/** Initialize decision rule */
m_DecisionRule = NULL;
m_NumberOfClasses = 0;
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
os << indent << "Number of classes: "
<< this->GetNumberOfClasses()
<< std::endl;
os << indent << "Decision Rule: "
<< this->GetDecisionRule()
<< std::endl;
os << indent << "Image: "
<< this->GetImage()
<< std::endl;
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::SetImage( const InputImageType * image )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(0,
const_cast< InputImageType * >( image ) );
}
template< class TSample, class TInputImage, class TOutputImage >
const TInputImage *
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::GetImage( ) const
{
if (this->GetNumberOfInputs() < 1)
{
return 0;
}
return static_cast<const TInputImage * >
(this->ProcessObject::GetInput(0) );
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::SetClassLabels( const ClassLabelVectorObjectType * classLabels )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(1,
const_cast< ClassLabelVectorObjectType * >( classLabels ) );
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::SetMembershipFunctions( const MembershipFunctionVectorObjectType * membershipFunctions )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(2,
const_cast< MembershipFunctionVectorObjectType * >( membershipFunctions ) );
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::SetMembershipFunctionsWeightsArray( const
MembershipFunctionsWeightsArrayObjectType * weightsArray )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(3,
const_cast<
MembershipFunctionsWeightsArrayObjectType * >( weightsArray ) );
}
template< class TSample, class TInputImage, class TOutputImage >
void
ImageClassifierFilter<TSample,TInputImage,TOutputImage>
::GenerateData()
{
const ClassLabelVectorObjectType * classLabelsDecorated =
static_cast< const ClassLabelVectorObjectType * >( this->ProcessObject::GetInput( 1 ) );
const MembershipFunctionVectorObjectType * membershipFunctionsDecorated =
static_cast< const MembershipFunctionVectorObjectType * >( this->ProcessObject::GetInput( 2 ) );
const MembershipFunctionsWeightsArrayObjectType *
membershipFunctionsWeightsArrayDecorated =
static_cast< const MembershipFunctionsWeightsArrayObjectType * >( this->ProcessObject::GetInput( 3 ) );
const ClassLabelVectorType & classLabels = classLabelsDecorated->Get();
const MembershipFunctionVectorType & membershipFunctions = membershipFunctionsDecorated->Get();
// Check number of Labels and MembershipSamples against the number of classes */
if( membershipFunctions.size() != this->m_NumberOfClasses )
{
itkExceptionMacro("Number of Membership functions does not match the number of classes");
}
if( classLabels.size() != this->m_NumberOfClasses )
{
itkExceptionMacro("Number of class labels does not match the number of classes");
}
if( m_DecisionRule.IsNull())
{
itkExceptionMacro("Decision rule is not set");
}
MembershipFunctionsWeightsArrayType membershipFunctionsWeightsArray;
if( membershipFunctionsWeightsArrayDecorated == NULL )
{
// no weights array is set and hence all membership functions will have equal
// weight
membershipFunctionsWeightsArray.SetSize( this->m_NumberOfClasses );
membershipFunctionsWeightsArray.Fill(1.0);
}
else
{
membershipFunctionsWeightsArray = membershipFunctionsWeightsArrayDecorated->Get();
}
if ( membershipFunctionsWeightsArray.Size() != this->m_NumberOfClasses
)
{
itkExceptionMacro("Membership functions weight array size does not match the\
number of classes ");
}
const InputImageType * inputImage =
static_cast< const InputImageType * >( this->ProcessObject::GetInput( 0 ) );
std::vector< double > discriminantScores;
discriminantScores.resize( this->m_NumberOfClasses );
OutputImageType * outputImage = dynamic_cast< OutputImageType * >(
this->ProcessObject::GetOutput(0));
outputImage->CopyInformation( inputImage );
outputImage->SetRegions( inputImage->GetBufferedRegion() );
outputImage->Allocate();
ImageRegionConstIterator< InputImageType > inpItr( inputImage, inputImage->GetBufferedRegion() );
ImageRegionIterator< OutputImageType > outItr( outputImage, outputImage->GetBufferedRegion() );
inpItr.GoToBegin();
outItr.GoToBegin();
while( !inpItr.IsAtEnd() )
{
MeasurementVectorType measurements;
MeasurementVectorTraits::Assign( measurements, inpItr.Get() );
for (unsigned int i = 0; i < this->m_NumberOfClasses; i++)
{
discriminantScores[i] = membershipFunctionsWeightsArray[i] *
membershipFunctions[i]->Evaluate(measurements);
}
unsigned int classIndex;
classIndex = m_DecisionRule->Evaluate(discriminantScores);
OutputPixelType value = static_cast< OutputPixelType >(classLabels[classIndex]);
outItr.Set(value);
++inpItr;
++outItr;
}
}
} // end of namespace Statistics
} // end of namespace itk
#endif
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