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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkSimpleMultiResolutionImageRegistrationUI.h,v $
Language: C++
Date: $Date: 2004-12-21 22:47:32 $
Version: $Revision: 1.5 $
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 _itkSimpleMultiResolutionImageRegistrationUI_h
#define _itkSimpleMultiResolutionImageRegistrationUI_h
#include "itkMultiResolutionImageRegistrationMethod.h"
#include "itkCommand.h"
#include "itkArray.h"
#include "itkGradientDescentOptimizer.h"
// The following classes are examples of simple user interface
// that controls a MultiResolutionImageRegistrationMethod process
template <typename TRegistrator>
class SimpleMultiResolutionImageRegistrationUI
{
public:
SimpleMultiResolutionImageRegistrationUI( TRegistrator * ptr )
{
if ( !ptr ) return;
m_Registrator = ptr;
typename itk::SimpleMemberCommand<SimpleMultiResolutionImageRegistrationUI>::Pointer
iterationCommand =
itk::SimpleMemberCommand<SimpleMultiResolutionImageRegistrationUI>::New();
iterationCommand->SetCallbackFunction( this,
&SimpleMultiResolutionImageRegistrationUI::StartNewLevel );
m_Tag = m_Registrator->AddObserver( itk::IterationEvent(), iterationCommand );
}
virtual ~SimpleMultiResolutionImageRegistrationUI()
{
if( m_Registrator ) { m_Registrator->RemoveObserver( m_Tag ); }
}
virtual void StartNewLevel()
{
std::cout << "--- Starting level " << m_Registrator->GetCurrentLevel()
<< std::endl;
}
protected:
typename TRegistrator::Pointer m_Registrator;
unsigned long m_Tag;
};
// This UI supports registration methods with gradient descent
// type optimizers.
// This UI allows the number of iterations and learning rate
// to be changes at each resolution level.
template <typename TRegistration>
class SimpleMultiResolutionImageRegistrationUI2 :
public SimpleMultiResolutionImageRegistrationUI<TRegistration>
{
public:
typedef SimpleMultiResolutionImageRegistrationUI<TRegistration>
Superclass;
SimpleMultiResolutionImageRegistrationUI2( TRegistration * ptr ) :
Superclass(ptr) {};
virtual ~SimpleMultiResolutionImageRegistrationUI2(){}
void SetNumberOfIterations( itk::Array<unsigned int> & iter )
{
m_NumberOfIterations = iter;
}
void SetLearningRates( itk::Array<double> & rates )
{
m_LearningRates = rates;
}
virtual void StartNewLevel()
{
// call the superclass's implementation
this->Superclass::StartNewLevel();
if ( !this->m_Registrator ) return;
// Try to cast the optimizer to a gradient descent type,
// return if casting didn't work.
itk::GradientDescentOptimizer::Pointer optimizer;
optimizer = dynamic_cast< itk::GradientDescentOptimizer * >(
this->m_Registrator->GetOptimizer() );
if ( !optimizer ) return;
unsigned int level = this->m_Registrator->GetCurrentLevel();
if ( m_NumberOfIterations.Size() >= level + 1 )
{
optimizer->SetNumberOfIterations( m_NumberOfIterations[level] );
}
if ( m_LearningRates.Size() >= level + 1 )
{
optimizer->SetLearningRate( m_LearningRates[level] );
}
std::cout << " No. Iterations: "
<< optimizer->GetNumberOfIterations()
<< " Learning rate: "
<< optimizer->GetLearningRate()
<< std::endl;
}
private:
itk::Array<unsigned int> m_NumberOfIterations;
itk::Array<double> m_LearningRates;
};
#endif
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