/*========================================================================= * * Copyright Insight Software Consortium * * 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.txt * * 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 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 class SimpleMultiResolutionImageRegistrationUI { public: SimpleMultiResolutionImageRegistrationUI( TRegistrator * ptr ): m_Tag(0) { if ( !ptr ) return; m_Registrator = ptr; typename itk::SimpleMemberCommand::Pointer iterationCommand = itk::SimpleMemberCommand::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 class SimpleMultiResolutionImageRegistrationUI2 : public SimpleMultiResolutionImageRegistrationUI { public: typedef SimpleMultiResolutionImageRegistrationUI Superclass; SimpleMultiResolutionImageRegistrationUI2( TRegistration * ptr ) : Superclass(ptr) {}; virtual ~SimpleMultiResolutionImageRegistrationUI2(){} void SetNumberOfIterations( itk::Array & iter ) { m_NumberOfIterations = iter; } void SetLearningRates( itk::Array & 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 = dynamic_cast< itk::GradientDescentOptimizer * >( this->m_Registrator->GetModifiableOptimizer() ); 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 m_NumberOfIterations; itk::Array m_LearningRates; }; #endif