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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkBayesianClassifierImageFilterTest.cxx,v $
Language: C++
Date: $Date: 2010-01-30 21:05:25 $
Version: $Revision: 1.10 $
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.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkBayesianClassifierImageFilter.h"
#include "itkBayesianClassifierInitializationImageFilter.h"
#include "itkImageFileWriter.h"
#include "itkGradientAnisotropicDiffusionImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "../IO/itkPipelineMonitorImageFilter.h"
int itkBayesianClassifierImageFilterTest(int argc, char* argv[] )
{
if( argc < 5 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile numberOfClasses smoothingIterations" << std::endl;
return EXIT_FAILURE;
}
// setup reader
const unsigned int Dimension = 2;
typedef unsigned char InputPixelType;
typedef itk::Image< InputPixelType, Dimension > InputImageType;
typedef itk::ImageFileReader< InputImageType > ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
typedef unsigned char LabelType;
typedef float PriorType;
typedef float PosteriorType;
typedef itk::BayesianClassifierInitializationImageFilter< InputImageType >
BayesianInitializerType;
BayesianInitializerType::Pointer bayesianInitializer = BayesianInitializerType::New();
bayesianInitializer->SetInput( reader->GetOutput() );
bayesianInitializer->SetNumberOfClasses( atoi( argv[3] ) );
typedef BayesianInitializerType::OutputImageType InitialLabelImageType;
typedef itk::BayesianClassifierImageFilter<
InitialLabelImageType, LabelType, PosteriorType, PriorType > ClassifierFilterType;
ClassifierFilterType::Pointer filter = ClassifierFilterType::New();
filter->SetInput( bayesianInitializer->GetOutput() );
//
// Exercise Set/GetNumberOfSmoothingIterations()
//
filter->SetNumberOfSmoothingIterations( 1 );
if( filter->GetNumberOfSmoothingIterations() != 1 )
{
std::cerr << "Error in Set/GetNumberOfSmoothingIterations()" << std::endl;
return EXIT_FAILURE;
}
filter->SetNumberOfSmoothingIterations( 19 );
if( filter->GetNumberOfSmoothingIterations() != 19 )
{
std::cerr << "Error in Set/GetNumberOfSmoothingIterations()" << std::endl;
return EXIT_FAILURE;
}
filter->SetNumberOfSmoothingIterations( 0 );
filter->SetNumberOfSmoothingIterations( atoi( argv[4] ));
typedef ClassifierFilterType::ExtractedComponentImageType ExtractedComponentImageType;
typedef itk::GradientAnisotropicDiffusionImageFilter<
ExtractedComponentImageType, ExtractedComponentImageType > SmoothingFilterType;
SmoothingFilterType::Pointer smoother = SmoothingFilterType::New();
smoother->SetNumberOfIterations( 1 );
smoother->SetTimeStep( 0.125 );
smoother->SetConductanceParameter( 3 );
filter->SetSmoothingFilter( smoother );
//
// Exercise Set/GetSmoothingFilter()
//
if( filter->GetSmoothingFilter().GetPointer() != smoother.GetPointer() )
{
std::cerr << "Error in Set/GetSmoothingFilter()" << std::endl;
return EXIT_FAILURE;
}
filter->SetSmoothingFilter( NULL );
if( filter->GetSmoothingFilter().GetPointer() != NULL )
{
std::cerr << "Error in Set/GetSmoothingFilter()" << std::endl;
return EXIT_FAILURE;
}
filter->SetSmoothingFilter( smoother );
typedef itk::PipelineMonitorImageFilter<InputImageType> MonitorFilterType;
MonitorFilterType::Pointer monitor = MonitorFilterType::New();
monitor->SetInput(filter->GetOutput());
typedef ClassifierFilterType::OutputImageType ClassifierOutputImageType;
typedef itk::Image< unsigned char, Dimension > OutputImageType;
typedef itk::RescaleIntensityImageFilter<
ClassifierOutputImageType, OutputImageType > RescalerType;
RescalerType::Pointer rescaler = RescalerType::New();
rescaler->SetInput( monitor->GetOutput() );
rescaler->SetOutputMinimum( 0 );
rescaler->SetOutputMaximum( 255 );
typedef itk::ImageFileWriter< OutputImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
writer->SetInput( rescaler->GetOutput() );
try
{
filter->Update();
writer->Update();
}
catch( itk::ExceptionObject & excp )
{
std::cerr << "Exception caught: " << std::endl;
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
if (!monitor->VerifyAllIputCanNotStream())
{
std::cout << "pipeline did not execute as expected!" << std::endl;
return EXIT_FAILURE;
}
filter->Print( std::cout );
std::cout << "Test passed." << std::endl;
typedef ClassifierFilterType::PriorsImageType PriorsImageType;
const InputImageType * inputImage = reader->GetOutput();
PriorsImageType::Pointer priorsImage = PriorsImageType::New();
priorsImage->CopyInformation( inputImage );
priorsImage->SetRegions( inputImage->GetLargestPossibleRegion() );
priorsImage->SetNumberOfComponentsPerPixel(5);
priorsImage->Allocate();
filter->SetPriors( priorsImage );
///TEST valid image type combinations. I have a hypothesis that the vector element type for
//TestInitialLabelImageType must be the same as for TestPriorType
{
const unsigned int TestDimension = 2;
typedef unsigned char TestLabelType;
typedef float TestPosteriorType;
typedef float TestPriorType;
typedef itk::VectorImage< TestPriorType ,TestDimension > TestInitialLabelImageType;
typedef itk::BayesianClassifierImageFilter<
TestInitialLabelImageType, TestLabelType, TestPosteriorType, TestPriorType > TestClassifierFilterType;
TestClassifierFilterType::Pointer test=TestClassifierFilterType::New();
}
{
const unsigned int TestDimension = 2;
typedef unsigned char TestLabelType;
typedef float TestPosteriorType;
typedef float TestPriorType;
typedef itk::VectorImage< double ,TestDimension > TestInitialLabelImageType; //The element type MUST be the PriorType
typedef itk::BayesianClassifierImageFilter<
TestInitialLabelImageType, TestLabelType, TestPosteriorType, TestPriorType > TestClassifierFilterType;
TestClassifierFilterType::Pointer test=TestClassifierFilterType::New();
}
{
const unsigned int TestDimension = 2;
typedef unsigned char TestLabelType;
typedef float TestPosteriorType;
typedef double TestPriorType;
typedef itk::VectorImage< TestPriorType ,TestDimension > TestInitialLabelImageType; //The element type MUST be the PriorType
typedef itk::BayesianClassifierImageFilter<
TestInitialLabelImageType, TestLabelType, TestPosteriorType, TestPriorType > TestClassifierFilterType;
TestClassifierFilterType::Pointer test=TestClassifierFilterType::New();
}
return EXIT_SUCCESS;
}
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