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/*=========================================================================
*
* 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.
*
*=========================================================================*/
#include "itkSmoothingRecursiveGaussianImageFilter.h"
#include "itkImageFileReader.h"
#include "itkFilterWatcher.h"
#include "itkImageFileWriter.h"
#include "itkImageRegionConstIterator.h"
#include "itkTestingMacros.h"
namespace
{
template< typename TFilter >
int InPlaceTest( char * inputFilename, bool normalizeAcrossScale, typename TFilter::SigmaArrayType::ValueType sigmaValue )
{
// Read the input image
typedef itk::ImageFileReader< typename TFilter::InputImageType > ReaderType;
typename ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( inputFilename );
// Create the filter
typename TFilter::Pointer filter = TFilter::New();
filter->SetNormalizeAcrossScale( normalizeAcrossScale );
filter->SetSigma( sigmaValue );
filter->SetInput( reader->GetOutput() );
if( !filter->CanRunInPlace() )
{
std::cerr << "Test failed!" << std::endl;
std::cerr << "Expected the filter to be able to run in-place!" << std::endl;
std::cerr << "Expected itk:SmoothingRecursiveGaussianImageFilter::CanRunInPlace to be true, but got: "
<< filter->CanRunInPlace() << std::endl;
return EXIT_FAILURE;
}
TRY_EXPECT_NO_EXCEPTION( filter->Update() );
typename TFilter::OutputImageType::Pointer outputImage1 = filter->GetOutput();
outputImage1->DisconnectPipeline();
// Set the InPlace flag to On
filter->InPlaceOn();
TRY_EXPECT_NO_EXCEPTION( filter->Update() );
typename TFilter::OutputImageType::Pointer outputImage2 = filter->GetOutput();
outputImage2->DisconnectPipeline();
typedef itk::ImageRegionConstIterator< typename TFilter::OutputImageType > IteratorType;
IteratorType it1( outputImage1, outputImage1->GetBufferedRegion() );
IteratorType it2( outputImage2, outputImage2->GetBufferedRegion() );
// Check whether the values of the in-place and not in-place executions are the same
it1.GoToBegin();
it2.GoToBegin();
double epsilon = itk::NumericTraits< double >::epsilon();
while( !it1.IsAtEnd() )
{
if( !itk::Math::FloatAlmostEqual( static_cast< double >( it1.Get() ), static_cast< double >( it2.Get() ), 10, epsilon ) )
{
std::cerr.precision( static_cast< int >( itk::Math::abs( std::log10( epsilon ) ) ) );
std::cerr << "Test failed!" << std::endl;
std::cerr << "Error in pixel value at index [" << std::endl;
std::cerr << "Error in pixel value at index [" << it1.GetIndex() << "]" << std::endl;
std::cerr << "Expected value " << it1.Get() << std::endl;
std::cerr << " differs from " << it2.Get();
std::cerr << " by more than " << epsilon << std::endl;
return EXIT_FAILURE;
}
++it1;
++it2;
}
return EXIT_SUCCESS;
}
}
int itkSmoothingRecursiveGaussianImageFilterTest( int argc, char* argv[] )
{
if( argc != 5 )
{
std::cerr << "Missing parameters." << std::endl;
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile normalizeAcrossScale sigma" << std::endl;
return EXIT_FAILURE;
}
int testStatus = EXIT_SUCCESS;
// Define the dimension of the images
const unsigned int Dimension = 2;
// Declare the types of the images
typedef unsigned char PixelType;
typedef itk::Image< PixelType, Dimension > ImageType;
// Read the input image
typedef itk::ImageFileReader< ImageType > ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( argv[1] );
// Declare the type for the itk::SmoothingRecursiveGaussianImageFilter
typedef itk::SmoothingRecursiveGaussianImageFilter< ImageType > SmoothingRecursiveGaussianImageFilterType;
// Create the filter
SmoothingRecursiveGaussianImageFilterType::Pointer filter = SmoothingRecursiveGaussianImageFilterType::New();
EXERCISE_BASIC_OBJECT_METHODS( filter, SmoothingRecursiveGaussianImageFilter, InPlaceImageFilter );
FilterWatcher watcher( filter );
// Set the scale normalization flag
bool normalizeAcrossScale = atoi( argv[3] );
TEST_SET_GET_BOOLEAN( filter, NormalizeAcrossScale, normalizeAcrossScale );
// Set the value ofthe standard deviation of the Gaussian used for smoothing
SmoothingRecursiveGaussianImageFilterType::SigmaArrayType::ValueType sigmaValue = atof( argv[4] );
SmoothingRecursiveGaussianImageFilterType::SigmaArrayType sigma;
sigma.Fill( sigmaValue );
filter->SetSigma( sigmaValue );
TEST_SET_GET_VALUE( sigmaValue, filter->GetSigma() );
filter->SetSigmaArray( sigma );
TEST_SET_GET_VALUE( sigma, filter->GetSigmaArray() );
// Set the input image
filter->SetInput( reader->GetOutput() );
// Run the filter
TRY_EXPECT_NO_EXCEPTION( filter->Update() );
// Write the output
typedef itk::ImageFileWriter< ImageType > WriterType;
WriterType::Pointer writer = WriterType::New();
writer->SetFileName( argv[2] );
writer->SetInput( filter->GetOutput() );
TRY_EXPECT_NO_EXCEPTION( writer->Update() );
// Test the InPlaceOn option output
if( InPlaceTest< SmoothingRecursiveGaussianImageFilterType >( argv[1], normalizeAcrossScale, sigmaValue ) == EXIT_FAILURE )
{
testStatus = EXIT_FAILURE;
}
// All objects should be automatically destroyed at this point
std::cout << "Test finished." << std::endl;
return testStatus;
}
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