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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 "itkLaplacianRecursiveGaussianImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkZeroCrossingImageFilter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"
int
itkLaplacianRecursiveGaussianImageFilterTest(int argc, char * argv[])
{
if (argc < 3)
{
std::cerr << "Usage: " << std::endl;
std::cerr << itkNameOfTestExecutableMacro(argv) << " inputImage outputImage " << std::endl;
return EXIT_FAILURE;
}
const char * inputFilename = argv[1];
const char * outputFilename = argv[2];
using CharPixelType = unsigned char; // IO
using RealPixelType = double; // Operations
constexpr unsigned int Dimension = 2;
using CharImageType = itk::Image<CharPixelType, Dimension>;
using RealImageType = itk::Image<RealPixelType, Dimension>;
using ReaderType = itk::ImageFileReader<CharImageType>;
using WriterType = itk::ImageFileWriter<CharImageType>;
using CastToRealFilterType = itk::CastImageFilter<CharImageType, RealImageType>;
using CastToCharFilterType = itk::CastImageFilter<RealImageType, CharImageType>;
using RescaleFilter = itk::RescaleIntensityImageFilter<RealImageType, RealImageType>;
using LaplacianFilter = itk::LaplacianRecursiveGaussianImageFilter<RealImageType, RealImageType>;
{ // Instantiate a 6D image for testing purposes
using HighDImageType = itk::Image<RealPixelType, 6>;
using LaplacianFilterHighDType = itk::LaplacianRecursiveGaussianImageFilter<HighDImageType, HighDImageType>;
auto nDTest = LaplacianFilterHighDType::New();
}
using ZeroCrossingFilter = itk::ZeroCrossingImageFilter<RealImageType, RealImageType>;
// Setting the IO
auto reader = ReaderType::New();
auto writer = WriterType::New();
auto toReal = CastToRealFilterType::New();
auto toChar = CastToCharFilterType::New();
auto rescale = RescaleFilter::New();
// Setting the ITK pipeline filter
auto lapFilter = LaplacianFilter::New();
itk::SimpleFilterWatcher watcher(lapFilter);
auto zeroFilter = ZeroCrossingFilter::New();
reader->SetFileName(inputFilename);
writer->SetFileName(outputFilename);
// The output of an edge filter is 0 or 1
rescale->SetOutputMinimum(0);
rescale->SetOutputMaximum(255);
toReal->SetInput(reader->GetOutput());
toChar->SetInput(rescale->GetOutput());
writer->SetInput(toChar->GetOutput());
// Edge Detection by Laplacian Image Filter:
lapFilter->SetInput(toReal->GetOutput());
lapFilter->SetSigma(2.0);
zeroFilter->SetInput(lapFilter->GetOutput());
rescale->SetInput(zeroFilter->GetOutput());
// Test itkGetMacro
bool bNormalizeAcrossScale = lapFilter->GetNormalizeAcrossScale();
std::cout << "lapFilter->GetNormalizeAcrossScale(): " << bNormalizeAcrossScale << std::endl;
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
return EXIT_SUCCESS;
}
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