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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 "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkStdStreamLogOutput.h"
#include "itkPatchBasedDenoisingImageFilter.h"
#include "itkTestingMacros.h"
template <typename ImageT>
int
doDenoising(const std::string & inputFileName, const std::string & outputFileName)
{
using ReaderType = itk::ImageFileReader<ImageT>;
using FilterType = itk::PatchBasedDenoisingImageFilter<ImageT, ImageT>;
using OutputImageType = typename FilterType::OutputImageType;
using WriterType = itk::ImageFileWriter<OutputImageType>;
// Read the noisy image to be denoised
auto reader = ReaderType::New();
reader->SetFileName(inputFileName);
ITK_TRY_EXPECT_NO_EXCEPTION(reader->Update());
// Create filter and initialize
auto filter = FilterType::New();
ITK_TEST_SET_GET_BOOLEAN(filter, UseSmoothDiscPatchWeights, true);
auto kernelBandwidthSigma = typename FilterType::RealArrayType{};
ITK_TEST_SET_GET_VALUE(kernelBandwidthSigma, filter->GetKernelBandwidthSigma());
ITK_TEST_SET_GET_VALUE(0.20, filter->GetKernelBandwidthFractionPixelsForEstimation());
ITK_TEST_SET_GET_BOOLEAN(filter, ComputeConditionalDerivatives, false);
ITK_TEST_SET_GET_BOOLEAN(filter, UseFastTensorComputations, true);
ITK_TEST_SET_GET_VALUE(1.0, filter->GetKernelBandwidthMultiplicationFactor());
ITK_TEST_SET_GET_VALUE(0, filter->GetNoiseSigma());
// Use 2 threads for consistency
filter->SetNumberOfWorkUnits(2);
filter->SetInput(reader->GetOutput());
// Denoise the image
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
std::cout << "NumIndependentComponents: " << filter->GetNumIndependentComponents() << std::endl;
// Write the denoised image to file
auto writer = WriterType::New();
writer->SetFileName(outputFileName);
writer->SetInput(filter->GetOutput());
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
return EXIT_SUCCESS;
}
int
itkPatchBasedDenoisingImageFilterDefaultTest(int argc, char * argv[])
{
if (argc < 3)
{
std::cerr << "Missing parameters." << std::endl;
std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv) << " inputImageFileName outputImageFileName"
<< " numDimensions" << std::endl;
return EXIT_FAILURE;
}
// Exercise basic object methods
// Done outside the helper function in the test because GCC is limited
// when calling overloaded base class functions.
using PixelType = float;
using ImageType = itk::Image<PixelType, 3>;
using FilterType = itk::PatchBasedDenoisingImageFilter<ImageType, ImageType>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, PatchBasedDenoisingImageFilter, PatchBasedDenoisingBaseImageFilter);
const std::string inFileName(argv[1]);
const std::string outFileName(argv[2]);
const unsigned int numDimensions = std::stoi(argv[3]);
using PixelComponentType = float;
using OneComponentType = PixelComponentType;
using OneComponent2DImage = itk::Image<OneComponentType, 2>;
using OneComponent3DImage = itk::Image<OneComponentType, 3>;
if (numDimensions == 2)
{
return doDenoising<OneComponent2DImage>(inFileName, outFileName);
}
else if (numDimensions == 3)
{
return doDenoising<OneComponent3DImage>(inFileName, outFileName);
}
else
{
std::cout << "Test failed!" << std::endl;
std::cout << numDimensions << " dimensions "
<< "isn't supported in this test driver." << std::endl;
return EXIT_FAILURE;
}
}
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