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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 "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkRobustAutomaticThresholdImageFilter.h"
#include "itkGradientMagnitudeRecursiveGaussianImageFilter.h"
#include "itkMath.h"
#include "itkTestingMacros.h"
int
itkRobustAutomaticThresholdImageFilterTest(int argc, char * argv[])
{
if (argc != 7)
{
std::cerr << "Missing parameters." << std::endl;
std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv);
std::cerr << " inputImage outputImage pow insideValue outsideValue expectedThreshold" << std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int Dimension = 2;
using PixelType = unsigned short;
using ImageType = itk::Image<PixelType, Dimension>;
using RealPixelType = float;
using RealImageType = itk::Image<RealPixelType, Dimension>;
using ReaderType = itk::ImageFileReader<ImageType>;
auto reader = ReaderType::New();
reader->SetFileName(argv[1]);
using GradientType = itk::GradientMagnitudeRecursiveGaussianImageFilter<ImageType, RealImageType>;
auto gradient = GradientType::New();
gradient->SetInput(reader->GetOutput());
gradient->SetSigma(10);
ITK_TRY_EXPECT_NO_EXCEPTION(gradient->Update());
using FilterType = itk::RobustAutomaticThresholdImageFilter<ImageType, RealImageType>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, RobustAutomaticThresholdImageFilter, ImageToImageFilter);
itk::SimpleFilterWatcher watcher(filter, "RobustAutomaticThresholdImageFilter");
filter->SetGradientImage(gradient->GetOutput());
double pow = std::stod(argv[3]);
filter->SetPow(pow);
ITK_TEST_SET_GET_VALUE(pow, filter->GetPow());
auto insideValue = static_cast<FilterType::InputPixelType>(std::stod(argv[4]));
filter->SetInsideValue(insideValue);
ITK_TEST_SET_GET_VALUE(insideValue, filter->GetInsideValue());
auto outsideValue = static_cast<FilterType::InputPixelType>(std::stod(argv[5]));
filter->SetOutsideValue(outsideValue);
ITK_TEST_SET_GET_VALUE(outsideValue, filter->GetOutsideValue());
filter->SetInput(reader->GetOutput());
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
// Regression test
auto expectedThreshold = static_cast<FilterType::InputPixelType>(std::stod(argv[6]));
FilterType::InputPixelType computedThreshold = filter->GetThreshold();
if (itk::Math::NotAlmostEquals(expectedThreshold, computedThreshold))
{
std::cerr << "Test failed!" << std::endl;
std::cerr << "Error in ik::RobustAutomaticThresholdImageFilter::GetThreshold" << std::endl;
std::cerr << "Expected: "
<< static_cast<itk::NumericTraits<FilterType::InputPixelType>::PrintType>(expectedThreshold) << std::endl;
std::cerr << ", but got: "
<< static_cast<itk::NumericTraits<FilterType::InputPixelType>::PrintType>(computedThreshold) << std::endl;
return EXIT_FAILURE;
}
using WriterType = itk::ImageFileWriter<ImageType>;
auto writer = WriterType::New();
writer->SetInput(filter->GetOutput());
writer->SetFileName(argv[2]);
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
std::cout << "Test finished." << std::endl;
return EXIT_SUCCESS;
}
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