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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 "itkInverseDisplacementFieldImageFilter.h"
#include "itkImageFileWriter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkThinPlateSplineKernelTransform.h"
#include "itkTestingMacros.h"
int
itkInverseDisplacementFieldImageFilterTest(int argc, char * argv[])
{
if (argc < 2)
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv);
std::cerr << " outputImage" << std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int Dimension = 2;
using VectorComponentType = float;
using VectorType = itk::Vector<VectorComponentType, Dimension>;
using DisplacementFieldType = itk::Image<VectorType, Dimension>;
using FilterType = itk::InverseDisplacementFieldImageFilter<DisplacementFieldType, DisplacementFieldType>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, InverseDisplacementFieldImageFilter, ImageToImageFilter);
itk::SimpleFilterWatcher watcher(filter);
auto kernelTransform = itk::ThinPlateSplineKernelTransform<double, FilterType::ImageDimension>::New();
filter->SetKernelTransform(kernelTransform);
ITK_TEST_SET_GET_VALUE(kernelTransform, filter->GetKernelTransform());
// Creating an input displacement field
auto field = DisplacementFieldType::New();
DisplacementFieldType::SpacingType spacing;
spacing.Fill(1.0);
DisplacementFieldType::PointType origin;
origin.Fill(0.0);
DisplacementFieldType::RegionType region;
DisplacementFieldType::SizeType size;
DisplacementFieldType::IndexType start;
size[0] = 128;
size[1] = 128;
start[0] = 0;
start[1] = 0;
region.SetSize(size);
region.SetIndex(start);
field->SetOrigin(origin);
field->SetSpacing(spacing);
field->SetRegions(region);
field->Allocate();
VectorType pixelValue;
itk::ImageRegionIteratorWithIndex<DisplacementFieldType> it(field, region);
// Fill the field with some vectors
it.GoToBegin();
while (!it.IsAtEnd())
{
DisplacementFieldType::IndexType index = it.GetIndex();
pixelValue[0] = index[0] * 2.0 - index[0];
pixelValue[1] = index[1] * 2.0 - index[1];
it.Set(pixelValue);
++it;
}
// Since the tested transform is upsampling by a factor of two, the
// size of the inverse field should be twice the size of the input
// field. All other geometry parameters are the same.
filter->SetOutputSpacing(spacing);
ITK_TEST_SET_GET_VALUE(spacing, filter->GetOutputSpacing());
// Keep the origin
filter->SetOutputOrigin(origin);
ITK_TEST_SET_GET_VALUE(origin, filter->GetOutputOrigin());
// Set the size
DisplacementFieldType::SizeType invFieldSize;
invFieldSize[0] = size[0] * 2;
invFieldSize[1] = size[1] * 2;
filter->SetSize(invFieldSize);
ITK_TEST_SET_GET_VALUE(invFieldSize, filter->GetSize());
filter->SetInput(field);
unsigned int subsamplingFactor = 16;
filter->SetSubsamplingFactor(subsamplingFactor);
ITK_TEST_SET_GET_VALUE(subsamplingFactor, filter->GetSubsamplingFactor());
ITK_TRY_EXPECT_NO_EXCEPTION(filter->UpdateLargestPossibleRegion());
// Write an image for regression testing
using WriterType = itk::ImageFileWriter<DisplacementFieldType>;
auto writer = WriterType::New();
writer->SetFileName(argv[1]);
writer->SetInput(filter->GetOutput());
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
// Now, test for loop invariant (acts as filter validation)
// f^-1(f(p1) + p1 ) - f(p1) = 0
it.GoToBegin();
while (!it.IsAtEnd())
{
DisplacementFieldType::PointType p1;
field->TransformIndexToPhysicalPoint(it.GetIndex(), p1);
DisplacementFieldType::PixelType fp1 = it.Get();
DisplacementFieldType::PointType p2;
p2[0] = p1[0] + fp1[0];
p2[1] = p1[1] + fp1[1];
DisplacementFieldType::IndexType id2 = filter->GetOutput()->TransformPhysicalPointToIndex(p2);
DisplacementFieldType::PixelType fp2 = filter->GetOutput()->GetPixel(id2);
if (itk::Math::abs(fp2[0] + fp1[0]) > 0.001 || itk::Math::abs(fp2[1] + fp1[1]) > 0.001)
{
std::cerr << "Loop invariant not satisfied for index " << it.GetIndex() << " : f^-1(f(p1) + p1 ) + f(p1) = 0"
<< std::endl;
std::cerr << "f(p1) = " << fp1 << std::endl;
std::cerr << "f^-1(f(p1) + p1 ) = " << fp2 << std::endl;
std::cerr << "diff: " << fp1[0] + fp2[0] << ", " << fp1[1] + fp2[1] << std::endl;
return EXIT_FAILURE;
}
++it;
}
std::cout << "Test finished" << std::endl;
return EXIT_SUCCESS;
}
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