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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 "itkSimilarityIndexImageFilter.h"
#include "itkMath.h"
#include "itkTestingMacros.h"
int
itkSimilarityIndexImageFilterTest(int, char *[])
{
using Pixel1Type = unsigned char;
using Pixel2Type = float;
enum
{
ImageDimension = 2
};
using Image1Type = itk::Image<Pixel1Type, ImageDimension>;
using Image2Type = itk::Image<Pixel2Type, ImageDimension>;
auto image1 = Image1Type::New();
auto image2 = Image2Type::New();
Image1Type::SizeType size;
size.Fill(8);
image1->SetRegions(size);
image2->SetRegions(size);
image1->Allocate();
image2->Allocate();
unsigned long numOfPixels = image1->GetBufferedRegion().GetNumberOfPixels();
unsigned long lower1 = 0;
unsigned long upper1 = static_cast<unsigned long>(static_cast<double>(numOfPixels) * 0.75) - 1;
auto lower2 = static_cast<unsigned long>(static_cast<double>(numOfPixels) * 0.25);
unsigned long upper2 = numOfPixels - 1;
itk::ImageRegionIterator<Image1Type> it1(image1, image1->GetBufferedRegion());
itk::ImageRegionIterator<Image2Type> it2(image2, image2->GetBufferedRegion());
unsigned long count = 0;
while (!it1.IsAtEnd() || !it2.IsAtEnd())
{
if (!it1.IsAtEnd())
{
if (lower1 <= count && count <= upper1)
{
it1.Set(5);
}
else
{
it1.Set(0);
}
++it1;
}
if (!it2.IsAtEnd())
{
if (lower2 <= count && count <= upper2)
{
it2.Set(7.2);
}
else
{
it2.Set(0);
}
++it2;
}
++count;
}
using FilterType = itk::SimilarityIndexImageFilter<Image1Type, Image2Type>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, SimilarityIndexImageFilter, ImageToImageFilter);
filter->SetInput1(image1);
filter->SetInput2(image2);
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
// check results
FilterType::RealType trueOverlap = 0.5 / 0.75;
FilterType::RealType overlap = filter->GetSimilarityIndex();
std::cout << " True index: " << trueOverlap << std::endl;
std::cout << " Computed index: " << overlap << std::endl;
if (itk::Math::abs(trueOverlap - overlap) > 0.1)
{
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
// test case where both images are zero
auto image3 = Image1Type::New();
auto image4 = Image2Type::New();
image3->SetRegions(image1->GetBufferedRegion());
image3->Allocate();
image3->FillBuffer(0);
image4->SetRegions(image2->GetBufferedRegion());
image4->Allocate();
image4->FillBuffer(0);
filter->SetInput1(image3);
filter->SetInput2(image4);
filter->Update();
if (itk::Math::NotExactlyEquals(filter->GetSimilarityIndex(), 0))
{
std::cout << "Overlap: " << filter->GetSimilarityIndex() << std::endl;
std::cout << "Zero overlap expected." << std::endl;
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed. " << std::endl;
return EXIT_SUCCESS;
}
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