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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 "itkUnsharpMaskImageFilter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"
int
itkUnsharpMaskImageFilterTestSimple(int, char *[])
{
// Define the dimension of the images
constexpr unsigned int Dimension = 2;
// Define the pixel types of the images
using PixelType = float;
// Declare the types of the images
using InputImageType = itk::Image<PixelType, Dimension>;
// Declare the type of the index to access images
using IndexType = itk::Index<Dimension>;
// Declare the type of the size
using SizeType = itk::Size<Dimension>;
// Declare the type of the Region
using RegionType = itk::ImageRegion<Dimension>;
// Create the input image
auto inputImage = InputImageType::New();
// Define its size, and start index
SizeType size;
size[0] = 20;
size[1] = 4;
IndexType start;
start.Fill(0);
RegionType region;
region.SetIndex(start);
region.SetSize(size);
// Initialize the input image
inputImage->SetRegions(region);
inputImage->Allocate();
// Declare an Iterator type for the input image
using InputImageIteratorType = itk::ImageRegionIteratorWithIndex<InputImageType>;
// Create one iterator for the input Image (this is a light object)
InputImageIteratorType it(inputImage, inputImage->GetRequestedRegion());
// Initialize the contents of the input image
while (!it.IsAtEnd())
{
if (it.GetIndex()[0] > itk::IndexValueType(size[0] / 2))
{
it.Set(1.0);
}
else
{
it.Set(0.0);
}
++it;
}
// Declare the type for the itk::UnsharpMaskImageFilter
using UnsharpMaskImageFilterFilterType = itk::UnsharpMaskImageFilter<InputImageType>;
using GradientImageType = UnsharpMaskImageFilterFilterType::OutputImageType;
// Create the filter
auto filter = UnsharpMaskImageFilterFilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, UnsharpMaskImageFilter, ImageToImageFilter);
itk::SimpleFilterWatcher watchit(filter);
// Connect the input images
filter->SetInput(inputImage);
UnsharpMaskImageFilterFilterType::InternalPrecisionType threshold = -0.1;
filter->SetThreshold(threshold);
ITK_TRY_EXPECT_EXCEPTION(filter->Update());
// Set the filter properties
UnsharpMaskImageFilterFilterType::SigmaArrayType::ValueType sigma = 2.5;
filter->SetSigma(sigma);
UnsharpMaskImageFilterFilterType::SigmaArrayType sigmas = filter->GetSigmas();
double tolerance = 10e-6;
for (unsigned int i = 0; i < sigmas.Size(); ++i)
{
UnsharpMaskImageFilterFilterType::SigmaArrayType::ValueType sigma2 = sigmas[i];
if (!itk::Math::FloatAlmostEqual(sigma, sigma2, 10, tolerance))
{
std::cerr.precision(static_cast<int>(itk::Math::abs(std::log10(tolerance))));
std::cerr << "Test FAILED! ";
std::cerr << "Error in the Sigma values" << std::endl;
std::cerr << "Expected " << sigma << " but got " << sigma2;
std::cerr << " along the [" << i << "]-th dimension." << std::endl;
return EXIT_FAILURE;
}
}
UnsharpMaskImageFilterFilterType::InternalPrecisionType amount = 0.8;
filter->SetAmount(amount);
ITK_TEST_SET_GET_VALUE(amount, filter->GetAmount());
threshold = 0.01;
filter->SetThreshold(threshold);
ITK_TEST_SET_GET_VALUE(threshold, filter->GetThreshold());
const bool clamp = std::is_integral_v<UnsharpMaskImageFilterFilterType::OutputPixelType>;
filter->SetClamp(clamp);
ITK_TEST_SET_GET_VALUE(clamp, filter->GetClamp());
if (clamp)
{
filter->ClampOn();
ITK_TEST_SET_GET_VALUE(true, filter->GetClamp());
}
else
{
filter->ClampOff();
ITK_TEST_SET_GET_VALUE(false, filter->GetClamp());
}
// Execute the filter
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
// Get the Smart Pointer to the Filter Output
// It is important to do it AFTER the filter is Updated
// Because the object connected to the output may be changed
// by another during GenerateData() call
GradientImageType::Pointer outputImage = filter->GetOutput();
// check that output is correct near the step
start[0] = 9;
float mins[4] = { -0.21f, -0.33f, 1.32f, 1.20f };
float maxs[4] = { -0.20f, -0.32f, 1.33f, 1.21f };
for (unsigned int i = 0; i < 4; ++i)
{
if (outputImage->GetPixel(start) < mins[i] || outputImage->GetPixel(start) > maxs[i])
{
std::cerr << "Test FAILED! Unexpected value: ";
std::cerr << outputImage->GetPixel(start) << std::endl;
std::cerr << "Expected value between " << mins[i];
std::cerr << " and " << maxs[i] << std::endl;
return EXIT_FAILURE;
}
++start[0];
}
// All objects should be automatically destroyed at this point
std::cout << std::endl << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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