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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 "itkGradientRecursiveGaussianImageFilter.h"
#include "itkTestingMacros.h"
int
itkGradientRecursiveGaussianFilterSpeedTest(int argc, char * argv[])
{
if (argc != 3)
{
std::cerr << "usage: " << itkNameOfTestExecutableMacro(argv) << " size reps" << std::endl;
return EXIT_FAILURE;
}
int imageSize = std::stoi(argv[1]);
int reps = std::stoi(argv[2]);
std::cout << "imageSize: " << imageSize << " reps: " << reps << std::endl;
// Define the dimension of the images
constexpr unsigned int myDimension = 3;
// Declare the types of the images
using myImageType = itk::Image<float, myDimension>;
// Declare the type of the index to access images
using myIndexType = itk::Index<myDimension>;
// Declare the type of the size
using mySizeType = itk::Size<myDimension>;
// Declare the type of the Region
using myRegionType = itk::ImageRegion<myDimension>;
// Create the image
auto inputImage = myImageType::New();
// Define their size, and start index
mySizeType size;
size[0] = imageSize;
size[1] = imageSize;
size[2] = imageSize;
myIndexType start;
start.Fill(0);
myRegionType region{ start, size };
// Initialize Image A
inputImage->SetRegions(region);
inputImage->Allocate();
// Declare Iterator type for the input image
using myIteratorType = itk::ImageRegionIteratorWithIndex<myImageType>;
// Create one iterator for the Input Image A (this is a light object)
myIteratorType it(inputImage, inputImage->GetRequestedRegion());
// Initialize the content of Image A
while (!it.IsAtEnd())
{
it.Set(0.0);
++it;
}
size.Fill(imageSize - 4);
start[0] = 2;
start[1] = 2;
start[2] = 2;
// Create one iterator for an internal region
myRegionType innerRegion{ start, size };
myIteratorType itb(inputImage, innerRegion);
// Initialize the content the internal region
while (!itb.IsAtEnd())
{
itb.Set(100.0);
++itb;
}
// Declare the type for the
using myFilterType = itk::GradientRecursiveGaussianImageFilter<myImageType>;
using myGradientImageType = myFilterType::OutputImageType;
// Create a Filter
auto filter = myFilterType::New();
// Connect the input images
filter->SetInput(inputImage);
// loop
for (int i = 0; i < reps; ++i)
{
// Select the value of Sigma
filter->SetSigma(2.5 + reps / 100.0);
// Execute the filter
filter->Update();
}
if (reps > 0)
{
// 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
myGradientImageType::Pointer outputImage = filter->GetOutput();
// Declare Iterator type for the output image
using myOutputIteratorType = itk::ImageRegionIteratorWithIndex<myGradientImageType>;
// Create an iterator for going through the output image
myOutputIteratorType itg(outputImage, outputImage->GetRequestedRegion());
// Print the content of the result image
std::cout << " Result " << std::endl;
itg.GoToBegin();
std::cout << itg.Get();
std::cout << std::endl;
}
return EXIT_SUCCESS;
}
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