SphinxExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussian/Code.cxx

/*=========================================================================
 *
 *  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 "itkImage.h"
#include "itkGradientRecursiveGaussianImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkVectorIndexSelectionCastImageFilter.h"
#include "itkVectorMagnitudeImageFilter.h"
 
int
main(int argc, char * argv[])
{
  if (argc != 5)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0];
    std::cerr << " <InputFileName> <OutputFileNameX> <OutputFileNameY> <OutputFileNameMagnitude>";
    std::cerr << std::endl;
    return EXIT_FAILURE;
  }
 
  const char * inputFileName = argv[1];
  const char * outputFileNameX = argv[2];
  const char * outputFileNameY = argv[3];
  const char * outputFileNameMagnitude = argv[4];
 
  const char * filenames[2];
  filenames[0] = outputFileNameX;
  filenames[1] = outputFileNameY;
 
  constexpr unsigned int Dimension = 2;
 
  // Input and output are png files, use unsigned char
  using PixelType = unsigned char;
  using ImageType = itk::Image<PixelType, Dimension>;
  // Double type for GradientRecursiveGaussianImageFilter
  using DoublePixelType = double;
  using DoubleImageType = itk::Image<DoublePixelType, Dimension>;
  // The output of GradientRecursiveGaussianImageFilter
  // are images of the gradient along X and Y, so the type of
  // the output is a covariant vector of dimension 2 (X, Y)
  using CovPixelType = itk::CovariantVector<DoublePixelType, Dimension>;
  using CovImageType = itk::Image<CovPixelType, Dimension>;
 
  const auto input = itk::ReadImage<ImageType>(inputFileName);
 
  using FilterType = itk::GradientRecursiveGaussianImageFilter<ImageType, CovImageType>;
  auto filter = FilterType::New();
  filter->SetInput(input);
 
  // Allows to select the X or Y output images
  using IndexSelectionType = itk::VectorIndexSelectionCastImageFilter<CovImageType, DoubleImageType>;
  auto indexSelectionFilter = IndexSelectionType::New();
  indexSelectionFilter->SetInput(filter->GetOutput());
 
  // Rescale for png output
  using RescalerType = itk::RescaleIntensityImageFilter<DoubleImageType, ImageType>;
  auto rescaler = RescalerType::New();
  rescaler->SetOutputMinimum(itk::NumericTraits<PixelType>::min());
  rescaler->SetOutputMaximum(itk::NumericTraits<PixelType>::max());
  rescaler->SetInput(indexSelectionFilter->GetOutput());
 
  // Write the X and Y images
  for (int i = 0; i < 2; ++i)
  {
    indexSelectionFilter->SetIndex(i);
 
    try
    {
      itk::WriteImage(rescaler->GetOutput(), filenames[i]);
    }
    catch (const itk::ExceptionObject & error)
    {
      std::cerr << "Error: " << error << std::endl;
      return EXIT_FAILURE;
    }
  }
 
  // Compute the magnitude of the vector and output the image
  using MagnitudeType = itk::VectorMagnitudeImageFilter<CovImageType, DoubleImageType>;
  auto magnitudeFilter = MagnitudeType::New();
  magnitudeFilter->SetInput(filter->GetOutput());
 
  // Rescale for png output
  rescaler->SetInput(magnitudeFilter->GetOutput());
 
  try
  {
    itk::WriteImage(rescaler->GetOutput(), outputFileNameMagnitude);
  }
  catch (const itk::ExceptionObject & error)
  {
    std::cerr << "Error: " << error << std::endl;
    return EXIT_FAILURE;
  }
 
  return EXIT_SUCCESS;
}