ITK  5.0.0
Insight Segmentation and Registration Toolkit
SphinxExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussian/Code.cxx
/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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
*
* http://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 "itkImage.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;
// Double type for GradientRecursiveGaussianImageFilter
using DoublePixelType = double;
// 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)
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( inputFileName );
FilterType::Pointer filter = FilterType::New();
filter->SetInput( reader->GetOutput() );
// Allows to select the X or Y output images
IndexSelectionType::Pointer indexSelectionFilter = IndexSelectionType::New();
indexSelectionFilter->SetInput( filter->GetOutput() );
// Rescale for png output
RescalerType::Pointer rescaler = RescalerType::New();
rescaler->SetOutputMinimum( itk::NumericTraits< PixelType >::min() );
rescaler->SetOutputMaximum( itk::NumericTraits< PixelType >::max() );
rescaler->SetInput( indexSelectionFilter->GetOutput() );
WriterType::Pointer writer = WriterType::New();
writer->SetInput( rescaler->GetOutput() );
// Write the X and Y images
for( int i = 0; i<2;++i )
{
writer->SetFileName( filenames[i] );
indexSelectionFilter->SetIndex( i );
try
{
writer->Update();
}
catch( itk::ExceptionObject & error )
{
std::cerr << "Error: " << error << std::endl;
return EXIT_FAILURE;
}
}
// Compute the magnitude of the vector and output the image
MagnitudeType::Pointer magnitudeFilter = MagnitudeType::New();
magnitudeFilter->SetInput( filter->GetOutput() );
// Rescale for png output
rescaler->SetInput( magnitudeFilter->GetOutput() );
writer->SetFileName( outputFileNameMagnitude );
writer->SetInput( rescaler->GetOutput() );
try
{
writer->Update();
}
catch( itk::ExceptionObject & error )
{
std::cerr << "Error: " << error << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}