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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.
*
*=========================================================================*/
// Software Guide : BeginLatex
//
// The following example illustrates how to preprocess and segment images
// using the \doxygen{WatershedImageFilter} for the particular case of
// grayscale scalar image.
//
// Software Guide : EndLatex
#include "itkWatershedImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkScalarToRGBPixelFunctor.h"
#include "itkUnaryFunctorImageFilter.h"
#include "itkGradientMagnitudeRecursiveGaussianImageFilter.h"
int
main(int argc, char * argv[])
{
if (argc < 5)
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << argv[0];
std::cerr << " inputImage outputImage lowerThreshold outputScaleLevel"
<< std::endl;
return EXIT_FAILURE;
}
using InternalPixelType = float;
using RGBPixelType = itk::RGBPixel<unsigned char>;
constexpr unsigned int Dimension = 3;
using InternalImageType = itk::Image<InternalPixelType, Dimension>;
using RGBImageType = itk::Image<RGBPixelType, Dimension>;
//
// We instantiate reader and writer types
//
using ReaderType = itk::ImageFileReader<InternalImageType>;
using WriterType = itk::ImageFileWriter<RGBImageType>;
auto reader = ReaderType::New();
auto writer = WriterType::New();
reader->SetFileName(argv[1]);
writer->SetFileName(argv[2]);
//
// Instantiate the GradientMagnitude image filter
//
using GradientMagnitudeFilterType =
itk::GradientMagnitudeRecursiveGaussianImageFilter<InternalImageType,
InternalImageType>;
auto gradienMagnitudeFilter = GradientMagnitudeFilterType::New();
gradienMagnitudeFilter->SetInput(reader->GetOutput());
gradienMagnitudeFilter->SetSigma(1.0);
//
// Instantiate the Watershed filter
//
using WatershedFilterType = itk::WatershedImageFilter<InternalImageType>;
auto watershedFilter = WatershedFilterType::New();
watershedFilter->SetInput(gradienMagnitudeFilter->GetOutput());
watershedFilter->SetThreshold(std::stod(argv[3]));
watershedFilter->SetLevel(std::stod(argv[4]));
//
// Instantiate the filter that will encode the label image
// into a color image (random color attribution).
//
using ColormapFunctorType =
itk::Functor::ScalarToRGBPixelFunctor<unsigned long>;
using LabeledImageType = WatershedFilterType::OutputImageType;
using ColormapFilterType =
itk::UnaryFunctorImageFilter<LabeledImageType,
RGBImageType,
ColormapFunctorType>;
auto colorMapFilter = ColormapFilterType::New();
colorMapFilter->SetInput(watershedFilter->GetOutput());
writer->SetInput(colorMapFilter->GetOutput());
try
{
writer->Update();
}
catch (const itk::ExceptionObject & excep)
{
std::cerr << "Exception caught !" << std::endl;
std::cerr << excep << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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