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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.
*
*=========================================================================*/
// Native ITK stuff
#include "itkSimpleFilterWatcher.h"
// Spatial function stuff
#include "itkSphereSpatialFunction.h"
#include "itkFloodFilledSpatialFunctionConditionalIterator.h"
// DOG gradient related stuff
#include "itkBinomialBlurImageFilter.h"
#include "itkDifferenceOfGaussiansGradientImageFilter.h"
#include "itkVectorMagnitudeImageFilter.h"
/*
This file tests:
itkDifferenceOfGaussiansGradientImageFilter
*/
int
itkDifferenceOfGaussiansGradientTest(int, char *[])
{
constexpr unsigned int dim = 3;
// Image type alias
using TImageType = itk::Image<unsigned char, dim>;
//-----------------Create a new input image--------------------
// Image size and spacing parameters
TImageType::SizeValueType sourceImageSize[] = { 20, 20, 20 };
TImageType::SpacingValueType sourceImageSpacing[] = { 1.0, 1.0, 1.0 };
TImageType::PointValueType sourceImageOrigin[] = { 0, 0, 0 };
// Creates the sourceImage (but doesn't set the size or allocate memory)
auto sourceImage = TImageType::New();
sourceImage->SetOrigin(sourceImageOrigin);
sourceImage->SetSpacing(sourceImageSpacing);
printf("New sourceImage created\n");
//-----The following block allocates the sourceImage-----
// Create a size object native to the sourceImage type
TImageType::SizeType sourceImageSizeObject;
// Set the size object to the array defined earlier
sourceImageSizeObject.SetSize(sourceImageSize);
// Create a region object native to the sourceImage type
TImageType::RegionType largestPossibleRegion;
// Resize the region
largestPossibleRegion.SetSize(sourceImageSizeObject);
// Set the largest legal region size (i.e. the size of the whole sourceImage), the buffered, and
// the requested region to what we just defined.
sourceImage->SetRegions(largestPossibleRegion);
// Now allocate memory for the sourceImage
sourceImage->Allocate();
printf("New sourceImage allocated\n");
// Initialize the image to hold all 0's
itk::ImageRegionIterator<TImageType> it(sourceImage, largestPossibleRegion);
for (it.GoToBegin(); !it.IsAtEnd(); ++it)
{
it.Set(0);
}
//---------Create and initialize a spatial function-----------
using TFunctionType = itk::SphereSpatialFunction<dim>;
using TFunctionPositionType = TFunctionType::InputType;
// Create and initialize a new sphere function
auto spatialFunc = TFunctionType::New();
spatialFunc->SetRadius(5);
TFunctionPositionType center;
center[0] = 10;
center[1] = 10;
center[2] = 10;
spatialFunc->SetCenter(center);
printf("Sphere spatial function created\n");
//---------Create and initialize a spatial function iterator-----------
TImageType::IndexType seedPos;
const TImageType::IndexValueType pos[] = { 10, 10, 10 };
seedPos.SetIndex(pos);
using TItType = itk::FloodFilledSpatialFunctionConditionalIterator<TImageType, TFunctionType>;
TItType sfi(sourceImage, spatialFunc, seedPos);
//
// show seed indices
std::cout << "Seeds for FloodFilledSpatialFunctionConditionalIterator" << std::endl;
for (const auto & seed : sfi.GetSeeds())
{
std::cout << seed << ' ';
}
std::cout << std::endl;
// Iterate through the entire image and set interior pixels to 255
for (; !(sfi.IsAtEnd()); ++sfi)
{
sfi.Set(255);
}
std::cout << "Spatial function iterator created, sphere drawn" << std::endl;
//--------------------Do blurring----------------
using TOutputType = TImageType;
// Create a binomial blur filter
itk::BinomialBlurImageFilter<TImageType, TOutputType>::Pointer binfilter;
binfilter = itk::BinomialBlurImageFilter<TImageType, TOutputType>::New();
sourceImage->SetRequestedRegion(sourceImage->GetLargestPossibleRegion());
// Set filter parameters
binfilter->SetInput(sourceImage);
binfilter->SetRepetitions(4);
// Set up the output of the filter
TImageType::Pointer blurredImage = binfilter->GetOutput();
// Execute the filter
binfilter->Update();
std::cout << "Binomial blur filter updated" << std::endl;
//------------Finally we can test the DOG filter------------
// Create a differennce of gaussians gradient filter
using TDOGFilterType = itk::DifferenceOfGaussiansGradientImageFilter<TOutputType, double>;
auto DOGFilter = TDOGFilterType::New();
itk::SimpleFilterWatcher watcher(DOGFilter);
// We're filtering the output of the binomial filter
DOGFilter->SetInput(blurredImage);
// Test the get/set macro for width
DOGFilter->SetWidth(4);
unsigned int theWidth = DOGFilter->GetWidth();
std::cout << "DOGFilter->GetWidth(): " << theWidth << std::endl;
// Get the output of the gradient filter
TDOGFilterType::TOutputImage::Pointer gradientImage = DOGFilter->GetOutput();
// Go!
DOGFilter->Update();
//-------------Test vector magnitude-------------
using VectorMagType = itk::VectorMagnitudeImageFilter<TDOGFilterType::TOutputImage, itk::Image<unsigned char, dim>>;
auto vectorMagFilter = VectorMagType::New();
vectorMagFilter->SetInput(gradientImage);
vectorMagFilter->Update();
return EXIT_SUCCESS;
}
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