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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 "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkPointSet.h"
#include "itkBSplineScatteredDataPointSetToImageFilter.h"
#include "itkTestingMacros.h"
/**
* In this test, we approximate a 2-D scalar field.
* The scattered data is derived from a segmented
* image. We write the output to an image for
* comparison.
*/
int
itkBSplineScatteredDataPointSetToImageFilterTest(int argc, char * argv[])
{
if (argc != 3)
{
std::cout << "Usage: " << itkNameOfTestExecutableMacro(argv) << " inputImage outputImage" << std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int ParametricDimension = 2;
constexpr unsigned int DataDimension = 1;
using PixelType = int;
using InputImageType = itk::Image<PixelType, ParametricDimension>;
using RealType = float;
using VectorType = itk::Vector<RealType, DataDimension>;
using VectorImageType = itk::Image<VectorType, ParametricDimension>;
using PointSetType = itk::PointSet<VectorImageType::PixelType, ParametricDimension>;
auto pointSet = PointSetType::New();
using ReaderType = itk::ImageFileReader<InputImageType>;
auto reader = ReaderType::New();
reader->SetFileName(argv[1]);
reader->Update();
itk::ImageRegionIteratorWithIndex<InputImageType> It(reader->GetOutput(),
reader->GetOutput()->GetLargestPossibleRegion());
// Iterate through the input image which consists of multivalued
// foreground pixels (=nonzero) and background values (=zero).
// The foreground pixels comprise the input point set.
for (It.GoToBegin(); !It.IsAtEnd(); ++It)
{
if (It.Get() != PixelType{})
{
// We extract both the 2-D location of the point
// and the pixel value of that point.
PointSetType::PointType point;
reader->GetOutput()->TransformIndexToPhysicalPoint(It.GetIndex(), point);
unsigned long i = pointSet->GetNumberOfPoints();
pointSet->SetPoint(i, point);
auto V = itk::MakeFilled<PointSetType::PixelType>(DataDimension);
V[0] = static_cast<RealType>(It.Get());
pointSet->SetPointData(i, V);
}
}
// Instantiate the B-spline filter and set the desired parameters.
using FilterType = itk::BSplineScatteredDataPointSetToImageFilter<PointSetType, VectorImageType>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, BSplineScatteredDataPointSetToImageFilter, PointSetToImageFilter);
unsigned int splineOrder = 0u;
ITK_TRY_EXPECT_EXCEPTION(filter->SetSplineOrder(splineOrder));
FilterType::ArrayType splineOrderArray;
splineOrderArray.Fill(4u);
filter->SetSplineOrder(splineOrderArray);
ITK_TEST_SET_GET_VALUE(splineOrderArray, filter->GetSplineOrder());
splineOrder = 3u;
filter->SetSplineOrder(splineOrder);
splineOrderArray.Fill(splineOrder);
ITK_TEST_SET_GET_VALUE(splineOrderArray, filter->GetSplineOrder());
unsigned int numberOfLevels = 0u;
ITK_TRY_EXPECT_EXCEPTION(filter->SetNumberOfLevels(numberOfLevels));
FilterType::ArrayType numberOfLevelsArray;
numberOfLevelsArray.Fill(4u);
filter->SetNumberOfLevels(numberOfLevelsArray);
ITK_TEST_SET_GET_VALUE(numberOfLevelsArray, filter->GetNumberOfLevels());
numberOfLevels = 3u;
filter->SetNumberOfLevels(numberOfLevels);
numberOfLevelsArray.Fill(numberOfLevels);
ITK_TEST_SET_GET_VALUE(numberOfLevelsArray, filter->GetNumberOfLevels());
FilterType::ArrayType ncps;
ncps.Fill(4u);
filter->SetNumberOfControlPoints(ncps);
ITK_TEST_SET_GET_VALUE(ncps, filter->GetNumberOfControlPoints());
FilterType::ArrayType close;
close.Fill(0u);
filter->SetCloseDimension(close);
ITK_TEST_SET_GET_VALUE(close, filter->GetCloseDimension());
// Define the parametric domain.
filter->SetOrigin(reader->GetOutput()->GetOrigin());
filter->SetSpacing(reader->GetOutput()->GetSpacing());
filter->SetSize(reader->GetOutput()->GetLargestPossibleRegion().GetSize());
filter->SetDirection(reader->GetOutput()->GetDirection());
filter->SetInput(pointSet);
ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
// Get the current number of control points to increase coverage
std::cout << "Current number of control points: " << filter->GetCurrentNumberOfControlPoints() << std::endl;
// Get the control point lattice produced by the fitting process to increase
// coverage
std::cout << "Control point lattice produced by the fitting process: " << std::endl;
std::cout << filter->GetPhiLattice() << std::endl;
VectorImageType * outputImage = filter->GetOutput();
// Write the output to an image.
using RealImageType = itk::Image<RealType, ParametricDimension>;
auto image = RealImageType::New();
image->SetRegions(reader->GetOutput()->GetLargestPossibleRegion());
image->Allocate();
itk::ImageRegionIteratorWithIndex<RealImageType> Itt(image, image->GetLargestPossibleRegion());
for (Itt.GoToBegin(); !Itt.IsAtEnd(); ++Itt)
{
Itt.Set(outputImage->GetPixel(Itt.GetIndex())[0]);
}
using WriterType = itk::ImageFileWriter<RealImageType>;
auto writer = WriterType::New();
writer->SetInput(image);
writer->SetFileName(argv[2]);
ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());
return EXIT_SUCCESS;
}
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