downsample types

packages/downsample/downsample.cxx

@@ -24,9 +24,86 @@
 #include "itkDiscreteGaussianImageFilter.h"
 #include "itkLinearInterpolateImageFunction.h"
 #include "itkResampleImageFilter.h"
+#include "itkVectorIndexSelectionCastImageFilter.h"
+#include "itkComposeImageFilter.h"
 
 #include "downsampleSigma.h"
 
+// Scalar image processing
+template <typename TImage>
+int
+DownsampleScalarImage(itk::wasm::Pipeline & pipeline, const TImage * inputImage)
+{
+  using ImageType = TImage;
+  constexpr unsigned int ImageDimension = ImageType::ImageDimension;
+
+  pipeline.get_option("input")->required()->type_name("INPUT_IMAGE");
+
+  std::vector<unsigned int> shrinkFactors{ 2, 2 };
+  pipeline.add_option("-s,--shrink-factors", shrinkFactors, "Shrink factors")->required()->type_size(ImageDimension);
+
+  std::vector<unsigned int> cropRadius;
+  pipeline.add_option("-r,--crop-radius", cropRadius, "Optional crop radius in pixel units.")
+    ->type_size(ImageDimension);
+
+  using OutputImageType = itk::wasm::OutputImage<ImageType>;
+  OutputImageType downsampledImage;
+  pipeline.add_option("downsampled", downsampledImage, "Output downsampled image")
+    ->required()
+    ->type_name("OUTPUT_IMAGE");
+
+  ITK_WASM_PARSE(pipeline);
+
+  auto sigmaValues = downsampleSigma(shrinkFactors);
+
+  using GaussianFilterType = itk::DiscreteGaussianImageFilter<ImageType, ImageType>;
+  auto gaussianFilter = GaussianFilterType::New();
+  gaussianFilter->SetInput(inputImage);
+  typename GaussianFilterType::ArrayType sigmaArray;
+  for (unsigned int i = 0; i < ImageDimension; ++i)
+  {
+    sigmaArray[i] = sigmaValues[i];
+  }
+  gaussianFilter->SetSigmaArray(sigmaArray);
+  gaussianFilter->SetUseImageSpacingOff();
+
+  const auto inputOrigin = inputImage->GetOrigin();
+  const auto inputSpacing = inputImage->GetSpacing();
+  const auto inputSize = inputImage->GetLargestPossibleRegion().GetSize();
+
+  typename ImageType::PointType   outputOrigin;
+  typename ImageType::SpacingType outputSpacing;
+  typename ImageType::SizeType    outputSize;
+  for (unsigned int i = 0; i < ImageDimension; ++i)
+  {
+    const double cropRadiusValue = cropRadius.size() ? cropRadius[i] : 0.0;
+
+    outputOrigin[i] = inputOrigin[i] + cropRadiusValue * inputSpacing[i];
+    outputSpacing[i] = inputSpacing[i] * shrinkFactors[i];
+    outputSize[i] = std::max<itk::SizeValueType>(0, (inputSize[i] - 2 * cropRadiusValue) / shrinkFactors[i]);
+  }
+
+  using InterpolatorType = itk::LinearInterpolateImageFunction<ImageType, double>;
+  auto interpolator = InterpolatorType::New();
+
+  using ResampleFilterType = itk::ResampleImageFilter<ImageType, ImageType>;
+  auto shrinkFilter = ResampleFilterType::New();
+  shrinkFilter->SetInput(gaussianFilter->GetOutput());
+  shrinkFilter->SetInterpolator(interpolator);
+  shrinkFilter->SetOutputOrigin(outputOrigin);
+  shrinkFilter->SetOutputSpacing(outputSpacing);
+  shrinkFilter->SetOutputDirection(inputImage->GetDirection());
+  shrinkFilter->SetSize(outputSize);
+  shrinkFilter->SetOutputStartIndex(inputImage->GetLargestPossibleRegion().GetIndex());
+
+  ITK_WASM_CATCH_EXCEPTION(pipeline, shrinkFilter->UpdateLargestPossibleRegion());
+
+  typename ImageType::ConstPointer result = shrinkFilter->GetOutput();
+  downsampledImage.Set(result);
+
+  return EXIT_SUCCESS;
+}
+
 template <typename TImage>
 class PipelineFunctor
 {
@@ -39,44 +116,64 @@ class PipelineFunctor
 
     using InputImageType = itk::wasm::InputImage<ImageType>;
     InputImageType inputImage;
+    pipeline.add_option("input", inputImage, "Input image")->type_name("INPUT_IMAGE");
+
+    ITK_WASM_PRE_PARSE(pipeline);
+
+    typename ImageType::ConstPointer image = inputImage.Get();
+    return DownsampleScalarImage<ImageType>(pipeline, image);
+  }
+};
+
+// Specialization for VectorImage types
+template <typename TPixel, unsigned int VDimension>
+class PipelineFunctor<itk::VectorImage<TPixel, VDimension>>
+{
+public:
+  int
+  operator()(itk::wasm::Pipeline & pipeline)
+  {
+    constexpr unsigned int Dimension = VDimension;
+    using PixelType = TPixel;
+    using VectorImageType = itk::VectorImage<PixelType, Dimension>;
+    using ScalarImageType = itk::Image<PixelType, Dimension>;
+
+    using InputImageType = itk::wasm::InputImage<VectorImageType>;
+    InputImageType inputImage;
     pipeline.add_option("input", inputImage, "Input image")->required()->type_name("INPUT_IMAGE");
 
     std::vector<unsigned int> shrinkFactors{ 2, 2 };
-    pipeline.add_option("-s,--shrink-factors", shrinkFactors, "Shrink factors")->required()->type_size(ImageDimension);
+    pipeline.add_option("-s,--shrink-factors", shrinkFactors, "Shrink factors")->required()->type_size(Dimension);
 
     std::vector<unsigned int> cropRadius;
     pipeline.add_option("-r,--crop-radius", cropRadius, "Optional crop radius in pixel units.")
-      ->type_size(ImageDimension);
+      ->type_size(Dimension);
 
-    using OutputImageType = itk::wasm::OutputImage<ImageType>;
+    using OutputImageType = itk::wasm::OutputImage<VectorImageType>;
     OutputImageType downsampledImage;
     pipeline.add_option("downsampled", downsampledImage, "Output downsampled image")
       ->required()
       ->type_name("OUTPUT_IMAGE");
 
     ITK_WASM_PARSE(pipeline);
 
-    auto sigmaValues = downsampleSigma(shrinkFactors);
+    // Get number of components
+    const unsigned int numberOfComponents = inputImage.Get()->GetNumberOfComponentsPerPixel();
 
-    using GaussianFilterType = itk::DiscreteGaussianImageFilter<ImageType, ImageType>;
-    auto gaussianFilter = GaussianFilterType::New();
-    gaussianFilter->SetInput(inputImage.Get());
-    typename GaussianFilterType::ArrayType sigmaArray;
-    for (unsigned int i = 0; i < ImageDimension; ++i)
-    {
-      sigmaArray[i] = sigmaValues[i];
-    }
-    gaussianFilter->SetSigmaArray(sigmaArray);
-    gaussianFilter->SetUseImageSpacingOff();
+    // Extract, process, and compose each component
+    using ExtractFilterType = itk::VectorIndexSelectionCastImageFilter<VectorImageType, ScalarImageType>;
+    using ComposeFilterType = itk::ComposeImageFilter<ScalarImageType>;
+
+    auto sigmaValues = downsampleSigma(shrinkFactors);
 
     const auto inputOrigin = inputImage.Get()->GetOrigin();
     const auto inputSpacing = inputImage.Get()->GetSpacing();
     const auto inputSize = inputImage.Get()->GetLargestPossibleRegion().GetSize();
 
-    typename ImageType::PointType   outputOrigin;
-    typename ImageType::SpacingType outputSpacing;
-    typename ImageType::SizeType    outputSize;
-    for (unsigned int i = 0; i < ImageDimension; ++i)
+    typename VectorImageType::PointType   outputOrigin;
+    typename VectorImageType::SpacingType outputSpacing;
+    typename VectorImageType::SizeType    outputSize;
+    for (unsigned int i = 0; i < Dimension; ++i)
     {
       const double cropRadiusValue = cropRadius.size() ? cropRadius[i] : 0.0;
 
@@ -85,23 +182,51 @@ class PipelineFunctor
       outputSize[i] = std::max<itk::SizeValueType>(0, (inputSize[i] - 2 * cropRadiusValue) / shrinkFactors[i]);
     }
 
-    using InterpolatorType = itk::LinearInterpolateImageFunction<ImageType, double>;
-    auto interpolator = InterpolatorType::New();
+    auto composeFilter = ComposeFilterType::New();
+
+    auto extractFilter = ExtractFilterType::New();
+    extractFilter->SetInput(inputImage.Get());
+
+    using GaussianFilterType = itk::DiscreteGaussianImageFilter<ScalarImageType, ScalarImageType>;
+    auto gaussianFilter = GaussianFilterType::New();
+
+    for (unsigned int component = 0; component < numberOfComponents; ++component)
+    {
+      // Extract component
+      extractFilter->SetIndex(component);
+
+      // Smooth component
+      gaussianFilter->SetInput(extractFilter->GetOutput());
+      typename GaussianFilterType::ArrayType sigmaArray;
+      for (unsigned int i = 0; i < Dimension; ++i)
+      {
+        sigmaArray[i] = sigmaValues[i];
+      }
+      gaussianFilter->SetSigmaArray(sigmaArray);
+      gaussianFilter->SetUseImageSpacingOff();
 
-    using ResampleFilterType = itk::ResampleImageFilter<ImageType, ImageType>;
-    auto shrinkFilter = ResampleFilterType::New();
-    shrinkFilter->SetInput(gaussianFilter->GetOutput());
-    shrinkFilter->SetInterpolator(interpolator);
-    shrinkFilter->SetOutputOrigin(outputOrigin);
-    shrinkFilter->SetOutputSpacing(outputSpacing);
-    shrinkFilter->SetOutputDirection(inputImage.Get()->GetDirection());
-    shrinkFilter->SetSize(outputSize);
-    shrinkFilter->SetOutputStartIndex(inputImage.Get()->GetLargestPossibleRegion().GetIndex());
+      // Resample component
+      using InterpolatorType = itk::LinearInterpolateImageFunction<ScalarImageType, double>;
+      auto interpolator = InterpolatorType::New();
+
+      using ResampleFilterType = itk::ResampleImageFilter<ScalarImageType, ScalarImageType>;
+      auto shrinkFilter = ResampleFilterType::New();
+      shrinkFilter->SetInput(gaussianFilter->GetOutput());
+      shrinkFilter->SetInterpolator(interpolator);
+      shrinkFilter->SetOutputOrigin(outputOrigin);
+      shrinkFilter->SetOutputSpacing(outputSpacing);
+      shrinkFilter->SetOutputDirection(inputImage.Get()->GetDirection());
+      shrinkFilter->SetSize(outputSize);
+      shrinkFilter->SetOutputStartIndex(inputImage.Get()->GetLargestPossibleRegion().GetIndex());
+      shrinkFilter->UpdateLargestPossibleRegion();
+
+      // Add to compose filter
+      composeFilter->SetInput(component, shrinkFilter->GetOutput());
+    }
 
-    ITK_WASM_CATCH_EXCEPTION(pipeline, shrinkFilter->UpdateLargestPossibleRegion());
+    ITK_WASM_CATCH_EXCEPTION(pipeline, composeFilter->UpdateLargestPossibleRegion());
 
-    typename ImageType::ConstPointer result = shrinkFilter->GetOutput();
-    downsampledImage.Set(result);
+    downsampledImage.Set(composeFilter->GetOutput());
 
     return EXIT_SUCCESS;
   }
@@ -123,5 +248,11 @@ main(int argc, char * argv[])
                                            uint64_t,
                                            int64_t,
                                            float,
-                                           double>::Dimensions<2U, 3U, 4U, 5U>("input", pipeline);
+                                           double,
+                                           itk::VariableLengthVector<uint8_t>,
+                                           itk::VariableLengthVector<uint16_t>,
+                                           itk::VariableLengthVector<int16_t>,
+                                           itk::VariableLengthVector<float>,
+                                           itk::VariableLengthVector<double>
+                                           >::Dimensions<2U, 3U, 4U, 5U>("input", pipeline);
 }

packages/downsample/package.json

@@ -1,16 +1,15 @@
 {
   "name": "@itk-wasm/downsample-build",
-  "version": "1.7.1",
+  "version": "1.8.0",
   "private": true,
   "description": "Pipelines for downsampling images.",
   "type": "module",
   "itk-wasm": {
     "emscripten-docker-image": "quay.io/itkwasm/emscripten:latest",
     "wasi-docker-image": "quay.io/itkwasm/wasi:latest",
-    "test-data-hash": "bafkreic7utwwa32sc7ekhouzdlnla4kffytphcwc7qwam5ndhixwjulydq",
+    "test-data-hash": "bafkreigtrr3oeqaunbyhrpuvvhc5hfmpbddc4u52jvonsvr2m2xe5ni3jq",
     "test-data-urls": [
-      "https://github.com/InsightSoftwareConsortium/ITK-Wasm/releases/download/itk-wasm-v1.0.0-b.163/itkwasm-downsample-test-data.tar.gz https://w3s.link/ipfs/bafybeifwebok64osjl2i3zc6rkn3izgon333wsjotqzqlxorkkvrbldjcy/data.tar.gz",
-      "https://w3s.link/ipfs/bafybeifwebok64osjl2i3zc6rkn3izgon333wsjotqzqlxorkkvrbldjcy/data.tar.gz"
+      "https://itk.mypinata.cloud/ipfs/bafkreigtrr3oeqaunbyhrpuvvhc5hfmpbddc4u52jvonsvr2m2xe5ni3jq"
     ],
     "typescript-package-name": "@itk-wasm/downsample",
     "python-package-name": "itkwasm-downsample",
@@ -29,7 +28,7 @@
     "build:gen:typescript": "itk-wasm pnpm-script build:gen:typescript",
     "build:gen:python": "pnpm build:wasi && pnpm bindgen:python",
     "test": "pnpm test:data:download && pnpm build:gen:python && pnpm test:python",
-    "test:data:download": "dam download test/data test/data.tar.gz bafkreic7utwwa32sc7ekhouzdlnla4kffytphcwc7qwam5ndhixwjulydq https://github.com/InsightSoftwareConsortium/ITK-Wasm/releases/download/itk-wasm-v1.0.0-b.163/itkwasm-downsample-test-data.tar.gz https://w3s.link/ipfs/bafybeifwebok64osjl2i3zc6rkn3izgon333wsjotqzqlxorkkvrbldjcy/data.tar.gz",
+    "test:data:download": "dam download test/data test/data.tar.gz bafkreigtrr3oeqaunbyhrpuvvhc5hfmpbddc4u52jvonsvr2m2xe5ni3jq https://itk.mypinata.cloud/ipfs/bafkreigtrr3oeqaunbyhrpuvvhc5hfmpbddc4u52jvonsvr2m2xe5ni3jq",
     "test:data:pack": "dam pack test/data test/data.tar.gz",
     "test:python:wasi": "pnpm test:data:download && pixi run --manifest-path=./pixi.toml test-wasi",
     "test:python:emscripten": "pnpm test:data:download && pixi run --manifest-path=./pixi.toml test-emscripten",