/*========================================================================= * * 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 * * 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. * *=========================================================================*/ // Software Guide : BeginLatex // // This example illustrates how to write an image whose pixel type is // \code{CovariantVector}. For practical purposes all the content in this // example is applicable to images of pixel type \doxygen{Vector}, // \doxygen{Point} and \doxygen{FixedArray}. These pixel types are similar // in that they are all arrays of fixed size in which the components have // the same representational type. // // In order to make this example a bit more interesting we setup a pipeline // to read an image, compute its gradient and write the gradient to a file. // Gradients are represented with \doxygen{CovariantVector}s as opposed to // Vectors. In this way, gradients are transformed correctly under // \doxygen{AffineTransform}s or in general, any transform having // anisotropic scaling. // // Let's start by including the relevant header files. // // \index{ImageFileWriter!Vector images} // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet #include "itkImageFileReader.h" #include "itkImageFileWriter.h" // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // We use the \doxygen{GradientRecursiveGaussianImageFilter} in order to // compute the image gradient. The output of this filter is an image whose // pixels are CovariantVectors. // // \index{itk::Gradient\-Recursive\-Gaussian\-Image\-Filter!header} // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet #include "itkGradientRecursiveGaussianImageFilter.h" // Software Guide : EndCodeSnippet int main(int argc, char ** argv) { // Verify the number of parameters in the command line if (argc < 3) { std::cerr << "Usage: " << std::endl; std::cerr << argv[0] << " inputImageFile outputVectorImageFile " << std::endl; return EXIT_FAILURE; } // Software Guide : BeginLatex // // We read an image of \code{signed short} pixels and compute the // gradient to produce an image of CovariantVectors where each // component is of type \code{float}. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet using InputPixelType = signed short; using ComponentType = float; constexpr unsigned int Dimension = 2; using OutputPixelType = itk::CovariantVector; using InputImageType = itk::Image; using OutputImageType = itk::Image; // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // The \doxygen{ImageFileReader} and \doxygen{ImageFileWriter} are // instantiated using the image types. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet using ReaderType = itk::ImageFileReader; using WriterType = itk::ImageFileWriter; // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // The GradientRecursiveGaussianImageFilter class is instantiated // using the input and output image types. A filter object is created with // the \code{New()} method and assigned to a \doxygen{SmartPointer}. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet using FilterType = itk::GradientRecursiveGaussianImageFilter; FilterType::Pointer filter = FilterType::New(); // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // We select a value for the $\sigma$ parameter of the // GradientRecursiveGaussianImageFilter. Note that $\sigma$ // for this filter is specified in millimeters. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet filter->SetSigma(1.5); // Sigma in millimeters // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // Below, we create the reader and writer using the \code{New()} method and // assign the result to a \doxygen{SmartPointer}. // // \index{itk::ImageFileReader!New()} // \index{itk::ImageFileWriter!New()} // \index{itk::ImageFileReader!SmartPointer} // \index{itk::ImageFileWriter!SmartPointer} // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet ReaderType::Pointer reader = ReaderType::New(); WriterType::Pointer writer = WriterType::New(); // Software Guide : EndCodeSnippet // // Here we recover the file names from the command line arguments // const char * inputFilename = argv[1]; const char * outputFilename = argv[2]; // Software Guide : BeginLatex // // The name of the file to be read or written is passed to the // \code{SetFileName()} method. // // \index{itk::ImageFileReader!SetFileName()} // \index{itk::ImageFileWriter!SetFileName()} // \index{SetFileName()!itk::ImageFileReader} // \index{SetFileName()!itk::ImageFileWriter} // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet reader->SetFileName(inputFilename); writer->SetFileName(outputFilename); // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // Below we connect the reader, filter and writer to form the data // processing pipeline. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet filter->SetInput(reader->GetOutput()); writer->SetInput(filter->GetOutput()); // Software Guide : EndCodeSnippet // Software Guide : BeginLatex // // Finally we execute the pipeline by invoking \code{Update()} on the // writer. The call is placed in a \code{try/catch} block in case // exceptions are thrown. // // Software Guide : EndLatex // Software Guide : BeginCodeSnippet try { writer->Update(); } catch (const itk::ExceptionObject & err) { std::cerr << "ExceptionObject caught !" << std::endl; std::cerr << err << std::endl; return EXIT_FAILURE; } // Software Guide : EndCodeSnippet return EXIT_SUCCESS; }