/*=========================================================================
 *
 *  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 "itkNeighborhoodAlgorithm.h"
#include <cmath>

// Software Guide : BeginLatex
//
// This example uses \doxygen{ShapedNeighborhoodIterator} to implement a
// binary erosion algorithm.  If we think of an image $I$ as a set of pixel
// indices, then erosion of $I$ by a smaller set $E$, called the
// \emph{structuring element}, is the set of all indices at locations $x$ in
// $I$ such that when $E$ is positioned at $x$, every element in $E$ is also
// contained in $I$.
//
// This type of algorithm is easy to implement with shaped neighborhood
// iterators because we can use the iterator itself as the structuring element
// $E$ and move it sequentially through all positions $x$.  The result at $x$
// is obtained by checking values in a simple iteration loop through the
// neighborhood stencil.
//
// We need two iterators, a shaped iterator for the input image and a regular
// image iterator for writing results to the output image.
//
// Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
#include "itkConstShapedNeighborhoodIterator.h"
#include "itkImageRegionIterator.h"
// Software Guide : EndCodeSnippet

int
main(int argc, char ** argv)
{
  if (argc < 4)
  {
    std::cerr << "Missing parameters. " << std::endl;
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << " inputImageFile outputImageFile element_radius"
              << std::endl;
    return EXIT_FAILURE;
  }

  // Software Guide : BeginLatex
  //
  // Since we are working with binary images in this example, an
  // \code{unsigned char} pixel type will do.  The image and iterator types
  // are defined using the pixel type.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  using PixelType = unsigned char;
  using ImageType = itk::Image<PixelType, 2>;

  using ShapedNeighborhoodIteratorType =
    itk::ConstShapedNeighborhoodIterator<ImageType>;

  using IteratorType = itk::ImageRegionIterator<ImageType>;
  // Software Guide : EndCodeSnippet

  using ReaderType = itk::ImageFileReader<ImageType>;
  auto reader = ReaderType::New();
  reader->SetFileName(argv[1]);

  try
  {
    reader->Update();
  }
  catch (const itk::ExceptionObject & err)
  {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
  }

  auto output = ImageType::New();
  output->SetRegions(reader->GetOutput()->GetRequestedRegion());
  output->Allocate();

  // Software Guide : BeginLatex
  //
  // Refer to the examples in Section~\ref{sec:itkNeighborhoodIterator} or the
  // source code of this example for a description of how to read the input
  // image and allocate a matching output image.
  //
  // The size of the structuring element is read from the command line and
  // used to define a radius for the shaped neighborhood iterator.  Using the
  // method developed in section~\ref{sec:itkNeighborhoodIterator} to minimize
  // bounds checking, the iterator itself is not initialized until entering
  // the main processing loop.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  unsigned int element_radius = std::stoi(argv[3]);
  ShapedNeighborhoodIteratorType::RadiusType radius;
  radius.Fill(element_radius);
  // Software Guide : EndCodeSnippet

  // Software Guide : BeginLatex
  //
  // The face calculator object introduced in
  // Section~\ref{sec:NeighborhoodExample3} is created and used as before.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  using FaceCalculatorType =
    itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<ImageType>;

  FaceCalculatorType                         faceCalculator;
  FaceCalculatorType::FaceListType           faceList;
  FaceCalculatorType::FaceListType::iterator fit;

  faceList =
    faceCalculator(reader->GetOutput(), output->GetRequestedRegion(), radius);
  // Software Guide : EndCodeSnippet

  // Software Guide : BeginLatex
  //
  // Now we initialize some variables and constants.
  //
  // Software Guide : EndLatex


  // Software Guide : BeginCodeSnippet
  IteratorType out;

  constexpr PixelType background_value = 0;
  constexpr PixelType foreground_value = 255;
  const auto          rad = static_cast<float>(element_radius);
  // Software Guide : EndCodeSnippet


  // Software Guide : BeginLatex
  //
  // The outer loop of the algorithm is structured as in previous neighborhood
  // iterator examples.  Each region in the face list is processed in turn. As
  // each new region is processed, the input and output iterators are
  // initialized on that region.
  //
  // The shaped iterator that ranges over the input is our structuring element
  // and its active stencil must be created accordingly.  For this example,
  // the structuring element is shaped like a circle of radius
  // \code{element\_radius}.  Each of the appropriate neighborhood offsets is
  // activated in the double \code{for} loop.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  for (fit = faceList.begin(); fit != faceList.end(); ++fit)
  {
    ShapedNeighborhoodIteratorType it(radius, reader->GetOutput(), *fit);
    out = IteratorType(output, *fit);

    // Creates a circular structuring element by activating all the pixels
    // less than radius distance from the center of the neighborhood.

    for (float y = -rad; y <= rad; ++y)
    {
      for (float x = -rad; x <= rad; ++x)
      {
        ShapedNeighborhoodIteratorType::OffsetType off;

        float dis = std::sqrt(x * x + y * y);
        if (dis <= rad)
        {
          off[0] = static_cast<int>(x);
          off[1] = static_cast<int>(y);
          it.ActivateOffset(off);
        }
      }
    }
    // Software Guide : EndCodeSnippet

    // Software Guide : BeginLatex
    //
    // The inner loop, which implements the erosion algorithm, is fairly
    // simple. The \code{for} loop steps the input and output iterators
    // through their respective images.  At each step, the active stencil of
    // the shaped iterator is traversed to determine whether all pixels
    // underneath the stencil contain the foreground value, i.e. are contained
    // within the set $I$.  Note the use of the stencil iterator, \code{ci},
    // in performing this check.
    //
    // Software Guide : EndLatex

    // Software Guide : BeginCodeSnippet

    // Implements erosion
    for (it.GoToBegin(), out.GoToBegin(); !it.IsAtEnd(); ++it, ++out)
    {
      ShapedNeighborhoodIteratorType::ConstIterator ci;

      bool flag = true;
      for (ci = it.Begin(); ci != it.End(); ++ci)
      {
        if (ci.Get() == background_value)
        {
          flag = false;
          break;
        }
      }
      if (flag == true)
      {
        out.Set(foreground_value);
      }
      else
      {
        out.Set(background_value);
      }
    }
  }
  // Software Guide : EndCodeSnippet

  using WriterType = itk::ImageFileWriter<ImageType>;

  auto writer = WriterType::New();
  writer->SetFileName(argv[2]);
  writer->SetInput(output);
  try
  {
    writer->Update();
  }
  catch (const itk::ExceptionObject & err)
  {
    std::cerr << "ExceptionObject caught !" << std::endl;
    std::cerr << err << std::endl;
    return EXIT_FAILURE;
  }

  return EXIT_SUCCESS;
}
