/*=========================================================================
 *
 *  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.
 *
 *=========================================================================*/
#ifndef itkGrayscaleConnectedClosingImageFilter_hxx
#define itkGrayscaleConnectedClosingImageFilter_hxx

#include "itkImageRegionIterator.h"
#include "itkReconstructionByErosionImageFilter.h"
#include "itkMinimumMaximumImageCalculator.h"
#include "itkProgressAccumulator.h"

namespace itk
{
template <typename TInputImage, typename TOutputImage>
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>::GrayscaleConnectedClosingImageFilter()

{
  m_Seed.Fill(typename InputImageIndexType::OffsetValueType{});
  m_FullyConnected = false;
}

template <typename TInputImage, typename TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
  // call the superclass' implementation of this method
  Superclass::GenerateInputRequestedRegion();

  // We need all the input.
  InputImagePointer input = const_cast<InputImageType *>(this->GetInput());
  if (input)
  {
    input->SetRequestedRegion(input->GetLargestPossibleRegion());
  }
}

template <typename TInputImage, typename TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>::EnlargeOutputRequestedRegion(DataObject *)
{
  this->GetOutput()->SetRequestedRegion(this->GetOutput()->GetLargestPossibleRegion());
}

template <typename TInputImage, typename TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>::GenerateData()
{
  // Allocate the output
  this->AllocateOutputs();


  OutputImageType *      outputImage = this->GetOutput();
  const InputImageType * inputImage = this->GetInput();

  // construct a marker image to manipulate using reconstruction by
  // dilation. the marker image will have the same pixel values as the
  // input image at the seed pixel and will have a minimum everywhere
  // else.
  //

  // compute the minimum pixel value in the input
  typename MinimumMaximumImageCalculator<TInputImage>::Pointer calculator =
    MinimumMaximumImageCalculator<TInputImage>::New();
  calculator->SetImage(inputImage);
  calculator->ComputeMaximum();

  InputImagePixelType maxValue;
  maxValue = calculator->GetMaximum();

  // compare this maximum value to the value at the seed pixel.
  InputImagePixelType seedValue;
  seedValue = inputImage->GetPixel(m_Seed);

  if (maxValue == seedValue)
  {
    itkWarningMacro("GrayscaleConnectedClosingImageFilter: pixel value at seed point matches maximum value in "
                    "image.  Resulting image will have a constant value.");
    outputImage->FillBuffer(maxValue);
    this->UpdateProgress(1.0);
    return;
  }

  // allocate a marker image
  InputImagePointer markerPtr = InputImageType::New();
  markerPtr->SetRegions(inputImage->GetRequestedRegion());
  markerPtr->CopyInformation(inputImage);
  markerPtr->Allocate();

  // fill the marker image with the maximum value from the input
  markerPtr->FillBuffer(maxValue);

  // mark the seed point
  markerPtr->SetPixel(m_Seed, seedValue);

  // Delegate to a geodesic dilation filter.
  //
  //
  typename ReconstructionByErosionImageFilter<TInputImage, TInputImage>::Pointer erode =
    ReconstructionByErosionImageFilter<TInputImage, TInputImage>::New();

  // Create a process accumulator for tracking the progress of this minipipeline
  auto progress = ProgressAccumulator::New();
  progress->SetMiniPipelineFilter(this);
  progress->RegisterInternalFilter(erode, 1.0f);

  // set up the erode filter
  // erode->RunOneIterationOff();             // run to convergence
  erode->SetMarkerImage(markerPtr);
  erode->SetMaskImage(inputImage);
  erode->SetFullyConnected(m_FullyConnected);

  // graft our output to the erode filter to force the proper regions
  // to be generated
  erode->GraftOutput(outputImage);

  // reconstruction by dilation
  erode->Update();

  // graft the output of the erode filter back onto this filter's
  // output. this is needed to get the appropriate regions passed
  // back.
  this->GraftOutput(erode->GetOutput());
}

template <typename TInputImage, typename TOutputImage>
void
GrayscaleConnectedClosingImageFilter<TInputImage, TOutputImage>::PrintSelf(std::ostream & os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);

  os << indent << "Seed point: " << m_Seed << std::endl;
  os << indent << "Number of iterations used to produce current output: " << m_NumberOfIterationsUsed << std::endl;
  os << indent << "FullyConnected: " << (m_FullyConnected ? "On" : "Off") << std::endl;
}
} // end namespace itk
#endif
