/* perform segmentation using the confidence connected image filter */

#include "vvITKFilterModuleDoubleOutput.h"

#include "itkConfidenceConnectedImageFilter.h"



template <class InputPixelType>
class ConfidenceConnectedRunner
  {
  public:
    itkStaticConstMacro( Dimension, unsigned int, 3);
    typedef  itk::Image< InputPixelType, Dimension >  InputImageType; 
    typedef  unsigned char                            OutputPixelType;
    typedef  itk::Image< OutputPixelType, Dimension > OutputImageType; 
    typedef  typename InputImageType::IndexType       IndexType;
    typedef  itk::ConfidenceConnectedImageFilter< InputImageType,  
                                                OutputImageType >   FilterType;
  public:
    ConfidenceConnectedRunner() {}
    void Execute( vtkVVPluginInfo *info, vtkVVProcessDataStruct *pds )
    {
      const unsigned int numberOfIterations = atoi( info->GetGUIProperty(info, 0, VVP_GUI_VALUE ) );
      const float        multiplier         = atof( info->GetGUIProperty(info, 1, VVP_GUI_VALUE ) );
      const int          replaceValue       = atoi( info->GetGUIProperty(info, 2, VVP_GUI_VALUE ) );
      const unsigned int initialRadius      = atoi( info->GetGUIProperty(info, 3, VVP_GUI_VALUE ) );
      const bool         compositeOutput    = atoi( info->GetGUIProperty(info, 4, VVP_GUI_VALUE ) );

      VolView::PlugIn::FilterModuleDoubleOutput< FilterType > module;
      module.SetPluginInfo( info );
      module.SetUpdateMessage("Confidence Connected Region Growing...");
      // Set the parameters on it
      module.GetFilter()->SetNumberOfIterations(        numberOfIterations );
      module.GetFilter()->SetMultiplier(                multiplier         );
      module.GetFilter()->SetReplaceValue(              replaceValue       );
      module.GetFilter()->SetInitialNeighborhoodRadius( initialRadius      );

      itk::Index<Dimension> seed;
      const unsigned int numberOfSeeds = info->NumberOfMarkers;
      for( unsigned int i=0; i<numberOfSeeds; i++)
        {
        VolView::PlugIn::FilterModuleBase::Convert3DMarkerToIndex( info, i, seed );
        module.GetFilter()->AddSeed( seed );
        }

      module.SetProduceDoubleOutput( compositeOutput          );
      // Execute the filter
      module.ProcessData( pds  );
    }
  };



static int ProcessData(void *inf, vtkVVProcessDataStruct *pds)
{

  vtkVVPluginInfo *info = (vtkVVPluginInfo *)inf;

  if( info->InputVolumeNumberOfComponents != 1 )
    {
    info->SetProperty( info, VVP_ERROR, "This filter requires a single-component data set as input" ); 
    return -1;
    }

  if( info->NumberOfMarkers < 1 )
    {
    info->SetProperty( info, VVP_ERROR, "Please select seed points using the 3D Markers in the Annotation menu" ); 
    return -1;
    }

  try 
  {
  switch( info->InputVolumeScalarType )
    {
    case VTK_CHAR:
      {
      ConfidenceConnectedRunner<signed char> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_UNSIGNED_CHAR:
      {
      ConfidenceConnectedRunner<unsigned char> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_SHORT:
      {
      ConfidenceConnectedRunner<signed short> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_UNSIGNED_SHORT:
      {
      ConfidenceConnectedRunner<unsigned short> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_INT:
      {
      ConfidenceConnectedRunner<signed int> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_UNSIGNED_INT:
      {
      ConfidenceConnectedRunner<unsigned int> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_LONG:
      {
      ConfidenceConnectedRunner<signed long> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_UNSIGNED_LONG:
      {
      ConfidenceConnectedRunner<unsigned long> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_FLOAT:
      {
      ConfidenceConnectedRunner<float> runner;
      runner.Execute( info, pds );
      break; 
      }
    case VTK_DOUBLE:
      {
      ConfidenceConnectedRunner<double> runner;
      runner.Execute( info, pds );
      break; 
      }
    }
  }
  catch( itk::ExceptionObject & except )
  {
    info->SetProperty( info, VVP_ERROR, except.what() ); 
    return -1;
  }
  return 0;
}


static int UpdateGUI(void *inf)
{
  vtkVVPluginInfo *info = (vtkVVPluginInfo *)inf;

  info->SetGUIProperty(info, 0, VVP_GUI_LABEL, "Number of Iterations");
  info->SetGUIProperty(info, 0, VVP_GUI_TYPE, VVP_GUI_SCALE);
  info->SetGUIProperty(info, 0, VVP_GUI_DEFAULT, "5");
  info->SetGUIProperty(info, 0, VVP_GUI_HELP, "Number of times that region growing process should be repeated. If initial statistical estimations are good, further iterations may improve the segmentation. After a certain number of iterations the result will not change. ");
  info->SetGUIProperty(info, 0, VVP_GUI_HINTS , "1 20 1");

  info->SetGUIProperty(info, 1, VVP_GUI_LABEL, "Variance Multiplier");
  info->SetGUIProperty(info, 1, VVP_GUI_TYPE, VVP_GUI_SCALE);
  info->SetGUIProperty(info, 1, VVP_GUI_DEFAULT, "2.5");
  info->SetGUIProperty(info, 1, VVP_GUI_HELP, "Factor that will multiplies the variance of the pixels region in order to define the intensity range for which new pixels will be accepted in the region.");
  info->SetGUIProperty(info, 1, VVP_GUI_HINTS , "0.1 10.0 0.1");

  info->SetGUIProperty(info, 2, VVP_GUI_LABEL, "Replace Value");
  info->SetGUIProperty(info, 2, VVP_GUI_TYPE, VVP_GUI_SCALE);
  info->SetGUIProperty(info, 2, VVP_GUI_DEFAULT, "255");
  info->SetGUIProperty(info, 2, VVP_GUI_HELP, "Value to assign to the binary mask of the segmented region. The rest of the image will be set to zero.");
  info->SetGUIProperty(info, 2, VVP_GUI_HINTS , "1 255.0 1.0");

  info->SetGUIProperty(info, 3, VVP_GUI_LABEL, "Initial Neighborhood Radius");
  info->SetGUIProperty(info, 3, VVP_GUI_TYPE, VVP_GUI_SCALE);
  info->SetGUIProperty(info, 3, VVP_GUI_DEFAULT, "2");
  info->SetGUIProperty(info, 3, VVP_GUI_HELP, "Size of the initial neighborhood used to compute the statistics of the region. If the region in which the seed points are placed happens to be a homogeneous intensity distribution, increasing this radius will safely improve the statistical estimation of mean and variance. Make sure that the radius is not large enough to make contours participate in the computation of the estimation. That is, from any seed point to the nearest important edge, there should be a distance larger than this radius.");
  info->SetGUIProperty(info, 3, VVP_GUI_HINTS , "1 20.0 1.0");

  info->SetGUIProperty(info, 4, VVP_GUI_LABEL, "Produce composite output");
  info->SetGUIProperty(info, 4, VVP_GUI_TYPE, VVP_GUI_CHECKBOX);
  info->SetGUIProperty(info, 4, VVP_GUI_DEFAULT, "0");
  info->SetGUIProperty(info, 4, VVP_GUI_HELP, "This filter produce by default a binary image as output. Enabling this option will instead generate a composite output combining the input image and the binary mask as an image of two components. This is convenient for evaluating the quality of a segmentation.");


  info->SetProperty(info, VVP_REQUIRED_Z_OVERLAP, "0");
  

  // Depending on this option, the filter will produce a 
  // single component or a double component output.
  // When single component is used, the output type is 'unsigned char'

  info->OutputVolumeScalarType = VTK_UNSIGNED_CHAR;
  info->OutputVolumeNumberOfComponents = 1;
  info->SetProperty(info, VVP_PER_VOXEL_MEMORY_REQUIRED,    "1");

  const char * compositeOutputProperty = info->GetGUIProperty(info, 4, VVP_GUI_VALUE ); 

  // During the startup of the application this string is not yet defined.
  // We should then check for it before trying to use it.
  if( compositeOutputProperty )
    {
    const bool compositeOutput  = atoi( compositeOutputProperty );
    if( compositeOutput )
      {
      info->OutputVolumeScalarType = info->InputVolumeScalarType;
      info->OutputVolumeNumberOfComponents = 2;
      info->SetProperty(info, VVP_PER_VOXEL_MEMORY_REQUIRED,    "2");
      }
    }


  memcpy(info->OutputVolumeDimensions,info->InputVolumeDimensions,
         3*sizeof(int));
  memcpy(info->OutputVolumeSpacing,info->InputVolumeSpacing,
         3*sizeof(float));
  memcpy(info->OutputVolumeOrigin,info->InputVolumeOrigin,
         3*sizeof(float));

  return 1;
}

extern "C" {
  
void VV_PLUGIN_EXPORT vvITKConfidenceConnectedInit(vtkVVPluginInfo *info)
{
  vvPluginVersionCheck();

  // setup information that never changes
  info->ProcessData = ProcessData;
  info->UpdateGUI = UpdateGUI;
  info->SetProperty(info, VVP_NAME, "Confidence Connected (ITK) ");
  info->SetProperty(info, VVP_GROUP, "Segmentation - Region Growing");
  info->SetProperty(info, VVP_TERSE_DOCUMENTATION,
                                "Confidence Connected Segmentation");
  info->SetProperty(info, VVP_FULL_DOCUMENTATION,
    "This filter applies an region growing algorithm for segmentation. The criterion for including new pixels in the region is defined by an intensity range around the mean value of the pixels existing in the region. The extent of the intensity interval is computed as the product of the variance and a multiplier provided by the user. The coordinates of the seed points are used as the initial position for start growing the region.");
  info->SetProperty(info, VVP_SUPPORTS_IN_PLACE_PROCESSING, "0");
  info->SetProperty(info, VVP_SUPPORTS_PROCESSING_PIECES,   "0");
  info->SetProperty(info, VVP_NUMBER_OF_GUI_ITEMS,          "5");
  info->SetProperty(info, VVP_REQUIRED_Z_OVERLAP,           "0");

  info->OutputVolumeScalarType = VTK_UNSIGNED_CHAR;
  info->OutputVolumeNumberOfComponents = 1;
  info->SetProperty(info, VVP_PER_VOXEL_MEMORY_REQUIRED,    "1");


}

}

