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#include <pcl/recognition/dotmod.h>

#include <fstream>


//////////////////////////////////////////////////////////////////////////////////////////////
pcl::DOTMOD::
DOTMOD(std::size_t template_width,
       std::size_t template_height) :
  template_width_ (template_width),
  template_height_ (template_height)
{
}

//////////////////////////////////////////////////////////////////////////////////////////////
pcl::DOTMOD::
~DOTMOD() = default;

//////////////////////////////////////////////////////////////////////////////////////////////
size_t 
pcl::DOTMOD::
createAndAddTemplate (const std::vector<pcl::DOTModality*> & modalities,
                      const std::vector<pcl::MaskMap*> & masks,
                      std::size_t template_anker_x,
                      std::size_t template_anker_y,
                      const pcl::RegionXY & region)
{
  DenseQuantizedMultiModTemplate dotmod_template;

  RegionXY actual_template_region;
  actual_template_region.x = static_cast<int> (template_anker_x);
  actual_template_region.y = static_cast<int> (template_anker_y);
  actual_template_region.width = static_cast<int> (template_width_);
  actual_template_region.height = static_cast<int> (template_height_);

  // get template data from available modalities
  const std::size_t nr_modalities = modalities.size();
  dotmod_template.modalities.resize (nr_modalities);
  for (std::size_t modality_index = 0; modality_index < nr_modalities; ++modality_index)
  {
    const MaskMap & mask = *(masks[modality_index]);
    const QuantizedMap & data = modalities[modality_index]->computeInvariantQuantizedMap (mask, actual_template_region);

    const std::size_t width = data.getWidth ();
    const std::size_t height = data.getHeight ();

    dotmod_template.modalities[modality_index].features.resize (width*height);

    for (std::size_t row_index = 0; row_index < height; ++row_index)
    {
      for (std::size_t col_index = 0; col_index < width; ++col_index)
      {
        dotmod_template.modalities[modality_index].features[row_index*width + col_index] = data (col_index, row_index);
      }
    }
  }

  // set region relative to the center
  dotmod_template.region.x = region.x - static_cast<int> (template_anker_x);
  dotmod_template.region.y = region.y - static_cast<int> (template_anker_y);
  dotmod_template.region.width = region.width;
  dotmod_template.region.height = region.height;

  // add template to template storage
  templates_.push_back(dotmod_template);

  return templates_.size () - 1;
}

//////////////////////////////////////////////////////////////////////////////////////////////
void
pcl::DOTMOD::
detectTemplates (const std::vector<DOTModality*> & modalities, 
                 const float template_response_threshold,
                 std::vector<DOTMODDetection> & detections,
                 const std::size_t bin_size ) const
{
  //std::cerr << ">> detectTemplates (...)" << std::endl;

  std::vector<QuantizedMap> maps;
  const std::size_t nr_modalities = modalities.size ();

  //std::cerr << "nr_modalities: " << nr_modalities << std::endl;

  for (std::size_t modality_index = 0; modality_index < nr_modalities; ++modality_index)
  {
    QuantizedMap &map = modalities[modality_index]->getDominantQuantizedMap ();
    maps.push_back(map);
  }

  //std::cerr << "1" << std::endl;
  
  
  const std::size_t width = maps[0].getWidth ();
  const std::size_t height = maps[0].getHeight ();
  const std::size_t nr_templates = templates_.size ();

  const std::size_t nr_template_horizontal_bins = template_width_ / bin_size;
  const std::size_t nr_template_vertical_bins = template_height_ / bin_size;

  //std::cerr << "---------------------------------------------------" << std::endl;
  //std::cerr << "width:                       " << width << std::endl;
  //std::cerr << "height:                      " << height << std::endl;
  //std::cerr << "nr_templates:                " << nr_templates << std::endl;
  //std::cerr << "nr_template_horizontal_bins: " << nr_template_horizontal_bins << std::endl;
  //std::cerr << "nr_template_vertical_bins:   " << nr_template_vertical_bins << std::endl;
  //std::cerr << "template_width_:             " << template_width_ << std::endl;
  //std::cerr << "template_height_:            " << template_height_ << std::endl;

  //std::cerr << "2" << std::endl;

  float best_response = 0.0f;
  for (std::size_t row_index = 0; row_index < (height - nr_template_vertical_bins); ++row_index)
  {
    for (std::size_t col_index = 0; col_index < (width - nr_template_horizontal_bins); ++col_index)
    {
      std::vector<float> responses (nr_templates, 0.0f);

      for (std::size_t modality_index = 0; modality_index < nr_modalities; ++modality_index)
      {
        const QuantizedMap map = maps[modality_index].getSubMap (col_index, row_index, nr_template_horizontal_bins, nr_template_vertical_bins);

        const unsigned char * image_data = map.getData ();
        for (std::size_t template_index = 0; template_index < nr_templates; ++template_index)
        {
          const unsigned char * template_data = templates_[template_index].modalities[modality_index].features.data();
          for (std::size_t data_index = 0; data_index < (nr_template_horizontal_bins*nr_template_vertical_bins); ++data_index)
          {
            if ((image_data[data_index] & template_data[data_index]) != 0)
              responses[template_index] += 1.0f;
          }
        }
      }

      // find templates with response over threshold
      const float scaling_factor = 1.0f / static_cast<float>(nr_template_horizontal_bins * nr_template_vertical_bins);
      for (std::size_t template_index = 0; template_index < nr_templates; ++template_index)
      {
        const float response = responses[template_index] * scaling_factor;

        if (response > template_response_threshold)
        {
          DOTMODDetection detection;
          detection.score = response;
          detection.template_id = template_index;
          detection.bin_x = col_index;
          detection.bin_y = row_index;

          detections.push_back (detection);
        }

        if (response > best_response)
          best_response = response;
      }
    }
  }

  //std::cerr << "best_response: " << best_response << std::endl;
  
  //std::cerr << "<< detectTemplates (...)" << std::endl;
}

//////////////////////////////////////////////////////////////////////////////////////////////
void
pcl::DOTMOD::
saveTemplates (const char * file_name) const
{
  std::ofstream file_stream;
  file_stream.open (file_name, std::ofstream::out | std::ofstream::binary);

  serialize (file_stream);

  file_stream.close ();
}

//////////////////////////////////////////////////////////////////////////////////////////////
void
pcl::DOTMOD::
loadTemplates (const char * file_name)
{
  std::ifstream file_stream;
  file_stream.open (file_name, std::ofstream::in | std::ofstream::binary);

  deserialize (file_stream);

  file_stream.close ();
}

//////////////////////////////////////////////////////////////////////////////////////////////
void
pcl::DOTMOD::
serialize (std::ostream & stream) const
{
  const int nr_templates = static_cast<int> (templates_.size ());
  write (stream, nr_templates);
  for (int template_index = 0; template_index < nr_templates; ++template_index)
    templates_[template_index].serialize (stream);
}

//////////////////////////////////////////////////////////////////////////////////////////////
void
pcl::DOTMOD::
deserialize (std::istream & stream)
{
  templates_.clear ();

  int nr_templates;
  read (stream, nr_templates);
  templates_.resize (nr_templates);
  for (int template_index = 0; template_index < nr_templates; ++template_index)
    templates_[template_index].deserialize (stream);
}
