Function compute

tools/match_linemod_template.cpp:106–158

}

void
compute (const PointCloudXYZRGBA::ConstPtr & input, const char * templates_filename)
{
  pcl::LINEMOD linemod;

  // Load the templates from disk
  linemod.loadTemplates (templates_filename);

  // Match the templates to the provided image
  std::vector<pcl::LINEMODDetection> detections = matchTemplates (input, linemod);

  // Output the position and score of the best match for each template
  for (std::size_t i = 0; i < detections.size (); ++i)
  {
    const LINEMODDetection & d = detections[i];
    printf ("%lu: %d %d %d %f\n", i, d.x, d.y, d.template_id, d.score);
  }

  /*// Visualization code for testing purposes (requires libpng++)
  int i = 0;
  png::image<png::rgb_pixel> image (640, 480);
  for (std::size_t y = 0; y < image.get_height (); ++y)
  {
    for (std::size_t x = 0; x < image.get_width (); ++x)
    {
      const pcl::PointXYZRGBA & p = (*input)[i++];
      image[y][x] = png::rgb_pixel(p.r, p.g, p.b);
    }
  }
  // Draw a green box around the object
  for (std::size_t i = 0; i < detections.size (); ++i)
  {
    const LINEMODDetection & d = detections[i];
    if (d.score < 0.6)
      continue;

    const pcl::SparseQuantizedMultiModTemplate & tmplt = linemod.getTemplate (d.template_id);
    int w = tmplt.region.width;
    int h = tmplt.region.height;
    for (int x = d.x; x < d.x+w; ++x)
    {
      image[d.y][x] = png::rgb_pixel(0, 255, 0);
      image[d.y+h-1][x] = png::rgb_pixel(0, 255, 0);
    }
    for (int y = d.y; y < d.y+h; ++y)
    {
      image[y][d.x] = png::rgb_pixel(0, 255, 0);
      image[y][d.x+w-1] = png::rgb_pixel(0, 255, 0);
    }
  }
  image.write("output.png");
  */
}

/* ---[ */
int