parameters: (
      track_dict: Dict[Tuple[str, str], tracking.TPairTracks], data: DataSetBase
  )
return_statement: return [pairs[o] for o in order]
docstring: All matched image pairs sorted by reconstructability.
docstring_summary: All matched image pairs sorted by reconstructability.
docstring_tokens: All matched image pairs sorted by reconstructability .
function: def compute_image_pairs(
      track_dict: Dict[Tuple[str, str], tracking.TPairTracks], data: DataSetBase
  ) -> List[Tuple[str, str]]:
      """All matched image pairs sorted by reconstructability."""
      cameras = data.load_camera_models()
      args = _pair_reconstructability_arguments(track_dict, cameras, data)
      processes = data.config["processes"]
      result = parallel_map(_compute_pair_reconstructability, args, processes)
      result = list(result)
      pairs = [(im1, im2) for im1, im2, r in result if r > 0]
      score = [r for im1, im2, r in result if r > 0]
      order = np.argsort(-np.array(score))
      return [pairs[o] for o in order]
function_tokens: def compute_image_pairs ( track_dict : Dict [ Tuple [ str , str ] , tracking . TPairTracks ] , data : DataSetBase ) -> List [ Tuple [ str , str ] ] : cameras = data . load_camera_models ( ) args = _pair_reconstructability_arguments ( track_dict , cameras , data ) processes = data . config [ "processes" ] result = parallel_map ( _compute_pair_reconstructability , args , processes ) result = list ( result ) pairs = [ ( im1 , im2 ) for im1 , im2 , r in result if r > 0 ] score = [ r for im1 , im2 , r in result if r > 0 ] order = np . argsort ( - np . array ( score ) ) return [ pairs [ o ] for o in order ]