def _postprocess_tracks()

in siammot/engine/inferencer.py [0:0]

• 14 lines of code
• 9 McCabe index (conditional complexity)

    def _postprocess_tracks(self, tracks: DataSample):
        """
        post_process the tracks to filter out short and non-confident tracks
        :param tracks: un-filtered tracks
        :return: filtered tracks that would be used for evaluation
        """
        track_ids = set()
        for _entity in tracks.entities:
            if _entity.id not in track_ids and _entity.id >= 0:
                track_ids.add(_entity.id)

        filter_tracks = tracks.get_copy_without_entities()
        for _id in track_ids:
            _id_entities = tracks.get_entities_with_id(_id)
            _track_conf = np.mean([_e.confidence for _e in _id_entities])
            if len(_id_entities) >= self._track_len \
                    and _track_conf >= self._track_conf:
                for _entity in _id_entities:
                    filter_tracks.add_entity(_entity)
        return filter_tracks