def merge_to_panoptic(detection_dicts, sem_seg_dicts):
    """
    Create dataset dicts for panoptic segmentation, by
    merging two dicts using "file_name" field to match their entries.

    Args:
        detection_dicts (list[dict]): lists of dicts for object detection or instance segmentation.
        sem_seg_dicts (list[dict]): lists of dicts for semantic segmentation.

    Returns:
        list[dict] (one per input image): Each dict contains all (key, value) pairs from dicts in
            both detection_dicts and sem_seg_dicts that correspond to the same image.
            The function assumes that the same key in different dicts has the same value.
    """
    results = []
    sem_seg_file_to_entry = {x["file_name"]: x for x in sem_seg_dicts}
    assert len(sem_seg_file_to_entry) > 0

    for det_dict in detection_dicts:
        dic = copy.copy(det_dict)
        dic.update(sem_seg_file_to_entry[dic["file_name"]])
        results.append(dic)
    return results

    Create dataset dicts for panoptic segmentation, by
    merging two dicts using "file_name" field to match their entries.

    Args:
        detection_dicts (list[dict]): lists of dicts for object detection or instance segmentation.
        sem_seg_dicts (list[dict]): lists of dicts for semantic segmentation.

    Returns:
        list[dict] (one per input image): Each dict contains all (key, value) pairs from dicts in
            both detection_dicts and sem_seg_dicts that correspond to the same image.
            The function assumes that the same key in different dicts has the same value.
    
video_chat_with_MOSS/models/grit_src/third_party/CenterNet2/detectron2/data/datasets/coco_panoptic.py