def load_ade20k_panoptic_json(json_file, image_dir, gt_dir, semseg_dir, meta):
    """
    Args:
        image_dir (str): path to the raw dataset. e.g., "~/coco/train2017".
        gt_dir (str): path to the raw annotations. e.g., "~/coco/panoptic_train2017".
        json_file (str): path to the json file. e.g., "~/coco/annotations/panoptic_train2017.json".
    Returns:
        list[dict]: a list of dicts in Detectron2 standard format. (See
        `Using Custom Datasets </tutorials/datasets.html>`_ )
    """

    def _convert_category_id(segment_info, meta):
        if segment_info["category_id"] in meta["thing_dataset_id_to_contiguous_id"]:
            segment_info["category_id"] = meta["thing_dataset_id_to_contiguous_id"][
                segment_info["category_id"]
            ]
            segment_info["isthing"] = True
        else:
            segment_info["category_id"] = meta["stuff_dataset_id_to_contiguous_id"][
                segment_info["category_id"]
            ]
            segment_info["isthing"] = False
        return segment_info

    with PathManager.open(json_file) as f:
        json_info = json.load(f)

    ret = []
    for ann in json_info["annotations"]:
        image_id = ann["image_id"]
        # TODO: currently we assume image and label has the same filename but
        # different extension, and images have extension ".jpg" for COCO. Need
        # to make image extension a user-provided argument if we extend this
        # function to support other COCO-like datasets.
        image_file = os.path.join(image_dir, os.path.splitext(ann["file_name"])[0] + ".jpg")
        label_file = os.path.join(gt_dir, ann["file_name"])
        sem_label_file = os.path.join(semseg_dir, ann["file_name"])
        segments_info = [_convert_category_id(x, meta) for x in ann["segments_info"]]
        ret.append(
            {
                "file_name": image_file,
                "image_id": image_id,
                "pan_seg_file_name": label_file,
                "sem_seg_file_name": sem_label_file,
                "segments_info": segments_info,
            }
        )
    assert len(ret), f"No images found in {image_dir}!"
    assert PathManager.isfile(ret[0]["file_name"]), ret[0]["file_name"]
    assert PathManager.isfile(ret[0]["pan_seg_file_name"]), ret[0]["pan_seg_file_name"]
    assert PathManager.isfile(ret[0]["sem_seg_file_name"]), ret[0]["sem_seg_file_name"]
    return ret

    Args:
        image_dir (str): path to the raw dataset. e.g., "~/coco/train2017".
        gt_dir (str): path to the raw annotations. e.g., "~/coco/panoptic_train2017".
        json_file (str): path to the json file. e.g., "~/coco/annotations/panoptic_train2017.json".
    Returns:
        list[dict]: a list of dicts in Detectron2 standard format. (See
        `Using Custom Datasets </tutorials/datasets.html>`_ )
    
ControlNet-v1-1-nightly/annotator/oneformer/oneformer/data/datasets/register_ade20k_panoptic.py