47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from typing import List
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import mmengine
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from mmengine.dataset import BaseDataset
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from mmengine.fileio import get_file_backend
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from pycocotools.coco import COCO
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from mmpretrain.registry import DATASETS
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@DATASETS.register_module()
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class NoCaps(BaseDataset):
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"""NoCaps dataset.
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Args:
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data_root (str): The root directory for ``data_prefix`` and
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``ann_file``..
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ann_file (str): Annotation file path.
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data_prefix (dict): Prefix for data field. Defaults to
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``dict(img_path='')``.
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pipeline (Sequence): Processing pipeline. Defaults to an empty tuple.
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**kwargs: Other keyword arguments in :class:`BaseDataset`.
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"""
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def load_data_list(self) -> List[dict]:
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"""Load data list."""
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img_prefix = self.data_prefix['img_path']
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with mmengine.get_local_path(self.ann_file) as ann_file:
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coco = COCO(ann_file)
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file_backend = get_file_backend(img_prefix)
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data_list = []
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for ann in coco.anns.values():
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image_id = ann['image_id']
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image_path = file_backend.join_path(
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img_prefix, coco.imgs[image_id]['file_name'])
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data_info = {
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'image_id': image_id,
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'img_path': image_path,
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'gt_caption': None
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}
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data_list.append(data_info)
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return data_list
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