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# Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import mmengine
from mmengine.dataset import BaseDataset
from mmengine.fileio import list_dir_or_file
from mmengine.utils import check_file_exist
from mmpretrain.registry import DATASETS
@DATASETS.register_module()
class IconQA(BaseDataset):
"""IconQA: A benchmark for abstract diagram understanding
and visual language reasoning.
Args:
data_root (str): The root directory for ``data_prefix``, ``ann_file``
and ``question_file``.
data_prefix (str): The directory of the specific task and split.
eg. ``iconqa/val/choose_text/``.
**kwargs: Other keyword arguments in :class:`BaseDataset`.
"""
def __init__(self, data_root: str, data_prefix: str, **kwarg):
super().__init__(
data_root=data_root,
data_prefix=dict(img_path=data_prefix),
**kwarg,
)
def load_data_list(self) -> List[dict]:
"""Load data list."""
sample_list = list(
list_dir_or_file(self.data_prefix['img_path'], list_file=False))
data_list = list()
for sample_id in sample_list:
# data json
# {
# "question": "How likely is it that you will pick a black one?",
# "choices": [
# "certain",
# "unlikely",
# "impossible",
# "probable"
# ],
# "answer": 2,
# "ques_type": "choose_txt",
# "grade": "grade1",
# "label": "S2"
# }
data_info = mmengine.load(
mmengine.join_path(self.data_prefix['img_path'], sample_id,
'data.json'))
data_info['gt_answer'] = data_info['choices'][int(
data_info['answer'])]
data_info['img_path'] = mmengine.join_path(
self.data_prefix['img_path'], sample_id, 'image.png')
check_file_exist(data_info['img_path'])
data_list.append(data_info)
return data_list
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