113 lines
3.8 KiB
Python
113 lines
3.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
from collections import Counter
|
|
from typing import List
|
|
|
|
import mmengine
|
|
from mmengine.dataset import BaseDataset
|
|
|
|
from mmpretrain.registry import DATASETS
|
|
|
|
|
|
@DATASETS.register_module()
|
|
class VizWiz(BaseDataset):
|
|
"""VizWiz dataset.
|
|
|
|
Args:
|
|
data_root (str): The root directory for ``data_prefix``, ``ann_file``
|
|
and ``question_file``.
|
|
data_prefix (str): The directory of images.
|
|
ann_file (str, optional): Annotation file path for training and
|
|
validation. Defaults to an empty string.
|
|
**kwargs: Other keyword arguments in :class:`BaseDataset`.
|
|
"""
|
|
|
|
def __init__(self,
|
|
data_root: str,
|
|
data_prefix: str,
|
|
ann_file: str = '',
|
|
**kwarg):
|
|
super().__init__(
|
|
data_root=data_root,
|
|
data_prefix=dict(img_path=data_prefix),
|
|
ann_file=ann_file,
|
|
**kwarg,
|
|
)
|
|
|
|
def load_data_list(self) -> List[dict]:
|
|
"""Load data list."""
|
|
annotations = mmengine.load(self.ann_file)
|
|
|
|
data_list = []
|
|
for ann in annotations:
|
|
# {
|
|
# "image": "VizWiz_val_00000001.jpg",
|
|
# "question": "Can you tell me what this medicine is please?",
|
|
# "answers": [
|
|
# {
|
|
# "answer": "no",
|
|
# "answer_confidence": "yes"
|
|
# },
|
|
# {
|
|
# "answer": "unanswerable",
|
|
# "answer_confidence": "yes"
|
|
# },
|
|
# {
|
|
# "answer": "night time",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "unanswerable",
|
|
# "answer_confidence": "yes"
|
|
# },
|
|
# {
|
|
# "answer": "night time",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "night time cold medicine",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "night time",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "night time",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "night time",
|
|
# "answer_confidence": "maybe"
|
|
# },
|
|
# {
|
|
# "answer": "night time medicine",
|
|
# "answer_confidence": "yes"
|
|
# }
|
|
# ],
|
|
# "answer_type": "other",
|
|
# "answerable": 1
|
|
# },
|
|
data_info = dict()
|
|
data_info['question'] = ann['question']
|
|
data_info['img_path'] = mmengine.join_path(
|
|
self.data_prefix['img_path'], ann['image'])
|
|
|
|
if 'answerable' not in ann:
|
|
data_list.append(data_info)
|
|
else:
|
|
if ann['answerable'] == 1:
|
|
# add answer_weight & answer_count, delete duplicate answer
|
|
answers = []
|
|
for item in ann.pop('answers'):
|
|
if item['answer_confidence'] == 'yes' and item[
|
|
'answer'] != 'unanswerable':
|
|
answers.append(item['answer'])
|
|
count = Counter(answers)
|
|
answer_weight = [i / len(answers) for i in count.values()]
|
|
data_info['gt_answer'] = list(count.keys())
|
|
data_info['gt_answer_weight'] = answer_weight
|
|
# data_info.update(ann)
|
|
data_list.append(data_info)
|
|
|
|
return data_list
|