Spaces:
Runtime error
Runtime error
File size: 3,002 Bytes
3b96cb1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
# Copyright (c) OpenMMLab. All rights reserved.
from typing import List
from mmengine.fileio import load
from mmpretrain.registry import DATASETS
from .base_dataset import BaseDataset
@DATASETS.register_module()
class VGVQA(BaseDataset):
"""Visual Genome VQA dataset."""
def load_data_list(self) -> List[dict]:
"""Load data list.
Compare to BaseDataset, the only difference is that coco_vqa annotation
file is already a list of data. There is no 'metainfo'.
"""
raw_data_list = load(self.ann_file)
if not isinstance(raw_data_list, list):
raise TypeError(
f'The VQA annotations loaded from annotation file '
f'should be a dict, but got {type(raw_data_list)}!')
# load and parse data_infos.
data_list = []
for raw_data_info in raw_data_list:
# parse raw data information to target format
data_info = self.parse_data_info(raw_data_info)
if isinstance(data_info, dict):
# For VQA tasks, each `data_info` looks like:
# {
# "question_id": 986769,
# "question": "How many people are there?",
# "answer": "two",
# "image": "image/1.jpg",
# "dataset": "vg"
# }
# change 'image' key to 'img_path'
# TODO: This process will be removed, after the annotation file
# is preprocess.
data_info['img_path'] = data_info['image']
del data_info['image']
if 'answer' in data_info:
# add answer_weight & answer_count, delete duplicate answer
if data_info['dataset'] == 'vqa':
answer_weight = {}
for answer in data_info['answer']:
if answer in answer_weight.keys():
answer_weight[answer] += 1 / len(
data_info['answer'])
else:
answer_weight[answer] = 1 / len(
data_info['answer'])
data_info['answer'] = list(answer_weight.keys())
data_info['answer_weight'] = list(
answer_weight.values())
data_info['answer_count'] = len(answer_weight)
elif data_info['dataset'] == 'vg':
data_info['answers'] = [data_info['answer']]
data_info['answer_weight'] = [0.2]
data_info['answer_count'] = 1
data_list.append(data_info)
else:
raise TypeError(
f'Each VQA data element loaded from annotation file '
f'should be a dict, but got {type(data_info)}!')
return data_list
|