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import base64
import io
import random
import os
# import pandas as pd
from PIL import Image
from tqdm import tqdm
import json
import string
import pdb
# Example:
# json_ann['questions'][0]
# {
# 'answer': 'A',
# 'choice_a': 'One',
# 'choice_b': 'Two',
# 'choice_c': 'Three',
# 'choice_d': 'Four',
# 'data_id': '1454426_2591111986',
# 'data_type': 'image',
# 'question': 'How many towels are in the image?',
# 'question_id': '101669',
# 'question_type_id': 5
# }
def convert_json_to_txt(json_path, image_path, txt_path, answer_path):
json_ann = json.load(open(json_path, 'rb'))
# pdb.set_trace()
with open(txt_path, 'w', encoding='utf-8') as f, open(answer_path, 'w', encoding='utf-8') as fa:
for index, item in tqdm(enumerate(json_ann['questions'])):
if item['data_type'] != 'image':
continue
question = item['question'].replace('\n', ' ')
image_file_path = os.path.join(image_path, item['data_id'])
options = {
'A': item['choice_a'],
'B': item['choice_b'],
'C': item['choice_c'],
'D': item['choice_d'],
}
for key, choice in options.items():
choice = choice.replace('\n', ' ').strip()
sentence = f'[image]{image_file_path}<tab>Question: {question} Answer: {choice}'
f.write(sentence + '\n')
fa.write("{}\t{}\t{}\t{}\t{}\t{}\n".format(index, question, choice, item['answer'], item['question_id'], item['question_type_id']))
if __name__ == '__main__':
save_dir = '/path/to/data'
convert_json_to_txt(
f'{save_dir}/SEED-Bench/SEED-Bench.json',
f'{save_dir}/SEED-Bench/SEED-Bench-image',
f'{save_dir}/SEED-Bench/seed_bench_pplformat.txt',
f'{save_dir}/SEED-Bench/seed_bench_pplformat.answer'
)
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