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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' | |
| ) | |