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50 lines
1.4 KiB
50 lines
1.4 KiB
2 years ago
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import pandas as pd
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import io
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import base64
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import json
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from PIL import Image
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'''
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This script convert mmbench_test tsv file to jsonl
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This script is very similar to mmbench_converter_dev except there's no answer for accuracy calculation
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'''
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datas = pd.read_csv("data/mmbench/mmbench_test_20230712/mmbench_test_20230712.tsv", sep='\t')
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global_choices = ['A', 'B', 'C', 'D']
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def decode_base64_to_image(base64_string):
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image_data = base64.b64decode(base64_string)
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image = Image.open(io.BytesIO(image_data))
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return image
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with open('./data/mmbench/mmbench_test_20230712/mmbench_test_20230712.jsonl', 'w') as f:
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for idx in range(len(datas)):
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data = datas.iloc[idx]
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index = int(data['index'])
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question = data['question']
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hint = data['hint'] if not pd.isna(data['hint']) else 'N/A'
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choices = []
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for opt in global_choices:
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if pd.isna(data[opt]):
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continue
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choices.append(data[opt])
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# answer = global_choices.index(data['answer'])
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image = decode_base64_to_image(data['image'])
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image.save("data/mmbench/mmbench_test_20230712/images/%d.jpg" % index)
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f.write(json.dumps({
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"index": index,
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"image": "data/mmbench/mmbench_test_20230712/images/%d.jpg" % index,
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"hint": hint,
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"question": question,
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"choices": choices,
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# "answer": answer,
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}) + "\n")
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