Upload 7 files
Browse files- .gitattributes +6 -0
- SEED-Bench-2-image.zip.001 +3 -0
- SEED-Bench-2-image.zip.002 +3 -0
- SEED-Bench-2-image.zip.003 +3 -0
- SEED-Bench-2-image.zip.004 +3 -0
- SEED-Bench-2-image.zip.005 +3 -0
- SEED-Bench-2-image.zip.006 +3 -0
- SEED-Bench-2.py +92 -0
.gitattributes
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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SEED-Bench_v2_level1_2_3.json filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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SEED-Bench_v2_level1_2_3.json filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.001 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.002 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.003 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.004 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.005 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.006 filter=lfs diff=lfs merge=lfs -text
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SEED-Bench-2-image.zip.001
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SEED-Bench-2-image.zip.002
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SEED-Bench-2-image.zip.003
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SEED-Bench-2-image.zip.004
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SEED-Bench-2-image.zip.005
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SEED-Bench-2-image.zip.006
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size 734003200
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SEED-Bench-2.py
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import json
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import os
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import pdb
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import datasets
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_BASE_URL = "https://huggingface.co/datasets/AILab-CVC/SEED-Bench-2/raw/main/SEED-Bench_v2_level1_2_3.json"
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class SEEDBenchDataset(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="default", version=VERSION, description="SEED-Bench-2 dataset"),
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]
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DEFAULT_CONFIG_NAME = "default"
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def _info(self):
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return datasets.DatasetInfo(
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features=datasets.Features(
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{
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"answer": datasets.Value("string"),
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"choice_a": datasets.Value("string"),
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"choice_b": datasets.Value("string"),
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"choice_c": datasets.Value("string"),
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"choice_d": datasets.Value("string"),
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"data_id": datasets.Value("string"),
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"data_source": datasets.Value("string"),
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"data_type": datasets.Value("string"),
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"level": datasets.Value("string"),
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"question": datasets.Value("string"),
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"question_id": datasets.Value("string"),
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"question_type_id": datasets.Value("string"),
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"subpart": datasets.Value("string"),
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"version": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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)
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def _split_generators(self, dl_manager):
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urls_to_download = {"data_file": _BASE_URL}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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# 为数据集创建一个测试拆分
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"data_file": downloaded_files["data_file"]},
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),
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]
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def _generate_examples(self, data_file):
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# pdb.set_trace()
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with open(data_file, 'r') as f:
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data = json.load(f)
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for item in data["questions"]:
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# 提取数据集中的每个字段
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answer = item["answer"]
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choice_a = item["choice_a"]
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choice_b = item["choice_b"]
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choice_c = item["choice_c"]
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choice_d = item["choice_d"]
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data_id = item["data_id"]
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data_source = item["data_source"]
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data_type = item["data_type"]
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level = item["level"]
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question = item["question"]
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question_id = item["question_id"]
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question_type_id = item["question_type_id"]
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subpart = item['subpart']
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version = item['version']
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# 返回一个包含数据集特征的字典
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yield question_id, {
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"answer": answer,
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"choice_a": choice_a,
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"choice_b": choice_b,
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"choice_c": choice_c,
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"choice_d": choice_d,
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"data_id": data_id,
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"data_source": data_source,
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"data_type": data_type,
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"level": level,
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"question": question,
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"question_id": question_id,
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"question_type_id": question_type_id,
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"subpart": subpart,
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"version": version,
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}
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