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import os |
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import json |
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import datasets |
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class Spatial457(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="L1_single"), |
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datasets.BuilderConfig(name="L2_objects"), |
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datasets.BuilderConfig(name="L3_2d_spatial"), |
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datasets.BuilderConfig(name="L4_occ"), |
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datasets.BuilderConfig(name="L4_pose"), |
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datasets.BuilderConfig(name="L5_6d_spatial"), |
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datasets.BuilderConfig(name="L5_collision"), |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description="Spatial457: A multi-task spatial visual question answering dataset.", |
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features=datasets.Features({ |
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"image": datasets.Image(), |
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"image_filename": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answer": datasets.Value("string"), |
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"question_index": datasets.Value("int32"), |
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"program": datasets.Sequence( |
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{ |
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"type": datasets.Value("string"), |
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"inputs": datasets.Sequence(datasets.Value("int32")), |
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"_output": datasets.Value("string"), |
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"value_inputs": datasets.Sequence(datasets.Value("string")), |
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} |
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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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data_dir = dl_manager.manual_dir |
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task_json = os.path.join(data_dir, "questions", f"{self.config.name}.json") |
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image_dir = os.path.join(data_dir, "images") |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"json_file": task_json, "image_dir": image_dir} |
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) |
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] |
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def _generate_examples(self, json_file, image_dir): |
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with open(json_file, "r", encoding="utf-8") as f: |
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all_data = json.load(f)["questions"] |
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for idx, q in enumerate(all_data): |
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img_path = os.path.join(image_dir, q["image_filename"]) |
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yield idx, { |
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"image": img_path, |
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"image_filename": q["image_filename"], |
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"question": q["question"], |
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"answer": str(q["answer"]), |
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"question_index": q["question_index"], |
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"program": q["program"], |
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} |
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