id -> index, finish moving compute_stats before hf_dataset push_to_hub
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@@ -49,7 +49,7 @@ print(f"number of episodes: {len(hf_dataset.unique('episode_id'))=}")
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print(f"average number of frames per episode: {len(hf_dataset) / len(hf_dataset.unique('episode_id')):.3f}")
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# select the frames belonging to episode number 5
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hf_dataset = hf_dataset.filter(lambda frame: frame["episode_id"] == 5)
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hf_dataset = hf_dataset.filter(lambda frame: frame["episode_index"] == 5)
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# load all frames of episode 5 in RAM in PIL format
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frames = hf_dataset["observation.image"]
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