| import json
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| import pandas as pd
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| from pathlib import Path
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|
|
|
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| DATASET_ROOT = Path(r"C:\Users\h28176\OneDrive - Centria ammattikorkeakoulu Oy\python_projects\RTDE_python\Ur5e_RTDE\lerobot_dataset_ur5e_dualcam")
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|
|
|
|
| info_path = DATASET_ROOT / "meta" / "info.json"
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| with open(info_path, "r") as f:
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| info = json.load(f)
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|
|
| info["codebase_version"] = "v3.0"
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|
|
|
|
| info["features"] = {
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| "observation.images.wrist": {
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| "dtype": "video",
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| "shape": [480, 640, 3],
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| "info": {"video.fps": 15, "video.codec": "h264"},
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| },
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| "observation.images.context": {
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| "dtype": "video",
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| "shape": [480, 640, 3],
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| "info": {"video.fps": 15, "video.codec": "h264"},
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| },
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| "observation.state": {"dtype": "float32", "shape": [6]},
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| "action": {"dtype": "float32", "shape": [6]},
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| "timestamp": {"dtype": "float32", "shape": []},
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| "frame_index": {"dtype": "int64", "shape": []},
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| "episode_index": {"dtype": "int64", "shape": []},
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| "index": {"dtype": "int64", "shape": []},
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| "task_index": {"dtype": "int64", "shape": []},
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| }
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|
|
| with open(info_path, "w") as f:
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| json.dump(info, f, indent=4)
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|
|
| print("✅ Updated info.json to v3.0 with your desired features.")
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|
|
|
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|
|
| data_dir = DATASET_ROOT / "data" / "chunk-000"
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| for pq in data_dir.glob("*.parquet"):
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| df = pd.read_parquet(pq)
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| if "index" not in df.columns:
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| df["index"] = range(len(df))
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| if "task_index" not in df.columns:
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| df["task_index"] = 0
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| df.to_parquet(pq, index=False)
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| print(f"🧩 Updated {pq.name}")
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|
|
| print("🎉 Dataset fully converted to LeRobot v3.0 structure.")
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|
|
