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