| |
| """Load every unified action22/state23 episode using unmodified official LeRobot.""" |
| import argparse |
| import json |
| import os |
| from pathlib import Path |
|
|
|
|
| def collection_root(root, name="all"): |
| |
| if name == "main": |
| name = "all" |
| root = Path(root).resolve() |
| registry = json.loads((root / "meta/collections.json").read_text()) |
| if registry.get("default_collection") != "all" or [r["name"] for r in registry["collections"]] != ["all"]: |
| raise ValueError("This loader requires the single unified all collection") |
| row = next((r for r in registry["collections"] if r["name"] == name), None) |
| if row is None: |
| raise ValueError(f"Unknown collection {name}; available: {[r['name'] for r in registry['collections']]}") |
| rel = Path(row["root"]) |
| if rel.is_absolute() or ".." in rel.parts: |
| raise ValueError("Collection root must stay inside the extracted dataset") |
| target = (root / rel).resolve() |
| if not target.is_relative_to(root): |
| raise ValueError("Collection root escapes dataset") |
| return target |
|
|
|
|
| def load_collection(root, name="all", episodes=None, cache_dir=None): |
| os.environ["HF_HUB_OFFLINE"] = "1" |
| os.environ["HF_DATASETS_OFFLINE"] = "1" |
| os.environ["TOKENIZERS_PARALLELISM"] = "false" |
| if cache_dir is not None: |
| os.environ["HF_DATASETS_CACHE"] = str(Path(cache_dir).resolve()) |
| from lerobot.datasets.lerobot_dataset import LeRobotDataset |
| return LeRobotDataset( |
| repo_id=f"local/robotagentbench-{name}", root=collection_root(root, name), episodes=episodes, |
| download_videos=False, video_backend="pyav", tolerance_s=0.0003, |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--root", type=Path, required=True, help="Extracted dataset directory containing meta/collections.json") |
| parser.add_argument("--collection", default="all") |
| parser.add_argument("--episode", type=int, default=0) |
| parser.add_argument("--frame", type=int, default=0) |
| parser.add_argument("--cache-dir", type=Path) |
| args = parser.parse_args() |
| dataset = load_collection(args.root, args.collection, [args.episode], args.cache_dir) |
| sample = dataset[args.frame] |
| print(json.dumps({"root": str(collection_root(args.root, args.collection)), "collection": args.collection, |
| "selected_episode": args.episode, "selected_episode_frames": len(dataset), |
| "task": sample.get("task"), |
| "sample_shapes": {k: list(v.shape) for k, v in sample.items() if hasattr(v, "shape")}}, indent=2)) |
|
|
