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| license: apache-2.0 | |
| task_categories: | |
| - robotics | |
| tags: | |
| - LeRobot | |
| - droid | |
| - openpi | |
| - federated-learning | |
| # droid8 (openpi format) | |
| 38,979 episodes of [DROID](https://droid-dataset.github.io/) for an 8-client federated-learning study: | |
| each client is **one DROID building** (the 8 buildings with the most usable episodes) with **all** its usable episodes | |
| (successful, a real language instruction, >= 2 s). 9,601,563 frames at 15 Hz, 25,686 | |
| distinct instructions. | |
| | client | building | episodes | episode_index range | | |
| |---|---|---|---| | |
| | c0 | Gates | 8,863 | 0–8862 | | |
| | c1 | TRI | 5,665 | 8863–14527 | | |
| | c2 | BWW | 5,051 | 14528–19578 | | |
| | c3 | KAIST | 4,699 | 19579–24277 | | |
| | c4 | BAIR | 3,976 | 24278–28253 | | |
| | c5 | Autolab | 3,981 | 28254–32234 | | |
| | c6 | 403 Fairmont | 3,493 | 32235–35727 | | |
| | c7 | RAIL | 3,251 | 35728–38978 | | |
| ## Download | |
| LeRobot v2.1 stores one file per episode per camera (~117k files), so the episodes ship as **39 tar shards** | |
| (`shards/droid8_chunk-XXX.tar`, uncompressed: data + videos of 1,000 episodes each). Unpack them into the dataset root: | |
| ```python | |
| import glob, os, tarfile | |
| from huggingface_hub import snapshot_download | |
| d = os.path.join(os.environ["HF_LEROBOT_HOME"], "DecentVLA/droid8_openpi") | |
| snapshot_download("DecentVLA/droid8_openpi", repo_type="dataset", local_dir=d, max_workers=8) | |
| for t in sorted(glob.glob(f"{d}/shards/*.tar")): | |
| with tarfile.open(t) as tf: | |
| tf.extractall(d, filter="data") | |
| os.remove(t) | |
| ``` | |
| ## Contents | |
| * **Source:** [`lerobot/droid_1.0.1`](https://huggingface.co/datasets/lerobot/droid_1.0.1) (DROID 1.0.1, Apache-2.0). | |
| Per-client source episode indices: `meta/decent_vla_clients.json`. Note: in that release the data files' `episode_index` | |
| column is not unique (42,644 values name two different episodes in two files); episodes here were taken by DROID's own | |
| episode table (global `index` in [dataset_from_index, dataset_to_index) of each episode's data file) and re-indexed 0..N-1. | |
| * **Format (after unpacking):** LeRobot v2.1 as read by openpi's pinned lerobot. Videos `exterior_image_1_left` | |
| (← exterior_1_left) and `wrist_image_left` are 180x320 AV1. `joint_position` (7) and `gripper_position` (1); `actions` (8) = | |
| ABSOLUTE joint-position targets + gripper position; `task` = `language_instruction`. | |
| * **Norm stats:** `assets/droid8/norm_stats.json` (openpi format), for the joint-position recipe. State = joints + gripper; | |
| actions = 15-step chunks with the 7 joints as deltas to the current state. | |
| * **Made by:** decent-vla `scripts/droid_to_openpi.py` (commit `69c379f`, tag `droid8-v1`). Recipe: | |
| `adapters/openpi/_droid.py` (`train_config: pi05_droid_jointpos`). Runbook: `examples/droid/README_droid8.md`. | |
| Please cite DROID (Khazatsky et al., "DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset", RSS 2024). | |