https://github.com/lancedb/lerobot-lancedb
https://github.com/lancedb/lerobot-lancedb
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/lancedb/lerobot-lancedb
- Owner: lancedb
- License: other
- Created: 2026-05-12T09:19:08.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2026-05-16T10:45:10.000Z (3 months ago)
- Last Synced: 2026-05-16T12:39:41.607Z (3 months ago)
- Language: Python
- Homepage: https://lancedb.github.io/lerobot-lancedb/
- Size: 793 KB
- Stars: 6
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# lerobot-lancedb
📖 **Docs: **
Lance-backed datasets for [LeRobot](https://github.com/huggingface/lerobot). Drop-in replacement for `LeRobotDataset` with two storage layouts:
- **`LeRobotLanceDataset`** — per-frame JPEG bytes (lossy, fastest at single-frame access, optional GPU NVJPEG decode).
- **`LeRobotLanceVideoDataset`** — per-file mp4 bytes stored via Lance blob v2, decoded on the fly with torchcodec. Bit-exact pixels, ~same disk size as upstream.
Both subclass `LeRobotDataset` so existing trainers / samplers / `isinstance` checks accept them transparently.
## Install
```bash
pip install lerobot-lancedb
```
For local development:
```bash
git clone https://github.com/lancedb/lerobot-lancedb.git
cd lerobot-lancedb
pip install -e '.[dev]'
```
## Quickstart
```bash
# Convert (recommended path for dtype=video sources)
lerobot-convert-to-lance-video \
--repo-id=lerobot/aloha_static_cups_open \
--output=./aloha_cups_open_lance_video --overwrite
```
```python
from lerobot_lancedb import LeRobotLanceVideoDataset
ds = LeRobotLanceVideoDataset(root="./aloha_cups_open_lance_video")
```
For the JPEG layout, use `lerobot-convert-to-lance` and `LeRobotLanceDataset` instead. See the [docs](https://lancedb.github.io/lerobot-lancedb/) for the full CLI / API reference.
## Benchmark
Realistic training read pattern (`delta_timestamps`, 8 frames / sample, batch 32, num_workers 4, CPU decode, H100):
| dataset | format | size MB | delta_ts fps | **speedup** |
|---|---|---:|---:|---:|
| **pusht** (96×96, 1-cam) | upstream parquet+mp4 | 7.3 | 750 | 1.00× |
| | `convert_to_lance` (JPEG-95) | 60.0 | 3510 | **4.68×** |
| | `convert_to_lance --jpeg-quality=100 --jpeg-subsampling=0` | 105.6 | 2909 | 3.88× |
| | **`convert_to_lance_video`** | **8.0** | 2853 | **3.80×** |
| **ALOHA cups_open** (480×640, 4-cam) | upstream parquet+mp4 | 485.6 | 18.7 | 1.00× |
| | `convert_to_lance` (JPEG-95) | 3626.0 | 46.0 | **2.46×** |
| | `convert_to_lance --jpeg-quality=100 --jpeg-subsampling=0` | 8735.4 | 32.5 | 1.74× |
| | **`convert_to_lance_video`** | **487.4** | 45.6 | **2.44×** |
| **Koch lego** (480×640, 2-cam) | upstream parquet+mp4 | 2014.1 | 26.6 | 1.00× |
| | `convert_to_lance` (JPEG-95) | 8541.0 | 70.8 | **2.66×** |
| | `convert_to_lance --jpeg-quality=100 --jpeg-subsampling=0` | 17 335.3 | 49.0 | 1.84× |
| | **`convert_to_lance_video`** | **2015.9** | 53.8 | **2.02×** |
Reproducible via [`examples/benchmark_formats.py`](examples/benchmark_formats.py).
## Training parity
`convert_to_lance_video` trains a `DiffusionPolicy` on pusht to **68.4 % gym-pusht success** (seed=42, 500 rollouts) — matches the head-to-head upstream parquet+mp4 result (68.0 %) and the published [`lerobot/diffusion_pusht`](https://huggingface.co/lerobot/diffusion_pusht) (65.4 %).
Full numbers (pusht env-eval + ALOHA cups_open held-out MSE across all storage modes) in [`docs/benchmarks.md`](https://lancedb.github.io/lerobot-lancedb/benchmarks/). Reproducers: [`examples/train_and_eval_lance.py`](examples/train_and_eval_lance.py) and [`examples/aloha_loader_parity.py`](examples/aloha_loader_parity.py).
## Cloud / Hub
Both readers accept `s3://`, `gs://`, `hf://datasets/...`, `hf://buckets/...` URIs and pick up credentials from the usual env vars (`AWS_*`, `GOOGLE_APPLICATION_CREDENTIALS`, `HF_TOKEN`). Lance does byte-range fetches — no full-dataset download.
Pre-converted reference datasets you can paste directly:
```python
from lerobot_lancedb import LeRobotLanceDataset, LeRobotLanceVideoDataset
LeRobotLanceDataset(repo_id="lance-format/pusht-lerobot-lancedb") # 60 MB JPEG layout
LeRobotLanceVideoDataset(repo_id="lance-format/pusht-lerobot-lancedb-video") # 8 MB video-blob layout
```
## License
Apache 2.0.