diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ff7a00b35915d734277da8a69d6c072a596eb9dd --- /dev/null +++ b/README.md @@ -0,0 +1,81 @@ +--- +license: apache-2.0 +task_categories: +- robotics +tags: +- LeRobot +- VLA +- franka +- fr3 +- real-robot +configs: +- config_name: default + data_files: data/*/*.parquet +--- + +# TASL FR3 — 10-task real-robot manipulation dataset (video format) + +Teleoperated (GELLO) demonstrations collected on a **Franka FR3 + Robotiq gripper** +bench at TASL, in **LeRobot v2.1** format. Used to LoRA fine-tune +[π0.5-DROID](https://github.com/Physical-Intelligence/openpi). + +- **250 episodes** — exactly **25 per task**, 10 tasks +- **66,463 frames** @ 15 fps (~74 minutes of teleoperation) +- **2 camera views**, 224×224 RGB, stored as **h264 mp4** (500 videos) + +> **This is the video-format copy**, made so the +> [LeRobot dataset visualizer](https://huggingface.co/spaces/lerobot/visualize_dataset) +> can open it (that viewer rejects image-only datasets). The image-in-parquet +> original — which is what the policy was actually trained on — lives at +> [`Litian2002/tasl-fr3-10task-250ep`](https://huggingface.co/datasets/Litian2002/tasl-fr3-10task-250ep). +> Frame data is identical; only the storage format differs. + +## Tasks + +| `task_index` | instruction | +|---|---| +| 0 | pick up the blue cup and place it into the red cup | +| 1 | stack the red block on top of the blue block | +| 2 | press the blue button | +| 3 | close the lid of the wooden shape sorter box | +| 4 | align the three colored blocks to the same orientation | +| 5 | rotate the red block so that it is perpendicular to the blue block | +| 6 | insert the orange block into the wooden shape sorter box | +| 7 | insert the book into the black book stand | +| 8 | pull the smaller book out of the black book stand | +| 9 | pull the small block out from under the large block | + +## Columns + +| column | shape / dtype | meaning | +|---|---|---| +| `observation.images.exterior` | 224×224×3 video | exterior camera (ZED 2i), looking at the table | +| `observation.images.wrist` | 224×224×3 video | wrist camera (ZED Mini, eye-in-hand) | +| `state` | float32 `[8]` | 7 joint angles + 1 gripper width | +| `actions` | float32 `[8]` | 7 joint velocities + 1 gripper command, normalized to [-1, 1] | +| `task_index` | int64 | index into `meta/tasks.jsonl` | +| `episode_index`, `frame_index`, `index`, `timestamp` | | standard LeRobot fields | +| `done`, `is_success`, `intervene_flag` | bool | **written by the collection stack but constant — carries no information** | + +## Notes / caveats + +- **No filtering was applied.** Every frame recorded during teleoperation is + present; no idle-frame removal, no success filtering. Idle frames are + effectively absent anyway (only 0.4% of frames have max |joint velocity| < 0.05). +- `is_success` and `intervene_flag` are `True` on **every** frame, so they cannot + be used to select successful demonstrations. +- Episode lengths: min 4, 1st pct 124, median 248, 99th pct ~700, max 971 frames. + **`episode_index=172` is only 4 frames long (0.3 s) and should be dropped.** +- The two camera images are a centre-square crop of a 1280×720 ZED frame, + resized to 224 — roughly 56% of the original horizontal field of view. +- Collected 2026-08-16 and 2026-08-20. + +## Loading + +```python +from lerobot.common.datasets.lerobot_dataset import LeRobotDataset +ds = LeRobotDataset("Litian2002/tasl-fr3-10task-250ep") +``` + +Fine-tuned checkpoints trained on this dataset: +[`Litian2002/pi05-droid-franka-lora-10task`](https://huggingface.co/Litian2002/pi05-droid-franka-lora-10task) diff --git a/data/chunk-000/episode_000000.parquet b/data/chunk-000/episode_000000.parquet new file 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