| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - RLDS |
| - Open-X-Embodiment |
| - TFDS |
| - dexbench |
| - dexterous-manipulation |
| pretty_name: DexBench (RLDS) |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: single |
| data_files: "single/1.0.0/dexbench_rlds-train.tfrecord-*" |
| - config_name: bimanual |
| data_files: "bimanual/1.0.0/dexbench_rlds-train.tfrecord-*" |
| --- |
| |
| # DexBench (RLDS) |
|
|
| DexBench dexterous manipulation demonstrations replayed through Isaac Lab, packaged as **Open-X-Embodiment-style RLDS / TFDS** datasets. Each frame: third-person + wrist RGB at 256×256, proprioception, joint-space action, and a natural-language instruction. |
|
|
| This repo contains **two variants** as sibling subdirectories — same source data + recording pipeline, different robot embodiments → separate TFDS configs: |
|
|
| | variant | episodes | tasks | action / state dim | wrist cameras | TFDS name | |
| |---|---|---|---|---|---| |
| | **[single](./single)** | 735 | 15 | 28 | `wrist_image` | `dexbench_rlds/single` | |
| | **[bimanual](./bimanual)** | 746 | 9 | 56 | `left_wrist_image` + `right_wrist_image` | `dexbench_rlds/bimanual` | |
|
|
| Total: 1,481 episodes, ~585k frames, 30 fps, 256×256 RGB. |
|
|
| **Per-episode visual randomization is disabled** — the HDRI background and table texture are fixed across all episodes for visually stable demonstrations. |
|
|
| ## Feature schema |
|
|
| Both variants share the same Open-X-Embodiment step structure. Image/state/action shapes vary by variant. |
|
|
| ``` |
| FeaturesDict({ |
| 'episode_metadata': FeaturesDict({ |
| 'file_path': Text(), |
| 'task': Text(), |
| }), |
| 'steps': Dataset({ |
| 'observation': FeaturesDict({ |
| 'image': Image((256, 256, 3), uint8), # third-person |
| 'wrist_image': Image((256, 256, 3), uint8), # single only |
| 'left_wrist_image': Image((256, 256, 3), uint8), # bimanual only |
| 'right_wrist_image': Image((256, 256, 3), uint8), # bimanual only |
| 'state': Tensor((28 | 56,), float32), |
| }), |
| 'action': Tensor((28 | 56,), float32), |
| 'discount': Scalar(float32), # always 1.0 |
| 'reward': Scalar(float32), # 1.0 on terminal success step, else 0.0 |
| 'is_first': Scalar(bool), |
| 'is_last': Scalar(bool), |
| 'is_terminal': Scalar(bool), |
| 'language_instruction': Text(), |
| }), |
| }) |
| ``` |
|
|
| ## Usage |
|
|
| The repo layout matches the TFDS data_dir convention. Clone the full repo, then load with `tensorflow_datasets`: |
|
|
| ```bash |
| mkdir -p ~/data/dexbench_rlds |
| hf download dexbench/rlds --repo-type dataset --local-dir ~/data/dexbench_rlds |
| # After: ~/data/dexbench_rlds/{single,bimanual}/1.0.0/*.tfrecord-NNNNN-of-NNNNN |
| ``` |
|
|
| ```python |
| import tensorflow_datasets as tfds |
| |
| # Single-hand variant |
| ds_s = tfds.builder("dexbench_rlds/single", data_dir="~/data").as_dataset(split="train") |
| # Bimanual variant |
| ds_b = tfds.builder("dexbench_rlds/bimanual", data_dir="~/data").as_dataset(split="train") |
| |
| for ep in ds_s.take(1): |
| print(ep["episode_metadata"]["task"].numpy().decode()) |
| for step in ep["steps"].take(1): |
| img = step["observation"]["image"] # (256, 256, 3) uint8 |
| state = step["observation"]["state"] # (28,) float32 |
| action = step["action"] # (28,) float32 |
| instr = step["language_instruction"].numpy().decode() |
| ``` |
|
|
| ## Tasks |
|
|
| ### Single-hand (15) |
|
|
| | `task_index` | task identifier | language instruction | |
| | ------------ | ------------------------------------------ | --------------------------------------------- | |
| | 0 | Dexbench-OpenFaucet-v0 | "open the faucet" | |
| | 1 | Dexbench-FunctionalDrillApply-v0 | "operate the power drill" | |
| | 2 | Dexbench-FunctionalHammerStrike-v0 | "strike the nail with the hammer" | |
| | 3 | Dexbench-FunctionalPourCan-v0 | "pour from the can" | |
| | 4 | Dexbench-FunctionalPourMug-v0 | "pour from the mug" | |
| | 5 | Dexbench-PivotLargeCuboidAgainstWall-v0 | "pivot the large cuboid against the wall" | |
| | 6 | Dexbench-TakeBookOffShelf-v0 | "take the book off the shelf" | |
| | 7 | Dexbench-GraspBleach-v0 | "grasp the bleach bottle" | |
| | 8 | Dexbench-GraspCup-v0 | "grasp the cup" | |
| | 9 | Dexbench-GraspKettle-v0 | "grasp the kettle" | |
| | 10 | Dexbench-GraspPan-v0 | "grasp the pan" | |
| | 11 | Dexbench-PickThinObjectFromContainer-v0 | "pick the thin object out of the container" | |
| | 12 | Dexbench-GearMesh-v0 | "mesh the gears together" | |
| | 13 | Dexbench-InsertPeg-v0 | "insert the peg into the hole" | |
| | 14 | Dexbench-PlugCharger-v0 | "plug the charger into the receptacle" | |
|
|
| ### Bimanual (9) |
|
|
| | `task_index` | task identifier | language instruction | |
| | ------------ | -------------------------------------------------- | ----------------------------------- | |
| | 0 | Dexbench-FixateThenManipulate-LiftBasketHandle-v0 | "lift the basket by its handle" | |
| | 1 | Dexbench-FixateThenManipulate-OpenFlatFolder-v0 | "open the flat folder" | |
| | 2 | Dexbench-FixateThenManipulate-OpenHuaweiPhone-v0 | "open the phone case" | |
| | 3 | Dexbench-FixateThenManipulate-OpenLaptop-v0 | "open the laptop" | |
| | 4 | Dexbench-FixateThenManipulate-OpenStapler-v0 | "open the stapler" | |
| | 5 | Dexbench-FixateThenManipulate-SlideUtilityKnife-v0 | "slide out the utility knife blade" | |
| | 6 | Dexbench-FixateThenManipulate-SqueezeScissors-v0 | "squeeze the scissors" | |
| | 7 | Dexbench-BimanualLiftBasket-v0 | "lift the basket with both hands" | |
| | 8 | Dexbench-BimanualLiftTray-v0 | "lift the tray with both hands" | |
|
|
| Some bimanual tasks have condition variants (`_lose_startup`, `_onthetable`) merged under the base task id. |
|
|
| ## LeRobot mirror |
|
|
| The same source data is also released as LeRobot v2.1 datasets, useful if you prefer that loader: |
|
|
| - **[dexbench/single-lerobot](https://huggingface.co/datasets/dexbench/single-lerobot)** — single-hand |
| - **[dexbench/bimanual-lerobot](https://huggingface.co/datasets/dexbench/bimanual-lerobot)** — bimanual |
|
|
| ## Source |
|
|
| Replayed from teleop trajectory pickles in the gated [`dexbench/DexBench_dataset`](https://huggingface.co/datasets/dexbench/DexBench_dataset) repo using DexBench's `scripts/create_demo_files_sequential.py` (one Isaac Sim env per task, episodes replayed serially within the env, per-episode HDRI / table-texture randomizers disabled). Then converted with `scripts/convert_to_rlds.py` (jpeg-in-tfrecord). |
|
|
| ## License |
|
|
| Apache-2.0. Defers to upstream DexBench terms for the underlying assets and teleop data. |
|
|
