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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 — they share the same source data + recording pipeline but differ in robot embodiment, so they're separate TFDS configs:
| variant | episodes | tasks | action / state dim | wrist cameras | TFDS name |
|---|---|---|---|---|---|
| **[single](./single)** | 685 | 14 | 28 | `wrist_image` | `dexbench_rlds/single` |
| **[bimanual](./bimanual)** | 746 | 9 | 56 | `left_wrist_image` + `right_wrist_image` | `dexbench_rlds/bimanual` |
Total: 1,431 episodes, ~574k frames, 30 fps, 256×256 RGB.
## 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-00128
```
```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 (14)
| `task_index` | task identifier | language instruction |
| ------------ | ------------------------------------------ | --------------------------------------------- |
| 0 | Dexbench-OpenFaucet-v0 | "open the faucet" |
| 1 | Dexbench-FunctionalDrillApply-v0 | "operate the power drill" |
| 2 | Dexbench-FunctionalPourCan-v0 | "pour from the can" |
| 3 | Dexbench-FunctionalPourMug-v0 | "pour from the mug" |
| 4 | Dexbench-PivotLargeCuboidAgainstWall-v0 | "pivot the large cuboid against the wall" |
| 5 | Dexbench-TakeBookOffShelf-v0 | "take the book off the shelf" |
| 6 | Dexbench-GraspBleach-v0 | "grasp the bleach bottle" |
| 7 | Dexbench-GraspCup-v0 | "grasp the cup" |
| 8 | Dexbench-GraspKettle-v0 | "grasp the kettle" |
| 9 | Dexbench-GraspPan-v0 | "grasp the pan" |
| 10 | Dexbench-PickThinObjectFromContainer-v0 | "pick the thin object out of the container" |
| 11 | Dexbench-GearMesh-v0 | "mesh the gears together" |
| 12 | Dexbench-InsertPeg-v0 | "insert the peg into the hole" |
| 13 | 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.py`, 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.
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