File size: 3,315 Bytes
62dbf5a ad9d0f7 62dbf5a ad9d0f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | ---
license: cc-by-4.0
pretty_name: T-Rex Dataset Visualizer
task_categories:
- robotics
- video-classification
language:
- en
tags:
- robotics
- tactile-sensing
- dexterous-manipulation
- bimanual-manipulation
- teleoperation
- video
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: metadata.csv
---
# T-Rex Dataset Visualizer
A browseable subset of the **T-Rex** dataset — *Tactile-Rich Bimanual Dexterous
Manipulation* — collected on a bimanual **Dexmate Vega-1** robot equipped with
two **Sharpa Wave** dexterous hands.
This visualizer subset contains **3,838 short trajectory clips** drawn from the
full 100-hour T-Rex collection, organized by `(verb, object, hand)` so you can
quickly inspect coverage across motion primitives and object categories.
> For the full dataset (multi-view RGB, robot states, joint actions, per-fingertip
> tactile signals, and language instructions), see the main project release.
## Schema
| Column | Type | Description |
|---------------|--------|-----------------------------------------------------------------|
| `file_name` | video | Relative path to the `.mp4` clip (head camera view). |
| `id` | string | Unique 5-digit clip identifier. |
| `verb` | string | Canonical motion primitive (e.g. `reach`, `grasp_and_lifting`). |
| `object` | string | Canonical object category (e.g. `book`, `airpods`). |
| `hand` | string | `left_hand` or `right_hand`. |
| `episode` | string | Episode identifier the clip was sampled from. |
| `verb_raw` | string | Raw verb label before canonicalization. |
| `object_raw` | string | Raw object label before canonicalization. |
## Coverage
- **Total clips:** 3,838
- **Motion primitives:** 22 (e.g. `grasp_and_lifting`, `reach`, `wrap`, `fold`,
`press`, `peel`, `wipe`, `squeeze`, `open`, `cut`, `close`, `shake`, `pour`,
`screw`, `insert`, `assemble`, …)
- **Object categories:** 270+ daily objects (top: `airpods`, `bubble_wrap`,
`book`, `aluminum_foil`, `button`, `clamshell_container`, `flip_phone`,
`bowl`, `sponge`, `plastic_wrap`, …)
- **Hands:** balanced left / right coverage
A full breakdown is provided in [`manifest.json`](./manifest.json).
## Usage
```python
from datasets import load_dataset
ds = load_dataset("Beakerman0101/trex-visualizer", split="train")
print(ds[0])
# {'file_name': <Video>, 'id': '00001', 'verb': 'reach', 'object': 'book',
# 'hand': 'left_hand', 'episode': 'episode_0000', ...}
```
You can also stream raw clips directly by URL:
```
https://huggingface.co/datasets/Beakerman0101/trex-visualizer/resolve/main/videos/<file_name>
```
## Filtering Examples
```python
# All "fold" demonstrations
folds = ds.filter(lambda r: r["verb"] == "fold")
# Left-hand "grasp_and_lifting" of a book
subset = ds.filter(
lambda r: r["verb"] == "grasp_and_lifting"
and r["object"] == "book"
and r["hand"] == "left_hand"
)
```
## License
Released under **CC-BY-4.0**. Please cite the T-Rex project if you use this
visualizer subset in published work.
|