Beakerman0101/trex-visualizer

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.

Usage

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

# 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.