Note

This is a Hugging Face dataset. For large datasets, ensure huggingface_hub>=1.1.3 to avoid rate limits. Learn more in the Hugging Face integration docs.

Dataset Card for Xense Tron2 RT Pick and Place (115 episodes)#

Xense Tron2 RT Pick and Place preview

This is a FiftyOne dataset with 115 samples. Each sample is one teleoperated episode.

Installation#

pip install -U fiftyone

Usage#

Load from the Hub#

import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

dataset = load_from_hub("Voxel51/xense-tron2rt-pnp-115ep")

session = fo.launch_app(dataset)

Download a snapshot and load it locally#

import fiftyone as fo
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="Voxel51/xense-tron2rt-pnp-115ep",
    repo_type="dataset",
    local_dir="xense-tron2rt-pnp-115ep",
)

dataset = fo.Dataset.from_dir(
    dataset_dir="xense-tron2rt-pnp-115ep",
    dataset_type=fo.types.LeRobotDataset,
    name="xense_tron2rt_pnp",
)

session = fo.launch_app(dataset)

Dataset Details#

Dataset Description#

115 teleoperated episodes (48,999 frames, 30 fps) on robot type tron2_rt. The task is “Put the block into the box”. Each episode has three RGB camera streams, four tactile video streams (left and right sensor on each side), and 20-D TCP state and action. The source is a LeRobot v3.0 repo recorded with the Xense LeRobot fork.

Shared by: Xense on Hugging Face
Language(s): en
License: apache-2.0

Dataset Sources#

Repository: https://huggingface.co/datasets/Xense/tron2rt-pnp-0918

Dataset Structure#

Topology. media_type: multimodal, 115 samples, one per episode, 30 fps, 321-666 frames (10.7-22.2 s), 48,999 frames total. Samples hold a media_reference to the per-frame parquet data and 7 video streams.

Field	FiftyOne type	Description
`media_reference`	`LeRobotEpisodeReference`	Pointers into `data/` parquet and the 7 video streams
`episode_index`	`IntField`	Episode index (0-114)
`task`	`StringField`	The single task instruction
`tasks`	`ListField(StringField)`	All task strings of the episode
`length`	`IntField`	Frames in the episode
`duration`	`FloatField`	Episode duration in seconds
`robot_type`	`StringField`	`tron2_rt`
`fps`	`FloatField`	30

Data behind media_reference (per-frame, from meta/info.json):

Feature	Shape	Description
`observation.state`	(20,)	Bimanual TCP: `left_tcp.{x,y,z,r1..r6}`, `right_tcp.{x,y,z,r1..r6}`, `left_gripper.pos`, `right_gripper.pos`
`action`	(20,)	Same 20 names and layout as `observation.state`
`observation.images.top`, `left_wrist`, `right_wrist`	480x640x3	RGB cameras (H.264 yuv420p)
`observation.images.left_tactile_left`, `left_tactile_right`, `right_tactile_left`, `right_tactile_right`	400x700x3	Four tactile video streams (H.264 yuv420p)

Label types and why. The importer produces episode-level samples with a media_reference; numeric streams (state, action) are read through the viewer and are not stored as FiftyOne label fields. The source has a single task, so task is constant. No custom fields were added, so the FiftyOne dataset matches what the LeRobot export contains.

dataset.info. lerobot entry with format, format_major, episode_count, imported_episode_count, skipped_episodes (empty).

Parsing decisions.

All episodes imported from the full repo (2.5 GB). No source file was modified, and no transcoding or metadata repair was needed.
All 7 video streams were imported; no modality was excluded. All streams are standard H.264 yuv420p.
The source does not state the tactile sensor model or the physical meaning of the tactile images.

Dataset Creation#

Source Data#

Data Collection and Processing#

The source card states only that it was created using LeRobot.

Annotations#

Annotation process#

A single task string is stored in meta/tasks.parquet.