TLabel

A Unified Annotation Framework for Cross-Sensor Tactile Manipulation Data

TLabel is the first cross-sensor tactile annotation schema with capability declarations and Compliance Level stratification. It enables heterogeneous tactile sensors — regardless of operating principle — to produce compatible 14-dimensional semantic annotations while preserving their unique strengths.

TL;DR — The Unicode for tactile data: one standard schema, every sensor.

Why TLabel?

Tactile datasets today ship as raw sensor signals without semantic annotations. Each sensor type demands its own ad-hoc processing, and results from different sensors cannot be compared or fused. TLabel addresses this by:

• Standardizing annotations at the semantic level — 14 dimensions covering spatial, mechanical, surface, dynamic, and meta perceptions
• Declaring capabilities — each sensor adapter explicitly states which dimensions it can and cannot annotate
• Stratifying compliance — Compliance Level (L1–L4) ensures every sensor participates at its appropriate information density
• Enabling cross-sensor comparison through a shared output format

Quick Start

Install

pip install tlabel

Load and explore data

import tlabel

# Load tactile data (auto-detects sensor format)
data = tlabel.load("path/to/sensor_data.pkl")

# Or try the built-in demo — no files needed
data = tlabel.demo("gelsight")

# Inspect annotation metadata
print(data.describe())
# -> {'num_frames': 500, 'sensor': 'gelsight', 'compliance_level': 'L2', ...}

Interactive annotation (Jupyter)

# Open the bilingual annotation panel (Chinese / English)
data.review()

Export to training formats

# JSON / CSV for analysis
data.export("output.json")

# FTP-1 Zarr for foundation model training
data.export_ftp1("output.zarr")

# LeRobot format
from tlabel.converters import tlabel_to_lerobot
tlabel_to_lerobot("annotations.json", "lerobot_episode/")

CLI

tlabel list                       # List all registered adapters
tlabel info gelsight              # Adapter details & compliance level
tlabel validate data.json         # Schema compliance check

Install optional dependencies

pip install tlabel[gelsight]      # GelSight / DIGIT (.pkl)
pip install tlabel[paxini]        # PaXini PXCap (.h5)
pip install tlabel[daimon]        # Daimon DM-TacClaw (.parquet)
pip install tlabel[ftp1]          # FTP-1 export (zarr)
pip install tlabel[all]           # Everything

Schema V2 — 14 Dimensions, 4 Compliance Levels

TLabel Schema V2 defines 14 semantic dimensions, with Compliance Levels (L1–L4) indicating annotation completeness:

#	Dimension	Type	Required
1	contact	bool	✅ Required
2	contact_centroid	[float × 2]	✅ Required (when contact)
3	force_magnitude	float	✅ Required (L2+)
4	slip_event	bool	✅ Required
5	confidence	float	✅ Required
6	compliance_level	L1 / L2 / L3 / L4	✅ Required
7	contact_region	enum	Optional
8	force_vector	[float × 3]	Optional (L3+)
9	torque_vector	[float × 3]	Optional
10	slip_velocity	[float × 2]	Optional
11	manipulation_phase	enum	Optional
12	texture_class	enum	Optional
13	object_deformation	float	Optional
14	temperature	float	Optional

Compliance Levels

Level	Name	Required Fields	Example Sensors
L1	Basic Tactile	contact, contact_centroid, slip_event, confidence	Single-point resistive, proximity
L2	Force-Aware	L1 + force_magnitude	Paxini, YCB-Slide, GelSight
L3	Full-Vector	L2 + force_vector	ToucHD, calibrated DM-TAC
L4	Rich-Semantic	L3 + all optional fields	BioTac, next-gen multimodal

Capability declarations are the core innovation: each adapter declares which of the 14 semantic dimensions it can and cannot annotate. Only supported fields appear in the output. No forced alignment, no data fabrication.

Supported Sensors

Dataset Adapters (offline data loading)

Sensor	Type	Format	Level
GelSight Mini / DIGIT	Visuo-tactile	.pkl	L3
Daimon DM-TacClaw	Multimodal	.parquet	L3
PaXini PXCap	Force array	.h5	L2
UniVTAC	Visuo-tactile	.hdf5	L3
TacQuad (AnyTouch)	Multi-sensor	directory	L3
VTouch	Visuo-tactile	.h5	L3
YCB-Slide	Visuo-tactile	.npy	L3

Real-time Sensor Adapters (hardware)

Sensor	Type	Connection	Level
PaXini GEN3	Force array	SDK	L2
Daimon DM-Tac	Visuo-tactile	USB / .avi	L3

Architecture

┌─────────────────────────────────────────────────┐
│  Layer 1: Schema                                │
│  14 semantic dimensions + Compliance Level L1-L4│
├─────────────────────────────────────────────────┤
│  Layer 2: Adapters                              │
│  DataAdapterBase │ SensorAdapterBase             │
│  (7 built-in + community-extensible)            │
├─────────────────────────────────────────────────┤
│  Layer 3: Downstream                            │
│  Feature derivation · Augmentation · Export      │
│  PredictEngine · FTP-1 · LeRobot · RLDS · ROS2 │
└─────────────────────────────────────────────────┘

• DataAdapterBase — subclass to add file-based sensor support (~30 min)
• SensorAdapterBase — subclass to add real-time hardware support
• Both share the unified export pipeline

Export Formats

Format	Purpose	Usage
JSON / CSV	General analysis	data.export("out.json")
FTP-1 Zarr	Foundation model training	data.export_ftp1("out.zarr")
LeRobot	LeRobot framework	tlabel_to_lerobot(src, dst)
RLDS	RLDS/TFDS pipeline	converters.rlds module
ROS2	Robot runtime	Stub (coming soon)

Key Results

Metric	Result
Schema	14 semantic dimensions + Compliance Level (L1–L4)
Schema version	v2.1.0
Hard errors across 750K+ observations	0
Cross-scenario generalization accuracy	+7.93% (p=0.029)
Slip-risk detection F1	+10.35% (p<0.001)
Sensors validated	Daimon-Infinity (GelSight) + PaXini PXCap (6D Hall-effect) + DIGIT (visuo-tactile)

Documentation

Document	Description
TLabel Format Spec	Complete annotation schema specification
Annotation Spec	Annotation methodology and guidelines
Design Document	Core design decisions and architecture
中文文档	Chinese version of this README

Contributing

TLabel is designed to be extensible. Add your sensor in ~30 minutes:

1. Fork contrib/adapter-template/
2. Subclass DataAdapterBase or SensorAdapterBase
3. Submit a PR or publish as a standalone package

See CONTRIBUTING.md for details.

Paper

TLabel: A Unified Annotation Framework for Cross-Sensor Tactile Manipulation Data

Xi Luo, Sheng Wu (Niuxu Tech)

[PDF]

LaTeX source available in paper/.

Validation

TLabel has been validated on three sensors with fundamentally different physics:

Sensor	Type	Episodes	Tasks	Hard Errors	Compliance Level
Daimon-Infinity	Vision-based GelSight	94	6	0	L2
PaXini PXCap	6D Hall-effect array	15	7	0	L2
DIGIT	Visuo-tactile	12	4	0	L2

License

This project is licensed under the MIT License — see LICENSE for details.

The TLabel Format specification is free to implement by anyone. We encourage the community to build adapters for additional sensors.

Acknowledgments

TLabel builds on insights from the tactile sensing community, including Open X-Embodiment, LeRobot, and OpenTouch.

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