touchtronix/FusionX-Multimodal-Sample-Data-V2

FusionX Multimodal Sample Dataset

This repository contains multimodal dataset capturing synchronized vision and tactile glove data across distinct tasks.

Dataset Overview

• RGB Video: 30 Hz 720p color stream (.mp4).
• Depth Data: Lossless 16-bit depth stream (.mkv) and raw 16-bit PNG frames.
• Mono Vision: Left and right monochrome camera views (raw PNG).
• Tactile Data: Per-frame aligned glove sensor data stored in high-performance .parquet format.
• Calibration: Intrinsic and extrinsic parameters provided in .json.

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Repository Structure

The dataset is organized by task. To optimize performance, raw image frames are compressed into modality-specific ZIP archives.

dataset/
├── dataset_info.json            # Global dataset metadata
├── [task_name]/                 # e.g., box_cut1, drill1, waterpour3
│   ├── depth.mkv                # Post-processed depth video
│   ├── rgb.mp4                  # Post-processed RGB video
│   ├── preview_all.mp4          # Synced visualization (Grid view)
│   ├── preview_glove.mp4        # Tactile data visualization
│   ├── frames.parquet           # Main data index (Timestamps + Tactile)
│   ├── calib.json               # Calibration matrices
│   ├── video_meta.json          # Post-processed video specifications
│   ├── depth.zip                # Raw 16-bit PNG frames
│   ├── mono_left.zip            # Raw mono-left PNG frames
│   ├── mono_right.zip           # Raw mono-right PNG frames
│   └── rgb.zip                  # Raw RGB JPG frames

Tactile Data Schema (frames.parquet)

The frames.parquet file is the central index for the dataset, providing per-frame synchronization between vision and tactile sensors.

1. Vision & Synchronization

Column	Description
frame_idx	Integer index of the frame.
timestamp	Global synchronized UNIX timestamp.
rgb_path, depth_path	Relative paths to the original RGB and Depth images.
mono_left_path, mono_right_path	Relative paths to the monochrome stereo images.

2. Camera IMU (OAK-D)

Column	Description
oak_imu_quaternion	4-element orientation vector (W, X, Y, Z).
oak_imu_gyro	Angular velocity (rad/s) for X, Y, Z axes.
oak_imu_accel	Linear acceleration (m/s²) for X, Y, Z axes.

3. Tactile Glove Data (Left Hand: lh_, Right Hand: rh_)

Each hand contains independent timestamping and comprehensive pressure/bend sensing:

Feature	Columns
Glove Timing	_glove_timestamp, _glove_dt_ms
Raw Pressure	_thumb_pressure, _index_pressure, _middle_pressure, _ring_pressure, _little_pressure, _palm_pressure
Calibrated Pressure	_thumb_pressure_cal, _index_pressure_cal, _middle_pressure_cal, _ring_pressure_cal, _little_pressure_cal, _palm_pressure_cal
Finger Kinematics	_finger_bend (Raw), _finger_bend_cal (Calibrated)
Glove IMU	_imu_quaternion, _imu_gyro, _imu_accel

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How to Use

1. Download the Dataset

You can clone this repository using Git LFS or use the huggingface_hub library:

from huggingface_hub import snapshot_download

# Download the specific task you need
snapshot_download(
    repo_id="touchtronix/FusionX-Multimodal-Sample-Data-V2",
    repo_type="dataset",
    allow_patterns="box_cut1/*" 
)

2. Accessing Raw Frames

If you require the original image files instead of the video streams, extract the modality zips within the task folder:

unzip box_cut1/rgb.zip -d box_cut1/rgb/

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License

Creative Commons Attribution 4.0 (CC BY 4.0) You are free to:

• Use: Incorporate the data into your own projects.
• Share: Copy and redistribute the material in any medium or format.
• Modify: Remix, transform, and build upon the material.
• Commercial Use: Use the data for commercial purposes.

As long as appropriate attribution is provided to Touchtronix Robotics.