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license: cc-by-4.0
task_categories:
- robotics
tags:
- robotics
- tactile
- manipulation
- multimodal
- gelsight
- realsense
- motion-capture
pretty_name: React (Tactile-Visual Manipulation)
size_categories:
- 10K<n<100K
configs:
- config_name: motherboard
data_files:
- split: train
path: processed/mode1_v1/motherboard/**/episode_*.pt
- config_name: all
data_files:
- split: train
path: processed/mode1_v1/**/episode_*.pt
---
# React
Multimodal manipulation recordings from a bimanual setup with vision-based tactile sensors and motion capture.
## Recording setup
| Stream | Hardware | Native shape | Rate |
|---|---|---|---|
| 3× RealSense color | Intel D415 (serials `143322063538`, `104122062574`, `217222066989`) | 480×640×3 uint8 (BGR) | 30 FPS |
| 3× RealSense depth | same | 480×640 uint16 (mm) | 30 FPS |
| 2× GelSight tactile | GelSight Mini (left / right) | 480×640×3 uint8 | ~25 FPS, resampled to camera ticks |
| 3× OptiTrack rigid bodies | `motherboard`, `sensor_left`, `sensor_right` | 7-vector (x, y, z, qx, qy, qz, qw) | ~120 Hz |
All streams share a common monotonic timestamp axis recorded under `timestamps`. Per-tracker OptiTrack streams carry their own higher-rate timestamps under `optitrack/<body>/timestamps`.
## Tasks
The dataset is organized **task-first** so new tasks can be added without renaming or recompute. Current tasks:
| Task | Description | Dates | Episodes |
|---|---|---|---|
| `motherboard` | Bimanual manipulation of components on a computer motherboard | 2026-03-23, 2026-05-10, 2026-05-11 | 30 |
`tasks.json` at the repo root is the source of truth for the task registry.
## Repository layout
```
tasks.json # registry
processed/
└─ mode1_v1/
└─ <task>/
└─ <date>/
├─ episode_000.pt
├─ episode_000.contact.json
└─ ...
```
The `processed/mode1_v1/` view is a **task-specific slice** of the underlying raw recordings, not the full sensor suite. It was produced by `twm/preprocess.py` + `twm/contact_index.py` from a private raw HDF5 mirror.
## `processed/mode1_v1/` schema
Each `episode_*.pt` is a Python dict loadable with `torch.load(..., weights_only=False)`.
| Key | Shape | dtype | Description |
|---|---|---|---|
| `view` | `(T, 3, 128, 128)` | uint8 | Overhead camera (`realsense/cam0/color`), center-cropped to square then bilinear-resized to 128×128 |
| `tactile_left` | `(T, 3, 128, 128)` | uint8 | Left GelSight, same crop/resize |
| `tactile_right` | `(T, 3, 128, 128)` | uint8 | Right GelSight, same crop/resize |
| `timestamps` | `(T,)` | float64 | Camera timestamps (seconds, monotonic clock) |
| `sensor_left_pose` | `(T, 7)` | float32 | Left GelSight rigid body OptiTrack pose, nearest-neighbor aligned to camera timestamps |
| `sensor_right_pose` | `(T, 7)` | float32 | Right GelSight rigid body OptiTrack pose, same alignment |
| `tactile_{left,right}_intensity` | `(T,)` | float32 | Per-frame mean per-pixel L2 distance from a contact-free reference frame |
| `tactile_{left,right}_area` | `(T,)` | float32 | Per-frame fraction of pixels with L2 diff > `tau` |
| `tactile_{left,right}_mixed` | `(T,)` | float32 | Mean of (diff × mask), captures intensity restricted to contact pixels |
| `_contact_meta` | dict | — | Per-episode contact metadata: `tau`, drift between first/p01 reference frames, p01 reference indices, the chosen reference RGB frames, etc. |
Each `.contact.json` is a small summary of the metric distributions plus drift diagnostics, intended for filtering / sanity checking without loading the full tensors.
### Contact metric definition
For each tactile sensor independently:
1. Pick a contact-free **reference frame**: the ~0.1th-percentile-quietest frame by mean L2 distance to the temporal median (`reference_strategy = "p01"`).
2. For each frame `t`, compute per-pixel `diff[t, x, y] = || frame[t, :, x, y] − ref[:, x, y] ||_2` (RGB L2 over channels).
3. Then:
- `intensity[t] = mean(diff[t])`
- `area[t] = mean(diff[t] > tau)` (default `tau = 8.0` on the uint8 scale)
- `mixed[t] = mean(diff[t] * (diff[t] > tau))`
`_contact_meta["drift_warning"]` is `True` if either sensor's drift (L2 distance between the first frame and the p01-reference frame) exceeds `2·tau`; in this release no episode triggers it.
## Quick start
Load one task via `datasets`:
```python
from datasets import load_dataset
ds = load_dataset("yxma/React", "motherboard", split="train")
# Each row is one .pt file path; the actual tensors live inside.
```
Or load a single episode directly:
```python
import torch
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="yxma/React",
repo_type="dataset",
filename="processed/mode1_v1/motherboard/2026-05-11/episode_003.pt",
)
ep = torch.load(path, weights_only=False)
print(ep["view"].shape, ep["tactile_left_intensity"].shape)
# torch.Size([10032, 3, 128, 128]) torch.Size([10032])
```
Load contact metadata only (much smaller — useful for filtering):
```python
import json
path = hf_hub_download(
repo_id="yxma/React",
repo_type="dataset",
filename="processed/mode1_v1/motherboard/2026-05-11/episode_003.contact.json",
)
meta = json.load(open(path))
print(meta["drift_left"], meta["drift_right"], meta["drift_warning"])
```
## Known caveats
- **Missing / dropped episodes** on `motherboard/2026-05-11`:
- `episode_000` and `episode_002` — short test recordings (8.8s and 10.4s) with no tactile contact on either sensor; intentionally excluded.
- `episode_001` — lost at recording time (HDF5 superblock never finalized when the writer was killed mid-write); intentionally absent.
- The remaining episode IDs are non-contiguous as a result. Don't infer ordering from filename gaps.
- **Lossy resize**: the 128×128 `view` and tactile fields are downsampled from native 480×640. Native resolution is **not** preserved in this release.
- **Single camera**: only `realsense/cam0/color` is included. The other two RealSense views and all depth streams are not in `processed/mode1_v1/`.
- **OptiTrack alignment**: the per-step poses are nearest-neighbor matched to camera ticks. The full ~120 Hz pose streams are not preserved here.
- **Mode is opinionated**: contact metrics depend on the chosen `tau` and the p01 reference strategy. If you want a different `tau`, re-deriving from raw is necessary.
## Roadmap
- **More tasks** — registry in `tasks.json` will grow.
- **LeRobot-format full-fidelity** variant (`lerobot/v1.0/`) is planned. It will include all three RealSense color and depth streams, GelSight at native resolution (FFV1 lossless), full-rate OptiTrack pose tracks for all three rigid bodies, and HF-native browser previews. The current `processed/mode1_v1/` slice will remain as a stable training-task view.
## Citation
If you use this dataset, please cite (TODO: add bibtex).
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