README.md

---
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: mode1_v1
    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 recorded

- **`motherboard`** — bimanual insertion / placement on a computer motherboard.

## Repository layout

```
processed/
└─ mode1_v1/
    ├─ 2026-03-23/   #  3 episodes  (2,141 / 1,948 / 2,109 frames)
    ├─ 2026-05-10/   # 12 episodes  ( 763 –  10,476 frames each)
    └─ 2026-05-11/   # 17 episodes  ( 263 –  33,739 frames each)
        ├─ episode_000.pt
        ├─ episode_000.contact.json
        ├─ episode_002.pt              # episode_001 missing (corrupt at recording time)
        └─ ...
```

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

```python
import torch
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="yxma/React",
    repo_type="dataset",
    filename="processed/mode1_v1/2026-05-11/episode_000.pt",
)
ep = torch.load(path, weights_only=False)
print(ep["view"].shape, ep["tactile_left_intensity"].shape)
# torch.Size([263, 3, 128, 128]) torch.Size([263])
```

To 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_v1/2026-05-11/episode_000.contact.json",
)
meta = json.load(open(path))
print(meta["drift_left"], meta["drift_right"], meta["drift_warning"])
```

## Known caveats

- **Missing episode**: `2026-05-11/episode_001` was lost at recording time (HDF5 superblock never finalized when the writer was killed mid-write). It is intentionally absent.
- **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

A **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).