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Browser-based 3D perception explorer for Waymo, nuScenes, and Argoverse 2

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<h1 align="center">EgoLens</h1>

Visualize point clouds, cameras, and 3D annotations in your browser 
 — straight from the most widely used autonomous driving datasets. 
 No conversion, no preprocessing.

<a href="https://egolens.org">Live Demo</a> ·
 <a href="#url-loading">URL Loading</a> ·
 <a href="#share-view">Share View</a> ·
 <a href="#dev-setup">Dev Setup</a>

<img src="assets/hero.png" alt="EgoLens screenshot" width="720" />

Waymo Open Dataset — 3D segmentation, keypoints, and camera views. Timeline markers indicate frames with annotations (cyan = LiDAR seg, lime = 3D keypoints, light-cyan = 2D keypoints, magenta = camera seg).

## What It Does

One tool for the three most widely used AV datasets. Drop a folder or paste a URL — auto-detected, zero setup.

- **LiDAR point clouds** with multiple colormap modes (intensity, height, range, segmentation, camera projection)
- **3D bounding boxes** as wireframes or 3D models with color-coded tracking
- **Synchronized camera views** with POV switching — click a camera to jump into its viewpoint
- **Trajectory trails** showing object movement over past frames
- **Semantic segmentation** overlays (LiDAR and camera)
- **Timeline** with play/pause, frame scrubber, and buffer progress bars

<table>
 <tr>
 <td><img src="assets/nuscenes_seg_lidarcam.gif" alt="nuScenes 32-class LiDAR segmentation with camera projection" /></td>
 <td><img src="assets/argoverse_cam_pov.gif" alt="Argoverse 2 camera colormap and POV switching" /></td>
 </tr>
 <tr>
 <td>nuScenes — 32-class LiDAR segmentation projected onto camera views via LiDAR overlay</td>
 <td>Argoverse 2 — camera colormap mode with 7-camera POV switching</td>
 </tr>
</table>

## Supported Datasets

| Feature | Waymo v2 | nuScenes | Argoverse 2 |
|---------|:--------:|:--------:|:-----------:|
| LiDAR point cloud | ✓ (5 sensors) | ✓ (1 sensor + 5 radar) | ✓ (2 sensors) |
| Camera images | ✓ (5 cams) | ✓ (6 cams) | ✓ (7 cams) |
| 3D bounding boxes | ✓ | ✓ | ✓ |
| 2D camera boxes | ✓ | — | — |
| Cross-modal hover linking | ✓ | — | — |
| Trajectory trails | ✓ | ✓ | ✓ |
| 3D human keypoints | ✓ | — | — |
| 2D camera keypoints | ✓ | — | — |
| LiDAR segmentation | ✓ (23-class) | ✓ (32-class) | — |
| Camera panoptic seg | ✓ (29-class) | — | — |
| POV camera switching | ✓ | ✓ | ✓ |
| Local (drag & drop) | ✓ | ✓ | ✓ |
| URL loading | ✓ | ✓ | ✓ |

Dataset format is auto-detected from folder structure.

## Quick Start

### Local files (drag & drop)

1. Open the [live demo](https://egolens.org)
2. Drag & drop your dataset folder into the browser
3. Done — browse frames, toggle sensors, play the timeline

### URL Loading

Load data directly from S3 or any static file server by providing a URL.

**Two modes:**

- **URL only** — auto-discovers all segments/scenes in the directory
- **URL + Segment ID** — loads a specific segment directly (works with any static file server)

```
https://egolens.org/?dataset=argoverse2&data=https://your-server.com/av2/sensor/val/
https://egolens.org/?dataset=nuscenes&data=https://your-server.com/nuscenes/
https://egolens.org/?dataset=waymo&data=https://your-server.com/waymo_data/&scene=SEGMENT_ID
```

The URL should point to a directory containing the dataset's standard folder structure. Works with S3 buckets, any HTTP server, or localhost.

> **Note:** Waymo's license prohibits data redistribution, so no hosted demo data is available. You'll need to host your own copy after accepting the [Waymo Open Dataset License](https://waymo.com/open/terms/).

### Share View

**Point your team to exactly what you see.** When data is loaded via URL, click Share View to get a link that encodes your exact view — frame, colormap, camera angle, overlays, everything. Paste it in Slack or a PR comment and your teammate lands on the same frame, same angle, same overlays. No screenshots, no "go to frame 142 and turn on segmentation."

<img src="assets/share_view.gif" alt="Share View — copy URL and restore exact camera angle in a new tab" width="720" />

Share what you see — one link captures frame, camera angle, overlays, and all settings.

## Dev Setup

```bash
git clone https://github.com/egolens/egolens.git
cd egolens
npm install
npm run dev
```

```bash
npm run build   # Type-check + production build
npm run lint    # ESLint
npm test        # Vitest
```

## Built With

React 19 · TypeScript · Three.js · React Three Fiber · Vite · Zustand · hyparquet · Web Workers

## Browser Support

**Chrome / Edge recommended.** Safari may crash on large datasets due to WebKit memory limits. Firefox works but lacks the folder picker API.

## Feedback

Found a bug? Have a feature idea? Want support for another dataset? [Open an issue](https://github.com/egolens/egolens/issues) — all feedback is welcome.

See [CONTRIBUTING.md](CONTRIBUTING.md) for development guidelines · [Changelog](CHANGELOG.md)

## Citation

If you use EgoLens in your research, please cite it via its Zenodo DOI:

```bibtex
@software{kim_egolens_2026,
  author    = {Kim, Heejae},
  title     = {{EgoLens: A browser-based viewer for autonomous-driving datasets}},
  year      = {2026},
  publisher = {Zenodo},
  version   = {1.0.0},
  doi       = {10.5281/zenodo.20460188},
  url       = {https://github.com/egolens/egolens}
}
```

Or use the **Cite this repository** button at the top of the GitHub page (powered by [`CITATION.cff`](CITATION.cff)).

## License

[MIT](LICENSE) · Built by [Heejae Kim](https://github.com/happyhj)

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