#### NOTE
This is a **Hugging Face dataset**. For large datasets, ensure `huggingface_hub>=1.1.3` to avoid rate limits. Learn more in the <a href="https://docs.voxel51.com/integrations/huggingface.html#loading-datasets-from-the-hub" target="_blank">Hugging Face integration docs</a>.

<a href="https://huggingface.co/datasets/Voxel51/TartanGround" target="_blank">![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-yellow)</a>

# TartanGround → FiftyOne (Native Multimodal MCAP)

![preview](https://huggingface.co/datasets/Voxel51/TartanGround/resolve/main/preview.gif)

Six trajectories from
[theairlabcmu/TartanGround](https://huggingface.co/datasets/theairlabcmu/TartanGround),
one per environment (AbandonedFactory, CyberPunkDowntown, GreatMarsh,
Hospital, JapaneseCity, NordicHarbor), converted to native multimodal MCAP
episodes. Each episode carries the front camera, its segmentation stream,
per-frame lidar point clouds, ego pose, and IMU plot channels on a 10 Hz
frame clock.

## Installation

```bash
pip install fiftyone
```

## Usage

```python
import fiftyone as fo
import fiftyone.utils.huggingface as fouh

dataset = fouh.load_from_hub(
    "Voxel51/TartanGround",
    name="TartanGround",
    persistent=True,
)
fo.launch_app(dataset)
```

## What you get

- 6 `.mcap` episodes of 757 to 3,727 frames
- Streams per episode: `/front-camera` (JPEG), `/front-segmentation` (PNG),
  `/lidar` (point clouds), `/ego-pose`, `/imu.plot`
- Per-episode fields: `environment`, `trajectory`, `num_frames`, `duration`

## License & attribution

The source dataset is released by the CMU AirLab under
[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/); this subset is
distributed under the same license. Changes from the source: trajectory
subsetting, conversion to MCAP, and JPEG transcoding of the RGB frames.

## Citation

```bibtex
@article{patel2025tartanground,
  title={TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation},
  author={Patel, Manthan and Yang, Fan and Qiu, Yuheng and Cadena, Cesar and Scherer, Sebastian and Hutter, Marco and Wang, Wenshan},
  journal={arXiv preprint arXiv:2505.10696},
  year={2025}
}
```