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---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
viewer: false
---

# Dataset Card for LaSOT-ext

## Dataset Description

- **Homepage:** [LaSOT homepage](http://vision.cs.stonybrook.edu/~lasot/)
- **Paper:** [LaSOT: A High-quality Large-scale Single Object Tracking Benchmark](https://arxiv.org/abs/2009.03465)
- **Point of Contact:** [Heng Fan](heng.fan@unt.edu)

### Dataset Summary

**La**rge-scale **S**ingle **O**bject **T**racking (**LaSOT**) aims to provide a dedicated platform for training data-hungry deep trackers as well as assessing long-term tracking performance.

This repository contains the new subset introduced in the journal version of LaSOT (commonly called **LaSOT<sub>ext</sub>**), published in IJCV ([LaSOT: A High-quality Large-scale Single Object Tracking Benchmark](https://arxiv.org/abs/2009.03465)).

For the training/testing splits of LaSOT (conference version), please refer to this [repo](https://huggingface.co/datasets/l-lt/LaSOT).

## Download

You can download the whole dataset via the ```huggingface_hub``` library ([guide](https://huggingface.co/docs/huggingface_hub/guides/download)):

```python
from huggingface_hub import snapshot_download
snapshot_download(repo_id='l-lt/LaSOT-ext', repo_type='dataset', local_dir='/path/to/download')
```

Alternatively, download the videos of a specific category manually from this [page](https://huggingface.co/datasets/l-lt/LaSOT-ext/tree/main).

LaSOT<sub>ext</sub> can also be downloaded from:

* As a single zip file: [OneDrive](https://1drv.ms/u/s!Akt_zO4y_u6DgoQrvo5h48AC15l67A?e=Zo6PWx) or [Homepage server](http://vision.cs.stonybrook.edu/~lasot/data/LaSOT_extension_subset.zip)

* As one zip file per category: [OneDrive](https://1drv.ms/f/s!Akt_zO4y_u6DgoQZH_aGsNh2f6x6Dg?e=sldyAx)

### Setup

Unzip all zip files and organize the paths as follows:
```
├── atv
│   ├── atv-1
│   ...
├── badminton
...
```

## Evaluation Metrics and Toolkit

See the [homepage](http://vision.cs.stonybrook.edu/~lasot/results.html) for more information.