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**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.
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This
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For the training/testing splits of LaSOT (conference version),
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## Download
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You can download the whole dataset
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```
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```
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Alternatively, download the videos of a specific category manually from this [page](https://huggingface.co/datasets/l-lt/LaSOT-ext/tree/main).
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LaSOT<sub>ext</sub> can also be downloaded from:
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*
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*
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###
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Unzip all zip files and organize the paths as follows:
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```
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**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.
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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)).
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For the training/testing splits of LaSOT (conference version), please refer to this [repo](https://huggingface.co/datasets/l-lt/LaSOT).
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## Download
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You can download the whole dataset via the ```huggingface_hub``` library ([guide](https://huggingface.co/docs/huggingface_hub/guides/download)):
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```python
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from huggingface_hub import snapshot_download
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snapshot_download(repo_id='l-lt/LaSOT-ext', repo_type='dataset', local_dir='/path/to/download')
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```
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Alternatively, download the videos of a specific category manually from this [page](https://huggingface.co/datasets/l-lt/LaSOT-ext/tree/main).
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LaSOT<sub>ext</sub> can also be downloaded from:
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* 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)
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* As one zip file per category: [OneDrive](https://1drv.ms/f/s!Akt_zO4y_u6DgoQZH_aGsNh2f6x6Dg?e=sldyAx)
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### Setup
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Unzip all zip files and organize the paths as follows:
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```
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