Datasets:
l-lt
/

ArXiv:
l-lt commited on
Commit
a974646
1 Parent(s): 78613ba

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +9 -8
README.md CHANGED
@@ -17,7 +17,7 @@ paperswithcode_id: lasot
17
 
18
  **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.
19
 
20
- This repositoy contains the conference version of LaSOT, published on CVPR-19 ([LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking](https://arxiv.org/abs/1809.07845)).
21
 
22
  **LaSOT** is featured in:
23
 
@@ -32,21 +32,22 @@ For the new subset (15 categories with 150 videos) in [extended journal version]
32
 
33
  ## Download
34
 
35
- You can download the whole dataset using Git (with Git LFS):
36
 
37
- ```bash
38
- git clone https://huggingface.co/datasets/l-lt/LaSOT
 
39
  ```
40
 
41
  Alternatively, download the videos of a specific category manually from this [page](https://huggingface.co/datasets/l-lt/LaSOT/tree/main).
42
 
43
- LaSOT is also distributed through serval cloud storage services:
44
 
45
- * In one zip file: [OneDrive](https://1drv.ms/u/s!Akt_zO4y_u6DgoQsxl9ixr5Y393qWA?e=7yTwjc)
46
 
47
- * One zip file per category: [OneDrive](https://1drv.ms/f/s!Akt_zO4y_u6DgoNSoMJrfnVwveDjhA?e=PBeyuD) or [Baidu Pan](https://pan.baidu.com/s/1xFANiqkBHytE7stMOLUpLQ)
48
 
49
- ### Unzip
50
 
51
  Unzip all zip files and the paths should be organized as following:
52
  ```
 
17
 
18
  **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.
19
 
20
+ This repository contains the conference version of LaSOT, published in CVPR-19 ([LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking](https://arxiv.org/abs/1809.07845)).
21
 
22
  **LaSOT** is featured in:
23
 
 
32
 
33
  ## Download
34
 
35
+ You can download the whole dataset via the ```huggingface_hub``` library ([guide](https://huggingface.co/docs/huggingface_hub/guides/download)):
36
 
37
+ ```python
38
+ from huggingface_hub import snapshot_download
39
+ snapshot_download(repo_id='l-lt/LaSOT', repo_type='dataset', local_dir='/path/to/download')
40
  ```
41
 
42
  Alternatively, download the videos of a specific category manually from this [page](https://huggingface.co/datasets/l-lt/LaSOT/tree/main).
43
 
44
+ LaSOT is also distributed through several cloud storage services (currently only OneDrive):
45
 
46
+ * As a single zip file: [OneDrive](https://1drv.ms/u/s!Akt_zO4y_u6DgoQsxl9ixr5Y393qWA?e=7yTwjc)
47
 
48
+ * As one zip file per category: [OneDrive](https://1drv.ms/f/s!Akt_zO4y_u6DgoNSoMJrfnVwveDjhA?e=PBeyuD) or [Baidu Pan](https://pan.baidu.com/s/1xFANiqkBHytE7stMOLUpLQ)
49
 
50
+ ### Setup
51
 
52
  Unzip all zip files and the paths should be organized as following:
53
  ```