[Doc] update opendatalab download link (add postfix) (#9738)

open-mmlab · Feb 8, 2023 · 78030a6 · 78030a6
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diff --git a/docs/en/user_guides/dataset_prepare.md b/docs/en/user_guides/dataset_prepare.md
@@ -7,7 +7,7 @@ It is recommended to download and extract the dataset somewhere outside the proj
 If your folder structure is different, you may need to change the corresponding paths in config files.
 
 We provide a script to download datasets such as COCO, you can run `python tools/misc/download_dataset.py --dataset-name coco2017` to download COCO dataset.
-For users in China, more datasets can be downloaded from the opensource dataset platform: [OpenDataLab](https://opendatalab.com/).
+For users in China, more datasets can be downloaded from the opensource dataset platform: [OpenDataLab](https://opendatalab.com/?source=OpenMMLab%20GitHub).
 
 For more usage please refer to [dataset-download](./useful_tools.md#dataset-download)
 

diff --git a/docs/en/user_guides/useful_tools.md b/docs/en/user_guides/useful_tools.md
@@ -389,12 +389,12 @@ python tools/misc/download_dataset.py --dataset-name voc2007
 python tools/misc/download_dataset.py --dataset-name lvis
 ```
 
-For users in China, these datasets can also be downloaded from [OpenDataLab](https://opendatalab.com/) with high speed:
+For users in China, these datasets can also be downloaded from [OpenDataLab](https://opendatalab.com/?source=OpenMMLab%20GitHub) with high speed:
 
-- [COCO2017](https://opendatalab.com/COCO_2017/download)
-- [VOC2007](https://opendatalab.com/PASCAL_VOC2007/download)
-- [VOC2012](https://opendatalab.com/PASCAL_VOC2012/download)
-- [LVIS](https://opendatalab.com/LVIS/download)
+- [COCO2017](https://opendatalab.com/COCO_2017/download?source=OpenMMLab%20GitHub)
+- [VOC2007](https://opendatalab.com/PASCAL_VOC2007/download?source=OpenMMLab%20GitHub)
+- [VOC2012](https://opendatalab.com/PASCAL_VOC2012/download?source=OpenMMLab%20GitHub)
+- [LVIS](https://opendatalab.com/LVIS/download?source=OpenMMLab%20GitHub)
 
 ## Benchmark
 

diff --git a/docs/zh_cn/user_guides/dataset_prepare.md b/docs/zh_cn/user_guides/dataset_prepare.md
@@ -9,7 +9,7 @@
 我们建议将数据集下载，然后解压到项目外部的某个文件夹内，然后通过符号链接的方式，将数据集根目录链接到 `$MMDETECTION/data` 文件夹下，格式如下所示。
 如果你的文件夹结构和下方不同的话，你需要在配置文件中改变对应的路径。
 我们提供了下载 COCO 等数据集的脚本，你可以运行 `python tools/misc/download_dataset.py --dataset-name coco2017` 下载 COCO 数据集。
-对于中国境内的用户，我们也推荐通过开源数据平台 [OpenDataLab](https://opendatalab.com/) 来下载数据，以获得更好的下载体验。
+对于中国境内的用户，我们也推荐通过开源数据平台 [OpenDataLab](https://opendatalab.com/?source=OpenMMLab%20GitHub) 来下载数据，以获得更好的下载体验。
 
 ```plain
 mmdetection

diff --git a/docs/zh_cn/user_guides/useful_tools.md b/docs/zh_cn/user_guides/useful_tools.md
@@ -370,12 +370,12 @@ python tools/misc/download_dataset.py --dataset-name voc2007
 python tools/misc/download_dataset.py --dataset-name lvis
 ```
 
-对于中国境内的用户，我们也推荐使用开源数据平台 [OpenDataLab](https://opendatalab.com/) 来获取这些数据集，以获得更好的下载体验:
+对于中国境内的用户，我们也推荐使用开源数据平台 [OpenDataLab](https://opendatalab.com/?source=OpenMMLab%20GitHub) 来获取这些数据集，以获得更好的下载体验:
 
-- [COCO2017](https://opendatalab.com/COCO_2017/download)
-- [VOC2007](https://opendatalab.com/PASCAL_VOC2007/download)
-- [VOC2012](https://opendatalab.com/PASCAL_VOC2012/download)
-- [LVIS](https://opendatalab.com/LVIS/download)
+- [COCO2017](https://opendatalab.com/COCO_2017/download?source=OpenMMLab%20GitHub)
+- [VOC2007](https://opendatalab.com/PASCAL_VOC2007/download?source=OpenMMLab%20GitHub)
+- [VOC2012](https://opendatalab.com/PASCAL_VOC2012/download?source=OpenMMLab%20GitHub)
+- [LVIS](https://opendatalab.com/LVIS/download?source=OpenMMLab%20GitHub)
 
 ## 基准测试