[Doc] add opendatalab download link

Author: wufan-tb

docs/en/user_guides/dataset_prepare.md

@@ -7,6 +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 more usage please refer to [dataset-download](./useful_tools.md#dataset-download)
 

docs/en/user_guides/useful_tools.md

@@ -389,6 +389,13 @@ 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:
+
+- [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)
+
 ## Benchmark
 
 ### Robust Detection Benchmark

docs/zh_cn/user_guides/dataset_prepare.md

@@ -9,6 +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.
 
 ```plain
 mmdetection

docs/zh_cn/user_guides/useful_tools.md

@@ -370,6 +370,13 @@ python tools/misc/download_dataset.py --dataset-name voc2007
 python tools/misc/download_dataset.py --dataset-name lvis
 ```
 
+对于国内用户，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, 通常可以获得更好地下载体验:
+
+- [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)
+
 ## 基准测试
 
 ### 鲁棒性测试基准