[DOC] Update datset download score from opendatalab to openXlab (open…

…-mmlab#1765) * update opendatalab to openXlab * update dataset-index --------- Co-authored-by: fangyixiao18 <[email protected]>
ASHORE1225 · Aug 22, 2023 · 853f0c6 · 853f0c6
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diff --git a/dataset-index.yml b/dataset-index.yml
@@ -1,11 +1,11 @@
 imagenet1k:
-  dataset: ImageNet-1K
+  dataset: OpenDataLab/ImageNet-1K
   download_root: data
   data_root: data/imagenet
   script: tools/dataset_converters/odl_imagenet1k_preprocess.sh
 
 cub:
-  dataset: CUB-200-2011
+  dataset: OpenDataLab/CUB-200-2011
   download_root: data
   data_root: data/CUB_200_2011
   script: tools/dataset_converters/odl_cub_preprocess.sh
diff --git a/docs/en/user_guides/dataset_prepare.md b/docs/en/user_guides/dataset_prepare.md
@@ -144,15 +144,15 @@ ImageNet has multiple versions, but the most commonly used one is [ILSVRC 2012](
 
 ````{group-tab} Download by MIM
 
-MIM supports downloading from [OpenDataLab](https://opendatalab.com/) and preprocessing ImageNet dataset with one command line.
+MIM supports downloading from [OpenXlab](https://openxlab.org.cn/datasets) and preprocessing ImageNet dataset with one command line.
 
-_You need to register an account at [OpenDataLab official website](https://opendatalab.com/) and login by CLI._
+_You need to register an account at [OpenXlab official website](https://openxlab.org.cn/datasets) and login by CLI._
 
 ```Bash
-# install OpenDataLab CLI tools
-pip install -U opendatalab
-# log in OpenDataLab, register if you don't have an account.
-odl login
+# install OpenXlab CLI tools
+pip install -U openxlab
+# log in OpenXLab
+openxlab login
 # download and preprocess by MIM, better to execute in $MMPreTrain directory.
 mim download mmpretrain --dataset imagenet1k
 ```
@@ -278,7 +278,7 @@ test_dataloader = val_dataloader
 | [`SUN397`](mmpretrain.datasets.SUN397)(data_root[, split, pipeline, ...])          | ["train", "test"]                   | [SUN397](https://vision.princeton.edu/projects/2010/SUN/) Dataset.                  |
 | [`VOC`](mmpretrain.datasets.VOC)(data_root[, image_set_path, pipeline, ...])       | ["train", "val", "tranval", "test"] | [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/) Dataset.                      |
 
-Some dataset homepage links may be unavailable, and you can download datasets through [OpenDataLab](https://opendatalab.com/), such as [Stanford Cars](https://opendatalab.com/Stanford_Cars/download).
+Some dataset homepage links may be unavailable, and you can download datasets through [OpenXLab](https://openxlab.org.cn/datasets), such as [Stanford Cars](https://openxlab.org.cn/datasets/OpenDataLab/Stanford_Cars).
 
 ## Supported Multi-modality Datasets
 

diff --git a/docs/zh_CN/user_guides/dataset_prepare.md b/docs/zh_CN/user_guides/dataset_prepare.md
@@ -142,15 +142,15 @@ ImageNet 有多个版本，但最常用的一个是 [ILSVRC 2012](http://www.ima
 
 ````{group-tab} MIM 下载
 
-MIM支持使用一条命令行从 [OpenDataLab](https://opendatalab.com/) 下载并预处理 ImageNet 数据集。
+MIM支持使用一条命令行从 [OpenXLab](https://openxlab.org.cn/datasets?lang=zh-CN) 下载并预处理 ImageNet 数据集。
 
-_需要在 [OpenDataLab 官网](https://opendatalab.com/) 注册账号并命令行登录_。
+_需要在 [OpenXLab 官网](https://openxlab.org.cn/datasets?lang=zh-CN) 注册账号并命令行登录_。
 
 ```Bash
-# 安装opendatalab库
-pip install -U opendatalab
-# 登录到 OpenDataLab, 如果还没有注册，请到官网注册一个
-odl login
+# 安装 OpenXLab CLI 工具
+pip install -U openxlab
+# 登录 OpenXLab
+openxlab login
 # 使用 MIM 下载数据集, 最好在 $MMPreTrain 目录执行
 mim download mmpretrain --dataset imagenet1k
 ```
@@ -276,7 +276,7 @@ test_dataloader = val_dataloader
 | [`SUN397`](mmpretrain.datasets.SUN397)(data_root[, split, pipeline, ...])           | ["train", "test"]                   | [SUN397](https://vision.princeton.edu/projects/2010/SUN/) 数据集                   |
 | [`VOC`](mmpretrain.datasets.VOC)(data_root[, image_set_path, pipeline, ...])        | ["train", "val", "tranval", "test"] | [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/) 数据集                       |
 
-有些数据集主页链接可能已经失效，您可以通过[OpenDataLab](https://opendatalab.com/)下载数据集，例如 [Stanford Cars](https://opendatalab.com/Stanford_Cars/download)数据集。
+有些数据集主页链接可能已经失效，您可以通过[OpenXLab](https://openxlab.org.cn/datasets?lang=zh-CN)下载数据集，例如 [Stanford Cars](https://openxlab.org.cn/datasets/OpenDataLab/Stanford_Cars)数据集。
 
 ## OpenMMLab 2.0 标准数据集