From 853f0c6bcab6d5d34c5843bd6bf580f5c6be2314 Mon Sep 17 00:00:00 2001 From: Ezra-Yu <18586273+Ezra-Yu@users.noreply.github.com> Date: Tue, 22 Aug 2023 11:29:42 +0800 Subject: [PATCH] [DOC] Update datset download score from opendatalab to openXlab (#1765) * update opendatalab to openXlab * update dataset-index --------- Co-authored-by: fangyixiao18 --- dataset-index.yml | 4 ++-- docs/en/user_guides/dataset_prepare.md | 14 +++++++------- docs/zh_CN/user_guides/dataset_prepare.md | 14 +++++++------- 3 files changed, 16 insertions(+), 16 deletions(-) diff --git a/dataset-index.yml b/dataset-index.yml index ecf7f5b59ca..40ca6206929 100644 --- 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 index 7421be22080..17ec229b866 100644 --- 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 index 59a0d0affbe..aa1e1fdebe5 100644 --- 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