[Doc] update doc link (open-mmlab#2863)

README.md

@@ -20,14 +20,14 @@
 
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mmsegmentation)](https://pypi.org/project/mmsegmentation/)
 [![PyPI](https://img.shields.io/pypi/v/mmsegmentation)](https://pypi.org/project/mmsegmentation)
-[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/en/main/)
+[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/en/latest/)
 [![badge](https://github.com/open-mmlab/mmsegmentation/workflows/build/badge.svg)](https://github.com/open-mmlab/mmsegmentation/actions)
 [![codecov](https://codecov.io/gh/open-mmlab/mmsegmentation/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmsegmentation)
 [![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/main/LICENSE)
 [![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
 [![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
 
-Documentation: <https://mmsegmentation.readthedocs.io/en/main/>
+Documentation: <https://mmsegmentation.readthedocs.io/en/latest/>
 
 English | [简体中文](README_zh-CN.md)
 
@@ -64,7 +64,7 @@ The [main](https://github.com/open-mmlab/mmsegmentation/tree/main) branch works
 
 We are thrilled to announce the official release of MMSegmentation's latest version! For this new release, the [main](https://github.com/open-mmlab/mmsegmentation/tree/main) branch serves as the primary branch, while the development branch is [dev-1.x](https://github.com/open-mmlab/mmsegmentation/tree/dev-1.x). The stable branch for the previous release remains as the [0.x](https://github.com/open-mmlab/mmsegmentation/tree/0.x) branch. Please note that the [master](https://github.com/open-mmlab/mmsegmentation/tree/master) branch will only be maintained for a limited time before being removed. We encourage you to be mindful of branch selection and updates during use. Thank you for your unwavering support and enthusiasm, and let's work together to make MMSegmentation even more robust and powerful! 💪
 
-MMSegmentation v1.x brings remarkable improvements over the 0.x release, offering a more flexible and feature-packed experience. To utilize the new features in v1.x, we kindly invite you to consult our detailed [📚 migration guide](https://mmsegmentation.readthedocs.io/en/main/migration/interface.html), which will help you seamlessly transition your projects. Your support is invaluable, and we eagerly await your feedback!
+MMSegmentation v1.x brings remarkable improvements over the 0.x release, offering a more flexible and feature-packed experience. To utilize the new features in v1.x, we kindly invite you to consult our detailed [📚 migration guide](https://mmsegmentation.readthedocs.io/en/latest/migration/interface.html), which will help you seamlessly transition your projects. Your support is invaluable, and we eagerly await your feedback!
 
 ![demo image](resources/seg_demo.gif)
 
@@ -103,8 +103,8 @@ Please refer to [get_started.md](docs/en/get_started.md#installation) for instal
 
 Please see [Overview](docs/en/overview.md) for the general introduction of MMSegmentation.
 
-Please see [user guides](https://mmsegmentation.readthedocs.io/en/main/user_guides/index.html#) for the basic usage of MMSegmentation.
-There are also [advanced tutorials](https://mmsegmentation.readthedocs.io/en/main/advanced_guides/index.html) for in-depth understanding of mmseg design and implementation .
+Please see [user guides](https://mmsegmentation.readthedocs.io/en/latest/user_guides/index.html#) for the basic usage of MMSegmentation.
+There are also [advanced tutorials](https://mmsegmentation.readthedocs.io/en/latest/advanced_guides/index.html) for in-depth understanding of mmseg design and implementation .
 
 A Colab tutorial is also provided. You may preview the notebook [here](demo/MMSegmentation_Tutorial.ipynb) or directly [run](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/main/demo/MMSegmentation_Tutorial.ipynb) on Colab.
 

README_zh-CN.md

@@ -20,14 +20,14 @@
 
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mmsegmentation)](https://pypi.org/project/mmsegmentation/)
 [![PyPI](https://img.shields.io/pypi/v/mmsegmentation)](https://pypi.org/project/mmsegmentation)
-[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/zh_CN/main/)
+[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmsegmentation.readthedocs.io/zh_CN/latest/)
 [![badge](https://github.com/open-mmlab/mmsegmentation/workflows/build/badge.svg)](https://github.com/open-mmlab/mmsegmentation/actions)
 [![codecov](https://codecov.io/gh/open-mmlab/mmsegmentation/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmsegmentation)
 [![license](https://img.shields.io/github/license/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/blob/main/LICENSE)
 [![issue resolution](https://isitmaintained.com/badge/resolution/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
 [![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmsegmentation.svg)](https://github.com/open-mmlab/mmsegmentation/issues)
 
-文档: <https://mmsegmentation.readthedocs.io/zh_CN/main>
+文档: <https://mmsegmentation.readthedocs.io/zh_CN/latest>
 
 [English](README.md) | 简体中文
 
@@ -63,7 +63,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
 
 我们非常高兴地宣布 MMSegmentation 最新版本的正式发布！在这个新版本中，主要分支是 [main](https://github.com/open-mmlab/mmsegmentation/tree/main) 分支，开发分支是 [dev-1.x](https://github.com/open-mmlab/mmsegmentation/tree/dev-1.x)。而之前版本的稳定分支保留为 [0.x](https://github.com/open-mmlab/mmsegmentation/tree/0.x) 分支。请注意，[master](https://github.com/open-mmlab/mmsegmentation/tree/master) 分支将只在有限的时间内维护，然后将被删除。我们鼓励您在使用过程中注意分支选择和更新。感谢您一如既往的支持和热情，让我们共同努力，使 MMSegmentation 变得更加健壮和强大！💪
 
-MMSegmentation v1.x 在 0.x 版本的基础上有了显著的提升，提供了更加灵活和功能丰富的体验。为了更好使用 v1.x 中的新功能，我们诚挚邀请您查阅我们详细的 [📚 迁移指南](https://mmsegmentation.readthedocs.io/zh_CN/main/migration/interface.html)，以帮助您无缝地过渡您的项目。您的支持对我们来说非常宝贵，我们热切期待您的反馈！
+MMSegmentation v1.x 在 0.x 版本的基础上有了显著的提升，提供了更加灵活和功能丰富的体验。为了更好使用 v1.x 中的新功能，我们诚挚邀请您查阅我们详细的 [📚 迁移指南](https://mmsegmentation.readthedocs.io/zh_CN/latest/migration/interface.html)，以帮助您无缝地过渡您的项目。您的支持对我们来说非常宝贵，我们热切期待您的反馈！
 
 ![示例图片](resources/seg_demo.gif)
 
@@ -98,7 +98,7 @@ MMSegmentation v1.x 在 0.x 版本的基础上有了显著的提升，提供了
 
 请参考[概述](docs/zh_cn/overview.md)对 MMSegmetation 进行初步了解
 
-请参考[用户指南](https://mmsegmentation.readthedocs.io/zh_CN/main/user_guides/index.html)了解 mmseg 的基本使用，以及[进阶指南](https://mmsegmentation.readthedocs.io/zh_CN/main/advanced_guides/index.html)深入了解 mmseg 设计和代码实现。
+请参考[用户指南](https://mmsegmentation.readthedocs.io/zh_CN/latest/user_guides/index.html)了解 mmseg 的基本使用，以及[进阶指南](https://mmsegmentation.readthedocs.io/zh_CN/latest/advanced_guides/index.html)深入了解 mmseg 设计和代码实现。
 
 同时，我们提供了 Colab 教程。你可以在[这里](demo/MMSegmentation_Tutorial.ipynb)浏览教程，或者直接在 Colab 上[运行](https://colab.research.google.com/github/open-mmlab/mmsegmentation/blob/main/demo/MMSegmentation_Tutorial.ipynb)。
 

docs/en/advanced_guides/datasets.md

@@ -179,7 +179,7 @@ print(dataset[0])
 
 ## BaseSegDataset
 
-As mentioned above, dataset classes have the same functions, we implemented  [`BaseSegDataset`](https://mmsegmentation.readthedocs.io/en/main/api.html?highlight=BaseSegDataset#mmseg.datasets.BaseSegDataset) to reues the common functions.
+As mentioned above, dataset classes have the same functions, we implemented  [`BaseSegDataset`](https://mmsegmentation.readthedocs.io/en/latest/api.html?highlight=BaseSegDataset#mmseg.datasets.BaseSegDataset) to reues the common functions.
 It inherits [`BaseDataset` of MMEngine](https://github.com/open-mmlab/mmengine/blob/main/docs/en/advanced_tutorials/basedataset.md) and follows unified initialization process of OpenMMLab. It supports the highly effective interior storing format, some functions like
 dataset concatenation and repeatedly sampling. In MMSegmentation `BaseSegDataset`, the **method of loading data information** (`load_data_list`) is redefined and adds new `get_label_map` method to **modify dataset classes information**.
 

docs/en/switch_language.md

@@ -1,3 +1,3 @@
-## <a href='https://mmsegmentation.readthedocs.io/en/main/'>English</a>
+## <a href='https://mmsegmentation.readthedocs.io/en/latest/'>English</a>
 
-## <a href='https://mmsegmentation.readthedocs.io/zh_CN/main/'>简体中文</a>
+## <a href='https://mmsegmentation.readthedocs.io/zh_CN/latest/'>简体中文</a>

docs/zh_cn/advanced_guides/datasets.md

@@ -166,7 +166,7 @@ print(dataset[0])
 
 ## BaseSegDataset
 
-由于 MMSegmentation 中的所有数据集的基本功能均包括(1) 加载[数据集预处理](../user_guides/2_dataset_prepare.md) 之后的数据信息和 (2) 将数据送入数据变换流水线中进行数据变换, 因此在 MMSegmentation 中将其中的共同接口抽象成 [`BaseSegDataset`](https://mmsegmentation.readthedocs.io/en/main/api.html?highlight=BaseSegDataset#mmseg.datasets.BaseSegDataset)，它继承自 [MMEngine 的 `BaseDataset`](https://github.com/open-mmlab/mmengine/blob/main/docs/en/advanced_tutorials/basedataset.md), 遵循 OpenMMLab 数据集初始化统一流程, 支持高效的内部数据存储格式, 支持数据集拼接、数据集重复采样等功能.
+由于 MMSegmentation 中的所有数据集的基本功能均包括(1) 加载[数据集预处理](../user_guides/2_dataset_prepare.md) 之后的数据信息和 (2) 将数据送入数据变换流水线中进行数据变换, 因此在 MMSegmentation 中将其中的共同接口抽象成 [`BaseSegDataset`](https://mmsegmentation.readthedocs.io/zh_CN/latest/api.html?highlight=BaseSegDataset#mmseg.datasets.BaseSegDataset)，它继承自 [MMEngine 的 `BaseDataset`](https://github.com/open-mmlab/mmengine/blob/main/docs/en/advanced_tutorials/basedataset.md), 遵循 OpenMMLab 数据集初始化统一流程, 支持高效的内部数据存储格式, 支持数据集拼接、数据集重复采样等功能.
 在 MMSegmentation BaseSegDataset 中重新定义了**数据信息加载方法**（`load_data_list`）和并新增了 `get_label_map` 方法用来**修改数据集的类别信息**.
 
 ### 数据信息加载

projects/faq.md

@@ -1,6 +1,6 @@
 Q1: Why set up `projects/` folder?
 
-Implementing new models and features into OpenMMLab's algorithm libraries could be troublesome due to the rigorous requirements on code quality, which could hinder the fast iteration of SOTA models and might discourage our members from sharing their latest outcomes here. And that's why we have this `projects/` folder now, where some experimental features, frameworks and models are placed, only needed to satisfy the minimum requirement on the code quality, and can be used as standalone libraries. Users are welcome to use them if they [use MMSegmentation from source](https://mmsegmentation.readthedocs.io/en/main/get_started.html#best-practices).
+Implementing new models and features into OpenMMLab's algorithm libraries could be troublesome due to the rigorous requirements on code quality, which could hinder the fast iteration of SOTA models and might discourage our members from sharing their latest outcomes here. And that's why we have this `projects/` folder now, where some experimental features, frameworks and models are placed, only needed to satisfy the minimum requirement on the code quality, and can be used as standalone libraries. Users are welcome to use them if they [use MMSegmentation from source](https://mmsegmentation.readthedocs.io/en/latest/get_started.html#best-practices).
 
 Q2: Why should there be a checklist for a project?