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diff --git a/.github/CODE_OF_CONDUCT.md b/.github/CODE_OF_CONDUCT.md
@@ -14,22 +14,22 @@ appearance, race, religion, or sexual identity and orientation.
 Examples of behavior that contributes to creating a positive environment
 include:
 
-* Using welcoming and inclusive language
-* Being respectful of differing viewpoints and experiences
-* Gracefully accepting constructive criticism
-* Focusing on what is best for the community
-* Showing empathy towards other community members
+- Using welcoming and inclusive language
+- Being respectful of differing viewpoints and experiences
+- Gracefully accepting constructive criticism
+- Focusing on what is best for the community
+- Showing empathy towards other community members
 
 Examples of unacceptable behavior by participants include:
 
-* The use of sexualized language or imagery and unwelcome sexual attention or
- advances
-* Trolling, insulting/derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or electronic
- address, without explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
- professional setting
+- The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
+- Trolling, insulting/derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information, such as a physical or electronic
+  address, without explicit permission
+- Other conduct which could reasonably be considered inappropriate in a
+  professional setting
 
 ## Our Responsibilities
 
@@ -70,7 +70,7 @@ members of the project's leadership.
 This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
 available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
 
-[homepage]: https://www.contributor-covenant.org
-
 For answers to common questions about this code of conduct, see
 https://www.contributor-covenant.org/faq
+
+[homepage]: https://www.contributor-covenant.org
diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
@@ -18,11 +18,11 @@ Contents
       - [Step 3: Commit your changes](#step-3-commit-your-changes)
       - [Step 4: Prepare to Pull Request](#step-4-prepare-to-pull-request)
         - [Step 4.1: Merge official repo updates to your fork](#step-41-merge-official-repo-updates-to-your-fork)
-        - [Step 4.2: Push <your_feature_branch> branch to your remote forked repo,](#step-42-push-your_feature_branch-branch-to-your-remote-forked-repo)
+        - [Step 4.2: Push \<your_feature_branch> branch to your remote forked repo,](#step-42-push-your_feature_branch-branch-to-your-remote-forked-repo)
         - [Step 4.3: Create a Pull Request](#step-43-create-a-pull-request)
         - [Step 4.4: Review code](#step-44-review-code)
-        - [Step 4.5: Revise <your_feature_branch>  (optional)](#step-45-revise-your_feature_branch--optional)
-        - [Step 4.6: Delete <your_feature_branch> branch if your PR is accepted.](#step-46-delete-your_feature_branch-branch-if-your-pr-is-accepted)
+        - [Step 4.5: Revise \<your_feature_branch>  (optional)](#step-45-revise-your_feature_branch--optional)
+        - [Step 4.6: Delete \<your_feature_branch> branch if your PR is accepted.](#step-46-delete-your_feature_branch-branch-if-your-pr-is-accepted)
   - [Code style](#code-style)
     - [Python](#python)
       - [Installing pre-commit hooks](#installing-pre-commit-hooks)
@@ -31,6 +31,7 @@ Contents
     - [C++ and CUDA](#c-and-cuda)
 
 ## Workflow
+
 ### Main Steps
 
 1. Fork and pull the latest MMOCR
@@ -59,10 +60,13 @@ All new developers to **MMOCR** need to follow the following steps:
 1. Fork the repo on GitHub or GitLab to your personal account. Click the `Fork` button on the [project page](https://github.com/open-mmlab/mmocr).
 
 2. Clone your new forked repo to your computer.
+
 ```
 git clone https://github.com/<your name>/mmocr.git
 ```
+
 3. Add the official repo as an upstream:
+
 ```
 git remote add upstream https://github.com/open-mmlab/mmocr.git
 ```
@@ -84,11 +88,12 @@ git push origin main
 ```
 
 ##### Step 2.2: Create a feature branch
+
 - Create an issue on [github](https://github.com/open-mmlab/mmocr)
 
 - Create a feature branch
--
-  ```bash
+
+- ```bash
   git checkout -b feature/iss_<index> main
   # index is the issue index on github above
   ```
@@ -118,7 +123,6 @@ git commit -m "fix #<issue_index>: <commit_message>"
 
 - Make sure to link your pull request to the related issue. Please refer to the [instructon](https://docs.github.com/en/github/managing-your-work-on-github/linking-a-pull-request-to-an-issue)
 
-
 ##### Step 4.1: Merge official repo updates to your fork
 
 ```
@@ -136,30 +140,34 @@ git rebase main
 # solve conflicts if any and Test
 ```
 
-##### Step 4.2: Push <your_feature_branch> branch to your remote forked repo,
+##### Step 4.2: Push \<your_feature_branch> branch to your remote forked repo,
+
 ```
 git checkout <your_feature_branch>
 git push origin <your_feature_branch>
 ```
+
 ##### Step 4.3: Create a Pull Request
 
 Go to the page for your fork on GitHub, select your new feature branch, and click the pull request button to integrate your feature branch into the upstream remote’s develop branch.
 
 ##### Step 4.4: Review code
 
+##### Step 4.5: Revise \<your_feature_branch>  (optional)
 
-##### Step 4.5: Revise <your_feature_branch>  (optional)
 If PR is not accepted, pls follow steps above till your PR is accepted.
 
-##### Step 4.6: Delete <your_feature_branch> branch if your PR is accepted.
+##### Step 4.6: Delete \<your_feature_branch> branch if your PR is accepted.
+
 ```
 git branch -d <your_feature_branch>
 git push origin :<your_feature_branch>
 ```
 
-
 ## Code style
+
 ### Python
+
 We adopt [PEP8](https://www.python.org/dev/peps/pep-0008/) as the preferred code style.
 
 We use the following tools for linting and formatting:
@@ -171,7 +179,7 @@ We use the following tools for linting and formatting:
 Style configurations of yapf and isort can be found in [setup.cfg](../setup.cfg).
 
 We use [pre-commit hook](https://pre-commit.com/) that checks and formats for `flake8`, `yapf`, `isort`, `trailing whitespaces`,
- fixes `end-of-files`, sorts `requirments.txt` automatically on every commit.
+fixes `end-of-files`, sorts `requirments.txt` automatically on every commit.
 The config for a pre-commit hook is stored in [.pre-commit-config](../.pre-commit-config.yaml).
 
 #### Installing pre-commit hooks
@@ -209,7 +217,6 @@ After you clone the repository, you will need to install and initialize pre-comm
 pip install -U pre-commit
 ```
 
-
 From the repository folder
 
 ```shell
@@ -218,7 +225,8 @@ pre-commit install
 
 After this on every commit check code linters and formatter will be enforced.
 
->Before you create a PR, make sure that your code lints and is formatted by yapf.
+> Before you create a PR, make sure that your code lints and is formatted by yapf.
 
 ### C++ and CUDA
+
 We follow the [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).
diff --git a/.github/ISSUE_TEMPLATE/error-report.md b/.github/ISSUE_TEMPLATE/error-report.md
@@ -4,7 +4,6 @@ about: Create a report to help us improve
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 Thanks for your error report and we appreciate it a lot.
@@ -32,8 +31,8 @@ A placeholder for the command.
 
 1. Please run `python mmocr/utils/collect_env.py` to collect necessary environment information and paste it here.
 2. You may add addition that may be helpful for locating the problem, such as
-    - How you installed PyTorch [e.g., pip, conda, source]
-    - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
+   - How you installed PyTorch \[e.g., pip, conda, source\]
+   - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
 
 **Error traceback**
 If applicable, paste the error traceback here.

diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -4,15 +4,14 @@ about: Suggest an idea for this project
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 **Describe the feature**
 
 **Motivation**
 A clear and concise description of the motivation of the feature.
-Ex1. It is inconvenient when [....].
-Ex2. There is a recent paper [....], which is very helpful for [....].
+Ex1. It is inconvenient when \[....\].
+Ex2. There is a recent paper \[....\], which is very helpful for \[....\].
 
 **Related resources**
 If there is an official code release or third-party implementations, please also provide the information here, which would be very helpful.

diff --git a/.github/ISSUE_TEMPLATE/general_questions.md b/.github/ISSUE_TEMPLATE/general_questions.md
@@ -4,5 +4,4 @@ about: Ask general questions to get help
 title: ''
 labels: ''
 assignees: ''
-
 ---
diff --git a/.github/ISSUE_TEMPLATE/reimplementation_questions.md b/.github/ISSUE_TEMPLATE/reimplementation_questions.md
@@ -2,9 +2,8 @@
 name: Reimplementation Questions
 about: Ask about questions during model reimplementation
 title: ''
-labels: 'reimplementation'
+labels: reimplementation
 assignees: ''
-
 ---
 
 **Notice**
@@ -52,7 +51,7 @@ A placeholder for the config.
 
 1. Please run `python mmocr/utils/collect_env.py` to collect necessary environment information and paste it here.
 2. You may add addition that may be helpful for locating the problem, such as
-   1. How you installed PyTorch [e.g., pip, conda, source]
+   1. How you installed PyTorch \[e.g., pip, conda, source\]
    2. Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
 
 **Results**

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -12,6 +12,17 @@ repos:
     rev: v0.30.0
     hooks:
       - id: yapf
+  - repo: https://github.com/executablebooks/mdformat
+    rev: 0.7.14
+    hooks:
+      - id: mdformat
+        args: ["--number"]
+        additional_dependencies:
+          - git+https://github.com/mzr1996/mdformat-tables.git#egg=mdformat-tables
+          - mdformat-gfm
+          - mdformat_frontmatter
+          - linkify-it-py
+          - mdformat-myst
   - repo: https://github.com/codespell-project/codespell
     rev: v2.1.0
     hooks:

diff --git a/README.md b/README.md
@@ -45,7 +45,7 @@ Documentation: https://mmocr.readthedocs.io/en/latest/.
 
 - **Comprehensive Pipeline**
 
-   The toolbox supports not only text detection and text recognition, but also their downstream tasks such as key information extraction.
+  The toolbox supports not only text detection and text recognition, but also their downstream tasks such as key information extraction.
 
 - **Multiple Models**
 

diff --git a/README_zh-CN.md b/README_zh-CN.md
@@ -45,20 +45,21 @@ MMOCR 是基于 PyTorch 和 mmdetection 的开源工具箱，专注于文本检
 
 -**全流程**
 
-   该工具箱不仅支持文本检测和文本识别，还支持其下游任务，例如关键信息提取。
+该工具箱不仅支持文本检测和文本识别，还支持其下游任务，例如关键信息提取。
 
 -**多种模型**
 
-  该工具箱支持用于文本检测，文本识别和关键信息提取的各种最新模型。
+该工具箱支持用于文本检测，文本识别和关键信息提取的各种最新模型。
 
 -**模块化设计**
 
-  MMOCR 的模块化设计使用户可以定义自己的优化器，数据预处理器，模型组件如主干模块，颈部模块和头部模块，以及损失函数。有关如何构建自定义模型的信
+MMOCR 的模块化设计使用户可以定义自己的优化器，数据预处理器，模型组件如主干模块，颈部模块和头部模块，以及损失函数。有关如何构建自定义模型的信
 息，请参考[快速入门](https://mmocr.readthedocs.io/zh_CN/latest/getting_started.html)。
 
 -**众多实用工具**
 
-  该工具箱提供了一套全面的实用程序，可以帮助用户评估模型的性能。它包括可对图像，标注的真值以及预测结果进行可视化的可视化工具，以及用于在训练过程中评估模型的验证工具。它还包括数据转换器，演示了如何将用户自建的标注数据转换为 MMOCR 支持的标注文件。
+该工具箱提供了一套全面的实用程序，可以帮助用户评估模型的性能。它包括可对图像，标注的真值以及预测结果进行可视化的可视化工具，以及用于在训练过程中评估模型的验证工具。它还包括数据转换器，演示了如何将用户自建的标注数据转换为 MMOCR 支持的标注文件。
+
 ## [模型库](https://mmocr.readthedocs.io/en/latest/modelzoo.html)
 
 支持的算法：
@@ -152,11 +153,11 @@ pip3 install -e .
 我们感谢所有的贡献者为改进和提升 MMOCR 所作出的努力。请参考[贡献指南](.github/CONTRIBUTING.md)来了解参与项目贡献的相关指引。
 
 ## 致谢
+
 MMOCR 是一款由来自不同高校和企业的研发人员共同参与贡献的开源项目。我们感谢所有为项目提供算法复现和新功能支持的贡献者，以及提供宝贵反馈的用户。 我们希望此工具箱可以帮助大家来复现已有的方法和开发新的方法，从而为研究社区贡献力量。
 
 ## OpenMMLab 的其他项目
 
-
 - [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab 计算机视觉基础库
 - [MIM](https://github.com/open-mmlab/mim): MIM 是 OpenMMlab 项目、算法、模型的统一入口
 - [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab 图像分类工具箱

diff --git a/configs/kie/sdmgr/README.md b/configs/kie/sdmgr/README.md
@@ -1,5 +1,6 @@
 # SDMGR
->[Spatial Dual-Modality Graph Reasoning for Key Information Extraction](https://arxiv.org/abs/2103.14470)
+
+> [Spatial Dual-Modality Graph Reasoning for Key Information Extraction](https://arxiv.org/abs/2103.14470)
 
 <!-- [ALGORITHM] -->
 
@@ -15,28 +16,29 @@ Key information extraction from document images is of paramount importance in of
 
 ### WildReceipt
 
-|                                 Method                                 |     Modality     | Macro F1-Score |                                                                                            Download                                                                                            |
-| :--------------------------------------------------------------------: | :--------------: | :------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
-|   [sdmgr_unet16](/configs/kie/sdmgr/sdmgr_unet16_60e_wildreceipt.py)   | Visual + Textual |     0.888      |  [model](https://download.openmmlab.com/mmocr/kie/sdmgr/sdmgr_unet16_60e_wildreceipt_20210520-7489e6de.pth) \| [log](https://download.openmmlab.com/mmocr/kie/sdmgr/20210520_132236.log.json)  |
+|                                 Method                                 |     Modality     | Macro F1-Score |                                               Download                                               |
+| :--------------------------------------------------------------------: | :--------------: | :------------: | :--------------------------------------------------------------------------------------------------: |
+|   [sdmgr_unet16](/configs/kie/sdmgr/sdmgr_unet16_60e_wildreceipt.py)   | Visual + Textual |     0.888      | [model](https://download.openmmlab.com/mmocr/kie/sdmgr/sdmgr_unet16_60e_wildreceipt_20210520-7489e6de.pth) \| [log](https://download.openmmlab.com/mmocr/kie/sdmgr/20210520_132236.log.json) |
 | [sdmgr_novisual](/configs/kie/sdmgr/sdmgr_novisual_60e_wildreceipt.py) |     Textual      |     0.870      | [model](https://download.openmmlab.com/mmocr/kie/sdmgr/sdmgr_novisual_60e_wildreceipt_20210517-a44850da.pth) \| [log](https://download.openmmlab.com/mmocr/kie/sdmgr/20210517_205829.log.json) |
 
-:::{note}
+:::\{note}
+
 1. For `sdmgr_novisual`, images are not needed for training and testing. So fake `img_prefix` can be used in configs. As well, fake `file_name` can be used in annotation files.
-:::
+   :::
 
 ### WildReceiptOpenset
 
-|                                     Method                                     | Modality | Edge F1-Score | Node Macro F1-Score | Node Micro F1-Score |                                                                                                Download                                                                                                |
-| :----------------------------------------------------------------------------: | :------: | :-----------: | :-----------------: | :-----------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+|                                Method                                 | Modality | Edge F1-Score | Node Macro F1-Score | Node Micro F1-Score |                                 Download                                 |
+| :-------------------------------------------------------------------: | :------: | :-----------: | :-----------------: | :-----------------: | :----------------------------------------------------------------------: |
 | [sdmgr_novisual](/configs/kie/sdmgr/sdmgr_novisual_60e_wildreceipt_openset.py) | Textual  |     0.786     |        0.926        |        0.935        | [model](https://download.openmmlab.com/mmocr/kie/sdmgr/sdmgr_novisual_60e_wildreceipt_openset_20210917-d236b3ea.pth) \| [log](https://download.openmmlab.com/mmocr/kie/sdmgr/20210917_050824.log.json) |
 
+:::\{note}
 
-:::{note}
 1. In the case of openset, the number of node categories is unknown or unfixed, and more node category can be added.
 2. To show that our method can handle openset problem, we modify the ground truth of `WildReceipt` to `WildReceiptOpenset`. The `nodes` are just classified into 4 classes: `background, key, value, others`, while adding `edge` labels for each box.
 3. The model is used to predict whether two nodes are a pair connecting by a valid edge.
 4. You can learn more about the key differences between CloseSet and OpenSet annotations in our [tutorial](tutorials/kie_closeset_openset.md).
-:::
+   :::
 
 ## Citation