[Improvement] Add markdown linter and fix linting errors (open-mmlab#171)

* [Improvement] Add markdown linter and fix linting errors

* fixed pip

Author: xvjiarui

.github/CONTRIBUTING.md

@@ -13,16 +13,19 @@ All kinds of contributions are welcome, including but not limited to the followi
 4. create a PR
 
 Note
+
 - If you plan to add some new features that involve large changes, it is encouraged to open an issue for discussion first.
 - If you are the author of some papers and would like to include your method to mmsegmentation,
-please contact Kai Chen (chenkaidev[at]gmail[dot]com). We will much appreciate your contribution.
+  please contact Kai Chen (chenkaidev[at]gmail[dot]com). We will much appreciate your contribution.
 
 ## 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:
+
 - [flake8](http://flake8.pycqa.org/en/latest/): linter
 - [yapf](https://github.com/google/yapf): formatter
 - [isort](https://github.com/timothycrosley/isort): sort imports
@@ -35,19 +38,20 @@ The config for a pre-commit hook is stored in [.pre-commit-config](../.pre-commi
 
 After you clone the repository, you will need to install initialize pre-commit hook.
 
-```
+```shell
 pip install -U pre-commit
 ```
 
 From the repository folder
-```
+
+```shell
 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.
 
 ### C++ and CUDA
+
 We follow the [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).

.github/ISSUE_TEMPLATE/error-report.md

@@ -10,17 +10,21 @@ assignees: ''
 Thanks for your error report and we appreciate it a lot.
 
 **Checklist**
+
 1. I have searched related issues but cannot get the expected help.
 2. The bug has not been fixed in the latest version.
 
 **Describe the bug**
 A clear and concise description of what the bug is.
 
 **Reproduction**
+
 1. What command or script did you run?
-```
-A placeholder for the command.
-```
+
+    ```none
+    A placeholder for the command.
+    ```
+
 2. Did you make any modifications on the code or config? Did you understand what you have modified?
 3. What dataset did you use?
 
@@ -32,10 +36,13 @@ A placeholder for the command.
     - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
 
 **Error traceback**
+
 If applicable, paste the error trackback here.
-```
+
+```none
 A placeholder for trackback.
 ```
 
 **Bug fix**
+
 If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!

.github/ISSUE_TEMPLATE/feature_request.md

@@ -7,7 +7,7 @@ assignees: ''
 
 ---
 
-**Describe the feature**
+# Describe the feature
 
 **Motivation**
 A clear and concise description of the motivation of the feature.

.github/workflows/build.yml

@@ -11,18 +11,16 @@ jobs:
         uses: actions/setup-python@v1
         with:
           python-version: 3.7
-      - name: Install linting dependencies
+      - name: Install pre-commit hook
         run: |
-          python -m pip install --upgrade pip
-          pip install flake8 isort==4.3.21 yapf interrogate
-      - name: Lint with flake8
-        run: flake8 .
-      - name: Lint with isort
-        run: isort --recursive --check-only --diff mmseg/ tests/ examples/
-      - name: Format python codes with yapf
-        run: yapf -r -d mmseg/ tests/ examples/
+          pip install pre-commit
+          pre-commit install
+      - name: Linting
+        run: pre-commit run --all-files
       - name: Check docstring
-        run: interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --exclude mmseg/ops --ignore-regex "__repr__" --fail-under 80 mmseg
+        run: |
+          pip install interrogate
+          interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --exclude mmseg/ops --ignore-regex "__repr__" --fail-under 80 mmseg
 
   build:
     env:

.pre-commit-config.yaml

@@ -28,6 +28,11 @@ repos:
         args: ["--remove"]
       - id: mixed-line-ending
         args: ["--fix=lf"]
+  - repo: https://github.com/jumanjihouse/pre-commit-hooks
+    rev: 2.1.4
+    hooks:
+      - id: markdownlint
+        args: ["-r", "~MD002,~MD013,~MD029,~MD033,~MD034,~MD036"]
   - repo: https://github.com/myint/docformatter
     rev: v1.3.1
     hooks:

README.md

@@ -54,13 +54,15 @@ Please refer to [changelog.md](docs/changelog.md) for details and release histor
 Results and models are available in the [model zoo](docs/model_zoo.md).
 
 Supported backbones:
+
 - [x] ResNet
 - [x] ResNeXt
 - [x] [HRNet](configs/hrnet/README.md)
 - [x] [ResNeSt](configs/resnest/README.md)
 - [x] [MobileNetV2](configs/mobilenet_v2/README.md)
 
 Supported methods:
+
 - [x] [FCN](configs/fcn)
 - [x] [PSPNet](configs/pspnet)
 - [x] [DeepLabV3](configs/deeplabv3)

configs/ann/README.md

@@ -1,7 +1,8 @@
 # Asymmetric Non-local Neural Networks for Semantic Segmentation
 
 ## Introduction
-```
+
+```latex
 @inproceedings{annn,
   author    = {Zhen Zhu and
                Mengde Xu and
@@ -18,6 +19,7 @@
 ## Results and models
 
 ### Cityscapes
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                        download                                                                                                                                                                                        |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | ANN    | R-50-D8  | 512x1024  |   40000 |        6 |           3.71 | 77.40 |         78.57 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_40k_cityscapes/ann_r50-d8_512x1024_40k_cityscapes_20200605_095211-049fc292.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x1024_40k_cityscapes/ann_r50-d8_512x1024_40k_cityscapes_20200605_095211.log.json)     |
@@ -30,6 +32,7 @@
 | ANN    | R-101-D8 | 769x769   |   80000 | -        | -              | 78.80 |         80.34 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_80k_cityscapes/ann_r101-d8_769x769_80k_cityscapes_20200607_013713-a9d4be8d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_769x769_80k_cityscapes/ann_r101-d8_769x769_80k_cityscapes_20200607_013713.log.json)     |
 
 ### ADE20K
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                download                                                                                                                                                                                |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | ANN    | R-50-D8  | 512x512   |   80000 |      9.1 |          21.01 | 41.01 |         42.30 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_80k_ade20k/ann_r50-d8_512x512_80k_ade20k_20200615_014818-26f75e11.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_80k_ade20k/ann_r50-d8_512x512_80k_ade20k_20200615_014818.log.json)         |
@@ -38,6 +41,7 @@
 | ANN    | R-101-D8 | 512x512   |  160000 | -        | -              | 42.94 |         44.06 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_160k_ade20k/ann_r101-d8_512x512_160k_ade20k_20200615_231733-955eb1ec.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r101-d8_512x512_160k_ade20k/ann_r101-d8_512x512_160k_ade20k_20200615_231733.log.json) |
 
 ### Pascal VOC 2012 + Aug
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                  download                                                                                                                                                                                  |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | ANN    | R-50-D8  | 512x512   |   20000 |        6 |          20.92 | 74.86 |         76.13 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_20k_voc12aug/ann_r50-d8_512x512_20k_voc12aug_20200617_222246-dfcb1c62.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ann/ann_r50-d8_512x512_20k_voc12aug/ann_r50-d8_512x512_20k_voc12aug_20200617_222246.log.json)     |

configs/ccnet/README.md

@@ -1,7 +1,8 @@
 # CCNet: Criss-Cross Attention for Semantic Segmentation
 
 ## Introduction
-```
+
+```latex
 @article{huang2018ccnet,
     title={CCNet: Criss-Cross Attention for Semantic Segmentation},
     author={Huang, Zilong and Wang, Xinggang and Huang, Lichao and Huang, Chang and Wei, Yunchao and Liu, Wenyu},
@@ -13,6 +14,7 @@
 ## Results and models
 
 ### Cityscapes
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                              download                                                                                                                                                                                              |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | CCNet  | R-50-D8  | 512x1024  |   40000 |        6 |           3.32 | 77.76 |         78.87 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x1024_40k_cityscapes/ccnet_r50-d8_512x1024_40k_cityscapes_20200616_142517-4123f401.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x1024_40k_cityscapes/ccnet_r50-d8_512x1024_40k_cityscapes_20200616_142517.log.json)     |
@@ -25,6 +27,7 @@
 | CCNet  | R-101-D8 | 769x769   |   80000 | -        | -              | 79.45 |         80.66 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r101-d8_769x769_80k_cityscapes/ccnet_r101-d8_769x769_80k_cityscapes_20200618_011502-ad3cd481.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r101-d8_769x769_80k_cityscapes/ccnet_r101-d8_769x769_80k_cityscapes_20200618_011502.log.json)     |
 
 ### ADE20K
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                      download                                                                                                                                                                                      |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | CCNet  | R-50-D8  | 512x512   |   80000 |      8.8 |          20.89 | 41.78 |         42.98 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x512_80k_ade20k/ccnet_r50-d8_512x512_80k_ade20k_20200615_014848-aa37f61e.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x512_80k_ade20k/ccnet_r50-d8_512x512_80k_ade20k_20200615_014848.log.json)         |
@@ -33,6 +36,7 @@
 | CCNet  | R-101-D8 | 512x512   |  160000 | -        | -              | 43.71 |         45.04 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r101-d8_512x512_160k_ade20k/ccnet_r101-d8_512x512_160k_ade20k_20200616_000644-e849e007.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r101-d8_512x512_160k_ade20k/ccnet_r101-d8_512x512_160k_ade20k_20200616_000644.log.json) |
 
 ### Pascal VOC 2012 + Aug
+
 | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                        download                                                                                                                                                                                        |
 |--------|----------|-----------|--------:|----------|----------------|------:|--------------:|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | CCNet  | R-50-D8  | 512x512   |   20000 |        6 |          20.45 | 76.17 |         77.51 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x512_20k_voc12aug/ccnet_r50-d8_512x512_20k_voc12aug_20200617_193212-fad81784.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/ccnet/ccnet_r50-d8_512x512_20k_voc12aug/ccnet_r50-d8_512x512_20k_voc12aug_20200617_193212.log.json)     |