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Bump v0.22.0 (#1347)

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* change version to v0.22.0

* change version to v0.22.0

* add mmcls version in get_started.md

* add mmcls installation and move PR1299 into enhancement

* add mmcls installation and move PR1299 into enhancement

* remove MMCLS and make mmcv <=1.5.0 version in get_started.md

* fix typo
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README.md
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@ -66,7 +66,7 @@ This project is released under the [Apache 2.0 license](LICENSE).
## Changelog
v0.21.0 was released in 2/9/2022.
v0.22.0 was released in 3/4/2022.
Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
## Benchmark and model zoo

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README_zh-CN.md
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@ -65,7 +65,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
## 更新日志
最新版本 v0.21.1 在 2022.2.9 发布。
最新版本 v0.22.0 在 2022.3.4 发布。
如果想了解更多版本更新细节和历史信息，请阅读[更新日志](docs/en/changelog.md)。
## 基准测试和模型库

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configs/convnext/README.md
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@ -32,7 +32,7 @@ The "Roaring 20s" of visual recognition began with the introduction of Vision Tr
### Usage
- This backbone need to install [MMClassification](https://github.com/open-mmlab/mmclassification) first, which has abundant backbones for downstream tasks.
- ConvNeXt backbone needs to install [MMClassification](https://github.com/open-mmlab/mmclassification) first, which has abundant backbones for downstream tasks.
```shell
pip install mmcls>=0.20.1

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docker/serve/Dockerfile
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@ -4,7 +4,7 @@ ARG CUDNN="7"
FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
ARG MMCV="1.4.4"
ARG MMSEG="0.21.0"
ARG MMSEG="0.22.0"
ENV PYTHONUNBUFFERED TRUE

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docs/en/changelog.md
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@ -1,6 +1,52 @@
## Changelog
### V0.22 (3/04/2022)
**Highlights**
- Officially Support ConvNeXt: A ConvNet for the 2020s. Please use the latest MMClassification (0.21.0) to try it out.
- Support iSAID aerial Dataset.
- Officially Support inference on Windows OS.
**New Features**
- Support ConvNeXt: A ConvNet for the 2020s. ([#1216](https://github.com/open-mmlab/mmsegmentation/pull/1216))
- Support iSAID aerial Dataset. ([#1115](https://github.com/open-mmlab/mmsegmentation/pull/1115)
- Generating and plotting confusion matrix. ([#1301](https://github.com/open-mmlab/mmsegmentation/pull/1301))
**Improvements**
- Refactor 4 decoder heads (ASPP, FCN, PSP, UPer): Split forward function into `_forward_feature` and `cls_seg`. ([#1299](https://github.com/open-mmlab/mmsegmentation/pull/1299))
- Add `min_size` arg in `Resize` to keep the shape after resize bigger than slide window. ([#1318](https://github.com/open-mmlab/mmsegmentation/pull/1318))
- Revise pre-commit-hooks. ([#1315](https://github.com/open-mmlab/mmsegmentation/pull/1315))
- Add win-ci. ([#1296](https://github.com/open-mmlab/mmsegmentation/pull/1296))
**Bug Fixes**
- Fix `mlp_ratio` type in Swin Transformer. ([#1274](https://github.com/open-mmlab/mmsegmentation/pull/1274))
- Fix path errors in `./demo` . ([#1269](https://github.com/open-mmlab/mmsegmentation/pull/1269))
- Fix bug in conversion of potsdam. ([#1279](https://github.com/open-mmlab/mmsegmentation/pull/1279))
- Make accuracy take into account `ignore_index`. ([#1259](https://github.com/open-mmlab/mmsegmentation/pull/1259))
- Add Pytorch HardSwish assertion in unit test. ([#1294](https://github.com/open-mmlab/mmsegmentation/pull/1294))
- Fix wrong palette value in vaihingen. ([#1292](https://github.com/open-mmlab/mmsegmentation/pull/1292))
- Fix the bug that SETR cannot load pretrain. ([#1293](https://github.com/open-mmlab/mmsegmentation/pull/1293))
- Update correct `In Collection` in metafile of each configs. ([#1239](https://github.com/open-mmlab/mmsegmentation/pull/1239))
- Upload completed STDC models. ([#1332](https://github.com/open-mmlab/mmsegmentation/pull/1332))
- Fix `DNLHead` exports onnx inference difference type Cast error. ([#1161](https://github.com/open-mmlab/mmsegmentation/pull/1332))
**Contributors**
- @JiaYanhao made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1269
- @andife made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1281
- @SBCV made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1279
- @HJoonKwon made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1259
- @Tsingularity made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1290
- @Waterman0524 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1115
- @MeowZheng made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1315
- @linfangjian01 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1318
### V0.21.1 (2/9/2022)
**Bug Fixes**

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docs/en/get_started.md
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@ -9,26 +9,27 @@
The compatible MMSegmentation and MMCV versions are as below. Please install the correct version of MMCV to avoid installation issues.
| MMSegmentation version | MMCV version |
|:----------------------:|:--------------------------:|
| master | mmcv-full>=1.4.4, <1.5.0 |
| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 |
| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
| MMSegmentation version | MMCV version | MMClassification version |
|:----------------------:|:--------------------------:|:------------------------:|
| master | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.22.0 | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.21.1 | mmcv-full>=1.4.4, <=1.5.0 | Not required |
| 0.20.2 | mmcv-full>=1.3.13, <=1.5.0 | Not required |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | Not required |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | Not required |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 | Not required |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 | Not required |
:::{note}
You need to run `pip uninstall mmcv` first if you have mmcv installed.

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docs/zh_cn/get_started.md
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@ -9,26 +9,27 @@
可编译的 MMSegmentation 和 MMCV 版本如下所示，请对照对应版本安装以避免安装问题。
| MMSegmentation 版本 | MMCV 版本 |
|:-----------------:|:--------------------------:|
| master | mmcv-full>=1.4.4, <1.5.0 |
| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 |
| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
| MMSegmentation 版本 | MMCV 版本 | MMClassification 版本 |
|:-----------------:|:--------------------------:|:----------------------:|
| master | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.22.0 | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.21.1 | mmcv-full>=1.4.4, <=1.5.0 | Not required |
| 0.20.2 | mmcv-full>=1.3.13, <=1.5.0 | Not required |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | Not required |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | Not required |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 | Not required |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 | Not required |
注意: 如果您已经安装好 mmcv， 您首先需要运行 `pip uninstall mmcv`。
如果 mmcv 和 mmcv-full 同时被安装，会报错 `ModuleNotFoundError`。

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mmseg/version.py
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@ -1,6 +1,6 @@
# Copyright (c) Open-MMLab. All rights reserved.
__version__ = '0.21.1'
__version__ = '0.22.0'
def parse_version_info(version_str):