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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 ## 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. Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
## Benchmark and model zoo ## 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 ## 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)。 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 ## 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 ### 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 ```shell
pip install mmcls>=0.20.1 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${CUDNN}-devel FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
ARG MMCV="1.4.4" ARG MMCV="1.4.4"
ARG MMSEG="0.21.0" ARG MMSEG="0.22.0"
ENV PYTHONUNBUFFERED TRUE ENV PYTHONUNBUFFERED TRUE

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docs/en/changelog.md
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@ -1,6 +1,52 @@
## Changelog ## 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) ### V0.21.1 (2/9/2022)
**Bug Fixes** **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. The compatible MMSegmentation and MMCV versions are as below. Please install the correct version of MMCV to avoid installation issues.
| MMSegmentation version | MMCV version | | MMSegmentation version | MMCV version | MMClassification version |
|:----------------------:|:--------------------------:| |:----------------------:|:--------------------------:|:------------------------:|
| master | mmcv-full>=1.4.4, <1.5.0 | | master | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 | | 0.22.0 | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 | | 0.21.1 | mmcv-full>=1.4.4, <=1.5.0 | Not required |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | | 0.20.2 | mmcv-full>=1.3.13, <=1.5.0 | Not required |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | | 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | | 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | | 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | | 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | | 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | Not required |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | | 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 | | 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | Not required |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 | | 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} :::{note}
You need to run `pip uninstall mmcv` first if you have mmcv installed. 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。 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 | | MMSegmentation 版本 | MMCV 版本 | MMClassification 版本 |
|:-----------------:|:--------------------------:| |:-----------------:|:--------------------------:|:----------------------:|
| master | mmcv-full>=1.4.4, <1.5.0 | | master | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 | | 0.22.0 | mmcv-full>=1.4.4, <=1.5.0 | mmcls>=0.20.1, <=1.0.0 |
| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 | | 0.21.1 | mmcv-full>=1.4.4, <=1.5.0 | Not required |
| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | | 0.20.2 | mmcv-full>=1.3.13, <=1.5.0 | Not required |
| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | | 0.19.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.18.0 | mmcv-full>=1.3.13, <1.3.17 | Not required |
| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.17.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | | 0.16.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | | 0.15.0 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | | 0.14.1 | mmcv-full>=1.3.7, <1.3.17 | Not required |
| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | | 0.14.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | | 0.13.0 | mmcv-full>=1.3.1, <1.3.2 | Not required |
| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.12.0 | mmcv-full>=1.1.4, <1.3.2 | Not required |
| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.11.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | | 0.10.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | | 0.9.0 | mmcv-full>=1.1.4, <1.3.0 | Not required |
| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 | | 0.8.0 | mmcv-full>=1.1.4, <1.2.0 | Not required |
| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 | | 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`。 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`。 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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# Copyright (c) Open-MMLab. All rights reserved. # Copyright (c) Open-MMLab. All rights reserved.
__version__ = '0.21.1' __version__ = '0.22.0'
def parse_version_info(version_str): def parse_version_info(version_str):