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bump v0.30.0 (open-mmlab#2462)
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README.md

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### 💎 Stable version
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v0.29.1 was released on 11/3/2022:
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v0.30.0 was released on 01/11/2023:
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- Add model ensemble tools
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- Update documents
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- Add 'Projects/' folder, and the first example project
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- Support Delving into High-Quality Synthetic Face Occlusion Segmentation Datasets
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Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
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### 🌟 Preview of 1.x version
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A brand new version of **MMSegmentation v1.0.0rc1** was released in 02/11/2022:
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A brand new version of **MMSegmentation v1.0.0rc3** was released in 12/31/2022:
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- Unifies interfaces of all components based on [MMEngine](https://github.com/open-mmlab/mmengine).
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- Faster training and testing speed with complete support of mixed precision training.

README_zh-CN.md

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### 💎 稳定版本
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最新版本 v0.29.12022.11.03 发布:
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最新版本 v0.30.02023.01.11 发布:
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- 添加模型集成工具
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- 更新文档
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- 添加 projects 目录以及示例项目
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- 支持高质量合成人脸数据集
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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)
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### 🌟 1.x 预览版本
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全新的 **MMSegmentation v1.0.0rc1** 版本已经在 2022.11.02 发布:
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全新的 **MMSegmentation v1.0.0rc3** 版本已经在 2022.12.31 发布:
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- 基于 [MMEngine](https://github.com/open-mmlab/mmengine) 统一了各组件接口。
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- 全面支持混合精度,训练测试速度更快。

docker/serve/Dockerfile

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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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ARG MMCV="1.5.0"
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ARG MMSEG="0.29.1"
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ARG MMSEG="0.30.0"
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ENV PYTHONUNBUFFERED TRUE
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docs/en/changelog.md

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## Changelog
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### V0.30.0 (01/09/2023)
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**New Features**
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- Support Delving into High-Quality Synthetic Face Occlusion Segmentation Datasets ([#2194](https://github.com/open-mmlab/mmsegmentation/pull/2194))
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**Bug Fixes**
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- Fix incorrect `test_cfg` setting in UNet base configs ([#2347](https://github.com/open-mmlab/mmsegmentation/pull/2347))
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- Fix KNet `IterativeDecodeHead` bug in master branch ([#2333](https://github.com/open-mmlab/mmsegmentation/pull/2333))
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- Fix deadlock issue related with MMSegWandbHook ([#2398](https://github.com/open-mmlab/mmsegmentation/pull/2398))
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**Enhancement**
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- Update CI and pre-commit checking ([#2309](https://github.com/open-mmlab/mmsegmentation/pull/2309),[#2331](https://github.com/open-mmlab/mmsegmentation/pull/2331))
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- Add `Projects/` folder, and the first example project in 0.x ([#2457](https://github.com/open-mmlab/mmsegmentation/pull/2457))
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- Fix the deprecation of `np.float` and CI configuration problems ([#2451](https://github.com/open-mmlab/mmsegmentation/pull/2451))
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**Documentation**
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- Add high quality synthetic face occlusion dataset link to readme ([#2453](https://github.com/open-mmlab/mmsegmentation/pull/2453))
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- Fix the docstring error in the `PascalContextDataset59` class ([#2450](https://github.com/open-mmlab/mmsegmentation/pull/2450))
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**Contributors**
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- @smttsp made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2347
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- @MilkClouds made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2398
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- @Spritea made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2450
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### V0.29.1 (11/3/2022)
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**New Features**

docs/en/faq.md

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| MMSegmentation version | MMCV version | MMClassification version |
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| :--------------------: | :-------------------------: | :----------------------: |
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| master | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.30.0 | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.29.1 | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.29.0 | mmcv-full>=1.5.0, \<1.7.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.28.0 | mmcv-full>=1.5.0, \<1.7.0 | mmcls>=0.20.1, \<=1.0.0 |

docs/zh_cn/faq.md

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| MMSegmentation version | MMCV version | MMClassification version |
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| :--------------------: | :-------------------------: | :----------------------: |
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| master | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.30.0 | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.29.1 | mmcv-full>=1.5.0, \<1.8.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.29.0 | mmcv-full>=1.5.0, \<1.7.0 | mmcls>=0.20.1, \<=1.0.0 |
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| 0.28.0 | mmcv-full>=1.5.0, \<1.7.0 | mmcls>=0.20.1, \<=1.0.0 |

mmseg/version.py

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# Copyright (c) Open-MMLab. All rights reserved.
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__version__ = '0.29.1'
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__version__ = '0.30.0'
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def parse_version_info(version_str):

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