Bump v0.26.0 (open-mmlab#1731)

Author: MengzhangLI

README.md

@@ -75,7 +75,7 @@ The master branch works with **PyTorch 1.5+**.
 
 ## What's New
 
-v0.25.0 was released in 6/2/2022:
+v0.26.0 was released in 7/1/2022:
 
 - Support PyTorch backend on MLU
 

README_zh-CN.md

@@ -72,7 +72,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
 
 ## 最新进展
 
-最新版本 v0.25.0 在 2022.6.2 发布：
+最新版本 v0.26.0 在 2022.7.1 发布：
 
 - 支持 PyTorch MLU 后端
 

docker/serve/Dockerfile

@@ -4,7 +4,7 @@ ARG CUDNN="8"
 FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
 
 ARG MMCV="1.5.0"
-ARG MMSEG="0.25.0"
+ARG MMSEG="0.26.0"
 
 ENV PYTHONUNBUFFERED TRUE
 

docs/en/changelog.md

@@ -1,5 +1,42 @@
 ## Changelog
 
+### V0.26.0 (7/1/2022)
+
+**Highlights**
+
+- Update New SegFormer models on ADE20K ([1705](https://github.com/open-mmlab/mmsegmentation/pull/1705))
+- Dedicated MMSegWandbHook for MMSegmentation ([1603](https://github.com/open-mmlab/mmsegmentation/pull/1603))
+
+**New Features**
+
+- Update New SegFormer models on ADE20K ([1705](https://github.com/open-mmlab/mmsegmentation/pull/1705))
+- Dedicated MMSegWandbHook for MMSegmentation ([1603](https://github.com/open-mmlab/mmsegmentation/pull/1603))
+- Add UPerNet r18 results ([1669](https://github.com/open-mmlab/mmsegmentation/pull/1669))
+
+**Enhancement**
+
+- Keep dimension of `cls_token_weight` for easier ONNX deployment ([1642](https://github.com/open-mmlab/mmsegmentation/pull/1642))
+- Support infererence with padding ([1607](https://github.com/open-mmlab/mmsegmentation/pull/1607))
+
+**Bug Fixes**
+
+- Fix typos ([#1640](https://github.com/open-mmlab/mmsegmentation/pull/1640), [#1667](https://github.com/open-mmlab/mmsegmentation/pull/1667), [#1656](https://github.com/open-mmlab/mmsegmentation/pull/1656), [#1699](https://github.com/open-mmlab/mmsegmentation/pull/1699), [#1702](https://github.com/open-mmlab/mmsegmentation/pull/1702), [#1695](https://github.com/open-mmlab/mmsegmentation/pull/1695), [#1707](https://github.com/open-mmlab/mmsegmentation/pull/1707), [#1708](https://github.com/open-mmlab/mmsegmentation/pull/1708), [#1721](https://github.com/open-mmlab/mmsegmentation/pull/1721))
+
+**Documentation**
+
+- Fix `mdformat` version to support python3.6 and remove ruby installation ([1672](https://github.com/open-mmlab/mmsegmentation/pull/1672))
+
+**Contributors**
+
+- @RunningLeon made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1642
+- @zhouzaida made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1655
+- @tkhe made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1667
+- @rotorliu made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1656
+- @EvelynWang-0423 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1679
+- @ZhaoYi1222 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1616
+- @Sanster made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1704
+- @ayulockin made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1603
+
 ### V0.25.0 (6/2/2022)
 
 **Highlights**

docs/en/faq.md

@@ -9,6 +9,7 @@ The compatible MMSegmentation and MMCV versions are as below. Please install the
 | MMSegmentation version |        MMCV version         | MMClassification version |
 | :--------------------: | :-------------------------: | :----------------------: |
 |         master         | mmcv-full>=1.5.0, \<=1.6.0  | mmcls>=0.20.1, \<=1.0.0  |
+|         0.26.0         | mmcv-full>=1.5.0, \<=1.6.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.25.0         | mmcv-full>=1.5.0, \<=1.6.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.24.1         | mmcv-full>=1.4.4, \<=1.6.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.23.0         | mmcv-full>=1.4.4, \<=1.6.0  | mmcls>=0.20.1, \<=1.0.0  |

mmseg/version.py

@@ -1,6 +1,6 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '0.25.0'
+__version__ = '0.26.0'
 
 
 def parse_version_info(version_str):