Bump v0.29.0 (#2167)

* bump v0.29.0

* remove 2159

README.md

@@ -77,10 +77,9 @@ The master branch works with **PyTorch 1.5+**.
 
 ### 💎 Stable version
 
-v0.28.0 was released in 9/08/2022:
+v0.29.0 was released on 10/10/2022:
 
-- Support Tversky Loss
-- Fix binary segmentation
+- Support PoolFormer (CVPR'2022)
 
 Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
 

README_zh-CN.md

@@ -74,10 +74,9 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
 
 ### 💎 稳定版本
 
-最新版本 v0.28.0 在 2022.9.8 发布：
+最新版本 v0.29.0 在 2022.10.10 发布：
 
-- 支持 Tversky Loss
-- 修复二值分割
+- 支持 PoolFormer (CVPR'2022)
 
 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)。
 

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="0.28.0"
+ARG MMSEG="0.29.0"
 
 ENV PYTHONUNBUFFERED TRUE
 

docs/en/changelog.md

@@ -1,5 +1,32 @@
 ## Changelog
 
+### V0.29.0 (10/10/2022)
+
+**New Features**
+
+- Support PoolFormer (CVPR'2022) ([#1537](https://github.com/open-mmlab/mmsegmentation/pull/1537))
+
+**Enhancement**
+
+- Improve structure and readability for FCNHead ([#2142](https://github.com/open-mmlab/mmsegmentation/pull/2142))
+- Support IterableDataset in distributed training ([#2151](https://github.com/open-mmlab/mmsegmentation/pull/2151))
+- Upgrade .dev scripts ([#2020](https://github.com/open-mmlab/mmsegmentation/pull/2020))
+- Upgrade pre-commit hooks ([#2155](https://github.com/open-mmlab/mmsegmentation/pull/2155))
+
+**Bug Fixes**
+
+- Fix mmseg.api.inference inference_segmentor ([#1849](https://github.com/open-mmlab/mmsegmentation/pull/1849))
+- fix bug about label_map in evaluation part ([#2075](https://github.com/open-mmlab/mmsegmentation/pull/2075))
+- Add missing dependencies to torchserve docker file ([#2133](https://github.com/open-mmlab/mmsegmentation/pull/2133))
+- Fix ddp unittest ([#2060](https://github.com/open-mmlab/mmsegmentation/pull/2060))
+
+**Contributors**
+
+- @jinwonkim93 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1849
+- @rlatjcj made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2075
+- @ShirleyWangCVR made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2151
+- @mangelroman made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/2133
+
 ### V0.28.0 (9/8/2022)
 
 **New Features**

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, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
+|         0.29.0         |  mmcv-full>=1.5.0, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.28.0         |  mmcv-full>=1.5.0, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.27.0         |  mmcv-full>=1.5.0, \<1.7.0  | 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  |

docs/zh_cn/faq.md

@@ -9,6 +9,7 @@
 | MMSegmentation version |        MMCV version         | MMClassification version |
 | :--------------------: | :-------------------------: | :----------------------: |
 |         master         |  mmcv-full>=1.5.0, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
+|         0.29.0         |  mmcv-full>=1.5.0, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.28.0         |  mmcv-full>=1.5.0, \<1.7.0  | mmcls>=0.20.1, \<=1.0.0  |
 |         0.27.0         |  mmcv-full>=1.5.0, \<1.7.0  | 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  |

mmseg/version.py

@@ -1,6 +1,6 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '0.28.0'
+__version__ = '0.29.0'
 
 
 def parse_version_info(version_str):