Bump to v0.18.0 (open-mmlab#940)

* bump to v0.18.0

* replace \ with /

Author: Junjun2016

README.md

@@ -49,7 +49,7 @@ This project is released under the [Apache 2.0 license](LICENSE).
 
 ## Changelog
 
-v0.17.0 was released in 09/01/2021.
+v0.18.0 was released in 10/07/2021.
 Please refer to [changelog.md](docs/changelog.md) for details and release history.
 
 ## Benchmark and model zoo

README_zh-CN.md

@@ -48,7 +48,7 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
 
 ## 更新日志
 
-最新的月度版本 v0.17.0 在 2021.09.01 发布。
+最新的月度版本 v0.18.0 在 2021.10.07 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/changelog.md)。
 
 ## 基准测试和模型库

docs/changelog.md

@@ -1,5 +1,36 @@
 ## Changelog
 
+### V0.18 (10/07/2021)
+
+**Highlights**
+
+- Support three real-time segmentation models (ICNet [#884](https://github.com/open-mmlab/mmsegmentation/pull/884), BiSeNetV1 [#851](https://github.com/open-mmlab/mmsegmentation/pull/851), and BiSeNetV2 [#804](https://github.com/open-mmlab/mmsegmentation/pull/804))
+- Support one efficient segmentation model (FastFCN [#885](https://github.com/open-mmlab/mmsegmentation/pull/885))
+- Support one efficient non-local/self-attention based segmentation model (ISANet [#70](https://github.com/open-mmlab/mmsegmentation/pull/70))
+- Support COCO-Stuff 10k and 164k datasets ([#625](https://github.com/open-mmlab/mmsegmentation/pull/625))
+- Support evaluate concated dataset separately ([#833](https://github.com/open-mmlab/mmsegmentation/pull/833))
+- Support loading GT for evaluation from multi-file backend ([#867](https://github.com/open-mmlab/mmsegmentation/pull/867))
+
+**New Features**
+
+- Support three real-time segmentation models (ICNet [#884](https://github.com/open-mmlab/mmsegmentation/pull/884), BiSeNetV1 [#851](https://github.com/open-mmlab/mmsegmentation/pull/851), and BiSeNetV2 [#804](https://github.com/open-mmlab/mmsegmentation/pull/804))
+- Support one efficient segmentation model (FastFCN [#885](https://github.com/open-mmlab/mmsegmentation/pull/885))
+- Support one efficient non-local/self-attention based segmentation model (ISANet [#70](https://github.com/open-mmlab/mmsegmentation/pull/70))
+- Support COCO-Stuff 10k and 164k datasets ([#625](https://github.com/open-mmlab/mmsegmentation/pull/625))
+- Support evaluate concated dataset separately ([#833](https://github.com/open-mmlab/mmsegmentation/pull/833))
+
+**Improvements**
+
+- Support loading GT for evaluation from multi-file backend ([#867](https://github.com/open-mmlab/mmsegmentation/pull/867))
+- Auto-convert SyncBN to BN when training on DP automatly([#772](https://github.com/open-mmlab/mmsegmentation/pull/772))
+- Refactor Swin-Transformer ([#800](https://github.com/open-mmlab/mmsegmentation/pull/800))
+
+**Bug Fixes**
+
+- Update mmcv installation in dockerfile ([#860](https://github.com/open-mmlab/mmsegmentation/pull/860))
+- Fix number of iteration bug when resuming checkpoint in distributed train ([#866](https://github.com/open-mmlab/mmsegmentation/pull/866))
+- Fix parsing parse in val_step ([#906](https://github.com/open-mmlab/mmsegmentation/pull/906))
+
 ### V0.17 (09/01/2021)
 
 **Highlights**

docs/get_started.md

@@ -12,6 +12,7 @@ The compatible MMSegmentation and MMCV versions are as below. Please install the
 | MMSegmentation version |    MMCV version     |
 |:-------------------:|:-------------------:|
 | master              | mmcv-full>=1.3.13, <1.4.0 |
+| 0.18.0              | mmcv-full>=1.3.13, <1.4.0 |
 | 0.17.0              | mmcv-full>=1.3.7, <1.4.0 |
 | 0.16.0              | mmcv-full>=1.3.7, <1.4.0 |
 | 0.15.0              | mmcv-full>=1.3.7, <1.4.0 |

docs_zh-CN/get_started.md

@@ -12,6 +12,7 @@
 | MMSegmentation 版本 |    MMCV 版本     |
 |:-------------------:|:-------------------:|
 | master              | mmcv-full>=1.3.13, <1.4.0 |
+| 0.18.0              | mmcv-full>=1.3.13, <1.4.0 |
 | 0.17.0              | mmcv-full>=1.3.7, <1.4.0 |
 | 0.16.0              | mmcv-full>=1.3.7, <1.4.0 |
 | 0.15.0              | mmcv-full>=1.3.7, <1.4.0 |

mmseg/version.py

@@ -1,6 +1,6 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '0.17.0'
+__version__ = '0.18.0'
 
 
 def parse_version_info(version_str):