Bump to v1.1.1 (#2569)

* add changelog

* add readme

* fix typo

* Update README.md
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

* Update README_zh-CN.md
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* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

* Update docs/en/notes/changelog.md
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

* Update docs/en/notes/changelog.md
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

* Update docs/en/notes/changelog.md
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* Update docs/en/notes/changelog.md
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---------
Co-authored-by: Jingwei Zhang <zjw18@mails.tsinghua.edu.cn>

README.md

@@ -52,15 +52,9 @@
 **We have renamed the branch `1.1`  to `main` and switched the default branch from `master` to `main`. We encourage
 users to migrate to the latest version, though it comes with some cost. Please refer to [Migration Guide](docs/en/migration.md) for more details.**
 
-**v1.1.0** was released in 6/4/2023
+**v1.1.1** was released in 30/5/2023
 
-We have supported more LiDAR-based segmentation methods, including Cylinder3D, MinkUNet and SPVCNN. More new features about 3D perception are on the way. Please stay tuned!
-
-**v1.1.0rc3** was released in 7/1/2023
-
-The compatibilities of models are broken due to the unification and simplification of coordinate systems after v1.0.0rc0. For now, most models are benchmarked with similar performance, though few models are still being benchmarked. In the following release, we will update all the model checkpoints and benchmarks. See more details in the [Changelog](docs/en/notes/changelog.md) and [Changelog-v1.0.x](docs/en/notes/changelog_v1.0.x.md).
-
-Documentation: https://mmdetection3d.readthedocs.io/
+We have constructed a comprehensive LiDAR semantic segmentation benchmark on SemanticKITTI, including Cylinder3D, MinkUNet and SPVCNN methods. Noteworthy, the improved MinkUNetv2 can achieve 70.3 mIoU on the validation set of SemanticKITTI. We have also supported the training of BEVFusion and an occupancy prediction method, TPVFomrer, in our `projects`. More new features about 3D perception are on the way. Please stay tuned!
 
 ## Introduction
 

README_zh-CN.md

@@ -49,15 +49,9 @@
 
 **我们将 `1.1` 分支重命名为 `main` 并将默认分支从 `master` 切换到 `main`。我们鼓励用户迁移到最新版本，请参考 [迁移指南](docs/en/migration.md) 以了解更多细节。**
 
-**v1.1.0** 版本已经在 2023.4.6 发布。
+**v1.1.1** 版本已于 2023.5.30 发布
 
-我们已经支持了更多基于 LiDAR 的 3D 分割算法。更多关于 3D 感知的新特性正在开发中，请拭目以待！
-
-**v1.1.0rc3** 版本已经在 2023.1.7 发布。
-
-由于坐标系的统一和简化，模型的兼容性会受到影响。目前，大多数模型都以类似的性能对齐了精度，但仍有少数模型在进行基准测试。在接下来的版本中，我们将更新所有的模型权重文件和基准。您可以在[变更日志](docs/zh_cn/notes/changelog.md)和 [v1.0.x 版本变更日志](docs/zh_cn/notes/changelog_v1.0.x.md)中查看更多详细信息。
-
-文档：https://mmdetection3d.readthedocs.io/
+我们在 SemanticKITTI 上构建了一个全面的点云语义分割基准，包括 Cylinder3D 、 MinkUNet 和 SPVCNN 方法。其中，改进后的 MinkUNetv2 在验证集上可以达到 70.3 mIoU 。我们还在 projects 中支持了 BEVFusion 的训练和全新的 3D 占有网格预测网络 TPVFormer 。更多关于3D感知的新功能正在进行中。请继续关注!
 
 ## 简介
 

docs/en/notes/changelog.md

 # Changelog of v1.1
 
+### v1.1.1 (30/5/2023)
+
+#### Highlights
+
+- Support [TPVFormer](https://arxiv.org/pdf/2302.07817.pdf) in `projects` (#2399, #2517, #2535)
+- Support the training of \[BEVFusion\] in `projects` (#2546)
+- Support lidar-based 3D semantic segmentation benchmark (#2530, #2559)
+
+#### New Features
+
+- Support [TPVFormer](https://arxiv.org/pdf/2302.07817.pdf) in `projects` (#2399, #2517, #2535)
+- Support the training of \[BEVFusion\] in `projects` (#2558)
+- Support lidar-based 3D Semantic Segmentation Benchmark (#2530, #2559)
+- Support test-time augmentation for Segmentor (#2382)
+- Support `Minkowski ConvModule` and `Residual` Block (#2528)
+- Support the visualization of multi-view images in multi-modal methods (#2453)
+
+#### Improvements
+
+- Upload checkpoints and training log of PETR (#2555)
+- Replace `np.float` by default `float` in segmentation evaluation (#2527)
+- Add docs of converting SemanticKITTI datasets (#2515)
+- Support different colors for different classes in visualization (#2500)
+- Support tensor-like operations for `BaseInstance3DBoxes` and `BasePoint`
+- Add information of LiDAR Segmentation in NuScenes annotation files
+- Provide annotation files of datasets generated offline (#2457)
+- Refactor document structure (#2429)
+- Complete typehints and docstring (#2396, #2457, #2468, #2464, #2485)
+
+#### Bug Fixes
+
+- Fix the bug of abnormal loss when training SECOND in Automatic mixed precision(AMP) mode (#2452)
+- Add a warning in function `post_process_coords` in mmdet3d/dataset/convert_utils.py (#2557)
+- Fix invalid configs (#2477, #2536)
+- Fix bugs of unit test (#2466)
+- Update `local-rank` argument in test.py for pytorch 2.0 (#2469)
+- Fix docker file (#2451)
+- Fix demo and visualization (#2453)
+- Fix SUN RGB-D data converter (#2440)
+- Fix readthedocs building (#2459, #2419, #2505, #2396)
+- Fix CI #(2445)
+- Fix the version error of `torch` in github merge stage test (#2424)
+- Loose the version restriction of `numba` (#2416)
+
+#### Contributors
+
+A total of 10 developers contributed to this release.
+
+@sunjiahao1999, @Xiangxu-0103, @JingweiZhang12, @chriscarving, @jaan1729, @pd-michaelstanley, @filaPro, @kabouzeid, @A-new-b, @lbin
+
 ### v1.1.0 (6/4/2023)
 
 #### Highlights

docs/en/notes/faq.md

@@ -12,10 +12,10 @@ We list some potential troubles encountered by users and developers, along with
   | --------------------- | :----------------------: | :---------------------: | :----------------------: |
   | dev-1.x               | mmengine>=0.7.1, \<1.0.0 | mmcv>=2.0.0rc4, \<2.1.0 |  mmdet>=3.0.0, \<3.1.0   |
   | main                  | mmengine>=0.7.1, \<1.0.0 | mmcv>=2.0.0rc4, \<2.1.0 |  mmdet>=3.0.0, \<3.1.0   |
+  | v1.1.1                | mmengine>=0.7.1, \<1.0.0 | mmcv>=2.0.0rc4, \<2.1.0 |  mmdet>=3.0.0, \<3.1.0   |
   | v1.1.0rc3             | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc3, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
   | v1.1.0rc2             | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc3, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
   | v1.1.0rc1             | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
-  | v1.1.0rc0             | mmengine>=0.1.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 | mmdet>=3.0.0rc0, \<3.1.0 |
 
   **Note:** If you want to install mmdet3d-v1.0.0rcx, the compatible MMDetection, MMSegmentation and MMCV versions table can be found at [here](https://mmdetection3d.readthedocs.io/en/latest/faq.html#mmcv-mmdet-mmdet3d-installation). Please choose the correct version of MMCV, MMDetection and MMSegmentation to avoid installation issues.
 

mmdet3d/version.py

 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '1.1.0'
+__version__ = '1.1.1'
 short_version = __version__