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Sep 26, 2022
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Bump version to 3.0.0rc1 #8873

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373dc73
bump version to 3.0.0rc1
hhaAndroid Sep 26, 2022
77a1922
Merge branch 'dev-3.x' of github.com:open-mmlab/mmdetection into chan…
hhaAndroid Sep 26, 2022
8fa6d48
update
hhaAndroid Sep 26, 2022
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hhaAndroid Sep 26, 2022
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9 changes: 3 additions & 6 deletions README.md
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Expand Up @@ -75,13 +75,10 @@ Apart from MMDetection, we also released [MMEngine](https://github.com/open-mmla

## What's New

**v3.0.0rc0** was released in 31/8/2022:
**v3.0.0rc1** was released in 26/9/2022:

- Unifies interfaces of all components based on [MMEngine](https://github.com/open-mmlab/mmengine).
- Faster training and testing speed with complete support of mixed precision training.
- Refactored and more flexible [architecture](https://mmdetection.readthedocs.io/en/3.x/overview.html).
- Provides more strong baselines and a general semi-supervised object detection framework. See [tutorial of semi-supervised detection](https://mmdetection.readthedocs.io/en/3.x/user_guides/semi_det.html).
- Allows any kind of single-stage model as an RPN in a two-stage model. See [tutorial](https://mmdetection.readthedocs.io/en/3.x/user_guides/single_stage_as_rpn.html).
- Release a high-precision, low-latency single-stage object detector [RTMDet](configs/rtmdet).
- Refactored anchor head and base head with `box type`.

## Installation

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8 changes: 3 additions & 5 deletions README_zh-CN.md
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Expand Up @@ -74,12 +74,10 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope

## 最新进展

**v3.0.0rc0** 版本已经在 2022.8.31 发布：
**v3.0.0rc1** 版本已经在 2022.9.26 发布：

- 基于 [MMEngine](https://github.com/open-mmlab/mmengine) 统一了各组件接口。
- 全面支持混合精度，训练测试速度更快。
- 提供了更强的基线模型，并支持了通用的半监督目标检测框架，详见[半监督目标检测教程](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/semi_det.html)。
- 支持使用任意单阶段检测器作为二阶段模型的 RPN，详见[教程](https://mmdetection.readthedocs.io/zh_CN/3.x/user_guides/single_stage_as_rpn.html)。
- 发布高精度低延时单阶段目标检测算法 [RTMDet](configs/rtmdet)。
- 重构 Anchor Head 和 Base Head 以支持 `box type`。

## 安装

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31 changes: 31 additions & 0 deletions docs/en/notes/changelog.md
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# Changelog of v3.x

## v3.0.0rc1 (26/9/2022)

### Highlights

- Release a high-precision, low-latency single-stage object detector [RTMDet](configs/rtmdet).

#### Bug Fixes

- Fix UT to be compatible with PyTorch 1.6 (#8707)
- Fix `NumClassCheckHook` bug when model is wrapped (#8794)
- Update the right URL of R-50-FPN with BoundedIoULoss (#8805)
- Fix potential bug of indices in RandAugment (#8826)
- Fix some types and links (#8839, #8820, #8793, #8868)
- Fix incorrect background fill values in `FSAF` and `RepPoints` Head (#8813)

#### Improvements

- Refactored anchor head and base head with `box type` (#8625)
- Refactored `SemiBaseDetector` and `SoftTeacher` (#8786)
- Add list to dict keys to avoid modify loss dict (#8828)
- Update `analyze_results.py` , `analyze_logs.py` and `loading.py` (#8430, #8402, #8784)
- Support dump results in `test.py` (#8814)
- Check empty predictions in `DetLocalVisualizer._draw_instances` (#8830)
- Fix `floordiv` warning in `SOLO` (#8738)

#### Contributors

A total of 16 developers contributed to this release.

Thanks @ZwwWayne, @jbwang1997, @Czm369, @ice-tong, @Zheng-LinXiao, @chhluo, @RangiLyu, @liuyanyi, @wanghonglie, @levan92, @JiayuXu0, @nye0, @hhaAndroid, @xin-li-67, @shuxp, @zytx121

## v3.0.0rc0 (31/8/2022)

We are excited to announce the release of MMDetection 3.0.0rc0. MMDet 3.0.0rc0 is the first version of MMDetection 3.x, a part of the OpenMMLab 2.0 projects. Built upon the new [training engine](https://github.com/open-mmlab/mmengine), MMDet 3.x unifies the interfaces of the dataset, models, evaluation, and visualization with faster training and testing speed. It also provides a general semi-supervised object detection framework and strong baselines.
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2 changes: 1 addition & 1 deletion mmdet/version.py
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# Copyright (c) OpenMMLab. All rights reserved.

__version__ = '3.0.0rc0'
__version__ = '3.0.0rc1'
short_version = __version__


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1 change: 1 addition & 0 deletions model-index.yml
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Expand Up @@ -53,6 +53,7 @@ Import:
- configs/pisa/metafile.yml
- configs/point_rend/metafile.yml
- configs/queryinst/metafile.yml
- configs/rtmdet/metafile.yml
- configs/regnet/metafile.yml
- configs/reppoints/metafile.yml
- configs/res2net/metafile.yml
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