[Doc]: Polish readme. (#6243)

* [Doc]: Polish readme. * fix link * update * update readme * delete useless lines * fix link * link to readthedoc * add projects
4 years ago · 4e24a86a7a
parent 622f0c4c11
commit 4e24a86a7a
5 changed files with 78 additions and 26 deletions
--- a/README.md
+++ b/README.md
@ -1,6 +1,6 @@
 <div align="center">
  <img src="resources/mmdet-logo.png" width="600"/>
-</div>
+

 [![PyPI](https://img.shields.io/pypi/v/mmdet)](https://pypi.org/project/mmdet)
 [![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdetection.readthedocs.io/en/latest/)
@ -9,7 +9,18 @@
 [![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/master/LICENSE)
 [![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)

-Documentation: https://mmdetection.readthedocs.io/
+
+  <img src="https://user-images.githubusercontent.com/12907710/137271636-56ba1cd2-b110-4812-8221-b4c120320aa9.png"/>
+
+
+[📘Documentation](https://mmdetection.readthedocs.io/en/v2.17.0/) |
+[🛠️Installation](https://mmdetection.readthedocs.io/en/v2.17.0/get_started.html) |
+[👀Model Zoo](https://mmdetection.readthedocs.io/zh_CN/v2.17.0/model_zoo.html) |
+[🆕Update News](https://mmdetection.readthedocs.io/en/v2.17.0/changelog.html) |
+[🚀Ongoing Projects](https://github.com/open-mmlab/mmdetection/projects) |
+[🤔Reporting Issues](https://github.com/open-mmlab/mmdetection/issues/new/choose)
+
+</div>

 ## Introduction

@ -19,11 +30,9 @@ MMDetection is an open source object detection toolbox based on PyTorch. It is
 a part of the [OpenMMLab](https://openmmlab.com/) project.

 The master branch works with **PyTorch 1.3+**.
-The old v1.x branch works with PyTorch 1.1 to 1.4, but v2.0 is strongly recommended for faster speed, higher performance, better design and more friendly usage.
-
-![demo image](resources/coco_test_12510.jpg)

-### Major features
+<details open>
+<summary>Major features</summary>

 - **Modular Design**

@ -40,6 +49,8 @@ The old v1.x branch works with PyTorch 1.1 to 1.4, but v2.0 is strongly recommen
 - **State of the art**

  The toolbox stems from the codebase developed by the *MMDet* team, who won [COCO Detection Challenge](http://cocodataset.org/#detection-leaderboard) in 2018, and we keep pushing it forward.
+</details>
+

 Apart from MMDetection, we also released a library [mmcv](https://github.com/open-mmlab/mmcv) for computer vision research, which is heavily depended on by this toolbox.

@ -49,15 +60,22 @@ This project is released under the [Apache 2.0 license](LICENSE).

 ## Changelog

-v2.17.0 was released in 28/09/2021.
+**2.17.0** was released in 28/09/2021:
+- Support PVT, PVTv2 and SOLO.
+- Support large scale jittering and New Mask R-CNN baselines.
+- Speed up YOLOv3 inference.
+
 Please refer to [changelog.md](docs/changelog.md) for details and release history.
-A comparison between v1.x and v2.0 codebases can be found in [compatibility.md](docs/compatibility.md).
+
+For compatibility changes between different versions of MMDetection, please refer to [compatibility.md](docs/compatibility.md).

 ## Benchmark and model zoo

 Results and models are available in the [model zoo](docs/model_zoo.md).

-Supported backbones:
+
+<details open>
+<summary>Supported backbones:</summary>

 - [x] ResNet (CVPR'2016)
 - [x] ResNeXt (CVPR'2017)
@ -70,8 +88,10 @@ Supported backbones:
 - [X] Swin (CVPR'2021)
 - [x] PVT (ICCV'2021)
 - [x] PVTv2 (ArXiv'2021)
+</details>

-Supported methods:
+<details open>
+<summary>Supported methods:</summary>

 - [x] [RPN (NeurIPS'2015)](configs/rpn)
 - [x] [Fast R-CNN (ICCV'2015)](configs/fast_rcnn)
@ -127,6 +147,7 @@ Supported methods:
 - [x] [CenterNet (CVPR'2019)](configs/centernet/README.md)
 - [x] [YOLOX (ArXiv'2021)](configs/yolox/README.md)
 - [x] [SOLO (ECCV'2020)](configs/solo/README.md)
+</details>

 Some other methods are also supported in [projects using MMDetection](./docs/projects.md).

@ -144,7 +165,7 @@ Please refer to [FAQ](docs/faq.md) for frequently asked questions.

 ## Contributing

-We appreciate all contributions to improve MMDetection. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.
+We appreciate all contributions to improve MMDetection. Ongoing projects can be found in out [GitHub Projects](https://github.com/open-mmlab/mmdetection/projects). Welcome community users to participate in these projects. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.

 ## Acknowledgement

--- a/README_zh-CN.md
+++ b/README_zh-CN.md
@ -1,10 +1,26 @@
 <div align="center">
  <img src="resources/mmdet-logo.png" width="600"/>
-</div>

-**新闻**: 我们在 [ArXiv](https://arxiv.org/abs/1906.07155) 上公开了技术报告。

-文档: https://mmdetection.readthedocs.io/
+[![PyPI](https://img.shields.io/pypi/v/mmdet)](https://pypi.org/project/mmdet)
+[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmdetection.readthedocs.io/en/latest/)
+[![badge](https://github.com/open-mmlab/mmdetection/workflows/build/badge.svg)](https://github.com/open-mmlab/mmdetection/actions)
+[![codecov](https://codecov.io/gh/open-mmlab/mmdetection/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmdetection)
+[![license](https://img.shields.io/github/license/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/blob/master/LICENSE)
+[![open issues](https://isitmaintained.com/badge/open/open-mmlab/mmdetection.svg)](https://github.com/open-mmlab/mmdetection/issues)
+
+
+  <img src="https://user-images.githubusercontent.com/12907710/137271636-56ba1cd2-b110-4812-8221-b4c120320aa9.png"/>
+
+
+[📘使用文档](https://mmdetection.readthedocs.io/zh_CN/v2.17.0/) |
+[🛠️安装教程](https://mmdetection.readthedocs.io/zh_CN/v2.17.0/get_started.html) |
+[👀模型库](https://mmdetection.readthedocs.io/zh_CN/v2.17.0/model_zoo.html) |
+[🆕更新日志](https://mmdetection.readthedocs.io/en/v2.17.0/changelog.html) |
+[🚀进行中的项目](https://github.com/open-mmlab/mmdetection/projects) |
+[🤔报告问题](https://github.com/open-mmlab/mmdetection/issues/new/choose)
+
+</div>

 ## 简介

@ -14,11 +30,9 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope

 主分支代码目前支持 PyTorch 1.3 以上的版本。

-v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户使用新的 2.x 的版本，新的版本速度更快，性能更高，有更优雅的代码设计，对用户使用也更加友好。
-
-![demo image](resources/coco_test_12510.jpg)

-### 主要特性
+<details open>
+<summary>主要特性</summary>

 - **模块化设计**

@ -35,6 +49,7 @@ v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户
 - **性能高**

  MMDetection 这个算法库源自于 COCO 2018 目标检测竞赛的冠军团队 *MMDet* 团队开发的代码，我们在之后持续进行了改进和提升。
+</details>

 除了 MMDetection 之外，我们还开源了计算机视觉基础库 [MMCV](https://github.com/open-mmlab/mmcv)，MMCV 是 MMDetection 的主要依赖。

@ -44,15 +59,21 @@ v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户

 ## 更新日志

-最新的月度版本 v2.17.0 在 2021.09.28 发布。
+最新的 **2.17.0** 版本已经在2021.09.28发布:
+- 支持了 PVT, PVTv2 and SOLO。
+- 支持了 large scale jittering 并且增加了新的 Mask R-CNN 基线模型。
+- 提升 YOLOv3 的推理速度。
+
 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)。
-在[兼容性说明文档](docs_zh-CN/compatibility.md)中我们提供了 1.x 和 2.0 版本的详细比较。
+
+如果想了解 MMDetection 不同版本之间的兼容性, 请参考[兼容性说明文档](docs/compatibility.md)。

 ## 基准测试和模型库

 测试结果和模型可以在[模型库](docs/model_zoo.md)中找到。

-已支持的骨干网络：
+<details open>
+<summary>已支持的骨干网络：</summary>

 - [x] ResNet (CVPR'2016)
 - [x] ResNeXt (CVPR'2017)
@ -65,8 +86,10 @@ v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户
 - [X] Swin (CVPR'2021)
 - [x] PVT (ICCV'2021)
 - [x] PVTv2 (ArXiv'2021)
+</details>

-已支持的算法：
+<details open>
+<summary>已支持的算法：</summary>

 - [x] [RPN (NeurIPS'2015)](configs/rpn)
 - [x] [Fast R-CNN (ICCV'2015)](configs/fast_rcnn)
@ -122,6 +145,7 @@ v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户
 - [x] [CenterNet (CVPR'2019)](configs/centernet/README.md)
 - [x] [YOLOX (ArXiv'2021)](configs/yolox/README.md)
 - [x] [SOLO (ECCV'2020)](configs/solo/README.md)
+</details>

 我们在[基于 MMDetection 的项目](./docs/projects.md)中列举了一些其他的支持的算法。

@ -140,7 +164,7 @@ v1.x 的历史版本支持 PyTorch 1.1 到 1.4，但是我们强烈建议用户

 ## 贡献指南

-我们感谢所有的贡献者为改进和提升 MMDetection 所作出的努力。请参考[贡献指南](.github/CONTRIBUTING.md)来了解参与项目贡献的相关指引。
+我们感谢所有的贡献者为改进和提升 MMDetection 所作出的努力。我们将正在进行中的项目添加进了[GitHub Projects](https://github.com/open-mmlab/mmdetection/projects)页面，非常欢迎社区用户能参与进这些项目中来。请参考[贡献指南](.github/CONTRIBUTING.md)来了解参与项目贡献的相关指引。

 ## 致谢

@ -184,7 +208,7 @@ MMDetection 是一款由来自不同高校和企业的研发人员共同参与
 扫描下方的二维码可关注 OpenMMLab 团队的 [知乎官方账号](https://www.zhihu.com/people/openmmlab)，加入 OpenMMLab 团队的 [官方交流 QQ 群](https://jq.qq.com/?_wv=1027&k=aCvMxdr3)

 <div align="center">
-<img src="/resources/zhihu_qrcode.jpg" height="400" />  <img src="/resources/qq_group_qrcode.jpg" height="400" />
+<img src="resources/zhihu_qrcode.jpg" height="400" />  <img src="resources/qq_group_qrcode.jpg" height="400" />
 </div>

 我们会在 OpenMMLab 社区为大家
--- a/docs/conf.py
+++ b/docs/conf.py
@ -85,7 +85,7 @@ html_theme_options = {
    'menu': [
        {
            'name': 'GitHub',
-            'url': 'https://github.com/open-mmlab/mmcv'
+            'url': 'https://github.com/open-mmlab/mmdetection'
        },
        {
            'name':
--- a/docs/projects.md
+++ b/docs/projects.md
@ -48,3 +48,10 @@ Methods already supported and maintained by MMDetection are not listed.
 - IterDet: Iterative Scheme for Object Detection in Crowded Environments. [[paper]](https://arxiv.org/abs/2005.05708)[[github]](https://github.com/saic-vul/iterdet)
 - Cross-Iteration Batch Normalization. [[paper]](https://arxiv.org/abs/2002.05712)[[github]](https://github.com/Howal/Cross-iterationBatchNorm)
 - A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection, NeurIPS2020 [[paper]](https://arxiv.org/abs/2009.13592)[[github]](https://github.com/kemaloksuz/aLRPLoss)
+- RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder, NeurIPS2020 [[paper]](https://arxiv.org/abs/2010.15831)[[github]](https://github.com/microsoft/RelationNet2)
+- Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection, CVPR2021[[paper]](https://arxiv.org/abs/2011.12885)[[github]](https://github.com/implus/GFocalV2)
+- Instances as Queries, ICCV2021[[paper]](http://arxiv.org/abs/2105.01928)[[github]](https://github.com/hustvl/QueryInst)
+- Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, ICCV2021[[paper]](https://arxiv.org/abs/2103.14030)[[github]](https://github.com/SwinTransformer/)
+- Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers, NeurIPS2021[[paper]](https://arxiv.org/abs/2107.00641)[[github]](https://github.com/microsoft/Focal-Transformer)
+- End-to-End Semi-Supervised Object Detection with Soft Teacher, ICCV2021[[paper]](https://arxiv.org/abs/2106.09018)[[github]](https://github.com/microsoft/SoftTeacher)
+- CBNetV2: A Novel Composite Backbone Network Architecture for Object Detection [[paper]](http://arxiv.org/abs/2107.00420)[[github]](https://github.com/VDIGPKU/CBNetV2)
--- a/docs_zh-CN/conf.py
+++ b/docs_zh-CN/conf.py
@ -85,7 +85,7 @@ html_theme_options = {
    'menu': [
        {
            'name': 'GitHub',
-            'url': 'https://github.com/open-mmlab/mmcv'
+            'url': 'https://github.com/open-mmlab/mmdetection'
        },
        {
            'name':