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update docs
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@Tau-J
Tau-J committed Aug 14, 2023
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41 changes: 4 additions & 37 deletions README.md
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Expand Up @@ -130,43 +130,7 @@ https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-

## 0.x / 1.x Migration

MMPose v1.0.0 is a major update, including many API and config file changes. Currently, a part of the algorithms have been migrated to v1.0.0, and the remaining algorithms will be completed in subsequent versions. We will show the migration progress in the following list.

<details close>
<summary><b>Migration Progress</b></summary>

| Algorithm | Status |
| :-------------------------------- | :---------: |
| MTUT (CVPR 2019) | |
| MSPN (ArXiv 2019) | done |
| InterNet (ECCV 2020) | |
| DEKR (CVPR 2021) | done |
| HigherHRNet (CVPR 2020) | |
| DeepPose (CVPR 2014) | done |
| RLE (ICCV 2021) | done |
| SoftWingloss (TIP 2021) | done |
| VideoPose3D (CVPR 2019) | done |
| Hourglass (ECCV 2016) | done |
| LiteHRNet (CVPR 2021) | done |
| AdaptiveWingloss (ICCV 2019) | done |
| SimpleBaseline2D (ECCV 2018) | done |
| PoseWarper (NeurIPS 2019) | |
| SimpleBaseline3D (ICCV 2017) | done |
| HMR (CVPR 2018) | |
| UDP (CVPR 2020) | done |
| VIPNAS (CVPR 2021) | done |
| Wingloss (CVPR 2018) | done |
| DarkPose (CVPR 2020) | done |
| Associative Embedding (NIPS 2017) | in progress |
| VoxelPose (ECCV 2020) | |
| RSN (ECCV 2020) | done |
| CID (CVPR 2022) | done |
| CPM (CVPR 2016) | done |
| HRNet (CVPR 2019) | done |
| HRNetv2 (TPAMI 2019) | done |
| SCNet (CVPR 2020) | done |

</details>
MMPose v1.0.0 is a major update, including many API and config file changes. Currently, a part of the algorithms have been migrated to v1.0.0, and the remaining algorithms will be completed in subsequent versions. We will show the migration progress in this [Roadmap](https://github.com/open-mmlab/mmpose/issues/2258).

If your algorithm has not been migrated, you can continue to use the [0.x branch](https://github.com/open-mmlab/mmpose/tree/0.x) and [old documentation](https://mmpose.readthedocs.io/en/0.x/).

Expand All @@ -186,6 +150,9 @@ We provided a series of tutorials about the basic usage of MMPose for new users:
- [Configs](https://mmpose.readthedocs.io/en/latest/user_guides/configs.html)
- [Prepare Datasets](https://mmpose.readthedocs.io/en/latest/user_guides/prepare_datasets.html)
- [Train and Test](https://mmpose.readthedocs.io/en/latest/user_guides/train_and_test.html)
- [Deployment](https://mmpose.readthedocs.io/en/dev-1.x/user_guides/how_to_deploy.html)
- [Model Analysis](https://mmpose.readthedocs.io/en/dev-1.x/user_guides/model_analysis.html)
- [Dataset Annotation and Preprocessing](https://mmpose.readthedocs.io/en/dev-1.x/user_guides/dataset_tools.html)

2. For developers who wish to develop based on MMPose:

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43 changes: 4 additions & 39 deletions README_CN.md
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## 0.x / 1.x 迁移

MMPose v1.0.0 是一个重大更新，包括了大量的 API 和配置文件的变化。目前 v1.0.0 中已经完成了一部分算法的迁移工作，剩余的算法将在后续的版本中陆续完成，我们将在下面的列表中展示迁移进度。

<details close>
<summary><b>迁移进度</b></summary>

| 算法名称 | 迁移进度 |
| :-------------------------------- | :---------: |
| MTUT (CVPR 2019) | |
| MSPN (ArXiv 2019) | done |
| InterNet (ECCV 2020) | |
| DEKR (CVPR 2021) | done |
| HigherHRNet (CVPR 2020) | |
| DeepPose (CVPR 2014) | done |
| RLE (ICCV 2021) | done |
| SoftWingloss (TIP 2021) | done |
| VideoPose3D (CVPR 2019) | done |
| Hourglass (ECCV 2016) | done |
| LiteHRNet (CVPR 2021) | done |
| AdaptiveWingloss (ICCV 2019) | done |
| SimpleBaseline2D (ECCV 2018) | done |
| PoseWarper (NeurIPS 2019) | |
| SimpleBaseline3D (ICCV 2017) | done |
| HMR (CVPR 2018) | |
| UDP (CVPR 2020) | done |
| VIPNAS (CVPR 2021) | done |
| Wingloss (CVPR 2018) | done |
| DarkPose (CVPR 2020) | done |
| Associative Embedding (NIPS 2017) | in progress |
| VoxelPose (ECCV 2020) | |
| RSN (ECCV 2020) | done |
| CID (CVPR 2022) | done |
| CPM (CVPR 2016) | done |
| HRNet (CVPR 2019) | done |
| HRNetv2 (TPAMI 2019) | done |
| SCNet (CVPR 2020) | done |

</details>
MMPose v1.0.0 是一个重大更新，包括了大量的 API 和配置文件的变化。目前 v1.0.0 中已经完成了一部分算法的迁移工作，剩余的算法将在后续的版本中陆续完成，我们将在这个 [Issue 页面](https://github.com/open-mmlab/mmpose/issues/2258) 中展示迁移进度。

如果您使用的算法还没有完成迁移，您也可以继续使用访问 [0.x 分支](https://github.com/open-mmlab/mmpose/tree/0.x) 和 [旧版文档](https://mmpose.readthedocs.io/zh_CN/0.x/)

Expand All @@ -184,6 +148,9 @@ MMPose v1.0.0 是一个重大更新，包括了大量的 API 和配置文件的
- [配置文件](https://mmpose.readthedocs.io/zh_CN/latest/user_guides/configs.html)
- [准备数据集](https://mmpose.readthedocs.io/zh_CN/latest/user_guides/prepare_datasets.html)
- [训练与测试](https://mmpose.readthedocs.io/zh_CN/latest/user_guides/train_and_test.html)
- [模型部署](https://mmpose.readthedocs.io/zh_CN/dev-1.x/user_guides/how_to_deploy.html)
- [模型分析工具](https://mmpose.readthedocs.io/zh_CN/dev-1.x/user_guides/model_analysis.html)
- [数据集标注与预处理脚本](https://mmpose.readthedocs.io/zh_CN/dev-1.x/user_guides/dataset_tools.html)

2. 对于希望基于 MMPose 进行开发的研究者和开发者：

Expand All @@ -194,8 +161,6 @@ MMPose v1.0.0 是一个重大更新，包括了大量的 API 和配置文件的
- [自定义数据变换](https://mmpose.readthedocs.io/zh_CN/latest/advanced_guides/customize_transforms.html)
- [自定义优化器](https://mmpose.readthedocs.io/zh_CN/latest/advanced_guides/customize_optimizer.html)
- [自定义日志](https://mmpose.readthedocs.io/zh_CN/latest/advanced_guides/customize_logging.html)
- [模型部署](https://mmpose.readthedocs.io/zh_CN/latest/advanced_guides/how_to_deploy.html)
- [模型分析工具](https://mmpose.readthedocs.io/zh_CN/latest/advanced_guides/model_analysis.html)
- [迁移指南](https://mmpose.readthedocs.io/zh_CN/latest/migration.html)

3. 对于希望加入开源社区，向 MMPose 贡献代码的研究者和开发者：
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