diff options
| author | CoprDistGit <infra@openeuler.org> | 2023-05-18 04:17:43 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-05-18 04:17:43 +0000 |
| commit | 5e8ff27bbb14fc4cad59372da17160080d0f4032 (patch) | |
| tree | f8f016844f336474878b0f72d58dbb14e7d47514 /python-mmpose.spec | |
| parent | d2c52dfdec5f22582b66dda3f921b0b2ac2cbe62 (diff) | |
automatic import of python-mmpose
Diffstat (limited to 'python-mmpose.spec')
| -rw-r--r-- | python-mmpose.spec | 1082 |
1 files changed, 1082 insertions, 0 deletions
diff --git a/python-mmpose.spec b/python-mmpose.spec new file mode 100644 index 0000000..13f7b19 --- /dev/null +++ b/python-mmpose.spec @@ -0,0 +1,1082 @@ +%global _empty_manifest_terminate_build 0 +Name: python-mmpose +Version: 1.0.0 +Release: 1 +Summary: OpenMMLab Pose Estimation Toolbox and Benchmark. +License: Apache License 2.0 +URL: https://github.com/open-mmlab/mmpose +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/78/f3/7e7fefa16762f0400d3898cf70dc06c28b99bfcebbf125230ed01ab5108f/mmpose-1.0.0.tar.gz +BuildArch: noarch + +Requires: python3-chumpy +Requires: python3-json-tricks +Requires: python3-matplotlib +Requires: python3-munkres +Requires: python3-numpy +Requires: python3-opencv-python +Requires: python3-pillow +Requires: python3-scipy +Requires: python3-torchvision +Requires: python3-xtcocotools +Requires: python3-numpy +Requires: python3-torch +Requires: python3-chumpy +Requires: python3-json-tricks +Requires: python3-matplotlib +Requires: python3-munkres +Requires: python3-opencv-python +Requires: python3-pillow +Requires: python3-scipy +Requires: python3-torchvision +Requires: python3-xtcocotools +Requires: python3-coverage +Requires: python3-flake8 +Requires: python3-interrogate +Requires: python3-isort +Requires: python3-parameterized +Requires: python3-pytest +Requires: python3-pytest-runner +Requires: python3-xdoctest +Requires: python3-yapf +Requires: python3-requests +Requires: python3-mmcv +Requires: python3-mmdet +Requires: python3-mmengine +Requires: python3-requests +Requires: python3-coverage +Requires: python3-flake8 +Requires: python3-interrogate +Requires: python3-isort +Requires: python3-parameterized +Requires: python3-pytest +Requires: python3-pytest-runner +Requires: python3-xdoctest +Requires: python3-yapf + +%description +<div align="center"> + <img src="resources/mmpose-logo.png" width="450"/> + <div> </div> + <div align="center"> + <b>OpenMMLab website</b> + <sup> + <a href="https://openmmlab.com"> + <i>HOT</i> + </a> + </sup> + + <b>OpenMMLab platform</b> + <sup> + <a href="https://platform.openmmlab.com"> + <i>TRY IT OUT</i> + </a> + </sup> + </div> + <div> </div> + +[](https://mmpose.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/open-mmlab/mmpose/actions) +[](https://codecov.io/gh/open-mmlab/mmpose) +[](https://pypi.org/project/mmpose/) +[](https://github.com/open-mmlab/mmpose/blob/master/LICENSE) +[](https://github.com/open-mmlab/mmpose/issues) +[](https://github.com/open-mmlab/mmpose/issues) + +[📘Documentation](https://mmpose.readthedocs.io/en/latest/) | +[🛠️Installation](https://mmpose.readthedocs.io/en/latest/installation.html) | +[👀Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) | +[📜Papers](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html) | +[🆕Update News](https://mmpose.readthedocs.io/en/latest/notes/changelog.html) | +[🤔Reporting Issues](https://github.com/open-mmlab/mmpose/issues/new/choose) | +[🔥RTMPose](/projects/rtmpose/) + +</div> + +<div align="center"> + <a href="https://openmmlab.medium.com/" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219255827-67c1a27f-f8c5-46a9-811d-5e57448c61d1.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://discord.com/channels/1037617289144569886/1072798105428299817" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://twitter.com/OpenMMLab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.youtube.com/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://space.bilibili.com/1293512903" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026751-d7d14cce-a7c9-4e82-9942-8375fca65b99.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.zhihu.com/people/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026120-ba71e48b-6e94-4bd4-b4e9-b7d175b5e362.png" width="3%" alt="" /></a> +</div> + +## Introduction + +English | [简体中文](README_CN.md) + +MMPose is an open-source toolbox for pose estimation based on PyTorch. +It is a part of the [OpenMMLab project](https://github.com/open-mmlab). + +The master branch works with **PyTorch 1.6+**. + +https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-84f6-24eeddbf4d91.mp4 + +<br/> + +<details close> +<summary><b>Major Features</b></summary> + +- **Support diverse tasks** + + We support a wide spectrum of mainstream pose analysis tasks in current research community, including 2d multi-person human pose estimation, 2d hand pose estimation, 2d face landmark detection, 133 keypoint whole-body human pose estimation, 3d human mesh recovery, fashion landmark detection and animal pose estimation. + See [Demo](demo/docs/) for more information. + +- **Higher efficiency and higher accuracy** + + MMPose implements multiple state-of-the-art (SOTA) deep learning models, including both top-down & bottom-up approaches. We achieve faster training speed and higher accuracy than other popular codebases, such as [HRNet](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch). + See [benchmark.md](docs/en/notes/benchmark.md) for more information. + +- **Support for various datasets** + + The toolbox directly supports multiple popular and representative datasets, COCO, AIC, MPII, MPII-TRB, OCHuman etc. + See [dataset_zoo](docs/en/dataset_zoo) for more information. + +- **Well designed, tested and documented** + + We decompose MMPose into different components and one can easily construct a customized + pose estimation framework by combining different modules. + We provide detailed documentation and API reference, as well as unittests. + +</details> + +## What's New + +- We are excited to release **YOLOX-Pose**, a One-Stage multi-person pose estimation model based on YOLOX. Checkout our [project page](/projects/yolox-pose/) for more details. + + + +- Welcome to [*projects of MMPose*](/projects/README.md), where you can access to the latest features of MMPose, and share your ideas and codes with the community at once. Contribution to MMPose will be simple and smooth: + + - Provide an easy and agile way to integrate algorithms, features and applications into MMPose + - Allow flexible code structure and style; only need a short code review process + - Build individual projects with full power of MMPose but not bound up with heavy frameworks + - Checkout new projects: + - [RTMPose](/projects/rtmpose/) + - [YOLOX-Pose](/projects/yolox-pose/) + - [MMPose4AIGC](/projects/mmpose4aigc/) + - Become a contributors and make MMPose greater. Start your journey from the [example project](/projects/example_project/) + +<br/> + +- 2022-04-06: MMPose [v1.0.0](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) is officially released, with the main updates including: + + - Release of [YOLOX-Pose](/projects/yolox-pose/), a One-Stage multi-person pose estimation model based on YOLOX + - Development of [MMPose for AIGC](/projects/mmpose4aigc/) based on RTMPose, generating high-quality skeleton images for Pose-guided AIGC projects + - Support for OpenPose-style skeleton visualization + - More complete and user-friendly [documentation and tutorials](https://mmpose.readthedocs.io/en/latest/overview.html) + + Please refer to the [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) for more updates brought by MMPose v1.0.0! + +## Installation + +Please refer to [installation.md](https://mmpose.readthedocs.io/en/latest/installation.html) for more detailed installation and dataset preparation. + +## Getting Started + +We provided a series of tutorials about the basic usage of MMPose for new users: + +1. For the basic usage of MMPose: + + - [A 20-minute Tour to MMPose](https://mmpose.readthedocs.io/en/latest/guide_to_framework.html) + - [Demos](https://mmpose.readthedocs.io/en/latest/demos.html) + - [Inference](https://mmpose.readthedocs.io/en/latest/user_guides/inference.html) + - [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) + +2. For developers who wish to develop based on MMPose: + + - [Learn about Codecs](https://mmpose.readthedocs.io/en/latest/advanced_guides/codecs.html) + - [Dataflow in MMPose](https://mmpose.readthedocs.io/en/latest/advanced_guides/dataflow.html) + - [Implement New Models](https://mmpose.readthedocs.io/en/latest/advanced_guides/implement_new_models.html) + - [Customize Datasets](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_datasets.html) + - [Customize Data Transforms](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_transforms.html) + - [Customize Optimizer](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_optimizer.html) + - [Customize Logging](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_logging.html) + - [How to Deploy](https://mmpose.readthedocs.io/en/latest/advanced_guides/how_to_deploy.html) + - [Model Analysis](https://mmpose.readthedocs.io/en/latest/advanced_guides/model_analysis.html) + - [Migration Guide](https://mmpose.readthedocs.io/en/latest/migration.html) + +3. For researchers and developers who are willing to contribute to MMPose: + + - [Contribution Guide](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) + +4. For some common issues, we provide a FAQ list: + + - [FAQ](https://mmpose.readthedocs.io/en/latest/faq.html) + +## Model Zoo + +Results and models are available in the **README.md** of each method's config directory. +A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) page. + +<details close> +<summary><b>Supported algorithms:</b></summary> + +- [x] [DeepPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#deeppose-cvpr-2014) (CVPR'2014) +- [x] [CPM](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#cpm-cvpr-2016) (CVPR'2016) +- [x] [Hourglass](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hourglass-eccv-2016) (ECCV'2016) +- [ ] [SimpleBaseline3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline3d-iccv-2017) (ICCV'2017) +- [ ] [Associative Embedding](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#associative-embedding-nips-2017) (NeurIPS'2017) +- [x] [SimpleBaseline2D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline2d-eccv-2018) (ECCV'2018) +- [x] [DSNT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#dsnt-2018) (ArXiv'2021) +- [x] [HRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnet-cvpr-2019) (CVPR'2019) +- [x] [IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#ipr-eccv-2018) (ECCV'2018) +- [ ] [VideoPose3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#videopose3d-cvpr-2019) (CVPR'2019) +- [x] [HRNetv2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnetv2-tpami-2019) (TPAMI'2019) +- [x] [MSPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mspn-arxiv-2019) (ArXiv'2019) +- [x] [SCNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#scnet-cvpr-2020) (CVPR'2020) +- [ ] [HigherHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#higherhrnet-cvpr-2020) (CVPR'2020) +- [x] [RSN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#rsn-eccv-2020) (ECCV'2020) +- [ ] [InterNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#internet-eccv-2020) (ECCV'2020) +- [ ] [VoxelPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#voxelpose-eccv-2020) (ECCV'2020) +- [x] [LiteHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#litehrnet-cvpr-2021) (CVPR'2021) +- [x] [ViPNAS](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vipnas-cvpr-2021) (CVPR'2021) +- [x] [Debias-IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#debias-ipr-iccv-2021) (ICCV'2021) +- [x] [SimCC](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simcc-eccv-2022) (ECCV'2022) + +</details> + +<details close> +<summary><b>Supported techniques:</b></summary> + +- [ ] [FPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fpn-cvpr-2017) (CVPR'2017) +- [ ] [FP16](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fp16-arxiv-2017) (ArXiv'2017) +- [ ] [Wingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#wingloss-cvpr-2018) (CVPR'2018) +- [ ] [AdaptiveWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#adaptivewingloss-iccv-2019) (ICCV'2019) +- [x] [DarkPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#darkpose-cvpr-2020) (CVPR'2020) +- [x] [UDP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#udp-cvpr-2020) (CVPR'2020) +- [ ] [Albumentations](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#albumentations-information-2020) (Information'2020) +- [ ] [SoftWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#softwingloss-tip-2021) (TIP'2021) +- [x] [RLE](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#rle-iccv-2021) (ICCV'2021) + +</details> + +<details close> +<summary><b>Supported datasets:</b></summary> + +- [x] [AFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#aflw-iccvw-2011) \[[homepage](https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/)\] (ICCVW'2011) +- [x] [sub-JHMDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#jhmdb-iccv-2013) \[[homepage](http://jhmdb.is.tue.mpg.de/dataset)\] (ICCV'2013) +- [x] [COFW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cofw-iccv-2013) \[[homepage](http://www.vision.caltech.edu/xpburgos/ICCV13/)\] (ICCV'2013) +- [x] [MPII](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-cvpr-2014) \[[homepage](http://human-pose.mpi-inf.mpg.de/)\] (CVPR'2014) +- [x] [Human3.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#human3-6m-tpami-2014) \[[homepage](http://vision.imar.ro/human3.6m/description.php)\] (TPAMI'2014) +- [x] [COCO](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-eccv-2014) \[[homepage](http://cocodataset.org/)\] (ECCV'2014) +- [x] [CMU Panoptic](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-iccv-2015) \[[homepage](http://domedb.perception.cs.cmu.edu/)\] (ICCV'2015) +- [x] [DeepFashion](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#deepfashion-cvpr-2016) \[[homepage](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion/LandmarkDetection.html)\] (CVPR'2016) +- [x] [300W](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#300w-imavis-2016) \[[homepage](https://ibug.doc.ic.ac.uk/resources/300-W/)\] (IMAVIS'2016) +- [x] [RHD](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#rhd-iccv-2017) \[[homepage](https://lmb.informatik.uni-freiburg.de/resources/datasets/RenderedHandposeDataset.en.html)\] (ICCV'2017) +- [x] [CMU Panoptic HandDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-handdb-cvpr-2017) \[[homepage](http://domedb.perception.cs.cmu.edu/handdb.html)\] (CVPR'2017) +- [x] [AI Challenger](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ai-challenger-arxiv-2017) \[[homepage](https://github.com/AIChallenger/AI_Challenger_2017)\] (ArXiv'2017) +- [x] [MHP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mhp-acm-mm-2018) \[[homepage](https://lv-mhp.github.io/dataset)\] (ACM MM'2018) +- [x] [WFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#wflw-cvpr-2018) \[[homepage](https://wywu.github.io/projects/LAB/WFLW.html)\] (CVPR'2018) +- [x] [PoseTrack18](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#posetrack18-cvpr-2018) \[[homepage](https://posetrack.net/users/download.php)\] (CVPR'2018) +- [x] [OCHuman](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ochuman-cvpr-2019) \[[homepage](https://github.com/liruilong940607/OCHumanApi)\] (CVPR'2019) +- [x] [CrowdPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#crowdpose-cvpr-2019) \[[homepage](https://github.com/Jeff-sjtu/CrowdPose)\] (CVPR'2019) +- [x] [MPII-TRB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-trb-iccv-2019) \[[homepage](https://github.com/kennymckormick/Triplet-Representation-of-human-Body)\] (ICCV'2019) +- [x] [FreiHand](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#freihand-iccv-2019) \[[homepage](https://lmb.informatik.uni-freiburg.de/projects/freihand/)\] (ICCV'2019) +- [x] [Animal-Pose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#animal-pose-iccv-2019) \[[homepage](https://sites.google.com/view/animal-pose/)\] (ICCV'2019) +- [x] [OneHand10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#onehand10k-tcsvt-2019) \[[homepage](https://www.yangangwang.com/papers/WANG-MCC-2018-10.html)\] (TCSVT'2019) +- [x] [Vinegar Fly](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#vinegar-fly-nature-methods-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Nature Methods'2019) +- [x] [Desert Locust](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#desert-locust-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [Grévy’s Zebra](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#grevys-zebra-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [ATRW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#atrw-acm-mm-2020) \[[homepage](https://cvwc2019.github.io/challenge.html)\] (ACM MM'2020) +- [x] [Halpe](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#halpe-cvpr-2020) \[[homepage](https://github.com/Fang-Haoshu/Halpe-FullBody/)\] (CVPR'2020) +- [x] [COCO-WholeBody](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-wholebody-eccv-2020) \[[homepage](https://github.com/jin-s13/COCO-WholeBody/)\] (ECCV'2020) +- [x] [MacaquePose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#macaquepose-biorxiv-2020) \[[homepage](http://www.pri.kyoto-u.ac.jp/datasets/macaquepose/index.html)\] (bioRxiv'2020) +- [x] [InterHand2.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#interhand2-6m-eccv-2020) \[[homepage](https://mks0601.github.io/InterHand2.6M/)\] (ECCV'2020) +- [x] [AP-10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ap-10k-neurips-2021) \[[homepage](https://github.com/AlexTheBad/AP-10K)\] (NeurIPS'2021) +- [x] [Horse-10](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#horse-10-wacv-2021) \[[homepage](http://www.mackenziemathislab.org/horse10)\] (WACV'2021) + +</details> + +<details close> +<summary><b>Supported backbones:</b></summary> + +- [x] [AlexNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#alexnet-neurips-2012) (NeurIPS'2012) +- [x] [VGG](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vgg-iclr-2015) (ICLR'2015) +- [x] [ResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnet-cvpr-2016) (CVPR'2016) +- [x] [ResNext](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnext-cvpr-2017) (CVPR'2017) +- [x] [SEResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#seresnet-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV1](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv1-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv2-eccv-2018) (ECCV'2018) +- [x] [MobilenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mobilenetv2-cvpr-2018) (CVPR'2018) +- [x] [ResNetV1D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnetv1d-cvpr-2019) (CVPR'2019) +- [x] [ResNeSt](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnest-arxiv-2020) (ArXiv'2020) +- [x] [Swin](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#swin-cvpr-2021) (CVPR'2021) +- [x] [HRFormer](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrformer-nips-2021) (NIPS'2021) +- [x] [PVT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvt-iccv-2021) (ICCV'2021) +- [x] [PVTV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvtv2-cvmj-2022) (CVMJ'2022) + +</details> + +### Model Request + +We will keep up with the latest progress of the community, and support more popular algorithms and frameworks. If you have any feature requests, please feel free to leave a comment in [MMPose Roadmap](https://github.com/open-mmlab/mmpose/issues/9). + +## Contributing + +We appreciate all contributions to improve MMPose. Please refer to [CONTRIBUTING.md](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) for the contributing guideline. + +## Acknowledgement + +MMPose is an open source project that is contributed by researchers and engineers from various colleges and companies. +We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. +We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models. + +## Citation + +If you find this project useful in your research, please consider cite: + +```bibtex +@misc{mmpose2020, + title={OpenMMLab Pose Estimation Toolbox and Benchmark}, + author={MMPose Contributors}, + howpublished = {\url{https://github.com/open-mmlab/mmpose}}, + year={2020} +} +``` + +## License + +This project is released under the [Apache 2.0 license](LICENSE). + +## Projects in OpenMMLab + +- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models. +- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision. +- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages. +- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark. +- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark. +- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection. +- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark. +- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark. +- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox. +- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark. +- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark. +- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark. +- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark. +- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark. +- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark. +- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark. +- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark. +- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox. +- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox. +- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab Model Deployment Framework. + + + + +%package -n python3-mmpose +Summary: OpenMMLab Pose Estimation Toolbox and Benchmark. +Provides: python-mmpose +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-mmpose +<div align="center"> + <img src="resources/mmpose-logo.png" width="450"/> + <div> </div> + <div align="center"> + <b>OpenMMLab website</b> + <sup> + <a href="https://openmmlab.com"> + <i>HOT</i> + </a> + </sup> + + <b>OpenMMLab platform</b> + <sup> + <a href="https://platform.openmmlab.com"> + <i>TRY IT OUT</i> + </a> + </sup> + </div> + <div> </div> + +[](https://mmpose.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/open-mmlab/mmpose/actions) +[](https://codecov.io/gh/open-mmlab/mmpose) +[](https://pypi.org/project/mmpose/) +[](https://github.com/open-mmlab/mmpose/blob/master/LICENSE) +[](https://github.com/open-mmlab/mmpose/issues) +[](https://github.com/open-mmlab/mmpose/issues) + +[📘Documentation](https://mmpose.readthedocs.io/en/latest/) | +[🛠️Installation](https://mmpose.readthedocs.io/en/latest/installation.html) | +[👀Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) | +[📜Papers](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html) | +[🆕Update News](https://mmpose.readthedocs.io/en/latest/notes/changelog.html) | +[🤔Reporting Issues](https://github.com/open-mmlab/mmpose/issues/new/choose) | +[🔥RTMPose](/projects/rtmpose/) + +</div> + +<div align="center"> + <a href="https://openmmlab.medium.com/" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219255827-67c1a27f-f8c5-46a9-811d-5e57448c61d1.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://discord.com/channels/1037617289144569886/1072798105428299817" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://twitter.com/OpenMMLab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.youtube.com/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://space.bilibili.com/1293512903" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026751-d7d14cce-a7c9-4e82-9942-8375fca65b99.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.zhihu.com/people/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026120-ba71e48b-6e94-4bd4-b4e9-b7d175b5e362.png" width="3%" alt="" /></a> +</div> + +## Introduction + +English | [简体中文](README_CN.md) + +MMPose is an open-source toolbox for pose estimation based on PyTorch. +It is a part of the [OpenMMLab project](https://github.com/open-mmlab). + +The master branch works with **PyTorch 1.6+**. + +https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-84f6-24eeddbf4d91.mp4 + +<br/> + +<details close> +<summary><b>Major Features</b></summary> + +- **Support diverse tasks** + + We support a wide spectrum of mainstream pose analysis tasks in current research community, including 2d multi-person human pose estimation, 2d hand pose estimation, 2d face landmark detection, 133 keypoint whole-body human pose estimation, 3d human mesh recovery, fashion landmark detection and animal pose estimation. + See [Demo](demo/docs/) for more information. + +- **Higher efficiency and higher accuracy** + + MMPose implements multiple state-of-the-art (SOTA) deep learning models, including both top-down & bottom-up approaches. We achieve faster training speed and higher accuracy than other popular codebases, such as [HRNet](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch). + See [benchmark.md](docs/en/notes/benchmark.md) for more information. + +- **Support for various datasets** + + The toolbox directly supports multiple popular and representative datasets, COCO, AIC, MPII, MPII-TRB, OCHuman etc. + See [dataset_zoo](docs/en/dataset_zoo) for more information. + +- **Well designed, tested and documented** + + We decompose MMPose into different components and one can easily construct a customized + pose estimation framework by combining different modules. + We provide detailed documentation and API reference, as well as unittests. + +</details> + +## What's New + +- We are excited to release **YOLOX-Pose**, a One-Stage multi-person pose estimation model based on YOLOX. Checkout our [project page](/projects/yolox-pose/) for more details. + + + +- Welcome to [*projects of MMPose*](/projects/README.md), where you can access to the latest features of MMPose, and share your ideas and codes with the community at once. Contribution to MMPose will be simple and smooth: + + - Provide an easy and agile way to integrate algorithms, features and applications into MMPose + - Allow flexible code structure and style; only need a short code review process + - Build individual projects with full power of MMPose but not bound up with heavy frameworks + - Checkout new projects: + - [RTMPose](/projects/rtmpose/) + - [YOLOX-Pose](/projects/yolox-pose/) + - [MMPose4AIGC](/projects/mmpose4aigc/) + - Become a contributors and make MMPose greater. Start your journey from the [example project](/projects/example_project/) + +<br/> + +- 2022-04-06: MMPose [v1.0.0](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) is officially released, with the main updates including: + + - Release of [YOLOX-Pose](/projects/yolox-pose/), a One-Stage multi-person pose estimation model based on YOLOX + - Development of [MMPose for AIGC](/projects/mmpose4aigc/) based on RTMPose, generating high-quality skeleton images for Pose-guided AIGC projects + - Support for OpenPose-style skeleton visualization + - More complete and user-friendly [documentation and tutorials](https://mmpose.readthedocs.io/en/latest/overview.html) + + Please refer to the [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) for more updates brought by MMPose v1.0.0! + +## Installation + +Please refer to [installation.md](https://mmpose.readthedocs.io/en/latest/installation.html) for more detailed installation and dataset preparation. + +## Getting Started + +We provided a series of tutorials about the basic usage of MMPose for new users: + +1. For the basic usage of MMPose: + + - [A 20-minute Tour to MMPose](https://mmpose.readthedocs.io/en/latest/guide_to_framework.html) + - [Demos](https://mmpose.readthedocs.io/en/latest/demos.html) + - [Inference](https://mmpose.readthedocs.io/en/latest/user_guides/inference.html) + - [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) + +2. For developers who wish to develop based on MMPose: + + - [Learn about Codecs](https://mmpose.readthedocs.io/en/latest/advanced_guides/codecs.html) + - [Dataflow in MMPose](https://mmpose.readthedocs.io/en/latest/advanced_guides/dataflow.html) + - [Implement New Models](https://mmpose.readthedocs.io/en/latest/advanced_guides/implement_new_models.html) + - [Customize Datasets](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_datasets.html) + - [Customize Data Transforms](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_transforms.html) + - [Customize Optimizer](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_optimizer.html) + - [Customize Logging](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_logging.html) + - [How to Deploy](https://mmpose.readthedocs.io/en/latest/advanced_guides/how_to_deploy.html) + - [Model Analysis](https://mmpose.readthedocs.io/en/latest/advanced_guides/model_analysis.html) + - [Migration Guide](https://mmpose.readthedocs.io/en/latest/migration.html) + +3. For researchers and developers who are willing to contribute to MMPose: + + - [Contribution Guide](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) + +4. For some common issues, we provide a FAQ list: + + - [FAQ](https://mmpose.readthedocs.io/en/latest/faq.html) + +## Model Zoo + +Results and models are available in the **README.md** of each method's config directory. +A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) page. + +<details close> +<summary><b>Supported algorithms:</b></summary> + +- [x] [DeepPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#deeppose-cvpr-2014) (CVPR'2014) +- [x] [CPM](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#cpm-cvpr-2016) (CVPR'2016) +- [x] [Hourglass](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hourglass-eccv-2016) (ECCV'2016) +- [ ] [SimpleBaseline3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline3d-iccv-2017) (ICCV'2017) +- [ ] [Associative Embedding](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#associative-embedding-nips-2017) (NeurIPS'2017) +- [x] [SimpleBaseline2D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline2d-eccv-2018) (ECCV'2018) +- [x] [DSNT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#dsnt-2018) (ArXiv'2021) +- [x] [HRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnet-cvpr-2019) (CVPR'2019) +- [x] [IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#ipr-eccv-2018) (ECCV'2018) +- [ ] [VideoPose3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#videopose3d-cvpr-2019) (CVPR'2019) +- [x] [HRNetv2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnetv2-tpami-2019) (TPAMI'2019) +- [x] [MSPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mspn-arxiv-2019) (ArXiv'2019) +- [x] [SCNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#scnet-cvpr-2020) (CVPR'2020) +- [ ] [HigherHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#higherhrnet-cvpr-2020) (CVPR'2020) +- [x] [RSN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#rsn-eccv-2020) (ECCV'2020) +- [ ] [InterNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#internet-eccv-2020) (ECCV'2020) +- [ ] [VoxelPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#voxelpose-eccv-2020) (ECCV'2020) +- [x] [LiteHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#litehrnet-cvpr-2021) (CVPR'2021) +- [x] [ViPNAS](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vipnas-cvpr-2021) (CVPR'2021) +- [x] [Debias-IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#debias-ipr-iccv-2021) (ICCV'2021) +- [x] [SimCC](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simcc-eccv-2022) (ECCV'2022) + +</details> + +<details close> +<summary><b>Supported techniques:</b></summary> + +- [ ] [FPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fpn-cvpr-2017) (CVPR'2017) +- [ ] [FP16](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fp16-arxiv-2017) (ArXiv'2017) +- [ ] [Wingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#wingloss-cvpr-2018) (CVPR'2018) +- [ ] [AdaptiveWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#adaptivewingloss-iccv-2019) (ICCV'2019) +- [x] [DarkPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#darkpose-cvpr-2020) (CVPR'2020) +- [x] [UDP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#udp-cvpr-2020) (CVPR'2020) +- [ ] [Albumentations](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#albumentations-information-2020) (Information'2020) +- [ ] [SoftWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#softwingloss-tip-2021) (TIP'2021) +- [x] [RLE](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#rle-iccv-2021) (ICCV'2021) + +</details> + +<details close> +<summary><b>Supported datasets:</b></summary> + +- [x] [AFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#aflw-iccvw-2011) \[[homepage](https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/)\] (ICCVW'2011) +- [x] [sub-JHMDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#jhmdb-iccv-2013) \[[homepage](http://jhmdb.is.tue.mpg.de/dataset)\] (ICCV'2013) +- [x] [COFW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cofw-iccv-2013) \[[homepage](http://www.vision.caltech.edu/xpburgos/ICCV13/)\] (ICCV'2013) +- [x] [MPII](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-cvpr-2014) \[[homepage](http://human-pose.mpi-inf.mpg.de/)\] (CVPR'2014) +- [x] [Human3.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#human3-6m-tpami-2014) \[[homepage](http://vision.imar.ro/human3.6m/description.php)\] (TPAMI'2014) +- [x] [COCO](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-eccv-2014) \[[homepage](http://cocodataset.org/)\] (ECCV'2014) +- [x] [CMU Panoptic](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-iccv-2015) \[[homepage](http://domedb.perception.cs.cmu.edu/)\] (ICCV'2015) +- [x] [DeepFashion](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#deepfashion-cvpr-2016) \[[homepage](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion/LandmarkDetection.html)\] (CVPR'2016) +- [x] [300W](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#300w-imavis-2016) \[[homepage](https://ibug.doc.ic.ac.uk/resources/300-W/)\] (IMAVIS'2016) +- [x] [RHD](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#rhd-iccv-2017) \[[homepage](https://lmb.informatik.uni-freiburg.de/resources/datasets/RenderedHandposeDataset.en.html)\] (ICCV'2017) +- [x] [CMU Panoptic HandDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-handdb-cvpr-2017) \[[homepage](http://domedb.perception.cs.cmu.edu/handdb.html)\] (CVPR'2017) +- [x] [AI Challenger](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ai-challenger-arxiv-2017) \[[homepage](https://github.com/AIChallenger/AI_Challenger_2017)\] (ArXiv'2017) +- [x] [MHP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mhp-acm-mm-2018) \[[homepage](https://lv-mhp.github.io/dataset)\] (ACM MM'2018) +- [x] [WFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#wflw-cvpr-2018) \[[homepage](https://wywu.github.io/projects/LAB/WFLW.html)\] (CVPR'2018) +- [x] [PoseTrack18](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#posetrack18-cvpr-2018) \[[homepage](https://posetrack.net/users/download.php)\] (CVPR'2018) +- [x] [OCHuman](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ochuman-cvpr-2019) \[[homepage](https://github.com/liruilong940607/OCHumanApi)\] (CVPR'2019) +- [x] [CrowdPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#crowdpose-cvpr-2019) \[[homepage](https://github.com/Jeff-sjtu/CrowdPose)\] (CVPR'2019) +- [x] [MPII-TRB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-trb-iccv-2019) \[[homepage](https://github.com/kennymckormick/Triplet-Representation-of-human-Body)\] (ICCV'2019) +- [x] [FreiHand](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#freihand-iccv-2019) \[[homepage](https://lmb.informatik.uni-freiburg.de/projects/freihand/)\] (ICCV'2019) +- [x] [Animal-Pose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#animal-pose-iccv-2019) \[[homepage](https://sites.google.com/view/animal-pose/)\] (ICCV'2019) +- [x] [OneHand10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#onehand10k-tcsvt-2019) \[[homepage](https://www.yangangwang.com/papers/WANG-MCC-2018-10.html)\] (TCSVT'2019) +- [x] [Vinegar Fly](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#vinegar-fly-nature-methods-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Nature Methods'2019) +- [x] [Desert Locust](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#desert-locust-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [Grévy’s Zebra](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#grevys-zebra-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [ATRW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#atrw-acm-mm-2020) \[[homepage](https://cvwc2019.github.io/challenge.html)\] (ACM MM'2020) +- [x] [Halpe](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#halpe-cvpr-2020) \[[homepage](https://github.com/Fang-Haoshu/Halpe-FullBody/)\] (CVPR'2020) +- [x] [COCO-WholeBody](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-wholebody-eccv-2020) \[[homepage](https://github.com/jin-s13/COCO-WholeBody/)\] (ECCV'2020) +- [x] [MacaquePose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#macaquepose-biorxiv-2020) \[[homepage](http://www.pri.kyoto-u.ac.jp/datasets/macaquepose/index.html)\] (bioRxiv'2020) +- [x] [InterHand2.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#interhand2-6m-eccv-2020) \[[homepage](https://mks0601.github.io/InterHand2.6M/)\] (ECCV'2020) +- [x] [AP-10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ap-10k-neurips-2021) \[[homepage](https://github.com/AlexTheBad/AP-10K)\] (NeurIPS'2021) +- [x] [Horse-10](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#horse-10-wacv-2021) \[[homepage](http://www.mackenziemathislab.org/horse10)\] (WACV'2021) + +</details> + +<details close> +<summary><b>Supported backbones:</b></summary> + +- [x] [AlexNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#alexnet-neurips-2012) (NeurIPS'2012) +- [x] [VGG](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vgg-iclr-2015) (ICLR'2015) +- [x] [ResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnet-cvpr-2016) (CVPR'2016) +- [x] [ResNext](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnext-cvpr-2017) (CVPR'2017) +- [x] [SEResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#seresnet-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV1](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv1-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv2-eccv-2018) (ECCV'2018) +- [x] [MobilenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mobilenetv2-cvpr-2018) (CVPR'2018) +- [x] [ResNetV1D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnetv1d-cvpr-2019) (CVPR'2019) +- [x] [ResNeSt](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnest-arxiv-2020) (ArXiv'2020) +- [x] [Swin](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#swin-cvpr-2021) (CVPR'2021) +- [x] [HRFormer](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrformer-nips-2021) (NIPS'2021) +- [x] [PVT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvt-iccv-2021) (ICCV'2021) +- [x] [PVTV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvtv2-cvmj-2022) (CVMJ'2022) + +</details> + +### Model Request + +We will keep up with the latest progress of the community, and support more popular algorithms and frameworks. If you have any feature requests, please feel free to leave a comment in [MMPose Roadmap](https://github.com/open-mmlab/mmpose/issues/9). + +## Contributing + +We appreciate all contributions to improve MMPose. Please refer to [CONTRIBUTING.md](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) for the contributing guideline. + +## Acknowledgement + +MMPose is an open source project that is contributed by researchers and engineers from various colleges and companies. +We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. +We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models. + +## Citation + +If you find this project useful in your research, please consider cite: + +```bibtex +@misc{mmpose2020, + title={OpenMMLab Pose Estimation Toolbox and Benchmark}, + author={MMPose Contributors}, + howpublished = {\url{https://github.com/open-mmlab/mmpose}}, + year={2020} +} +``` + +## License + +This project is released under the [Apache 2.0 license](LICENSE). + +## Projects in OpenMMLab + +- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models. +- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision. +- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages. +- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark. +- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark. +- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection. +- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark. +- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark. +- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox. +- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark. +- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark. +- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark. +- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark. +- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark. +- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark. +- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark. +- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark. +- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox. +- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox. +- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab Model Deployment Framework. + + + + +%package help +Summary: Development documents and examples for mmpose +Provides: python3-mmpose-doc +%description help +<div align="center"> + <img src="resources/mmpose-logo.png" width="450"/> + <div> </div> + <div align="center"> + <b>OpenMMLab website</b> + <sup> + <a href="https://openmmlab.com"> + <i>HOT</i> + </a> + </sup> + + <b>OpenMMLab platform</b> + <sup> + <a href="https://platform.openmmlab.com"> + <i>TRY IT OUT</i> + </a> + </sup> + </div> + <div> </div> + +[](https://mmpose.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/open-mmlab/mmpose/actions) +[](https://codecov.io/gh/open-mmlab/mmpose) +[](https://pypi.org/project/mmpose/) +[](https://github.com/open-mmlab/mmpose/blob/master/LICENSE) +[](https://github.com/open-mmlab/mmpose/issues) +[](https://github.com/open-mmlab/mmpose/issues) + +[📘Documentation](https://mmpose.readthedocs.io/en/latest/) | +[🛠️Installation](https://mmpose.readthedocs.io/en/latest/installation.html) | +[👀Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) | +[📜Papers](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html) | +[🆕Update News](https://mmpose.readthedocs.io/en/latest/notes/changelog.html) | +[🤔Reporting Issues](https://github.com/open-mmlab/mmpose/issues/new/choose) | +[🔥RTMPose](/projects/rtmpose/) + +</div> + +<div align="center"> + <a href="https://openmmlab.medium.com/" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219255827-67c1a27f-f8c5-46a9-811d-5e57448c61d1.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://discord.com/channels/1037617289144569886/1072798105428299817" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://twitter.com/OpenMMLab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.youtube.com/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://space.bilibili.com/1293512903" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026751-d7d14cce-a7c9-4e82-9942-8375fca65b99.png" width="3%" alt="" /></a> + <img src="https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png" width="3%" alt="" /> + <a href="https://www.zhihu.com/people/openmmlab" style="text-decoration:none;"> + <img src="https://user-images.githubusercontent.com/25839884/219026120-ba71e48b-6e94-4bd4-b4e9-b7d175b5e362.png" width="3%" alt="" /></a> +</div> + +## Introduction + +English | [简体中文](README_CN.md) + +MMPose is an open-source toolbox for pose estimation based on PyTorch. +It is a part of the [OpenMMLab project](https://github.com/open-mmlab). + +The master branch works with **PyTorch 1.6+**. + +https://user-images.githubusercontent.com/15977946/124654387-0fd3c500-ded1-11eb-84f6-24eeddbf4d91.mp4 + +<br/> + +<details close> +<summary><b>Major Features</b></summary> + +- **Support diverse tasks** + + We support a wide spectrum of mainstream pose analysis tasks in current research community, including 2d multi-person human pose estimation, 2d hand pose estimation, 2d face landmark detection, 133 keypoint whole-body human pose estimation, 3d human mesh recovery, fashion landmark detection and animal pose estimation. + See [Demo](demo/docs/) for more information. + +- **Higher efficiency and higher accuracy** + + MMPose implements multiple state-of-the-art (SOTA) deep learning models, including both top-down & bottom-up approaches. We achieve faster training speed and higher accuracy than other popular codebases, such as [HRNet](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch). + See [benchmark.md](docs/en/notes/benchmark.md) for more information. + +- **Support for various datasets** + + The toolbox directly supports multiple popular and representative datasets, COCO, AIC, MPII, MPII-TRB, OCHuman etc. + See [dataset_zoo](docs/en/dataset_zoo) for more information. + +- **Well designed, tested and documented** + + We decompose MMPose into different components and one can easily construct a customized + pose estimation framework by combining different modules. + We provide detailed documentation and API reference, as well as unittests. + +</details> + +## What's New + +- We are excited to release **YOLOX-Pose**, a One-Stage multi-person pose estimation model based on YOLOX. Checkout our [project page](/projects/yolox-pose/) for more details. + + + +- Welcome to [*projects of MMPose*](/projects/README.md), where you can access to the latest features of MMPose, and share your ideas and codes with the community at once. Contribution to MMPose will be simple and smooth: + + - Provide an easy and agile way to integrate algorithms, features and applications into MMPose + - Allow flexible code structure and style; only need a short code review process + - Build individual projects with full power of MMPose but not bound up with heavy frameworks + - Checkout new projects: + - [RTMPose](/projects/rtmpose/) + - [YOLOX-Pose](/projects/yolox-pose/) + - [MMPose4AIGC](/projects/mmpose4aigc/) + - Become a contributors and make MMPose greater. Start your journey from the [example project](/projects/example_project/) + +<br/> + +- 2022-04-06: MMPose [v1.0.0](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) is officially released, with the main updates including: + + - Release of [YOLOX-Pose](/projects/yolox-pose/), a One-Stage multi-person pose estimation model based on YOLOX + - Development of [MMPose for AIGC](/projects/mmpose4aigc/) based on RTMPose, generating high-quality skeleton images for Pose-guided AIGC projects + - Support for OpenPose-style skeleton visualization + - More complete and user-friendly [documentation and tutorials](https://mmpose.readthedocs.io/en/latest/overview.html) + + Please refer to the [release notes](https://github.com/open-mmlab/mmpose/releases/tag/v1.0.0) for more updates brought by MMPose v1.0.0! + +## Installation + +Please refer to [installation.md](https://mmpose.readthedocs.io/en/latest/installation.html) for more detailed installation and dataset preparation. + +## Getting Started + +We provided a series of tutorials about the basic usage of MMPose for new users: + +1. For the basic usage of MMPose: + + - [A 20-minute Tour to MMPose](https://mmpose.readthedocs.io/en/latest/guide_to_framework.html) + - [Demos](https://mmpose.readthedocs.io/en/latest/demos.html) + - [Inference](https://mmpose.readthedocs.io/en/latest/user_guides/inference.html) + - [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) + +2. For developers who wish to develop based on MMPose: + + - [Learn about Codecs](https://mmpose.readthedocs.io/en/latest/advanced_guides/codecs.html) + - [Dataflow in MMPose](https://mmpose.readthedocs.io/en/latest/advanced_guides/dataflow.html) + - [Implement New Models](https://mmpose.readthedocs.io/en/latest/advanced_guides/implement_new_models.html) + - [Customize Datasets](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_datasets.html) + - [Customize Data Transforms](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_transforms.html) + - [Customize Optimizer](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_optimizer.html) + - [Customize Logging](https://mmpose.readthedocs.io/en/latest/advanced_guides/customize_logging.html) + - [How to Deploy](https://mmpose.readthedocs.io/en/latest/advanced_guides/how_to_deploy.html) + - [Model Analysis](https://mmpose.readthedocs.io/en/latest/advanced_guides/model_analysis.html) + - [Migration Guide](https://mmpose.readthedocs.io/en/latest/migration.html) + +3. For researchers and developers who are willing to contribute to MMPose: + + - [Contribution Guide](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) + +4. For some common issues, we provide a FAQ list: + + - [FAQ](https://mmpose.readthedocs.io/en/latest/faq.html) + +## Model Zoo + +Results and models are available in the **README.md** of each method's config directory. +A summary can be found in the [Model Zoo](https://mmpose.readthedocs.io/en/latest/model_zoo.html) page. + +<details close> +<summary><b>Supported algorithms:</b></summary> + +- [x] [DeepPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#deeppose-cvpr-2014) (CVPR'2014) +- [x] [CPM](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#cpm-cvpr-2016) (CVPR'2016) +- [x] [Hourglass](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hourglass-eccv-2016) (ECCV'2016) +- [ ] [SimpleBaseline3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline3d-iccv-2017) (ICCV'2017) +- [ ] [Associative Embedding](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#associative-embedding-nips-2017) (NeurIPS'2017) +- [x] [SimpleBaseline2D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simplebaseline2d-eccv-2018) (ECCV'2018) +- [x] [DSNT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#dsnt-2018) (ArXiv'2021) +- [x] [HRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnet-cvpr-2019) (CVPR'2019) +- [x] [IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#ipr-eccv-2018) (ECCV'2018) +- [ ] [VideoPose3D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#videopose3d-cvpr-2019) (CVPR'2019) +- [x] [HRNetv2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrnetv2-tpami-2019) (TPAMI'2019) +- [x] [MSPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mspn-arxiv-2019) (ArXiv'2019) +- [x] [SCNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#scnet-cvpr-2020) (CVPR'2020) +- [ ] [HigherHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#higherhrnet-cvpr-2020) (CVPR'2020) +- [x] [RSN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#rsn-eccv-2020) (ECCV'2020) +- [ ] [InterNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#internet-eccv-2020) (ECCV'2020) +- [ ] [VoxelPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#voxelpose-eccv-2020) (ECCV'2020) +- [x] [LiteHRNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#litehrnet-cvpr-2021) (CVPR'2021) +- [x] [ViPNAS](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vipnas-cvpr-2021) (CVPR'2021) +- [x] [Debias-IPR](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#debias-ipr-iccv-2021) (ICCV'2021) +- [x] [SimCC](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/algorithms.html#simcc-eccv-2022) (ECCV'2022) + +</details> + +<details close> +<summary><b>Supported techniques:</b></summary> + +- [ ] [FPN](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fpn-cvpr-2017) (CVPR'2017) +- [ ] [FP16](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#fp16-arxiv-2017) (ArXiv'2017) +- [ ] [Wingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#wingloss-cvpr-2018) (CVPR'2018) +- [ ] [AdaptiveWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#adaptivewingloss-iccv-2019) (ICCV'2019) +- [x] [DarkPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#darkpose-cvpr-2020) (CVPR'2020) +- [x] [UDP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#udp-cvpr-2020) (CVPR'2020) +- [ ] [Albumentations](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#albumentations-information-2020) (Information'2020) +- [ ] [SoftWingloss](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#softwingloss-tip-2021) (TIP'2021) +- [x] [RLE](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/techniques.html#rle-iccv-2021) (ICCV'2021) + +</details> + +<details close> +<summary><b>Supported datasets:</b></summary> + +- [x] [AFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#aflw-iccvw-2011) \[[homepage](https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/)\] (ICCVW'2011) +- [x] [sub-JHMDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#jhmdb-iccv-2013) \[[homepage](http://jhmdb.is.tue.mpg.de/dataset)\] (ICCV'2013) +- [x] [COFW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cofw-iccv-2013) \[[homepage](http://www.vision.caltech.edu/xpburgos/ICCV13/)\] (ICCV'2013) +- [x] [MPII](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-cvpr-2014) \[[homepage](http://human-pose.mpi-inf.mpg.de/)\] (CVPR'2014) +- [x] [Human3.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#human3-6m-tpami-2014) \[[homepage](http://vision.imar.ro/human3.6m/description.php)\] (TPAMI'2014) +- [x] [COCO](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-eccv-2014) \[[homepage](http://cocodataset.org/)\] (ECCV'2014) +- [x] [CMU Panoptic](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-iccv-2015) \[[homepage](http://domedb.perception.cs.cmu.edu/)\] (ICCV'2015) +- [x] [DeepFashion](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#deepfashion-cvpr-2016) \[[homepage](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion/LandmarkDetection.html)\] (CVPR'2016) +- [x] [300W](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#300w-imavis-2016) \[[homepage](https://ibug.doc.ic.ac.uk/resources/300-W/)\] (IMAVIS'2016) +- [x] [RHD](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#rhd-iccv-2017) \[[homepage](https://lmb.informatik.uni-freiburg.de/resources/datasets/RenderedHandposeDataset.en.html)\] (ICCV'2017) +- [x] [CMU Panoptic HandDB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#cmu-panoptic-handdb-cvpr-2017) \[[homepage](http://domedb.perception.cs.cmu.edu/handdb.html)\] (CVPR'2017) +- [x] [AI Challenger](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ai-challenger-arxiv-2017) \[[homepage](https://github.com/AIChallenger/AI_Challenger_2017)\] (ArXiv'2017) +- [x] [MHP](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mhp-acm-mm-2018) \[[homepage](https://lv-mhp.github.io/dataset)\] (ACM MM'2018) +- [x] [WFLW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#wflw-cvpr-2018) \[[homepage](https://wywu.github.io/projects/LAB/WFLW.html)\] (CVPR'2018) +- [x] [PoseTrack18](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#posetrack18-cvpr-2018) \[[homepage](https://posetrack.net/users/download.php)\] (CVPR'2018) +- [x] [OCHuman](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ochuman-cvpr-2019) \[[homepage](https://github.com/liruilong940607/OCHumanApi)\] (CVPR'2019) +- [x] [CrowdPose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#crowdpose-cvpr-2019) \[[homepage](https://github.com/Jeff-sjtu/CrowdPose)\] (CVPR'2019) +- [x] [MPII-TRB](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#mpii-trb-iccv-2019) \[[homepage](https://github.com/kennymckormick/Triplet-Representation-of-human-Body)\] (ICCV'2019) +- [x] [FreiHand](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#freihand-iccv-2019) \[[homepage](https://lmb.informatik.uni-freiburg.de/projects/freihand/)\] (ICCV'2019) +- [x] [Animal-Pose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#animal-pose-iccv-2019) \[[homepage](https://sites.google.com/view/animal-pose/)\] (ICCV'2019) +- [x] [OneHand10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#onehand10k-tcsvt-2019) \[[homepage](https://www.yangangwang.com/papers/WANG-MCC-2018-10.html)\] (TCSVT'2019) +- [x] [Vinegar Fly](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#vinegar-fly-nature-methods-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Nature Methods'2019) +- [x] [Desert Locust](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#desert-locust-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [Grévy’s Zebra](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#grevys-zebra-elife-2019) \[[homepage](https://github.com/jgraving/DeepPoseKit-Data)\] (Elife'2019) +- [x] [ATRW](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#atrw-acm-mm-2020) \[[homepage](https://cvwc2019.github.io/challenge.html)\] (ACM MM'2020) +- [x] [Halpe](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#halpe-cvpr-2020) \[[homepage](https://github.com/Fang-Haoshu/Halpe-FullBody/)\] (CVPR'2020) +- [x] [COCO-WholeBody](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#coco-wholebody-eccv-2020) \[[homepage](https://github.com/jin-s13/COCO-WholeBody/)\] (ECCV'2020) +- [x] [MacaquePose](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#macaquepose-biorxiv-2020) \[[homepage](http://www.pri.kyoto-u.ac.jp/datasets/macaquepose/index.html)\] (bioRxiv'2020) +- [x] [InterHand2.6M](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#interhand2-6m-eccv-2020) \[[homepage](https://mks0601.github.io/InterHand2.6M/)\] (ECCV'2020) +- [x] [AP-10K](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#ap-10k-neurips-2021) \[[homepage](https://github.com/AlexTheBad/AP-10K)\] (NeurIPS'2021) +- [x] [Horse-10](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/datasets.html#horse-10-wacv-2021) \[[homepage](http://www.mackenziemathislab.org/horse10)\] (WACV'2021) + +</details> + +<details close> +<summary><b>Supported backbones:</b></summary> + +- [x] [AlexNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#alexnet-neurips-2012) (NeurIPS'2012) +- [x] [VGG](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#vgg-iclr-2015) (ICLR'2015) +- [x] [ResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnet-cvpr-2016) (CVPR'2016) +- [x] [ResNext](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnext-cvpr-2017) (CVPR'2017) +- [x] [SEResNet](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#seresnet-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV1](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv1-cvpr-2018) (CVPR'2018) +- [x] [ShufflenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#shufflenetv2-eccv-2018) (ECCV'2018) +- [x] [MobilenetV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#mobilenetv2-cvpr-2018) (CVPR'2018) +- [x] [ResNetV1D](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnetv1d-cvpr-2019) (CVPR'2019) +- [x] [ResNeSt](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#resnest-arxiv-2020) (ArXiv'2020) +- [x] [Swin](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#swin-cvpr-2021) (CVPR'2021) +- [x] [HRFormer](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#hrformer-nips-2021) (NIPS'2021) +- [x] [PVT](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvt-iccv-2021) (ICCV'2021) +- [x] [PVTV2](https://mmpose.readthedocs.io/en/latest/model_zoo_papers/backbones.html#pvtv2-cvmj-2022) (CVMJ'2022) + +</details> + +### Model Request + +We will keep up with the latest progress of the community, and support more popular algorithms and frameworks. If you have any feature requests, please feel free to leave a comment in [MMPose Roadmap](https://github.com/open-mmlab/mmpose/issues/9). + +## Contributing + +We appreciate all contributions to improve MMPose. Please refer to [CONTRIBUTING.md](https://mmpose.readthedocs.io/en/latest/contribution_guide.html) for the contributing guideline. + +## Acknowledgement + +MMPose is an open source project that is contributed by researchers and engineers from various colleges and companies. +We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. +We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models. + +## Citation + +If you find this project useful in your research, please consider cite: + +```bibtex +@misc{mmpose2020, + title={OpenMMLab Pose Estimation Toolbox and Benchmark}, + author={MMPose Contributors}, + howpublished = {\url{https://github.com/open-mmlab/mmpose}}, + year={2020} +} +``` + +## License + +This project is released under the [Apache 2.0 license](LICENSE). + +## Projects in OpenMMLab + +- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models. +- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision. +- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages. +- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark. +- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark. +- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection. +- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark. +- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark. +- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox. +- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark. +- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark. +- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark. +- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark. +- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark. +- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark. +- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark. +- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark. +- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox. +- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox. +- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab Model Deployment Framework. + + + + +%prep +%autosetup -n mmpose-1.0.0 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-mmpose -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.0-1 +- Package Spec generated |