initial

.gitignore

@@ -0,0 +1,162 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+imgs/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

@@ -0,0 +1,106 @@
+<h1 align="left">ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation<a href="https://arxiv.org/abs/2204.12484"><img src="https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg" ></a> </h1> 
+
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/vitpose-simple-vision-transformer-baselines/pose-estimation-on-coco-test-dev)](https://paperswithcode.com/sota/pose-estimation-on-coco-test-dev?p=vitpose-simple-vision-transformer-baselines)
+
+<p align="center">
+  <a href="#Results">Results</a> |
+  <a href="#Updates">Updates</a> |
+  <a href="#Usage">Usage</a> |
+  <a href='#Todo'>Todo</a> |
+  <a href="#Acknowledge">Acknowledge</a>
+</p>
+
+<p align="center">
+<a href="https://giphy.com/gifs/UfPQB1qKir7Vqem6sL/fullscreen"><img src="https://media.giphy.com/media/ZewXwZuixYKS2lZmNL/giphy.gif"></a>   <a href="https://giphy.com/gifs/DCvf1DrWZgbwPa8bWZ/fullscreen"><img src="https://media.giphy.com/media/2AEeuicbIjwqp2mbug/giphy.gif"></a>
+</p>
+<p align="center">
+<a href="https://giphy.com/gifs/r3GaZz7H1H6zpuIvPI/fullscreen"><img src="https://media.giphy.com/media/13oe6zo6b2B7CdsOac/giphy.gif"></a>    <a href="https://giphy.com/gifs/FjzrGJxsOzZAXaW7Vi/fullscreen"><img src="https://media.giphy.com/media/4JLERHxOEgH0tt5DZO/giphy.gif"></a>
+</p>
+
+This branch contains the pytorch implementation of <a href="https://arxiv.org/abs/2204.12484">ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation</a>. It obtains 81.1 AP on MS COCO Keypoint test-dev set.
+
+## Results from this repo on MS COCO val set
+
+Using detection results from a detector that obtains 56 mAP on person.
+
+| Model | Pretrain | Resolution | AP | AR | config | log | weight |
+| :----: | :----: | :----: | :----: | :----: | :----: | :----: | :----: |
+| ViT-Base | MAE | 256x192 | 75.8 | 81.1 | config | log |  |
+| ViT-Large | MAE | 256x192 | 78.3 | 83.5 | config | log |  |
+| ViT-Huge | MAE | 256x192 | 79.1 | 84.1 | config | log |  |
+
+## Updates
+
+> [2022-04-27] Our ViTPose with ViTAE-G obtains 81.1 AP on COCO test-dev set! 
+
+> Applications of ViTAE Transformer include: [image classification](https://github.com/ViTAE-Transformer/ViTAE-Transformer/tree/main/Image-Classification) | [object detection](https://github.com/ViTAE-Transformer/ViTAE-Transformer/tree/main/Object-Detection) | [semantic segmentation](https://github.com/ViTAE-Transformer/ViTAE-Transformer/tree/main/Semantic-Segmentation) | [animal pose segmentation](https://github.com/ViTAE-Transformer/ViTAE-Transformer/tree/main/Animal-Pose-Estimation) | [remote sensing](https://github.com/ViTAE-Transformer/ViTAE-Transformer-Remote-Sensing) | [matting](https://github.com/ViTAE-Transformer/ViTAE-Transformer-Matting) | [VSA](https://github.com/ViTAE-Transformer/ViTAE-VSA) | [ViTDet](https://github.com/ViTAE-Transformer/ViTDet)
+
+## Usage
+
+We use PyTorch 1.9.0 or NGC docker 21.06, and mmcv 1.3.9 for the experiments.
+```bash
+git clone https://github.com/open-mmlab/mmcv.git
+cd mmcv
+git checkout v1.3.9
+MMCV_WITH_OPS=1 pip install -e .
+cd ..
+git clone https://github.com/ViTAE-Transformer/ViTPose.git
+cd ViTPose
+pip install -v -e .
+```
+
+After install the two repos, install timm and einops, i.e.,
+```bash
+pip install timm==0.4.9 einops
+```
+
+Download the pretrained models from [MAE](https://github.com/facebookresearch/mae) or [ViTAE](https://github.com/ViTAE-Transformer/ViTAE-Transformer), and then conduct the experiments by
+
+```bash
+# for single machine
+bash tools/dist_train.sh <Config PATH> <NUM GPUs> --cfg-options model.pretrained=<Pretrained PATH> --seed 0
+
+# for multiple machines
+python -m torch.distributed.launch --nnodes <Num Machines> --node_rank <Rank of Machine> --nproc_per_node <GPUs Per Machine> --master_addr <Master Addr> --master_port <Master Port> tools/train.py <Config PATH> --cfg-options model.pretrained=<Pretrained PATH> --launcher pytorch --seed 0
+```
+
+## Todo
+
+This repo current contains modifications including:
+
+- [ ] Upload configs and pretrained models
+
+- [ ] More models with SOTA results
+
+## Acknowledge
+We acknowledge the excellent implementation from [mmpose](https://github.com/open-mmlab/mmdetection) and [MAE](https://github.com/facebookresearch/mae).
+
+## Citing ViTPose
+```
+@misc{xu2022vitpose,
+      title={ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation}, 
+      author={Yufei Xu and Jing Zhang and Qiming Zhang and Dacheng Tao},
+      year={2022},
+      eprint={2204.12484},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```
+
+For ViTAE and ViTAEv2, please refer to:
+```
+@article{xu2021vitae,
+  title={Vitae: Vision transformer advanced by exploring intrinsic inductive bias},
+  author={Xu, Yufei and Zhang, Qiming and Zhang, Jing and Tao, Dacheng},
+  journal={Advances in Neural Information Processing Systems},
+  volume={34},
+  year={2021}
+}
+
+@article{zhang2022vitaev2,
+  title={ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond},
+  author={Zhang, Qiming and Xu, Yufei and Zhang, Jing and Tao, Dacheng},
+  journal={arXiv preprint arXiv:2202.10108},
+  year={2022}
+}
+```