{ "info": { "author": "Gul Varol", "author_email": "gulvarols@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: OS Independent", "Programming Language :: Python :: 3" ], "description": "SMPL layer for PyTorch\n=======\n\n[SMPL](http://smpl.is.tue.mpg.de) human body [\\[1\\]](#references) layer for [PyTorch](https://pytorch.org/) (tested with v0.4 and v1.x)\nis a differentiable PyTorch layer that deterministically maps from pose and shape parameters to human body joints and vertices.\nIt can be integrated into any architecture as a differentiable layer to predict body meshes.\nThe code is adapted from the [manopth](https://github.com/hassony2/manopth) repository by [Yana Hasson](https://github.com/hassony2).\n\n

\n\"smpl\"\n

\n\n## Installation\n\nYou can install smpl-pytorch from [PyPI](https://pypi.org/project/smpl-pytorch/):\n\n pip install smpl-pytorch\n\nAdditionally, you have to download the SMPL pickle files:\n * Download the models from the [SMPL website](http://smpl.is.tue.mpg.de/) by choosing \"SMPL for Python users\". Note that you need to comply with the [SMPL model license](http://smpl.is.tue.mpg.de/license_model).\n * Extract and copy the `models` folder into the `smpl/native/` folder.\n\nAlternatively, you can set up the package manually (see next).\n\n\n## Setting up\n\n* Dependencies:\n * Install the dependencies listed in [environment.yml](environment.yml)\n * In an existing conda environment, `conda env update -f environment.yml`\n * In a new environment, `conda env create -f environment.yml`, will create a conda environment named `smplpytorch`\n* Download SMPL pickle files:\n * Download the models from the [SMPL website](http://smpl.is.tue.mpg.de/) by choosing \"SMPL for Python users\". Note that you need to comply with the [SMPL model license](http://smpl.is.tue.mpg.de/license_model).\n * Extract and copy the `models` folder into the `smpl/native/` folder.\n\n## Demo\n\nForward pass the randomly created pose and shape parameters from the SMPL layer and display the human body mesh and joints:\n\n`python demo.py`\n\n## Acknowledgements\nThe code **largely** builds on the [manopth](https://github.com/hassony2/manopth) repository from [Yana Hasson](https://github.com/hassony2), which implements the [MANO](http://mano.is.tue.mpg.de) hand model [\\[2\\]](#references) layer.\n\nThe code is a PyTorch port of the original [SMPL](http://smpl.is.tue.mpg.de) model from [chumpy](https://github.com/mattloper/chumpy). It builds on the work of [Loper](https://github.com/mattloper) et al. [\\[1\\]](#references).\n\nThe code [reuses](https://github.com/gulvarol/smpl/pytorch/rodrigues_layer.py) [part of the code](https://github.com/MandyMo/pytorch_HMR/blob/master/src/util.py) by [Zhang Xiong](https://github.com/MandyMo) to compute the rotation utilities.\n\nIf you find this code useful for your research, please cite the original [SMPL](http://smpl.is.tue.mpg.de) publication:\n\n```\n@article{SMPL:2015,\n author = {Loper, Matthew and Mahmood, Naureen and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.},\n title = {{SMPL}: A Skinned Multi-Person Linear Model},\n journal = {ACM Trans. Graphics (Proc. SIGGRAPH Asia)},\n number = {6},\n pages = {248:1--248:16},\n volume = {34},\n year = {2015}\n}\n```\n\n## References\n\n\\[1\\] Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black, \"SMPL: A Skinned Multi-Person Linear Model,\" SIGGRAPH Asia, 2015.\n\n\\[2\\] Javier Romero, Dimitrios Tzionas, and Michael J. Black, \"Embodied Hands: Modeling and Capturing Hands and Bodies Together,\" SIGGRAPH Asia, 2017.\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/gulvarol/smpl-pytorch", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "smpl-pytorch", "package_url": "https://pypi.org/project/smpl-pytorch/", "platform": "", "project_url": "https://pypi.org/project/smpl-pytorch/", "project_urls": { "Homepage": "https://github.com/gulvarol/smpl-pytorch" }, "release_url": "https://pypi.org/project/smpl-pytorch/0.0.7/", "requires_dist": [ "opencv-python", "matplotlib", "numpy" ], "requires_python": ">=3.5.0", "summary": "SMPL human body layer for PyTorch is a differentiable PyTorch layer", "version": "0.0.7" }, "last_serial": 5540113, "releases": { "0.0.7": [ { "comment_text": "", "digests": { "md5": "fda607200b37e4683970301f0e583aa0", "sha256": "805c4186505c0b1d5ad1a81510bde4c4260c80ed37dc7a58ad896e231d7eed60" }, "downloads": -1, "filename": "smpl_pytorch-0.0.7-py3-none-any.whl", "has_sig": false, "md5_digest": "fda607200b37e4683970301f0e583aa0", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.5.0", "size": 22928, "upload_time": "2019-07-16T09:32:59", "url": "https://files.pythonhosted.org/packages/b8/5b/aef8b891353f1161fbba8819474b751742b97de648e9dec971926942b408/smpl_pytorch-0.0.7-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "ded6fbde1e960660601922d22a0aa775", "sha256": "1ad0581c030b11d6de38c407be1c4c702b1c9aef8de774f8b15d9505a832100d" }, "downloads": -1, "filename": "smpl-pytorch-0.0.7.tar.gz", "has_sig": false, "md5_digest": "ded6fbde1e960660601922d22a0aa775", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.5.0", "size": 9067, "upload_time": "2019-07-16T09:33:00", "url": "https://files.pythonhosted.org/packages/6c/b6/ec1070cf01a7d1b84f6e3e7e5a9cc6abf2c4c76e26a42a7fb30dd46c7c7d/smpl-pytorch-0.0.7.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "fda607200b37e4683970301f0e583aa0", "sha256": "805c4186505c0b1d5ad1a81510bde4c4260c80ed37dc7a58ad896e231d7eed60" }, "downloads": -1, "filename": "smpl_pytorch-0.0.7-py3-none-any.whl", "has_sig": false, "md5_digest": "fda607200b37e4683970301f0e583aa0", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.5.0", "size": 22928, "upload_time": "2019-07-16T09:32:59", "url": "https://files.pythonhosted.org/packages/b8/5b/aef8b891353f1161fbba8819474b751742b97de648e9dec971926942b408/smpl_pytorch-0.0.7-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "ded6fbde1e960660601922d22a0aa775", "sha256": "1ad0581c030b11d6de38c407be1c4c702b1c9aef8de774f8b15d9505a832100d" }, "downloads": -1, "filename": "smpl-pytorch-0.0.7.tar.gz", "has_sig": false, "md5_digest": "ded6fbde1e960660601922d22a0aa775", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.5.0", "size": 9067, "upload_time": "2019-07-16T09:33:00", "url": "https://files.pythonhosted.org/packages/6c/b6/ec1070cf01a7d1b84f6e3e7e5a9cc6abf2c4c76e26a42a7fb30dd46c7c7d/smpl-pytorch-0.0.7.tar.gz" } ] }