{"id":13638941,"url":"https://github.com/vchoutas/smplify-x","last_synced_at":"2025-05-15T13:06:43.353Z","repository":{"id":39545885,"uuid":"191319653","full_name":"vchoutas/smplify-x","owner":"vchoutas","description":"Expressive Body Capture: 3D Hands, Face, and Body from a Single Image","archived":false,"fork":false,"pushed_at":"2024-02-23T12:10:19.000Z","size":702,"stargazers_count":1871,"open_issues_count":86,"forks_count":350,"subscribers_count":67,"default_branch":"master","last_synced_at":"2025-04-15T02:10:03.857Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://smpl-x.is.tue.mpg.de/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vchoutas.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-06-11T07:41:05.000Z","updated_at":"2025-04-14T21:48:38.000Z","dependencies_parsed_at":"2024-11-09T09:31:21.121Z","dependency_job_id":"e06de99a-79a2-4830-92de-a8521fb7b9ad","html_url":"https://github.com/vchoutas/smplify-x","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vchoutas%2Fsmplify-x","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vchoutas%2Fsmplify-x/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vchoutas%2Fsmplify-x/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vchoutas%2Fsmplify-x/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vchoutas","download_url":"https://codeload.github.com/vchoutas/smplify-x/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254346624,"owners_count":22055808,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-02T01:00:55.614Z","updated_at":"2025-05-15T13:06:39.554Z","avatar_url":"https://github.com/vchoutas.png","language":"Python","funding_links":[],"categories":["Body","Python"],"sub_categories":[],"readme":"## Expressive Body Capture: 3D Hands, Face, and Body from a Single Image\n\n[[Project Page](https://smpl-x.is.tue.mpg.de/)] \n[[Paper](https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/497/SMPL-X.pdf)]\n[[Supp. Mat.](https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/498/SMPL-X-supp.pdf)]\n\n![SMPL-X Examples](./images/teaser_fig.png)\n\n## Table of Contents\n  * [License](#license)\n  * [Description](#description)\n    * [Fitting](#fitting)\n    * [Different Body Models](#different-body-models)\n    * [Visualizing Results](#visualizing-results)\n  * [Dependencies](#dependencies)\n  * [Citation](#citation)\n  * [Acknowledgments](#acknowledgments)\n  * [Contact](#contact)\n\n\n## License\n\nSoftware Copyright License for **non-commercial scientific research purposes**.\nPlease read carefully the [terms and conditions](https://github.com/vchoutas/smplx/blob/master/LICENSE) and any accompanying documentation before you download and/or use the SMPL-X/SMPLify-X model, data and software, (the \"Model \u0026 Software\"), including 3D meshes, blend weights, blend shapes, textures, software, scripts, and animations. By downloading and/or using the Model \u0026 Software (including downloading, cloning, installing, and any other use of this github repository), you acknowledge that you have read these terms and conditions, understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not download and/or use the Model \u0026 Software. Any infringement of the terms of this agreement will automatically terminate your rights under this [License](./LICENSE).\n\n## Disclaimer\n\nThe original images used for the figures 1 and 2 of the paper can be found in [this link](https://www.gettyimages.de/search/stack/546047069#). \nThe images in the paper are used under license from gettyimages.com.\nWe have acquired the right to use them in the publication, but redistribution is not allowed.\nPlease follow the instructions on the given link to acquire right of usage.\nOur results are obtained on the 483 × 724 pixels resolution of the original images.\n\n## Description\n\nThis repository contains the fitting code used for the experiments in [Expressive Body Capture: 3D Hands, Face, and Body from a Single Image](https://smpl-x.is.tue.mpg.de/).\n\n### Fitting \nRun the following command to execute the code:\n```Shell\npython smplifyx/main.py --config cfg_files/fit_smplx.yaml \n    --data_folder DATA_FOLDER \n    --output_folder OUTPUT_FOLDER \n    --visualize=\"True/False\"\n    --model_folder MODEL_FOLDER\n    --vposer_ckpt VPOSER_FOLDER\n    --part_segm_fn smplx_parts_segm.pkl\n```\nwhere the `DATA_FOLDER` should contain two subfolders, *images*, where the\nimages are located, and *keypoints*, where the OpenPose output should be\nstored.\n\n### Different Body Models\n\nTo fit [SMPL](http://smpl.is.tue.mpg.de/) or [SMPL+H](http://mano.is.tue.mpg.de), replace the *yaml* configuration file \nwith either *fit_smpl.yaml* or *fit_smplx.yaml*, i.e.:\n * for SMPL:\n ```Shell\n python smplifyx/main.py --config cfg_files/fit_smpl.yaml \n    --data_folder DATA_FOLDER \n    --output_folder OUTPUT_FOLDER \n    --visualize=\"True/False\"\n    --model_folder MODEL_FOLDER\n    --vposer_ckpt VPOSER_FOLDER\n ```\n  * for SMPL+H:\n ```Shell\n python smplifyx/main.py --config cfg_files/fit_smplh.yaml \n    --data_folder DATA_FOLDER \n    --output_folder OUTPUT_FOLDER \n    --visualize=\"True/False\"\n    --model_folder MODEL_FOLDER\n    --vposer_ckpt VPOSER_FOLDER\n ```\n \n### Visualizing Results\n\nTo visualize the results produced by the method you can run the following script:\n```Shell\npython smplifyx/render_results.py --mesh_fns OUTPUT_MESH_FOLDER\n```\nwhere *OUTPUT_MESH_FOLDER* is the folder that contains the resulting meshes.\n\n## Dependencies\n\nFollow the installation instructions for each of the following before using the\nfitting code.\n\n1. [PyTorch](https://pytorch.org/)\n2. [SMPL-X](https://github.com/vchoutas/smplx)\n3. [VPoser](https://github.com/nghorbani/HumanBodyPrior)\n4. [Homogenus](https://github.com/nghorbani/homogenus)\n\n### Optional Dependencies\n\n1. [PyTorch Mesh self-intersection](https://github.com/vchoutas/torch-mesh-isect) for interpenetration penalty \n   * Download the per-triangle part segmentation: [smplx_parts_segm.pkl](https://smpl-x.is.tue.mpg.de/download.php) (ctrl/cmd +F for the filename)\n1. [Trimesh](https://trimsh.org/) for loading triangular meshes\n1. [Pyrender](https://pyrender.readthedocs.io/) for visualization\n\nThe code has been tested with Python 3.6, CUDA 10.0, CuDNN 7.3 and PyTorch 1.0 on Ubuntu 18.04. \n\n## Citation\n\nIf you find this Model \u0026 Software useful in your research we would kindly ask you to cite:\n\n```\n@inproceedings{SMPL-X:2019,\n  title = {Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},\n  author = {Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},\n  booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},\n  year = {2019}\n}\n```\n\n## Acknowledgments\n\n### LBFGS with Strong Wolfe Line Search\n\nThe LBFGS optimizer with Strong Wolfe Line search is taken from this [Pytorch pull request](https://github.com/pytorch/pytorch/pull/8824). Special thanks to \n[Du Phan](https://github.com/fehiepsi) for implementing this. \nWe will update the repository once the pull request is merged.\n\n## Contact\nThe code of this repository was implemented by [Vassilis Choutas](mailto:vassilis.choutas@tuebingen.mpg.de) and\n[Georgios Pavlakos](mailto:pavlakos@seas.upenn.edu).\n\nFor questions, please contact [smplx@tue.mpg.de](mailto:smplx@tue.mpg.de). \n\nFor commercial licensing (and all related questions for business applications), please contact [ps-licensing@tue.mpg.de](mailto:ps-licensing@tue.mpg.de).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvchoutas%2Fsmplify-x","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvchoutas%2Fsmplify-x","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvchoutas%2Fsmplify-x/lists"}