Metadata-Version: 2.1
Name: FLAME-PyTorch
Version: 0.0.1
Summary: PyTorch implementation of the 3D FLAME model.
Home-page: https://github.com/soubhiksanyal/FLAME_PyTorch
Author: Soubhik Sanyal
Author-email: soubhik.sanyal@tuebingen.mpg.de
License: See LICENSE
Project-URL: Source, https://github.com/soubhiksanyal/FLAME_PyTorch
Description: # FLAME: Articulated Expressive 3D Head Model (PyTorch)
        
        This is an implementation of the [FLAME](http://flame.is.tue.mpg.de/) 3D head model in PyTorch.
        
        We also provide [Tensorflow FLAME](https://github.com/TimoBolkart/TF_FLAME), a [Chumpy](https://github.com/mattloper/chumpy)-based [FLAME-fitting repository](https://github.com/Rubikplayer/flame-fitting), and code to [convert from Basel Face Model to FLAME](https://github.com/TimoBolkart/BFM_to_FLAME).
        
        <p align="center"> 
        <img src="gifs/model_variations.gif">
        </p>
        
        FLAME is a lightweight and expressive generic head model learned from over 33,000 of accurately aligned 3D scans. FLAME combines a linear identity shape space (trained from head scans of 3800 subjects) with an articulated neck, jaw, and eyeballs, pose-dependent corrective blendshapes, and additional global expression blendshapes. For details please see the following [scientific publication](https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/400/paper.pdf)
        
        ```bibtex
        Learning a model of facial shape and expression from 4D scans
        Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, and Javier Romero
        ACM Transactions on Graphics (Proc. SIGGRAPH Asia) 2017
        ```
        
        and the [supplementary video](https://youtu.be/36rPTkhiJTM).
        
        ## Installation
        
        The code uses **Python 3.7** and it is tested on PyTorch 1.4.
        
        ### Setup FLAME PyTorch Virtual Environment
        
        ```shell
        python3.7 -m venv <your_home_dir>/.virtualenvs/FLAME_PyTorch
        source <your_home_dir>/.virtualenvs/FLAME_PyTorch/bin/activate
        ```
        
        ### Clone the project and install requirements
        
        ```shell
        git clone https://github.com/soubhiksanyal/FLAME_PyTorch
        cd FLAME_PyTorch
        python setup.py install
        mkdir model
        ```
        
        ## Download models
        
        * Download FLAME model from [here](http://flame.is.tue.mpg.de/). You need to sign up and agree to the model license for access to the model. Copy the downloaded model inside the **model** folder. 
        * Download Landmark embedings from [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model). Copy it inside the **model** folder. 
        
        ## Demo
        
        ### Loading FLAME and visualising the 3D landmarks on the face
        
        Please note we used the pose dependent conture for the face as introduced by [RingNet Project](https://github.com/soubhiksanyal/RingNet/tree/master/flame_model).
        
        Run the following command from the terminal
        
        ```shell
        python main.py
        ```
        
        ## License
        
        FLAME is available under [Creative Commons Attribution license](https://creativecommons.org/licenses/by/4.0/). By using the model or the code code, you acknowledge that you have read the license terms (https://flame.is.tue.mpg.de/modellicense.html), understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not use the code.
        
        ## Referencing FLAME
        
        When using this code in a scientific publication, please cite
        
        ```bibtex
        @article{FLAME:SiggraphAsia2017,
          title = {Learning a model of facial shape and expression from {4D} scans},
          author = {Li, Tianye and Bolkart, Timo and Black, Michael. J. and Li, Hao and Romero, Javier},
          journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)},
          volume = {36},
          number = {6},
          year = {2017},
          url = {https://doi.org/10.1145/3130800.3130813}
        }
        ```
        
        Additionally if you use the pose dependent dynamic landmarks from this codebase, please cite 
        
        ```bibtex
        @inproceedings{RingNet:CVPR:2019,
        title = {Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision},
        author = {Sanyal, Soubhik and Bolkart, Timo and Feng, Haiwen and Black, Michael},
        booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},
        month = jun,
        year = {2019},
        month_numeric = {6}
        }
        ```
        
        ## Supported Projects
        
        FLAME supports several projects such as
        
        * [CoMA: Convolutional Mesh Autoencoders](https://github.com/anuragranj/coma)
        * [RingNet: 3D Face Shape and Expression Reconstruction from an Image without 3D Supervision](https://github.com/soubhiksanyal/RingNet)
        * [VOCA: Voice Operated Character Animation](https://github.com/TimoBolkart/voca)
        * [Expressive Body Capture: 3D Hands, Face, and Body from a Single Image](https://github.com/vchoutas/smplify-x)
        * [ExPose: Monocular Expressive Body Regression through Body-Driven Attention](https://github.com/vchoutas/expose)
        * [GIF: Generative Interpretable Faces](https://github.com/ParthaEth/GIF)
        * [DECA: Detailed Expression Capture and Animation](https://github.com/YadiraF/DECA)
        
        FLAME is part of [SMPL-X: : A new joint 3D model of the human body, face and hands together](https://github.com/vchoutas/smplx)
        
        ## Contact
        
        If you have any questions regarding the PyTorch implementation then you can contact us at soubhik.sanyal@tuebingen.mpg.de and timo.bolkart@tuebingen.mpg.de.
        
        ## Acknowledgements
        
        This repository is build with modifications from [SMPLX](https://github.com/vchoutas/smplx).
        
Keywords: FLAME,3D Face Modelling
Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
