FLAME Face Model

This codebase demonstrates how to load and play with FLAME, a lightweight and expressive generic face model to be presented in:

Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, and Javier Romero, Learning a model of facial shape and expression from 4D scans, ACM Transactions on Graphics (Proc. SIGGRAPH Asia) 2017

With this code, you can:

Load and evaluate FLAME model
Fit FLAME model to 3D landmarks

To request for FLAME model and registrations, please see the project page

This repo is maintained by Tianye Li. The codes in smpl_webuser are directly from SMPL Python code.

Dependencies

This code uses Python 2.7 and need the following dependencies:

Set-up

Clone the git project:

$ git clone https://github.com/Rubikplayer/flame-fitting.git

Set up virtual environment:

$ mkdir <your_home_dir>/.virtualenvs
$ virtualenv --system-site-packages <your_home_dir>/.virtualenvs/flame

Activate virtual environment:

$ cd flame-fitting
$ source <your_home_dir>/.virtualenvs/flame/bin/activate

Update the PYTHONPATH environment variable so that the system knows how to find the SMPL code. Add the following lines to your ~/.bash_profile file (create it if it doesn't exist; Linux users might have ~/.bashrc file instead), set the location to where you clone the project to.

FLAME_LOCATION=<flame_project_dir>
export PYTHONPATH=$PYTHONPATH:$FLAME_LOCATION

and run:

$ source ~/.bash_profile

To install numpy, scipy and chumpy:

$ pip install numpy
$ pip install scipy
$ pip install chumpy

To deactivate the virtual environment:

$ deactivate

Demo

See hello_world.py and facefit_lmk3d.py for the demos.

Citing

Tianye Li*, Timo Bolkart*, Michael J. Black, Hao Li, and Javier Romero. 2017. Learning a model of facial shape and expression from 4D scans. ACM Trans. Graph. 36, 6, Article 194 (November 2017), 17 pages. https://doi.org/10.1145/3130800.3130813

License