Default set-up

Probably you want to either run FACSvatar in real-time mode for interactive purposes or create high-quality facial animation/pictures.

  • Real-time: Modified OpenFace –> FACSvatar modules –> Unity3D
  • Offline: (Modified) OpenFace –> .csv –> FACSvatar modules –> Blender

There 3 things that have to be setup:

  1. FACS input (Modified OpenFace)
  2. FACSvatar modules (Python 3.5+)
  3. Animation-Visualization (Unity3D / Blender)

If you’re already done setting FACSvatar up, please head here: First run

but before that, let’s download the FACSvatar GitHub repro with:
git clone
and download all other necessary files from the release page:

FACS input

Animation can be either in real-time or in offline mode. For the moment, FACSvatar is only working with OpenFace, however any module that provides FACS based data could be used.

Real-time allows for interactive systems, but at present the quality of FACS tracking from OpenFace is of lower quality in this mode. If interactivity is not your goal, the offline version is most likely a better choice.


Note: Requires 1 Windows PC (due to ZeroMQ being integrated in the GUI)

For the real-time version of FACSvatar we need to use a modified OpenFace which includes a ZeroMQ component to stream AU, gaze and head pose data out of it into. You can either

Build OpenFace with ZeroMQ

  1. Overwrite MainWindow.xaml.cs in OpenFaceguiOpenFaceOffline with openface/MainWindow.xaml.cs from FACSvatar GitHub
  2. Open visual studios:
    • Open OpenFace/OpenFace.sln with Visual Studio 2015
    • Open OpenFace_vs2017.sln with Visual Studio 2017 (didn’t work for me so far)
  3. (In visual studio) Right click in “Solution Explorer” on “OpenFaceOffline” –> Manage NuGet Packages…
  4. Browse and search for netmq; install NetMQ by NetMQ with version v4.0.0.1 (AsyncIO.0.1.26) note: Search under “Browse” not “Installed”
    • Don’t update AsyncIO to a newer version (v0.1.40)
  5. Search for json; Install Newtonsoft.Json by James Newton-King v11.0.2
  6. Select OpenFaceOffline –> Release, x64, OpenFaceOffline –> Build –> (Re)build OpenFaceOffline
  7. Copy config.xml from FACSvatar GitHub and put it at OpenFacex64Releaseconfig.xml # DON’T FORGET - otherwise crashes at startup


FACSvatar modules

At present, all the core modules work with Python, so let’s setup an environment. FACSvatar recommends using Anaconda for managing packages and virtual environments for Python, therefore code instructions assume Anaconda. Probably pip install .. will do the same without problems.

This project uses the Asyncio library for asynchronous code execution, hence we use Python 3.6+ (although some modules work with Python 3.5). I wanted to keep it Python 3.5 compatible, but due to the use of asynchronous generators used in some standard modules, the default version is 3.6+.

Anaconda setup

conda create --name facsvatar python=3.7  # new virtual env and force python 3.x
#conda install python=3.7  # IF you already have an existing env
source activate facsvatar  # activate env (Windows: conda activate facsvatar)

conda install pyzmq  # make sure it's for py3.6
conda install pandas  # library for dataframes; used for .csv reading and JSON-to-Dataframe

# Basic environment setup finished, but ipykernel setup recommended for control panel GUI

conda install ipykernel  # allows the use of env kernels in jupyter notebook
conda install ipywidgets  # GUI elements in jupyter notebook
python -m ipykernel install --user --name facsvatar --display-name "py3 facsvatar"  # enable our env as kernel in jupyter notebook

Test new environment

Go into a Python environment in your terminal with: python - enter

import zmq
print("Current libzmq version is %s" % zmq.zmq_version())  # 4.2.5 at time of writing
print("Current  pyzmq version is %s" % zmq.__version__)  # 17.1.2 at time of writing


Unity3D - game engine

Recommended for real-time or game like interaction applications. Unity3D version 2018.2.10f1 recommended.

  1. Download either Unity3D (single version) or UnityHub (recommended; manages Unity3D versions)
  2. Open the FACSvatar project in Unity3D by navigation to FACSvatar/unity_FACSvatar folder in the FACSvatar GitHub repro.
  3. (In the Asset Store tab: Search for JSON .NET for Unity (by PARENTELEMENT, LLC) and click Download.)
    • This step is probably not needed anymore.

Blender - open source 3D creation suite

Sorry, these instructions are still a mess.
Recommended for high-quality image/video rendering and post-modification.
Hopefully going to be real-time and as a Blender add-on when version 2.8 with EEVEE is released.
  1. Download Blender
  2. Download Manuel Bastioni LAB (MBLAB) add-on v.1.6.1a for Blender
  3. Start Blender in terminal by opening a terminal in the folder blender-2.79 and run:
    • Windows: blender.exe
    • Ubuntu: ./blender
  4. Import the .zip into Blender to install add-on: File –> User Preferences –> Add-ons –> Install Add-on from File –> –> check-mark in front of Characters: ManuelbastioniLAB
  5. Create a model with MBLAB by clicking Init character (leave default options for export to Unity3D), modify and press Finalize tools --> Finalize
  6. If Blender version is below 2.8 (likely the case if done in 2018 or earlier):
    • Create a Python 3.5 environment by following the instructions under Anaconda setup , but replacing --name facsvatar python=3.7 for --name blender python=3.5 (you can skip commands about Jupyter Notebook)
  7. Change line 7 in FACSvatar/blender/ to correctly point to your blender anaconda environment.
    • Windows (something like): c:\Users\*you*\AppData\Local\conda\conda\envs\blender\Lib\site-packages
    • Ubuntu (something like): /home/you/anaconda3/envs/blender/lib/python3.5/site-packages

Enabling FACS sliders in MBLAB add-on

Copy .json files found in FACSvatar/modules/process_facstoblend/au_json to:

  • Windows: C:\Users\*user*\AppData\Roaming\Blender Foundation\Blender\2.79\scripts\addons\manuelbastionilab\data\expressions_comb\human_expressions\
  • Ubuntu: /home/*user*/.config/blender/2.79/scripts/addons/manuelbastionilab/data/expressions_comb/human_expressions/