eos 1.4.0
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eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14.
At the moment, it mainly provides the following functionality:
draw_sample()
. Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-boxpip install eos-py
!)An experimental model viewer to visualise 3D Morphable Models and blendshapes is available here.
To use the library in your own project, just add the following directories to your include path:
eos/include
eos/3rdparty/cereal/include
eos/3rdparty/nanoflann/include
eos/3rdparty/eigen/Eigen
eos/3rdparty/eigen3-nnls/src
eos/3rdparty/toml11
Make sure to clone with --recursive
to download the required submodules!
To build:
It is strongly recommended to use vcpkg to install the dependencies on Windows. Users who wish to manage dependencies manually may find it helpful to copy initial_cache.cmake.template
to initial_cache.cmake
, edit the necessary paths and run cmake
with -C ../eos/initial_cache.cmake
. On Linux, you may also want to set -DCMAKE_BUILD_TYPE=...
appropriately.
The fit-model example app creates a 3D face from a 2D image.
After make install
or running the INSTALL
target, an example image with landmarks can be found in install/bin/data/
. The model and the necessary landmarks mapping file are installed to install/share/
.
You can run the example just by running:
fit-model
It will load the face model, landmark-to-vertex mappings, blendshapes, and other required files from the ../share/
directory, and run on the example image. It can be run on other images by giving it a -i
parameter for the image and -l
for a set of ibug landmarks. The full set of parameters can be viewed by running fit-model --help
.
If you are just getting started, it is recommended to have a look at fit-model-simple
too, as it requires much fewer input, and only fits pose and shape, without any blendshapes or edge-fitting. Its full set of arguments is:
fit-model-simple -m ../share/sfm_shape_3448.bin -p ../share/ibug_to_sfm.txt -i data/image_0010.png -l data/image_0010.pts
The output in both cases is an obj
file with the shape and a png
with the extracted texture map. The estimated pose angles and shape coefficients are available in the code via the API.
See examples/fit-model.cpp for the full code.
The library includes a low-resolution shape-only version of the Surrey Morphable Face Model. It is a PCA model of shape variation built from 3D face scans. It comes with uv-coordinates to perform texture remapping.
The full model is available at http://www.cvssp.org/facemodel.
eos can be used to load, use and do basic fitting with the 4D Face Model (4DFM) from 4dface Ltd. The model features 39 expressions/action units, and diverse identity variation.
More information about the model can be found on www.4dface.io/4dfm.
eos includes python bindings for some of its functionality (and more can be added!). It can be installed from PyPI with pip install eos-py
. You will still need the data files from this repository. Make sure that you've got >=gcc-7 or >=clang-5 as the default compiler on Linux (for example from the ubuntu-toolchain-r/test repository) or do CC=`which gcc-7` CXX=`which g++-7` pip install eos-py
. Also make sure you've got >=cmake-3.8.2 (or >=cmake-3.10.0 for MSVC) in your path. In case of issues, the bindings can also be built manually: Clone the repository and set -DEOS_GENERATE_PYTHON_BINDINGS=on
when running cmake
(and optionally set PYTHON_EXECUTABLE
to point to your python interpreter if it's not found automatically).
After having obtained the bindings, they can be used like any python module:
See demo.py
for an example on how to run the fitting.
Experimental (not maintained currently): eos includes Matlab bindings for the fit_shape_and_pose(...)
function, which means the fitting can be run from Matlab. Set -DEOS_GENERATE_MATLAB_BINDINGS=on
when running cmake
to build the required mex-file and run the INSTALL
target to install everything. (Set Matlab_ROOT_DIR
to point to your Matlab directory if it's not found automatically). More bindings (e.g. the MorphableModel itself) might be added in the future.
Go to the install/eos/matlab
directory and run demo.m
to see how to run the fitting. The result is a mesh and rendering parameters (pose).
Doxygen: http://patrikhuber.github.io/eos/doc/
The fit-model example and the Namespace List in doxygen are a good place to start.
This code is licensed under the Apache License, Version 2.0. The 3D morphable face model under share/sfm_shape_3448.bin is free for use for non-commercial purposes. For commercial purposes and to obtain other model resolutions, see http://www.cvssp.org/facemodel.
Contributions are very welcome! (best in the form of pull requests.) Please use GitHub issues for any bug reports, ideas, and discussions.
If you use this code in your own work, please cite the following paper: A Multiresolution 3D Morphable Face Model and Fitting Framework, P. Huber, G. Hu, R. Tena, P. Mortazavian, W. Koppen, W. Christmas, M. Rätsch, J. Kittler, International Conference on Computer Vision Theory and Applications (VISAPP) 2016, Rome, Italy [PDF].