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A lightweight 3D Morphable Face Model library in modern C++
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# eos: A lightweight header-only 3D Morphable Face Model fitting library in modern C++11/14. [][release] [][github-actions-build] [][license] [][sponsor] [release]: https://github.com/patrikhuber/eos/releases [github-actions-build]: https://github.com/patrikhuber/eos/actions [license]: https://github.com/patrikhuber/eos/blob/master/LICENSE [sponsor]: https://github.com/sponsors/patrikhuber 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: * MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like `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-box * The low-resolution, shape-only Surrey Face Model ([share/sfm_shape_3448.bin](https://github.com/patrikhuber/eos/blob/master/share/sfm_shape_3448.bin)) * Fast, linear pose, shape and expression fitting, edge and contour fitting: * Linear scaled orthographic projection camera pose estimation * Linear shape-to-landmarks fitting, implementation of O. Aldrian & W. Smith, _Inverse Rendering of Faces with a 3D Morphable Model_, PAMI 2013 * Expression fitting, with 6 linear expression blendshapes of the SFM: anger, disgust, fear, happiness, sadness, surprise * Edge-fitting, heavily inspired by: A. Bas et al., _Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences_, ACCVW 2016 * Texture extraction to obtain a pose-invariant representation of the face texture * **Python bindings**: Much of eos's functionality is available as a python module (try `pip install eos-py`!) * (_Experimental_): Non-linear fitting cost functions using Ceres for shape, camera, blendshapes and the colour model (needs Ceres to be installed separately) An experimental model viewer to visualise 3D Morphable Models and blendshapes is available [here](https://github.com/patrikhuber/eos-model-viewer). ## Usage * Tested with the following compilers: >=gcc-6, >=clang-5, >=Visual Studio 2017 15.5, >=Xcode 9.2. * The library and python bindings **do not require any external dependencies**. The example applications require Boost (>=1.71.0) and OpenCV (>=2.4.3). 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!** ### Build the examples and tests * Needed dependencies for the example app: CMake (>=3.8.2, or >=3.10.0 for MSVC), Boost system, filesystem, program_options (>=1.71.0), OpenCV core, imgproc, highgui (>=2.4.3). To build: ``` git clone --recursive https://github.com/patrikhuber/eos.git mkdir build && cd build # creates a build directory next to the 'eos' folder cmake -G "<your favourite generator>" ../eos -DCMAKE_INSTALL_PREFIX=../install/ make && make install # or open the project file and build in an IDE like Visual Studio ``` It is strongly recommended to use [vcpkg](https://github.com/Microsoft/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
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c4dba7c6ce482b42, topic:computer-vision, readme:pose estimation