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https://cmusatyalab.github.io/openface/

Face recognition with deep neural networks.
https://cmusatyalab.github.io/openface/

deep-learning face-recognition facenet

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Face recognition with deep neural networks.

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README 

        
# OpenFace • [![Build Status][travis-image]][travis] [![Release][release-image]][releases] [![License][license-image]][license] [![Gitter][gitter-image]][gitter]



*Free and open source face recognition with

deep neural networks.*



[travis-image]: https://travis-ci.org/cmusatyalab/openface.svg?branch=master

[travis]: http://travis-ci.org/cmusatyalab/openface



[release-image]: http://img.shields.io/badge/release-0.2.1-blue.svg?style=flat

[releases]: https://github.com/cmusatyalab/openface/releases



[license-image]: http://img.shields.io/badge/license-Apache--2-blue.svg?style=flat

[license]: LICENSE



[gitter-image]: https://badges.gitter.im/Join%20Chat.svg

[gitter]: https://gitter.im/cmusatyalab/openface



---



+ Website: http://cmusatyalab.github.io/openface/

+ [API Documentation](http://openface-api.readthedocs.org/en/latest/index.html)

+ Join the

  [cmu-openface group](https://groups.google.com/forum/#!forum/cmu-openface)

  or the

  [gitter chat](https://gitter.im/cmusatyalab/openface)

  for discussions and installation issues.

+ Development discussions and bugs reports are on the

  [issue tracker](https://github.com/cmusatyalab/openface/issues).



---



This research was supported by the National Science Foundation (NSF)

under grant number CNS-1518865.  Additional support

was provided by the Intel Corporation, Google, Vodafone, NVIDIA, and the

Conklin Kistler family fund.  Any opinions, findings, conclusions or

recommendations expressed in this material are those of the authors

and should not be attributed to their employers or funding sources.



# What's in this repository?

+ [batch-represent](https://github.com/cmusatyalab/openface/tree/master/batch-represent): Generate representations from

  a batch of images. [Example directory structure.](https://gist.github.com/bamos/f03037f5df7e05ad0cc8)

+ [demos/web](https://github.com/cmusatyalab/openface/tree/master/demos/web): Real-time web demo.

+ [demos/compare.py](https://github.com/cmusatyalab/openface/tree/master/demos/compare.py): Demo to compare two images.

+ [demos/vis-outputs.lua](https://github.com/cmusatyalab/openface/tree/master/demos/vis-outputs.lua): Demo to

  visualize the network's outputs.

+ [demos/classifier.py](https://github.com/cmusatyalab/openface/tree/master/demos/classifier.py): Demo to train and use classifiers.

+ [demos/classifier_webcam.py](https://github.com/cmusatyalab/openface/blob/master/demos/classifier_webcam.py): Demo to use a trained classifier on a webcam stream.

+ [evaluation](https://github.com/cmusatyalab/openface/blob/master/evaluation): LFW accuracy evaluation scripts.

+ [openface](https://github.com/cmusatyalab/openface/tree/master/openface): Python library code.

+ [models](https://github.com/cmusatyalab/openface/tree/master/models): Model directory for openface and 3rd party libraries.

+ [tests](https://github.com/cmusatyalab/openface/tree/master/tests): Tests for scripts and library code, including neural network training.

+ [training](https://github.com/cmusatyalab/openface/tree/master/training): Scripts to train new OpenFace neural network models.

+ [util](https://github.com/cmusatyalab/openface/tree/master/util): Utility scripts.



# Citations



Please cite OpenFace in your publications if it helps your research.

The following is a [BibTeX](http://www.bibtex.org/) and plaintext reference for our

[OpenFace tech report](http://reports-archive.adm.cs.cmu.edu/anon/anon/2016/CMU-CS-16-118.pdf).



```

@techreport{amos2016openface,

  title={OpenFace: A general-purpose face recognition

    library with mobile applications},

  author={Amos, Brandon and Bartosz Ludwiczuk and Satyanarayanan, Mahadev},

  year={2016},

  institution={CMU-CS-16-118, CMU School of Computer Science},

}



B. Amos, B. Ludwiczuk, M. Satyanarayanan,

"Openface: A general-purpose face recognition library with mobile applications,"

CMU-CS-16-118, CMU School of Computer Science, Tech. Rep., 2016.

```



# Licensing

Unless otherwise stated, the source code and trained Torch and Python

model files are copyright Carnegie Mellon University and licensed

under the [Apache 2.0 License](./LICENSE).

Portions from the following third party sources have

been modified and are included in this repository.

These portions are noted in the source files and are

copyright their respective authors with

the licenses listed.



Project | Modified | License

---|---|---|

[Atcold/torch-TripletEmbedding](https://github.com/Atcold/torch-TripletEmbedding) | No | MIT

[facebook/fbnn](https://github.com/facebook/fbnn) | Yes | BSD

[dlib-models](https://github.com/davisking/dlib-models) (68 face landmark detector) | No | CC0