Our motto is “Let’s learn something everyday!” Last week, Medyamax technology specialists enjoyed learning, testing and finding out new capabilities. Basically it was “experiencing the future“. We did some experimental work on DeepFace Live,real-time face swap by running Python commands using Anaconda which is a free and open-source distribution of Python and DeepFace files from GitHub. DeepFace Live is a real-time face swapping application that allows for face swaps during video calls and streaming.
Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, ArcFace, Dlib and SFace. Experiments show that human beings have 97.53% accuracy on facial recognition tasks whereas those models already reached and passed that accuracy level. A modern face recognition pipeline consists of 5 common stages: detect, align, normalize, represent and verify. While Deepface handles all these common stages in the background. Face recognition models are regular convolutional neural networks and they are responsible to represent faces as vectors. Deepface also comes with a strong facial attribute analysis module including age, gender, facial expression (including angry, fear, neutral, sad, disgust, happy and surprise) and race (including asian, white, middle eastern, indian, latino and black) predictions. Result is going to be the size of faces appearing in the source image. You can run deepface for real time videos as well. Stream function will access your webcam and apply both face recognition and facial attribute analysis. DeepFace serves an API as well. You can clone deepface source code and run the api via gunicorn server. Face recognition, facial attribute analysis and vector representation functions are covered in the API. You can deploy the deepface api on a kubernetes cluster with docker. DeepFace comes with a command line interface as well. You can also run these commands if you are running deepface with docker.
Copyrights notice: Pypi.org, DeepFace is licensed under the MIT license; other mentioned names and brands are “property” of their respective owners.
@inproceedings{serengil2020lightface,
title = {LightFace: A Hybrid Deep Face Recognition Framework},
author = {Serengil, Sefik Ilkin and Ozpinar, Alper},
booktitle = {2020 Innovations in Intelligent Systems and Applications Conference (ASYU)},
pages = {23-27},
year = {2020},
doi = {10.1109/ASYU50717.2020.9259802},
url = {https://doi.org/10.1109/ASYU50717.2020.9259802},
organization = {IEEE}
} 
