Sefik Ilkin Serengil
Serengil received his MSc in Computer Science from Galatasaray University in 2011.
He has been working as a software engineer since 2010 for a fintech company.
He enjoys to contribute open source. He is the creator of deepface and chefboost. Those are popular python libraries already got thousand of stars, and hundred thousands of installations.
Live broadcast: https://www.youtube.com/watch?v=9fwOBMWRTiI
Facial recognition has been a challenging task for a long time. Nowadays, we can reach and pass the human level accuracy with deep learning based state-of-the-art models. In this talk, you are going to learn how to build highly scalable facial recognition pipelines in python programming language with DeepFace library from its creator.
DeepFace is the most lightweight facial recognition and facial attribute analysis (age, gender, emotion / facial expression, race / ethnicity) library for Python. It wraps many state-of-the-art face recognition models: VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, Dlib and ArcFace. Experiments show that human beings have 97.53% score on LFW dataset whereas VGG, FaceNet, Dlib and ArcFace are passed that level already. Besides, OpenFace, DeepID and DeepFace have a close score as well. You can also build and run any one those cutting-edge models with just a few lines of code. The library got almost 2K stars on GitHub and 200K installations on PyPi / Pip.