Sefik Serengil
Unboxing the DeepFace
#1about 4 minutes
Introducing the DeepFace facial recognition library
Learn about the open-source DeepFace Python library, its key features, and how to install and use it for basic face verification.
#2about 2 minutes
Understanding face verification versus face recognition
Face verification is a one-to-one comparison with O(1) complexity, while face recognition is a one-to-many search with O(n) complexity.
#3about 2 minutes
Analyzing facial attributes like age and gender
DeepFace can predict apparent age, gender, emotion, and race to help reduce search space or mitigate dataset bias.
#4about 2 minutes
Stage 1: Detecting faces with different backends
Choose from various face detectors like OpenCV for speed or RetinaFace for higher accuracy in crowded images.
#5about 2 minutes
Stages 2 & 3: Aligning and normalizing facial images
Improve accuracy by rotating images to align the eyes horizontally and cropping the facial area to remove background noise.
#6about 6 minutes
Stage 4: Creating vector embeddings with neural networks
Convolutional neural networks convert facial images into unique vector embeddings, avoiding the need to retrain the model for new identities.
#7about 3 minutes
Stage 5: Verifying identity using distance and thresholds
Calculate the distance between two vector embeddings to determine if they represent the same person by comparing it to a pre-defined threshold.
#8about 3 minutes
The challenge of scaling facial recognition to billions of images
Traditional one-to-many search is too slow for large-scale applications like those at Google or Facebook, requiring more advanced algorithms.
#9about 2 minutes
Using Approximate Nearest Neighbor for fast searching
Accelerate large-scale searches by using Approximate Nearest Neighbor (ANN) algorithms, which trade perfect accuracy for significant speed gains.
#10about 3 minutes
Choosing the right tech stack for your use case
Select key-value stores like Redis for fast verification, distributed systems like Spark for high-confidence recognition, or vector databases for ANN-powered search.
#11about 3 minutes
Key benefits of using the DeepFace library
DeepFace is a lightweight, easy-to-install, open-source library that wraps state-of-the-art models and is language-independent via its API.
#12about 13 minutes
Audience Q&A on emotion detection, 3D sensors, and bias
The speaker answers questions about measuring emotion, handling 3D data, determining thresholds, and addressing bias in training datasets.
Related jobs
Jobs that call for the skills explored in this talk.
Picnic Technologies B.V.
Amsterdam, Netherlands
Intermediate
Senior
Python
Structured Query Language (SQL)
+1
Matching moments
04:57 MIN
Increasing the value of talk recordings post-event
Cat Herding with Lions and Tigers - Christian Heilmann
01:32 MIN
Organizing a developer conference for 15,000 attendees
Cat Herding with Lions and Tigers - Christian Heilmann
06:44 MIN
Using Chrome's built-in AI for on-device features
Devs vs. Marketers, COBOL and Copilot, Make Live Coding Easy and more - The Best of LIVE 2025 - Part 3
02:54 MIN
Automating video post-production with local scripts
Cat Herding with Lions and Tigers - Christian Heilmann
06:28 MIN
Using AI agents to modernize legacy COBOL systems
Devs vs. Marketers, COBOL and Copilot, Make Live Coding Easy and more - The Best of LIVE 2025 - Part 3
05:55 MIN
The security risks of AI-generated code and slopsquatting
Slopquatting, API Keys, Fun with Fonts, Recruiters vs AI and more - The Best of LIVE 2025 - Part 2
04:04 MIN
Shifting HR from standard products to AI-powered platforms
Turning People Strategy into a Transformation Engine
03:28 MIN
Why corporate AI adoption lags behind the hype
What 2025 Taught Us: A Year-End Special with Hung Lee
Featured Partners
Related Videos
27:23From ML to LLM: On-device AI in the Browser
Nico Martin
46:42Deepfakes in Realtime - How Neural Networks Are Changing Our World
Thomas Endres & Martin Förtsch & Jonas Mayer
48:38Computer Vision from the Edge to the Cloud done easy
Flo Pachinger
56:46A beginner’s guide to modern natural language processing
Jodie Burchell
32:54The pitfalls of Deep Learning - When Neural Networks are not the solution
Adrian Spataru & Bohdan Andrusyak
57:46Overview of Machine Learning in Python
Adrian Schmitt
50:37Debugging Machine Learning Code
Svetlin Penkov
34:34Vision for Websites: Training Your Frontend to See
Daniel Madalitso Phiri
Related Articles
View all articles
.gif?w=240&auto=compress,format)
From learning to earning
Jobs that call for the skills explored in this talk.
European Tech Recruit
Intermediate
Python
PyTorch