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Build a Deep Facial Recognition App - Real Time Predictions with OpenCV - Python

Nicholas Renotte via YouTube

Overview

Learn how to implement real-time facial recognition using OpenCV in Python in this comprehensive tutorial video. Explore the process of building a deep facial recognition application for authentication purposes, based on the Siamese Neural Networks approach. Set up verification images, construct a verify function, and perform recognition in real-time using OpenCV. Follow along as the instructor guides you through setting up the verification images folder, building the verification function, making predictions, calculating detection and verification thresholds, accessing the webcam, and adding verification to the main loop. Gain hands-on experience by testing the final model and understanding its practical applications. Access the provided GitHub repository for the complete code and additional resources, including the referenced research paper and dataset.

Syllabus

- Start
- Explainer
- Tutorial Start
- Whiteboard
- Setup Verification Images Folder
- Build Verification Function
- Make Predictions
- Calculate Detection and Verification Thresholds
- Access Webcam
- Add Verification to Loop
- Testing the Final Model

Taught by

Nicholas Renotte

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