Learn to build a free anti-spoofing and liveness detection system for face recognition in this comprehensive video tutorial. Explore computer vision techniques to differentiate between real and fake faces, enhancing the security of facial recognition systems. Follow step-by-step instructions on installations, face detection, data collection, preprocessing, model training, and implementation. Gain hands-on experience with popular tools like OpenCV, YOLO, and Google Colab while mastering concepts such as bounding box manipulation, blurriness detection, confidence scoring, and data normalization. By the end of this tutorial, develop the skills to create a robust anti-spoofing solution for various computer vision applications.
Anti Spoofing - Liveliness Detector for Face Recognition System - Fake VS Real - Computer Vision
Murtaza's Workshop - Robotics and AI via YouTube
Overview
Syllabus
Introduction
Overview
Installations
Testing Face Detector
Testing Yolo
GPU
File Creation Test
Data Collection Overview
Bigger Bounding Box
Face Blurriness
Confidence Value
Normalization
Drawing
Saving Image
Save Label File
Recheck Label File
Collecting Data
Creating Directories
Get Name List
Shuffle Data
Split Data
Copy Files
Data.yaml
Training On Local PC
Training On Google Colab
Drawing
Taught by
Murtaza's Workshop - Robotics and AI
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