Face Recognition Gate Opening System Using Deep Learning

This project presents a Face Recognition Gate Opening System using Deep Learning techniques. The system uses OpenCV for real-time face detection and DeepFace (FaceNet512 model) for facial recognition. 

The system captures live video through a webcam, detects faces, and compares them with stored facial embeddings using Euclidean distance. If a match is found, the gate opens automatically; otherwise, access is denied.

The system also maintains logs of user entries for security tracking. This solution provides a secure, efficient, and contactless access control system, overcoming limitations of traditional methods like keys and ID cards.

Technologies used include Python, OpenCV, DeepFace, and Convolutional Neural Networks (CNN).