Real-Time Facial Recognition System This repository contains the implementation of a Real-Time Facial Recognition System that leverages Python, OpenCV, and the face_recognition library to detect and identify known faces in video streams. The project is designed with flexibility and scalability in mind, incorporating dynamic image management, real-time accuracy scoring, and multi-camera support to adapt to diverse use cases.
Features 🎯 Real-Time Face Detection and Identification Uses OpenCV and face_recognition to detect and identify faces with high precision. Displays real-time accuracy scores for identified faces. 📂 Dynamic Image Management Integrates Google Drive API to dynamically load and update the dataset of known faces. Allows for remote and flexible image management without restarting the system. 📊 Enhanced Usability Includes a live face counter to display the number of faces detected in the video stream. Supports multiple cameras for simultaneous face recognition across different feeds. ⚡ High Performance Optimized for real-time processing, making it suitable for various real-world applications such as surveillance, attendance systems, and more. Key Technologies Programming Language: Python Libraries: OpenCV, face_recognition, Google Drive API Additional Features: Multi-camera support, live statistics display, and dynamic dataset updates.