A Deep Learning Approach for Real-Time Facial Recognition and Analysis

This project presents A Deep Learning Approach for Real-Time Facial Recognition and Analysis that uses computer vision and deep learning to detect and interpret human facial attributes, including age, gender, emotion, and race. The system captures live video from a webcam, detects faces using OpenCV, and analyzes them using the DeepFace library. It is designed to run efficiently on standard laptops and provide instant feedback by displaying detected attributes directly on the screen.Despite challenges like poor lighting and ambiguous facial expressions, the use of pre-trained deep learning models improved the system's accuracy. This project demonstrates the practical integration of AI in real-world scenarios and lays a foundation for future enhancements such as face recognition or emotion tracking.