The project introduces a real-time facial emotion detection (FED) system using deep learning, employing convolutional neural networks (CNNs) and pre-trained models to accurately classify a range of emotions from facial expressions. With a user-friendly interface and robust performance, the solution is applicable in various fields such as human-computer interaction, sentiment analysis, and mental health monitoring.