Drowsiness Detection System using Deep Learning

Developed a Deep Learning-based system to detect driver drowsiness in real-time by analyzing eye state (open/closed) using computer vision techniques.

Built and trained a Convolutional Neural Network (CNN) model to classify eye status from video frames.

Integrated the model with real-time video processing using OpenCV to monitor live camera input.

Implemented an alert mechanism that triggers a warning when signs of drowsiness are detected.

The project was developed using Python with libraries such as TensorFlow/Keras and OpenCV