Driver Drowsiness Detection System Using Computer Vision

Developed a driver drowsiness detection system using computer vision and machine learning techniques to help detect signs of driver fatigue.

The project processes images to detect faces and eyes and applies image processing techniques for fatigue analysis. The system uses Python, OpenCV, and machine learning techniques to preprocess images, extract features, train a classification model, and evaluate the results.

Key features include face detection, eye detection, image preprocessing, feature extraction, data augmentation, model training, and fatigue classification.