Project Description
Driver fatigue is one of the major causes of accidents in the world. Detecting the drowsiness of the driver is one of the surest ways of measuring driver fatigue. In this project, we aim to develop a drowsiness detection system. This system works by monitoring the eyes of the driver and sounding an alarm when he/she is drowsy.
The system so designed is a non-intrusive real-time monitoring system. The priority is on improving the safety of the driver without being obtrusive. In this project, the eye blink of the driver is detected. If the driver’s eyes remain closed for more than a certain period of time, the driver is said to be drowsy and an alarm is sounded. The programming for this is done in OpenCV using the Haarcascade library for the detection of facial features.
Note:- You will need to have a basic understanding of how Jupyter notebook works to successfully execute the project.
refer this to get a basic understanding of jupyter notebook
OBJECTIVE:
To build a drowsiness detection system that will detect that a person’s eyes are closed for a few seconds.
Implementation and Output
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| Converting the images to grayscale |
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| creating categories from the dataset |