https://github.com/sayamalt/driver-drowsiness-detection

Successfully established a deep learning model which can accurately predict the drowsiness state of an individual and thereby alert a driver who is in a drowsy state for preventing fatal accidents.
https://github.com/sayamalt/driver-drowsiness-detection

convolutional-neural-networks deep-learning driver-drowsiness-detection opencv

Last synced: 4 months ago
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Successfully established a deep learning model which can accurately predict the drowsiness state of an individual and thereby alert a driver who is in a drowsy state for preventing fatal accidents.

• Host: GitHub
• URL: https://github.com/sayamalt/driver-drowsiness-detection
• Owner: SayamAlt
• Created: 2022-08-23T11:03:28.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2022-11-13T09:19:17.000Z (over 3 years ago)
• Last Synced: 2025-04-10T02:47:49.843Z (about 1 year ago)
• Topics: convolutional-neural-networks, deep-learning, driver-drowsiness-detection, opencv
• Language: Jupyter Notebook
• Homepage:
• Size: 944 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Driver-Drowsiness-Detection

## Objective

Day and night, the roadway is filled with uncountable vehicles. People who travel long distances and those who operate heavy machinery all experience sleep deprivation. Consequently, driving while drowsy is quite risky. The reason for the majority of accidents is the drowsiness of the driver. Continuous driving can be tedious and exhausting. A driver may get drowsy and perhaps nod off due to inactivity. In this project, I've developed a drowsy driver detection system to address such an issue.

![Driver Drowsiness](https://repository-images.githubusercontent.com/322089592/8646cd80-403a-11eb-86c7-07ac8f8bc482)

![Driver Drowsiness Detection](https://www.eetasia.com/wp-content/uploads/sites/2/2020/04/eye-trackinh.jpg)

![Driver Sleepiness](https://assets-global.website-files.com/595d6b420002832258c527cb/618abc9cdfbae01bc36d2ce5_hero_advanced_drowsiness.jpg)

## Dataset Used

Link: https://www.kaggle.com/datasets/serenaraju/yawn-eye-dataset-new

## Content

The dataset is divided into train and test sets with each set consisting of 4 target classes, namely "Closed", "no_yawn", "yawn" and "Open". 

## Technologies Used



  
Keras

  
Tensorflow

  
OpenCV

  
Numpy

  
Scikit-learn

  
Pillow(PIL)

  
Matplotlib

  
Seaborn