Driver-Drowsiness-Detection

Drowsiness detection is a safety technology that can prevent accidents that are caused by drivers who fell asleep while driving. This technology will alert the driver when drowsiness is detected. 😴 🚨

Contents of the Repository

• CNN Approach
• Transfer Learning Approach
• Readme
• Dataset
• Required Libraries
• Installation Setup
• Results
• Research Article
• Video Demonstration

Dataset

Sorry we were not able to upload dataset on GitHub due to size limitation
But you can find the links to download the dataset from the following text files

1. For CNN - Dataset.txt
2. For Transfer Learning - get_dataset.txt

Required Libraries

• keras
• cv2
• pygame
• numpy
• matplotlib
• glob
• tqdm

Installation Setup

1. Clone the repository

You can clone this repository using command: git clone https://github.com/rudrabarad/Driver-Drowsiness-Detection.git

2. Training respective model

• For CNN open and run DDDS_CNN/model_training.py
• For Transfer Learning open and run Transfer_learning/Model_Training_TL.ipynb

3. Execute all the cells consecutively to see the accuracy of both models.

4. Execute programs using the models

• For CNN run DDDS_CNN/main_capture.py
• For Transfer Learning run Transfer_learning/tl_capture.py

Note: Currently there is no Models folder in both CNN & Transfer folders but it will be created as soon as user executes model training file

Results

Approach	Training Accuracy	Validation Accuracy
CNN	99.01%	95.19%
Transfer Learning	82%	79%

Video

For viewing or downloading video click here 🎬

Facing any issues???

Feel free to open an issue. We are glad to help you. ❤️

License

Project is published under the MIT license.