Drowsiness Detection

[praveenarjun]

To create an announcement text for your model, please provide the key details about the model, such as its main features, purpose, and the specific benefits it provides. This will help in drafting a clear and impactful announcement.

Result
https://user-images.githubusercontent.com/73580507/159136371-943b6761-0a8f-44af-a471-ff0b78d18514.gif

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

[praveenarjun]

pls provide labels for this pull request

[UppuluriKalyani]

@praveenarjun can you please add readme file with clear description and also attach results how code works

[praveenarjun]

yes I will Add read me file Even In readme file i need to show which type of model i used and about my data too or my use cases

[praveenarjun]

README.md

I pull request But I am unable to see the changes Can you check where i am facing the issue
From vs code I commit and I use git push origin main command and I push in github but i cant see any changes can you pls check and conform it

[praveenarjun]

pls give me labels so that it will be helpfull

[praveenarjun]

how much time it take to review the changes

[UppuluriKalyani]

how much time it take to review the changes

Please mention the issue you solved

[praveenarjun]

The issue I proposed is a Feature request "Implement Drowsiness Detection to Enhance Driver Safety"
Title

Implement Drowsiness Detection to Enhance Driver Safety
Description

Integrate a drowsiness detection system using the YOLOv5 model to monitor driver alertness in real-time. This feature aims to enhance driver safety by detecting signs of drowsiness and providing timely alerts to prevent accidents.
Objectives

Develop a machine learning model using YOLOv5 for drowsiness detection.
Integrate the model into the existing driver monitoring system.
Ensure real-time processing and alerting capabilities.

Proposed Solution

Data Collection: Gather a dataset of images or videos depicting drowsy and alert drivers.
Model Training: Train the YOLOv5 model on the collected dataset to accurately detect drowsiness.
Integration: Incorporate the trained model into the driver monitoring system.
Real-time Processing: Implement real-time image or video processing to continuously monitor the driver's state.
Alert System: Develop a mechanism to alert the driver when signs of drowsiness are detected.

Benefits

Enhances road safety by preventing drowsiness-related accidents.
Provides a real-time monitoring solution for drivers.
Utilizes advanced machine learning techniques to ensure high accuracy.

Additional Information

Related Projects: Mention any related projects or previous work done in this area within the repository.
Dependencies: List any dependencies or libraries required for implementing this feature.
Milestones: Outline the key milestones and timelines for the development of this feature.

References

[YOLOv5 Documentation](https://github.com/ultralytics/yolov5)
Existing Driver Monitoring Systems

[praveenarjun]

solved issue #69
GSSOC'24 Extended and Hacktoberfest