https://github.com/mosesab/yolov11-drowsiness-detection

This repo contains the fine-tune implementation of a drowsy detection system, using a YOLO v11 model.
https://github.com/mosesab/yolov11-drowsiness-detection

computer-vision drowsiness-detection drowsiness-detection-python fine-tuning yolo yolov11

Last synced: about 1 month ago
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This repo contains the fine-tune implementation of a drowsy detection system, using a YOLO v11 model.

• Host: GitHub
• URL: https://github.com/mosesab/yolov11-drowsiness-detection
• Owner: mosesab
• License: mit
• Created: 2025-06-29T21:41:19.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2026-02-03T13:17:16.000Z (6 months ago)
• Last Synced: 2026-02-04T02:53:34.788Z (6 months ago)
• Size: 12.5 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
### YOLO v11 for Driver Drowsiness Detection

📌 **Notebook moved to Kaggle:**  

👉 https://www.kaggle.com/code/themosesab/yolov11-for-driver-drowsiness-detection

This repository contains a complete, end-to-end pipeline for training a YOLO v11 classification model to detect driver drowsiness using the ultralytics library.  

The project covers every stage of the machine learning lifecycle, from automated data acquisition and cleaning to model evaluation and explainability using GradCAM.

![alt text](https://img.shields.io/badge/Python-3.10-blue.svg)

![alt text](https://img.shields.io/badge/Framework-PyTorch-orange.svg)

![alt text](https://img.shields.io/badge/License-MIT-green.svg)

![alt text](https://img.shields.io/badge/Data-Kaggle-blue.svg)

### Quick Summary

Accuracy	99.80%	Overall correctness on the test set.

APCER	0.00%	Rate of 'Drowsy' drivers missed (False Negatives).

BPCER	0.41%	Rate of 'Non Drowsy' drivers flagged (False Positives).

ACER	0.21%	Average of APCER and BPCER.

### Acknowledgements

This project uses the following datasets from Kaggle:

- Driver Drowsiness Dataset (DDD) by ISMAIL NASRI.

- Drowsy Detection Dataset by YASHAR JEBRAEILY.

### License

This project is licensed under the MIT License. See the LICENSE file for details.