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--- |
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title: Driver Drowsiness Detection |
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emoji: 🚗 |
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colorFrom: blue |
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colorTo: indigo |
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sdk: gradio |
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sdk_version: 5.31.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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paper: arxiv.org/abs/2505.17392 |
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--- |
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# Driver Drowsiness Detection System |
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This is a real-time driver drowsiness detection system that uses computer vision and deep learning to detect signs of drowsiness in drivers. The system can process webcam feeds, video files, and single images. |
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## Features |
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- Real-time webcam monitoring |
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- Video file processing |
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- Single image analysis |
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- Face detection and drowsiness prediction |
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- Visual feedback with bounding boxes and status indicators |
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## How to Use |
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1. **Webcam Mode**: Click the "Start Webcam" button to begin real-time monitoring |
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2. **Video Mode**: Upload a video file for processing |
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3. **Image Mode**: Upload a single image for analysis |
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The system will display the results with: |
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- Green box: Alert (not drowsy) |
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- Red box: Drowsy |
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- Probability score for drowsiness |
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## Technical Details |
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- Built with PyTorch and Vision Transformer (ViT) |
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- Uses OpenCV for face detection |
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- Gradio interface for easy interaction |
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- Real-time processing capabilities |
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## Model |
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The system uses a Vision Transformer (ViT) model trained on driver drowsiness detection. The model is capable of detecting subtle signs of drowsiness in facial expressions. |
