Object Detection
ultralytics
English
driver-monitoring
drowsiness-detection
yolo
computer-vision
safety
Instructions to use raj5517/safedrive-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use raj5517/safedrive-model with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("raj5517/safedrive-model") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
SafeDrive Model Suite
Models powering the safedrive-ai Python SDK for real-time driver monitoring.
Files
| File | Purpose | Accuracy |
|---|---|---|
yolo_safedrive.pt |
YOLOv8-nano, 9-class detection | mAP50=0.940 |
mobilenet_webcam.pth |
MobileNetV3 eye classifier (webcam fine-tuned) | 97.99% |
mobilenet_best.pth |
MobileNetV3 eye classifier (lab-trained) | 97.99% |
drowsiness_cnn_best.pth |
Custom CNN eye classifier | 96.74% |
face_landmarker.task |
MediaPipe face landmark model | — |
Classes (YOLO)
eye_open, eye_half, eye_closed, mouth_open, mouth_closed, phone, cigarette, seatbelt_on, seatbelt_off
Usage
pip install safedrive-ai
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