Tunisian License Plate - Arabic Text Detection (YOLOv8s)
This model detects the Arabic word "ุชููุณ" (Tunis) in Tunisian license plates using YOLOv8s.
Model Description
- Model Type: YOLOv8s (Small)
- Task: Object Detection
- Classes: 1 class - "tunis" (Arabic text region)
- Purpose: Detecting and localizing the word "ุชููุณ" in Tunisian license plates for OCR preprocessing
Use Case
This model is designed to be used as a preprocessing step for license plate OCR:
- Detect the Arabic text "ุชููุณ" region
- Mask or crop this region
- Apply OCR on the remaining numeric characters for better accuracy
Training Details
- Base Model: YOLOv8s pretrained weights
- Image Size: 512x512
- Framework: Ultralytics YOLOv8
- Training Dataset: Tunisian license plate images
Usage
from ultralytics import YOLO
# Load the model
model = YOLO("yassine-mhirsi/tunis-word-detection-yolov8s")
# Run inference
results = model.predict("path/to/license_plate.jpg", conf=0.5)
# Process results
for result in results:
boxes = result.boxes
for box in boxes:
print(f"Confidence: {box.conf[0]:.2f}")
print(f"Bounding Box: {box.xyxy[0]}")
Model Files
best.pt- Best weights from traininglast.pt- Last checkpoint- Training metrics and visualizations included
Example
Citation
If you use this model, please cite:
@misc{tunis-word-detection-yolov8s,
authors = {Yassine Mhirsi,Malek Messaoudi},
title = {Tunisian License Plate Arabic Text Detection},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/Safe-Drive-TN/tunis-word-detection-yolov8s/}}
}
License
MIT License
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