--- language: en license: mit tags: - yolov8 - object-detection - license-plate - arabic-text - tunisia - computer-vision library_name: ultralytics pipeline_tag: object-detection datasets: - Safe-Drive-TN/tunis-word-tunisian-license-plate --- # Tunisian License Plate - Arabic Text Detection (YOLOv8s) This model detects the Arabic word "تونس" (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 "تونس" in Tunisian license plates for OCR preprocessing ## Use Case This model is designed to be used as a preprocessing step for license plate OCR: 1. Detect the Arabic text "تونس" region 2. Mask or crop this region 3. 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 ```python 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 training - `last.pt` - Last checkpoint - Training metrics and visualizations included ## Example ![Tunisian License Plate](https://huggingface.co/Safe-Drive-TN/tunis-word-detection-yolov8s/resolve/main/runs/detect/predict/100_jpg.rf.aaedf56d49016b0342c4b68049cbc360.jpg) ## 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