ALPR Plate Detection Model
Overview
This repository contains a fine-tuned YOLO-based model for detecting Saudi vehicle license plates as part of a complete Automatic License Plate Recognition (ALPR) pipeline.
The model is designed to accurately localize license plates in images before they are passed to the OCR stage for character recognition.
Model Details
- Task: License Plate Detection
- Framework: Ultralytics YOLO (PyTorch)
- Input: RGB image
- Output: Bounding box coordinates of detected license plates
Intended Use
This model is intended for:
- Automatic License Plate Recognition (ALPR)
- Smart Parking Systems
- Traffic Monitoring
- Access Control Systems
- Computer Vision Research
- Educational Purposes
Repository Contents
best.pt — Fine-tuned model weights
Training
This model was fine-tuned specifically for Saudi license plate detection.
The training dataset is not included in this repository.
Usage
Load the model using the Ultralytics YOLO API:
1from ultralytics import YOLO
2
3model = YOLO("best.pt")
4results = model("image.jpg")
Source Code
The complete ALPR pipeline, including preprocessing, OCR integration, visualization, and application logic, is available in the corresponding GitHub repository.
License
See the repository license for usage terms.
