dhia619/License-plate-detector-TN

Object detection model for car license plate in tunisia # Tunisian Car License Plate Detection using YOLOv8 🚗: This repository contains a fine-tuned YOLOv8 model for detecting car license plates in tunisia. The model has been trained and optimized for accurate plate detection in various environments. The `tn_car_license_plate.pt` file provided here contains the trained weights of the model. ## Overview This project uses the YOLOv8 architecture to detect car license plates. YOLOv8 is a powerful and efficient object detection framework that achieves state-of-the-art results while being lightweight and fast. The fine-tuned model is suitable for: - Real-time car plate detection. --- ## Getting Started ### Requirements - Python - PyTorch - `ultralytics` package (for YOLOv8) ### Installation 1. Clone this repository: ```bash git clone github.com ``` 2. Install dependencies: ```bash pip install -r requirements.txt ``` ### Usage 1. Loading the Model: ```python from ultralytics import model = YOLO("tn_car_license_plate.pt") ``` 2. Running Inference: ```python # Run inference on an image results = model("path/to/your/image.jpg") ``` ```python # Run inference on a video results = model("path/to/your/video.mp4", save=True) # Output video with detections saved in the `runs/detect` directory ``` ### Dataset - collected 104 images from different videos, images were taken from different angles and in different lighting conditions. - Manually labeled the images using Make Sense. ### Training details: - **Model** : YOLOv8 medium - **Epochs** : 15 - **Training images** : 104