dhia619/License-plate-detector-TN
Record type:
model
Creator:
dhi
Host:
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