https://github.com/arij01/platepatrol
UK license plate detection using YOLOv8
https://github.com/arij01/platepatrol
computer-vision deep-learning easyocr opencv python tracking-algorithm yolov8
Last synced: 4 months ago
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UK license plate detection using YOLOv8
- Host: GitHub
- URL: https://github.com/arij01/platepatrol
- Owner: arij01
- License: other
- Created: 2024-07-19T14:06:46.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-12-23T16:01:42.000Z (6 months ago)
- Last Synced: 2025-01-06T19:58:21.699Z (6 months ago)
- Topics: computer-vision, deep-learning, easyocr, opencv, python, tracking-algorithm, yolov8
- Language: Python
- Homepage:
- Size: 914 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: license_plate_detector.pt
- Security: SECURITY.md
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README
# PlatePatrol
https://github.com/user-attachments/assets/8551d49c-a361-4bf1-b01e-b2fe9fd7bf5e
## Description
This project develops a real-time vehicle detection and license plate recognition system using advanced deep learning techniques. By integrating the YOLO (You Only Look Once) model for object detection and the SORT (Simple Online and Realtime Tracking) algorithm for tracking, the system efficiently identifies and tracks vehicles in video footage. Additionally, it utilizes a specialized model for accurately detecting and reading license plate numbers.
## Data
The video I used in this tutorial can be downloaded [here](https://www.pexels.com/video/traffic-flow-in-the-highway-2103099/).
## Model
A Yolov8 pre-trained model (YOLOv8n) was used to detect vehicles.
A licensed plate detector was used to detect license plates. The model was trained with Yolov8 using this [dataset](https://universe.roboflow.com/roboflow-universe-projects/license-plate-recognition-rxg4e/dataset/4).
## Dependencies
The sort module needs to be downloaded from this [repository](https://github.com/abewley/sort).
## Installation
To get started, follow these steps:
1. **Clone the repository:**
```bash
git clone https://github.com/arij01/automatic-number-plate-recognition.git
2. **Navigate to the project directory:**
```bash
cd automatic-number-plate-recognition
3. **Install dependencies:**
```bash
pip install -r requirements.txt
4. **Run main.py:**
```bash
python main.py
5. **Run the add_missing_data.py file:**
```bash
python add_missing_data.py
6. **Run the visualize.py file:**
```bash
python visualize.py