Automatic License Plate Recognition (ALPR)

Following are the main contents to follow, you can jump to any section:

• Introduction
  
• Tech Stack
  
• Infrastructure
  
• Run Locally
  
  • Environment Setup
    
  • Environment Variables
    
  • Run Project
    
• Conclusion
  

Introduction

Automatic License Plate Recognition (ALPR), has advanced in the past few years. With the ability to identify license plates and match them to stolen vehicles or drivers with outstanding warrants, officers have a valuable tool in crime fighting.

This project is a license plate recognition system that utilizes deep learning algorithms to recognize and extract license plate information from images or videos. The project is designed to identify license plates in various lighting and weather conditions, and can be used for applications such as traffic monitoring, parking management, and law enforcement.

Realtime Detection and Alerts

Tech Stack Used

1. Python
2. Cloud Storage
3. NoSQL
4. Deep learning algorithms
5. YOLOv8
6. Paddle OCR
7. Readtime Database

Infrastructure

1. Google Cloud Storage (GCS)
2. Firebase
3. GitHub
4. GPU

Run Locally

• Ensure you have Python 3.7+ installed.

• Create a new Python Conda environment:

conda create -n venv python=3.10  
conda activate venv 

OR

• Create a new Python virtual environment with pip:

virtualenv venv
source venv/Scripts/activate

Install dependencies

  pip install -r requirements.txt

Clone the project

  git clone https://github.com/Hassi34/automatic-license-plate-recognition.git

Go to the project directory

  cd automatic-license-plate-recognition

Export the environment variable

DATABASE_URL=""
STORAGE_BUCKET_URL=""

Run Project

  python detector.py

Conclusion

In conclusion, the implementation of automatic number plate recognition (ANPR) technology is a significant step forward in the field of automated traffic management systems. ANPR systems have the potential to greatly enhance the accuracy and efficiency of traffic surveillance, law enforcement, and parking management.

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📃 License

MIT © Hasanain

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