Skip to main content

Automatic Number Plate Recognition System

Project description

ANPRS (Automatic Number Plate Recognition System)

This project served as the B.Tech project of four Electrical Engineering students in 2022.

Usage

  1. Install Package (Requires python 3.x)
    pip install anprs
    
  2. Sample Usage
     from anprs.anprs import LPR, OCR
    
     lpr = LPR()
     ocr = OCR()
    
     image_path = 'path/to/your/image'
    
     lpr_res = lpr.perform_lpr(image_path)
    
     license_plate_number = ""
    
     if lpr_res:
         license_plate_number = ocr.get_results()
     else:
         print('License plate not detected')
    
     print(lpr_res, license_plate_number)
    

Research Paper

The implementation in this repository corresponds to the following research paper:

Title: Deep Learning-based approach for Indian License Plate Recognition using Optical Character Recognition

Authors:

  • Aditya Upadhye
  • Atharvraj Patil
  • Jayesh Ingale
  • Sakshi Jaiswal
  • Suhas Kakade
  • Abhishek Bhatt

Link: https://ieeexplore.ieee.org/abstract/document/10183391

Build Project

  1. Setup Virtual Env
# create virtual env
python -m venv local_env

# use this to activate the environment
source local_env/Scripts/activate

# install dependencies
pip install -r requirements.txt
  1. Create Media Folder in root directory
  2. Add your image of a vehicle and rename it to photo.jpg

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

anprs-0.0.5.tar.gz (14.6 MB view details)

Uploaded Source

Built Distribution

anprs-0.0.5-py3-none-any.whl (14.6 MB view details)

Uploaded Python 3

File details

Details for the file anprs-0.0.5.tar.gz.

File metadata

  • Download URL: anprs-0.0.5.tar.gz
  • Upload date:
  • Size: 14.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.19

File hashes

Hashes for anprs-0.0.5.tar.gz
Algorithm Hash digest
SHA256 d0e3dc07f7276270f81dc61b5ae2af68fcb31338ffaf0a79aff52c65a996d29b
MD5 c114431a2c3e303df9a1b18a5abc2578
BLAKE2b-256 f1ff57eb08094df47d91a2b3a8e7dd2136cf867f42265afd8959fa316c14681e

See more details on using hashes here.

File details

Details for the file anprs-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: anprs-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 14.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.19

File hashes

Hashes for anprs-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 df63cdefc63b5e7979aeca714c2348b97d742e7c9868a945ab65c60674b5d78c
MD5 2f489b799bb3d7bc9d529ee1a69aeeda
BLAKE2b-256 a5b532725c419415b862a8505a9d4223803abd849f852c1748b7739ca461a8ca

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page