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License-plate Detection by YOLO

This repository contains a method to detect Iranian vehicle license plates as a representation of vehicle presence in an image. We have utilized You Only Look Once version 3 (YOLO v.3) to detect the license plates inside an input image. The method has the advantages of high accuracy and real-time performance, according to YOLO v.3 architecture. The presented system receives a series of vehicle images and produces the processed image with added bounding-boxes containing the vehicles' license plates. The flow of how we have trained and tested the application is published in a paper accessible from the citation section.

Sample output of the system

Environment

  • Python v.3
  • You Only Look Once (YOLO) v.3
  • A vehicle image dataset containing 3000+ samples (it will be available for academic usage soon)

How to employ?

You can download the weight file from this link.

Test on a single image:

python object_detection_yolo.py --image=bird.jpg

Test on a single video file:

python object_detection_yolo.py --video=cars.mp4

Test on the webcam:

python object_detection_yolo.py

Citation

Please cite us as below formation:

  1. S. Khazaee, A. Tourani, S. Soroori, A. Shahbahrami, and C. Y. Suen, “A Real-time License-Plate Detection Method using a Deep Learning Approach,” Lecture Notes in Computer Science (Springer, Cham), vol. 12068, pp. 425-438, 2020. (link)

Collaborators