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 plates inside an input image. The method has the advantages of high accuracy and real-time performance, thanks 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.
- Python v.3
- You Only Look Once (YOLO) v.3
- A vehicle image dataset containing 3000+ samples
You can download the weights file from this link. It can also be downloaded from the weights folder (splitted files).
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
Please cite the following paper:
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)