基于Pytorch使用深度学习的方案对中国车牌进行检测和识别.zip

# License-plate Detection by YOLO # Author:电子科技大学刘俊凯、陈昂 # https://github.com/JKLinUESTC/License-Plate-Recognization-Pytorch ## 代码运行要点 YOLOv3运行的时候需要输入命令语句python object_detection_yolo.py --image=图片名.jpg YOLOv3的权重模型，可以从链接：https://pan.baidu.com/s/1I2Hv__uiN7ql7RLe99nWsw 提取码：rsue得到 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.  ## 运行环境 - 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](https://drive.google.com/file/d/1vXjIoRWY0aIpYfhj3TnPUGdmJoHnWaOc/ "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**,” 2nd International Conference on Pattern Recognition and Artificial Intelligence, Zhongshan, 2020. ([link](https://users.encs.concordia.ca/~icprai20/ "link")) ## Collaborators - [Sajjad Soroori](https://github.com/SajjadSo "Sajjad Soroori") - [Ali Tourani](https://github.com/alitourani "Ali Tourani")