/Traffic-Sign-Recognition-PyQt5-YOLOv5-GUI

这是一个基于YOLOv5🚀的道路标志识别系统😊，使用了MySQL数据库💽，PyQt5进行界面设计🎨，PyTorch深度学习框架和TensorRT进行加速⚡，同时包含了CSS样式🌈。系统由五个主要模块组成：系统登录模块🔑负责用户登陆；初始化参数模块📋提供YOLOv5模型的初始化参数设置；标志识别模块🔍是系统的核心，负责对道路标志进行识别并将结果导入数据库；数据库模块💾包含基本数据库操作和数据分析两个子模块；图像处理模块🖼️负责单个图像的处理和数据增强。整个系统支持多种数据输入和模型切换，提供了包括mossic和mixup在内的图像增强方法📈。

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Road Sign Recognition Project Based on YOLOv5 (YOLOv5 GUI)

English | 简体中文

训练策略

This is a road sign recognition project based on YOLOv5, developed with a PyQt5 interface, YOLOv5 trained model, and MySQL database. The project consists of five modules: parameter initialization, sign recognition, database, data analysis, and image processing(Please refer to the Chinese document for details).

Screenshots

  • Sign Recognition Module

    img.png

  • Image Processing and Data Augmentation Module

    img_1.png

  • Parameter Initialization Module

    img_2.png

  • Database Module

    img_3.png

  • Data Analysis Module

    img_4.png

  • Login Interface

    img_5.png

Video

Road Sign Recognition System Based on YOLOV5

Getting Started

Run main.py.

Account and Password

  • admin 123456
  • 1 2
  • Modify the main function to enter directly

Project Modules

  • pt folder: Contains the model
  • main_with folder: login.py (login UI), win.py (main UI)
  • dialog folder: RTSP pop-up interface
  • apprcc_rc.py: Resource file
  • login_ji.py: Interface login logic file
  • run-exp52: Road sign recognition model trained for 300 epochs
  • tt100k_to_voc-main folder: JSON to YOLO format converter
  • Dataset: TT100k : Traffic-Sign Detection and Classification in the Wild

Install Dependencies

pip install -r requirements.txt

Acknowledgements