基于pytorch框架和yolov5实现第一人称射击(FPS)游戏的辅助瞄准系统源码+项目说明.zip

上传者: DeepLearning_ | 上传时间: 2022-12-16 15:26:17 | 文件大小: 3.24MB | 文件类型: ZIP
基于pytorch框架和yolov5实现第一人称射击(FPS)游戏的辅助瞄准系统源码+项目说明.zip ​ 本程序基于pytorch框架与yolov5物体检测平台,实现了人工智能对FPS(第一人称射击)游戏的辅助瞄准。与传统游戏作弊方式不同,本程序不读取或改动游戏的内存数据,而是通过人工智能实时分析游戏画面、确定敌人位置并移动鼠标射击,反应流程与人脑相同,难以被普通反作弊方式检测。本程序的特点有: 单次识别过程经过反复优化,在RTX30系显卡下单次时延$\leq 0.1s$​ 前后端分离,前端启动器UI界面现代化、扁平化,提供参数调节功能并与后端通过json参数共享 设计演示模式,实时展现AI的识别过程 设计静态和动态模式,在敌人静态和近匀速运动时有可观的射击精准度 适配多款射击游戏,对CS:GO(《反恐精英:全球攻势》)单独优化,考虑到鼠标加速与鼠标灵敏度设置对程序参数的影响

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