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
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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