
RookieAI_yolov8
基于yolov8实现的AI自瞄项目 AI self-aiming project based on yolov8
Stars: 340

RookieAI_yolov8 is an open-source project designed for developers and users interested in utilizing YOLOv8 models for object detection tasks. The project provides instructions for setting up the required libraries and Pytorch, as well as guidance on using custom or official YOLOv8 models. Users can easily train their own models and integrate them with the software. The tool offers features for packaging the code, managing model files, and organizing the necessary resources for running the software. It also includes updates and optimizations for better performance and functionality, with a focus on FPS game aimbot functionalities. The project aims to provide a comprehensive solution for object detection tasks using YOLOv8 models.
README:
[!IMPORTANT] 使用前请先阅读参数解释文档
[!NOTE] 前言:为什么不提供直接打包成型的软件?
每个程序都有独立的特征码,如果大家都使用同一个程序,一旦其中一个人被BAN其他人会被联BAN。所以鼓励大家自行修改部分代码并自行打包即可避免此类情况发生。
Version | Python |
---|---|
2.4.3或更早 |
3.7+ |
2.4.4.2+ |
3.10+ |
- 使用以下代码获取本代码需要的库与Pytorch库
✨ 超高速无痛下载 ✨
pip install -r requirements.txt -i https://pypi.doubanio.com/simple/
pip uninstall torch torchvision torchaudio
pip install torch torchvision torchaudio -f https://mirror.sjtu.edu.cn/pytorch-wheels/torch_stable.html --no-index
海外用户请使用以下命令
pip install -r requirements.txt
pip uninstall torch torchvision torchaudio
pip install torch torchvision torchaudio -f https://download.pytorch.org/whl/torch_stable.html --no-index
-
你还需要一个自己的模型(目前支持.pt/.engine/.onnx模型),如果没有可暂时使用ultralytics官方模型
-
当未找到模型时会自动下载YOLOv8n模型,你也可以⬇️
访问YOLOv8GitHub界面获取更多官方yolov8模型以快速开始
访问ultralytics官网查看官方网站帮助文档
- 运行
在脚本所在目录打开终端,键入以下内容并回车
python RookieAI.py
建议自行训练
V3.0预告
3.0版本注重使用多线程进行优化,理论上可以提升截图效率与推理效率,但是可能会导致延迟问题。当然也提供原始的单进程推理模式可供选择。
该版本从底层代码到UI界面进行了完全重构,多线程也可以带来更多使用上的优化,例如可随意调整鼠标移动的频率,不再受到推理帧数的限制等。目前测试主系统空载YOLO使用YOLO11n模型推理的帧数从55提升到了80,有明显提升。配合独立的鼠标移动进程,理论上可以带来不错的使用体验。
对电脑配置的要求也会有一定程度的降低。代码目前处于早期开发阶段,未集成Aimbot等基础功能,开发进度与源代码请稍后关注对应文档。
推荐使用Atlas游戏系统配合boosterX性能优化软件获得更好体验
AtlasOS对 Windows 进行修改,专为游戏玩家设计。具有更高的游戏帧率和更低的延迟。同时在此系统上使用RookieAI可更高效的利用GPU资源得到更高的推理帧率。
boosterX是一款系统优化软件,优化Windows,降低延迟、提高 FPS。在AtlasOS系统上使用可进一步进行优化。
配置单: 截图模式:mss 截图高/宽:320 显卡:RTX4080M 模型:YOLOv8s_TheFinals_teammate_enemy_04.engine
原版windows空载运行RookieAI2.4.3 对比 AtlasOS 空载运行RookieAI2.4.3:
此项目最初目的为Apex的Aimbot,未考虑其他游戏,可能会出现因反作弊禁止WIN32移动方式而无法使用的情况!
已知游戏:VALORANT
面对日益增多的配置文件参数,我新建了参数解释文档,里面介绍了配置文件内所有参数的信息,前往参数解释文档查看。
❗V3支持KmBoxNet,VALORANT确认可用
🎉🎉🎉非常感谢由RicardoJoaquim提供的英文特别版本🎉🎉🎉
Current latest version: ###
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