{"id":13645083,"url":"https://github.com/Lucid1ty/Yolov5ForCSGO","last_synced_at":"2025-04-21T13:31:43.623Z","repository":{"id":40392559,"uuid":"496882786","full_name":"Lucid1ty/Yolov5ForCSGO","owner":"Lucid1ty","description":"CSGO agent detection and auto 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Detection Applications"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# Yolov5ForCSGO\n\n[English](../README.md) | 简体中文\n\n\n![GitHub Repo stars](https://img.shields.io/github/stars/Lucid1ty/Yolov5ForCSGO?style=social)\n![GitHub issues](https://img.shields.io/github/issues/Lucid1ty/Yolov5ForCSGO)\n![GitHub forks](https://img.shields.io/github/forks/Lucid1ty/Yolov5ForCSGO?style=social)\n![GitHub watchers](https://img.shields.io/github/watchers/Lucid1ty/Yolov5ForCSGO?style=social)\n\u003cdiv\u003e\n\n\n\u003c/div\u003e\n\n\u003cp\u003e\n    本项目利用 \u003ca href=\"https://github.com/ultralytics/yolov5\"\u003eYOLOv5\u003c/a\u003e 实现 CSGO 游戏中的人物检测和自动瞄准\n\nYOLOv5🚀是一个在COCO数据集上预训练的物体检测架构和模型系列，它代表了\u003ca href=\"https://ultralytics.com\"\u003eUltralytics\u003c/a\u003e对未来视觉AI方法的公开研究，其中包含了在数千小时的研究和开发中所获得的经验和最佳实践。\n\u003c/p\u003e\n\n\u003cdiv align=\"center\"\u003e\n   \u003ca href=\"https://www.oscs1024.com/project/oscs/Lucid1ty/Yolov5ForCSGO?ref=badge_small\" alt=\"OSCS Status\"\u003e\n   \u003cimg src=\"https://www.oscs1024.com/platform/badge/Lucid1ty/Yolov5ForCSGO.svg?size=small\"/\u003e\n   \u003c/a\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\n\n## \u003cdiv align=\"center\"\u003eYOLOv5文档\u003c/div\u003e\n请参阅[YOLOv5 Docs](https://docs.ultralytics.com)，了解有关训练、测试和部署的完整文件。\n\n## \u003cdiv align=\"center\"\u003e快速上手\u003c/div\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003e安装\u003c/summary\u003e\n\n下载本仓库，然后确保在[**Python\u003e=3.7.0**](https://www.python.org/) 的环境中使用并安装 [requirements.txt](https://github.com/Lucid1ty/Yolov5ForCSGO/blob/main/requirements.txt)，包括[**PyTorch\u003e=1.7**](https://pytorch.org)。\n```bash\npip install -r requirements.txt\n```\n\n\u003c/details\u003e\n\u003cdetails open\u003e\n\u003csummary\u003e使用\u003c/summary\u003e\n\u003cul\u003e\n\u003cli\u003e请使用管理员身份打开你的Pycharm(或者别的IDE)，然后在CSGO的设置中 : 鼠标\u0026键盘 -\u003e 原生输入 -\u003e 关闭\u003c/li\u003e\n\u003cli\u003e如果你没有权重文件并且想直接用我给你提供的权重文件，那么直接运行 aim-csgo 目录下的 main.py\u003c/li\u003e\n\u003cli\u003e如果你已经有了权重文件(类似于 xxx.pt)并且不想用我给你提供的权重文件，那么直接打开 aim-csgo/CSGOModels 这个目录，将自己的权重文件放进去，然后打开 aim-csgo/cs_model.py ，将第 13 行代码修改(改为你自己的权重文件路径)。然后运行 main.py\u003c/li\u003e\n\u003cli\u003e如果你没有权重文件又不想用我提供的权重文件，那么请先训练自己的权重文件，然后参考上一条\u003c/li\u003e\n\u003cli\u003e成功运行 main.py 后，你会看到一个检测窗口，这时候你可以通过按下鼠标侧键(mouse5)来打开自瞄模式\u003c/li\u003e\n\u003cli\u003e关闭本程序 : 单击检测窗口，然后按下q\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/details\u003e\n\n\n## \u003cdiv align=\"center\"\u003e贡献\u003c/div\u003e\n\n开始之前请先点击并查看 : [贡献指南](../CONTRIBUTING.md)\n\n\n## \u003cdiv align=\"center\"\u003e联系\u003c/div\u003e\n\n关于 Yolov5ForCSGO 的漏洞和功能问题，请访问 [GitHub Issues](https://github.com/Lucid1ty/Yolov5ForCSGO/issues)。\n\n\n\u003cdiv align=\"center\"\u003e\n    \u003ca href=\"https://github.com/Lucid1ty\"\u003e\n        \u003cimg src=\"https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-github.png\" width=\"3%\"/\u003e\n    \u003c/a\u003e\n\u003c/div\u003e\n\n[assets]: https://github.com/Lucid1ty/Yolov5ForCSGO/releases\n\n\n# 本项目搭建教程\n\nComing soon...\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FLucid1ty%2FYolov5ForCSGO","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FLucid1ty%2FYolov5ForCSGO","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FLucid1ty%2FYolov5ForCSGO/lists"}