AI tools for yolo 自瞄
Related Tools:
Ultralytics YOLO
Ultralytics YOLO is an advanced real-time object detection and image segmentation model that leverages cutting-edge advancements in deep learning and computer vision. It offers unparalleled performance in terms of speed and accuracy, making it suitable for various applications and easily adaptable to different hardware platforms. The comprehensive Ultralytics Docs provide resources to help users understand and utilize its features and capabilities, catering to both seasoned machine learning practitioners and newcomers to the field.
Ultralytics
Ultralytics is an AI tool that revolutionizes the world of Vision AI by enabling users to easily turn images into AI to get useful insights without writing any code. It offers a drag-and-drop interface for data input, model training, and deployment, making it accessible for startups, enterprises, data scientists, ML engineers, hobbyists, researchers, and academics. Ultralytics YOLO, the flagship tool, allows users to train machine learning models in seconds, select from pre-built models, test models on mobile devices, and deploy custom models to various formats. The tool is powered by Ultralytics Python package and is open-source, with a focus on computer vision, object detection, and image classification.
crossfire-yolo-TensorRT
This repository supports the YOLO series models and provides an AI auto-aiming tool based on YOLO-TensorRT for the game CrossFire. Users can refer to the provided link for compilation and running instructions. The tool includes functionalities for screenshot + inference, mouse movement, and smooth mouse movement. The next goal is to automatically set the optimal PID parameters on the local machine. Developers are welcome to contribute to the improvement of this tool.
RookieAI_yolov8
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.
aibydoing-feedback
AI By Doing is a hands-on artificial intelligence tutorial series that aims to help beginners understand the principles of machine learning and deep learning while providing practical applications. The content covers various supervised and unsupervised learning algorithms, machine learning engineering, deep learning fundamentals, frameworks like TensorFlow and PyTorch, and applications in computer vision and natural language processing. The tutorials are written in Jupyter Notebook format, combining theory, mathematical derivations, and Python code implementations to facilitate learning and understanding.
llm-course
The llm-course repository is a collection of resources and materials for a course on Legal and Legislative Drafting. It includes lecture notes, assignments, readings, and other educational materials to help students understand the principles and practices of drafting legal documents. The course covers topics such as statutory interpretation, legal drafting techniques, and the role of legislation in the legal system. Whether you are a law student, legal professional, or someone interested in understanding the intricacies of legal language, this repository provides valuable insights and resources to enhance your knowledge and skills in legal drafting.
blog
这是一个程序员关于 ChatGPT 学习过程的记录，其中包括了 ChatGPT 的使用技巧、相关工具和资源的整理，以及一些个人见解和思考。 **使用技巧** * **充值 OpenAI API**：可以通过 https://beta.openai.com/account/api-keys 进行充值，支持信用卡和 PayPal。 * **使用专梯**：推荐使用稳定的专梯，可以有效提高 ChatGPT 的访问速度和稳定性。 * **使用魔法**：可以通过 https://my.x-air.app:666/#/register?aff=32853 访问 ChatGPT，无需魔法即可访问。 * **下载各种 apk**：可以通过 https://apkcombo.com 下载各种安卓应用的 apk 文件。 * **ChatGPT 官网**：ChatGPT 的官方网站是 https://ai.com。 * **Midjourney**：Midjourney 是一个生成式 AI 图像平台，可以通过 https://midjourney.com 访问。 * **文本转视频**：可以通过 https://www.d-id.com 将文本转换为视频。 * **国内大模型**：国内也有很多大模型，如阿里巴巴的通义千问、百度文心一言、讯飞星火、阿里巴巴通义听悟等。 * **查看 OpenAI 状态**：可以通过 https://status.openai.com/ 查看 OpenAI 的服务状态。 * **Canva 画图**：Canva 是一个在线平面设计平台，可以通过 https://www.canva.cn 进行画图。 **相关工具和资源** * **文字转语音**：可以通过 https://modelscope.cn/models?page=1&tasks=text-to-speech&type=audio 找到文字转语音的模型。 * **可好好玩玩的项目**： * https://github.com/sunner/ChatALL * https://github.com/labring/FastGPT * https://github.com/songquanpeng/one-api * **个人博客**： * https://baoyu.io/ * https://gorden-sun.notion.site/527689cd2b294e60912f040095e803c5?v=4f6cc12006c94f47aee4dc909511aeb5 * **srt 2 lrc 歌词**：可以通过 https://gotranscript.com/subtitle-converter 将 srt 格式的字幕转换为 lrc 格式的歌词。 * **5 种速率限制**：OpenAI API 有 5 种速率限制：RPM（每分钟请求数）、RPD（每天请求数）、TPM（每分钟 tokens 数量）、TPD（每天 tokens 数量）、IPM（每分钟图像数量）。 * **扣子平台**：coze.cn 是一个扣子平台，可以提供各种扣子。 * **通过云函数免费使用 GPT-3.5**：可以通过 https://juejin.cn/post/7353849549540589587 免费使用 GPT-3.5。 * **不蒜子 统计网页基数**：可以通过 https://busuanzi.ibruce.info/ 统计网页的基数。 * **视频总结和翻译网页**：可以通过 https://glarity.app/zh-CN 总结和翻译视频。 * **视频翻译和配音工具**：可以通过 https://github.com/jianchang512/pyvideotrans 翻译和配音视频。 * **文字生成音频**：可以通过 https://www.cnblogs.com/jijunjian/p/18118366 将文字生成音频。 * **memo ai**：memo.ac 是一个多模态 AI 平台，可以将视频链接、播客链接、本地音视频转换为文字，支持多语言转录后翻译，还可以将文字转换为新的音频。 * **视频总结工具**：可以通过 https://summarize.ing/ 总结视频。 * **可每天免费玩玩**：可以通过 https://www.perplexity.ai/ 每天免费玩玩。 * **Suno.ai**：Suno.ai 是一个 AI 语言模型，可以通过 https://bibigpt.co/ 访问。 * **CapCut**：CapCut 是一个视频编辑软件，可以通过 https://www.capcut.cn/ 下载。 * **Valla.ai**：Valla.ai 是一个多模态 AI 模型，可以通过 https://www.valla.ai/ 访问。 * **Viggle.ai**：Viggle.ai 是一个 AI 视频生成平台，可以通过 https://viggle.ai 访问。 * **使用免费的 GPU 部署文生图大模型**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 部署文生图大模型。 * **语音转文字**：可以通过 https://speech.microsoft.com/portal 将语音转换为文字。 * **投资界的 ai**：可以通过 https://reportify.cc/ 了解投资界的 ai。 * **抓取小视频 app 的各种信息**：可以通过 https://github.com/NanmiCoder/MediaCrawler 抓取小视频 app 的各种信息。 * **马斯克 Grok1 开源**：马斯克的 Grok1 模型已经开源，可以通过 https://github.com/xai-org/grok-1 访问。 * **ChatALL**：ChatALL 是一个跨端支持的聊天机器人，可以通过 https://github.com/sunner/ChatALL 访问。 * **零一万物**：零一万物是一个 AI 平台，可以通过 https://www.01.ai/cn 访问。 * **智普**：智普是一个 AI 语言模型，可以通过 https://chatglm.cn/ 访问。 * **memo ai 下载**：可以通过 https://memo.ac/ 下载 memo ai。 * **ffmpeg 学习**：可以通过 https://www.ruanyifeng.com/blog/2020/01/ffmpeg.html 学习 ffmpeg。 * **自动生成文章小工具**：可以通过 https://www.cognition-labs.com/blog 生成文章。 * **简易商城**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 搭建简易商城。 * **物联网**：可以通过 https://www.cnblogs.com/xuxiaona/p/18088404 学习物联网。 * **自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表**：可以通过 https://www.cnblogs.com/whuanle/p/18086537 实现自定义表单、自定义列表、自定义上传和下载、自定义流程、自定义报表。 **个人见解和思考** * ChatGPT 是一个强大的工具，可以用来提高工作效率和创造力。 * ChatGPT 的使用门槛较低，即使是非技术人员也可以轻松上手。 * ChatGPT 的发展速度非常快，未来可能会对各个行业产生深远的影响。 * 我们应该理性看待 ChatGPT，既要看到它的优点，也要意识到它的局限性。 * 我们应该积极探索 ChatGPT 的应用场景，为社会创造价值。
awesome-LLM-resources
This repository is a curated list of resources for learning and working with Large Language Models (LLMs). It includes a collection of articles, tutorials, tools, datasets, and research papers related to LLMs such as GPT-3, BERT, and Transformer models. Whether you are a researcher, developer, or enthusiast interested in natural language processing and artificial intelligence, this repository provides valuable resources to help you understand, implement, and experiment with LLMs.
PythonPark
PythonPark is a paradise for learning Python, providing babysitter-level tutorials on AI labs, treasure videos, data structures, study guides, machine learning practicals, deep learning practicals, Python basics, web scraping, big company interview experiences, programming life, and resource sharing. Original articles are published at least twice a week, with the latest articles being first released on WeChat and videos on Bilibili. Join the WeChat group for technical discussions or to provide feedback. Continuously improving and outputting content!
nndeploy
nndeploy is a tool that allows you to quickly build your visual AI workflow without the need for frontend technology. It provides ready-to-use algorithm nodes for non-AI programmers, including large language models, Stable Diffusion, object detection, image segmentation, etc. The workflow can be exported as a JSON configuration file, supporting Python/C++ API for direct loading and running, deployment on cloud servers, desktops, mobile devices, edge devices, and more. The framework includes mainstream high-performance inference engines and deep optimization strategies to help you transform your workflow into enterprise-level production applications.
awesome-cuda-tensorrt-fpga
Okay, here is a JSON object with the requested information about the awesome-cuda-tensorrt-fpga repository:
