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AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
This is the project for implementing a chip-8 emulator for the software training course at the end of the 2025 autumn to 2026 spring semester, which is taught by Teacher Li Kuan.
A powerful and artistic UI library based on PyQt5，基于 PyQt5 的UI框架，灵动、优雅而轻便
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
[CVPR2026] Detect Anything via Next Point Prediction
# 🎯 YOLOv智能标注工具 一个功能强大的网页端YOLOv自动标注工具，支持目标检测和实例分割，可加载自定义训练模型，自动标注图片和视频，并导出为多种训练格式，可调整数据集导出比例，自定义类型ID。
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Master programming by recreating your favorite technologies from scratch.
Open-Source AI Presentation Generator and API (Gamma, Beautiful AI, Decktopus Alternative)
[CVPR 2025 Highlight] PyTorch implementation of "Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition"
YOLO+DeepSort+DepthAnything 单目摄像头测距测速
一些关于目标检测的脚本和改进思路代码，详细请看readme.md
An open-source cross-platform alternative to AirDrop
New generated dataset for fight detection in surveillance cameras.
a GUI application, which uses YOLOs (YOLOv8, YOLO11, YOLOv13) for Object Detection/Tracking, Human Pose Estimation/Tracking from images, videos or camera
We write your reusable computer vision tools. 💜
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
3FUI 是 ffmpeg 在 Windows 上的轻度专业交互外壳，收录大量参数，界面美观，交互友好。此项目面向国内使用环境，让普通人也能够轻松压制视频和转换格式。
PI-MAPP: Practices & Insights on Mapping the AI Path & Parsing Classic Models
CesiumJS2026年最新Examples，200多个原生示例：自定义纹理、地形开挖、可视域分析、洪水淹没、缓冲分析、日照分析、方量分析、通透分析、剖面、单体化、视频融合、视频投射、雨雪雾、天空盒、场景出图、体积云、闪电、视锥体、雷达扫描、水波纹、动态扩散点、电子围栏、粒子效果、物理引擎、克里金、海流、大数据可视化、坐标转换、相机、飞行漫游、瓦片加载、xyz、tms、wms、wmts、天…
学校图书借阅管理系统——大学生MySQL数据库、python课程高分项目，完成度高、含详细报告。python MySQL结课大作业、课设
✔（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
deeplearning.ai , By Andrew Ng, All slide and notebook + data + solutions and video link
标注自己的数据集，训练、评估、测试、部署自己的人工智能算法
《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持简中、繁中、English、日本語，提供 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 等代码实现