Open Source Computer Vision Library
Best Computer Vision GitHub Repositories
Top 90 open source projects in Computer Vision. Ranked by stars, activity, and recorded community growth.
Learn AI Engineering! Learn it. Build it. Ship it for others.
12 Weeks, 24 Lessons, AI for All!
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
We write your reusable computer vision tools. 💜
Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active
Xray, Penetrates Everything. Also the best v2ray-core. Where the magic happens. An open platform for various uses.
Cross-platform, customizable ML solutions for live and streaming media.
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Automate browser based workflows with AI
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
Open-source simulator for autonomous driving research.
A toolkit for making real world machine learning and data analysis applications in C++
Visualize, query, and stream to train on multimodal robotics data.
🐍 Geometric Computer Vision Library for Spatial AI
Refine high-quality datasets and visual AI models
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Fast and Accurate ML in 3 Lines of Code