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At Ultralytics, we are dedicated to creating the best artificial intelligence models in the world. Our open source works here on GitHub offer cutting-edge solutions for a wide range of AI tasks, including object detection, tracking, instance segmentation, semantic segmentation, image classification, and pose estimation 🚀.
We welcome contributions from the global community 🌍 and are always eager to hear from users with feature requests and bug reports. If you're looking for state-of-the-art AI models that are fast, accurate, and easy to use, Ultralytics is the place to be. For commercial deployments, explore our enterprise licensing options.
Join us on our mission to push the boundaries of AI and make it accessible to everyone! 💡🌟
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Ultralytics GitHub Actions for formatting, PR reviews, labeling, CI retries, CLA checks, and dependency updates.
A fast, local workspace for Claude Code, Codex, Gemini CLI, Kimi Code, Qwen Code, DeepSeek, OpenRouter, and your shell.
Generate interactive API documentation and typed Python SDKs from any OpenAPI specification
Ultralytics company handbook covering our mission, values, onboarding, people, policies, security, and operations.
Official Ultralytics YOLO Flutter plugin for real-time inference on Android and iOS across major vision tasks.
Ultralytics Rust project template with library and CLI examples, tests, benchmarks, rustfmt, clippy, coverage, dependency checks, and crates.io publishing.
Daily Ultralytics analytics for GitHub, PyPI, Google Analytics, Reddit, and Platform metrics, published as static JSON with historical star tracking.
High-performance Ultralytics YOLO inference in Rust with ONNX Runtime, GPU backends, CLI, and WebGPU/WASM.
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