ultralytics
Object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
GraphCanon updated 2w · GitHub synced 2w
Decision brief
Ultralytics is renowned for advanced computer vision tasks including object detection, instance segmentation, and tracking through its YOLO series.
Good fit when
- When precision in real-time object detection and segmentation across multiple domains (e.g., robotics, surveillance) is needed.
- For projects that benefit from an active community and collaboration on open-source improvements with AGPL-3.0 licensing.
Avoid when
- If a project requires proprietary modifications or integrations where source code contributions must be tightly controlled, as the AGPL-3.0 would require sharing modified versions of Ultralytics.
- When deployment scenarios strictly limit the use of open-source software due to compliance or security policies that might conflict with AGPL licensing.
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install ultralyticsHow it fits your stack(9)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Ultralytics YOLO series for advanced computer vision tasks including detection, segmentation, and tracking.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 6, 2026
- Languages
- python
Source: github.language+pyproject.toml · Aug 6, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 6, 2026)
Discover more examples in the YOLO [Python Docs](https://docs.ultralytics.com/usage/python).Source link
Tags
README
Export the model to ONNX format for deployment
path = model.export(format="onnx") # Returns the path to the exported model
Discover more examples in the YOLO [Python Docs](https://docs.ultralytics.com/usage/python).
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## 📜 License
Ultralytics offers two licensing options to suit different needs:
- **AGPL-3.0 License**: This [OSI-approved](https://opensource.org/license/agpl-3.0) open-source license is perfect for students, researchers, and enthusiasts. It encourages open collaboration and knowledge sharing. See the [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for full details.
- **Ultralytics Enterprise License**: For development and production use, this license enables seamless integration of Ultralytics software and AI models into business products and services, including internal tools, automated workflows, and production deployments, bypassing the open-source requirements of AGPL-3.0. To get started, please contact us via [Ultralytics Licensing](https://www.ultralytics.com/license).
For agents
This page has a .md twin and JSON over the API.