Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Detect objects, track movements, and classify images using advanced AI models.
pip install ultralytics
Documentation ↗Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeUltralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
ultralytics has 59.6k stars on GitHub. It has been forked 11.4k times. ultralytics is written mainly in Python. It has been in active development since 2022. ultralytics is available under the AGPL-3.0 license. Its main topics are computer-vision, deep-learning, image-classification, instance-segmentation.
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
ultralytics is an open-source project. It is released under the AGPL-3.0 license.
Yes. ultralytics is free and open source — you can use, modify and self-host it. Its AGPL-3.0 license is a strong copyleft: if you distribute a modified version — including offering it as a network service — your changes must be released under the same license.
ultralytics is available under the AGPL-3.0 license.
ultralytics is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/ultralytics-ultralytics.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.