Announcing Ultralytics YOLO11 v8.3.0!
Summary
We’re thrilled to announce the release of Ultralytics YOLO11, the latest advancement in real-time object detection and computer vision. Developed with contributions from @Laughing-q and @glenn-jocher, YOLO11 redefines performance and efficiency. Dive into the details in PR #16539.
Key Highlights
YOLO11 Model Unveiled: A major upgrade over YOLOv8, featuring enhanced architecture and optimized pipelines.
Revamped Documentation: Improved guides and resources for a seamless transition to YOLO11.
Streamlined CI & Dockerfiles: Optimized for YOLO11 to ensure smooth workflows.
Augmentation & Blocks Upgraded: New modules boost performance across tasks.
YOLO11-Specific Configurations: Tailored configurations to leverage advanced features.
Purpose & Impact
- Top-Tier Performance: Achieve better accuracy with fewer parameters, enhancing real-time detection.
- Versatility: Supports a wide range of tasks, from object detection to pose estimation, adaptable across environments.
- Easy Adoption: Updated resources and tutorials make it easy to maximize YOLO11’s capabilities.
What’s Changed
- Update
test_exports.pyby @glenn-jocher in PR #16527 - Fix
hand-keypoints.yamlimage counts by @jk4e in PR #16528 - Update
Dockerfile-pythonby @glenn-jocher in PR #16529 - Use
apt-getin Dockerfiles by @glenn-jocher in PR #16535 ultralytics 8.3.0YOLO11 Models Release by @glenn-jocher in PR #16539
Full Changelog: View here
Try It Now!
We invite you to explore YOLO11 v8.3.0 and share your feedback. Your insights are invaluable to us as we continue to enhance our models. Check out the release page for more details.
Thank you for being part of the Ultralytics community!