ultralytics 8.3.111

v8.3.111 - `ultralytics 8.3.111` YOLOv10 skip `one2many` head when fused (#20193)

on Python PyPI

🌟 Summary

This release brings significant efficiency improvements to YOLOv10 models, enhances logging and integration options, and streamlines user experience in Ultralytics tutorials and workflows. 🚀✨

📊 Key Changes

• YOLOv10 Model Optimization: The fuse() method now removes the "one2many" detection head when not needed, reducing model size and computation for inference.
• Faster, Lighter YOLOv10: After fusion, YOLOv10n drops from 125 to 102 layers and from 2.76M to 2.30M parameters, making it faster and more efficient for deployment.
• TensorBoard Logging Default Changed: TensorBoard is now disabled by default for faster training startup; users can re-enable it as needed.
• Tutorial Notebook Improvements: The YOLO11 Colab notebook has clearer instructions, updated visuals, and improved links to documentation and community resources.
• Better Integration Options: Users can now easily select between TensorBoard and Weights & Biases for experiment tracking.
• Cleaner Output: Suppressed unnecessary warnings from the Albumentations library for a smoother notebook experience.
• TensorRT Export Fix: Improved support for exporting YOLO-World models to TensorRT by handling dynamic shapes more robustly.
• Stronger Link Checking: Documentation workflows now fail if broken links are found, ensuring higher quality docs.

🎯 Purpose & Impact

• Faster Inference & Smaller Models: The YOLOv10 optimization means users get quicker predictions and reduced resource usage, especially important for edge devices and production deployments.
• Streamlined Training: Disabling TensorBoard by default speeds up training for users who don’t need logging, while still allowing easy opt-in for those who do.
• Improved Usability: The revamped tutorial and cleaner output make it easier for both beginners and experienced users to get started and stay productive.
• Robust Integrations: Enhanced support for popular experiment tracking tools and export formats broadens compatibility and flexibility for diverse workflows.
• Higher Documentation Quality: Automated link checking helps ensure users always have access to up-to-date and working resources.

This update is all about making YOLO models faster, easier to use, and more reliable—whether you're deploying to production or just getting started! 🚦📈

What's Changed

• Explicit shape handling for dynamic YOLO-World exports to TensorRT by @laugh12321 in #20205
• Update links.yml to ignore TIMEOUT issues by @glenn-jocher in #20210
• Default tensorboard=False for speed by @glenn-jocher in #20213
• ultralytics 8.3.111 YOLOv10 skip one2many head when fused by @Y-T-G in #20193

New Contributors

• @laugh12321 made their first contribution in #20205

Full Changelog: v8.3.110...v8.3.111