Ultralytics YOLO

🌟 Summary

🛠️ v8.4.108 improves MuSGD stability, inference and tracking efficiency, analytics quality, ONNX compatibility, and documentation usability—without changing model accuracy or architecture.

📊 Key Changes

• Fixed a MuSGD training crash by @Y-T-G:

  • MuSGD now applies its Muon-style update only to supported 2D linear weights and 4D convolution filters.
  • LayerScale gains, normalization weights, biases, and other parameters use the existing SGD update path.
  • Prevents AssertionError failures when training models containing parameters such as (C, 1, 1) LayerScale tensors.

• Improved prediction performance reporting:

  • Predictors now retain per-image preprocessing, inference, and postprocessing times through predictor.speed.
  • Added average processed image area through predictor.pixels.
  • Timing information is reset correctly for each run and supports mixed image sizes.

• Reduced tracking overhead and preserved device placement:

  • TrackTrack computes motion cues only for detection pairs supported by IoU, reducing unnecessary CPU work, especially in crowded scenes.
  • Removed redundant NumPy array copies in ByteTrack and TrackTrack.
  • Tracked boxes now remain on the same device as the original detections, avoiding unexpected CPU/GPU data splits.

• Improved ONNX Runtime example compatibility:

  • Corrected image height/width handling during letterbox preprocessing.
  • Added fallback support for models with dynamic input dimensions.

• Strengthened training and inference analytics:

  • Training events now report final outcomes such as fitness, duration, completed epochs, optimizer, architecture, and dataset information.
  • Multi-GPU runs now record the GPU count instead of a simple distributed-training flag.
  • Invalid modes and tasks are excluded from analytics events.

• Expanded Ultralytics Platform integration:

  • Model weights for YOLO26, YOLO11, YOLOv8, and supported YOLOv5 variants now link to their corresponding Ultralytics Platform model pages.
  • Huawei Ascend 310B1 and 310B4 targets are now documented as supported on Platform.

• Improved generated reference documentation:

  • Fixed broken tables for union types such as str | Path.
  • Preserved multi-line return descriptions.
  • Documented inherited constructors correctly.
  • Improved source panels, examples formatting, frontmatter handling, and empty argument tables.

• Updated documentation links and CI reliability:

  • Replaced unstable ADE20K and Flickr30K links with maintained GitHub sources.
  • Excluded Gitee links from automated checks to avoid false failures caused by bot protection.

🎯 Purpose & Impact

• ✅ MuSGD users can train a wider range of models reliably, including architectures with LayerScale or other non-matrix parameters.
• 🚀 Inference and tracking are more efficient, with lower avoidable CPU work and better GPU/CPU device consistency.
• 📈 Performance measurements and analytics are more useful, making it easier to compare real-world runs across hardware and distributed setups.
• 🔄 ONNX Runtime examples work with more exported models, including dynamic-shape models.
• 📚 Documentation is easier to navigate and more accurate, with working model links, corrected API references, and clearer examples.
• 🌐 Users can more easily explore, train, and deploy supported models through the Ultralytics Platform, the recommended workflow for managing YOLO projects.

What's Changed

• Fix unstable dataset links in docs by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25445
• Link model weights to Platform pages by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25446
• Exclude gitee.com from broken link checks by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25449
• fix input size handling in YOLOv8/YOLO11 ONNXRuntime example by @onuralpszr in https://github.com/ultralytics/ultralytics/pull/25451
• Add predictor speed attribute and predict event fields by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25440
• Escape pipes in reference tables so union types stay in one column by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25455
• Fix reference truncation, constructor signatures, and empty argument tables by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25457
• Record training outcomes in the train event by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25456
• Fix Examples captions and hard-wrapped table descriptions by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25458
• Update OrangePi Huawei Ascend 310B Platform support by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25459
• Document inherited constructors and anchor frontmatter parsing by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25460
• Only send events for a valid mode and task by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25461
• Reduce TrackTrack CPU and keep tracked boxes on the source device by @onuralpszr in https://github.com/ultralytics/ultralytics/pull/25448
• Record the GPU count instead of a ddp flag by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25463
• Skip the redundant contiguous copy in RandomFlip by @JESUSROYETH in https://github.com/ultralytics/ultralytics/pull/25462
• Fix MuSGD crash on non-matrix params like LayerScale by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/25447

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.107...v8.4.108