🌟 Summary (single-line synopsis)

Ultralytics v8.4.4 refines MuSGD training behavior (better scaling for short vs. long runs) and includes several quality-of-life fixes for exports, segmentation outputs, logging, and filesystem side effects 🚀🧠

📊 Key Changes

• 🧠 MuSGD optimizer scaling update (PR #23279 by @Laughing-q)
  MuSGD scale factors are now chosen more appropriately based on total training iterations:

  • > 10,000 iterations: (muon=0.1, sgd=1.0)
  • ≤ 10,000 iterations: (muon=0.5, sgd=0.5)
    This is a behavior change in ultralytics/engine/trainer.py.

• 📷 Sony IMX500 export compatibility improved (PR #23266 by @Laughing-q)

  • IMX exporter now accepts multiple valid layer counts (a set of allowed values) instead of requiring exactly one, reducing false “unsupported model” failures ✅
  • IMX500 docs/examples are refreshed to focus on YOLO11 (model names and paths updated).

• 🧩 Segmentation proto/output handling fixed across backends (PR #23241 by @Laughing-q)

  • Segmentation post-processing now pulls the proto masks from the correct output index for both PyTorch and exported models.
  • TensorFlow segmentation handling in AutoBackend now triggers based on task == "segment" (more reliable than guessing from output shape/length).

• 📁 No more empty run folders when save=False (PR #23268 by @Y-T-G)
  get_save_dir() no longer auto-creates directories while computing a unique run path—reduces unwanted “predict” folders appearing on disk 🧹

• 📈 TensorBoard OBB graph logging made safer (PR #23276 by @Y-T-G)
  TensorBoard graph logging now uses smart_inference_mode() to avoid gradient tracking—often less memory/overhead and fewer callback edge cases ⚙️

• 🔗 Docs branding/link refresh (PR #23283 by @glenn-jocher)
  Multiple repo/docs links now point to the Ultralytics Platform entry point (and wording updated accordingly) 🧭

🎯 Purpose & Impact

• 🚀 More consistent training dynamics with MuSGD
  If you use MuSGD (muon/sgd), you may see improved stability and convergence depending on whether your run is short or long—especially around the 10k-iteration threshold 🧠📉

• ✅ Fewer export surprises (IMX500 + segmentation exports)
  IMX500 exports should fail less often due to minor layer-count differences, and segmentation outputs should be more consistent across PyTorch/exported/TF backends 📦🧩

• 🧹 Cleaner local runs and tooling behavior
  Computing a save directory no longer creates folders prematurely, which is especially helpful for dry runs, scripts, and save=False predictions 📁✨

• ⚡ More robust logging during training
  TensorBoard graph logging becomes less intrusive and more reliable (particularly for OBB setups) 📊🛡️

What's Changed

• Fix YOLOv8/YOLO11 IMX export by @Laughing-q in https://github.com/ultralytics/ultralytics/pull/23266
• Disable automatic directory creation with mkdir by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/23268
• Use YOLO26n for benchmark tests by @Laughing-q in https://github.com/ultralytics/ultralytics/pull/23241
• Fix TensorBoard error with OBB by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/23276
• Replace HUB -> Platform links by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/23283
• ultralytics 8.4.4 MuSGD optimizer scale factor update by @Laughing-q in https://github.com/ultralytics/ultralytics/pull/23279

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.3...v8.4.4