ultralytics 8.4.19

v8.4.19 - `ultralytics 8.4.19` Platform training pass model ID fix (#23761)

on Python PyPI

🌟 Summary (single-line synopsis)

Ultralytics v8.4.19 focuses on much more reliable Ultralytics Platform training sync (especially model tracking via model_id), plus a few quality improvements for SAM outputs, lightweight model stability, and clearer YOLO26 end-to-end docs 🚀

📊 Key Changes

• 🔴 Most important (current PR #23761 by @glenn-jocher): Platform training model_id fix

  • Training callbacks now consistently pass model_id during model uploads and training events.
  • Platform callback state was refactored into a single trainer.platform context (instead of scattered trainer fields), including:
    • model_id
    • last upload time
    • cancellation status
    • console/system loggers
  • Upload and event flow was tightened for better session continuity, cancellation handling, and final result linking.
  • Platform URL handling now better supports server-adjusted model slugs (for example when names auto-increment).

• 🧠 SAM prediction cleanup (#23751 by @Laughing-q)

  • Added NMS in SAM3SemanticPredictor postprocessing and feature-inference paths.
  • Reduces duplicate overlapping detections and keeps boxes/masks aligned.

• 🛡️ PSA attention edge-case fix (#23758 by @Y-T-G)

  • Prevents zero attention heads in PSABlock for very small channel configs.
  • Improves robustness for lightweight/custom model scales.

• 📘 Docs clarification for end-to-end models (#23720 by @raimbekovm)

  • Clarifies that in end-to-end mode (YOLO26, YOLOv10), max_det and agnostic_nms are supported directly.
  • Notes that setting end2end=False is mainly for enabling traditional iou-based NMS behavior.

• ⚙️ CI maintenance

  • GitHub Actions artifact upload/download actions were bumped to newer major versions (#23748, #23749).
  • African Wildlife dataset tutorial video embed updated in docs (#23757). 🎥

🎯 Purpose & Impact

• For Ultralytics Platform users: ✅
  Training runs should now be more reliable to track end-to-end, with fewer mismatches between uploaded checkpoints and the correct model session. This is the biggest practical improvement in this release.

• For production and team workflows: 📡
  Better callback state management means cleaner event handling, better cancellation behavior, and improved confidence that results and artifacts land in the right place.

• For segmentation users (SAM): 🎯
  Cleaner predictions with fewer duplicate overlaps can improve downstream usability and visual quality.

• For custom/small models: 🧱
  Fewer architecture edge-case failures when using very small widths or low channel counts.

• For all users reading docs: 📚
  Clearer expectations around end-to-end inference/validation args in YOLO26 and YOLOv10 reduce confusion and setup mistakes.

What's Changed

• Document max_det and agnostic_nms support in end2end mode by @raimbekovm in #23720
• Bump actions/download-artifact from 7 to 8 in /.github/workflows by @dependabot[bot] in #23749
• Bump actions/upload-artifact from 6 to 7 in /.github/workflows by @dependabot[bot] in #23748
• Add NMS to SAM3SemanticPredictor to eliminate overlapping boxes by @Laughing-q in #23751
• Add https://youtu.be/EXYB-dbgJjY to docs by @RizwanMunawar in #23757
• Fix division by zero in PSABlock num_heads by @Y-T-G in #23758
• ultralytics 8.4.19 Platform training pass model ID fix by @glenn-jocher in #23761

Full Changelog: v8.4.18...v8.4.19