fix(deps): update dependency ultralytics ( 8.4.18 → 8.4.19 )#303
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jazzlyn-bot[bot] merged 1 commit intomainfrom Mar 1, 2026
Merged
fix(deps): update dependency ultralytics ( 8.4.18 → 8.4.19 )#303jazzlyn-bot[bot] merged 1 commit intomainfrom
jazzlyn-bot[bot] merged 1 commit intomainfrom
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| datasource | package | from | to | | ---------- | ----------- | ------ | ------ | | pypi | ultralytics | 8.4.18 | 8.4.19 |
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This PR contains the following updates:
==8.4.18→==8.4.19Release Notes
ultralytics/ultralytics (ultralytics)
v8.4.19: -ultralytics 8.4.19Platform training pass model ID fix (#23761)Compare Source
🌟 Summary (single-line synopsis)
Ultralytics
v8.4.19focuses on much more reliable Ultralytics Platform training sync (especially model tracking viamodel_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_idfixmodel_idduring model uploads and training events.trainer.platformcontext (instead of scattered trainer fields), including:model_id🧠 SAM prediction cleanup (#23751 by @Laughing-q)
SAM3SemanticPredictorpostprocessing and feature-inference paths.🛡️ PSA attention edge-case fix (#23758 by @Y-T-G)
PSABlockfor very small channel configs.📘 Docs clarification for end-to-end models (#23720 by @raimbekovm)
max_detandagnostic_nmsare supported directly.end2end=Falseis mainly for enabling traditionaliou-based NMS behavior.⚙️ CI maintenance
🎯 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
max_detandagnostic_nmssupport in end2end mode by @raimbekovm in #23720SAM3SemanticPredictorto eliminate overlapping boxes by @Laughing-q in #23751num_headsby @Y-T-G in #23758ultralytics 8.4.19Platform training pass model ID fix by @glenn-jocher in #23761Full Changelog: ultralytics/ultralytics@v8.4.18...v8.4.19
Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Enabled.
♻ Rebasing: Whenever PR is behind base branch, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.
This PR has been generated by Renovate Bot.