Ultralytics v8.4.161 is here
Ultralytics YOLO v8.4.161 focuses on reliability: smoother training resumes, more resilient prediction and plotting, better dataset handling, and clearer export and Ultralytics Platform guidance. See the v8.4.161 release for the release details.
Bug fixes
- Six fixes in one update: RT-DETR tensors move correctly between devices; older Adam/AdamW checkpoints retain their runtime fused setting on resume; empty image files no longer crash prediction; results load from paths containing brackets; plots handle odd numbers of panels; and Platform uploads can use
last.ptwhensave=Falseleaves nobest.pt. See PR #26301 by @glenn-jocher. - CoreML export errors are easier to diagnose: removing an invalid
.mlmodelfallback prevents it from obscuring the original save error. See PR #26298 by @amanharshx.
Dataset and training improvements
.tgzdataset archives now extract correctly in PR #26294 by @aswanth-07.- Semantic datasets skip polygon resampling when no augmentation needs the polygons, reducing unnecessary processing. See PR #26295 by @raimbekovm.
- CLI fuzz testing now recognizes wrapped missing-dataset-split errors as expected. See PR #26299 by @aswanth-07.
Clearer export and Platform guidance
- Export documentation now covers the
deviceargument for OpenVINO, Hailo, and Ascend in PR #26286 by @raimbekovm, and explains why static exports can produce different predictions on non-square images in PR #26285 by @Vaishnavi220506. - Platform documentation has been refreshed across image copying, face blurring, annotation providers, deployment, monitoring, and related API and billing details. See PR #26297 by @raimbekovm.
Welcome to first-time contributor @Vaishnavi220506! Thanks to every contributor and the YOLO community for helping make this release possible.
Give v8.4.161 a try and let us know how it works for your training, inference, and export workflows. For every change, browse the full changelog.