Download Latest Version v8.4.201 - _ultralytics 8.4.201_ Up to 15x faster PIL plotting across all tasks (#27014) source code.zip (3.7 MB)
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🌟 Summary

Ultralytics 8.4.200 displays Arabic class names correctly in plots and makes training, export, and dataset workflows more reliable. No model architecture changes are included.

πŸ“Š Key Changes

  • πŸ“ Arabic class names display correctly in plots β€” Letters now join and read right-to-left in prediction, training and validation images on every install, with numbers and Latin text kept readable. No new dependency or argument is needed. This is the release’s main change.
  • 🦺 Construction-PPE dataset updated β€” The new version has 1,000 images, 12 classes, and 14,863 reviewed annotations, with an 800/200 training-validation split. It adds forklift and missing-vest classes and changes class IDs. The new archive is separate from legacy downloads. Browse the dataset on Ultralytics Platform.
  • πŸ–₯️ Invalid multi-GPU batch sizes fail earlier β€” Training now reports an error before distributed training starts if the batch is smaller than the number of GPUs. Batches that are not evenly divisible by the GPU count still work, with the remainder dropped.
  • πŸ“¦ Small INT8 calibration datasets are handled more reliably β€” When there are fewer calibration images than the requested batch size, images are repeated to fill the batch, helping avoid export failures with some runtimes.
  • πŸ“„ YAML directive headers are accepted β€” YAML files with standard %YAML or %TAG headers can now be parsed instead of being rejected.

🎯 Purpose & Impact

  • Arabic class names in annotated images are now legible on Windows, Linux, macOS and Docker installs where they previously showed as separate, reversed letters.
  • The updated Construction-PPE dataset adds coverage for more workplace-safety scenarios, but its changed class ordering may require updates to projects that rely on the old class IDs. The legacy dataset remains available separately.
  • Earlier batch-size checks and fuller INT8 calibration batches help users catch training configuration errors sooner and avoid certain export failures.
  • YAML files produced by other tools are more likely to work without manual edits.

What's Changed

New Contributors

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.199...v8.4.200

Source: README.md, updated 2026-11-03