pypi ultralytics 8.4.26
v8.4.26 - Platform NDJSON autosplit (#23990)

5 hours ago

🌟 Summary

v8.4.26 focuses on reliability and usability improvements: smarter Platform dataset handling (auto-validation split for NDJSON), more robust Platform URL resolution, and an important FP16 SAM inference crash fix—plus CI and docs polish. 🚀

📊 Key Changes

  • ✅ Platform NDJSON auto-split (PR #23990, @glenn-jocher)
    If a dataset has a train split but no val/test, Ultralytics now automatically creates a small validation split from training data instead of failing immediately.

    • Uses a deterministic split approach for consistency.
    • Warns users to still create a manual validation split for best quality.
  • 🌐 More reliable Ultralytics Platform URI resolution (PR #23990, @glenn-jocher)
    Improved ul://... resolution with:

    • Retry logic for transient connection issues
    • Better timeout strategy (fast connect timeout + longer read timeout for large dataset processing)
    • Clearer handling for auth, permission, not-found, and processing states
  • 🧠 FP16 SAM TinyViT inference crash fix (PR #23780, @Edwin-Kevin)
    Fixed a half-precision inference error in SAM TinyViT models (like mobile_sam.pt) caused by dtype mismatch in cached tensors.

    • Model setup order was adjusted so cached eval-time tensors match FP16 expectations.
    • Added/updated CUDA test coverage with half=True.
  • ⚙️ CI simplification and stability updates (mainly PR #23990)

    • Removed dedicated HUB CI job and related manual trigger
    • Standardized many CI runners from cpu-latest to ubuntu-latest
    • Temporarily pinned GPU CI to torch<2.11 until CUDA 13 driver support is ready
  • 📚 Platform docs improvements

    • Added embedded onboarding videos to key Platform docs pages (Quickstart, Account, Data, Train, Deploy) via PR #23986 by @RizwanMunawar
    • Updated docs chat script to v0.2.7 via PR #23989 by @glenn-jocher

🎯 Purpose & Impact

  • Less friction for dataset conversion 📦
    Users importing NDJSON datasets into YOLO workflows are less likely to hit hard failures when a validation split is missing.

  • Better reliability in cloud/remote workflows ☁️
    Platform URI retries and timeout tuning reduce flaky failures, especially with large datasets or temporary network instability.

  • More stable FP16 segmentation inference 🎯
    Users running SAM TinyViT in half precision on GPU should see fewer runtime dtype crashes and smoother deployment behavior.

  • Cleaner maintenance pipeline for Ultralytics 🛠️
    CI changes reduce complexity and improve consistency, helping keep releases stable.

  • Faster onboarding for new users 🎥
    The new Platform tutorial videos make it easier for broad audiences to get started quickly with data, training, and deployment.

What's Changed

New Contributors

Full Changelog: v8.4.25...v8.4.26

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