ultralytics 8.4.56

v8.4.56 - Fix QNN export with built-in provider wheels (#24618)

on Python PyPI

🌟 Summary

Ultralytics v8.4.56 improves QNN export reliability by fixing compatibility with newer onnxruntime-qnn packages, especially on Linux x86-64. 🚀

📊 Key Changes

• Fixed QNN export for built-in provider wheels 🔧
  Ultralytics now detects whether onnxruntime-qnn already includes QNNExecutionProvider internally, instead of always trying to register it as a separate plugin.

• Avoids export failures on some Linux setups 🐧
  This prevents a known failure on Linux x86-64 wheels where plugin registration could crash with an undefined symbol error.

• Supports both QNN packaging styles 📦
  The export flow now works with:

  • plugin-based QNN wheels, where the provider must be registered manually
  • built-in QNN wheels, where registration is not needed

• Smarter QNN session creation 🧠
  If the provider is built in, Ultralytics now launches the ONNX Runtime session directly with the QNN provider. If it is plugin-based, it keeps the previous registration path.

• Documentation/comments updated for clarity 📝
  Internal descriptions were updated to reflect that QNN may be exposed either as a plugin or as a built-in ONNX Runtime provider.

🎯 Purpose & Impact

• Makes QNN export more robust ✅
  Users exporting models to Qualcomm QNN should see fewer environment-specific errors and smoother exports.

• Improves compatibility with newer runtime wheels 🔄
  This is especially helpful as onnxruntime-qnn packaging evolves across platforms and releases.

• Reduces setup friction for deployment 📱
  If you are exporting YOLO models like YOLO26 for Qualcomm and edge hardware workflows, this change lowers the chance of export-time breakage.

• No major model architecture changes in this release 🤖
  v8.4.56 is mainly a stability and export compatibility update, not a new model or training feature release.

• Most relevant for advanced deployment users ⚡
  If you use standard training and inference, this release may not change much day to day. But for users targeting QNN / Qualcomm deployment pipelines, it should have a meaningful positive impact.

🙌 Bottom line

This release is a small but important deployment fix: it makes QNN export smarter and more portable by handling both old and new onnxruntime-qnn layouts correctly, with the biggest benefit for Linux-based export environments.

What's Changed

• Fix QNN export with built-in provider wheels by @glenn-jocher in #24618

Full Changelog: v8.4.55...v8.4.56