New Release: Ultralytics v8.4.188

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:rocket: Ultralytics v8.4.188: Smoother Android Deployment and Leaner Depth Exports

Ultralytics YOLO v8.4.188 is here! This release improves Android QNN model loading, removes an unnecessary operation from non-LiteRT depth exports, and refreshes the LiteRT export toolchain. These are export and deployment improvements—model architectures and weights are unchanged.

:mobile_phone: Android QNN Fixes and Depth Export Improvements

The changes in PR #26872 by @glenn-jocher address two deployment pain points:

  • More compatible Android QNN exports: Input and output quantization now stay inside the QNN context, avoiding an io_name_overrides attribute that newer export tools can add but Android’s built-in QNN Execution Provider cannot read. This should resolve loading issues for affected models, including in apps using the Ultralytics Flutter plugin.
  • Leaner depth exports outside LiteRT: The export-only ReLU is now limited to LiteRT, where it remains a workaround for an Intel NPU compiler issue. QNN and other export formats avoid that extra operation, potentially improving runtime efficiency.

:package: Updated LiteRT Toolchain and Export Docker Image

The updates in PR #26869 by @glenn-jocher bring the LiteRT export dependencies in line with current mobile NPU runtimes:

  • litert-torch >= 0.10.0
  • ai-edge-litert >= 2.3.0
  • ai-edge-quantizer >= 0.10.0

The export Docker image now installs the full export dependency set, including LiteRT support. These updates can improve export compatibility for supported devices.

:hammer_and_wrench: Try It and Share Your Feedback

Upgrade to the release with:

pip install --upgrade ultralytics==8.4.188

Check the v8.4.188 release notes for the release details, or browse the full changelog to review the changes.

Working with Android QNN, LiteRT, or depth models? Give this release a try and let us know how it performs. Share your device, export format, and results below—your feedback helps improve deployment for everyone! :raising_hands: