Ultralytics YOLO

🌟 Summary

Release 8.4.188 improves QNN exports for Android, removes an unnecessary operation from non-LiteRT depth exports, and updates the LiteRT export toolchain.

📊 Key Changes

• Fixes Android QNN model loading: QNN exports now keep input and output quantization inside the QNN context. This avoids an io_name_overrides attribute that newer QNN export tools can add but Android's built-in QNN Execution Provider cannot read.
• Speeds up depth exports outside LiteRT: The export-only ReLU is now applied only for LiteRT. It remains there as a workaround for an Intel NPU compiler issue, but is avoided in QNN and other formats.
• Updates LiteRT export requirements: Minimum versions are raised to litert-torch 0.10.0, ai-edge-litert 2.3.0, and ai-edge-quantizer 0.10.0.
• Refreshes the export Docker image: It now installs the full export dependency set, including LiteRT support.

🎯 Purpose & Impact

• 📱 Android users should be able to load affected QNN exports with ONNX Runtime's built-in QNN provider, including in apps using the Ultralytics Flutter plugin.
• ⚡ Depth-model exports may run more efficiently where the ReLU workaround is not needed.
• 📦 LiteRT exporters use a newer toolchain aligned with current mobile NPU runtimes, which can improve compatibility when exporting for supported devices.
• 🧩 These are export and deployment improvements; the release does not change model architecture or weights.

What's Changed

• Raise LiteRT export toolchain floors to LiteRT 2.3 by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/26869
• ultralytics 8.4.188 Fix Android loading and depth speed of QNN exports by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/26872

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.187...v8.4.188