ultralytics 8.4.59

v8.4.59 - Validate RKNN INT8 calibration dataset path (#24659)

on Python PyPI

🌟 Summary

Ultralytics v8.4.59 improves Rockchip RKNN export with safer and clearer INT8 quantization support, making deployment on Rockchip edge devices more reliable and easier to use 🚀

📊 Key Changes

• ✅ RKNN INT8 calibration file is now validated before export proceeds

  • The release’s main follow-up change from @glenn-jocher checks that the internally generated calibration image list actually exists before loading the RKNN Toolkit.
  • This helps catch setup issues earlier, with clearer error messages instead of failing later in a more confusing way.

• 🧠 Simpler RKNN INT8 workflow for users

  • Users continue to provide a standard YOLO dataset YAML with data=... during export.
  • Ultralytics now handles conversion of that dataset into RKNN’s internal dataset.txt calibration file automatically.
  • dataset.txt stays an internal implementation detail, not something users are expected to manage directly.

• ⚡ New RKNN INT8 export support introduced in this release cycle

  • RKNN export now supports:
    • int8=True
    • data=...
    • fraction=...
  • This enables INT8-quantized RKNN model export, which is especially important for Rockchip devices that require INT8 models.

• 📱 Expanded support for INT8-only Rockchip chips

  • Devices such as RV1103, RV1106, RV1103B, and RV1106B are now supported through INT8 export.
  • The exporter also warns and auto-adjusts when a selected chip requires int8=True.

• 📚 Documentation and export tables updated

  • RKNN docs now clearly explain:
    • floating-point export behavior for FP16-capable targets
    • when int8=True is required
    • use of data and fraction for calibration
  • Export reference tables and tutorial content were updated to reflect the new RKNN options.

• 🛡️ Better RKNN API error handling

  • Internal RKNN API calls now check return values more carefully.
  • Failures in config, ONNX loading, build, or export are surfaced as clearer runtime errors.

🎯 Purpose & Impact

• More reliable RKNN exports 🔒

  • Validating the calibration file up front reduces frustrating export failures and makes debugging easier.

• Easier INT8 quantization for everyone 🙌

  • Users can stick to the familiar Ultralytics pattern of passing data=coco8.yaml or another dataset YAML, without learning RKNN-specific file conventions.

• Better support for edge deployment on Rockchip hardware 📦

  • INT8 export opens the door to more Rockchip NPUs, including chips that cannot use floating-point RKNN models.

• Cleaner user experience 🧹

  • The release hides low-level RKNN details from users and keeps the interface aligned with other Ultralytics export formats.

• Potential performance and compatibility gains 🚀

  • INT8 models are often smaller and better suited for constrained edge devices.
  • For supported Rockchip targets, this can improve deployability and help users target hardware that previously wasn’t practical with RKNN export.

• Lower risk of misconfiguration ⚠️

  • Clearer warnings, updated docs, and improved validation make it less likely that users will choose unsupported settings by accident.

If helpful, I can also provide a 1-paragraph release note version or a developer-focused changelog summary for v8.4.59.

What's Changed

• ultralytics 8.4.59 Rockchip RKNN INT8 export option by @glenn-jocher in #24656
• Validate RKNN INT8 calibration dataset path by @glenn-jocher in #24659

Full Changelog: v8.4.58...v8.4.59