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README_rkopt.md

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YOLOX - RKNN optimize

Source

Base on https://github.com/Megvii-BaseDetection/YOLOX (v0.3.0) with commit id as 419778480ab6ec0590e5d3831b3afb3b46ab2aa3

What different

With inference result values unchanged, the following optimizations were applied:

  • Optimize focus/SPPF block, getting better performance with same result
  • Change output node, remove post_process from the model. (post process block in model is unfriendly for quantization)

How to use

python3 tools/export_onnx.py --output-name yolox_s.onnx -n yolox-s -c yolox_s.pth --rknpu
  • Replace 'yolox_s.pth' with your model path
  • NOTICE: Please call with --rknpu param, do not changing the default rknpu value in export.py.

Deploy demo

Please refer https://github.com/airockchip/rknn_model_zoo