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yolov8-quant's Introduction

YOLOv8 Quantization Demo

yolov8's official repository

my demo is based on v8.1.0.

  • finish ptq and debug
  • finish qat
  • add q/dq manually
  • sensitivity analysis
  • skip some sensitive layers
  • quant details... (fuse? amax?)
  • some warnings/errors(may not affect the results) wait to fix (tracer, onnx export...)
  • export format onnx to engine for tensorrt to inference

Quick Start

python yolov8_flow.py --qat

yolov8 quant flow

load model -> prepare calibration dataset -> (ptq) -> (sensitivity analysis) -> (qat) -> export model.onnx

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