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LPCV 2023 solution

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LPCV 2023 introduction

https://lpcv.ai/2023LPCVC/introduction

LPCV 2023 Leaderboard

https://lpcv.ai/scoreboard/Segmentation23

News

  • 10/31/2023 IEEE Computer Society published a blog about the LPCV 2023. Our team ModelTC was announced as the winner of this year’s competition.

Inference Environment

Hardware

NVIDIA Jetson Nano 2GB

Software

refer to official sample: 23LPCVC_Segmentation_Track-Sample_Solution

Our submission

  • file submit_pyz/submit_0803.pyz
  • SHA256 = f1db90947eebedc3229bd5dd70ce5af586893ed8e370acce4f1b9ce33c62c315
  • Submitted at 2023-08-03 09:16:28 EST
  • Perfomance Score 75.608

Usage of our inference code

  • train a segmentation model on your server
  • export a '.onnx' file from your framework on your server
  • Use trtexec on Jetson Nano, convert onnx model to tensorrt model:
trtexec --workspace=4096 --onnx=xxx.onnx --saveEngine=xxx.trt --best --useSpinWait --outputIOFormats=fp16:chw --inputIOFormats=fp16:chw --verbose
  • put the tensorrt model file into inference_code folder
  • pack inference_code folder into pyz and submit(this step is same as the sample solution)

Training

Goto Train readme for training details, log, codebase, trained weights and reproduction