LPCV 2023 solution

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