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Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher

Pytorch implementation of MICCAI'23 paper Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher.

Installation

  • Install python 3.10.5, pytorch 1.12.0, CUDA 11.6 and other essential packages (Note that using other versions of packages may affect performance.)
  • Clone this repo
git clone https://github.com/lloongx/SFDA-CBMT.git
cd SFDA-CBMT

Training

  • Download datasets from here.
  • Download source domain model from here or specify the --data-dir in ./train_source.py and then run it.
  • Save source domain model into folder ./logs_train/.
  • Run ./train_target.py with specified --model-file and --data-dir to start the SFDA training process.

Acknowledgement

This repo benefits from BEAL and SFDA-DPL. Thanks for their wonderful works.

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Pytorch implementation of MICCAI'23 pape: Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher.

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