conda create -n m2mrf python=3.7 -y
conda activate m2mrf

conda install pytorch=1.6.0 torchvision cudatoolkit=10.2 -c pytorch -y
pip install mmcv-full==1.2.0 -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html -i https://pypi.douban.com/simple/
pip install opencv-python
pip install scipy
pip install tensorboard tensorboardX
pip install sklearn
pip install terminaltables
pip install matplotlib

cd M2MRF-Lesion-Segmentation
chmod u+x tools/*
pip install -e .

# prepare dataset
python tools/prepare_labels.py
python tools/augment.py

# train
CUDA_VISIBLE_DEVICES=0,1,2,3 PORT=12345 tools/dist_train.sh configs/_m2mrf_idrid/fcn_hr48-M2MRF-C_40k_idrid_bdice.py 4

# test
CUDA_VISIBLE_DEVICES=0,1,2,3 PORT=12345 tools/dist_test.sh configs/_m2mrf_idrid/fcn_hr48-M2MRF-C_40k_idrid_bdice.py /path/to/fcn_hr48-M2MRF-C_40k_idrid_bdice_iter_40000.pth 4 --eval mIoU

@misc{liu2021m2mrf,
      title={M2MRF: Many-to-Many Reassembly of Features for Tiny Lesion Segmentation in Fundus Images},
      author={Qing Liu and Haotian Liu and Wei Ke and Yixiong Liang},
      year={2021},
      eprint={2111.00193},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}