Awesome

Installation

This implementation based on BasicSR which is a open source toolbox for image/video restoration tasks.

python 3.6.9
pytorch 1.5.1
cuda 10.1

cd SharpFormer
pip install -r requirements.txt
python setup.py develop --no_cuda_ext

• prepare data

  • mkdir ./datasets/GoPro

  • download the train set in ./datasets/GoPro/train and test set in ./datasets/GoPro/test (refer to MPRNet)

  • it should be like:

    ./datasets/
    ./datasets/GoPro/
    ./datasets/GoPro/train/
    ./datasets/GoPro/train/input/
    ./datasets/GoPro/train/target/
    ./datasets/GoPro/test/
    ./datasets/GoPro/test/input/
    ./datasets/GoPro/test/target/
    

  • python scripts/data_preparation/gopro.py

    • crop the train image pairs to 512x512 patches.

• eval

  • python basicsr/test.py -opt options/test/GoPro/SharpFormer-GoPro.yml

• train

  • python -m torch.distributed.launch --nproc_per_node=8 --master_port=4321 basicsr/train.py -opt options/train/GoPro/SharpFormer.yml --launcher pytorch