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sharpformer's Introduction

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

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