A Pytorch implement of NTIRE2018 No.1 network WDSR https://arxiv.org/abs/1808.08718v1
Dataset: DIV2K 2017 https://data.vision.ee.ethz.ch/cvl/DIV2K/
DATA
├── HR
└── LR
Training data is augmented with random horizontal filp and rotations, check utility.py and rewrite class SRdataset!
Delete & make new
vim ./loss.log
mkdir ./samples
mkdir ./checkpoint
GPUs are needed for training
python main.py --cuda
Test method
700x700 HR image and its LR counterpart are randomly cropped from every image in DIV2K Validset
Calculate the mean PSNR of HR image and Image Restored by network
make correspond empty folder to store samples before test
mkdir ./foldername/
change samples save_path and model to restore in psnr.py
python psnr.py
Specific description of given samples, checkpoint as well as test results can be found in .numbers file ^_^
