Official PyTorch implementation of “FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow” [paper]
CVPRW 2022, Runner-up at NTIRE 2022 Learning the Super Resolution Space Challenge
python pip install -r requirements.txt
We recommand a virtual environment such as Anaconda for running this code.
python prepare_data.py /path/to/img_dir
RRDB pretrained weights
Download pretrained weights of RRDB and place them into ‘pretrained_weights’ folder
These pretrained weights are originally from SRFlow
python train.py -opt path/to/Confpath
- path/to/Confpath is model parameter script which is in code/confs/~.yml
python eval.py --scale scale_factor --lrtest_path path/to/LRpath --conf_path path/to/Confpath
- To eval with pretrained model, please check model_path in Confpath.
- Pretriained models should be in code/pretrained_model