This repository is for CoMoNet introduced in the following paper
Yuanfei Huang, Jie Li, Yanting Hu, Hua Huang and Xinbo Gao, "Deep Convolution Modulation for Image Super-resolution", submitted.
- python 3.8
- pytorch >= 1.7.0
- NVIDIA GPU + CUDA
Download DIV2K datasets into the path "../../Datasets/Train/DIV2K".
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Replace the train dataset path '../../Datasets/Train/' and validation dataset '../../Datasets/Test/' with your training and validation datasets, respectively.
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Set the configurations in 'option.py' as you want.
python main.py --train 'Train'-
Download models from 'models/'.
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Replace the test dataset path '../../Datasets/Test/' with your datasets.
python main.py --train 'Test'
