MIRNet

super-resolution image-denoising image-enhancement

Installation

For installing, follow these intructions

conda install pytorch=1.1 torchvision=0.3 cudatoolkit=9.0 -c pytorch
pip install matplotlib scikit-image opencv-python yacs joblib natsort h5py tqdm

Image Denoising

python test_denoising_sidd.py

Image Super-resolution

python test_super_resolution.py --save_images --scale 3
python test_super_resolution.py --save_images --scale 4

Image Enhancement

python test_enhancement.py --save_images --input_dir ./datasets/lol/ --result_dir ./results/enhancement/lol/ --weights ./pretrained_models/enhancement/model_lol.pth

python test_enhancement.py --save_images --input_dir ./datasets/fivek_sample_images/ --result_dir ./results/enhancement/fivek/ --weights ./pretrained_models/enhancement/model_fivek.pth