Code for CVPR21 paper NBNet.

The illustration of our key insight:

• MegEngine >= 1.3.1 (For DistributedDataParallel)

python prepare_data.py --data_dir yours_sidd_data_path

For SIDD benchmark, use:

python train_mge.py -d prepared_data_path -n num_gpus

For DnD benchmark, we use MixUp additionally:

python train_mge.py -d prepared_data_path -n num_gpus --dnd

Download the pretrained checkpoint and use:

python test.py -d prepared_data_path -c checkpoint_path

The result is PSNR 39.765.

MegEngine checkpoint for SIDD benchmark can be downloaded via Google Drive or GitHub Release.