Awesome
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
Code for CVPR21 paper NBNet.
<u>The illustration of our key insight:</u>
<img src="./Fig/fig2.png" alt="projection_concept" style="zoom:100%;" />Dependencies
- MegEngine >= 1.3.1 (For DistributedDataParallel)
Training
Preparation
python prepare_data.py --data_dir yours_sidd_data_path
Begin training:
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
Begin testing:
Download the pretrained checkpoint and use:
python test.py -d prepared_data_path -c checkpoint_path
The result is PSNR 39.765.
Pretrained model
MegEngine checkpoint for SIDD benchmark can be downloaded via Google Drive or GitHub Release.