README.md
April 11, 2024 · View on GitHub
Neumann Network with Recursive Kernels for Single Image Defocus Deblurring
Official PyTorch Implementation of the CVPR 2023 Paper
This repo contains training and evaluation code for the following paper:
Neumann Network with Recursive Kernels for Single Image Defocus Deblurring.
IEEE Computer Vision and Pattern Recognition (CVPR) 2023
Getting Started
Prerequisites
conda create -n NRKNet python=3.7
conda activate NRKNet
cd ./NRKNet
pip install -r requirements.txt
Datasets
Download and unzip datasets under [DATASET_ROOT]:
- DPDD dataset: Google Drive | Dropbox
- CUHK test set: Google Drive | Dropbox
- RealDOF test set: Google Drive | Dropbox
- LFDOF dataset: Download path
- RTF test set: Please contact the author (Laurent, laurentdandres@gmail.com), he will kindly share the dataset and necessary information with you.
[DATASET_ROOT]
├── DPDD
├── RealDOF
├── CUHK
├── LFDOF
└── RTF
[DATASET_ROOT]can be modified with [config.data_offset] in./config.py.
Train the NRKNet
Train the NRKNet with different training datasets (DPDD | LFDOF).
# Trained with DPDD
CUDA_VISIBLE_DEVICES=0 python train_DPDD.py
# Trained with LFDOF
CUDA_VISIBLE_DEVICES=0 python train_LFDOF.py
Test the NRKNet
Download the pre-trained models
Download the pre-trained models and unzip datasets under [NRKNet-main]:
Options
-
Select the training and testing datasets in config.py.
- 'train['train_dataset_name']': The name of a dataset to train.
DPDD|LFDOF. Default:DPDD - 'test['dataset']': The name of a dataset to evaluate.
DPDD|LFDOF|RTF|RealDOF. Default:DPDD
- 'train['train_dataset_name']': The name of a dataset to train.
-
Run test.py.
CUDA_VISIBLE_DEVICES=0 python test.py
Test with your re-trained models
- Modify the path of a re-trained model in config.py.
# From
train['resume'] = './save/NRKNet_' + train['train_dataset_name'] + '/0'
#To
train['resume'] = './save/NRKNet_' + train['train_dataset_name'] + '/1'
-
Select the training and testing datasets in config.py.
-
Run test.py
Contact
Open an issue for any inquiries. You may also have contact with zicongwu.scut@gmail.com
Citation
@inproceedings{quan2023neumann,
title={Neumann Network With Recursive Kernels for Single Image Defocus Deblurring},
author={Yuhui Quan, Zicong Wu and Hui Ji},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={5754--5763},
year={2023}
}