The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'

Overview

PWC PWC PWC PWC PWC PWC

Deep Residual Fourier Transformation for Single Image Deblurring

Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang

News

  • 2021.12.5 Release DeepRFT model

Paper: https://arxiv.org/abs/2111.11745

Network Architecture

Overall Framework of DeepRFT

Installation

The model is built in PyTorch 1.8.0 and tested on Ubuntu 18.04 environment (Python3.8, CUDA11.1).

For installing, follow these intructions

conda create -n pytorch python=3.8
conda activate pytorch
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
pip install matplotlib scikit-image opencv-python yacs joblib natsort h5py tqdm kornia tensorboard ptflops

Install warmup scheduler

cd pytorch-gradual-warmup-lr; python setup.py install; cd ..

Quick Run

To test the pre-trained models of Deblur and Defocus Google Drive or 百度网盘 on your own images, run

python test.py --weights ckpt_path_here --input_dir path_to_images --result_dir save_images_here --win_size 256 # deblur
python test.py --weights ckpt_path_here --input_dir path_to_images --result_dir save_images_here --win_size 512 # defocus

Here is an example to train:

python train.py

Results

Experiment for image deblurring.

Deblurring on GoPro Datasets.

Reference Code:

Citation

If you use DeepRFT, please consider citing:

@inproceedings{,
    title={Deep Residual Fourier Transformation for Single Image Deblurring},
    author={Xintian Mao, Yiming Liu, Wei Shen, Qingli Li, Yan Wang},
    booktitle={arXiv:2111.11745},
    year={2021}
}

Contact

If you have any question, please contact [email protected]

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