SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical)

1. Introduction

This repo is not only used for our paper(SDWNet) but also used for Deblur codebase. We implement a number of components that allow you to quickly implement your own model.

Paper The SDWNet has been accepted by iccvw2021, you can read the paper here.
Model

2. Folder Structure

  ---SDWNet
  |
  |- config
  |    |- model.yaml                            -> Model all traninig hyparameters with data log.
  |    |-Config.py                              -> Translate the config file to dict.
  |- data
  |    |- vanilar_dataset.py                    -> The dataset for build the LR & HR images.
  |    |- utils.py                              -> Utils for get patch and calculate the model metrics.
  |    |- augments.py                           -> Augment method for LR & HR images.
  |- model
  |    - NTIRE2021_Deblur
  |        - uniA_ELU
  |            |- layerlib_stage1               -> Model module.
  |            |- model_stage1_dual_branch_tail.py -> Main model.
  |- loss
  |   |- gendrator_loss.py                      -> Loss function define.
  |- optim
  |   |- optimizer.py                           -> Optimizer function define.
  |- train.py                                   -> Training.
  |- goprol_train.sh                             -> Training shell.
  |- inference_ddp.py                           -> Inference.
  |- inference_ddp.sh                           -> Inference shell.

3. Training

Crop the src Training LR and HR images to 480x480 by sliding window which step is 240, so we got 24 patchs form one 720x1280 images both LR and HR.
Training the model with the 416 x 416 size, use randomcrop, RGB shuffle, horizon flip, rotate and so on.
Normalize the images to Tensor with 255 but not 1. which without process the mean and std.

python -W ignore train.py \
--config_file $config_folder \
--dist-url 'tcp://127.0.0.1:8888' \
--dist-backend 'nccl' \
--multiprocessing-distributed=1 \
--world-size=1 \
--rank=0 \

4. Inference

Inference the src LR images and get the SR images

python -W ignore inference_ddp.py \
--config_file $config_folder \
--dist-url 'tcp://127.0.0.1:8989' \
--dist-backend 'nccl' \
--multiprocessing-distributed=1 \
--world-size=1 \
--rank=0 \

5. Calculate

Calculate the PSNR and SSIM

python utils/calc_psnr_ssim_official.py

If you find this repo useful for your research, please consider citing the papers

@InProceedings{
  Zou_2021_ICCV, 
  author = {Zou, Wenbin and Jiang, Mingchao and Zhang, Yunchen and Chen, Liang and Lu, Zhiyong and Wu, Yi}, 
  title = {SDWNet: A Straight Dilated Network With Wavelet Transformation for Image Deblurring}, 
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, 
  month = {October}, 
  year = {2021}, 
  pages = {1895-1904} 
  }

An Straight Dilated Network with Wavelet for image Deblurring

Related tags

Overview

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical)

1. Introduction

2. Folder Structure

3. Training

4. Inference

5. Calculate

Owner

FlyEgle

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom

Official implementation of NeurIPS'2021 paper TransformerFusion

Sequence-to-Sequence learning using PyTorch

Pcos-prediction - Predicts the likelihood of Polycystic Ovary Syndrome based on patient attributes and symptoms

This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

Object tracking using YOLO and a tracker(KCF, MOSSE, CSRT) in openCV

I3-master-layout - Simple master and stack layout script

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

Winners of the Facebook Image Similarity Challenge

Source code for our paper "Empathetic Response Generation with State Management"

Implementation of parameterized soft-exponential activation function.

Generate indoor scenes with Transformers

SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation

Time Series Cross-Validation -- an extension for scikit-learn

PyTorch implementation of DreamerV2 model-based RL algorithm

Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.

RaceBERT -- A transformer based model to predict race and ethnicty from names

Pytorch implementation of the paper: "SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Image Deraining"

This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (ICLR 2022)

An NVDA add-on to split screen reader and audio from other programs to different sound channels