DAN: Unfolding the Alternating Optimization for Blind Super Resolution

Related tags

Deep LearningDAN-Basd-on-Openmmlab
Overview

DAN-Basd-on-Openmmlab

DAN: Unfolding the Alternating Optimization for Blind Super Resolution

We reproduce DAN via mmediting based on open-sourced code.

Requirements

  • PyTorch >= 1.3
  • mmediting >= 0.9

DataSets

We use DIV2K and Flickr2K as our training datasets. For evaluation of Setting 2, we use DIV2KRK datasets,

Usages

How to run this repo: copy the file to the mmediting workspace and run the program directly based on the commands in mmediting

  1. Copy files to MMEditing workspace.
cd DAN-Basd-on-Openmmlab/
mv ./mmedit/models/restorers/dan.py ${mmediting_workspace}/mmedit/models/restorers/
mv ./mmedit/models/backbones/sr_backbones/dan_net.py ${mmediting_workspace}/mmedit/models/backbones/sr_backbones/
mv ./mmedit/models/common/DANpreprocess.py ${mmediting_workspace}/mmedit/models/common
mv ./configs/restorers/dan ${mmediting_workspace}/configs/restorers/
mv ./tools/data/super-resolution/dan_datasets ${mmediting_workspace}/tools/data/super-resolution/
  1. Modify the configuration file as follows:
pca_matrix_path='${mmediting_workspace}/tools/data/super-resolution/div2k/pca_matrix/pca_aniso_matrix_x4.pth' # your pca_matrix path
# Training
gt_folder='${dataset_workspace}/dataset/DF2K_train_HR_sub' # your train data path
# Testing
lq_folder='${dataset_workspace}/dataset/DIV2KRK/lr_x4' # your test data LR path
gt_folder='${dataset_workspace}/dataset/DIV2KRK/gt' # your test data HR path
  1. Add script to init file, as follows:
  • modify the mmedit/models/backbones/sr_backbones/__init__.py:
from .dan_net import DAN
# add DAN into __all__ list.
  • modify the mmedit/models/commons/__init__.py:
from .dan_preprocess import SRMDPreprocessing
# add SRMDreprocessing into __all__ list.
  • modify the mmedit/models/restorers/__init__.py:
from .dan import DAN
# add DAN into __all__ list.
  1. Training/Test

Before using it, please download and process the dataset and set the path in the configuration file.

  • Train
# Single GPU
python tools/train.py configs/restorers/dan/dan_setting2.py --work_dir ${YOUR_WORK_DIR}

# Multiple GPUs
./tools/dist_train.sh configs/restorers/dan/dan_setting2.py ${GPU_NUM} --work_dir ${YOUR_WORK_DIR}
  • Test
# Single GPU
python tools/test.py configs/restorers/dan/dan_setting2.py ${CHECKPOINT_FILE} [--metrics ${METRICS}] [--out ${RESULT_FILE}]

# Multiple GPUs
./tools/dist_test.sh configs/restorers/dan/dan_setting2.py ${CHECKPOINT_FILE} ${GPU_NUM} [--metrics ${METRICS}] [--out ${RESULT_FILE}]

Result

DIV2KRK

The passwds of download links are all 'ta2o'

Method scale Datasets PSNR Download
DAN x4 DIV2KRK 27.41 model / test_pkl
Owner
AlexZou
AlexZou
GitHub Repository
The implementation of our CIKM 2021 paper titled as: "Cross-Market Product Recommendation"

FOREC: A Cross-Market Recommendation System This repository provides the implementation of our CIKM 2021 paper titled as "Cross-Market Product Recomme

Hamed Bonab 16 Sep 12, 2022
This is the repo for the paper "Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement".

Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement This is the repository for the paper "Improving the Accuracy-Memory Trad

3 Dec 29, 2022
Decorators for maximizing memory utilization with PyTorch & CUDA

torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and

Max Berrendorf 10 May 02, 2022
Official repository for GCR rerank, a GCN-based reranking method for both image and video re-ID

Official repository for GCR rerank, a GCN-based reranking method for both image and video re-ID

53 Nov 22, 2022
Official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation

SegPC-2021 This is the official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation by

Datascience IIT-ISM 13 Dec 14, 2022
A self-supervised 3D representation learning framework named viewpoint bottleneck.

Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In

63 Aug 11, 2022
Official implementation of "MetaSDF: Meta-learning Signed Distance Functions"

MetaSDF: Meta-learning Signed Distance Functions Project Page | Paper | Data Vincent Sitzmann*, Eric Ryan Chan*, Richard Tucker, Noah Snavely Gordon W

Vincent Sitzmann 100 Jan 01, 2023
Implementation of OpenAI paper with Simple Noise Scale on Fastai V2

README Implementation of OpenAI paper "An Empirical Model of Large-Batch Training" for Fastai V2. The code is based on the batch size finder implement

13 Dec 10, 2021
Robotics with GPU computing

Robotics with GPU computing Cupoch is a library that implements rapid 3D data processing for robotics using CUDA. The goal of this library is to imple

Shirokuma 625 Jan 07, 2023
Pairwise model for commonlit competition

Pairwise model for commonlit competition To run: - install requirements - create input directory with train_folds.csv and other competition data - cd

abhishek thakur 45 Aug 31, 2022
This is a TensorFlow implementation for C2-Rec

This is a TensorFlow implementation for C2-Rec We refer to the repo SASRec. Requirements requirement.txt Datasets This repo includes Amazon Beauty dat

7 Nov 14, 2022
Fast, flexible and fun neural networks.

Brainstorm Discontinuation Notice Brainstorm is no longer being maintained, so we recommend using one of the many other,available frameworks, such as

IDSIA 1.3k Nov 21, 2022
A project to make Amazon Echo respond to sign language using your webcam

Making Alexa respond to Sign Language using Tensorflow.js Try the live demo Read the Blog Post on Tensorflow's Blog Coming Soon Watch the video This p

Abhishek Singh 444 Jan 03, 2023
An executor that performs image segmentation on fashion items

ClothingSegmenter U2NET fashion image/clothing segmenter based on https://github.com/levindabhi/cloth-segmentation Overview The ClothingSegmenter exec

Jina AI 5 Mar 30, 2022
Generalized Data Weighting via Class-level Gradient Manipulation

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

18 Nov 12, 2022
Code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction

Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,

stanley 152 Dec 16, 2022
An official implementation of the Anchor DETR.

Anchor DETR: Query Design for Transformer-Based Detector Introduction This repository is an official implementation of the Anchor DETR. We encode the

MEGVII Research 276 Dec 28, 2022
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

Benedek Rozemberczki 259 Dec 05, 2022
Speedy Implementation of Instance-based Learning (IBL) agents in Python

A Python library to create single or multi Instance-based Learning (IBL) agents that are built based on Instance Based Learning Theory (IBLT) 1 Instal

0 Nov 18, 2021
Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation in PyTorch

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Ima

Xuanchi Ren 86 Dec 07, 2022