Pytorch implementation of Deep Recursive Residual Network for Super Resolution (DRRN)

Related tags

Deep LearningDRRN-pytorch
Overview

DRRN-pytorch

This is an unofficial implementation of "Deep Recursive Residual Network for Super Resolution (DRRN)", CVPR 2017 in Pytorch. [Paper]

You can get the official Caffe implementation here.

Usage

Training

usage: main.py [-h] [--batchSize BATCHSIZE] [--nEpochs NEPOCHS] [--lr LR]
               [--step STEP] [--cuda] [--resume RESUME]
               [--start-epoch START_EPOCH] [--clip CLIP] [--threads THREADS]
               [--momentum MOMENTUM] [--weight-decay WEIGHT_DECAY]
               [--pretrained PRETRAINED]
               
optional arguments:
  -h, --help            Show this help message and exit
  --batchSize           Training batch size
  --nEpochs             Number of epochs to train for
  --lr                  Learning rate. Default=0.1
  --step                Learning rate decay, Default: n=5 epochs
  --cuda                Use cuda?
  --resume              Path to checkpoint
  --clip                Clipping Gradients. Default=0.01
  --threads             Number of threads for data loader to use Default=1
  --momentum            Momentum, Default: 0.9
  --weight-decay        Weight decay, Default: 1e-4
  --pretrained          Path to the pretrained model, used for weight initialization (default: none)

Evaluation

usage: eval.py [-h] [--cuda] [--model MODEL] [--dataset DATASET]
               [--scale SCALE]

PyTorch DRRN Evaluation

optional arguments:
  -h, --help         show this help message and exit
  --cuda             use cuda?
  --model MODEL      model path
  --dataset DATASET  dataset name, Default: Set5

An example of training usage is shown as follows:

python eval.py --cuda

Prepare Training dataset

  • the training data is generated with Matlab Bicubic Interpolation, please refer Code for Data Generation for creating training files.

Performance

  • We provide a rough pre-trained DRRN_B1U25 model trained on 291 images with data augmentation. The model can achieve a better performance with a smart optimization strategy. For the DRRN_B1U9 implementation, you can manually modify the number of recursive blocks here.
  • The same adjustable gradient clipping's implementation as original paper.
  • No bias is used in this implementation.
  • No batch normalization is used in this implementation.
  • Performance in PSNR on Set5
Scale DRRN_B1U25 Paper DRRN_B1U25 PyTorch
x2 37.74 37.69
x3 34.03 34.02
x4 31.68 31.70
Owner
yun_yang
yun_yang
GitHub Repository
This project uses ViT to perform image classification tasks on DATA set CIFAR10.

Vision-Transformer-Multiprocess-DistributedDataParallel-Apex Introduction This project uses ViT to perform image classification tasks on DATA set CIFA

Kaicheng Yang 3 Jun 03, 2022
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

Shiming Chen 6 Aug 16, 2022
The Pytorch implementation for "Video-Text Pre-training with Learned Regions"

Region_Learner The Pytorch implementation for "Video-Text Pre-training with Learned Regions" (arxiv) We are still cleaning up the code further and pre

Rui Yan 0 Mar 20, 2022
TabNet for fastai

TabNet for fastai This is an adaptation of TabNet (Attention-based network for tabular data) for fastai (=2.0) library. The original paper https://ar

Mikhail Grankin 116 Oct 21, 2022
A Japanese Medical Information Extraction Toolkit

JaMIE: a Japanese Medical Information Extraction toolkit Joint Japanese Medical Problem, Modality and Relation Recognition The Train/Test phrases requ

7 Dec 12, 2022
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences

Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences 1. Introduction This project is for paper Model-free Vehicle Tracking and St

TuSimple 92 Jan 03, 2023
A python library for self-supervised learning on images.

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

Lightly 2k Jan 08, 2023
This is a Python Module For Encryption, Hashing And Other stuff

EnroCrypt This is a Python Module For Encryption, Hashing And Other Basic Stuff You Need, With Secure Encryption And Strong Salted Hashing You Can Do

5 Sep 15, 2022
A collection of resources on GAN Inversion.

This repo is a collection of resources on GAN inversion, as a supplement for our survey

857 Dec 29, 2022
Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation)

Official PyTorch Implementation for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'2021, Oral Presentation) HOTR: End-to-

Kakao Brain 114 Nov 28, 2022
Supplementary code for TISMIR paper "Sliding-Window Pitch-Class Histograms as a Means of Modeling Musical Form"

Sliding-Window Pitch-Class Histograms as a Means of Modeling Musical Form This is supplementary code for the TISMIR paper Sliding-Window Pitch-Class H

1 Nov 27, 2021
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"

PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe

Benoit Brummer 6 Jun 16, 2022
Hand Gesture Volume Control | Open CV | Computer Vision

Gesture Volume Control Hand Gesture Volume Control | Open CV | Computer Vision Use gesture control to change the volume of a computer. First we look i

Jhenil Parihar 3 Jun 15, 2022
BrainGNN - A deep learning model for data-driven discovery of functional connectivity

A deep learning model for data-driven discovery of functional connectivity https://doi.org/10.3390/a14030075 Usman Mahmood, Zengin Fu, Vince D. Calhou

Usman Mahmood 3 Aug 28, 2022
A library to inspect itermediate layers of PyTorch models.

A library to inspect itermediate layers of PyTorch models. Why? It's often the case that we want to inspect intermediate layers of a model without mod

archinet.ai 380 Dec 28, 2022
StellarGraph - Machine Learning on Graphs

StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get

S T E L L A R 2.6k Jan 05, 2023
An end-to-end project on customer segmentation

End-to-end Customer Segmentation Project Note: This project is in progress. Tools Used in This Project Prefect: Orchestrate workflows hydra: Manage co

Ocelot Consulting 8 Oct 06, 2022
Leveraging OpenAI's Codex to solve cornerstone problems in Music

Music-Codex Leveraging OpenAI's Codex to solve cornerstone problems in Music Please NOTE: Presented generated samples were created by OpenAI's Codex P

Alex 2 Mar 11, 2022
particle tracking model, works with the ROMS output file(qck.nc, his.nc)

particle-tracking-model-for-ROMS particle tracking model, works with the ROMS output file(qck.nc, his.nc) description this is a 2-dimensional particle

xusheng 1 Jan 11, 2022
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.

BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.

Zhen Dong 36 Dec 02, 2022