Half Instance Normalization Network for Image Restoration

Overview

HINet

Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet.

Dependencies

  • NumPy
  • PyTorch, preferably with CUDA. Note that torchvision and torchaudio are not required and hence can be omitted from the command.
  • VapourSynth
  • (Optional) TensorRT. Note that uff and PyCUDA are not required and hence can be skipped from the guide.
  • (Optional) torch2trt

Installation

pip install --upgrade vshinet
python -m vshinet

Usage

from vshinet import HINet

ret = HINet(clip)

See __init__.py for the description of the parameters.

You might also like...
Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

Real-ESRGAN Colab Demo for Real-ESRGAN . Portable Windows executable file. You can find more information here. Real-ESRGAN aims at developing Practica

Image restoration with neural networks but without learning.
Image restoration with neural networks but without learning.

Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s

SwinIR: Image Restoration Using Swin Transformer
SwinIR: Image Restoration Using Swin Transformer

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]
Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]

Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan

An official repository for Paper
An official repository for Paper "Uformer: A General U-Shaped Transformer for Image Restoration".

Uformer: A General U-Shaped Transformer for Image Restoration Zhendong Wang, Xiaodong Cun, Jianmin Bao and Jianzhuang Liu Paper: https://arxiv.org/abs

Image Restoration Using Swin Transformer for VapourSynth

SwinIR SwinIR function for VapourSynth, based on https://github.com/JingyunLiang/SwinIR. Dependencies NumPy PyTorch, preferably with CUDA. Note that t

The 7th edition of NTIRE: New Trends in Image Restoration and Enhancement workshop will be held on June 2022 in conjunction with CVPR 2022.
The 7th edition of NTIRE: New Trends in Image Restoration and Enhancement workshop will be held on June 2022 in conjunction with CVPR 2022.

NTIRE 2022 - Image Inpainting Challenge Important dates 2022.02.01: Release of train data (input and output images) and validation data (only input) 2

[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination
[ArXiv 2021] Data-Efficient Instance Generation from Instance Discrimination

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

Comments
  • mode 1 tiling issue

    mode 1 tiling issue

    using 'HINet(clip=clip, mode=1, device_index=0, tile_x=424, tile_y=480, fp16=True)' I see green artifact artifacts uploaded the full script and the source file to my GoogleDrive

    Okay, correction, this does also happen when tiling is deactivated, so this seems to be a bug in mode=1. Using clip = HINet(clip=clip, mode=1, device_type="cpu") does not show theses artifacts. (using cpu instead of gpu)

    opened by Selur 2
  • [REQ] Restormer port

    [REQ] Restormer port

    opened by AIisCool 1
  • [REQ] Investigating Tradeoffs in Real-World Video Super-Resolution code available !

    [REQ] Investigating Tradeoffs in Real-World Video Super-Resolution code available !

    RealBasicVSR by @ckkelvinchan has just been released:

    https://user-images.githubusercontent.com/7676947/143370499-9fe4069b-46cc-4f12-b6ff-5595e8e5e0b8.mp4

    https://user-images.githubusercontent.com/7676947/143370350-91f751f3-0f33-4ee4-9b1a-b9279bf41c18.mp4

    https://user-images.githubusercontent.com/7676947/143370556-9e7019d4-e718-46af-859f-54d5576cd370.mp4

    https://user-images.githubusercontent.com/7676947/143370859-e0293b97-f962-476f-acf8-14fad27cea77.mp4

    (videos have been compressed. Therefore, the results are inferior to that of the actual outputs)

    opened by forart 0
Owner
Holy Wu
Holy Wu
AI drive app that can help user become beautiful.

爱美丽 Beauty 简体中文 Features Beauty is an AI drive app that can help user become beautiful. it contain those functions: face score cheek face beauty repor

Starved Midnight 1 Jan 30, 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
Detecting Potentially Harmful and Protective Suicide-related Content on Twitter

TwitterSuicideML Scripts for reproducing the Machine Learning analysis of the paper: Detecting Potentially Harmful and Protective Suicide-related Cont

3 Oct 17, 2022
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

Fan-Yun Sun 232 Dec 28, 2022
Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"

Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir

Michael Janner 269 Jan 05, 2023
A PyTorch-Based Framework for Deep Learning in Computer Vision

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Donny You 2.2k Jan 09, 2023
[ICCV21] Self-Calibrating Neural Radiance Fields

Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google

381 Dec 30, 2022
Code for ECIR'20 paper Diagnosing BERT with Retrieval Heuristics

Bert Axioms This is the repository with the code for the Paper Diagnosing BERT with Retrieval Heuristics Required Data In order to run this code, you

Arthur Câmara 5 Jan 21, 2022
RP-GAN: Stable GAN Training with Random Projections

RP-GAN: Stable GAN Training with Random Projections This repository contains a reference implementation of the algorithm described in the paper: Behna

Ayan Chakrabarti 20 Sep 18, 2021
a baseline to practice

ccks2021_track3_baseline a baseline to practice 路径可能会有问题,自己改改 torch==1.7.1 pyhton==3.7.1 transformers==4.7.0 cuda==11.0 this is a baseline, you can fi

45 Nov 23, 2022
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition (NeurIPS 2019)

MLCR This is the source code for paper Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition. Xuesong Niu, Hu Han, Shiguang

Edson-Niu 60 Nov 29, 2022
Code for the paper "Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds" (ICCV 2021)

Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds This is the official code implementation for the paper "Spatio-temporal Se

Hesper 63 Jan 05, 2023
Code for "Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans" CVPR 2021 best paper candidate

News 05/17/2021 To make the comparison on ZJU-MoCap easier, we save quantitative and qualitative results of other methods at here, including Neural Vo

ZJU3DV 748 Jan 07, 2023
Unbalanced Feature Transport for Exemplar-based Image Translation (CVPR 2021)

UNITE and UNITE+ Unbalanced Feature Transport for Exemplar-based Image Translation (CVPR 2021) Unbalanced Intrinsic Feature Transport for Exemplar-bas

Fangneng Zhan 183 Nov 09, 2022
Text completion with Hugging Face and TensorFlow.js running on Node.js

Katana ML Text Completion 🤗 Description Runs with with Hugging Face DistilBERT and TensorFlow.js on Node.js distilbert-model - converter from Hugging

Katana ML 2 Nov 04, 2022
Data Augmentation Using Keras and Python

Data-Augmentation-Using-Keras-and-Python Data augmentation is the process of increasing the number of training dataset. Keras library offers a simple

Happy N. Monday 3 Feb 15, 2022
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper

Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh

Sohil Shah 197 Nov 29, 2022
A Python module for the generation and training of an entry-level feedforward neural network.

ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin

Riadh 2 Jan 31, 2022
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

Xintao 593 Jan 03, 2023
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C

tjwei 1.5k Dec 16, 2022