Half Instance Normalization Network for Image Restoration

Related tags

Deep Learningpytorchhinetvapoursynth
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

Xintao 17.2k Jan 2, 2023
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

Dmitry Ulyanov 7.4k Jan 1, 2023
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

Jingyun Liang 2.4k Jan 8, 2023
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

Kai Zhang 2k Dec 31, 2022
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

Jian Zhang 84 Dec 9, 2022
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

Zhendong Wang 497 Dec 22, 2022
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

Holy Wu 11 Jun 19, 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.
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

Andrés Romero 37 Nov 27, 2022
[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,

GenForce: May Generative Force Be with You 93 Dec 25, 2022
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
GitHub Repository
Learning Features with Parameter-Free Layers (ICLR 2022)

Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up

NAVER AI 65 Dec 07, 2022
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Utkarsh Agiwal 1 Feb 03, 2022
Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

Raschka Research Group 14 Dec 27, 2022
Hierarchical Time Series Forecasting with a familiar API

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

Carlo Mazzaferro 204 Dec 17, 2022
Unified learning approach for egocentric hand gesture recognition and fingertip detection

Unified Gesture Recognition and Fingertip Detection A unified convolutional neural network (CNN) algorithm for both hand gesture recognition and finge

Mohammad 227 Dec 25, 2022
Dynamic View Synthesis from Dynamic Monocular Video

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer This repository contains code to compute depth from a

Intelligent Systems Lab Org 2.3k Jan 01, 2023
Official PyTorch implementation for paper "Efficient Two-Stage Detection of Human–Object Interactions with a Novel Unary–Pairwise Transformer"

UPT: Unary–Pairwise Transformers This repository contains the official PyTorch implementation for the paper Frederic Z. Zhang, Dylan Campbell and Step

Frederic Zhang 109 Dec 20, 2022
Matplotlib Image labeller for classifying images

mpl-image-labeller Use Matplotlib to label images for classification. Works anywhere Matplotlib does - from the notebook to a standalone gui! For more

Ian Hunt-Isaak 5 Sep 24, 2022
DaReCzech is a dataset for text relevance ranking in Czech

Dataset DaReCzech is a dataset for text relevance ranking in Czech. The dataset consists of more than 1.6M annotated query-documents pairs,

Seznam.cz a.s. 8 Jul 26, 2022
RobustVideoMatting and background composing in one model by using onnxruntime.

RVM_onnx_compose RobustVideoMatting and background composing in one model by using onnxruntime. Usage pip install -r requirements.txt python infer_cam

Quantum Liu 4 Apr 07, 2022
Implementation of ToeplitzLDA for spatiotemporal stationary time series data.

Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from

Jan Sosulski 5 Nov 07, 2022
A framework for GPU based high-performance medical image processing and visualization

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both mu

Erik Smistad 315 Dec 30, 2022
Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper

Continual Learning With Filter Atom Swapping Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper If find t

11 Aug 29, 2022
UFT - Universal File Transfer With Python

UFT 2.0.0 UFT (Universal File Transfer) is a CLI tool , which can be used to upl

Merwin 1 Feb 18, 2022
Autonomous racing with the Anki Overdrive

Anki Autonomous Racing Autonomous racing with the Anki Overdrive. Using the Overdrive-Python API (https://github.com/xerodotc/overdrive-python) develo

3 Dec 11, 2022
Deep learning models for change detection of remote sensing images

Change Detection Models (Remote Sensing) Python library with Neural Networks for Change Detection based on PyTorch. ⚡ ⚡ ⚡ I am trying to build this pr

Kaiyu Li 176 Dec 24, 2022
Live Hand Tracking Using Python

Live-Hand-Tracking-Using-Python Project Description: In this project, we will be

Hassan Shahzad 2 Jan 06, 2022
Implementation of "Bidirectional Projection Network for Cross Dimension Scene Understanding" CVPR 2021 (Oral)

Bidirectional Projection Network for Cross Dimension Scene Understanding CVPR 2021 (Oral) [ Project Webpage ] [ arXiv ] [ Video ] Existing segmentatio

Hu Wenbo 135 Dec 26, 2022
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have underg

Nafis Ahmed 1 Dec 28, 2021
Official TensorFlow code for the forthcoming paper

~ Efficient-CapsNet ~ Are you tired of over inflated and overused convolutional neural networks? You're right! It's time for CAPSULES :)

Vittorio Mazzia 203 Jan 08, 2023