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
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
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper

ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni

574 Jan 02, 2023
MAU: A Motion-Aware Unit for Video Prediction and Beyond, NeurIPS2021

MAU (NeurIPS2021) Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye, Xinguang Xiang, Wen GAo. Official PyTorch Code for "MAU: A Motion-Aware

ZhengChang 20 Nov 25, 2022
An easy-to-use app to visualise attentions of various VQA models.

Ask Me Anything: A tool for visualising Visual Question Answering (AMA) An easy-to-use app to visualise attentions of various VQA models. Please click

Apoorve 37 Nov 13, 2022
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021

LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie

Hieu Duong 7 Jan 12, 2022
Personals scripts using ageitgey/face_recognition

HOW TO USE pip3 install requirements.txt Add some pictures of known people in the folder 'people' : a) Create a folder called by the name of the perso

Antoine Bollengier 1 Jan 06, 2022
Unbiased Learning To Rank Algorithms (ULTRA)

This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiments and research on learning to rank with human annotated or noisy labels.

71 Dec 01, 2022
FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection

FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection arXi

59 Nov 29, 2022
Flax is a neural network ecosystem for JAX that is designed for flexibility.

Flax: A neural network library and ecosystem for JAX designed for flexibility Overview | Quick install | What does Flax look like? | Documentation See

Google 3.9k Jan 02, 2023
nnFormer: Interleaved Transformer for Volumetric Segmentation

nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation ". Please

jsguo 610 Dec 28, 2022
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021)

DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction (3DV 2021) This repo is the implementation of DPC. Tested environment Pyth

Dvir Ginzburg 30 Nov 30, 2022
PyVideoAI: Action Recognition Framework

This reposity contains official implementation of: Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognitio

Kiyoon Kim 22 Dec 29, 2022
Real time Human Detection Counting

In this python project, we are going to build the Human Detection and Counting System through Webcam or you can give your own video or images. This is a deep learning project on computer vision, whic

Mir Nawaz Ahmad 2 Jun 17, 2022
Flower - A Friendly Federated Learning Framework

Flower - A Friendly Federated Learning Framework Flower (flwr) is a framework for building federated learning systems. The design of Flower is based o

Adap 1.8k Jan 01, 2023
The implementation of DeBERTa

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

Microsoft 1.2k Jan 06, 2023
A set of examples around hub for creating and processing datasets

Examples for Hub - Dataset Format for AI A repository showcasing examples of using Hub Uploading Dataset Places365 Colab Tutorials Notebook Link Getti

Activeloop 11 Dec 14, 2022
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)

Self-labelling via simultaneous clustering and representation learning ๐Ÿ†— ๐Ÿ†— ๐ŸŽ‰ NEW models (20th August 2020): Added standard SeLa pretrained torchvis

Yuki M. Asano 469 Jan 02, 2023
Morphable Detector for Object Detection on Demand

Morphable Detector for Object Detection on Demand (ICCV 2021) PyTorch implementation of the paper Morphable Detector for Object Detection on Demand. I

9 Feb 23, 2022
UPSNet: A Unified Panoptic Segmentation Network

UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te

Uber Research 622 Dec 26, 2022
Jittor implementation of Recursive-NeRF: An Efficient and Dynamically Growing NeRF

Recursive-NeRF: An Efficient and Dynamically Growing NeRF This is a Jittor implementation of Recursive-NeRF: An Efficient and Dynamically Growing NeRF

33 Nov 30, 2022