Image Restoration Using Swin Transformer for VapourSynth

Overview

SwinIR

SwinIR function for VapourSynth, based on https://github.com/JingyunLiang/SwinIR.

Dependencies

  • NumPy
  • PyTorch, preferably with CUDA. Note that torchvision and torchaudio are not required and hence can be omitted from the command.
  • VapourSynth

Installation

pip install --upgrade vsswinir
python -m vsswinir

Usage

from vsswinir import SwinIR

ret = SwinIR(clip)

See __init__.py for the description of the parameters.

You might also like...
Implementation of the Swin Transformer in PyTorch.
Implementation of the Swin Transformer in PyTorch.

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

Tensorflow implementation of Swin Transformer model.
Tensorflow implementation of Swin Transformer model.

Swin Transformer (Tensorflow) Tensorflow reimplementation of Swin Transformer model. Based on Official Pytorch implementation. Requirements tensorflow

Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training.
Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training.

Updates (2020/06/21) Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training. Pyr

This project aims to explore the deployment of Swin-Transformer based on TensorRT, including the test results of FP16 and INT8.

Swin Transformer This project aims to explore the deployment of SwinTransformer based on TensorRT, including the test results of FP16 and INT8. Introd

Unofficial PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution

PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].

Multi-Stage Progressive Image Restoration
Multi-Stage Progressive Image Restoration

Multi-Stage Progressive Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Sh

(under submission) Bayesian Integration of a Generative Prior for Image Restoration
(under submission) Bayesian Integration of a Generative Prior for Image Restoration

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration Authors: Majed El Helou, and Sabine Süsstrunk {Note: p

 HINet: Half Instance Normalization Network for Image Restoration
HINet: Half Instance Normalization Network for Image Restoration

HINet: Half Instance Normalization Network for Image Restoration Liangyu Chen, Xin Lu, Jie Zhang, Xiaojie Chu, Chengpeng Chen Paper: https://arxiv.org

This is an implementation for the CVPR2020 paper
This is an implementation for the CVPR2020 paper "Learning Invariant Representation for Unsupervised Image Restoration"

Learning Invariant Representation for Unsupervised Image Restoration (CVPR 2020) Introduction This is an implementation for the paper "Learning Invari

Owner
Holy Wu
Holy Wu
Pytorch implementation of SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation

SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation Efficient Self-Ensemble Framework for Semantic Segmentation by Walid Bousselham

61 Dec 26, 2022
FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX.

FedJAX: Federated learning with JAX What is FedJAX? FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX. FedJAX priori

Google 208 Dec 14, 2022
NALSM: Neuron-Astrocyte Liquid State Machine

NALSM: Neuron-Astrocyte Liquid State Machine This package is a Tensorflow implementation of the Neuron-Astrocyte Liquid State Machine (NALSM) that int

Computational Brain Lab 4 Nov 28, 2022
YOLOv7 - Framework Beyond Detection

🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥

JinTian 3k Jan 01, 2023
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution Kai Zhang, Jingyun Liang, Luc Van Gool, Radu Timofte Computer Vision Lab

Kai Zhang 804 Jan 08, 2023
Experiments with the Robust Binary Interval Search (RBIS) algorithm, a Query-Based prediction algorithm for the Online Search problem.

OnlineSearchRBIS Online Search with Best-Price and Query-Based Predictions This is the implementation of the Robust Binary Interval Search (RBIS) algo

S. K. 1 Apr 16, 2022
A computer vision pipeline to identify the "icons" in Christian paintings

Christian-Iconography A computer vision pipeline to identify the "icons" in Christian paintings. A bit about iconography. Iconography is related to id

Rishab Mudliar 3 Jul 30, 2022
Bringing sanity to world of messed-up data

Sanitize sanitize is a Python module for making sure various things (e.g. HTML) are safe to use. It was originally written by Mark Pilgrim and is dist

Alireza Savand 63 Oct 26, 2021
Convnet transfer - Code for paper How transferable are features in deep neural networks?

How transferable are features in deep neural networks? This repository contains source code necessary to reproduce the results presented in the follow

Jason Yosinski 143 Sep 13, 2022
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

CIFS This repository provides codes for CIFS (ICML 2021). CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Sel

Hanshu YAN 19 Nov 12, 2022
TinyML Cookbook, published by Packt

TinyML Cookbook This is the code repository for TinyML Cookbook, published by Packt. Author: Gian Marco Iodice Publisher: Packt About the book This bo

Packt 93 Dec 29, 2022
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l

DongYoung Kim 33 Jan 04, 2023
Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN)

Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN) This code implements the skeleton-based action segmentation MS-GCN model from Autom

Benjamin Filtjens 8 Nov 29, 2022
Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)

Neuron Merging: Compensating for Pruned Neurons Pytorch implementation of Neuron Merging: Compensating for Pruned Neurons, accepted at 34th Conference

Woojeong Kim 33 Dec 30, 2022
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C

Yin Cui 546 Jan 08, 2023
v objective diffusion inference code for PyTorch.

v-diffusion-pytorch v objective diffusion inference code for PyTorch, by Katherine Crowson (@RiversHaveWings) and Chainbreakers AI (@jd_pressman). The

Katherine Crowson 635 Dec 30, 2022
It is a system used to detect bone fractures. using techniques deep learning and image processing

MohammedHussiengadalla-Intelligent-Classification-System-for-Bone-Fractures It is a system used to detect bone fractures. using techniques deep learni

Mohammed Hussien 7 Nov 11, 2022
PyTorch implementation of neural style transfer algorithm

neural-style-pt This is a PyTorch implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias

770 Jan 02, 2023
Code & Models for 3DETR - an End-to-end transformer model for 3D object detection

3DETR: An End-to-End Transformer Model for 3D Object Detection PyTorch implementation and models for 3DETR. 3DETR (3D DEtection TRansformer) is a simp

Facebook Research 487 Dec 31, 2022
ReferFormer - Official Implementation of ReferFormer

The official implementation of the paper: Language as Queries for Referring Video Object Segmentation Language as Queries for Referring Video Object S

Jonas Wu 232 Dec 29, 2022