BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

Overview

BasicVSR

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

Ported from https://github.com/xinntao/BasicSR

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 vsbasicvsr

Usage

from vsbasicvsr import BasicVSR

ret = BasicVSR(clip)

See __init__.py for the description of the parameters.

You might also like...
VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).
VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).

VSR-Transformer By Jiezhang Cao, Yawei Li, Kai Zhang, Luc Van Gool This paper proposes a new Transformer for video super-resolution (called VSR-Transf

EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

MoCoPnet - Deformable 3D Convolution for Video Super-Resolution
MoCoPnet - Deformable 3D Convolution for Video Super-Resolution

Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l

Simple, but essential Bayesian optimization package

BayesO: A Bayesian optimization framework in Python Simple, but essential Bayesian optimization package. http://bayeso.org Online documentation Instal

An essential implementation of BYOL in PyTorch + PyTorch Lightning
An essential implementation of BYOL in PyTorch + PyTorch Lightning

Essential BYOL A simple and complete implementation of Bootstrap your own latent: A new approach to self-supervised Learning in PyTorch + PyTorch Ligh

A 2D Visual Localization Framework based on Essential Matrices [ICRA2020]
A 2D Visual Localization Framework based on Essential Matrices [ICRA2020]

A 2D Visual Localization Framework based on Essential Matrices This repository provides implementation of our paper accepted at ICRA: To Learn or Not

Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.

Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex

Official Pytorch implementation of
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021

TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r

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

Comments
  • Tile doesn't seem to work.

    Tile doesn't seem to work.

    Using:

    # Imports
    import vapoursynth as vs
    # getting Vapoursynth core
    core = vs.core
    # Loading Plugins
    core.std.LoadPlugin(path="I:/Hybrid/64bit/vsfilters/Support/fmtconv.dll")
    core.std.LoadPlugin(path="I:/Hybrid/64bit/vsfilters/SourceFilter/vsrawsource/vsrawsource.dll")
    # source: 'C:\Users\Selur\Desktop\stefan_sif.y4m'
    # current color space: YUV420P8, bit depth: 8, resolution: 352x240, fps: 29.97, color matrix: 470bg, yuv luminance scale: full, scanorder: progressive
    # Loading C:\Users\Selur\Desktop\stefan_sif.y4m using RawsSource
    clip = core.raws.Source("C:/Users/Selur/Desktop/stefan_sif.y4m")
    # making sure input color matrix is set as 470bg
    clip = core.resize.Bicubic(clip, matrix_in_s="470bg",range_s="full")
    # making sure frame rate is set to 29.970
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30000, fpsden=1001)
    # Setting color range to PC (full) range.
    clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=0)
    # adjusting color space from YUV420P8 to RGBS for vsBasicVSR
    clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, matrix_in_s="470bg", range_s="full")
    # resizing using BasicVSR
    from vsbasicvsr import BasicVSR
    clip = BasicVSR(clip=clip, radius=15, device_type="cuda", tile=2)
    # adjusting resizing to hit target resolution 
    clip = core.fmtc.resample(clip=clip, w=1280, h=874, kernel="lanczos", interlaced=False, interlacedd=False)
    # adjusting output color from: RGB48 to YUV420P10 for x265Model
    clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P10, matrix_s="470bg", range_s="full")
    # set output frame rate to 29.970fps
    clip = core.std.AssumeFPS(clip=clip, fpsnum=30000, fpsden=1001)
    # Output
    clip.set_output()
    

    gives me

    Input and output sizes should be greater than 0, but got input (H: 0, W: 0) output (H: 0, W: 0)
    

    without the tile=2, it works.

    opened by Selur 5
Releases(v1.2.0)
Owner
Holy Wu
Holy Wu
A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022
Implementations of LSTM: A Search Space Odyssey variants and their training results on the PTB dataset.

An LSTM Odyssey Code for training variants of "LSTM: A Search Space Odyssey" on Fomoro. Check out the blog post. Training Install TensorFlow. Clone th

Fomoro AI 95 Apr 13, 2022
CMT: Convolutional Neural Networks Meet Vision Transformers

CMT: Convolutional Neural Networks Meet Vision Transformers [arxiv] 1. Introduction This repo is the CMT model which impelement with pytorch, no refer

FlyEgle 83 Dec 30, 2022
Implementation of Shape and Electrostatic similarity metric in deepFMPO.

DeepFMPO v3D Code accompanying the paper "On the value of using 3D-shape and electrostatic similarities in deep generative methods". The paper can be

34 Nov 28, 2022
DeepRec is a recommendation engine based on TensorFlow.

DeepRec Introduction DeepRec is a recommendation engine based on TensorFlow 1.15, Intel-TensorFlow and NVIDIA-TensorFlow. Background Sparse model is a

Alibaba 676 Jan 03, 2023
Extreme Rotation Estimation using Dense Correlation Volumes

Extreme Rotation Estimation using Dense Correlation Volumes This repository contains a PyTorch implementation of the paper: Extreme Rotation Estimatio

Ruojin Cai 29 Nov 18, 2022
Seeing All the Angles: Learning Multiview Manipulation Policies for Contact-Rich Tasks from Demonstrations

Seeing All the Angles: Learning Multiview Manipulation Policies for Contact-Rich Tasks from Demonstrations Trevor Ablett, Daniel (Yifan) Zhai, Jonatha

STARS Laboratory 3 Feb 01, 2022
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

TU Delft 43 Dec 07, 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
SSL_SLAM2: Lightweight 3-D Localization and Mapping for Solid-State LiDAR (mapping and localization separated) ICRA 2021

SSL_SLAM2 Lightweight 3-D Localization and Mapping for Solid-State LiDAR (Intel Realsense L515 as an example) This repo is an extension work of SSL_SL

Wang Han 王晗 1.3k Jan 08, 2023
Top #1 Submission code for the first https://alphamev.ai MEV competition with best AUC (0.9893) and MSE (0.0982).

alphamev-winning-submission Top #1 Submission code for the first alphamev MEV competition with best AUC (0.9893) and MSE (0.0982). The code won't run

70 Oct 29, 2022
A different spin on dataclasses.

dataklasses Dataklasses is a library that allows you to quickly define data classes using Python type hints. Here's an example of how you use it: from

David Beazley 752 Nov 18, 2022
Self-Supervised Speech Pre-training and Representation Learning Toolkit.

What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site

s3prl 1.6k Jan 08, 2023
Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks

OnsagerNet Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks This is the original pyTorch implemenati

Haijun.Yu 3 Aug 24, 2022
Official code for the publication "HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder".

HyFactor Graph-based architectures are becoming increasingly popular as a tool for structure generation. Here, we introduce a novel open-source archit

Laboratoire-de-Chemoinformatique 11 Oct 10, 2022
Prososdy Morph: A python library for manipulating pitch and duration in an algorithmic way, for resynthesizing speech.

ProMo (Prosody Morph) Questions? Comments? Feedback? Chat with us on gitter! A library for manipulating pitch and duration in an algorithmic way, for

Tim 71 Jan 02, 2023
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

Erick Cobos 73 Dec 04, 2022
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.

Trading Gym Trading Gym is an open-source project for the development of reinforcement learning algorithms in the context of trading. It is currently

Dimitry Foures 535 Nov 15, 2022
Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

EagerMOT: 3D Multi-Object Tracking via Sensor Fusion Read our ICRA 2021 paper here. Check out the 3 minute video for the quick intro or the full prese

Aleksandr Kim 276 Dec 30, 2022
A crash course in six episodes for software developers who want to become machine learning practitioners.

Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P

Google Cloud Platform 2.6k Jan 08, 2023