BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
Ported from https://github.com/xinntao/BasicSR
torchvision and torchaudio are not required and hence can be omitted from the command.pip install --upgrade vsbasicvsr
from vsbasicvsr import BasicVSR
ret = BasicVSR(clip)
See __init__.py for the description of the parameters.
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 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
Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l
BayesO: A Bayesian optimization framework in Python Simple, but essential Bayesian optimization package. http://bayeso.org Online documentation Instal
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 This repository provides implementation of our paper accepted at ICRA: To Learn or Not
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
TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r
MAU (NeurIPS2021) Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye, Xinguang Xiang, Wen GAo. Official PyTorch Code for "MAU: A Motion-Aware
Using:
225 Nov 13, 2022
6 Oct 20, 2021
28 Dec 15, 2022
74 Dec 5, 2022
48 Sep 27, 2022
![A 2D Visual Localization Framework based on Essential Matrices [ICRA2020]](https://github.com/GrumpyZhou/visloc-relapose/raw/master/pipeline/pipeline.jpg)
27 Nov 7, 2022
139 Jan 1, 2023
215 Jan 6, 2023
20 Nov 25, 2022
# 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.
fp16 parameter.tile parameter to tile_x and tile_y.There have been billions of academic papers around the world. However, maybe only 0.0...01% among them are valuable or are worth reading. Since our limited life has never been forever, TopPaper provi
Trans-Net Code for (Visual Boundary Knowledge Translation for Foreground Segmentation, AAAI2021). [https://ojs.aaai.org/index.php/AAAI/article/view/16
🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort
English | 简体中文 Why Non-Euclidean Geometry Considering these simple graph structures shown below. Nodes with same color has 2-hop distance whereas 1-ho
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A
Official PyTorch implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 Spotlight Paper) Zhisheng
Clean-Samples Like Dirt-Samples, but cleaned up, with clear provenance and license info (generally a permissive creative commons licence but check the
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-ba
ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset
Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language This repository contains UA-GEC data and an accompanying Python lib
Data Consistency for Magnetic Resonance Imaging Data Consistency (DC) is crucial for generalization in multi-modal MRI data and robustness in detectin
TransZero [arXiv] This repository contains the testing code for the paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning" accepted to
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021] Abstract Analyzing complex scenes with DNN is a challenging ta
Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision Download links and PyTorch implementation of "Towers of Ba
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation The reference code of Improving Factual Completeness and C
level_based_customer_segmentation Level Based Customer Segmentation Persona Veri Seti kullanılarak müşteri segmentasyonu yapılmıştır. KOLONLAR : PRICE
IMF: Inferred Model-based Fuzzer IMF is a kernel API fuzzer that leverages an automated API model inferrence techinque proposed in our paper at CCS. I
228 Dec 18, 2022
2 Mar 04, 2022
647 Jan 05, 2023
123 Dec 12, 2022
14 Nov 13, 2022
132 Sep 23, 2022
45 Dec 26, 2022
39 Nov 30, 2022
370 Dec 27, 2022
14 Oct 17, 2022
15 Sep 02, 2022
226 Dec 29, 2022
19 Dec 12, 2022
52 Jan 01, 2023
24 Jun 27, 2022
40 Dec 14, 2022
1 Nov 15, 2021
46 Dec 15, 2022
6 Dec 21, 2021
104 Sep 28, 2022