199 Repositories
Python super-fiesta Libraries
JF⚡can - Super fast port scanning & service discovery using Masscan and Nmap. Scan large networks with Masscan and use Nmap's scripting abilities to discover information about services. Generate report.
Description Killing features Perform a large-scale scans using Nmap! Allows you to use Masscan to scan targets and execute Nmap on detected ports with
Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"
BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022
LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu
Official implementation of the paper 'Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution'
DASR Paper Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution Jie Liang, Hui Zeng, and Lei Zhang. In arxiv preprint. Abs
A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution (CVPR2022)
A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution (CVPR2022) https://arxiv.org/abs/2203.09388 Jianqi Ma, Zheto
Activating More Pixels in Image Super-Resolution Transformer
HAT [Paper Link] Activating More Pixels in Image Super-Resolution Transformer Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong BibTeX @article{ch
Use the state-of-the-art m2m100 to translate large data on CPU/GPU/TPU. Super Easy!
Easy-Translate is a script for translating large text files in your machine using the M2M100 models from Facebook/Meta AI. We also privide a script fo
[CVPR 2022] Official PyTorch Implementation for "Reference-based Video Super-Resolution Using Multi-Camera Video Triplets"
Reference-based Video Super-Resolution (RefVSR) Official PyTorch Implementation of the CVPR 2022 Paper Project | arXiv | RealMCVSR Dataset This repo c
Codes for "Efficient Long-Range Attention Network for Image Super-resolution"
ELAN Codes for "Efficient Long-Range Attention Network for Image Super-resolution", arxiv link. Dependencies & Installation Please refer to the follow
Evaluation and Benchmarking of Speech Super-resolution Methods
Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e
Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.
Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli
Pytorch implementation of "ARM: Any-Time Super-Resolution Method"
ARM-Net Dependencies Python 3.6 Pytorch 1.7 Results Train Data preprocessing cd data_scripts python extract_subimages_test.py python data_augmentation
Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution
FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T
Object Database for Super Mario Galaxy 1/2.
Super Mario Galaxy Object Database Welcome to the public object database for Super Mario Galaxy and Super Mario Galaxy 2. Here, we document all object
Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.
Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima
The Begin button and menu for the Meadows operating system. The start button for UNIX/Linux.
By: Seanpm2001, Meadows Et; Al. Top README.md Read this article in a different language Sorted by: A-Z Sorting options unavailable ( af Afrikaans Afri
S2s2net - Sentinel-2 Super-Resolution Segmentation Network
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
Super-Fast-Adversarial-Training - A PyTorch Implementation code for developing super fast adversarial training
Super-Fast-Adversarial-Training This is a PyTorch Implementation code for develo
Instant-nerf-pytorch - NeRF trained SUPER FAST in pytorch
instant-nerf-pytorch This is WORK IN PROGRESS, please feel free to contribute vi
Real-CUGAN - Real Cascade U-Nets for Anime Image Super Resolution
Real Cascade U-Nets for Anime Image Super Resolution 中文 | English 🔥 Real-CUGAN
Learning Super-Features for Image Retrieval
Learning Super-Features for Image Retrieval This repository contains the code for running our FIRe model presented in our ICLR'22 paper: @inproceeding
traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation toolbox based on PyTorch.
traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to
Code for You Only Cut Once: Boosting Data Augmentation with a Single Cut
You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta
PyTorch implementation of "VRT: A Video Restoration Transformer"
VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer
Self-Supervised Deep Blind Video Super-Resolution
Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight
Revisiting RCAN: Improved Training for Image Super-Resolution Introduction Image super-resolution (SR) is a fast-moving field with novel architectures
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021)
T2Net Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021) [Paper][Code] Dependencies numpy==1.18.5 scikit_image==
Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN
Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN Introduction Image super-resolution (SR) is the process of recovering high-resoluti
Curvipy - The Python package for visualizing curves and linear transformations in a super simple way
Curvipy - The Python package for visualizing curves and linear transformations in a super simple way
Pydrawer: The Python package for visualizing curves and linear transformations in a super simple way
pydrawer 📐 The Python package for visualizing curves and linear transformations in a super simple way. ✏️ Installation Install pydrawer package with
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution
Deep Learning: Architectures & Methods Project: Deep Learning for Audio Super-Resolution Figure: Example visualization of the method and baseline as a
Detail-Preserving Transformer for Light Field Image Super-Resolution
DPT Official Pytorch implementation of the paper "Detail-Preserving Transformer for Light Field Image Super-Resolution" accepted by AAAI 2022 . Update
Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"
NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise
AirDrive lets you store unlimited files to cloud for free. Upload & download files from your personal drive at any time using its super-fast API.
AirDrive lets you store unlimited files to cloud for free. Upload & download files from your personal drive at any time using its super-fast API.
Simple BRender SDK KeyGen.
Super Simple BRender KeyGen Simple BRender SDK KeyGen. Info This is just a super simple keygen for the BRender SDK installer coded in python. All test
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
subpixel: A subpixel convnet for super resolution with Tensorflow
subpixel: A subpixel convolutional neural network implementation with Tensorflow Left: input images / Right: output images with 4x super-resolution af
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda
A High-Quality Real Time Upscaler for Anime Video
Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua
We simulate traveling back in time with a modern camera to rephotograph famous historical subjects.
[SIGGRAPH Asia 2021] Time-Travel Rephotography [Project Website] Many historical people were only ever captured by old, faded, black and white photos,
This is a super simple visualization toolbox (script) for transformer attention visualization ✌
Trans_attention_vis This is a super simple visualization toolbox (script) for transformer attention visualization ✌ 1. How to prepare your attention m
Augmentation for Single-Image-Super-Resolution
SRAugmentation Augmentation for Single-Image-Super-Resolution Implimentation CutBlur Cutout CutMix Cutup CutMixup Blend RGBPermutation Identity OneOf
Removes all archived super productivity tasks. Just run the python script.
delete-archived-sp-tasks.py Removes all archived super productivity tasks. Just run the python script. This is helpful to do a cleanup every 3-6 month
Paper Title: Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution
HKDnet Paper Title: "Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution" Email: 18186470991@163.
CSV database for chihuahua (HUAHUA) blockchain transactions
super-fiesta Shamelessly ripped components from https://github.com/hodgerpodger/staketaxcsv - Thanks for doing all the hard work. This code does only
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab
PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
Single Image Super-Resolution with EDSR, WDSR and SRGAN A Tensorflow 2.x based implementation of Enhanced Deep Residual Networks for Single Image Supe
MoCoPnet - Deformable 3D Convolution for Video Super-Resolution
Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l
Super Pix Adv - Offical implemention of Robust Superpixel-Guided Attentional Adversarial Attack (CVPR2020)
Super_Pix_Adv Offical implemention of Robust Superpixel-Guided Attentional Adver
PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'
Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll
edge-SR: Super-Resolution For The Masses
edge-SR: Super Resolution For The Masses Citation Pablo Navarrete Michelini, Yunhua Lu and Xingqun Jiang. "edge-SR: Super-Resolution For The Masses",
PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'
Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll
Code for the paper: Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution
Fusformer Code for the paper: "Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution" Plateform Python 3.8.5 + Pytor
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR.
Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.
AI Mario challenges you to clear all stage of Super Mario game.
mario-ai-challenge Challenge AI Mario to clear all stages of Super Mario. GitHub Pages Site Rules Enjoy building AI Mario. Share information. Use Goog
Super Resolution for images using deep learning.
Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase
PyTorch implementation of Super SloMo by Jiang et al.
Super-SloMo PyTorch implementation of "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" by Jiang H., Sun
A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind
An OpenAI Gym environment for Super Mario Bros
gym-super-mario-bros An OpenAI Gym environment for Super Mario Bros. & Super Mario Bros. 2 (Lost Levels) on The Nintendo Entertainment System (NES) us
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀
Using VapourSynth with super resolution models and speeding them up with TensorRT.
VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi
Using image super resolution models with vapoursynth and speeding them up with TensorRT
vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since
A super lightweight Lagrangian model for calculating millions of trajectories using ERA5 data
Easy-ERA5-Trck Easy-ERA5-Trck Galleries Install Usage Repository Structure Module Files Version iteration Easy-ERA5-Trck is a super lightweight Lagran
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution
DRSAN A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution Karam Park, Jae Woong Soh, and Nam Ik Cho Environments U
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:
Fast and Context-Aware Framework for Space-Time Video Super-Resolution (VCIP 2021)
Fast and Context-Aware Framework for Space-Time Video Super-Resolution Preparation Dependencies PyTorch 1.2.0 CUDA 10.0 DCNv2 cd model/DCNv2 bash make
Open Source Light Field Toolbox for Super-Resolution
BasicLFSR BasicLFSR is an open-source and easy-to-use Light Field (LF) image Super-Ressolution (SR) toolbox based on PyTorch, including a collection o
[NeurIPS'21 Spotlight] PyTorch code for our paper "Aligned Structured Sparsity Learning for Efficient Image Super-Resolution"
ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)
Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress
A command line tool that creates a super timeline from SentinelOne's Deep Visibility data
S1SuperTimeline A command line tool that creates a super timeline from SentinelOne's Deep Visibility data What does it do? The script accepts a S1QL q
Pmapper is a super-resolution and deconvolution toolkit for python 3.6+
pmapper pmapper is a super-resolution and deconvolution toolkit for python 3.6+. PMAP stands for Poisson Maximum A-Posteriori, a highly flexible and a
Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"
RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain
AdaDM: Enabling Normalization for Image Super-Resolution
AdaDM AdaDM: Enabling Normalization for Image Super-Resolution. You can apply BN, LN or GN in SR networks with our AdaDM. Pretrained models (EDSR*/RDN
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"
NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
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
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
SinGAN Project | Arxiv | CVF | Supplementary materials | Talk (ICCV`19) Official pytorch implementation of the paper: "SinGAN: Learning a Generative M
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020
UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx
A super easy, but really really bad DBMS
Dumb DB Are you looking for a reliable database management system? Then you've come to the wrong place. This is a very small database management syste
GUI for TOAD-GAN, a PCG-ML algorithm for Token-based Super Mario Bros. Levels.
If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene
Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"
RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain
Super simple bar charts for django admin list views visualizing the number of objects based on date_hierarchy using Chart.js.
Super simple bar charts for django admin list views visualizing the number of objects based on date_hierarchy using Chart.js.
Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]
Image super-resolution through deep learning
srez Image super-resolution through deep learning. This project uses deep learning to upscale 16x16 images by a 4x factor. The resulting 64x64 images
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Official Python implementation of the 'Sparse deconvolution'-v0.3.0
Sparse deconvolution Python v0.3.0 Official Python implementation of the 'Sparse deconvolution', and the CPU (NumPy) and GPU (CuPy) calculation backen
[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution
TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel This repository is the official PyTorch implementation of BSRDM w
The project covers common metrics for super-resolution performance evaluation.
Super-Resolution Performance Evaluation Code The project covers common metrics for super-resolution performance evaluation. Metrics support The script
PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.
English | 简体中文 PaddleGAN PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and s
Dataset and Code for ICCV 2021 paper "Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme"
Dataset and Code for RealVSR Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme Xi Yang, Wangmeng Xiang,
Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective
Unofficial pytorch implementation of the paper "Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective"
Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
Deep-Rep-MFIR Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising Publication: Deep Reparametrization of M
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).
RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Unofficial pytorch implementation of the paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution"
DFSA Unofficial pytorch implementation of the ICCV 2021 paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution" (p
PyTorch implementation of a Real-ESRGAN model trained on custom dataset
Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥