Python Super Resources

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

BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

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) https://arxiv.org/abs/2203.09388 Jianqi Ma, Zheto

HAT [Paper Link] Activating More Pixels in Image Super-Resolution Transformer Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong BibTeX @article{ch

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

Reference-based Video Super-Resolution (RefVSR) Official PyTorch Implementation of the CVPR 2022 Paper Project | arXiv | RealMCVSR Dataset This repo c

ELAN Codes for "Efficient Long-Range Attention Network for Image Super-resolution", arxiv link. Dependencies & Installation Please refer to the follow

Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

ARM-Net Dependencies Python 3.6 Pytorch 1.7 Results Train Data preprocessing cd data_scripts python extract_subimages_test.py python data_augmentation

FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T

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

Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima

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 Getting started Install

Super-Fast-Adversarial-Training This is a PyTorch Implementation code for develo

instant-nerf-pytorch This is WORK IN PROGRESS, please feel free to contribute vi

Real Cascade U-Nets for Anime Image Super Resolution 中文 | English 🔥 Real-CUGAN

Learning Super-Features for Image Retrieval This repository contains the code for running our FIRe model presented in our ICLR'22 paper: @inproceeding

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta

VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer

Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base

Revisiting RCAN: Improved Training for Image Super-Resolution Introduction Image super-resolution (SR) is a fast-moving field with novel architectures

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 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

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 Figure: Example visualization of the method and baseline as a

DPT Official Pytorch implementation of the paper "Detail-Preserving Transformer for Light Field Image Super-Resolution" accepted by AAAI 2022 . Update

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.

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

subpixel: A subpixel convolutional neural network implementation with Tensorflow Left: input images / Right: output images with 4x super-resolution af

100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

[SIGGRAPH Asia 2021] Time-Travel Rephotography [Project Website] Many historical people were only ever captured by old, faded, black and white photos,

Trans_attention_vis This is a super simple visualization toolbox (script) for transformer attention visualization ✌ 1. How to prepare your attention m

SRAugmentation Augmentation for Single-Image-Super-Resolution Implimentation CutBlur Cutout CutMix Cutup CutMixup Blend RGBPermutation Identity OneOf

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

HKDnet Paper Title: "Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution" Email: 18186470991@163.

super-fiesta Shamelessly ripped components from https://github.com/hodgerpodger/staketaxcsv - Thanks for doing all the hard work. This code does only

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

Single Image Super-Resolution with EDSR, WDSR and SRGAN A Tensorflow 2.x based implementation of Enhanced Deep Residual Networks for Single Image Supe

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

Super_Pix_Adv Offical implemention of Robust Superpixel-Guided Attentional Adver

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 Citation Pablo Navarrete Michelini, Yunhua Lu and Xingqun Jiang. "edge-SR: Super-Resolution For The Masses",

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

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🔥

Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.

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

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

Super-SloMo PyTorch implementation of "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" by Jiang H., Sun

A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind

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

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since

Easy-ERA5-Trck Easy-ERA5-Trck Galleries Install Usage Repository Structure Module Files Version iteration Easy-ERA5-Trck is a super lightweight Lagran

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 YouTube | arXiv Prerequisites Kaolin is available here:

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

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

ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)

Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress

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 pmapper is a super-resolution and deconvolution toolkit for python 3.6+. PMAP stands for Poisson Maximum A-Posteriori, a highly flexible and a

RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain

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

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

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

SinGAN Project | Arxiv | CVF | Supplementary materials | Talk (ICCV`19) Official pytorch implementation of the paper: "SinGAN: Learning a Generative M

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

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

If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene

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.

Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]

srez Image super-resolution through deep learning. This project uses deep learning to upscale 16x16 images by a 4x factor. The resulting 64x64 images

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

Sparse deconvolution Python v0.3.0 Official Python implementation of the 'Sparse deconvolution', and the CPU (NumPy) and GPU (CuPy) calculation backen

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 This repository is the official PyTorch implementation of BSRDM w

Super-Resolution Performance Evaluation Code The project covers common metrics for super-resolution performance evaluation. Metrics support The script

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 RealVSR Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme Xi Yang, Wangmeng Xiang,

Unofficial pytorch implementation of the paper "Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective"

Deep-Rep-MFIR Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising Publication: Deep Reparametrization of M

Super Simple Similarities Service

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

DFSA Unofficial pytorch implementation of the ICCV 2021 paper "Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution" (p

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 🔥