563 Repositories
Python high-resolution Libraries
CertPy is a high level toolkit for generating x509 (e.g. SSL/TLS/HTTPS) certificates in Python.
CertPy CertPy is a high level toolkit for generating x509 (e.g. SSL/TLS/HTTPS) certificates in Python. Certificate “profiles” are implemented as Pytho
Official repository for "Restormer: Efficient Transformer for High-Resolution Image Restoration". SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,
Unsupervised clustering of high content screen samples
Microscopium Unsupervised clustering and dataset exploration for high content screens. See microscopium in action Public dataset BBBC021 from the Broa
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.
Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.
Taichi is a parallel programming language for high-performance numerical computations.
Taichi is a parallel programming language for high-performance numerical computations.
VGGFace2-HQ - A high resolution face dataset for face editing purpose
The first open source high resolution dataset for face swapping!!! A high resolution version of VGGFace2 for academic face editing purpose
You Can download any video/image in all social medias very easy and High Speed.
All-Downloader You Can download any video/image in all social medias very easy and High Speed. also you can easily download videos from web browsers s
A Python package for generating concise, high-quality summaries of a probability distribution
GoodPoints A Python package for generating concise, high-quality summaries of a probability distribution GoodPoints is a collection of tools for compr
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation
Official repository for "Restormer: Efficient Transformer for High-Resolution Image Restoration". SOTA results for single-image motion deblurring, image deraining, image denoising (synthetic and real data), and dual-pixel defocus deblurring.
Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,
Collection of scripts for making high quality beautiful math-related posters.
Poster Collection of scripts for making high quality beautiful math-related posters. The poster can have as large printing size as 3x2 square feet wit
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,
Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation
CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c
Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics
Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)
GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral) [Project] [Paper] [Demo] [Related Work: A2RL (for Auto Image Cropping)] [C
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
A high performance implementation of HDBSCAN clustering.
HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates
Implements (high-dimenstional) clustering algorithm
Description Implements (high-dimenstional) clustering algorithm described in https://arxiv.org/pdf/1804.02624.pdf Dependencies python3 pytorch (=0.4)
Subpopulation detection in high-dimensional single-cell data
PhenoGraph for Python3 PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph ("network") repr
High performance distributed framework for training deep learning recommendation models based on PyTorch.
High performance distributed framework for training deep learning recommendation models based on PyTorch.
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control Official implementation of: Cooperative multi-agent reinfor
Pansharpening by convolutional neural networks in the full resolution framework
Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
High-resolution networks and Segmentation Transformer for Semantic Segmentation
High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v
Full Resolution Residual Networks for Semantic Image Segmentation
Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018
ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a
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
MVP monorepo to rapidly develop scalable, reliable, high-quality components for Amazon Linux instance configuration management
Ansible Amazon Base Repository Ansible Amazon Base Repository About Setting Up Ansible Environment Configuring Python VENV and Ansible Editor Configur
TensorLight - A high-level framework for TensorFlow
TensorLight is a high-level framework for TensorFlow-based machine intelligence applications. It reduces boilerplate code and enables advanced feature
[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
A high-performance DNS stub resolver for bulk lookups and reconnaissance (subdomain enumeration)
MassDNS A high-performance DNS stub resolver MassDNS is a simple high-performance DNS stub resolver targeting those who seek to resolve a massive amou
Torch-based tool for quantizing high-dimensional vectors using additive codebooks
Trainable multi-codebook quantization This repository implements a utility for use with PyTorch, and ideally GPUs, for training an efficient quantizer
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
PyScaffold is a project generator for bootstrapping high quality Python packages
PyScaffold is a project generator for bootstrapping high quality Python packages, ready to be shared on PyPI and installable via pip. It is easy to use and encourages the adoption of the best tools and practices of the Python ecosystem, helping you and your team to stay sane, happy and productive. The best part? It is stable and has been used by thousands of developers for over half a decade!
ObjTables: Tools for creating and reusing high-quality spreadsheets
ObjTables: Tools for creating and reusing high-quality spreadsheets ObjTables is a toolkit which makes it easy to use spreadsheets (e.g., XLSX workboo
Code for "Long Range Probabilistic Forecasting in Time-Series using High Order Statistics"
Long Range Probabilistic Forecasting in Time-Series using High Order Statistics This is the code produced as part of the paper Long Range Probabilisti
A high-level framework for building GitHub applications in Python.
A high-level framework for building GitHub applications in Python. Core Features Async Proper ratelimit handling Handles interactions for you (
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,
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model
RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos
RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti
Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021
LPTN Paper | Supplementary Material | Poster High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network Ji
Taming Transformers for High-Resolution Image Synthesis
Taming Transformers for High-Resolution Image Synthesis CVPR 2021 (Oral) Taming Transformers for High-Resolution Image Synthesis Patrick Esser*, Robin
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
ecoglib: visualization and statistics for high density microecog signals
ecoglib: visualization and statistics for high density microecog signals This library contains high-level analysis tools for "topos" and "chronos" asp
A python screen recorder for low-end computers, provides high quality video output.
RecorderX - v1.0 A screen recorder made in Python with the help of OpenCv, it has ability to record your screen in high quality. No matter what your P
cLoops2: full stack analysis tool for chromatin interactions
cLoops2: full stack analysis tool for chromatin interactions Introduction cLoops2 is an extension of our previous work, cLoops. From loop-calling base
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
Real-Time High-Resolution Background Matting
Real-Time High-Resolution Background Matting Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires captur
Benchmark library for high-dimensional HPO of black-box models based on Weighted Lasso regression
LassoBench LassoBench is a library for high-dimensional hyperparameter optimization benchmarks based on Weighted Lasso regression. Note: LassoBench is
[CVPR 2021] NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning
NormalFusion: Real-Time Acquisition of Surface Normals for High-Resolution RGB-D Scanning Project Page | Paper | Supplemental material #1 | Supplement
Q-Tracker is originally a High School Project created by Admins of Cirus Lab.
Q-Tracker is originally a High School Project created by Admins of Cirus Lab. It's completly coded in python along with mysql.(Tkinter For GUI)
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
A modular, research-friendly framework for high-performance and inference of sequence models at many scales
T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of
Framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample resolution
Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re
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
Neural Nano-Optics for High-quality Thin Lens Imaging
Neural Nano-Optics for High-quality Thin Lens Imaging Project Page | Paper | Data Ethan Tseng, Shane Colburn, James Whitehead, Luocheng Huang, Seung-H
The fastest way to copy to (not from) high speed flash storage.
FastestCopy The fastest way to copy to (not from) high speed flash storage. This is about 3-6x faster than file copy on explorer.exe to usb flash driv
Implementation for HFGI: High-Fidelity GAN Inversion for Image Attribute Editing
HFGI: High-Fidelity GAN Inversion for Image Attribute Editing High-Fidelity GAN Inversion for Image Attribute Editing Update: We released the inferenc
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train
🔥 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 🔥
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
[peer review] An Arbitrary Scale Super-Resolution Approach for 3D MR Images using Implicit Neural Representation
ArSSR This repository is the pytorch implementation of our manuscript "An Arbitrary Scale Super-Resolution Approach for 3-Dimensional Magnetic Resonan
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
Unofficial pytorch implementation of the paper "Context Reasoning Attention Network for Image Super-Resolution (ICCV 2021)"
CRAN Unofficial pytorch implementation of the paper "Context Reasoning Attention Network for Image Super-Resolution (ICCV 2021)" This code doesn't exa
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
Some problems of SSLC ( High School ) before outputs and after outputs
Some problems of SSLC ( High School ) before outputs and after outputs 1] A Python program and its output (output1) while running the program is given
Implementation for the paper 'YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs'
YOLO-ReT This is the original implementation of the paper: YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs. Prakhar Ganesh, Ya
Asterisk is a framework to generate high-quality training datasets at scale
Asterisk is a framework to generate high-quality training datasets at scale
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
High-fidelity performance metrics for generative models in PyTorch
High-fidelity performance metrics for generative models in PyTorch
[SIGGRAPH Asia 2021] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning.
DeepVecFont This is the homepage for "DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning". Yizhi Wang and Zhouhui Lian. WI
[SIGGRAPH Asia 2021] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning.
DeepVecFont This is the homepage for "DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning". Yizhi Wang and Zhouhui Lian. WI
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr
API with high performance to create a simple blog and Auth using OAuth2 ⛏
DogeAPI API with high performance built with FastAPI & SQLAlchemy, help to improve connection with your Backend Side to create a simple blog and Cruds
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr
Code base for the paper "Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation"
This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati
Using machine learning to predict and analyze high and low reader engagement for New York Times articles posted to Facebook.
How The New York Times can increase Engagement on Facebook Using machine learning to understand characteristics of news content that garners "high" Fa
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
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
Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN)
Flickr-Faces-HQ Dataset (FFHQ) Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative
Seaborn-image is a Python image visualization library based on matplotlib and provides a high-level API to draw attractive and informative images quickly and effectively.
seaborn-image: image data visualization Description Seaborn-image is a Python image visualization library based on matplotlib and provides a high-leve
A high-level Python library for Quantum Natural Language Processing
lambeq About lambeq is a toolkit for quantum natural language processing (QNLP). Documentation: https://cqcl.github.io/lambeq/ User support: lambeq-su
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation
PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation
Scalable implementation of Lee / Mykland (2012) and Ait-Sahalia / Jacod (2012) Jump tests for noisy high frequency data
JumpDetectR Name of QuantLet : JumpDetectR Published in : 'To be published as "Jump dynamics in high frequency crypto markets"' Description : 'Scala