Python Pytorch-image-classification Resources

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

A Python Library for Document Layout Understanding

Official implementation of GOCor This is the official implementation of our paper : GOCor: Bringing Globally Optimized Correspondence Volumes into You

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

Hyperbolic Graph Convolutional Auto-Encoders Accepted to CVPR2021 🎉 Official PyTorch code of Unsupervised Hyperbolic Representation Learning via Mess

Invertible Image Signal Processing This repository includes official codes for "Invertible Image Signal Processing (CVPR2021)". Figure: Our framework

CoReNet CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image. It produces coherent reconstructions, where all objec

Chinese mandarin text to speech based on Fastspeech2 and Unet This is a modification and adpation of fastspeech2 to mandrin(普通话）. Many modifications t

PointDSC repository PyTorch implementation of PointDSC for CVPR'2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency",

Ratio Image Based Rendering for Deep Single-Image Portrait Relighting [Project Page] This is part of the Deep Portrait Relighting project. If you find

AOT-GAN for High-Resolution Image Inpainting Arxiv Paper | AOT-GAN: Aggregated Contextual Transformations for High-Resolution Image Inpainting Yanhong

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Demo video: CVPR 2021 Oral: Single Channel Manipulation: Localized or attribu

Implementation of various Vision Transformers I found interesting

Knowledge Distillation for BERT Unsupervised Domain Adaptation Official PyTorch implementation | Paper Abstract A pre-trained language model, BERT, ha

Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo

DNA This repository provides the code of our paper: Blockwisely Supervised Neural Architecture Search with Knowledge Distillation. Illustration of DNA

TRIQ Implementation TF-Keras implementation of TRIQ as described in Transformer for Image Quality Assessment. Installation Clone this repository. Inst

Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Improving Unsupervised Image Clustering With Robust Learning This repo is the PyTorch codes for "Improving Unsupervised Image Clustering With Robust L

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and folium

A collection of loss functions for medical image segmentation

SimDeblur (Simple Deblurring) is an open source framework for image and video deblurring toolbox based on PyTorch, which contains most deep-learning based state-of-the-art deblurring algorithms. It is easy to implement your own image or video deblurring or other restoration algorithms.

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

wsss-analysis The code of: A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains, arXiv pre-print 2019 paper.

[NEW!] Check out our latest work involution accepted to CVPR'21 that introduces a new neural operator, other than convolution and self-attention. PyTo

An Image is Worth 16x16 Words, What is a Video Worth? paper Official PyTorch Implementation Gilad Sharir, Asaf Noy, Lihi Zelnik-Manor DAMO Academy, Al

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A

Domain Generalization for Medical Imaging Classification with Linear Dependency Regularization The code release of paper 'Domain Generalization for Me

SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a

PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic

FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt

RobustNet (CVPR 2021 Oral): Official Project Webpage Codes and pretrained models will be released soon. This repository provides the official PyTorch

ArtFlow Official PyTorch implementation of the paper: ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows Jie An*, Siyu Huang*, Yibing

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

Need Help? If you’re new to StyleGAN2-ADA and looking to get started, please check out this video series from a course Lia Coleman and I taught in Oct

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

leaf-audio-pytorch Pytorch port of Google Research's LEAF Audio paper published at ICLR 2021. This port is not completely finished, but the Leaf() fro

Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation This paper has been accepted and early accessed

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep

512x512 flowers after 12 hours of training, 1 gpu 256x256 flowers after 12 hours of training, 1 gpu Pizza 'Lightweight' GAN Implementation of 'lightwe

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens

Neural Network CUDA Example Several simple examples for neural network toolkits (PyTorch, TensorFlow, etc.) calling custom CUDA operators. We provide

OTA: Optimal Transport Assignment for Object Detection This project provides an implementation for our CVPR2021 paper "OTA: Optimal Transport Assignme

Neural Style Transfer Transition Video Processing By Brycen Westgarth and Tristan Jogminas Description This code extends the neural style transfer ima

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

iterative-stratification iterative-stratification is a project that provides scikit-learn compatible cross validators with stratification for multilab

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

micrograd A tiny Autograd engine (with a bite! :)). Implements backpropagation (reverse-mode autodiff) over a dynamically built DAG and a small neural

Tez: a simple pytorch trainer NOTE: Currently, we are not accepting any pull requests! All PRs will be closed. If you want a feature or something does

Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l

For something in between a pytorch and a karpathy/micrograd This may not be the best deep learning framework, but it is a deep learning framework. Due

Tensor Sensor See article Clarifying exceptions and visualizing tensor operations in deep learning code. One of the biggest challenges when writing co

Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random

Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these

(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently

PyTorch Scatter Documentation This package consists of a small extension library of highly optimized sparse update (scatter and segment) operations fo

Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i

EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor

torch-optimizer torch-optimizer -- collection of optimizers for PyTorch compatible with optim module. Simple example import torch_optimizer as optim

Keras style model.summary() in PyTorch Keras has a neat API to view the visualization of the model which is very helpful while debugging your network.

Pretrained models for Pytorch (Work in progress) The goal of this repo is: to help to reproduce research papers results (transfer learning setups for

Rembg is a tool to remove images background.

ipyexperiments jupyter/ipython experiment containers and utils for profiling and reclaiming GPU and general RAM, and detecting memory leaks. About Thi

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray What is Analytics Zoo? Analytics Zo

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti