4624 Repositories
Python deep-forecast-pytorch Libraries
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021)
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021, official Pytorch implementatio
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis
Using approximate bayesian posteriors in deep nets for active learning
Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components
Functional tensors for probabilistic programming
Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.
Gaussian processes in TensorFlow
Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow
A highly efficient and modular implementation of Gaussian Processes in PyTorch
GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
Probabilistic reasoning and statistical analysis in TensorFlow
TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl
A simplified framework and utilities for PyTorch
Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
micrograd A tiny Autograd engine (with a bite! :)). Implements backpropagation (reverse-mode autodiff) over a dynamically built DAG and a small neural
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.
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
High-level batteries-included neural network training library for Pytorch
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
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l
You like pytorch? You like micrograd? You love tinygrad! ❤️
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
The goal of this library is to generate more helpful exception messages for numpy/pytorch matrix algebra expressions.
Tensor Sensor See article Clarifying exceptions and visualizing tensor operations in deep learning code. One of the biggest challenges when writing co
An implementation of Performer, a linear attention-based transformer, in Pytorch
Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random
PyTorch extensions for fast R&D prototyping and Kaggle farming
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
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.
higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
(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
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently
PyTorch Extension Library of Optimized Scatter Operations
PyTorch Scatter Documentation This package consists of a small extension library of highly optimized sparse update (scatter and segment) operations fo
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench
Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i
A PyTorch implementation of EfficientNet
EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor
torch-optimizer -- collection of optimizers for Pytorch
torch-optimizer torch-optimizer -- collection of optimizers for PyTorch compatible with optim module. Simple example import torch_optimizer as optim
Model summary in PyTorch similar to `model.summary()` in Keras
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 ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Pretrained models for Pytorch (Work in progress) The goal of this repo is: to help to reproduce research papers results (transfer learning setups for
jupyter/ipython experiment containers for GPU and general RAM re-use
ipyexperiments jupyter/ipython experiment containers and utils for profiling and reclaiming GPU and general RAM, and detecting memory leaks. About Thi
Library for faster pinned CPU - GPU transfer in Pytorch
SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases.
Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
A high performance and generic framework for distributed DNN training
BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith
a distributed deep learning platform
Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis
PyTorch extensions for high performance and large scale training.
Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray What is Analytics Zoo? Analytics Zo
Microsoft Machine Learning for Apache Spark
Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas
Distributed Deep learning with Keras & Spark
Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc
BigDL: Distributed Deep Learning Framework for Apache Spark
BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear
Time series forecasting with PyTorch
Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time
Probabilistic time series modeling in Python
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
PyTorch reimplementation of minimal-hand (CVPR2020)
Minimal Hand Pytorch Unofficial PyTorch reimplementation of minimal-hand (CVPR2020). you can also find in youtube or bilibili bare hand youtube or bil
PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
Contrast to Divide: self-supervised pre-training for learning with noisy labels This is an official implementation of "Contrast to Divide: self-superv
Deep Implicit Moving Least-Squares Functions for 3D Reconstruction
DeepMLS: Deep Implicit Moving Least-Squares Functions for 3D Reconstruction This repository contains the implementation of the paper: Deep Implicit Mo
A pytorch reprelication of the model-based reinforcement learning algorithm MBPO
Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo
An implementation of Geoffrey Hinton's paper "How to represent part-whole hierarchies in a neural network" in Pytorch.
GLOM An implementation of Geoffrey Hinton's paper "How to represent part-whole hierarchies in a neural network" for MNIST Dataset. To understand this
Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks
PWLQ Updates 2020/07/16 - We are working on getting permission from our institution to release our source code. We will release it once we are granted
Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"
Hold me tight! Influence of discriminative features on deep network boundaries This is the source code to reproduce the experiments of the NeurIPS 202
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones
HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re
Spatial Intention Maps for Multi-Agent Mobile Manipulation (ICRA 2021)
spatial-intention-maps This code release accompanies the following paper: Spatial Intention Maps for Multi-Agent Mobile Manipulation Jimmy Wu, Xingyua
This is an implementation of PIFuhd based on Pytorch
Open-PIFuhd This is a unofficial implementation of PIFuhd PIFuHD: Multi-Level Pixel-Aligned Implicit Function forHigh-Resolution 3D Human Digitization
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept
Repository to hold code for the cap-bot varient that is being presented at the SIIC Defence Hackathon 2021.
capbot-siic Repository to hold code for the cap-bot varient that is being presented at the SIIC Defence Hackathon 2021. Problem Inspiration A plethora
Official code for the paper: Deep Graph Matching under Quadratic Constraint (CVPR 2021)
QC-DGM This is the official PyTorch implementation and models for our CVPR 2021 paper: Deep Graph Matching under Quadratic Constraint. It also contain
We have implemented shaDow-GNN as a general and powerful pipeline for graph representation learning. For more details, please find our paper titled Deep Graph Neural Networks with Shallow Subgraph Samplers, available on arXiv (https//arxiv.org/abs/2012.01380).
Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.
Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
SmallPebble Project status: experimental, unstable. SmallPebble is a minimal/toy automatic differentiation/deep learning library written from scratch
Pytorch Lightning Distributed Accelerators using Ray
Distributed PyTorch Lightning Training on Ray This library adds new PyTorch Lightning plugins for distributed training using the Ray distributed compu
One Metrics Library to Rule Them All!
onemetric Installation Install onemetric from PyPI (recommended): pip install onemetric Install onemetric from the GitHub source: git clone https://gi
[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias
Counterfactual VQA (CF-VQA) This repository is the Pytorch implementation of our paper "Counterfactual VQA: A Cause-Effect Look at Language Bias" in C
Text recognition (optical character recognition) with deep learning methods.
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis | paper | training and evaluation data | failure cases and cle
Generate text images for training deep learning ocr model
New version release:https://github.com/oh-my-ocr/text_renderer Text Renderer Generate text images for training deep learning OCR model (e.g. CRNN). Su
A collection of resources (including the papers and datasets) of OCR (Optical Character Recognition).
OCR Resources This repository contains a collection of resources (including the papers and datasets) of OCR (Optical Character Recognition). Contents
A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.
awesome-deep-text-detection-recognition A curated list of awesome deep learning based papers on text detection and recognition. Text Detection Papers
A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約
Scene Text Localization & Recognition Resources Read this institute-wise: English, 简体中文. Read this year-wise: English, 简体中文. Tags: [STL] (Scene Text L
A machine learning software for extracting information from scholarly documents
GROBID GROBID documentation Visit the GROBID documentation for more detailed information. Summary GROBID (or Grobid, but not GroBid nor GroBiD) means
a Deep Learning Framework for Text
DeLFT DeLFT (Deep Learning Framework for Text) is a Keras and TensorFlow framework for text processing, focusing on sequence labelling (e.g. named ent
Repository collecting all the submodules for the new PyTorch-based OCR System.
OCRopus3 is being replaced by OCRopus4, which is a rewrite using PyTorch 1.7; release should be soonish. Please check github.com/tmbdev/ocropus for up
Pure Javascript OCR for more than 100 Languages 📖🎉🖥
Version 2 is now available and under development in the master branch, read a story about v2: Why I refactor tesseract.js v2? Check the support/1.x br
第一届西安交通大学人工智能实践大赛(2018AI实践大赛--图片文字识别)第一名;仅采用densenet识别图中文字
OCR 第一届西安交通大学人工智能实践大赛(2018AI实践大赛--图片文字识别)冠军 模型结果 该比赛计算每一个条目的f1score,取所有条目的平均,具体计算方式在这里。这里的计算方式不对一句话里的相同文字重复计算,故f1score比提交的最终结果低: - train val f1score 0
A pure pytorch implemented ocr project including text detection and recognition
ocr.pytorch A pure pytorch implemented ocr project. Text detection is based CTPN and text recognition is based CRNN. More detection and recognition me
[python3.6] 运用tf实现自然场景文字检测,keras/pytorch实现ctpn+crnn+ctc实现不定长场景文字OCR识别
本文基于tensorflow、keras/pytorch实现对自然场景的文字检测及端到端的OCR中文文字识别 update20190706 为解决本项目中对数学公式预测的准确性,做了其他的改进和尝试,效果还不错,https://github.com/xiaofengShi/Image2Katex 希
Textboxes : Image Text Detection Model : python package (tensorflow)
shinTB Abstract A python package for use Textboxes : Image Text Detection Model implemented by tensorflow, cv2 Textboxes Paper Review in Korean (My Bl
TextBoxes: A Fast Text Detector with a Single Deep Neural Network https://github.com/MhLiao/TextBoxes 基于SSD改进的文本检测算法,textBoxes_note记录了之前整理的笔记。
TextBoxes: A Fast Text Detector with a Single Deep Neural Network Introduction This paper presents an end-to-end trainable fast scene text detector, n
Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector
CRAFT: Character-Region Awareness For Text detection Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector | Paper |
CRAFT-Pyotorch:Character Region Awareness for Text Detection Reimplementation for Pytorch
CRAFT-Reimplementation Note:If you have any problems, please comment. Or you can join us weChat group. The QR code will update in issues #49 . Reimple
Official implementation of Character Region Awareness for Text Detection (CRAFT)
CRAFT: Character-Region Awareness For Text detection Official Pytorch implementation of CRAFT text detector | Paper | Pretrained Model | Supplementary
Tool which allow you to detect and translate text.
Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr
PyTorch Re-Implementation of EAST: An Efficient and Accurate Scene Text Detector
Description This is a PyTorch Re-Implementation of EAST: An Efficient and Accurate Scene Text Detector. Only RBOX part is implemented. Using dice loss
This is a pytorch re-implementation of EAST: An Efficient and Accurate Scene Text Detector.
EAST: An Efficient and Accurate Scene Text Detector Description: This version will be updated soon, please pay attention to this work. The motivation
AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST, and the significant improvement was also made, which make long text predictions more accurate.https://github.com/huoyijie/raspberrypi-car
AdvancedEAST AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST:An Efficient and Accurate Scene Text Dete
A tensorflow implementation of EAST text detector
EAST: An Efficient and Accurate Scene Text Detector Introduction This is a tensorflow re-implementation of EAST: An Efficient and Accurate Scene Text
keras复现场景文本检测网络CPTN: 《Detecting Text in Natural Image with Connectionist Text Proposal Network》;欢迎试用,关注,并反馈问题...
keras-ctpn [TOC] 说明 预测 训练 例子 4.1 ICDAR2015 4.1.1 带侧边细化 4.1.2 不带带侧边细化 4.1.3 做数据增广-水平翻转 4.2 ICDAR2017 4.3 其它数据集 toDoList 总结 说明 本工程是keras实现的CPTN: Detecti
TensorFlow Implementation of FOTS, Fast Oriented Text Spotting with a Unified Network.
FOTS: Fast Oriented Text Spotting with a Unified Network I am still working on this repo. updates and detailed instructions are coming soon! Table of
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection (TIP 2019)
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection Introduction The code and trained models of: TextField: Learning A Deep
This repository provides train&test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.
SCUT-CTW1500 Datasets We have updated annotations for both train and test set. Train: 1000 images [images][annos] Additional point annotation for each
A PyTorch implementation of ECCV2018 Paper: TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes
TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes A PyTorch implement of TextSnake: A Flexible Representation for Detecting
Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition
STN-OCR: A single Neural Network for Text Detection and Text Recognition This repository contains the code for the paper: STN-OCR: A single Neural Net