4423 Repositories
Python deep-image-search Libraries
[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep
Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
512x512 flowers after 12 hours of training, 1 gpu 256x256 flowers after 12 hours of training, 1 gpu Pizza 'Lightweight' GAN Implementation of 'lightwe
Implementation of the Swin Transformer in PyTorch.
Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,
Implementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu
Enabling easy statistical significance testing for deep neural networks.
deep-significance: Easy and Better Significance Testing for Deep Neural Networks Contents ⁉️ Why 📥 Installation 🔖 Examples Intermezzo: Almost Stocha
Polaris is a Face recognition attendance system .
Support Me 🚀 About Polaris 📄 Polaris is a system based on facial recognition with a futuristic GUI design, Can easily find people informations store
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on
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
This code extends the neural style transfer image processing technique to video by generating smooth transitions between several reference style images
Neural Style Transfer Transition Video Processing By Brycen Westgarth and Tristan Jogminas Description This code extends the neural style transfer ima
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
Gaussian processes in TensorFlow
Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow
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
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
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
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
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
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.
Rembg is a tool to remove images background.
Rembg is a tool to remove images background.
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
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
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 (
Search and download Copernicus Sentinel satellite images
sentinelsat Sentinelsat makes searching, downloading and retrieving the metadata of Sentinel satellite images from the Copernicus Open Access Hub easy
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 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
Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)
Diverse Image Captioning with Context-Object Split Latent Spaces This repository is the PyTorch implementation of the paper: Diverse Image Captioning
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
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
BossNAS This repository contains PyTorch evaluation code, retraining code and pretrained models of our paper: BossNAS: Exploring Hybrid CNN-transforme
Conversion of Image, video, text into ASCII format
asciju Python package that converts image to ascii Free software: MIT license
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
Code for CVPR 2021 paper: Anchor-Free Person Search
Introduction This is the implementationn for Anchor-Free Person Search in CVPR2021 License This project is released under the Apache 2.0 license. Inst
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
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
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji
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
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched or copy-pasted. ocrmypdf # it's a scriptable c
Open Source research tool to search, browse, analyze and explore large document collections by Semantic Search Engine and Open Source Text Mining & Text Analytics platform (Integrates ETL for document processing, OCR for images & PDF, named entity recognition for persons, organizations & locations, metadata management by thesaurus & ontologies, search user interface & search apps for fulltext search, faceted search & knowledge graph)
Open Semantic Search https://opensemanticsearch.org Integrated search server, ETL framework for document processing (crawling, text extraction, text a
ScanTailor Advanced is the version that merges the features of the ScanTailor Featured and ScanTailor Enhanced versions, brings new ones and fixes.
ScanTailor Advanced The ScanTailor version that merges the features of the ScanTailor Featured and ScanTailor Enhanced versions, brings new ones and f
document image degradation
ocrodeg The ocrodeg package is a small Python library implementing document image degradation for data augmentation for handwriting recognition and OC
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
A selectional auto-encoder approach for document image binarization
The code of this repository was used for the following publication. If you find this code useful please cite our paper: @article{Gallego2019, title =
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
Geometric Augmentation for Text Image
Text Image Augmentation A general geometric augmentation tool for text images in the CVPR 2020 paper "Learn to Augment: Joint Data Augmentation and Ne
PAGE XML format collection for document image page content and more
PAGE-XML PAGE XML format collection for document image page content and more For an introduction, please see the following publication: http://www.pri
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
OCR system for Arabic language that converts images of typed text to machine-encoded text.
Arabic OCR OCR system for Arabic language that converts images of typed text to machine-encoded text. The system currently supports only letters (29 l
Solution for Problem 1 by team codesquad for AIDL 2020. Uses ML Kit for OCR and OpenCV for image processing
CodeSquad PS1 Solution for Problem Statement 1 for AIDL 2020 conducted by @unifynd technologies. Problem Given images of bills/invoices, the task was
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
A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.
Attention-based OCR Visual attention-based OCR model for image recognition with additional tools for creating TFRecords datasets and exporting the tra
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
The first open-source library that detects the font of a text in a image.
Typefont Typefont is an experimental library that detects the font of a text in a image. Usage Import the main function and invoke it like in the foll
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 |
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
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
Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)
Detecting Text in Natural Image with Connectionist Text Proposal Network The codes are used for implementing CTPN for scene text detection, described
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
Scene text detection and recognition based on Extremal Region(ER)
Scene text recognition A real-time scene text recognition algorithm. Our system is able to recognize text in unconstrain background. This algorithm is
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
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
SEE: Towards Semi-Supervised End-to-End Scene Text Recognition Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text
This is a c++ project deploying a deep scene text reading pipeline with tensorflow. It reads text from natural scene images. It uses frozen tensorflow graphs. The detector detect scene text locations. The recognizer reads word from each detected bounding box.
DeepSceneTextReader This is a c++ project deploying a deep scene text reading pipeline. It reads text from natural scene images. Prerequsites The proj
This project modify tensorflow object detection api code to predict oriented bounding boxes. It can be used for scene text detection.
This is an oriented object detector based on tensorflow object detection API. Most of the code is not changed except for those related to the need of
caffe re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection
R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection Abstract This is a caffe re-implementation of R2CNN: Rotational Region CNN fo
Pytorch implementation of PSEnet with Pyramid Attention Network as feature extractor
Scene Text-Spotting based on PSEnet+CRNN Pytorch implementation of an end to end Text-Spotter with a PSEnet text detector and CRNN text recognizer. We
CUTIE (TensorFlow implementation of Convolutional Universal Text Information Extractor)
CUTIE TensorFlow implementation of the paper "CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor." Xiaohu