2652 Repositories
Python anime-character-data Libraries
Provides OCR (Optical Character Recognition) services through web applications
OCR4all As suggested by the name one of the main goals of OCR4all is to allow basically any given user to independently perform OCR on a wide variety
make a better chinese character recognition OCR than tesseract
deep ocr See README_en.md for English installation documentation. 只在ubuntu下面测试通过,需要virtualenv安装,安装路径可自行调整: git clone https://github.com/JinpengLI/deep
ISI's Optical Character Recognition (OCR) software for machine-print and handwriting data
VistaOCR ISI's Optical Character Recognition (OCR) software for machine-print and handwriting data Publications "How to Efficiently Increase Resolutio
Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
English | 简体中文 Introduction PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and a
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
https://arxiv.org/abs/1904.01941
Character-Region-Awareness-for-Text-Detection- https://arxiv.org/abs/1904.01941 Train You can train SynthText data use python source/train_SynthText.p
Text language identification using Wikipedia data
Text language identification using Wikipedia data The aim of this project is to provide high-quality language detection over all the web's languages.
Python library to extract tabular data from images and scanned PDFs
Overview ExtractTable - API to extract tabular data from images and scanned PDFs The motivation is to make it easy for developers to extract tabular d
Extract tables from scanned image PDFs using Optical Character Recognition.
ocr-table This project aims to extract tables from scanned image PDFs using Optical Character Recognition. Install Requirements Tesseract OCR sudo apt
Turn images of tables into CSV data. Detect tables from images and run OCR on the cells.
Table of Contents Overview Requirements Demo Modules Overview This python package contains modules to help with finding and extracting tabular data fr
Unofficial implementation of "TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images"
TableNet Unofficial implementation of ICDAR 2019 paper : TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from
Handwritten_Text_Recognition
Deep Learning framework for Line-level Handwritten Text Recognition Short presentation of our project Introduction Installation 2.a Install conda envi
Handwritten Number Recognition using CNN and Character Segmentation
Handwritten-Number-Recognition-With-Image-Segmentation Info About this repository This Repository is aimed at reading handwritten images of numbers an
Generic framework for historical document processing
dhSegment dhSegment is a tool for Historical Document Processing. Its generic approach allows to segment regions and extract content from different ty
Character Segmentation using TensorFlow
Character Segmentation Segment characters and spaces in one text line,from this paper Chinese English mixed Character Segmentation as Semantic Segment
DECAF: Deep Extreme Classification with Label Features
DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain
Pack up to 3MB of data into a tweetable PNG polyglot file.
tweetable-polyglot-png Pack up to 3MB of data into a tweetable PNG polyglot file. See it in action here: https://twitter.com/David3141593/status/13719
Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)
Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations
Visualize Data From Stray Scanner https://keke.dev/blog/2021/03/10/Stray-Scanner.html
StrayVisualizer A set of scripts to work with data collected using Stray Scanner. Usage Installing Dependencies Install dependencies with pip -r requi
First Party data integration solution built for marketing teams to enable audience and conversion onboarding into Google Marketing products (Google Ads, Campaign Manager, Google Analytics).
Megalista Sample integration code for onboarding offline/CRM data from BigQuery as custom audiences or offline conversions in Google Ads, Google Analy
TorchMetrics is a collection of 25+ PyTorch metrics implementations and an easy-to-use API to create custom metrics.
Machine learning metrics for distributed, scalable PyTorch applications.
Ralph is the CMDB / Asset Management system for data center and back office hardware.
Ralph Ralph is full-featured Asset Management, DCIM and CMDB system for data centers and back offices. Features: keep track of assets purchases and th
IP address management (IPAM) and data center infrastructure management (DCIM) tool.
NetBox is an IP address management (IPAM) and data center infrastructure management (DCIM) tool. Initially conceived by the network engineering team a
a full featured file system for online data storage
S3QL S3QL is a file system that stores all its data online using storage services like Google Storage, Amazon S3, or OpenStack. S3QL effectively provi
An open source multi-tool for exploring and publishing data
Datasette An open source multi-tool for exploring and publishing data Datasette is a tool for exploring and publishing data. It helps people take data
🦉Data Version Control | Git for Data & Models
Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci
Finds Jobs on LinkedIn using web-scraping
Find Jobs on LinkedIn 📔 This program finds jobs by scraping on LinkedIn 👨💻 Relies on User Input. Accepts: Country, City, State 📑 Data about jobs
Character Controllers using Motion VAEs
Character Controllers using Motion VAEs This repo is the codebase for the SIGGRAPH 2020 paper with the title above. Please find the paper and demo at
Consistency Regularization for Adversarial Robustness
Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho
All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.
Data Structures and Algorithms Python INDEX 1. Resources - Books Data Structures - Reema Thareja competitiveCoding Big-O Cheat Sheet DAA Syllabus Inte
Synthetic data for the people.
zpy: Synthetic data in Blender. Website • Install • Docs • Examples • CLI • Contribute • Licence Abstract Collecting, labeling, and cleaning data for
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain
Django project starter on steroids: quickly create a Django app AND generate source code for data models + REST/GraphQL APIs (the generated code is auto-linted and has 100% test coverage).
Create Django App 💛 We're a Django project starter on steroids! One-line command to create a Django app with all the dependencies auto-installed AND
(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan
Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!
Rubicon Purpose Rubicon is a data science tool that captures and stores model training and execution information, like parameters and outcomes, in a r
Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper
Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont
Create HTML profiling reports from pandas DataFrame objects
Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great
An extension to pandas dataframes describe function.
pandas_summary An extension to pandas dataframes describe function. The module contains DataFrameSummary object that extend describe() with: propertie
A library for augmenting annotated audio data
muda A library for Musical Data Augmentation. muda package implements annotation-aware musical data augmentation, as described in the muda paper. The
The Python ensemble sampling toolkit for affine-invariant MCMC
emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense
Supervised domain-agnostic prediction framework for probabilistic modelling
A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,
A fast xgboost feature selection algorithm
BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l
Automatic extraction of relevant features from time series:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to
Build, test, deploy, iterate - Dev and prod tool for data science pipelines
Prodmodel is a build system for data science pipelines. Users, testers, contributors are welcome! Motivation · Concepts · Installation · Usage · Contr
A Python toolkit for processing tabular data
meza: A Python toolkit for processing tabular data Index Introduction | Requirements | Motivation | Hello World | Usage | Interoperability | Installat
Clean APIs for data cleaning. Python implementation of R package Janitor
pyjanitor pyjanitor is a Python implementation of the R package janitor, and provides a clean API for cleaning data. Why janitor? Originally a port of
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo
functional data manipulation for pandas
pandas-ply: functional data manipulation for pandas pandas-ply is a thin layer which makes it easier to manipulate data with pandas. In particular, it
Easy pipelines for pandas DataFrames.
pdpipe ˨ Easy pipelines for pandas DataFrames (learn how!). Website: https://pdpipe.github.io/pdpipe/ Documentation: https://pdpipe.github.io/pdpipe/d
Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second 🚀
What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data
Koalas: pandas API on Apache Spark
pandas API on Apache Spark Explore Koalas docs » Live notebook · Issues · Mailing list Help Thirsty Koalas Devastated by Recent Fires The Koalas proje
A Python package for manipulating 2-dimensional tabular data structures
datatable This is a Python package for manipulating 2-dimensional tabular data structures (aka data frames). It is close in spirit to pandas or SFrame
High performance datastore for time series and tick data
Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-
A pure Python implementation of Apache Spark's RDD and DStream interfaces.
pysparkling Pysparkling provides a faster, more responsive way to develop programs for PySpark. It enables code intended for Spark applications to exe
Universal 1d/2d data containers with Transformers functionality for data analysis.
XPandas (extended Pandas) implements 1D and 2D data containers for storing type-heterogeneous tabular data of any type, and encapsulates feature extra
Pandas Google BigQuery
pandas-gbq pandas-gbq is a package providing an interface to the Google BigQuery API from pandas Installation Install latest release version via conda
NumPy and Pandas interface to Big Data
Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar inte
Create HTML profiling reports from pandas DataFrame objects
Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great
Logging MXNet data for visualization in TensorBoard.
Logging MXNet Data for Visualization in TensorBoard Overview MXBoard provides a set of APIs for logging MXNet data for visualization in TensorBoard. T
Interpretability and explainability of data and machine learning models
AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase
A library for debugging/inspecting machine learning classifiers and explaining their predictions
ELI5 ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following m
An intuitive library to add plotting functionality to scikit-learn objects.
Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
With Holoviews, your data visualizes itself.
HoloViews Stop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data a
How on earth can I ever think of a solution like that in an interview?!
fuck-coding-interviews This repository is created by an awkward programmer who always struggles with coding problems on LeetCode, even with some Easy
Algorithms and data structures for educational, demonstrational and experimental purposes.
Algorithms and Data Structures (ands) Introduction This project was created for personal use mostly while studying for an exam (starting in the month
:computer: Data Structures and Algorithms in Python
Algorithms in Python Implementations of a few algorithms and datastructures for fun and profit! Completed Karatsuba Multiplication Basic Sorting Rabin
Python library that makes it easy for data scientists to create charts.
Chartify Chartify is a Python library that makes it easy for data scientists to create charts. Why use Chartify? Consistent input data format: Spend l
Keras community contributions
keras-contrib : Keras community contributions Keras-contrib is deprecated. Use TensorFlow Addons. The future of Keras-contrib: We're migrating to tens
Machine Learning Platform for Kubernetes
Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica
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
Data loaders and abstractions for text and NLP
torchtext This repository consists of: torchtext.datasets: The raw text iterators for common NLP datasets torchtext.data: Some basic NLP building bloc
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Python-based implementations of algorithms for learning on imbalanced data.
ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
[HELP REQUESTED] Generalized Additive Models in Python
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc
A toolkit for making real world machine learning and data analysis applications in C++
dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
daily report of @arkinvest ETF activity + data collection
ark_invest daily weekday report of @arkinvest ETF activity + data collection This script was created to: Extract and save daily csv's from ARKInvest's
test
Lidar-data-decode In this project, you can decode your lidar data frame(pcap file) and make your own datasets(test dataset) in Windows without any hug
An automated tool that fetches information about your crypto stake and generates historical data in time.
Introduction Yield explorer is a WIP! I needed a tool that would show me historical data and performance of my staked crypto but was unable to find a
Deep Illuminator is a data augmentation tool designed for image relighting.
Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently genera
Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.
Demo Code for "Talking Head Anime from a Single Image 2: More Expressive" This repository contains demo programs for the Talking Head Anime
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
3D visualization of scientific data in Python
Mayavi: 3D visualization of scientific data in Python Mayavi docs: http://docs.enthought.com/mayavi/mayavi/ TVTK docs: http://docs.enthought.com/mayav
Data intensive science for everyone.
The latest information about Galaxy can be found on the Galaxy Community Hub. Community support is available at Galaxy Help. Galaxy Quickstart Galaxy