Recent Trend

Hazel
Hazel Engine
PayloadsAllTheThings
A list of useful payloads and bypass for Web Application Security and Pentest/CTF
send
Simple, private file sharing from the makers of Firefox
windows
V2ray , Trojan, Trojan-go, NaiveProxy, shadowsocksR install tools for windows V2ray,Trojan,Trojan-go, NaiveProxy, shadowsocksR的一键安装工具windows下用(一键科学上网)
silero-models
Silero Models: pre-trained STT models and benchmarks made embarrassingly simple
vue-next
Repo for Vue 3.0 (currently in RC)
FreeCAD
This is the official source code of FreeCAD, a free and opensource multiplatform 3D parametric modeler. Issues are managed on our own bug tracker at https://www.freecadweb.org/tracker
kb
A minimalist knowledge base manager
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
mimikatz
A little tool to play with Windows security
vagas-junior-estagio
Empresas que constantemente oferecem vagas para junior e estagiários
material-shell
A modern desktop interface for Linux. Improve your user experience and get rid of the anarchy of traditional desktop workflows. Designed to simplify navigation and reduce the need to manipulate window
dayjs
⏰ Day.js 2KB immutable date library alternative to Moment.js with the same modern API
ML_course
EPFL Machine Learning Course, Fall 2019
create-react-app
Set up a modern web app by running one command.
Background-Matting
Background Matting: The World is Your Green Screen
Kingfisher
A lightweight, pure-Swift library for downloading and caching images from the web.
istio
Connect, secure, control, and observe services.
linux-command
Linux命令大全搜索工具,内容包含Linux命令手册、详解、学习、搜集。https://git.io/linux
generative_inpainting
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
yearn-protocol
Yearn solidity smart contracts
pebble
RocksDB/LevelDB inspired key-value database in Go
jazzit
Laughs at your expense
moment
Parse, validate, manipulate, and display dates in javascript.
n8n
Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.
Hero
Elegant transition library for iOS & tvOS
DAIN
Depth-Aware Video Frame Interpolation (CVPR 2019)
eat_tensorflow2_in_30_days
Tensorflow2.0 ?? is delicious, just eat it! ??
tmpmail
✉️ A temporary email right from your terminal
team-comtress-2
Team Fortress 2, but with a lot of fixes, QoL improvements and performance optimizations!
CVE-2020-1472
PoC for Zerologon - all research credits go to Tom Tervoort of Secura
DefinitelyTyped
The repository for high quality TypeScript type definitions.
rails
Ruby on Rails
stats-illustrations
R & stats illustrations by @allison_horst
pytorch-gans
My implementation of various GAN (generative adversarial networks) architectures like vanilla GAN, cGAN, DCGAN, etc.
data-science-interviews
Data science interview questions and answers
sds1

jupyter-text2code
A proof-of-concept jupyter extension which converts english queries into relevant python code
Notebooks
Learn Python for free using open-source notebooks in Hebrew.
jellyfin
The Free Software Media System
BIGTREETECH-SKR-mini-E3
BIGTREETECH SKR-mini-E3 motherboard is a ultra-quiet, low-power, high-quality 3D printing machine control board. It is launched by the 3D printing team of Shenzhen BIGTREE technology co., LTD. This bo
XiaomiADBFastbootTools
A simple tool for managing Xiaomi devices on desktop using ADB and Fastboot
fastmac
Get a MacOS or Linux shell, for free, in around 2 minutes
pipedream
Serverless integration and compute platform. Free for developers.
DeepVision
在我很多项目中用到的CV算法推理框架应用。
dive
A tool for exploring each layer in a docker image
libra
Libra’s mission is to enable a simple global payment system and financial infrastructure that empowers billions of people.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters,
kinto

CVE-2020-1472
Test tool for CVE-2020-1472
leetcode_company_wise_questions
This is a repository containing the list of company wise questions available on leetcode premium
makani
Makani was a project to develop a commercial-scale airborne wind turbine, culminating in a flight test of the Makani M600 off the coast of Norway. All Makani software has now been open-sourced. This r
Fantasy-Premier-League
Creates a .csv file of all players in the English Player League with their respective team and total fantasy points
996.ICU
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
graal
GraalVM: Run Programs Faster Anywhere ?
understand-nodejs
通过源码分析nodejs原理
tensorboard
TensorFlow's Visualization Toolkit
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
Relativty
An open source VR headset with SteamVR supports for $200
guide-rpc-framework
A custom RPC framework implemented by Netty+Kyro+Zookeeper.(一款基于 Netty+Kyro+Zookeeper 实现的自定义 RPC 框架-附详细实现过程和相关教程。)
UTM
Virtual machines for iOS
v2ray-heroku
用于在 Heroku 上部署 V2Ray Websocket,本项目不宜做为长期使用之对策。
learning
Becoming 1% better at data science everyday
wirehole

minecraft-react

mem-doc
This is a document to help with .NET memory analysis and diagnostics.
HarmonyOS
A curated list of awesome things related to HarmonyOS. 华为鸿蒙操作系统。
radar-covid-backend-dp3t-server
DP^3T Radar COVID fork
eiten
Statistical and Algorithmic Investing Strategies for Everyone
radar-covid-backend-verification-server
Radar COVID Verification Service
radar-covid-ios
Native iOS app using DP^3T iOS sdk to handle Exposure Notification framework from Apple
radar-covid-android
Native Android app using DP^3T Android sdk to handle Exposure Notifications API from Google
react-challenge-amazon-clone

solana
Web-Scale Blockchain for fast, secure, scalable, decentralized apps and marketplaces.
cockroach
CockroachDB - the open source, cloud-native distributed SQL database.
machine-learning-for-trading
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
hwp.js
Open source hwp viewer and parser library powered by web technology
awesome-react
A collection of awesome things regarding React ecosystem
connectedhomeip
Project Connected Home over IP is a new Working Group within the Zigbee Alliance. This Working Group plans to develop and promote the adoption of a new connectivity standard to increase compatibility
Yolo-Fastest
⚡ Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB
laravel
A PHP framework for web artisans
onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
cim
?cim(cross IM) 适用于开发者的分布式即时通讯系统
ESP32-WiFi-Hash-Monster
WiFi Hash Purple Monster, store EAPOL & PMKID packets in an SD CARD using a M5STACK / ESP32 device
react-portfolio

Algorithms
A collection of algorithms and data structures
frp
A fast reverse proxy to help you expose a local server behind a NAT or firewall to the internet.
funNLP
中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名
GRAT2
We developed GRAT2 Command & Control (C2) project for learning purpose.
DescomplicandoKubernetes

aes-finder
Utility to find AES keys in running processes
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
ultimate-python
Ultimate Python study guide for newcomers and professionals alike. ? ? ?
sushiswap-frontend

pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
awesome-flutter
An awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.
Interview_Question_for_Beginner
? ? Technical-Interview guidelines written for those who started studying programming. I wish you all the best. ?
free

talk
A group video call for the web. No signups. No downloads.
bitcoin
Bitcoin Core integration/staging tree
eleventy-high-performance-blog
A high performance blog template for the 11ty static site generator.
awesome-project-ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
ghcide
A library for building Haskell IDE tooling
moon
? The minimal & fast library for functional user interfaces
jdk
JDK main-line development
Tasmota
Alternative firmware for ESP8266 with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full docum
Server
PanDownload的个人维护版本
a32nx
The A32NX Project is a community driven open source project to create a free Airbus A320neo in Microsoft Flight Simulator that is as close to reality as possible. It aims to enhance the default A320ne
keras
Deep Learning for humans
Red-Teaming-Toolkit
A collection of open source and commercial tools that aid in red team operations.
data-engineer-roadmap
Roadmap to becoming a data engineer in 2020
hivemind
Decentralized deep learning framework in pytorch. Built to train models on thousands of volunteers across the world.
scipio
Scipio is a thread-per-core framework that aims to make the task of writing highly parallel asynchronous application in a thread-per-core architecture easier for rustaceans
hoppscotch
? A free, fast and beautiful API request builder used by 75k+ developers. https://hoppscotch.io
Wav2Lip
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.
KingOfBugBountyTips

autoscraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
100-nlp-papers
100 Must-Read NLP Papers
croc
Easily and securely send things from one computer to another ? ?
spark-nlp
State of the Art Natural Language Processing
display-switch
Turn a $30 USB switch into a full-featured multi-monitor KVM switch
surpriver
Find big moving stocks before they move using machine learning and anomaly detection
flink-learning
flink learning blog. http://www.flink-learning.com 含 Flink 入门、概念、原理、实战、性能调优、源码解析等内容。涉及 Flink Connector、Metrics、Library、DataStream API、Table API & SQL 等内容的学习案例,还有 Flink 落地应用的大型项目案例(PVUV、日志存储、百亿数据实时去重、监
deeplearning-models
A collection of various deep learning architectures, models, and tips
fes.js
Fes.js 是一个管理台应用解决方案,提供初始项目、开发调试、编译打包的命令行工具,内置布局、权限、数据字典、状态管理、Api等多个模块,文件目录结构即路由,用户只需要编写页面内容。基于Vue.js,内置管理台常用能力,让用户写的更少,更简单。经过多个项目中打磨,趋于稳定。
stitches
The modern styling library. Near-zero runtime, server-side rendering, multi-variant support, and best-in-class developer experience.
18S191
Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia
grafana
The tool for beautiful monitoring and metric analytics & dashboards for Graphite, InfluxDB & Prometheus & More
fortify

jetstream

scikit-learn-tips
?⚡ Daily scikit-learn tips
12306
12306智能刷票,订票
desafio-6-2020

30-seconds-of-code
Short JavaScript code snippets for all your development needs
gdal
GDAL is an open source X/MIT licensed translator library for raster and vector geospatial data formats.
toBeTopJavaer
To Be Top Javaer - Java工程师成神之路
companies-sponsoring-visas
A list of companies that sponsor employees from other countries.
howtheytest
A collection of public resources about how software companies test their software
bicep

htop
htop - an interactive process viewer
portainer
Making Docker management easy.
gorm
The fantastic ORM library for Golang, aims to be developer friendly
SuperPower
Here you should find the best power supplies for your low-power projects
CompEcon2020
Computational Economics Course 2020 by Kenneth Judd
vimac
Vimium for macOS.
Windows10Debloater
Script to remove Windows 10 bloatware.
HowToHunt
Some Tutorials and Things to Do while Hunting That Vulnerability.
Hack-Tools
The all-in-one Red Team extension for Web Pentester ?
KingOfBugBountyTips

Showkase
? Showkase is an annotation-processor based Android library that helps you organize, discover, search and visualize Jetpack Compose UI elements
webrtc-for-the-curious
WebRTC for the Curious: Go beyond the APIs
matplotplusplus
Matplot++: A C++ Graphics Library for Data Visualization ??
Flutter-Course-Resources
Learn to Code While Building Apps - The Complete Flutter Development Bootcamp
flutter-development-roadmap
Flutter App Developer Roadmap - A complete roadmap to learn Flutter App Development. I tried to learn flutter using this roadmap. If you want to add something please contribute to the project. Happy L
objax

sushiswap
? SushiSwap smart contracts
Cloudreve
?支持多家云存储的云盘系统 (A project helps you build your own cloud in minutes)
learn-python
? Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Python-programming-exercises
100+ Python challenging programming exercises
learn-python3
Jupyter notebooks for teaching/learning Python 3
vscode-debug-visualizer
An extension for VS Code that visualizes data during debugging.
rapier
2D and 3D physics engines focused on performances.
project-guidelines
A set of best practices for JavaScript projects
d3
Bring data to life with SVG, Canvas and HTML. ???
OpenBot
OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones suppo
speakeasy
Windows kernel and user mode emulation.
Learn-Vim
A book for learning the Vim editor
maratona-fullcycle-4

arwes
Futuristic Sci-Fi and Cyberpunk Graphical User Interface Framework for Web Apps
gitignore
A collection of useful .gitignore templates
black
The uncompromising Python code formatter
airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
shift-ctrl-f
? Search the information available on a webpage using natural language instead of an exact string match.
traefik
The Cloud Native Edge Router
TecoGAN
This repo will contain source code and materials for the TecoGAN project, i.e. code for a TEmporally COherent GAN
present
A terminal-based presentation tool with colors and effects.
gitpod
Gitpod is an open-source Kubernetes application providing prebuilt, collaborative development environments in your browser - powered by VS Code.
compose-samples

react-native-navigation
A complete native navigation solution for React Native
kubernetes-examples
Minimal self-contained examples of standard Kubernetes features and patterns in YAML
vscode
Visual Studio Code
cpp-httplib
A C++ header-only HTTP/HTTPS server and client library
AWS-SAA-C02-Course
Personal notes for SAA-C02 test from: https://learn.cantrill.io
clean-architecture-swiftui
A demo project showcasing the production setup of the SwiftUI app with Clean Architecture
Gooey
Turn (almost) any Python command line program into a full GUI application with one line
baiduwp-php
PanDownload网页复刻版
latexify_py
Generates LaTeX math description from Python functions.
open-source-cs-python

RAFT

volt-bootstrap-5-dashboard
⚡️ Volt Bootstrap 5 Admin Dashboard Template with vanilla Javascript
itlwm
Intel Wi-Fi Drivers
packer
Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
open-source-cs
Video discussing this curriculum:
nsfw-filter
A Google Chrome / Firefox extension that blocks NSFW images from the web pages that you load using TensorFlow JS.
sudoku-solver
Smart solution to solve sudoku in VR
desafio-4-2020

msfs-a320neo

mit-15-003-data-science-tools
Study guides for MIT's 15.003 Data Science Tools
CascadeTabNet
This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
certified-kubernetes-administrator-course
Certified Kubernetes Administrator - CKA Course
everyones-guide-for-starting-up-on-wechat-network
微信互联网平民创业
manim
Animation engine for explanatory math videos
CS-Notes
我的自学笔记,在学习shell和MLSys,整理C++、算法、操作系统,后续学习分布式系统,终身更新。
egua
? Linguagem de programação simples e moderna em português
talent-plan
open source training courses about distributed database and distributed systemes
godot
Godot Engine – Multi-platform 2D and 3D game engine
desafio-3-2020

optuna
A hyperparameter optimization framework
Ventoy
A new bootable USB solution.
Alt-F4
Alternative Factorio Friday Fan Facts, also known as Alt-F4
awesome-made-by-brazilians
?? A collection of amazing open source projects built by brazilian developers
zig
General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
cxx
Safe interop between Rust and C++
lireddit

chakra-ui
⚡️ Simple, Modular & Accessible UI Components for your React Applications
VancedManager
Vanced Installer
react-native-video
A
NYPD-Misconduct-Complaint-Database
This database is a record of NYPD misconduct complaints made by the public to the Civilian Complaint Review Board (CCRB).
awesome-django
A curated list of awesome things related to Django
Front-End-Checklist
? The perfect Front-End Checklist for modern websites and meticulous developers
fet.sh
a fetch written in posix shell without any external commands (linux only)
baiduwp
PanDownload Web, built with CloudFlare Workers
machine-learning-interview
Minimum Viable Study Plan for Machine Learning Interviews from FAAG, Snapchat, LinkedIn.
RSSHub
? Everything is RSSible
metamask-extension
? ? The MetaMask browser extension enables browsing Ethereum blockchain enabled websites
amplify-flutter
Amplify Framework provides a declarative and easy-to-use interface across different categories of cloud operations.
ent
An entity framework for Go
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
element3
(WIP)fork from ElemeFE/element ,A Vue.js 3.0 UI Toolkit for Web
posthog
? PostHog is developer-friendly, open-source product analytics.
awesome-hpp
A curated list of awesome header-only C++ libraries
fabric
Hyperledger Fabric is an enterprise-grade permissioned distributed ledger framework for developing solutions and applications. Its modular and versatile design satisfies a broad range of industry use
insight
Repository for Project Insight: NLP as a Service
omatsuri
Browser application with 9 open source frontend focused tools
InfoSpider
INFO-SPIDER 是一个集众多数据源于一身的爬虫工具箱?,旨在安全快捷的帮助用户拿回自己的数据,工具代码开源,流程透明。支持数据源包括GitHub、QQ邮箱、网易邮箱、阿里邮箱、新浪邮箱、Hotmail邮箱、Outlook邮箱、京东、淘宝、支付宝、中国移动、中国联通、中国电信、知乎、哔哩哔哩、网易云音乐、QQ好友、QQ群、生成朋友圈相册、浏览器浏览历史、12306、博客园、CSDN博客、开源
element-plus
A Vue.js 3.0 UI Toolkit for Web
autoscaler
Autoscaling components for Kubernetes
magento2
All Submissions you make to Magento Inc. ("Magento") through GitHub are subject to the following terms and conditions: (1) You grant Magento a perpetual, worldwide, non-exclusive, no charge, royalty f
ts-migrate
A tool to help migrate JavaScript code quickly and conveniently to TypeScript
ar-cutpaste
Cut and paste your surroundings using AR
chinese-programmer-wrong-pronunciation
中国程序员容易发音错误的单词
labs_campaigns

AdGuardHome
Network-wide ads & trackers blocking DNS server
COLA
Clean Object-oriented & Layered Architecture
Godzilla
哥斯拉
diagrams
? Diagram as Code for prototyping cloud system architectures
PaddleDetection
Object detection and instance segmentation toolkit based on PaddlePaddle.
handcalcs
Python library for converting Python calculations into rendered latex.
mern-course-bootcamp
Complete Free Coding Bootcamp 2020 MERN Stack
handwritten.js
Convert typed text to realistic handwriting!
archivy
Archivy is a self-hosted knowledge repository that allows you to safely preserve useful content that contributes to your knowledge bank.
mall-swarm
mall-swarm是一套微服务商城系统,采用了 Spring Cloud Hoxton & Alibaba、Spring Boot 2.3、Oauth2、MyBatis、Docker、Elasticsearch等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。文档齐全,附带全套Spring Clou
umami
Umami is a simple, fast, website analytics alternative to Google Analytics.
nl-covid19-notification-app-android
Android sources for the Dutch Covid19 Notification App
contenidos
Material del curso IIC2233 Programación Avanzada ?
locast2plex
A very simple script to connect locast to Plex's live tv/dvr feature.
h1st
H1st AI solves the critical “cold-start” problem of Industrial AI: encoding human expertise to augment the lack of data, while building a smooth transition toward a machine-learning future. This probl
minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Catch2
A modern, C++-native, header-only, test framework for unit-tests, TDD and BDD - using C++11, C++14, C++17 and later (or C++03 on the Catch1.x branch)
libra
Ergonomic machine learning.
annie
? Fast, simple and clean video downloader
spotMicro
Spot Micro Quadripeg Project
LeetCode-Go
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
bootcamp-gostack-desafios
Repositório contendo todos os desafios dos módulos do Bootcamp Gostack
NoVmp
A static devirtualizer for VMProtect x64 3.x. powered by VTIL.
fullcalendar
Full-sized drag & drop event calendar
latexify_py
Generates LaTeX math description from Python functions.
vue-nodejs-youtube-clone
This is the frontend (VueJS) of the Youtube clone called VueTube.
youtube-clone-nodejs-api
VueTube is a YouTube clone built with nodejs, expressjs & mongodb. This is the RESTful API repository.
Behinder
“冰蝎”动态二进制加密网站管理客户端
low-level-design-primer

E-commerce-Complete-Flutter-UI

handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
aws-machine-learning-university-accelerated-tab

aws-machine-learning-university-accelerated-cv

mogollar
A MongoDB UI built with Electron
BespokeSynth
Software modular synth
desafio-1-2020

desafio-1-2020

kosmonaut
A web browser engine for the space age ?
aws-machine-learning-university-accelerated-nlp

fastbook
Draft of the fastai book
Hierarchical-Localization
Visual localization made easy
TypeScript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
Penetration_Testing_POC
渗透测试有关的POC、EXP、脚本、提权、小工具等,欢迎补充、完善---About penetration-testing python-script poc getshell csrf xss cms php-getshell domainmod-xss penetration-testing-poc csrf-webshell cobub-razor cve rce sql sql-poc p
God-Of-BigData
大数据面试题,大数据成神之路开启...Flink/Spark/Hadoop/Hbase/Hive...
OSCPRepo
A list of commands, scripts, resources, and more that I have gathered and attempted to consolidate for use as OSCP (and more) study material. Commands in 'Usefulcommands' Keepnote. Bookmarks and readi
drogon
Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows
papercups
Open-source live customer chat
jupyter-book
Build interactive, publication-quality documents from Jupyter Notebooks
awesome-java
Collection of awesome Java project on Github(Github 上非常棒的 Java 开源项目集合).
espflix
A free video streaming service that runs on a ESP32
servo
The Servo Browser Engine
halfmoon
Front-end framework with a built-in dark mode, designed for rapidly building beautiful dashboards and product pages.
eventnative
EventNative is an open-source data collection framework
go-github
Go library for accessing the GitHub API
yam-protocol
A stablizing reserve currency protocol
mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
sherlock
? Hunt down social media accounts by username across social networks
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
clean-code-javascript
? Clean Code concepts adapted for JavaScript
laravel-admin
Build a full-featured administrative interface in ten minutes
OpenJailbreak
GeoSn0w's OpenJailbreak Project, an open-source iOS 11 to iOS 13 Jailbreak project & vault.
azure-quickstart-templates
Azure Quickstart Templates
nodejs.dev
A new Node.js resource built using Gatsby.js with React.js, TypeScript, Emotion, and Remark.
KOOM
KOOM is an OOM killer on mobile platform by Kwai.
bevy
A refreshingly simple data-driven game engine built in Rust
eat_pytorch_in_20_days
Pytorch?? is delicious, just eat it! ??
datasets
? 2,000,000+ Unsplash images made available for research and machine learning
malwoverview
Malwoverview is a first response tool to perform an initial and quick triage in a directory containing malware samples, specific malware sample, suspect URL and domains. Additionally, it allows to dow
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Kalman-and-Bayesian-Filters-in-Python

Jupyter Notebook LINK
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters,

Kalman and Bayesian Filters in Python

Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn?

"Kalman and Bayesian Filters in Python" looks amazing! ... your book is just what I needed - Allen Downey, Professor and O'Reilly author.

Thanks for all your work on publishing your introductory text on Kalman Filtering, as well as the Python Kalman Filtering libraries. We’ve been using it internally to teach some key state estimation concepts to folks and it’s been a huge help. - Sam Rodkey, SpaceX

Start reading online now by clicking the binder or Azure badge below:

Binder

alt tag

What are Kalman and Bayesian Filters?

Sensors are noisy. The world is full of data and events that we want to measure and track, but we cannot rely on sensors to give us perfect information. The GPS in my car reports altitude. Each time I pass the same point in the road it reports a slightly different altitude. My kitchen scale gives me different readings if I weigh the same object twice.

In simple cases the solution is obvious. If my scale gives slightly different readings I can just take a few readings and average them. Or I can replace it with a more accurate scale. But what do we do when the sensor is very noisy, or the environment makes data collection difficult? We may be trying to track the movement of a low flying aircraft. We may want to create an autopilot for a drone, or ensure that our farm tractor seeded the entire field. I work on computer vision, and I need to track moving objects in images, and the computer vision algorithms create very noisy and unreliable results.

This book teaches you how to solve these sorts of filtering problems. I use many different algorithms, but they are all based on Bayesian probability. In simple terms Bayesian probability determines what is likely to be true based on past information.

If I asked you the heading of my car at this moment you would have no idea. You'd proffer a number between 1° and 360° degrees, and have a 1 in 360 chance of being right. Now suppose I told you that 2 seconds ago its heading was 243°. In 2 seconds my car could not turn very far, so you could make a far more accurate prediction. You are using past information to more accurately infer information about the present or future.

The world is also noisy. That prediction helps you make a better estimate, but it also subject to noise. I may have just braked for a dog or swerved around a pothole. Strong winds and ice on the road are external influences on the path of my car. In control literature we call this noise though you may not think of it that way.

There is more to Bayesian probability, but you have the main idea. Knowledge is uncertain, and we alter our beliefs based on the strength of the evidence. Kalman and Bayesian filters blend our noisy and limited knowledge of how a system behaves with the noisy and limited sensor readings to produce the best possible estimate of the state of the system. Our principle is to never discard information.

Say we are tracking an object and a sensor reports that it suddenly changed direction. Did it really turn, or is the data noisy? It depends. If this is a jet fighter we'd be very inclined to believe the report of a sudden maneuver. If it is a freight train on a straight track we would discount it. We'd further modify our belief depending on how accurate the sensor is. Our beliefs depend on the past and on our knowledge of the system we are tracking and on the characteristics of the sensors.

The Kalman filter was invented by Rudolf Emil Kálmán to solve this sort of problem in a mathematically optimal way. Its first use was on the Apollo missions to the moon, and since then it has been used in an enormous variety of domains. There are Kalman filters in aircraft, on submarines, and on cruise missiles. Wall street uses them to track the market. They are used in robots, in IoT (Internet of Things) sensors, and in laboratory instruments. Chemical plants use them to control and monitor reactions. They are used to perform medical imaging and to remove noise from cardiac signals. If it involves a sensor and/or time-series data, a Kalman filter or a close relative to the Kalman filter is usually involved.

Motivation

The motivation for this book came out of my desire for a gentle introduction to Kalman filtering. I'm a software engineer that spent almost two decades in the avionics field, and so I have always been 'bumping elbows' with the Kalman filter, but never implemented one myself. As I moved into solving tracking problems with computer vision the need became urgent. There are classic textbooks in the field, such as Grewal and Andrew's excellent Kalman Filtering. But sitting down and trying to read many of these books is a dismal experience if you do not have the required background. Typically the first few chapters fly through several years of undergraduate math, blithely referring you to textbooks on topics such as Itō calculus, and present an entire semester's worth of statistics in a few brief paragraphs. They are good texts for an upper undergraduate course, and an invaluable reference to researchers and professionals, but the going is truly difficult for the more casual reader. Symbology is introduced without explanation, different texts use different terms and variables for the same concept, and the books are almost devoid of examples or worked problems. I often found myself able to parse the words and comprehend the mathematics of a definition, but had no idea as to what real world phenomena they describe. "But what does that mean?" was my repeated thought.

However, as I began to finally understand the Kalman filter I realized the underlying concepts are quite straightforward. A few simple probability rules, some intuition about how we integrate disparate knowledge to explain events in our everyday life and the core concepts of the Kalman filter are accessible. Kalman filters have a reputation for difficulty, but shorn of much of the formal terminology the beauty of the subject and of their math became clear to me, and I fell in love with the topic.

As I began to understand the math and theory more difficulties present themselves. A book or paper's author makes some statement of fact and presents a graph as proof. Unfortunately, why the statement is true is not clear to me, nor is the method for making that plot obvious. Or maybe I wonder "is this true if R=0?" Or the author provides pseudocode at such a high level that the implementation is not obvious. Some books offer Matlab code, but I do not have a license to that expensive package. Finally, many books end each chapter with many useful exercises. Exercises which you need to understand if you want to implement Kalman filters for yourself, but exercises with no answers. If you are using the book in a classroom, perhaps this is okay, but it is terrible for the independent reader. I loathe that an author withholds information from me, presumably to avoid 'cheating' by the student in the classroom.

From my point of view none of this is necessary. Certainly if you are designing a Kalman filter for an aircraft or missile you must thoroughly master all of the mathematics and topics in a typical Kalman filter textbook. I just want to track an image on a screen, or write some code for an Arduino project. I want to know how the plots in the book are made, and chose different parameters than the author chose. I want to run simulations. I want to inject more noise in the signal and see how a filter performs. There are thousands of opportunities for using Kalman filters in everyday code, and yet this fairly straightforward topic is the provenance of rocket scientists and academics.

I wrote this book to address all of those needs. This is not the book for you if you program navigation computers for Boeing or design radars for Raytheon. Go get an advanced degree at Georgia Tech, UW, or the like, because you'll need it. This book is for the hobbyist, the curious, and the working engineer that needs to filter or smooth data.

This book is interactive. While you can read it online as static content, I urge you to use it as intended. It is written using Jupyter Notebook, which allows me to combine text, math, Python, and Python output in one place. Every plot, every piece of data in this book is generated from Python that is available to you right inside the notebook. Want to double the value of a parameter? Click on the Python cell, change the parameter's value, and click 'Run'. A new plot or printed output will appear in the book.

This book has exercises, but it also has the answers. I trust you. If you just need an answer, go ahead and read the answer. If you want to internalize this knowledge, try to implement the exercise before you read the answer.

This book has supporting libraries for computing statistics, plotting various things related to filters, and for the various filters that we cover. This does require a strong caveat; most of the code is written for didactic purposes. It is rare that I chose the most efficient solution (which often obscures the intent of the code), and in the first parts of the book I did not concern myself with numerical stability. This is important to understand - Kalman filters in aircraft are carefully designed and implemented to be numerically stable; the naive implementation is not stable in many cases. If you are serious about Kalman filters this book will not be the last book you need. My intention is to introduce you to the concepts and mathematics, and to get you to the point where the textbooks are approachable.

Finally, this book is free. The cost for the books required to learn Kalman filtering is somewhat prohibitive even for a Silicon Valley engineer like myself; I cannot believe they are within the reach of someone in a depressed economy, or a financially struggling student. I have gained so much from free software like Python, and free books like those from Allen B. Downey here. It's time to repay that. So, the book is free, it is hosted on free servers, and it uses only free and open software such as IPython and MathJax to create the book.

Reading Online

The book is written as a collection of Jupyter Notebooks, an interactive, browser based system that allows you to combine text, Python, and math into your browser. There are multiple ways to read these online, listed below.

binder

binder serves interactive notebooks online, so you can run the code and change the code within your browser without downloading the book or installing Jupyter.

Binder

nbviewer

The website http://nbviewer.org provides a Jupyter Notebook server that renders notebooks stored at github (or elsewhere). The rendering is done in real time when you load the book. You may use this nbviewer link to access my book via nbviewer. If you read my book today, and then I make a change tomorrow, when you go back tomorrow you will see that change. Notebooks are rendered statically - you can read them, but not modify or run the code.

nbviewer seems to lag the checked in version by a few days, so you might not be reading the most recent content.

GitHub

GitHub is able to render the notebooks directly. The quickest way to view a notebook is to just click on them above. However, it renders the math incorrectly, and I cannot recommend using it if you are doing more than just dipping into the book.

PDF Version

A PDF version of the book is available here

The PDF will usually lag behind what is in github as I don't update it for every minor check in.

Downloading and Running the Book

However, this book is intended to be interactive and I recommend using it in that form. It's a little more effort to set up, but worth it. If you install IPython and some supporting libraries on your computer and then clone this book you will be able to run all of the code in the book yourself. You can perform experiments, see how filters react to different data, see how different filters react to the same data, and so on. I find this sort of immediate feedback both vital and invigorating. You do not have to wonder "what happens if". Try it and see!

The book and supporting software can be downloaded from GitHub by running this command on the command line:

git clone --depth=1 https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python.git
pip install filterpy

Instructions for installation of the IPython ecosystem can be found in the Installation appendix, found here.

Once the software is installed you can navigate to the installation directory and run Juptyer notebook with the command line instruction

jupyter notebook

This will open a browser window showing the contents of the base directory. The book is organized into chapters, each contained within one IPython Notebook (these notebook files have a .ipynb file extension). For example, to read Chapter 2, click on the file 02-Discrete-Bayes.ipynb. Sometimes there are supporting notebooks for doing things like generating animations that are displayed in the chapter. These are not intended to be read by the end user, but of course if you are curious as to how an animation is made go ahead and take a look. You can find these notebooks in the folder named Supporting_Notebooks.

This is admittedly a somewhat cumbersome interface to a book; I am following in the footsteps of several other projects that are somewhat repurposing Jupyter Notebook to generate entire books. I feel the slight annoyances have a huge payoff - instead of having to download a separate code base and run it in an IDE while you try to read a book, all of the code and text is in one place. If you want to alter the code, you may do so and immediately see the effects of your change. If you find a bug, you can make a fix, and push it back to my repository so that everyone in the world benefits. And, of course, you will never encounter a problem I face all the time with traditional books - the book and the code are out of sync with each other, and you are left scratching your head as to which source to trust.

Companion Software

Latest Version

I wrote an open source Bayesian filtering Python library called FilterPy. I have made the project available on PyPi, the Python Package Index. To install from PyPi, at the command line issue the command

pip install filterpy

If you do not have pip, you may follow the instructions here: https://pip.pypa.io/en/latest/installing.html.

All of the filters used in this book as well as others not in this book are implemented in my Python library FilterPy, available here. You do not need to download or install this to read the book, but you will likely want to use this library to write your own filters. It includes Kalman filters, Fading Memory filters, H infinity filters, Extended and Unscented filters, least square filters, and many more. It also includes helper routines that simplify the designing the matrices used by some of the filters, and other code such as Kalman based smoothers.

FilterPy is hosted on github at (https://github.com/rlabbe/filterpy). If you want the bleeding edge release you will want to grab a copy from github, and follow your Python installation's instructions for adding it to the Python search path. This might expose you to some instability since you might not get a tested release, but as a benefit you will also get all of the test scripts used to test the library. You can examine these scripts to see many examples of writing and running filters while not in the Jupyter Notebook environment.

Alternative Way of Running the Book in Conda environment

If you have conda or miniconda installed, you can create an environment by

conda env update -f environment.yml

and use

conda activate kf_bf

and

conda deactivate kf_bf

to activate and deactivate the environment.

Issues or Questions

If you have comments, you can write an issue at GitHub so that everyone can read it along with my response. Please don't view it as a way to report bugs only. Alternatively I've created a gitter room for more informal discussion. Join the chat at https://gitter.im/rlabbe/Kalman-and-Bayesian-Filters-in-Python

License

Creative Commons License
Kalman and Bayesian Filters in Python by Roger R. Labbe is licensed under a Creative Commons Attribution 4.0 International License.

All software in this book, software that supports this book (such as in the the code directory) or used in the generation of the book (in the pdf directory) that is contained in this repository is licensed under the following MIT license:

The MIT License (MIT)

Copyright (c) 2015 Roger R. Labbe Jr

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.TION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contact

rlabbejr at gmail.com