Open Source Linux Raspberry Pi Software - Page 2
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Raspberry Pi Software for Linux
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berryboot
Berryboot -- Boot menu / OS installer for ARM devices
Berryboot is a simple operating system installer and boot selection screen for ARM devices such as the Raspberry Pi and Cubieboard. It allows you to put multiple Linux distribution on a single SD card. -
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DeepSpeech
Open source embedded speech-to-text engine
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page. -
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avbuild
ffmpeg build tool and prebuilt packages for all platforms
iOS, android, raspberry pi, windows store, windows desktop, linux, macOS etc. Multiple toolchains support, include gcc, clang, vs2013, vs2015, vs2017. Hardware accelerated decoders and encoders support. Source code: https://github.com/wang-bin/avbuild -
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Raspberry Pi GCC Toolchains
CI maintained precompiled GCC ARM/ARM64 Toolchains for Raspberry Pi
This project provides latest Raspberry Pi hardware optimized GCC Cross Compiler & Native (ARM & ARM64) automated Build-Scripts and Precompiled standalone Toolchains binaries, that will save you tons of time & thereby helps you get quickly started with software development on Pi. -
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FreeJ2ME
A J2ME emulator for Windows, Linux, and Raspberry Pi
FreeJ2ME is a simple J2ME emulator with a focus on old mobile phone games. It was designed to run on Windows, desktop Linux, and on the Raspberry Pi 3 using Libretro and Retroarch as provided by RetroPie. It supports some games not playable using MicroEmulator and Kemulat0r, though it does not support every game those play. At the moment, it's best to have all three if you're interested in those types of games. Some games only run at specific resolutions. Per-game configuration is available from the menu (by pressing esc). Preferences are saved and will automatically load. Games automatically scale with the window size, making it easy to play games designed for smaller screen sizes. The Java portion can be built using Apache Ant with the build.xml file provided. The Libretro core can be built using the build.sh script. Installation instructions for the Libretro core for RetroPie are included. Follow the development process here: https://github.com/hex007/freej2me -
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RaspEX Kodi
RaspEX Kodi 64bit is a perfect system for Raspberry Pi 5
RaspEX Kodi Build 260117 with LXQt/Kodi 21.3 ("Omega") is made especially for the new Raspberry Pi 5. In RaspEX Kodi I’ve added the LXQt 2.2 Desktop with many useful applications, such as NetworkManager. Makes it easy to configure your wireless network. I’ve also upgraded Kodi to version 21.3 "Omega" , which makes it possible to include many useful Add-ons. PERFORMANCE RaspEX Kodi is now very fast and responsive. And the video performance is brilliant. Almost as good as if you use a new "big" computer. INSTALLATION Use Rufus in Windows to transfer the IMAGE file to a SD card. USED KERNEL Kernel 6.12.40-exton-v8-16k+ for Rpi5. You can ONLY run this RaspEX Kodi version on a Raspberry Pi 5. ABOUT Kodi 21.3 Version 21.3 ("Omega") was released 251216. ABOUT the YouTube Add-on in Kodi I have created permanent API keys so that the YouTube Add-on will work. -
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Linux Air Combat
Combat Flight Simulator for LINUX. WW2. Network and VOIP. Open-source.
WW2 Combat Flight Simulator. Free. Current Version: 9.92. This is now the world's leading open-source combat flight sim for LINUX. Linux Air Combat ("LAC") runs on almost any desktop LINUX system (even Steam Deck & Raspberry Pi) and generates smooth, high-performance flight. If it runs TOO fast on your hardware (framerates beyond 100 FPS), you should activate LAC's built-in FrameRate Limiter as documented here: https://askmisterwizard.com/2019/LinuxAirCombat/FrameRateLimiter.htm Clean, open source code provides an option to compile yourself, or use our precompiled executable AppImage to eliminate compiling on all popular X86 LINUX distros. Control flight and views with mouse and keyboard, console game controller, or joystick, all easily configured from prominent configuration menus. Learn all about LAC from our primary, official Web Page: http://askmisterwizard.com/2019/LinuxAirCombat/LacOnlineDocs.htm Recent video clip: https://youtu.be/C77C-e8axWs -
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GeigerLog
Python program for Geiger counters and Environmental Sensors
GeigerLog is a combination of data logger, presenter, and analyzer, and is now released in version 2.1! Based on Python (Version 3), it runs on Linux, Windows, Macs, Raspberry Pi, and other. GeigerLog is WiFi-enabled for servers and clients; it can be monitored by SmartPhone. Initially developed for Geiger counters, it is now a more universal tool, which equally well handles data like temperature, air-pressure, humidity, CO2. Continues to support Geiger counters like GQ Electronic's GMC-300/500/600 , RadMon, RadPro, Gamma-Scout, audio-click and other low-cost Geiger counters, IoT devices, I2C based sensors, GQ EMF devices. GeigerLog reads data from devices, saves them to databases, prints to screen and plots as auto-updated, customizable graphs. Quality control using Statistics, Scatter, Poisson, FFT & Autocorrelation, and more. Gamma Spectra - can be displayed, calibrated, and evaluated in GeigerLog! The Raspberry Pi 4, 5 qualify as GeigerLog hosts. -
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Binance Trading Bot
Automated Binance trading bot, trade multiple cryptocurrencies
Automated Binance trading bot. Trade multiple cryptocurrencies. Buy low/sell high with Grid Trading. Integrated with TradingView technical analysis. This bot is using the concept of trailing buy/sell order which allows following the price fall/rise. Trailing Stop Orders About Trailing Stop Orders Concept you can find at Binance Official document. Place orders at a fixed value or percentage when the price changes. Using this feature you can buy at the lowest possible price when buying down and sell at the highest possible price when selling up. The bot supports multiple buy/sell orders based on the configuration. The bot is using MongoDB to provide a persistence database. However, it does not use the latest MongoDB to support Raspberry Pi 32bit. Used MongoDB version is 3.2.20, which is provided by apcheamitru. The bot is tested/working with Linux and Raspberry Pi 4 32bit. Other platforms are not tested. -
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RetroPie BIOS
Full BIOS collection for RetroPie
RetroPie BIOS is a curated collection of BIOS files intended for use with the RetroPie emulation platform, providing the essential firmware required to run a wide range of classic gaming systems. The repository organizes BIOS files for numerous consoles and arcade systems, ensuring compatibility with RetroPie and related emulation environments. Each file in the collection has been verified against reference databases such as the Libretro system definitions, ensuring accuracy and reliability. The project simplifies the process of setting up emulation systems by consolidating required BIOS files into a single, organized package that users can directly integrate into their RetroPie installation. It also includes checksum validation mechanisms, allowing users to verify file integrity and ensure that BIOS files match expected standards. By maintaining a structured and verified dataset, the repository reduces common issues associated with missing or incorrect BIOS files. -
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Blynk C++ Library
Blynk library for embedded hardware
Blynk is the most popular Internet of Things platform for connecting any hardware to the cloud, designing apps to control them, and managing your deployed products at scale. With Blynk Library you can connect over 400 hardware models (including ESP8266, ESP32, NodeMCU, all Arduinos, Raspberry Pi, Particle, Texas Instruments, etc.)to the Blynk Cloud. With Blynk apps for iOS and Android apps you can easily drag-n-drop graphic interfaces for any DIY or commercial project. It's a pure WYSIWG experience, no coding on iOS or Android required. Hardware can connect to Blynk Cloud (open-source server) over the Internet using hardware connectivity available on your board (like ESP32), or with the use of various shields (Ethernet, WiFi, GSM, LTE, etc). Blynk Cloud is available for every user of Blynk for free. Direct connection over Bluetooth is also possible. Check the included examples on how to use different types of connections (transports) and explore Blynk features. -
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FarmBot OS
The operating system and all related software
The operating system and all related software that runs on FarmBot's Raspberry Pi. The FarmBot OS release page has moved to my.farm.bot/os. Old versions of FarmBot OS can still be found. Get configured over WiFi, mitigating the need to plug in a mouse, keyboard, or screen. Communicate with the web application over WiFi or ethernet so that it can synchronize (download) sequences, regimens, farm designs, events, and more; upload logs and sensor data; and accept real-time commands. Communicate with the Farmduino to send G and F commands and receive sensor and encoder data. Take photos with a USB or Raspberry Pi camera, and upload the photos to the web application. You must use a .img writing tool to write FarmBot OS onto the microSD card. We recommend downloading and installing balenaEtcher for this purpose. -
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K3s
Lightweight Kubernetes
Lightweight Kubernetes. Production-ready, easy to install, half the memory, all in a binary less than 100 MB. K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. K3s is packaged as a single <70MB binary that reduces the dependencies and steps needed to install, run and auto-update a production Kubernetes cluster. Both ARM64 and ARMv7 are supported with binaries and multiarch images available for both. K3s works great on something as small as a Raspberry Pi to an AWS a1.4xlarge 32GiB server. -
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AmogOS
Among-us themed OS. As seen on Reddit and Youtube
A parody OS inspired by Among Us. (pronounced A-mog-O-S). -
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Wiki.js
A modern and powerful wiki app built on Node.js
Works on virtually any platform and is compatible with either PostgreSQL, MySQL, MariaDB, MS SQL Server or SQLite! Manage all aspects of your wiki using the extensive and intuitive admin area. Running on the blazing-fast Node.js engine, Wiki.js is built with performance in mind. Fully customize the appearance of your wiki, including a light and dark mode. You'll be ready to go within minutes! Step-by-step install guides are available for all platforms. Make your wiki public, completely private, or a mix of both. Whether it's on a tiny Raspberry Pi or on a high-performance VM in the cloud, Wiki.js intelligently makes use of the available resources. Built-in authentication with self-registration and password recovery capabilities. Use 3rd-party authentication services like Google, Facebook, Microsoft, GitHub, Discord, Slack and more. Add an extra layer of security using two-factor authentication for supported authentication modules. -
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raspberry-gpio-python
A Python module to control the GPIO on a Raspberry Pi
To get started with RPi.GPIO, it would be worthwhile reading the examples in the project wiki (link above). Note that this module is unsuitable for real-time or timing critical applications. This is because you can not predict when Python will be busy garbage collecting. It also runs under the Linux kernel which is not suitable for real time applications - it is multitasking O/S and another process may be given priority over the CPU, causing jitter in your program. If you are after true real-time performance and predictability, buy yourself an Arduino! (see http://www.arduino.cc ) Note that the current release does not support SPI, I2C, 1-wire or serial functionality on the RPi yet. This is planned for the near future - watch this space! -
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VitalSignsCapture
Download data from medical device interfaces in ICU & Anaesthesia
A C# .NET app to download or capture data from several medical device interfaces such as Datex AS3 S/5 Anesthesia, Philips Intellivue, GE Dash, Mindray HL7, Spacelabs, Draeger Infinity, Draeger HL7 patient monitors, GE Engstrom, Draeger (MedibusX), Maquet (Servo-i, Servo-U & Flow-i), Puritan Bennett ventilators, Covidien BIS Vista cerebral monitor, Fresenius Agilia, Alaris Carefusion, BBraun Spacecom syringe and volumetric pumps, Roche Cobas ASTM ABG analyzers. Requires Visual Studio 2022, .NET 8 or Visual Studio for Mac to compile. Support for capture from other monitors is planned in future. -
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Coolify
An open-source & self-hostable Heroku / Netlify / Vercel alternative
Coolify is an open-source & self-hostable alternative to Heroku / Netlify / Vercel / etc. It helps you manage your servers, applications, and databases on your own hardware; you only need an SSH connection. You can manage VPS, Bare Metal, Raspberry PIs, and anything else. Imagine having the ease of a cloud but with your own servers. That is Coolify. No vendor lock-in, which means that all the configurations for your applications/databases/etc are saved to your server. So, if you decide to stop using Coolify, you could still manage your running resources. You lose the automation and all the magic. -
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GPUImage 2
Framework for GPU-accelerated video and image processing
GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. By relying on the GPU to run these operations, performance improvements of 100X or more over CPU-bound code can be realized. This is particularly noticeable in mobile or embedded devices. On an iPhone 4S, this framework can easily process 1080p video at over 60 FPS. On a Raspberry Pi 3, it can perform Sobel edge detection on live 720p video at over 20 FPS. -
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Mirrorcast
Open Source Alternative to Chromecast, Mirror Desktop and Play media r
The idea is to replicate what Chromecast can do in regards to screen mirroring and streaming media to a remote display. Google chromes screen mirroring feature works well when used with a receiver such as Chromecast but this is a proprietary solution and audio does not work for desktop mirroring on some operating systems. At the moment, there is only a client for Debian/Ubuntu Operating systems and a server/receiver application for Raspberry pi. Mirrorcast aims to be a low latency screen mirroring solution with high-quality video and audio at 25-30fps, the later is why we will not use something like VNC. Mirrorcast uses up about the same amount of system resources as google chromes cast feature. The delay is less than 1 second on most networks. To achieve this we will use existing FOSS software such as ffmpeg, mpv, and omxplayer. -
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Porcupine
On-device wake word detection powered by deep learning
Build always-listening yet private voice applications. Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. Self-service. Developers can train custom wake word models using Picovoice Console. Porcupine is the right product if you need to detect one or a few static (always-listening) voice commands. If you want to create voice experiences similar to Alexa or Google, see the Picovoice platform. -
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RF24
OSI Layer 2 driver for nRF24L01 on Arduino & Raspberry Pi/Linux
Optimized high-speed driver for nRF24L01(+) 2.4GHz wireless transceiver. More compliant with the manufacturer specified operation of the chip, while allowing advanced users to work outside the recommended operation. Utilize the capabilities of the radio to their full potential via Arduino. More reliable, responsive, bug-free and feature-rich. Easy for beginners to use, with well-documented examples and features. Consumed with a public interface that's similar to other Arduino standard libraries. OSI Network Layer for multi-device communication. Create a home sensor network. -
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RaspiBolt
Bitcoin & Lightning full node on a Raspberry Pi
Build your own “do-everything-yourself” Bitcoin full node that will make you a sovereign peer in the Bitcoin and Lightning network. With this guide, you can set up a Bitcoin and Lightning node from scratch, doing everything yourself. You will learn about Linux, Bitcoin, and Lightning. As a result, you’ll have your very own RaspiBolt node, built by you and no one else. Let your node validate your own Bitcoin transactions. No need to ask someone else to tell you what’s happening in the Bitcoin network. Connect your wallets to your node so that you no longer need to reveal their whole financial history to external servers. Run your own Lightning node for everyday payments and help building a robust, decentralized Bitcoin Lightning network. Full client with stable long-term channels and web-based and mobile-based management interfaces. We strive to give foolproof instructions. But the goal is also to do everything ourselves. -
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AWS IoT Device SDK v2 for Python
Next generation AWS IoT Client SDK for Python
Next-generation AWS IoT Client SDK for Python using the AWS Common Runtime. This document provides information about the AWS IoT Device SDK v2 for Python. This SDK is built on the AWS Common Runtime, a collection of libraries (aws-c-common, aws-c-io, aws-c-mqtt, aws-c-compression, aws-c-http, aws-c-cal, aws-c-auth, s2n ...) written in C to be cross-platform, high-performance, secure, and reliable. The libraries are bound to Python by the awscrt package (PyPI). AWS IoT provides the cloud services that connect your IoT devices to other devices and AWS cloud services. AWS IoT provides device software that can help you integrate your IoT devices into AWS IoT-based solutions. If your devices can connect to AWS IoT, AWS IoT can connect them to the cloud services that AWS provides. AWS IoT lets you select the most appropriate and up-to-date technologies for your solution.
