Open Source Swift Raspberry Pi Software

Swift Raspberry Pi Software

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Browse free open source Swift Raspberry Pi Software and projects below. Use the toggles on the left to filter open source Swift Raspberry Pi Software by OS, license, language, programming language, and project status.

  • QA Wolf | We Write, Run and Maintain Tests Icon
    QA Wolf | We Write, Run and Maintain Tests

    For developer teams searching for a testing software

    QA Wolf is an AI-native service that delivers 80% automated E2E test coverage for web & mobile apps in weeks not years.
    Learn More
  • Point of Sale. Powerful and Simple. Icon
    Point of Sale. Powerful and Simple.

    For retail store owners and multi-location retail operations needing a tool to manage sales, inventory, staff and channels in one place

    Vibe Retail is an all-in-one retail point-of-sale and operations platform built for single-store and multi-location retailers seeking to unify inventory, sales, staff and customer data from one mobile-friendly interface. The system lets you track inventory across locations and warehouses, handle item variations (size, color, material), manage purchase orders and supplier deliveries, print custom barcodes, and transfer stock between stores in real time. On the sales side, Vibe supports multiple payment types (cards, cash, checks, gift cards, EBT), layaway workflows, serial number tracking, delivery management, loyalty programs and branded receipts. Retailers can integrate with online platforms (such as Shopify and WooCommerce), sync in-store and online sales, access 40+ real-time reports on sales, inventory and performance, set up promotions and discounts, and print receipts from mobile devices.
    Learn More
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    GPUImage 2

    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.
    Downloads: 0 This Week
    Last Update:
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