Showing 2 open source projects for "machine vision"

View related business solutions
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • MyQ Print Management Software Icon
    MyQ Print Management Software

    SAVE TIME WITH PERSONALIZED PRINT SOLUTIONS

    Boost your digital or traditional workplace with MyQ’s secure print and scan solutions that respect your time and help you focus on what you do best.
    Learn More
  • 1
    Posturr

    Posturr

    A macOS app that blurs your screen when you slouch

    Posturr is a macOS application that uses computer vision and machine learning — specifically Apple’s Vision framework — to monitor a user’s posture in real time and encourage healthier habits by visually responding when poor posture is detected. Running locally on the Mac, the app accesses the built-in camera to detect when you slouch or sit incorrectly, and when it recognizes sustained slouching, it applies a progressive visual blur to the screen as a subtle but effective cue to straighten up. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    GPUImage 2

    GPUImage 2

    Framework for GPU-accelerated video and image processing

    ...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: 8 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB