Showing 4 open source projects for "gpu-g"

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    Stats

    Stats

    macOS system monitor in your menu bar

    Stats currently supported on macOS 10.13 (High Sierra) and higher. Stats is an application that allows you to monitor your macOS system. CPU utilization, GPU utilization, memory usage, disk utilization, sensors information (Temperature/Voltage/Power), battery level, network usage, fans speed, fan control, and Bluetooth devices. Supports many languages, such as English, Polski, Українська, Русский, and many more. You can help by adding a new language or improve existing translation.
    Downloads: 26 This Week
    Last Update:
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  • 2
    SFSafe Symbols

    SFSafe Symbols

    Safely access Apple's SF Symbols using static typing

    At WWDC 2019, Apple announced a new library of icons that came included with that year's new operating system versions. To browse them, there's a dedicated Mac app called SF Symbols. You can be sure your symbol code won't crash due to typos or symbol availability issues. This is because all symbols are tested via a CI (on the latest iOS & tvOS versions and also some earlier OS versions). Lookups in the SF Symbols app (e. g. about available layersets, available localizations & the look...
    Downloads: 0 This Week
    Last Update:
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  • 3
    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...
    Downloads: 0 This Week
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  • 4
    Bender

    Bender

    Easily craft fast Neural Networks on iOS

    .... Either way, it just takes a few minutes. Bender suports the most common ML nodes and layers but it is also extensible so you can write your own custom functions. With Core ML, you can integrate trained machine learning models into your app, it supports Caffe and Keras 1.2.2+ at the moment. Apple released conversion tools to create CoreML models which then can be run easily. Finally, there is no easy way to add additional pre or post-processing layers to run on the GPU.
    Downloads: 0 This Week
    Last Update:
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