Showing 3 open source projects for "cuda gpu"

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  • 1
    rembg

    rembg

    Rembg is a tool to remove images background

    Rembg is a powerful tool that utilizes AI (specifically U^2-Net) to automatically remove backgrounds from images, offering a streamlined command-line interface and Docker support. It's ideal for batch processing and integrates smoothly into workflows
    Downloads: 8 This Week
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  • 2
    ArrayFire

    ArrayFire

    ArrayFire, a general purpose GPU library

    ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if...
    Downloads: 0 This Week
    Last Update:
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  • 3
    HIPAcc

    HIPAcc

    Heterogeneous Image Processing Acceleration (HIPACC) Framework

    HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages.
    Downloads: 0 This Week
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