Showing 4 open source projects for "gpu image"

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  • 1
    CycleGAN and pix2pix in PyTorch

    CycleGAN and pix2pix in PyTorch

    Image-to-Image Translation in PyTorch

    ...The code supports standard training and inference pipelines, and as of recent updates, compatibility with the latest Python and PyTorch versions (e.g. Python 3.11, PyTorch 2.4) as well as support for distributed/multi-GPU training for scalable workflows. Because of its flexibility, users can apply it to many tasks: e.g. style transfer between domains (e.g. season changes, art-to-photo, etc.), mapping sketches/edges to real images, image colorization, day-to-night, photo enhancement, and more.
    Downloads: 0 This Week
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  • 2
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
    Downloads: 2 This Week
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  • 3
    PyMapStitcher-3---Cuda-Maps-Downloader

    PyMapStitcher-3---Cuda-Maps-Downloader

    A low ram maps downloader to keep your ram free.

    PyMapStitcher 3 is a desktop application for downloading, stitching, and exporting very large satellite map areas as GeoTIFF/BigTIFF files. The software supports GPU acceleration with NVIDIA CUDA and CuPy, direct GeoTIFF georeferencing, WebView-based map selection, and high-performance tile processing for large-scale mapping workflows.
    Downloads: 2 This Week
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  • 4

    cphcttoolbox

    Cph CT Toolbox is a selection of Computed Tomography tools

    Copenhagen Computed Tomography Toolbox is a collection of applications and libraries for flexible and efficient CT reconstruction. The toolbox apps generally take a set of projections (X-ray intensity measurements) and filter and back project them in order to recreate the image or volume that the projections represent. The project includes both mostly informative CPU implementations and highly efficient GPU implementations. Regular releases are hosted at the Python Package Index.
    Downloads: 0 This Week
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