Showing 5 open source projects for "morphological image processing"

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  • 1
    Dream Textures

    Dream Textures

    Stable Diffusion built-in to Blender

    ...Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended.
    Downloads: 7 This Week
    Last Update:
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  • 2
    Waifu2x-Extension-GUI

    Waifu2x-Extension-GUI

    Photo/Video/GIF enlargement using machine learning

    Image & GIF & Video Super-Resolution using Deep Convolutional Neural Networks. Built-in image processing algorithm: Waifu2x / SRMD / RealSR / Anime4K / ACNet Built-in image processing engine: Waifu2x-caffe / Waifu2x-converter / Waifu2x-ncnn-vulkan / SRMD-ncnn-vulkan / RealSR-ncnn-vulkan / Anime4KCPP Github: https://github.com/AaronFeng753/Waifu2x-Extension-GUI
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    Downloads: 587 This Week
    Last Update:
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  • 3
    Batch Auto Upscale Images xBRZ

    Batch Auto Upscale Images xBRZ

    Auto Upscale All Images Using xBRZ 234x

    ...Unlike AI-driven upscaling, which takes gigabytes of space and enormous processing power, xBRZ is lightweight and can run on a potato PC! Only 5MB! (Source code is included with the program .zip file.)
    Downloads: 5 This Week
    Last Update:
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  • 4
    Warlock-Studio

    Warlock-Studio

    AI Suite for upscaling, interpolating & restoring images/videos

    v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system...
    Downloads: 20 This Week
    Last Update:
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  • 5

    waifu2x-cpu-torch-vks

    waifu2x fork without CUDA

    The original is here: https://github.com/nagadomi/waifu2x Differences: - CPU only, no CUDA needed; - double-precision version; - GPU and CPU-trained models (on the fly conversion in memory); - adapted for Lua v5.2 (works with Torch 7 on x32 Ubuntu). 31-12-2016: - removed unneeded data copies, left from CUDA processing; - removed large duplicate files (see "ReadMe" before use).
    Downloads: 0 This Week
    Last Update:
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