Showing 5 open source projects for "cuda gpu"

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    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: 28 This Week
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  • 2
    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...
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    Downloads: 30 This Week
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  • 3
    Imaging Instruments Lite

    Imaging Instruments Lite

    Image processing App for Windows Desktop

    Imaging Instruments lite is a comprehensive image processing application developed following the Model-View-Controller (MVC) design pattern, utilizing Python, Tkinter, and OpenCV. It provides users with image manipulation capabilities, leveraging multi-threading with OpenMP and GPU acceleration using CUDA-C. Fueled by yerba mate and a passion for coding. Created by Agustin Tortolero. website: https://agustintortolero.pythonanywhere.com/ Source code: https://github.com/agustinTortolero/Imaging-Instruments-lite
    Downloads: 0 This Week
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  • 4
    A2M — Audio to MIDI

    A2M — Audio to MIDI

    A2M is a desktop app that converts AUDIO TO MIDI in one click.

    A2M (Audio To MIDI) is a simple desktop tool for transcribing local audio files into MIDI files with one click. It is designed primarily for piano recording transcription, and works best on solo piano recordings. Using A2M is straightforward: Select an audio file, click Convert, and the application generates a MIDI file automatically in your Downloads/A2M folder. All processing is done locally on your device, no uploads, no accounts, and no telemetry. The app runs on CPU by...
    Downloads: 25 This Week
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  • 5
    Stable Diffusion in Docker

    Stable Diffusion in Docker

    Run the Stable Diffusion releases in a Docker container

    Run the Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint. Run the Stable Diffusion releases on Huggingface in a GPU-accelerated Docker container. By default, the pipeline uses the full model and weights which requires a CUDA capable GPU with 8GB+ of VRAM. It should take a few seconds to create one image. On less powerful GPUs you may need to modify some of the options; see the Examples section for more details. If you lack a suitable GPU you can set the options --device cpu and --onnx instead. ...
    Downloads: 2 This Week
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