Showing 4 open source projects for "linux-tools"

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  • 1
    Clarity AI Upscaler

    Clarity AI Upscaler

    AI Image Upscaler & Enhancer

    ...Unlike traditional interpolation-based upscaling algorithms, the system generates additional visual information that improves perceived clarity and sharpness. The project is intended as a free and open alternative to commercial AI upscaling tools, allowing developers and digital artists to run the technology locally or integrate it into their own workflows. The repository includes a full application environment with scripts, configuration files, and model support that allow users to run the upscaler as a standalone tool or integrate it into other pipelines.
    Downloads: 10 This Week
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  • 2
    QualityScaler

    QualityScaler

    Image/video AI upscaler app (BSRGAN)

    Qualityscaler is a Windows app that uses BSRGAN Artificial Intelligence to enhance, enlarge and reduce noise in photographs and videos. QualityScaler is completely written in Python, from the backend to the front end. Image/list of images upscale. Video upscale. Drag&drop files [image / multiple images/video] Automatic image tiling and merging to avoid gpu VRAM limitation. Resize image/video before upscaling. Multiple Gpu support. Compatible images - png, jpeg, bmp, webp, tif. Compatible...
    Downloads: 83 This Week
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  • 3
    Dream Textures

    Dream Textures

    Stable Diffusion built-in to Blender

    Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what...
    Downloads: 16 This Week
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  • 4
    Image Super-Resolution (ISR)

    Image Super-Resolution (ISR)

    Super-scale your images and run experiments with Residual Dense

    The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few...
    Downloads: 0 This Week
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