Showing 3 open source projects for "mpv-player"

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  • 1
    Anime Player

    Anime Player

    Video player for improving quality of hand-drawn images

    A video player that enhances the quality of a hand-drawn image using Anime4K's high-performance scaling algorithm. This program is a video player written in the Python programming language using the PySimpleGUI graphical user interface library, an mpv media player, and the Anime4K scaling algorithm . Anime Player is designed to play video and audio files and includes functions such as opening files, URLs and folders, setting image scaling parameters using the Anime4K algorithm, creating an mpv config for watching videos using the Anime4K algorithm on Android, viewing help and information about tuning the algorithm. ...
    Downloads: 27 This Week
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  • 2
    ACNetGLSL

    ACNetGLSL

    Anime4KCPP Net re-implemented in GLSL for real-time anime upscaling

    ACNet is a CNN algorithm, implemented by Anime4KCPP, it aims to provide both high-quality and high performance. This GLSL implementation can be used in MPV player, it is cross-platform. Windows users can also use Anime4KCPP DirectShow Filter for MPC-HC/BE or potplayer. Download the glsl file and MPV player. Copy glsl to the root directory of MPV. Create a file named mpv.conf in the root directory of MPV, and add the following statement (Assume the glsl file name is ACNet.glsl). When playing the video, press Shift + i and then 2 to check if it is enabled.
    Downloads: 0 This Week
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  • 3
    AviSynth AiUpscale v1.2.0

    AviSynth AiUpscale v1.2.0

    AviSynth+ implementation of Super-Resolution Convolutional Neural

    An AviSynth+ implementation of some Super-Resolution Convolutional Neural Networks. Independent luma/chroma upscaling and chroma resampling. Two modes for Video/Photography and Line Art. KrigBilateral option for chroma upscaling/resampling. mpv user shaders of all models for real-time upscaling. Copy AiUpscale.avsi and the Shaders folder to the AviSynth+ plugins folder. The low resolution images were generated using the bicubic filter with Catmull-Rom settings, which is the method commonly used for training super-resolution networks, including those tested here. Note however that as an exception to this, the Anime4K models were trained using the average area downsampling method. ...
    Downloads: 0 This Week
    Last Update:
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