Showing 12 open source projects for "using"

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  • Atera all-in-one platform IT management software with AI agents Icon
    Atera all-in-one platform IT management software with AI agents

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  • AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

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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: 18 This Week
    Last Update:
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  • 2
    Real-ESRGAN GUI

    Real-ESRGAN GUI

    Cross-platform GUI for image upscaler Real-ESRGAN

    ...According to actual measurements, arm64the single-architecture performance is better than universal2the dual- architecture Mac on the Apple chip, so Apple chip users are advised to pack arm64single-architecture applications by themselves. Real-ESRGAN can only enlarge the input image with a fixed 2-4x magnification (related to the selected model). This functionality is achieved by downsampling using a conventional scaling algorithm after multiple calls to Real-ESRGAN. Split each frame of the GIF and record the duration, zoom in one by one and then merge. Drag an image file or directory to any position in the window, and its path can be automatically set as the input.
    Downloads: 134 This Week
    Last Update:
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  • 3
    AI Upscaler for Blender

    AI Upscaler for Blender

    AI Upscaler for Blender using Real-ESRGAN

    Blender add-on to dramatically reduce render times using the Real-ESRGAN upscaler. Rendering an HD image in Blender takes 37 minutes. Upscaling can render a similar quality image in 5 mins total. Any PC or laptop can now do 3D rendering. 4k images can be rendered in the time it would take to render HD 1080p images. HD 1080p images can be rendered in record time on low-end hardware. Installation is easy.
    Downloads: 2 This Week
    Last Update:
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  • 4
    enhancr

    enhancr

    Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT

    enhancr is an elegant and easy to use GUI for Video Frame Interpolation and Video Upscaling which takes advantage of artificial intelligence - built using node.js and Electron. It was created to enhance the user experience for anyone interested in enhancing video footage using artificial intelligence. The GUI was designed to provide a stunning experience powered by state-of-the-art technologies without feeling clunky and outdated like other alternatives. It features blazing-fast TensorRT inference by NVIDIA, which can speed up AI processes significantly. ...
    Downloads: 36 This Week
    Last Update:
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  • Outgrown Windows Task Scheduler? Icon
    Outgrown Windows Task Scheduler?

    Free diagnostic identifies where your workflow is breaking down—with instant analysis of your scheduling environment.

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  • 5
    AI Models

    AI Models

    A repository of trained models

    All models (at least currently) are supported by chaiNNer, an upscaling GUI that allows for both very simple and very complex tasks to be completed in a nice manner where you "chain" nodes together. Highly recommended for images. If you're looking to upscale videos using the models then use enhancr simply due to the fact that it supports TensorRT, which will allow you to upscale videos at incredible speeds! The GUI is one of the best looking applications out there and is personally my go to option. While yes builds are paid, it is well worth your money and beats any other GUI out there currently.
    Downloads: 3 This Week
    Last Update:
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  • 6
    G2SConverter

    G2SConverter

    Convert models from GoldSource engine to Source engine with AI

    Convert models from GoldSource engine to the Source engine with AI. This utility converts GoldSource engine models to Source engine models. A feature of this utility is the ability to improve the quality of textures of models using Upscaling, deblurring, and normal map generating. All operations to improve the quality of textures are performed by neural networks. To improve the quality of the texture, it is first Upscaled using RealESRGAN. The user can select scaling factor: x2, x4 or x8. After the Upscaling procedure, the texture is deblured using the Scale-recurrent Network for Deep Image Deblurring. ...
    Downloads: 0 This Week
    Last Update:
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  • 7
    UpscalerJS

    UpscalerJS

    Image Upscaling in Javascript. Increase image resolution up to 4x

    Image Upscaling in Javascript. Increase image resolution up to 4x using Tensorflow.js. Open source, browser/Node compatibility, and completely free to use under the MIT license. Scale images up to 4x their original size, all in Javascript. UpscalerJS ships with pre-trained models in the box covering a wide variety of use cases. Or bring your own! Browser, Node (CPU and GPU-accelerated), and Service Worker environments all supported.
    Downloads: 0 This Week
    Last Update:
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  • 8
    VSGAN

    VSGAN

    VapourSynth Single Image Super-Resolution Generative Adversarial

    ...Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS) inputs. Using VapourSynth you can pass a Video directly to VSGAN, without any frame extraction needed. Any edit you make in the VapourSynth script with or without VSGAN can be re-used for any other video. VSGAN is released under the MIT License, ensuring it will stay free, with the ability to be used commercially.
    Downloads: 0 This Week
    Last Update:
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  • 9
    Easy Upscale

    Easy Upscale

    A simple image upscaler application using EDSR, ESPCN, FSRCNN, etc.

    ...The concept of the application is an application to upgrade/enhance image quality. The main theme is queues, we implement circular queues for pooling/storing a list of images to be upscaled. Gui creation is made manually using the tkinter library. For the upscale process itself, it uses the OpenCV library with a model obtained from open source. Checked using vermin. Minimum required versions: 3.6 Incompatible versions: 2.
    Downloads: 0 This Week
    Last Update:
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  • Failed Payment Recovery for Subscription Businesses Icon
    Failed Payment Recovery for Subscription Businesses

    For subscription companies searching for a failed payment recovery solution to grow revenue, and retain customers.

    FlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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  • 10
    Upscale

    Upscale

    This program is upscaling any image by a factor 2 using an algorithm

    This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV.
    Downloads: 0 This Week
    Last Update:
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  • 11
    MNIST-WGAN

    MNIST-WGAN

    A C# WGAN

    This project generates hand-written digits from the MNIST dataset using WGAN architecture. While debugged, a few lingering issues may remain, if you encounter any please submit them and they will be resolved. The sources and features of the project can be found in the wiki. Before use, one should verify that the network architecture is as-desired. This may be done with the GUI to the right of the number display.
    Downloads: 0 This Week
    Last Update:
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  • 12
    Super-résolution via CNN

    Super-résolution via CNN

    Super resolution using a CNN, based on the work of the DGtal team

    Super-resolution using a CNN, based on the work of the DGtal team. First of all, an Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended to parallelize the CNN. You will then need to install CUDA. No CUDA = dozens of times slower. This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test batch and lrto the learning rate. ...
    Downloads: 0 This Week
    Last Update:
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