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Showing 18 open source projects for "using"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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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. ... -
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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. -
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Waifu2x-Extension-GUI
Video, Image and GIF upscale/enlarge(Super-Resolution)
Photo/Video/GIF enlargement and Video frame interpolation using machine learning. Waifu2x-Extension-GUI is a video, image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet. The beta build has a faster update cycle than the stable build, which allows you to experience the latest features of the software in advance. -
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SeedVR2 Upscaler ComfyUI
Official SeedVR2 Video Upscaler for ComfyUI
...This project packages the SeedVR2 architecture as a custom node for ComfyUI, letting users upscale low-resolution video or imagery inside a node-based interface without needing to write code manually. The underlying SeedVR2 model is known for delivering high-quality video enhancement with strong temporal consistency and improved detail preservation by using diffusion-based techniques that are trained specifically on video sequences. Within the ComfyUI ecosystem, the upscaler integrates with existing nodes and pipelines, making it easier to combine with other processing steps such as denoising, color correction, or format conversion. Enthusiasts often use it for workflows ranging from hobby video enhancement to professional content improvement. -
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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. -
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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. ... -
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SuperImage
Sharpen your low-resolution pictures with the power of AI upscaling
...SuperImage is a neural network-based image upscaling application for Android built with the MNN deep learning framework and Real-ESRGAN. The input image is processed in tiles on the device GPU, using a pre-trained Real-ESRGAN model. The tiles are then merged into the final high-resolution image. This application requires Vulkan or OpenCL support and Android 7 or above. -
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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. -
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MAGPIE
A real-time upscaling software that can upscale any application
...Run Magpie and keep it open in the background / minimize to tray. Open the desired game / visual novel in windowed mode. Use Alt + F11 hotkeys to upscale your game window using magpie. Modify the ScaleModels.json if you want your very own custom stack of presets to use with Magpie. You'll need to start Magpie as admin if you want to upscale a game that's also running with admin privileges. Uses the CAS filter from FSR. Higher overall contrast and sharpness. I used this one instead of the standard CAS cause IMO it makes the details stand out a lot more. ... -
Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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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. ... -
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FFmpegUpscalerHelper
A simple program with a UI for exporting video to png and encoding png
A simple program with a UI for exporting video to png and encoding png images to video using FFmpeg, for the purpose of upscaling. A simple program with a UI for exporting video to png and encoding png images to video using FFmpeg, for the purpose of upscaling. This program does not upscale your video, it's a tool to be used to save time for your upscaling process. Instead of opening CMD yourself and navigating to your ffmpeg location and then enter the command, this program does all that for you. ... -
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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. -
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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. -
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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. -
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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. -
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AviSynth AiUpscale v1.2.0
AviSynth+ implementation of Super-Resolution Convolutional Neural
...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. The AiUpscale models used for all datasets were the "Photo" models, except for the Manga109 dataset for which the "LineArt" models were used. ... -
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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. -
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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. ...
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