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Showing 18 open source projects for "using"
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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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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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Video Object Remover – Frame-Accurate
🎥 A free & open-source Python tool to remove unwanted objects from videos frame-by-frame using brush masking and AI inpainting (OpenCV + FFmpeg). EXE included.
Video Object Remover – Frame Accurate Edition is a free and open-source desktop application that helps you remove unwanted objects, logos, or watermarks from videos using brush-based masking and AI inpainting. The tool extracts video frames using FFmpeg, lets you mask objects frame-by-frame, and removes them using OpenCV. Built with Python and Tkinter, it features a modern dark-themed GUI, adjustable brush tool, zoom control, and real-time logging. The cleaned video is rebuilt and exported with original quality. ... -
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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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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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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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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. -
The complete IT asset and license management platformThe platform seamlessly integrates with 100+ IT systems, including MDM, RMM, IDP, SSO, HR, finance, helpdesk tools, and more.
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10
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. -
11
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. -
12
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. -
13
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. ... -
14
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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urmusic5
The Free and Open Source Music Visualizer Tool
urmusic is a free and open-source software that allows you to easily create your own music visualizer and create a music video for it! It makes use of hardware acceleration to render frames as fast as possible. Donations: Support me on ko-fi: https://ko-fi.com/nasso -
17
Virtualdub filter blenderM
Mixes current masked Virtualdub frame with a previous frame
...The original version by Steven Don could only use one mask or one set of percentage mixes. This version supports multiple masks and mixes. You can apply other filters to one area using a mask, then apply other mods to a different area using another mask, and so on. The original had, in my opinion, confusing options which mixed the current frame with saved frame B and applied the mask to frame B. The current version mixes the masked current frame with saved frame A. To enable this filter: Move fblenderM.vdf to the plugin folder for virtualdub. ... -
18
Border Control Mod Virtualdub
Create pleasing border to video using Virtualdub
Filter to modify the edges of a video frame. 1. Fill a fixed border with selected color 2. Smear a single line to the edge of the border, next line to smear region used 3. Stretch N lines to fill to the edge of border, N lines above smear region used 4. Fade video from selected line to edge of border fade can be to black or to border color 5. Cross smear progressively softens the smeared lines to make smear less obvious 6. Range of values is suitable for HD videos While this...
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