Open Source Windows Image Upscalers
Sort By:
Image Upscalers for Windows
View 33 business solutionsBrowse free open source Image Upscalers and projects for Windows below. Use the toggles on the left to filter open source Image Upscalers by OS, license, language, programming language, and project status.
-
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
Upscayl
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows built with Linux-First philosophy. Upscayl is a cross-platform application built with the Linux-first philosophy. This means that we prioritize Linux builds over others but that doesn't mean we'll break things for other OSes. Upscayl does not work without a GPU, sorry. You'll need a Vulkan-compatible GPU to upscale images. CPU or iGPU won't work. You can also download the flatpak version and double-click the flatpak file to install via Store but wait for the full release, we'll be pushing it to Flathub for easy access. Upscayl uses AI models to enhance your images by guessing what the details could be. It uses Real-ESRGAN (and more in the future) model to achieve this. The CLI tool is called real-esrgan-ncnn-vulkan and it's available on the Real-ESRGAN repository. -
2
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 video - mp4, wemb, gif, mkv, flv, avi, mov, qt. -
3
Waifu2x-Extension-GUI
Photo/Video/GIF enlargement using machine learning
Image & GIF & Video Super-Resolution using Deep Convolutional Neural Networks. Built-in image processing algorithm: Waifu2x / SRMD / RealSR / Anime4K / ACNet Built-in image processing engine: Waifu2x-caffe / Waifu2x-converter / Waifu2x-ncnn-vulkan / SRMD-ncnn-vulkan / RealSR-ncnn-vulkan / Anime4KCPP Github: https://github.com/AaronFeng753/Waifu2x-Extension-GUI -
4
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 you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
5
Clarity AI Upscaler
AI Image Upscaler & Enhancer
Clarity AI Upscaler is an open-source AI image enhancement tool designed to increase the resolution and visual quality of images using modern generative techniques. The system uses deep learning models based on diffusion and other image generation methods to reconstruct high-resolution versions of low-resolution images while preserving important visual details. 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. -
6
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 commands. When training your own model, start with only PSNR loss (50+ epochs, depending on the dataset) and only then introduce GANS and feature loss. This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ISR is compatible with Python 3.6 and is distributed under the Apache 2.0 license. -
7
waifu2x
Single-image super-resolution for anime-style art
Single-Image Super-Resolution for Anime-Style Art using Deep Convolutional Neural Networks. And it supports photo. You can train your own model, change image size, reduce image noise, upscale and customize your image's style. It provides the option of converting and downloading your edited images. -
8
Warlock-Studio
AI Suite for upscaling, interpolating & restoring images/videos
v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system designed to overcome GPU VRAM limitations. -
9
HDcube
This is an ESRGAN model trained specifically for upscaling GameCube
This is an ESRGAN model trained specifically for upscaling GameCube and Wii textures, but it can of course be used for other textures from that period, like PlayStation 2, Xbox or PC games from that time. It can be used for all image formats supported by Gamecube and Wii hardware and can remove its typical artifacts like CMPR Block Compression (DXT1 algorithm, also known as BC1), color palette errors, color reduction up to 8bit color depth and 1bit alpha depth. I recommend chaiNNer, which offers a graphical user interface and is based on a node system that can be used to solve very simple as well as very complex tasks effectively by "chaining" nodes together. You get the best quality if you upscale the alpha channel separately. -
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.
-
10
Batch Auto Upscale Images xBRZ
Auto Upscale All Images Using xBRZ 234x
This tool allows you to easily upscale all your PNG, JPG and GIF images en masse, such as pixel art or AI-generated art, using the open source, amazing, best-in-class, hyperfast non-AI xBRZ algorithm. Unlike the original xBRZ preview program which could only do one image at a time, the new .bat script allows you to mass upscale ALL your images in bulk without needing to fumble with unintuitive commandline nonsense! Perfect for the layperson artist. This is NOT a creative AI upscale type of thing, but it IS better than a typical simple upscale like Lanczos, Mitchell, Bilinear, etc.! It creates cool stylized results! Unlike AI-driven upscaling, which takes gigabytes of space and enormous processing power, xBRZ is lightweight and can run on a potato PC! Only 5MB! (Source code is included with the program .zip file.) -
11
PNG Upscale
AI Super - Resolution
Download is available from the Releases Page or Google Drive or MediaFire. Be careful when trying to resize very large pictures, it can take considerable time and resources. To upscale an image you just need to choose a mode, load a picture and press start. Save button can be used to choose an output folder and filename before you start the process (either just name or .png) You can double-click the text box to change [Dark - Light] theme (disabled when upScaling) Use PNG images for best results. Download the executable corresponding with your operating system, and the Models folder. It's possible to download only some of the models if you want (It just won't let you use them inside the program) The Models folder needs to be in the same directory as the Jar/Exe to use them. -
12
waifu2x-ROS
ReactOS and Windows XP compatible build of waifu2x.
To speed up, use "-b 256 -j 4" options. The original is there: https://github.com/WL-Amigo/waifu2x-converter-cpp Here are some minor cosmetic changes (switch to control memory usage and slightly reformatted output) and files needed to build under MinGW32-W64. To recompile (in Linux), run "make clean; make". 2016-10-17 UPDATE: added simple GUI. 2016-10-18 FIX: corrected typo, added some crashes handling. 2016-11-20 UPDATE: - added "TTA" and "number of passes" options; - enabled RGB models (without internal upscaling); - updated JPEG, TIFF, WebP and OpenEXR libraries; - modified OpenCV to enable JPEG compression in TIFF images (sources included); - replaced models with Nagadomi's ones (https://github.com/nagadomi/waifu2x). 2016-12-28: Happy New Year and Merry Christmas! - "Stop" button works; updated OpenCV, WebP and JasPer libraries; - fix: didn't filter images when scale < 0.5; fixed conversion to 8 bpp in OpenCV and reading of some JPEG-compressed TIFFs in LibTIFF. -
13
waifu2x-cpu-torch-vks
waifu2x fork without CUDA
The original is here: https://github.com/nagadomi/waifu2x Differences: - CPU only, no CUDA needed; - double-precision version; - GPU and CPU-trained models (on the fly conversion in memory); - adapted for Lua v5.2 (works with Torch 7 on x32 Ubuntu). 31-12-2016: - removed unneeded data copies, left from CUDA processing; - removed large duplicate files (see "ReadMe" before use).
- Previous
- You're on page 1
- Next
