Cupscale is described as 'Image Upscaling GUI based on ESRGAN' and is a Image Upscaling app in the photos & graphics category. There are more than 10 alternatives to Cupscale for a variety of platforms, including Windows, Linux, Web-based, Mac and Flathub apps. The best Cupscale alternative is Upscayl, which is both free and Open Source. Other great apps like Cupscale are REAL Video Enhancer, Video2X, chaiNNer and Magnific AI.
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows built with Linux-First philosophy.
Upscayl is the most popular Windows, Mac & Linux alternative to Cupscale.
Upscayl is the most popular Open Source & free alternative to Cupscale.
REAL Video Enhancer is a redesigned and enhanced version of the original Rife ESRGAN App for Linux. This program offers convenient access to frame interpolation and upscaling functionalities on Linux, comparable to Flowframes or enhancr on Windows.
Video2X is a video/GIF/image upscaling software based on Waifu2X, Anime4K, SRMD and RealSR written in Python 3. It upscales videos, GIFs and images, restoring details from low-resolution inputs. Video2X also accepts GIF input to video output and video input to GIF output.
A flowchart/node-based image processing GUI aimed at making chaining image processing tasks (especially upscaling done by neural networks) easy, intuitive, and customizable.
The most advanced AI upscaler & enhancer. Magnific can hallucinate and reimagine as many details as you wish guided by your own prompt and parameters!.
Magnific AI is the most popular Web-based alternative to Cupscale.
Magnific AI is the most popular commercial alternative to Cupscale.
An image, gif and video upscaling and denoiser app developed with electron, react, waifu2x and ffmpeg.
RealScaler is a Windows app based on Real-ESRGAN AI to enhance, enlarge and reduce noise in photographs and videos.
Elevate your images with cutting-edge AI technology and a suite of tools for restoration, upscaling, and more.
jdPixelUpscaler upscales images by simply replacing one pixel with several of the same color. For example, if you set the scaling factor to 2, one pixel becomes 2x2 pixels of the same color. No attention is paid to the surrounding pixels or to transitions.
Recent state-of-the-art super-resolution methods have achieved impressive performance on ideal datasets regardless of blur and noise. However, these methods always fail in real-world image super-resolution, since most of them adopt simple bicubic downsampling from high-quality...
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