SinGAN VS upscayl

Compare SinGAN vs upscayl and see what are their differences.

upscayl

🆙 Upscayl - #1 Free and Open Source AI Image Upscaler for Linux, MacOS and Windows. (by upscayl)
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SinGAN upscayl
1 126
3,285 26,817
- 10.9%
0.0 9.6
12 months ago 6 days ago
Python TypeScript
GNU General Public License v3.0 or later GNU Affero General Public License v3.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

SinGAN

Posts with mentions or reviews of SinGAN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-30.

upscayl

Posts with mentions or reviews of upscayl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-05-02.

What are some alternatives?

When comparing SinGAN and upscayl you can also consider the following projects:

super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

waifu2x - Image Super-Resolution for Anime-Style Art

PaddleGAN - PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.

Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps

Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

SHARK - SHARK - High Performance Machine Learning Distribution

cupscale - Image Upscaling GUI based on ESRGAN

ultimate-upscale-for-automatic1111