This is a simplified guide to an AI model called Realesrgan maintained by Xinntao. If you like these kinds of guides, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter.

Model overview

realesrgan is a practical image restoration algorithm developed by the Tencent ARC Lab. It aims to develop effective algorithms for general image/video restoration, extending the powerful ESRGAN model to practical real-world applications. realesrgan is trained using only synthetic data, but can achieve impressive results on real-world low-resolution images, outperforming traditional super-resolution methods.

realesrgan can be considered an improved version of the ESRGAN model, with enhancements for real-world applicability. It performs well on natural images as well as anime/cartoon-style images, thanks to its versatile training approach. Unlike the face-specific GFPGAN and Codeformer models, realesrgan can be applied to a broader range of image types.

Model inputs and outputs

Inputs

• img: The input image, which can be a URI to an image file.
• tile: The tile size to use for processing the image. Setting this to a non-zero value can help with GPU memory issues, but may introduce some artifacts.
• scale: The desired upscaling factor, typically 2x or 4x.
• version: The version of the realesrgan model to use, such as the general "General - v3" or the anime-optimized "RealESRGAN_x4plus_anime_6B".
• face_enhance: A boolean flag to enable face enhancement using the GFPGAN model. This is not recommended for anime/cartoon-style images.

Outputs

• The upscaled and restored output image, returned as a URI.

Capabilities

realesrgan can effectively restore and upscale a variety of image types, from natural scenes to anime/cartoon-style images. It can handle noise, blur, and other common degradations, producing high-quality results. The model's versatility comes from its synthetic training data, which covers a wide range of image characteristics.

What can I use it for?

realesrgan is a powerful tool for enhancing the resolution and quality of images, with applications in photography, graphic design, animation, and more. It can be used to upscale and restore low-quality images, such as those from the web or old photos, to create high-quality assets for various projects.

For example, you could use realesrgan to upscale and restore images for use in website backgrounds, social media posts, or marketing materials. It could also be used to enhance the quality of anime or cartoon images for use in fan art, illustrations, or game assets.

Things to try

One interesting aspect of realesrgan is its ability to handle both natural images and anime/cartoon-style images well. You could try experimenting with different input images, comparing the results of the general "General - v3" model to the anime-optimized "RealESRGAN_x4plus_anime_6B" model. This can help you understand the strengths and limitations of each version and choose the best one for your specific use case.

Additionally, you could try adjusting the scale parameter to see how it affects the output quality and file size. Experimenting with the tile size can also be useful, as it can help mitigate GPU memory issues, but may introduce some artifacts.

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