realesrgan
Maintainer: lqhl
15
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
realesrgan is an AI model for image restoration and face enhancement. It was created by Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan from the Tencent ARC Lab and Shenzhen Institutes of Advanced Technology. realesrgan extends the powerful ESRGAN model to a practical restoration application, training on pure synthetic data. It aims to develop algorithms for general image and video restoration. realesrgan can be contrasted with similar models like GFPGAN, which focuses on restoring real-world faces, and real-esrgan, which adds optional face correction and adjustable upscaling to the base realesrgan model.
Model inputs and outputs
realesrgan takes an input image and can output an upscaled and enhanced version of that image. The model supports arbitrary upscaling factors using the --outscale argument. It can also optionally perform face enhancement using the --face_enhance flag, which integrates the GFPGAN model for improved facial details.
Inputs
- img: The input image to be processed
- tile: The tile size to use for processing. Setting this to a non-zero value can help with GPU memory issues, but may introduce some artifacts.
- scale: The upscaling factor to apply to the input image.
- version: The specific version of the
realesrganmodel to use, such as the general "RealESRGAN_x4plus" or the anime-optimized "RealESRGAN_x4plus_anime_6B". - face_enhance: A boolean flag to enable face enhancement using the GFPGAN model.
Outputs
- The upscaled and enhanced output image.
Capabilities
realesrgan can effectively restore and enhance a variety of image types, including natural scenes, anime illustrations, and faces. It is particularly adept at upscaling low-resolution images while preserving details and reducing artifacts. The model's face enhancement capabilities can also improve the appearance of faces in images, making them appear sharper and more natural.
What can I use it for?
realesrgan can be a valuable tool for a wide range of image processing and enhancement tasks. For example, it could be used to upscale low-resolution images for use in presentations, publications, or social media. The face enhancement capabilities could also be leveraged to improve the appearance of portraits or AI-generated faces. Additionally, realesrgan could be integrated into content creation workflows, such as anime or video game development, to enhance the quality of in-game assets or animated scenes.
Things to try
One interesting aspect of realesrgan is its ability to handle a wide range of input image types, including those with alpha channels or grayscale. Experimenting with different input formats and the --outscale parameter can help you find the best configuration for your specific needs. Additionally, the model's performance can be tuned by adjusting the --tile size, which can be particularly useful when dealing with high-resolution or memory-intensive images.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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