AuraSR

AuraSR is a super-resolution image processing model based on GANs for improving the quality of generated images.

CommonProductProductivityImage processingSuper-resolution

AuraSR is a Super-Resolution model based on GAN, which enhances the quality of generated images through image conditional enhancement techniques. The model is implemented as a variant of the GigaGAN paper and utilizes the Torch framework. AuraSR's strength lies in its ability to effectively improve the resolution and quality of images, making it suitable for the field of image processing.

GAN-based super-resolution processing
Enhancing the quality of generated images
Implementing image conditional enhancement
Using a variant of the GigaGAN paper
Implementing with the Torch framework
Effectively enhancing image resolution and quality
Suitable for the field of image processing

{target Audience:Researchers
artists
designers
and developers in the image processing field
as well as users who need to enhance image quality and resolution.

Improving the quality and detail representation of low-resolution images.
Applicable to image generation tasks
such as image super-resolution and image enhancement.
Applicable in image processing research and practice
improving image processing efficiency.

Load AuraSR from a pre-trained model.
Load an image via URL and call the upscale_4x method for image super-resolution processing.

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AuraSR Visit Over Time

Monthly Visits

17104189

Bounce Rate

44.67%

Page per Visit

5.5

Visit Duration

00:05:49

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