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Cover image for A beginner's guide to the Magic-Image-Refiner model by Fermatresearch on Replicate
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A beginner's guide to the Magic-Image-Refiner model by Fermatresearch on Replicate

This is a simplified guide to an AI model called Magic-Image-Refiner maintained by Fermatresearch. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

magic-image-refiner is a powerful image enhancement model built on ControlNet architecture. Created by fermatresearch, it serves as an alternative to SDXL refiners by providing enhanced detail and quality control. The model integrates with Diffusers ControlNet technology for precise image manipulation.

Model Inputs and Outputs

The model processes images through a control-guided system that allows for targeted refinements while maintaining the original image's core characteristics. Users can adjust multiple parameters to achieve their desired output.

Inputs

  • Image - Base image for refinement
  • Prompt - Text description guiding the refinement process
  • Mask - Optional mask for targeted area refinement
  • Resolution - Output size (original, 1024, or 2048)
  • Creativity - Denoising strength from 0 to 1
  • Resemblance - ControlNet conditioning scale
  • HDR - High dynamic range enhancement level
  • Guidance Scale - Parameter for classifier-free guidance
  • Steps - Number of refinement iterations

Outputs

  • Array of image URLs containing the refined results

Capabilities

The system excels at image refinement t...

Click here to read the full guide to Magic-Image-Refiner

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