illusions

Maintainer: fofr

Total Score

7

Last updated 6/21/2024
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Model overview

The illusions model is a Cog implementation of the Monster Labs' QR code control net that allows users to create visual illusions using img2img and masking support. This model is part of a collection of AI models created by fofr, who has also developed similar models like become-image, image-merger, sticker-maker, image-merge-sdxl, and face-to-many.

Model inputs and outputs

The illusions model allows users to generate images that create visual illusions. The model takes in a prompt, an optional input image for img2img, an optional mask image for inpainting, and a control image. It also allows users to specify various parameters like the seed, width, height, number of outputs, guidance scale, negative prompt, prompt strength, and controlnet conditioning.

Inputs

  • Prompt: The text prompt that guides the image generation.
  • Image: An optional input image for img2img.
  • Mask Image: An optional mask image for inpainting.
  • Control Image: An optional control image.
  • Seed: The seed to use for reproducible image generation.
  • Width: The width of the generated image.
  • Height: The height of the generated image.
  • Num Outputs: The number of output images to generate.
  • Guidance Scale: The scale for classifier-free guidance.
  • Negative Prompt: The negative prompt to guide image generation.
  • Prompt Strength: The strength of the prompt when using img2img or inpainting.
  • Sizing Strategy: How to resize images, such as using the width/height, resizing based on the input image, or resizing based on the control image.
  • Controlnet Start: When the controlnet conditioning starts.
  • Controlnet End: When the controlnet conditioning ends.
  • Controlnet Conditioning Scale: How strong the controlnet conditioning is.

Outputs

  • Output Images: An array of generated image URLs.

Capabilities

The illusions model can generate a variety of visual illusions, such as optical illusions, trick art, and other types of mind-bending imagery. By using the img2img and masking capabilities, users can create unique and surprising effects by combining existing images with the model's generative abilities.

What can I use it for?

The illusions model could be used for a range of applications, such as creating unique artwork, designing optical illusion-based posters or graphics, or even generating visuals for interactive entertainment experiences. The model's ability to work with existing images makes it a versatile tool for both professional and amateur creators looking to add a touch of visual trickery to their projects.

Things to try

One interesting thing to try with the illusions model is to experiment with using different control images and see how they affect the generated illusions. You could also try using the img2img and masking capabilities to transform existing images in unexpected ways, or to combine multiple images to create more complex visual effects.



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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