swap-sd

Maintainer: usamaehsan

Total Score

6

Last updated 5/21/2024
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Model LinkView on Replicate
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Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The swap-sd model is an experimental AI tool developed by Usama Ehsan. It is designed for non-commercial use only and is not suitable for production applications. The model is related to several other AI models focused on image generation, inpainting, and enhancement, including controlnet-x-ip-adapter-realistic-vision-v5, playground-v2.5, real-esrgan, deliberate-v6, and gfpgan.

Model inputs and outputs

The swap-sd model takes several inputs, including an image, a prompt, and various parameters to control the output. The model can generate new images based on the input prompt and use the input image as a reference for pose, face, and other visual elements.

Inputs

  • Image: The input image, which can be used as a reference for the generated output.
  • Width: The maximum width of the generated image, with a default of 512 pixels.
  • Height: The maximum height of the generated image, with a default of 512 pixels.
  • Prompt: The text prompt that describes the desired output image, using the Compel language to control the attention weighting of different elements.
  • Swap Face: A boolean flag that determines whether the model should swap the face from the input image onto the generated image.
  • Pose Image: An optional image that can be used as a reference for the pose of the generated image.
  • Pose Scale: A scale factor that adjusts the size of the pose reference image.
  • Use GFPGAN: A boolean flag that determines whether the model should use the GFPGAN face enhancement algorithm.
  • Guidance Scale: A scaling factor that controls the amount of guidance from the text prompt.
  • Negative Prompt: A text prompt that describes elements that should be avoided in the generated image.
  • Ip Adapter Scale: A scale factor that adjusts the size of the IP adapter reference image.
  • Num Inference Steps: The number of steps to run the denoising process.
  • Disable Safety Check: A boolean flag that disables the safety check, which should be used with caution.
  • Use Pose Image Resolution: A boolean flag that determines whether the generated image should match the resolution of the pose reference image.

Outputs

  • Output Images: The generated images, returned as an array of image URLs.

Capabilities

The swap-sd model is capable of generating new images based on a text prompt, while using an input image as a reference for the composition, pose, and other visual elements. It can swap the face from the input image onto the generated image, and can also use the GFPGAN algorithm to enhance the quality of the generated faces. The model offers a range of parameters to fine-tune the output, including the ability to control the guidance scale, negative prompt, and inference steps.

What can I use it for?

The swap-sd model could be used for a variety of creative applications, such as generating portraits, character designs, or conceptual art. By using an input image as a reference, the model can help maintain consistent visual elements, such as pose and facial features, while generating new and unique imagery. However, due to the experimental nature of the model and the potential risks of disabling the safety check, it is important to use the model with caution and only for non-commercial purposes.

Things to try

One interesting aspect of the swap-sd model is the ability to use a pose reference image to influence the generated output. This could be used to create dynamic, action-oriented images by providing a reference pose that captures a specific movement or expression. Additionally, the ability to control the negative prompt and guidance scale could be used to fine-tune the model's output, allowing users to experiment with different styles, moods, and visual elements.



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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