high-resolution-controlnet-tile

Maintainer: batouresearch

Total Score

402

Last updated 6/19/2024
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Model overview

The high-resolution-controlnet-tile is an open-source implementation of the ControlNet 1.1 model, developed by batouresearch. This model is designed to provide efficient and high-quality upscaling capabilities, with a focus on encouraging creative hallucination. It can be seen as a counterpart to the magic-image-refiner model, which aims to provide a better alternative to SDXL refiners. Additionally, the sdxl-controlnet-lora model, which supports img2img, and the GFPGAN face restoration model, can also be considered related to this implementation.

Model inputs and outputs

The high-resolution-controlnet-tile model takes a variety of inputs, including an image, a prompt, and various parameters such as the number of steps, the resemblance, creativity, and guidance scale. These inputs allow users to fine-tune the model's behavior and output, enabling them to achieve their desired results.

Inputs

  • Image: The control image for the scribble controlnet.
  • Prompt: The text prompt that guides the model's generation process.
  • Steps: The number of steps to be used in the sampling process.
  • Scheduler: The scheduler to be used, with options like DDIM.
  • Creativity: The denoising strength, with 1 meaning total destruction of the original image.
  • Resemblance: The conditioning scale for the controlnet.
  • Guidance Scale: The scale for classifier-free guidance.
  • Negative Prompt: The negative prompt to be used during generation.

Outputs

  • The generated image(s) as a list of URIs.

Capabilities

The high-resolution-controlnet-tile model is capable of producing high-quality upscaled images while encouraging creative hallucination. By leveraging the ControlNet 1.1 architecture, the model can generate images that are both visually appealing and aligned with the provided prompts and control images.

What can I use it for?

The high-resolution-controlnet-tile model can be used for a variety of creative and artistic applications, such as generating illustrations, concept art, or even photorealistic images. Its ability to upscale images while maintaining visual quality and introducing creative elements makes it a valuable tool for designers, artists, and content creators. Additionally, the model's flexibility in terms of input parameters allows users to fine-tune the output to their specific needs and preferences.

Things to try

One interesting aspect of the high-resolution-controlnet-tile model is its ability to handle the trade-off between maintaining the original image and introducing creative hallucination. By adjusting the "creativity" and "resemblance" parameters, users can experiment with different levels of deviation from the input image, allowing them to explore a wide range of creative possibilities.



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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