This is a simplified guide to an AI model called Hand-Refiner maintained by Camenduru. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model overview
hand-refiner is an AI model developed by Camenduru that aims to refine and improve the rendering of hands in generated images. It is similar to other image refinement models like magic-image-refiner and ml-mgie, as well as models for tasks like background removal and line art colorization. The model is based on the ControlNet-HandRefiner-pruned model, which was derived from the research paper HandRefiner: Refining Malformed Hands in Generated Images by Diffusion-based Conditional Inpainting.
Model inputs and outputs
hand-refiner takes in an image and a text prompt, and outputs a refined version of the image with improved hand rendering. The model is designed to work well with images containing human figures making hand gestures.
Inputs
- Prompt: A text description of the desired image, including details about the hand gesture and scene.
- Input Image: An image containing a person making a hand gesture, which the model will refine.
- Seed: A numerical seed value to control the random generation of the image.
- Strength: A value between 0 and 1 that controls the strength of the refinement.
Outputs
- Refined Image: The output image with the hands refined and improved compared to the input.
Capabilities
hand-refiner is capable of improving...
Top comments (0)