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Realistic Vision Inpainting

Modify images with text prompts

Realistic Vision Inpainting, is an additional tool for image manipulation through text-to-image generation and inpainting.

Mask specific portions of an image and modify them using text prompts. For instance: add a missing feature, transform or repair defects with inpainting. 

To use an inpainting model, especially this variant of Stable Diffusion 1.5 called Realistic Vision, start from  an image for modification. This model is more context-aware, ideal for fixing or modifying overall pictures. Write a new prompt describing desired changes, like correcting a hand holding a coffee cup. Draw a mask over areas needing inpainting, ensuring only these parts will be altered. 

Because its based on the Stable Diffusion Architecture, it has the same amount of control over the settings:

  • Flexible Parameters: Offers control over image dimensions, transformation strength, and other settings.
  • Enhanced Image Processing: Incorporates multiple inference steps for quality enhancement and provides options for guidance scale and negative prompts.

Considerations:

  • The model may not achieve complete photorealism.
  • Challenges in rendering clear text and complex compositions.
  • Biases due to training primarily on English-language data.
  • Safety measures are essential due to the adult material in the training dataset.