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stability-ai/stable-diffusion-inpainting

A specialized variant of Stability AI's Stable Diffusion model specifically fine-tuned for high-quality image inpainting tasks. This model enables selective modification of existing images by filling masked areas with newly generated content based on text prompts. Stable-Diffusion-Inpainting was developed by resuming training from the Stable Diffusion 2 base model for an additional 200,000 steps, implementing the mask-generation strategy presented in LAMA combined with latent VAE representations of masked images as additional conditioning. The model excels at seamlessly integrating new elements into existing images while maintaining coherence with the unmasked portions.

Technical Specifications:

  • Architecture: Latent Diffusion Model with specialized inpainting conditioning
  • Text Encoder: OpenCLIP-ViT/H for enhanced prompt understanding
  • Training: Additional 200k steps beyond SD2 base model with mask conditioning
  • Input Method: Original image + binary mask + text prompt
  • Processing: Conditions on both mask regions and text descriptions
  • Applications: Object removal/replacement, background changes, creative editing
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