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Control V11p Sd15 Inpaint

Developed by krnl
ControlNet v1.1 is a neural network architecture based on diffusion models, designed to control image generation through additional conditions, particularly suited for image inpainting tasks.
Downloads 35
Release Time : 1/17/2024

Model Overview

This model controls diffusion models by adding extra conditions, primarily used for image inpainting tasks and can be integrated with Stable Diffusion.

Model Features

Image Inpainting Control
A ControlNet model optimized specifically for image inpainting tasks, capable of precisely controlling content generation in the inpainted regions.
Compatibility with Stable Diffusion
Seamlessly integrates with Stable Diffusion v1.5, extending its image generation capabilities.
End-to-End Learning
Capable of learning task-specific conditions while maintaining robustness even on small datasets (<50k samples).

Model Capabilities

Image Inpainting
Conditional Image Generation
Image Editing
Content Filling

Use Cases

Image Editing
Object Removal and Replacement
Remove unwanted objects from images and fill them with new content
Generates natural and seamless inpainting effects
Facial Retouching
Repair or modify specific areas in facial images
Maintains facial feature consistency while completing modifications
Creative Design
Concept Art Creation
Generate complete artworks based on partial sketches or images
Quickly realizes creative concepts
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