Extend an image to a larger size with prompts
Text-to-Image
Transform images with AI to create enhanced versions
Enhance images to improve quality and details
Generate images based on text prompts
Extend images using prompts for desired dimensions
Clarity AI Upscaler Reproduction
Enhance image quality automatically
Enhance image quality automatically
Extend and refine images using prompts and masks
Guided Img2Img with control for guidance/strength/model/iter
Enhance and beautify images with AI
Upscale images to increase their resolution
Diffusers Image Outpaint is a powerful tool designed to extend images beyond their original borders. It leverages advanced AI algorithms to generate new content that seamlessly matches the original image's style and context. This technology is particularly useful for creating larger, more detailed, or contextually expanded versions of images while maintaining artistic consistency.
• Automatic Image Extension: Extend images to larger sizes while preserving the original composition and style.
• Prompt-Based Generation: Use text prompts to guide the outpainting process, ensuring the extension aligns with your creative vision.
• Integration with Diffusers Ecosystem: Built on the popular Diffusers framework, it offers compatibility with existing workflows and tools.
• High-Quality Output: Produces realistic and contextually relevant results that blend naturally with the original image.
• Customizable Parameters: Adjust settings like model selection, output size, and quality to fine-tune the results.
Install the Package:
Run pip install diffusers-image-outpaint to install the library.
Import the Required Modules:
from diffusers import StableDiffusionPipeline, ImageOutpaintPipeline
import torch
Load the Original Image:
image = Image.open("input_image.png")
Create the Diffusion Model:
model_id = "runwayml/sdxl:c221b2b8ef527988b0414d3fb3f56c356500 onslaught"
pipe = StableDiffusionPipeline.from_pretrained(model_id)
Generate the Outpaint:
outpaint_pipeline = ImageOutpaintPipeline.from_pipeline(pipe)
image_outpaint = outpaint_pipeline(image, prompt="a scenic landscape")
Save the Result:
image_outpaint.images[0].save("output_image.png")
What is the resolution limit for outpainting?
The resolution limit depends on the model used. Most models support up to 2048x2048 pixels, but you can experiment with higher resolutions for specific use cases.
How can I customize the outpaint output?
Use prompts to guide the generation. You can describe styles, colors, or context to influence the output. For example, "a sunset over mountains in an impressionist style."
Can I use this tool for non-photorealistic images?
Yes. Diffusers Image Outpaint works well with both photorealistic and artistic styles, making it versatile for creative projects.