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GitHub Repository: huggingface/notebooks
 Path: blob/main/diffusers/stable_diffusion_repaint.ipynb
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Stable Diffusion Repaint

This pipeline uses the RePaint logic on the latent space of stable diffusion. It can be used similarly to other image inpainting pipelines but does not rely on a specific inpainting model. This means you can use models that are not specifically created for inpainting.

Make sure to use the RePaintScheduler as shown in the example below.

Disclaimer: The mask gets transferred into latent space, this may lead to unexpected changes on the edge of the masked part. The inference time is a lot slower.

The script was contributed by Markus Pobitzer and the notebook by Parag Ekbote.

pip install pillow torch transformers diffusers
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mpmath<1.4,>=1.1.0 in /system/conda/miniconda3/envs/cloudspace/lib/python3.10/site-packages (from sympy->torch) (1.3.0) Note: you may need to restart the kernel to use updated packages. 
import PIL
import requests
import torch
from io import BytesIO
from diffusers import StableDiffusionPipeline, RePaintScheduler

def download_image(url):
    response = requests.get(url)
    return PIL.Image.open(BytesIO(response.content)).convert("RGB")
img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
init_image = download_image(img_url).resize((512, 512))
mask_image = download_image(mask_url).resize((512, 512))
mask_image = PIL.ImageOps.invert(mask_image)
pipe = StableDiffusionPipeline.from_pretrained(
    "CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16, custom_pipeline="stable_diffusion_repaint",
)
pipe.scheduler = RePaintScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")
prompt = "Face of a yellow cat, high resolution, sitting on a park bench"
image = pipe(prompt=prompt, image=init_image, mask_image=mask_image).images[0]

image.save("image.jpg")