diffusers/v0.21.0/en/_app/pages/using-diffusers/inpaint.mdx-hf-doc-builder.js

import{S as st,i as nt,s as lt,e as s,k as p,w as v,t as h,M as it,c as n,d as a,m,a as i,x as j,h as c,b as r,N as Qe,G as t,g as o,y as G,q as B,o as E,B as X,v as rt}from"../../chunks/vendor-hf-doc-builder.js";import{T as ot}from"../../chunks/Tip-hf-doc-builder.js";import{I as tt}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{C as De}from"../../chunks/CodeBlock-hf-doc-builder.js";import{D as pt}from"../../chunks/DocNotebookDropdown-hf-doc-builder.js";function mt(Me){let u,M;return{c(){u=s("p"),M=h("A previous experimental implementation of inpainting used a different, lower-quality process. To ensure backwards compatibility, loading a pretrained pipeline that doesn\u2019t contain the new model will still apply the old inpainting method.")},l(d){u=n(d,"P",{});var f=i(u);M=c(f,"A previous experimental implementation of inpainting used a different, lower-quality process. To ensure backwards compatibility, loading a pretrained pipeline that doesn\u2019t contain the new model will still apply the old inpainting method."),f.forEach(a)},m(d,f){o(d,u,f),t(u,M)},d(d){d&&a(u)}}}function ht(Me){let u,M,d,f,pe,F,xe,me,ze,Ue,S,Te,g,He,H,Ae,qe,V,he,Pe,Ke,_e,U,Le,A,Oe,ea,We,Y,ke,q,aa,Ze,C,Ie,P,ta,ve,R,je,T,ce,y,K,ue,sa,na,L,de,la,ia,O,fe,ra,oa,ee,pa,ma,ye,b,ae,N,Ua,ha,te,$,Ta,ca,se,be,ge,ua,da,ne,Q,_a,Ge,_,Be,le,fa,Ee,w,Wa,Xe,J,W,we,D,ya,Je,ba,Fe,k,ga,ie,wa,Ja,Se,x,Ve,re,Ma,Ye;return F=new tt({}),S=new pt({props:{classNames:"absolute z-10 right-0 top-0",options:[{label:"Mixed",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/en/inpaint.ipynb"},{label:"PyTorch",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/en/pytorch/inpaint.ipynb"},{label:"TensorFlow",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/en/tensorflow/inpaint.ipynb"},{label:"Mixed",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/en/inpaint.ipynb"},{label:"PyTorch",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/en/pytorch/inpaint.ipynb"},{label:"TensorFlow",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/en/tensorflow/inpaint.ipynb"}]}}),Y=new De({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> PIL
<span class="hljs-keyword">import</span> requests
<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> io <span class="hljs-keyword">import</span> BytesIO

<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionInpaintPipeline

pipeline = StableDiffusionInpaintPipeline.from_pretrained(
    <span class="hljs-string">&quot;runwayml/stable-diffusion-inpainting&quot;</span>,
    torch_dtype=torch.float16,
    use_safetensors=<span class="hljs-literal">True</span>,
    variant=<span class="hljs-string">&quot;fp16&quot;</span>,
)
pipeline = pipeline.to(<span class="hljs-string">&quot;cuda&quot;</span>)`}}),C=new De({props:{code:"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",highlighted:`<span class="hljs-keyword">def</span> <span class="hljs-title function_">download_image</span>(<span class="hljs-params">url</span>):
    response = requests.get(url)
    <span class="hljs-keyword">return</span> PIL.Image.<span class="hljs-built_in">open</span>(BytesIO(response.content)).convert(<span class="hljs-string">&quot;RGB&quot;</span>)


img_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png&quot;</span>
mask_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png&quot;</span>

init_image = download_image(img_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))
mask_image = download_image(mask_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))`}}),R=new De({props:{code:"cHJvbXB0JTIwJTNEJTIwJTIyRmFjZSUyMG9mJTIwYSUyMHllbGxvdyUyMGNhdCUyQyUyMGhpZ2glMjByZXNvbHV0aW9uJTJDJTIwc2l0dGluZyUyMG9uJTIwYSUyMHBhcmslMjBiZW5jaCUyMiUwQWltYWdlJTIwJTNEJTIwcGlwZWxpbmUocHJvbXB0JTNEcHJvbXB0JTJDJTIwaW1hZ2UlM0Rpbml0X2ltYWdlJTJDJTIwbWFza19pbWFnZSUzRG1hc2tfaW1hZ2UpLmltYWdlcyU1QjAlNUQ=",highlighted:`prompt = <span class="hljs-string">&quot;Face of a yellow cat, high resolution, sitting on a park bench&quot;</span>
image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>]`}}),_=new ot({props:{warning:!0,$$slots:{default:[mt]},$$scope:{ctx:Me}}}),D=new tt({}),x=new De({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> PIL
<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> torch

<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionInpaintPipeline
<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image

device = <span class="hljs-string">&quot;cuda&quot;</span>
pipeline = StableDiffusionInpaintPipeline.from_pretrained(
    <span class="hljs-string">&quot;runwayml/stable-diffusion-inpainting&quot;</span>,
    torch_dtype=torch.float16,
)
pipeline = pipeline.to(device)

img_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png&quot;</span>
mask_url = <span class="hljs-string">&quot;https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png&quot;</span>

init_image = load_image(img_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))
mask_image = load_image(mask_url).resize((<span class="hljs-number">512</span>, <span class="hljs-number">512</span>))

prompt = <span class="hljs-string">&quot;Face of a yellow cat, high resolution, sitting on a park bench&quot;</span>
repainted_image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[<span class="hljs-number">0</span>]
repainted_image.save(<span class="hljs-string">&quot;repainted_image.png&quot;</span>)

<span class="hljs-comment"># Convert mask to grayscale NumPy array</span>
mask_image_arr = np.array(mask_image.convert(<span class="hljs-string">&quot;L&quot;</span>))
<span class="hljs-comment"># Add a channel dimension to the end of the grayscale mask</span>
mask_image_arr = mask_image_arr[:, :, <span class="hljs-literal">None</span>]
<span class="hljs-comment"># Binarize the mask: 1s correspond to the pixels which are repainted</span>
mask_image_arr = mask_image_arr.astype(np.float32) / <span class="hljs-number">255.0</span>
mask_image_arr[mask_image_arr &lt; <span class="hljs-number">0.5</span>] = <span class="hljs-number">0</span>
mask_image_arr[mask_image_arr &gt;= <span class="hljs-number">0.5</span>] = <span class="hljs-number">1</span>

<span class="hljs-comment"># Take the masked pixels from the repainted image and the unmasked pixels from the initial image</span>
unmasked_unchanged_image_arr = (<span class="hljs-number">1</span> - mask_image_arr) * init_image + mask_image_arr * repainted_image
unmasked_unchanged_image = PIL.Image.fromarray(unmasked_unchanged_image_arr.<span class="hljs-built_in">round</span>().astype(<span class="hljs-string">&quot;uint8&quot;</span>))
unmasked_unchanged_image.save(<span class="hljs-string">&quot;force_unmasked_unchanged.png&quot;</span>)`}}),{c(){u=s("meta"),M=p(),d=s("h1"),f=s("a"),pe=s("span"),v(F.$$.fragment),xe=p(),me=s("span"),ze=h("Text-guided image-inpainting"),Ue=p(),v(S.$$.fragment),Te=p(),g=s("p"),He=h("The "),H=s("a"),Ae=h("StableDiffusionInpaintPipeline"),qe=h(" allows you to edit specific parts of an image by providing a mask and a text prompt. 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