diffusers/v0.25.0/ko/_app/immutable/nodes/159.b68fe34d.js

import{s as X,n as K,o as O}from"../chunks/scheduler.182ea377.js";import{S as ee,i as te,g as n,s as l,p as C,A as ae,h as p,f as a,c as r,j as B,q as Q,m as T,k as y,v as k,a as s,r as S,d as D,t as V,u as H}from"../chunks/index.008d68e4.js";import{I as se}from"../chunks/IconCopyLink.96bbb92b.js";import{C as q}from"../chunks/CodeBlock.5ed6eb7b.js";import{D as ie}from"../chunks/DocNotebookDropdown.bb388256.js";function oe(N){let i,v,o,m,J,d,R,M,z="Text-guided depth-to-image generation",_,h,Z,c,P='The <a href="/docs/diffusers/v0.25.0/ko/api/pipelines/stable_diffusion/depth2img#diffusers.StableDiffusionDepth2ImgPipeline">StableDiffusionDepth2ImgPipeline</a> lets you pass a text prompt and an initial image to condition the generation of new images. In addition, you can also pass a <code>depth_map</code> to preserve the image structure. If no <code>depth_map</code> is provided, the pipeline automatically predicts the depth via an integrated <a href="https://github.com/isl-org/MiDaS" rel="nofollow">depth-estimation model</a>.',U,g,Y='Start by creating an instance of the <a href="/docs/diffusers/v0.25.0/ko/api/pipelines/stable_diffusion/depth2img#diffusers.StableDiffusionDepth2ImgPipeline">StableDiffusionDepth2ImgPipeline</a>:',j,u,W,f,E="Now pass your prompt to the pipeline. You can also pass a <code>negative_prompt</code> to prevent certain words from guiding how an image is generated:",I,b,$,w,A='<thead><tr><th>Input</th> <th>Output</th></tr></thead> <tbody><tr><td><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/coco-cats.png" width="500"/></td> <td><img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/depth2img-tigers.png" width="500"/></td></tr></tbody>',G;return d=new se({}),h=new ie({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/ko/depth2img.ipynb"},{label:"PyTorch",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/ko/pytorch/depth2img.ipynb"},{label:"TensorFlow",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/ko/tensorflow/depth2img.ipynb"},{label:"Mixed",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/depth2img.ipynb"},{label:"PyTorch",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/pytorch/depth2img.ipynb"},{label:"TensorFlow",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/tensorflow/depth2img.ipynb"}]}}),u=new q({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> torch
<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionDepth2ImgPipeline
<span class="hljs-keyword">from</span> diffusers.utils <span class="hljs-keyword">import</span> load_image, make_image_grid

pipeline = StableDiffusionDepth2ImgPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-2-depth&quot;</span>,
    torch_dtype=torch.float16,
    use_safetensors=<span class="hljs-literal">True</span>,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)`}}),b=new q({props:{code:"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",highlighted:`url = <span class="hljs-string">&quot;http://images.cocodataset.org/val2017/000000039769.jpg&quot;</span>
init_image = load_image(url)
prompt = <span class="hljs-string">&quot;two tigers&quot;</span>
negative_prompt = <span class="hljs-string">&quot;bad, deformed, ugly, bad anatomy&quot;</span>
image = pipeline(prompt=prompt, image=init_image, negative_prompt=negative_prompt, strength=<span class="hljs-number">0.7</span>).images[<span class="hljs-number">0</span>]
make_image_grid([init_image, image], rows=<span class="hljs-number">1</span>, cols=<span class="hljs-number">2</span>)`}}),{c(){i=n("meta"),v=l(),o=n("h1"),m=n("a"),J=n("span"),C(d.$$.fragment),R=l(),M=n("span"),M.textContent=z,_=l(),C(h.$$.fragment),Z=l(),c=n("p"),c.innerHTML=P,U=l(),g=n("p"),g.innerHTML=Y,j=l(),C(u.$$.fragment),W=l(),f=n("p"),f.innerHTML=E,I=l(),C(b.$$.fragment),$=l(),w=n("table"),w.innerHTML=A,this.h()},l(e){const t=ae("svelte-1phssyn",document.head);i=p(t,"META",{name:!0,content:!0}),t.forEach(a),v=r(e),o=p(e,"H1",{class:!0});var x=B(o);m=p(x,"A",{id:!0,class:!0,href:!0});var L=B(m);J=p(L,"SPAN",{});var F=B(J);Q(d.$$.fragment,F),F.forEach(a),L.forEach(a),R=r(x),M=p(x,"SPAN",{"data-svelte-h":!0}),T(M)!=="svelte-eac7ow"&&(M.textContent=z),x.forEach(a),_=r(e),Q(h.$$.fragment,e),Z=r(e),c=p(e,"P",{"data-svelte-h":!0}),T(c)!=="svelte-lkt5bj"&&(c.innerHTML=P),U=r(e),g=p(e,"P",{"data-svelte-h":!0}),T(g)!=="svelte-vbea9g"&&(g.innerHTML=Y),j=r(e),Q(u.$$.fragment,e),W=r(e),f=p(e,"P",{"data-svelte-h":!0}),T(f)!=="svelte-deexa5"&&(f.innerHTML=E),I=r(e),Q(b.$$.fragment,e),$=r(e),w=p(e,"TABLE",{"data-svelte-h":!0}),T(w)!=="svelte-175x2as"&&(w.innerHTML=A),this.h()},h(){y(i,"name","hf:doc:metadata"),y(i,"content",JSON.stringify(ne)),y(m,"id","textguided-depthtoimage-generation"),y(m,"class","header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full"),y(m,"href","#textguided-depthtoimage-generation"),y(o,"class","relative group")},m(e,t){k(document.head,i),s(e,v,t),s(e,o,t),k(o,m),k(m,J),S(d,J,null),k(o,R),k(o,M),s(e,_,t),S(h,e,t),s(e,Z,t),s(e,c,t),s(e,U,t),s(e,g,t),s(e,j,t),S(u,e,t),s(e,W,t),s(e,f,t),s(e,I,t),S(b,e,t),s(e,$,t),s(e,w,t),G=!0},p:K,i(e){G||(D(d.$$.fragment,e),D(h.$$.fragment,e),D(u.$$.fragment,e),D(b.$$.fragment,e),G=!0)},o(e){V(d.$$.fragment,e),V(h.$$.fragment,e),V(u.$$.fragment,e),V(b.$$.fragment,e),G=!1},d(e){e&&(a(v),a(o),a(_),a(Z),a(c),a(U),a(g),a(j),a(W),a(f),a(I),a($),a(w)),a(i),H(d),H(h,e),H(u,e),H(b,e)}}}const ne={local:"textguided-depthtoimage-generation",title:"Text-guided depth-to-image generation"};function le(N){return O(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class ce extends ee{constructor(i){super(),te(this,i,le,oe,X,{})}}export{ce as component};