diffusers/pr_13770/ko/_app/immutable/nodes/35.f7ee4aa3.js

import{s as be,a as $e,n as _e,o as ye}from"../chunks/scheduler.23542ac5.js";import{S as we,i as ve,e as a,s as i,c as f,h as Me,a as o,d as n,b as s,f as se,g,j as m,k as U,l as xe,m as l,n as u,t as c,o as d,p as h}from"../chunks/index.9b1f405b.js";import{C as ke,H as Te,E as Pe}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.4b1c11f9.js";import{C as ie}from"../chunks/CodeBlock.1a9e91ec.js";import{D as je}from"../chunks/DocNotebookDropdown.68a629d2.js";function Ce(ae){let r,W,H,q,b,V,$,D,_,E,y,oe="조건부 이미지 생성을 사용하면 텍스트 프롬프트에서 이미지를 생성할 수 있습니다. 텍스트는 임베딩으로 변환되며, 임베딩은 노이즈에서 이미지를 생성하도록 모델을 조건화하는 데 사용됩니다.",S,w,pe="<code>DiffusionPipeline</code>은 추론을 위해 사전 훈련된 diffusion 시스템을 사용하는 가장 쉬운 방법입니다.",B,v,re='먼저 <code>DiffusionPipeline</code>의 인스턴스를 생성하고 다운로드할 파이프라인 <a href="https://huggingface.co/models?library=diffusers&amp;sort=downloads" rel="nofollow">체크포인트</a>를 지정합니다.',F,M,me='이 가이드에서는 <a href="https://huggingface.co/CompVis/ldm-text2im-large-256" rel="nofollow">잠재 Diffusion</a>과 함께 텍스트-이미지 생성에 <code>DiffusionPipeline</code>을 사용합니다:',N,x,R,k,fe=`<code>DiffusionPipeline</code>은 모든 모델링, 토큰화, 스케줄링 구성 요소를 다운로드하고 캐시합니다.
이 모델은 약 14억 개의 파라미터로 구성되어 있기 때문에 GPU에서 실행할 것을 강력히 권장합니다.
PyTorch에서와 마찬가지로 생성기 객체를 GPU로 이동할 수 있습니다:`,z,T,X,P,ge="이제 텍스트 프롬프트에서 <code>생성기</code>를 사용할 수 있습니다:",A,j,Q,C,ue='출력값은 기본적으로 <a href="https://pillow.readthedocs.io/en/stable/reference/Image.html?highlight=image#the-image-class" rel="nofollow"><code>PIL.Image</code></a> 객체로 래핑됩니다.',Y,Z,ce="호출하여 이미지를 저장할 수 있습니다:",K,L,O,G,de="아래 스페이스를 사용해보고 안내 배율 매개변수를 자유롭게 조정하여 이미지 품질에 어떤 영향을 미치는지 확인해 보세요!",ee,p,he,te,J,ne,I,le;return b=new ke({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),$=new je({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;",options:[{label:"Mixed",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/ko/conditional_image_generation.ipynb"},{label:"PyTorch",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/ko/pytorch/conditional_image_generation.ipynb"},{label:"TensorFlow",value:"https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers_doc/ko/tensorflow/conditional_image_generation.ipynb"},{label:"Mixed",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/conditional_image_generation.ipynb"},{label:"PyTorch",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/pytorch/conditional_image_generation.ipynb"},{label:"TensorFlow",value:"https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/diffusers_doc/ko/tensorflow/conditional_image_generation.ipynb"}]}}),_=new Te({props:{title:"조건부 이미지 생성",local:"조건부-이미지-생성",headingTag:"h1"}}),x=new ie({props:{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBJTBBZ2VuZXJhdG9yJTIwJTNEJTIwRGlmZnVzaW9uUGlwZWxpbmUuZnJvbV9wcmV0cmFpbmVkKCUyMkNvbXBWaXMlMkZsZG0tdGV4dDJpbS1sYXJnZS0yNTYlMjIp",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

<span class="hljs-meta">&gt;&gt;&gt; </span>generator = DiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/ldm-text2im-large-256&quot;</span>)`,lang:"python",wrap:!1}}),T=new ie({props:{code:"Z2VuZXJhdG9yLnRvKCUyMmN1ZGElMjIp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>generator.to(<span class="hljs-string">&quot;cuda&quot;</span>)',lang:"python",wrap:!1}}),j=new ie({props:{code:"aW1hZ2UlMjAlM0QlMjBnZW5lcmF0b3IoJTIyQW4lMjBpbWFnZSUyMG9mJTIwYSUyMHNxdWlycmVsJTIwaW4lMjBQaWNhc3NvJTIwc3R5bGUlMjIpLmltYWdlcyU1QjAlNUQ=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>image = generator(<span class="hljs-string">&quot;An image of a squirrel in Picasso style&quot;</span>).images[<span class="hljs-number">0</span>]',lang:"python",wrap:!1}}),L=new ie({props:{code:"aW1hZ2Uuc2F2ZSglMjJpbWFnZV9vZl9zcXVpcnJlbF9wYWludGluZy5wbmclMjIp",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>image.save(<span class="hljs-string">&quot;image_of_squirrel_painting.png&quot;</span>)',lang:"python",wrap:!1}}),J=new Pe({props:{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/ko/using-diffusers/conditional_image_generation.md"}}),{c(){r=a("meta"),W=i(),H=a("p"),q=i(),f(b.$$.fragment),V=i(),f($.$$.fragment),D=i(),f(_.$$.fragment),E=i(),y=a("p"),y.textContent=oe,S=i(),w=a("p"),w.innerHTML=pe,B=i(),v=a("p"),v.innerHTML=re,F=i(),M=a("p"),M.innerHTML=me,N=i(),f(x.$$.fragment),R=i(),k=a("p"),k.innerHTML=fe,z=i(),f(T.$$.fragment),X=i(),P=a("p"),P.innerHTML=ge,A=i(),f(j.$$.fragment),Q=i(),C=a("p"),C.innerHTML=ue,Y=i(),Z=a("p"),Z.textContent=ce,K=i(),f(L.$$.fragment),O=i(),G=a("p"),G.textContent=de,ee=i(),p=a("iframe"),te=i(),f(J.$$.fragment),ne=i(),I=a("p"),this.h()},l(e){const t=Me("svelte-u9bgzb",document.head);r=o(t,"META",{name:!0,content:!0}),t.forEach(n),W=s(e),H=o(e,"P",{}),se(H).forEach(n),q=s(e),g(b.$$.fragment,e),V=s(e),g($.$$.fragment,e),D=s(e),g(_.$$.fragment,e),E=s(e),y=o(e,"P",{"data-svelte-h":!0}),m(y)!=="svelte-ywp3eh"&&(y.textContent=oe),S=s(e),w=o(e,"P",{"data-svelte-h":!0}),m(w)!=="svelte-rsjwii"&&(w.innerHTML=pe),B=s(e),v=o(e,"P",{"data-svelte-h":!0}),m(v)!=="svelte-16j05gn"&&(v.innerHTML=re),F=s(e),M=o(e,"P",{"data-svelte-h":!0}),m(M)!=="svelte-1zljx"&&(M.innerHTML=me),N=s(e),g(x.$$.fragment,e),R=s(e),k=o(e,"P",{"data-svelte-h":!0}),m(k)!=="svelte-1swfe66"&&(k.innerHTML=fe),z=s(e),g(T.$$.fragment,e),X=s(e),P=o(e,"P",{"data-svelte-h":!0}),m(P)!=="svelte-yx8neo"&&(P.innerHTML=ge),A=s(e),g(j.$$.fragment,e),Q=s(e),C=o(e,"P",{"data-svelte-h":!0}),m(C)!=="svelte-kfigs4"&&(C.innerHTML=ue),Y=s(e),Z=o(e,"P",{"data-svelte-h":!0}),m(Z)!=="svelte-1qprq36"&&(Z.textContent=ce),K=s(e),g(L.$$.fragment,e),O=s(e),G=o(e,"P",{"data-svelte-h":!0}),m(G)!=="svelte-1av7pf"&&(G.textContent=de),ee=s(e),p=o(e,"IFRAME",{src:!0,frameborder:!0,width:!0,height:!0}),se(p).forEach(n),te=s(e),g(J.$$.fragment,e),ne=s(e),I=o(e,"P",{}),se(I).forEach(n),this.h()},h(){U(r,"name","hf:doc:metadata"),U(r,"content",Ze),$e(p.src,he="https://stabilityai-stable-diffusion.hf.space")||U(p,"src",he),U(p,"frameborder","0"),U(p,"width","850"),U(p,"height","500")},m(e,t){xe(document.head,r),l(e,W,t),l(e,H,t),l(e,q,t),u(b,e,t),l(e,V,t),u($,e,t),l(e,D,t),u(_,e,t),l(e,E,t),l(e,y,t),l(e,S,t),l(e,w,t),l(e,B,t),l(e,v,t),l(e,F,t),l(e,M,t),l(e,N,t),u(x,e,t),l(e,R,t),l(e,k,t),l(e,z,t),u(T,e,t),l(e,X,t),l(e,P,t),l(e,A,t),u(j,e,t),l(e,Q,t),l(e,C,t),l(e,Y,t),l(e,Z,t),l(e,K,t),u(L,e,t),l(e,O,t),l(e,G,t),l(e,ee,t),l(e,p,t),l(e,te,t),u(J,e,t),l(e,ne,t),l(e,I,t),le=!0},p:_e,i(e){le||(c(b.$$.fragment,e),c($.$$.fragment,e),c(_.$$.fragment,e),c(x.$$.fragment,e),c(T.$$.fragment,e),c(j.$$.fragment,e),c(L.$$.fragment,e),c(J.$$.fragment,e),le=!0)},o(e){d(b.$$.fragment,e),d($.$$.fragment,e),d(_.$$.fragment,e),d(x.$$.fragment,e),d(T.$$.fragment,e),d(j.$$.fragment,e),d(L.$$.fragment,e),d(J.$$.fragment,e),le=!1},d(e){e&&(n(W),n(H),n(q),n(V),n(D),n(E),n(y),n(S),n(w),n(B),n(v),n(F),n(M),n(N),n(R),n(k),n(z),n(X),n(P),n(A),n(Q),n(C),n(Y),n(Z),n(K),n(O),n(G),n(ee),n(p),n(te),n(ne),n(I)),n(r),h(b,e),h($,e),h(_,e),h(x,e),h(T,e),h(j,e),h(L,e),h(J,e)}}}const Ze='{"title":"조건부 이미지 생성","local":"조건부-이미지-생성","sections":[],"depth":1}';function Le(ae){return ye(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class We extends we{constructor(r){super(),ve(this,r,Le,Ce,be,{})}}export{We as component};