import{S as uf,i as hf,s as cf,e as a,k as f,w as le,t as l,M as pf,c as r,d as t,m as d,a as i,x as se,h as s,b as n,N as Gr,G as e,g as h,y as ne,L as mf,q as fe,o as de,B as ue,v as gf}from"../../../../chunks/vendor-hf-doc-builder.js";import{D as vf}from"../../../../chunks/Docstring-hf-doc-builder.js";import{C as df}from"../../../../chunks/CodeBlock-hf-doc-builder.js";import{I as Ja}from"../../../../chunks/IconCopyLink-hf-doc-builder.js";function _f(Jl){let O,Ka,L,V,Bt,he,Rr,Ht,Nr,Qa,v,jr,qt,Vr,Br,ce,Hr,qr,pe,Ur,zr,me,Fr,Zr,ge,Yr,Wr,Xa,k,Jr,ve,Kr,Qr,Qe,Xr,ei,er,M,ti,_e,ai,ri,Ee,ii,oi,tr,be,Ut,li,si,ar,Xe,et,ni,De,tt,Kl,rr,we,zt,fi,di,ir,B,Ft,E,Zt,ui,hi,Yt,ci,pi,at,mi,gi,rt,vi,_i,p,b,Wt,it,Ei,bi,Jt,Kt,Di,wi,ot,Se,lt,Ql,Si,st,Te,Ti,xi,D,Qt,nt,Ii,Pi,Xt,ea,yi,Ai,ft,xe,dt,Xl,$i,ut,Ie,ki,Mi,w,ta,ht,Oi,Li,Pe,aa,Ci,Gi,ra,Ri,Ni,ct,ye,pt,es,ji,mt,Vi,Bi,S,ia,gt,Hi,qi,Ae,oa,Ui,zi,la,Fi,Zi,sa,Yi,vt,Wi,Ji,T,na,_t,Ki,Qi,$e,fa,Xi,eo,da,to,ao,ua,ro,Et,ke,io,oo,x,ha,bt,lo,so,Me,ca,no,fo,pa,uo,ho,ma,co,Dt,po,mo,I,ga,wt,go,vo,Oe,va,_o,Eo,_a,bo,Do,Ea,wo,St,So,To,P,ba,Tt,xo,Io,Le,Da,Po,yo,wa,Ao,$o,Sa,ko,xt,Ce,Mo,Oo,y,Ta,It,Lo,Co,Ge,xa,Go,Ro,Ia,No,jo,Pa,Vo,Pt,Re,Bo,Ho,A,ya,yt,qo,Uo,Ne,Aa,zo,Fo,$a,Zo,Yo,ka,Wo,At,je,Jo,Ko,$,Ma,$t,Qo,Xo,Ve,Oa,el,tl,La,al,rl,Ca,il,kt,Be,ol,or,C,H,Ga,He,ll,Ra,sl,lr,G,q,Na,qe,nl,ja,fl,sr,c,dl,Mt,ul,hl,Va,cl,pl,Ot,ml,gl,Lt,vl,_l,Ct,El,bl,Gt,Dl,wl,Rt,Sl,Tl,Ba,xl,Il,Ha,Pl,yl,Nt,Al,$l,nr,Ue,fr,R,U,qa,ze,kl,Ua,Ml,dr,z,Ol,za,Ll,Cl,ur,F,Fe,Gl,Ze,Rl,Nl,jl,Ye,Vl,Fa,Bl,Hl,hr,We,cr,N,Z,Za,Je,ql,Ya,Ul,pr,j,Ke,zl,Wa,Fl,mr;return he=new Ja({}),He=new Ja({}),qe=new Ja({}),Ue=new df({props:{code:`from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler

pipeline = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config)

# or
euler_scheduler = EulerDiscreteScheduler.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="scheduler")
pipeline = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", scheduler=euler_scheduler)`,highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> StableDiffusionPipeline, EulerDiscreteScheduler

<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.scheduler = EulerDiscreteScheduler.from_config(pipeline.scheduler.config)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># or</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>euler_scheduler = EulerDiscreteScheduler.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>, subfolder=<span class="hljs-string">&quot;scheduler&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>, scheduler=euler_scheduler)`}}),ze=new Ja({}),We=new df({props:{code:`from diffusers import (
    StableDiffusionPipeline,
    StableDiffusionImg2ImgPipeline,
    StableDiffusionInpaintPipeline,
)

text2img = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
img2img = StableDiffusionImg2ImgPipeline(**text2img.components)
inpaint = StableDiffusionInpaintPipeline(**text2img.components)

# now you can use text2img(...), img2img(...), inpaint(...) just like the call methods of each respective pipeline`,highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> (
<span class="hljs-meta">... </span>    StableDiffusionPipeline,
<span class="hljs-meta">... </span>    StableDiffusionImg2ImgPipeline,
<span class="hljs-meta">... </span>    StableDiffusionInpaintPipeline,
<span class="hljs-meta">... </span>)

<span class="hljs-meta">&gt;&gt;&gt; </span>text2img = StableDiffusionPipeline.from_pretrained(<span class="hljs-string">&quot;CompVis/stable-diffusion-v1-4&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>img2img = StableDiffusionImg2ImgPipeline(**text2img.components)
<span class="hljs-meta">&gt;&gt;&gt; </span>inpaint = StableDiffusionInpaintPipeline(**text2img.components)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># now you can use text2img(...), img2img(...), inpaint(...) just like the call methods of each respective pipeline</span>`}}),Je=new Ja({}),Ke=new vf({props:{name:"class diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput",anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput",parameters:[{name:"images",val:": typing.Union[typing.List[PIL.Image.Image], numpy.ndarray]"},{name:"nsfw_content_detected",val:": typing.Optional[typing.List[bool]]"}],parametersDescription:[{anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput.images",description:`<strong>images</strong> (<code>List[PIL.Image.Image]</code> or <code>np.ndarray</code>) &#x2014;
List of denoised PIL images of length <code>batch_size</code> or numpy array of shape <code>(batch_size, height, width, num_channels)</code>. PIL images or numpy array present the denoised images of the diffusion pipeline.`,name:"images"},{anchor:"diffusers.pipelines.stable_diffusion.StableDiffusionPipelineOutput.nsfw_content_detected",description:`<strong>nsfw_content_detected</strong> (<code>List[bool]</code>) &#x2014;
List of flags denoting whether the corresponding generated image likely represents &#x201C;not-safe-for-work&#x201D;
(nsfw) content, or <code>None</code> if safety checking could not be performed.`,name:"nsfw_content_detected"}],source:"https://github.com/huggingface/diffusers/blob/v0.16.0/src/diffusers/pipelines/stable_diffusion/__init__.py#L22"}}),{c(){O=a("meta"),Ka=f(),L=a("h1"),V=a("a"),Bt=a("span"),le(he.$$.fragment),Rr=f(),Ht=a("span"),Nr=l("Stable diffusion pipelines"),Qa=f(),v=a("p"),jr=l("Stable Diffusion is a text-to-image "),qt=a("em"),Vr=l("latent diffusion"),Br=l(" model created by the researchers and engineers from "),ce=a("a"),Hr=l("CompVis"),qr=l(", "),pe=a("a"),Ur=l("Stability AI"),zr=l(" and "),me=a("a"),Fr=l("LAION"),Zr=l(". It\u2019s trained on 512x512 images from a subset of the "),ge=a("a"),Yr=l("LAION-5B"),Wr=l(" dataset. This model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. 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