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| import{S as rt,i as ot,s as tt,e as t,k as n,w as f,t as m,M as at,c as a,d as o,m as i,a as s,x as u,h as c,b as l,G as e,g as $,y as h,L as st,q as _,o as v,B as b,v as nt}from"../../chunks/vendor-hf-doc-builder.js";import{D as I}from"../../chunks/Docstring-hf-doc-builder.js";import{I as Io}from"../../chunks/IconCopyLink-hf-doc-builder.js";function it(Eo){let w,Oe,L,T,ge,Y,dr,fe,pr,Be,E,gr,ue,fr,ur,de,hr,_r,Ge,P,vr,he,br,$r,_e,yr,Pr,ve,Ir,Er,be,Vr,Dr,We,z,N,$e,J,wr,ye,Lr,Fe,d,j,zr,Pe,xr,Tr,A,K,Nr,Ie,Ar,Cr,C,Q,Mr,Ee,kr,Rr,M,X,Sr,Ve,Or,Br,k,Z,Gr,De,Wr,Fr,R,ee,qr,we,Hr,Ur,S,re,Yr,Le,Jr,jr,O,oe,Kr,ze,Qr,Xr,B,te,Zr,xe,eo,ro,G,ae,oo,se,to,Te,ao,so,qe,x,W,Ne,ne,no,Ae,io,He,F,mo,Ce,co,lo,Ue,y,ie,po,Me,go,fo,q,me,uo,ke,ho,_o,H,ce,vo,Re,bo,$o,U,le,yo,Se,Po,Ye;return Y=new Io({}),J=new Io({}),j=new I({props:{name:"class diffusers.image_processor.VaeImageProcessor",anchor:"diffusers.image_processor.VaeImageProcessor",parameters:[{name:"do_resize",val:": bool = True"},{name:"vae_scale_factor",val:": int = 8"},{name:"resample",val:": str = 'lanczos'"},{name:"do_normalize",val:": bool = True"},{name:"do_convert_rgb",val:": bool = False"}],parametersDescription:[{anchor:"diffusers.image_processor.VaeImageProcessor.do_resize",description:`<strong>do_resize</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) — | |
| Whether to downscale the image’s (height, width) dimensions to multiples of <code>vae_scale_factor</code>. Can accept | |
| <code>height</code> and <code>width</code> arguments from <a href="/docs/diffusers/v0.18.2/en/api/image_processor#diffusers.image_processor.VaeImageProcessor.preprocess">image_processor.VaeImageProcessor.preprocess()</a> method.`,name:"do_resize"},{anchor:"diffusers.image_processor.VaeImageProcessor.vae_scale_factor",description:`<strong>vae_scale_factor</strong> (<code>int</code>, <em>optional</em>, defaults to <code>8</code>) — | |
| VAE scale factor. If <code>do_resize</code> is <code>True</code>, the image is automatically resized to multiples of this factor.`,name:"vae_scale_factor"},{anchor:"diffusers.image_processor.VaeImageProcessor.resample",description:`<strong>resample</strong> (<code>str</code>, <em>optional</em>, defaults to <code>lanczos</code>) — | |
| Resampling filter to use when resizing the image.`,name:"resample"},{anchor:"diffusers.image_processor.VaeImageProcessor.do_normalize",description:`<strong>do_normalize</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) — | |
| Whether to normalize the image to [-1,1].`,name:"do_normalize"},{anchor:"diffusers.image_processor.VaeImageProcessor.do_convert_rgb",description:`<strong>do_convert_rgb</strong> (<code>bool</code>, <em>optional</em>, defaults to be <code>False</code>) — | |
| Whether to convert the images to RGB format.`,name:"do_convert_rgb"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L27"}}),K=new I({props:{name:"convert_to_rgb",anchor:"diffusers.image_processor.VaeImageProcessor.convert_to_rgb",parameters:[{name:"image",val:": Image"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L119"}}),Q=new I({props:{name:"denormalize",anchor:"diffusers.image_processor.VaeImageProcessor.denormalize",parameters:[{name:"images",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L112"}}),X=new I({props:{name:"normalize",anchor:"diffusers.image_processor.VaeImageProcessor.normalize",parameters:[{name:"images",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L105"}}),Z=new I({props:{name:"numpy_to_pil",anchor:"diffusers.image_processor.VaeImageProcessor.numpy_to_pil",parameters:[{name:"images",val:": ndarray"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L58"}}),ee=new I({props:{name:"numpy_to_pt",anchor:"diffusers.image_processor.VaeImageProcessor.numpy_to_pt",parameters:[{name:"images",val:": ndarray"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L86"}}),re=new I({props:{name:"pil_to_numpy",anchor:"diffusers.image_processor.VaeImageProcessor.pil_to_numpy",parameters:[{name:"images",val:": typing.Union[typing.List[PIL.Image.Image], PIL.Image.Image]"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L74"}}),oe=new I({props:{name:"preprocess",anchor:"diffusers.image_processor.VaeImageProcessor.preprocess",parameters:[{name:"image",val:": typing.Union[torch.FloatTensor, PIL.Image.Image, numpy.ndarray]"},{name:"height",val:": typing.Optional[int] = None"},{name:"width",val:": typing.Optional[int] = None"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L147"}}),te=new I({props:{name:"pt_to_numpy",anchor:"diffusers.image_processor.VaeImageProcessor.pt_to_numpy",parameters:[{name:"images",val:": FloatTensor"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L97"}}),ae=new I({props:{name:"resize",anchor:"diffusers.image_processor.VaeImageProcessor.resize",parameters:[{name:"image",val:": Image"},{name:"height",val:": typing.Optional[int] = None"},{name:"width",val:": typing.Optional[int] = None"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L127"}}),ne=new Io({}),ie=new I({props:{name:"class diffusers.image_processor.VaeImageProcessorLDM3D",anchor:"diffusers.image_processor.VaeImageProcessorLDM3D",parameters:[{name:"do_resize",val:": bool = True"},{name:"vae_scale_factor",val:": int = 8"},{name:"resample",val:": str = 'lanczos'"},{name:"do_normalize",val:": bool = True"}],parametersDescription:[{anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.do_resize",description:`<strong>do_resize</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) — | |
| Whether to downscale the image’s (height, width) dimensions to multiples of <code>vae_scale_factor</code>.`,name:"do_resize"},{anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.vae_scale_factor",description:`<strong>vae_scale_factor</strong> (<code>int</code>, <em>optional</em>, defaults to <code>8</code>) — | |
| VAE scale factor. If <code>do_resize</code> is <code>True</code>, the image is automatically resized to multiples of this factor.`,name:"vae_scale_factor"},{anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.resample",description:`<strong>resample</strong> (<code>str</code>, <em>optional</em>, defaults to <code>lanczos</code>) — | |
| Resampling filter to use when resizing the image.`,name:"resample"},{anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.do_normalize",description:`<strong>do_normalize</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) — | |
| Whether to normalize the image to [-1,1].`,name:"do_normalize"}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L255"}}),me=new I({props:{name:"numpy_to_depth",anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.numpy_to_depth",parameters:[{name:"images",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L309"}}),ce=new I({props:{name:"numpy_to_pil",anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.numpy_to_pil",parameters:[{name:"images",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L282"}}),le=new I({props:{name:"rgblike_to_depthmap",anchor:"diffusers.image_processor.VaeImageProcessorLDM3D.rgblike_to_depthmap",parameters:[{name:"image",val:""}],source:"https://github.com/huggingface/diffusers/blob/v0.18.2/src/diffusers/image_processor.py#L298"}}),{c(){w=t("meta"),Oe=n(),L=t("h1"),T=t("a"),ge=t("span"),f(Y.$$.fragment),dr=n(),fe=t("span"),pr=m("VAE Image Processor"),Be=n(),E=t("p"),gr=m("The "),ue=t("code"),fr=m("VaeImageProcessor"),ur=m(" provides a unified API for "),de=t("a"),hr=m("StableDiffusionPipeline"),_r=m("\u2019s to prepare image inputs for VAE encoding and post-processing outputs once they\u2019re decoded. 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Xet Storage Details
- Size:
- 21.6 kB
- Xet hash:
- 4e7124f933b1b36552e202708881351be8b342f1b219ec5abff5fc5b76733412
·
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